Evaluating Differences of Erosion Patterns in Natural and Anthropogenic Basins through Scenario Testing: A Case Study of the Claise, France and Nahr Ibrahim, Lebanon

*Mario J. Al Sayah, Rachid Nedjai, Chadi Abdallah, Michel Khouri, Talal Darwish and François Pinet*

## **Abstract**

This study assessed soil erosion risks of two basins representing different geographical, topographical, climatological and land occupation/management settings. A comparison and an evaluation of site-specific factors influencing erosion in the French Claise and the Lebanese Nahr Ibrahim basins were performed. The Claise corresponds to a natural park with a flat area and an oceanic climate, and is characterized by the presence of 2179 waterbodies (mostly ponds) considered as hydro-sedimentary alternating structures, while Nahr Ibrahim represents an orographic Mediterranean basin characterized by a random unequal land occupation distribution. The Claise was found to be under 12.48% no erosion (attributed to the dense pond network), 65.66% low, 21.68% moderate and 0.18% high erosion risks; while Nahr Ibrahim was found to be under 4, 39.5 and 56.4%, low, moderate and high erosion risks, along with 66% land degradation determined from the intersection of land capability and land occupation maps. Under the alternative scenario for the Claise where ponds were considered dried, erosion risks became 1.12, 0.52, 76.8 and 21.56%, no erosion, low, moderate and high risks, respectively. For Nahr Ibrahim, and following the Land Degradation Neutrality intervention, high erosion risks decreased by 13.9%, while low and moderate risks increased by 3 and 10.8%.

**Keywords:** erosion, LDN, land degradation, ponds, Mediterranean climate, oceanic climate

## **1. Introduction**

Soil erosion is considered as the most amplified manifestation of land loss worldwide. It has become one of the most pressuring global problems facing sustainable development at rates exceeding pedogenesis by 10–40 times [1].

According to Lal [2], a worldwide area of 1094 million ha is subject to soil erosion, of which 751 million ha have been severely eroded. As a result of soil erosion, significant declines in land quality due to the loss of the much needed fertile topsoil layers used for agriculture and for providing primary eco-services have been reported [3] particularly in arable lands whose decline accounts for losses in the order of 400 billion US dollars/year globally [4]. From the various erosion forms, water erosion is considered as the most problematic, due to the increase in its extent and intensity, leading to deleterious losses in land capital and environmental sustainability [4, 5]. Europe and the Mediterranean particularly are significantly affected by this process [6, 7] where in Europe, soil erosion is one of the most threatening challenges for soil resources causing losses of 3–40 t/ ha/year [8] while in the Mediterranean region, particularly in its Middle Eastern and North African parts [9, 10], soil erosion rates have significantly surpassed Mediterranean pedogenesis rates [11, 12].

In Europe, soil loss can be attributed primarily to water erosion due to climate (abundant rainfall), soil management practices and agrarian intensification coupled to unsustainable practices such as overgrazing [13]. In the Mediterranean region on the other hand, factors are much more complex due to the pronounced rainfall variability and heterogeneity of site-specific characteristics [14] even within the same landscape. As a result of weakly resistant pedology [15], unequal and random land use/land cover distribution [16] occurring due to the absence of governance, management plans and restraints [17], low precipitations, erratic intense rain episodes, prolonged droughts, steep slopes and increasing anthropogenic effects [18], soil erosion has reached an irreversible state in some regions, while in others erosion has ceased because no more soil is left to erode [13]. Consequently, soil erosion has led to the process of land degradation causing significant loss of land capital [19], thereby threatening food security and sustainable development in the region [20]. For that purpose, a simultaneous assessment englobing both soil erosion and land degradation must be carried out. Nevertheless, this task is contested by several factors namely the non-uniqueness of definitions of the process [21], the existence of unmeasurable interdependent driving factors [22] and the absence of clear methodological or application workflows [23].

This deteriorating state of soil erosion in Europe has led to the development of the European common framework for the Thematic Strategy on Soil Protection and the Common Agricultural Policy that highlight the need to protect European soils to reduce soil erosion [4, 24]. In contrast, the Mediterranean basin still lacks concrete and direct policies or legislations targeting soil erosion [25] due to contested definitions of land loss in the region [26]. Under any circumstance and prior to treating soil erosion, assessing its extent and identifying hotspots are required [13, 27]. However, this assessment is not an easy task given the heterogeneity and large spatial/temporal variability of its driving factors [28, 29], particularly in Mediterranean landscapes [30] that are characterized by a complexity of slope, climate and land occupation factors [10].

The process of soil erosion is attributed to various interdependent driving factors, notably climate, pedologic properties, topography and vegetation cover [31]. Despite being a natural process at its origin, soil erosion has significantly increased as a result of anthropogenic activity [32], where land use and land cover changes have become the main drivers of soil erosion [29] combined to soil management and conservation strategies [33]. When considering soil erosion, a multi-scale problem is at hand due to the role and status of soil erosion in several environmental, socioeconomic and developmental processes, often causing a cascade of direct on-site and indirect off-site effects. Under the environmental scope, soil erosion is considered as the main form of soil loss leading to negative impacts on water

**59**

*Evaluating Differences of Erosion Patterns in Natural and Anthropogenic Basins…*

challenges for achieving sustainable development [37, 38].

creating challenges for watershed managers [41].

problems of field measurements and logistics.

between two different geographical and management contexts.

quality, biodiversity, organic carbon stocks and eco-services [24]. At the socioeconomic scale, soil erosion has become one of the governing factors in land use allocation, notably under the scope of agriculture as function of market economy [34], where increasing needs for increased productivity led to significant removal of natural cover for agricultural expansion rendering large areas vulnerable to soil erosion [33]. At the developmental scale, soil erosion has caused notable declines in the productive capacity of lands, often leading them to become unproductive, ultimately resulting in agrarian abandonment [1]. The latter, in turn, causes an amplification of erosion due to increased exposure of soil to water [35], thus promoting loss of land and soil resources both quantitatively and qualitatively. Collectively, the previously cited factors culminate not only to create short-term losses in agricultural productivity [1], but also to affect long-term food security [36], thus imposing

Further, soil erosion forms the head component of van Rijn's [39] sedimentary cycle, consisting of erosion, transport and deposition, rendering it partly responsible for shaping the hydromorphological aspects of landscapes along with surface runoff, sediment transport, baseflow and stream discharge [40]. Given the status of soil erosion as the head of the sediment transport chain, changes of soil erosion are capable of causing a cascading effect influencing the whole cycle and ultimately modifying both the hydro-sedimentary response and equilibrium of basins, thus

Studies regarding soil erosion have received growing interest under different approaches; these have led to the development of several models for estimating erosion [42] of which the USLE [43], MUSLE and RUSLE [44] are some of the most basic yet widely used models. Other models such as EUROSEM [45], WEPP [46], CORINE [47], TOPOG [48] and SedNet [49] have also been employed at different scales and study areas with various degrees of success. Ref. [50] summarized a number of applied approaches for studying erosion that can be grouped under: (a) use of models (e.g., [12, 42, 51]), (b) erosion plot data for direct in-situ measurements (e.g., [52]) and (c) by means of measuring sediment yield (e.g., [53]) since the latter is the net product of soil erosion [54]. Among these various methods, the use of models has been deemed to be the best given its efficiency, not only for displaying current conditions but also for revealing changes resulting from alternative simulations presenting changes of natural conditions [55] in addition to overcoming the

For erosion assessment, the basin scale is considered as most suitable given its capacity to reveal anthropogenic-interference effect [56] and due to the fact that soil erosion is one of the most pronounced problems in basins posing a considerable challenge for hydrologists and basin managers [41]. Given the scope of this study for comparing natural and managed basins having different natural contexts under different land occupation and managed settings, the French Claise and Lebanese Nahr Ibrahim basins are chosen as study areas for establishing a comparative framework

The Claise basin is one of the several basins corresponding to the French Brenne Regional Natural Park. The latter is an international heritage area housing a large number of ponds in its premises, nearly 4500, of which 2179 are in the Claise [57]. It is chosen as a representative of Northern European basins which are often covered by a prevalent number of ponds. In France particularly, three main pond density zones are present; these are the Sologne region, Brenne (Centre France) and Dombes (Eastern France). Ponds are considered to be one of the most important hydro-sedimentary modifying manmade structures [58] that possess an aggregative effect far more important than larger water bodies [59] on altering the regime of basins they take part of. Therefore, in response to the recommendations of the Directive-Cadre

*DOI: http://dx.doi.org/10.5772/intechopen.89088*

*Evaluating Differences of Erosion Patterns in Natural and Anthropogenic Basins… DOI: http://dx.doi.org/10.5772/intechopen.89088*

quality, biodiversity, organic carbon stocks and eco-services [24]. At the socioeconomic scale, soil erosion has become one of the governing factors in land use allocation, notably under the scope of agriculture as function of market economy [34], where increasing needs for increased productivity led to significant removal of natural cover for agricultural expansion rendering large areas vulnerable to soil erosion [33]. At the developmental scale, soil erosion has caused notable declines in the productive capacity of lands, often leading them to become unproductive, ultimately resulting in agrarian abandonment [1]. The latter, in turn, causes an amplification of erosion due to increased exposure of soil to water [35], thus promoting loss of land and soil resources both quantitatively and qualitatively. Collectively, the previously cited factors culminate not only to create short-term losses in agricultural productivity [1], but also to affect long-term food security [36], thus imposing challenges for achieving sustainable development [37, 38].

Further, soil erosion forms the head component of van Rijn's [39] sedimentary cycle, consisting of erosion, transport and deposition, rendering it partly responsible for shaping the hydromorphological aspects of landscapes along with surface runoff, sediment transport, baseflow and stream discharge [40]. Given the status of soil erosion as the head of the sediment transport chain, changes of soil erosion are capable of causing a cascading effect influencing the whole cycle and ultimately modifying both the hydro-sedimentary response and equilibrium of basins, thus creating challenges for watershed managers [41].

Studies regarding soil erosion have received growing interest under different approaches; these have led to the development of several models for estimating erosion [42] of which the USLE [43], MUSLE and RUSLE [44] are some of the most basic yet widely used models. Other models such as EUROSEM [45], WEPP [46], CORINE [47], TOPOG [48] and SedNet [49] have also been employed at different scales and study areas with various degrees of success. Ref. [50] summarized a number of applied approaches for studying erosion that can be grouped under: (a) use of models (e.g., [12, 42, 51]), (b) erosion plot data for direct in-situ measurements (e.g., [52]) and (c) by means of measuring sediment yield (e.g., [53]) since the latter is the net product of soil erosion [54]. Among these various methods, the use of models has been deemed to be the best given its efficiency, not only for displaying current conditions but also for revealing changes resulting from alternative simulations presenting changes of natural conditions [55] in addition to overcoming the problems of field measurements and logistics.

For erosion assessment, the basin scale is considered as most suitable given its capacity to reveal anthropogenic-interference effect [56] and due to the fact that soil erosion is one of the most pronounced problems in basins posing a considerable challenge for hydrologists and basin managers [41]. Given the scope of this study for comparing natural and managed basins having different natural contexts under different land occupation and managed settings, the French Claise and Lebanese Nahr Ibrahim basins are chosen as study areas for establishing a comparative framework between two different geographical and management contexts.

The Claise basin is one of the several basins corresponding to the French Brenne Regional Natural Park. The latter is an international heritage area housing a large number of ponds in its premises, nearly 4500, of which 2179 are in the Claise [57]. It is chosen as a representative of Northern European basins which are often covered by a prevalent number of ponds. In France particularly, three main pond density zones are present; these are the Sologne region, Brenne (Centre France) and Dombes (Eastern France). Ponds are considered to be one of the most important hydro-sedimentary modifying manmade structures [58] that possess an aggregative effect far more important than larger water bodies [59] on altering the regime of basins they take part of. Therefore, in response to the recommendations of the Directive-Cadre

*Soil Erosion - Rainfall Erosivity and Risk Assessment*

Mediterranean pedogenesis rates [11, 12].

ological or application workflows [23].

climate and land occupation factors [10].

According to Lal [2], a worldwide area of 1094 million ha is subject to soil erosion, of which 751 million ha have been severely eroded. As a result of soil erosion, significant declines in land quality due to the loss of the much needed fertile topsoil layers used for agriculture and for providing primary eco-services have been reported [3] particularly in arable lands whose decline accounts for losses in the order of 400 billion US dollars/year globally [4]. From the various erosion forms, water erosion is considered as the most problematic, due to the increase in its extent and intensity, leading to deleterious losses in land capital and environmental sustainability [4, 5]. Europe and the Mediterranean particularly are significantly affected by this process [6, 7] where in Europe, soil erosion is one of the most threatening challenges for soil resources causing losses of 3–40 t/ ha/year [8] while in the Mediterranean region, particularly in its Middle Eastern and North African parts [9, 10], soil erosion rates have significantly surpassed

In Europe, soil loss can be attributed primarily to water erosion due to climate (abundant rainfall), soil management practices and agrarian intensification coupled to unsustainable practices such as overgrazing [13]. In the Mediterranean region on the other hand, factors are much more complex due to the pronounced rainfall variability and heterogeneity of site-specific characteristics [14] even within the same landscape. As a result of weakly resistant pedology [15], unequal and random land use/land cover distribution [16] occurring due to the absence of governance, management plans and restraints [17], low precipitations, erratic intense rain episodes, prolonged droughts, steep slopes and increasing anthropogenic effects [18], soil erosion has reached an irreversible state in some regions, while in others erosion has ceased because no more soil is left to erode [13]. Consequently, soil erosion has led to the process of land degradation causing significant loss of land capital [19], thereby threatening food security and sustainable development in the region [20]. For that purpose, a simultaneous assessment englobing both soil erosion and land degradation must be carried out. Nevertheless, this task is contested by several factors namely the non-uniqueness of definitions of the process [21], the existence of unmeasurable interdependent driving factors [22] and the absence of clear method-

This deteriorating state of soil erosion in Europe has led to the development of the European common framework for the Thematic Strategy on Soil Protection and the Common Agricultural Policy that highlight the need to protect European soils to reduce soil erosion [4, 24]. In contrast, the Mediterranean basin still lacks concrete and direct policies or legislations targeting soil erosion [25] due to contested definitions of land loss in the region [26]. Under any circumstance and prior to treating soil erosion, assessing its extent and identifying hotspots are required [13, 27]. However, this assessment is not an easy task given the heterogeneity and large spatial/temporal variability of its driving factors [28, 29], particularly in Mediterranean landscapes [30] that are characterized by a complexity of slope,

The process of soil erosion is attributed to various interdependent driving factors, notably climate, pedologic properties, topography and vegetation cover [31]. Despite being a natural process at its origin, soil erosion has significantly increased as a result of anthropogenic activity [32], where land use and land cover changes have become the main drivers of soil erosion [29] combined to soil management and conservation strategies [33]. When considering soil erosion, a multi-scale problem is at hand due to the role and status of soil erosion in several environmental, socioeconomic and developmental processes, often causing a cascade of direct on-site and indirect off-site effects. Under the environmental scope, soil erosion is considered as the main form of soil loss leading to negative impacts on water

**58**

Européenne sur l'eau (DCE) [60], regarding the importance of understanding the impact of hydromorphological factors on watershed processes, the Claise basin which takes part of the Brenne Natural Regional Park is chosen as the natural watershed of this study. In contrast, the Nahr Ibrahim basin represents the managed basin of this study. It is a Lebanese basin known for excessive erosion rates [12] that have led to significant land degradation [61] and landslides [62] coupled to a typical Mediterranean unequal land occupation distribution that has expanded due to the absence of land use planning [20].

The workflow of this chapter consists of using the CORINE erosion model [48] given its relative accuracy with respect to simple data requirements consisting of climate, slope, soil properties and vegetation cover, and its widespread application [63]. Erosion assessment in the Claise basin serves to respond to DCE recommendations for assessment of the effect of hydromorphological altering structures on basins. For Nahr Ibrahim, the CORINE model serves as a tool for mapping land degradation as function of soil erosion. Following the establishment of both actual soil erosion maps, a comparison between the natural and managed settings allows the assessment of the impact of land occupation and management on erosion risks.

Given the flexibility of the CORINE model incorporating both natural (slope, pedology and climate) and vegetation cover (human controlled), alternative vegetation covers for both basins were used to re-assess changes in erosion patterns and risks. This step was performed to pinpoint the impact of ponds on erosion patterns of the Claise basin and to prospect the efficiency of the Land Degradation Neutrality (LDN) concept for erosion reduction through land use planning [64]. LDN is defined by the United Nations Convention to Combat Desertification (UNCCD), [65], to be "a state whereby the amount and quality of land resources necessary to support ecosystem functions and services and enhance food security remain stable or increase within specified temporal and spatial scales and ecosystems." LDN aims to halt ongoing losses by land degradation. Unlike past approaches, LDN creates a target for land degradation management by means of a dual phased approach containing measures to avoid or reduce land degradation as a first phase. The second phase presents a combination with the first where specific applications to reverse or to treat past degradation are employed in order to rehabilitate degraded zones. Therefore, the concept of neutrality involves counterbalancing losses and equivalent gains. However, many factors enter in the estimation of losses including the effects of planning decisions (e.g., granting permits for open-cut mining), the effects of past and previous decisions (e.g., continuation of agricultural practices known to deplete soil carbon) and mostly the natural drivers of land degradation (e.g., impacts of drought, wildfire) [67].

Ideally, the most effective strategy would be to take immediate action to prevent land degradation where non-degraded lands are at risk. For effective implementation, it is important to consider the resilience of the counterbalancing intervention over the long term, the potential impacts of climate change and the likely trade-offs between ecosystem services. For these reasons, the proposed land use scenario for the Nahr Ibrahim basin consists of a realistic plan accounting for the trade-off between natural resources and the need to promote sustainable urban development. This task is achieved following the LDN's "soil" indicators of land use/land cover change and soil organic C stocks in analogy to the work done by Al Sayah et al. [66] and in response to the LDN hierarchy involving three actions in descending order of importance: avoid, reduce and reverse.

Through this study, the comparative land occupation framework in addition to the alternative modeling approach aims to provide an understanding

**61**

**Figure 1.**

*Study area description, BNP: Brenne Regional Natural Park.*

*Evaluating Differences of Erosion Patterns in Natural and Anthropogenic Basins…*

regarding the relationship between land occupation (as land use/land cover and management) and soil erosion, as well as integrating soil erosion as part of

**2. Geographical context and site-specific description of the test-site** 

The Indre section of the Claise basin (46° 56′ 23.89″ N and 1° 31′ 32.61″ E) is one of the three basins corresponding to the Brenne Regional Natural Park. The

as the land of thousand ponds due to the presence of 4500 ponds extending in a natural landscape mosaic [57]. A large number of these water bodies are located in the corresponding section of Claise basin (2179 ponds) that describes an area of

of the 87.6-km-long Claise River (Rougé (1927) in [68]) described by an average

ies: the channel of the Five Bonds (or Blizon), the Yoson and Suin Rivers. Despite the proficient presence of water bodies within, the Claise basin is described by a poorly organized and extensively fragmented hydrological network [70]. Since the study area takes part of a national park, the land occupation pattern of the Claise basin has remained relatively unchanged for the last 19 years except for pond proliferation. The land occupation setting of the Claise consists mainly of a homogeneous interlocking mosaic of abundant grasslands, agricultural areas and forests as opposed to a very low urban occupation [69]. The climate of the Claise basin mainly

park is located in the French Centre-Val-de-Loire region and is renowned

[67] (**Figure 1**). These are speculated to be one of the key feeding sources

/s and originating at 146 m of altitude [69] with three main tributar-

**2.1 The Claise basin: a particular mosaic under a natural setting**

*DOI: http://dx.doi.org/10.5772/intechopen.89088*

land planning.

**basins**

1760 km2

707 km<sup>2</sup>

flow of 4.50 m3

*Evaluating Differences of Erosion Patterns in Natural and Anthropogenic Basins… DOI: http://dx.doi.org/10.5772/intechopen.89088*

regarding the relationship between land occupation (as land use/land cover and management) and soil erosion, as well as integrating soil erosion as part of land planning.

## **2. Geographical context and site-specific description of the test-site basins**

## **2.1 The Claise basin: a particular mosaic under a natural setting**

The Indre section of the Claise basin (46° 56′ 23.89″ N and 1° 31′ 32.61″ E) is one of the three basins corresponding to the Brenne Regional Natural Park. The 1760 km2 park is located in the French Centre-Val-de-Loire region and is renowned as the land of thousand ponds due to the presence of 4500 ponds extending in a natural landscape mosaic [57]. A large number of these water bodies are located in the corresponding section of Claise basin (2179 ponds) that describes an area of 707 km<sup>2</sup> [67] (**Figure 1**). These are speculated to be one of the key feeding sources of the 87.6-km-long Claise River (Rougé (1927) in [68]) described by an average flow of 4.50 m3 /s and originating at 146 m of altitude [69] with three main tributaries: the channel of the Five Bonds (or Blizon), the Yoson and Suin Rivers. Despite the proficient presence of water bodies within, the Claise basin is described by a poorly organized and extensively fragmented hydrological network [70]. Since the study area takes part of a national park, the land occupation pattern of the Claise basin has remained relatively unchanged for the last 19 years except for pond proliferation. The land occupation setting of the Claise consists mainly of a homogeneous interlocking mosaic of abundant grasslands, agricultural areas and forests as opposed to a very low urban occupation [69]. The climate of the Claise basin mainly

**Figure 1.** *Study area description, BNP: Brenne Regional Natural Park.*

*Soil Erosion - Rainfall Erosivity and Risk Assessment*

absence of land use planning [20].

management on erosion risks.

drought, wildfire) [67].

importance: avoid, reduce and reverse.

Européenne sur l'eau (DCE) [60], regarding the importance of understanding the impact of hydromorphological factors on watershed processes, the Claise basin which takes part of the Brenne Natural Regional Park is chosen as the natural watershed of this study. In contrast, the Nahr Ibrahim basin represents the managed basin of this study. It is a Lebanese basin known for excessive erosion rates [12] that have led to significant land degradation [61] and landslides [62] coupled to a typical Mediterranean unequal land occupation distribution that has expanded due to the

The workflow of this chapter consists of using the CORINE erosion model [48] given its relative accuracy with respect to simple data requirements consisting of climate, slope, soil properties and vegetation cover, and its widespread application [63]. Erosion assessment in the Claise basin serves to respond to DCE recommendations for assessment of the effect of hydromorphological altering structures on basins. For Nahr Ibrahim, the CORINE model serves as a tool for mapping land degradation as function of soil erosion. Following the establishment of both actual soil erosion maps, a comparison between the natural and managed settings allows the assessment of the impact of land occupation and

Given the flexibility of the CORINE model incorporating both natural (slope,

Ideally, the most effective strategy would be to take immediate action to prevent land degradation where non-degraded lands are at risk. For effective implementation, it is important to consider the resilience of the counterbalancing intervention over the long term, the potential impacts of climate change and the likely trade-offs between ecosystem services. For these reasons, the proposed land use scenario for the Nahr Ibrahim basin consists of a realistic plan accounting for the trade-off between natural resources and the need to promote sustainable urban development. This task is achieved following the LDN's "soil" indicators of land use/land cover change and soil organic C stocks in analogy to the work done by Al Sayah et al. [66] and in response to the LDN hierarchy involving three actions in descending order of

Through this study, the comparative land occupation framework in addition to the alternative modeling approach aims to provide an understanding

pedology and climate) and vegetation cover (human controlled), alternative vegetation covers for both basins were used to re-assess changes in erosion patterns and risks. This step was performed to pinpoint the impact of ponds on erosion patterns of the Claise basin and to prospect the efficiency of the Land Degradation Neutrality (LDN) concept for erosion reduction through land use planning [64]. LDN is defined by the United Nations Convention to Combat Desertification (UNCCD), [65], to be "a state whereby the amount and quality of land resources necessary to support ecosystem functions and services and enhance food security remain stable or increase within specified temporal and spatial scales and ecosystems." LDN aims to halt ongoing losses by land degradation. Unlike past approaches, LDN creates a target for land degradation management by means of a dual phased approach containing measures to avoid or reduce land degradation as a first phase. The second phase presents a combination with the first where specific applications to reverse or to treat past degradation are employed in order to rehabilitate degraded zones. Therefore, the concept of neutrality involves counterbalancing losses and equivalent gains. However, many factors enter in the estimation of losses including the effects of planning decisions (e.g., granting permits for open-cut mining), the effects of past and previous decisions (e.g., continuation of agricultural practices known to deplete soil carbon) and mostly the natural drivers of land degradation (e.g., impacts of

**60**

corresponds to the degraded oceanic continental climate with high oceanic influence having annual average temperatures of 11°C, 8–14 days of temperatures below −5°C and annual cumulative precipitations in the order of 700 mm [71]. However, Nedjai et al. [57] have shown that the pond dense zone possesses the ability to create a local microclimate quite different from its surrounding. In terms of topography, the Claise basin can be described as a flat area with an altitude range of 76–181 m. According to Fischer et al. [72], six soil groups are present in the basin; these are in descending order of spatial coverage: Luvisols, Podzols, Leptosols, Cambisols, Fluvisols and Arenosols. According to Barrier and Gagnaison [73], the geological setting is dominated by Cenomanian, Jurassic and clay deposits and was completed at the end of the Tertiary era.

As a result of its poor hydrographic network, quasi-impermeable pedological setting, litho-stratigraphic composition, flat topography and abundant rainfall, stagnation of incoming water in the basin resulted in the formation of ponds [57, 74]. However, the proliferation of ponds in great numbers is not only due to natural origins, but also a translation of significant anthropogenic interference to overcome economic restraints imposed by the challenging soil productive capacity for use for extensive aquaculture [57, 75]. Despite the proficiency of aquaculture in the region, the Brenne Regional Natural Park displays a population density of 17.9 inhabitants/ km2 , which has been considered as one of the lowest in the Région Centre [76] and has been engaging in decreasing trends since the year 2006 [77]. This state leads to a population exodus in the study area, thus constricting further the presence and associated impact of anthropogenic activity.

Overall, the presence of a dominantly natural vegetated land cover and the absence of sloping areas generally imply a low erosive setting. However, given the questions raised regarding the impact of ponds, known to be modifiers of the hydro-sedimentary response of basins, particularly due to their presence in significant numbers and their position as a chain setting, this basin was chosen for investigation of the pond-impact on basin erosion risks.

#### **2.2 The Nahr Ibrahim basin: a representative Mediterranean basin**

The Nahr Ibrahim basin is one of the 11 coastal basins of Lebanon. It describes an area of 309 km<sup>2</sup> accounting for 3% of the country's area between 36° 2′ 46″ E, 34° 12′ 46″ N and 35° 38′ 35″ E, 33° 59′ 36″ N [62] and represents one of the most important Lebanese basins. The basin houses the perennial Nahr Ibrahim River, one of the 17 rivers protected by the Lebanese Ministry of Environment [78] given its biological and ecological significance and its role as a vital input for the local economy [79], primarily for agricultural irrigation, freshwater supplies and eco-tourism services [80]. The basin is characterized by a rich hydrological network consisting of several effluents feeding the 27-km-long river that originates from the Afqa and Roueiss springs at an altitude of 1200 m and 1265 m, respectively [62], and flows at 507 million m3 /year [81]. A typical heterogeneous Mediterranean basin land occupation pattern consisting of a heavily urbanized lower part, a semi-natural middle section and a mountainous upper basin accounting for nearly 60% of the basin is observed within. As many other regions of Lebanon, land occupation dynamics have occurred under a lack of governance, regulations, restraints and management plans [17] leading to an unequal repartition in the same landscape, thus giving rise to a heterogeneity of basin processes within. A typical Mediterranean climate showing increasing tendency toward prolonged droughts and more erratic intense rainfall events dominates the study area. Precipitations occur in the form of rainfall ranging from 900 mm to over 1400 mm, while in the upper mountainous part, snowfall is prevalent during the November–March period with a snow cover

**63**

*Evaluating Differences of Erosion Patterns in Natural and Anthropogenic Basins…*

**Parameters Claise basin Nahr Ibrahim basin** Climate Degraded oceanic Mediterranean

Rich

Dominated by Cenomanian, Jurassic and

Permeable soils with heterogeneous distribution

middle region with a diversity of superficial lands exploited with urban zones, agricultural fields planted with fruit trees, pasture with low

Quaternary deposits

Mountainous upper portion;

vegetation and forestry; heavily urbanized lower region

**Heterogeneous**

Topography Flat Heterogeneous, characterized by steep slopes

Severely fragmented, characterized by the presence of ponds in great numbers

Jurassic and clay deposits

Dominantly natural with the presence of manmade ponds

in large numbers **Homogeneous**

often lasting until late summer [62]. Geomorphologically, the basin corresponds to a mountainous area characterized by a varied topography consisting of hills and valleys with an upward slope gradient of nearly 20–25 m/km, along with a moderately sharp surface relief extending between the coast and 2600 m of altitude [61]. According to Darwish et al. [82], the Nahr Ibrahim basin is comprised of 11

Light showing minor increases Increasing

Andosols, Regosols, Anthrosols, Arenosols, Luvisols, cliffs, Cambisols, Gleysols and Fluvisols. According to Dubertret [83], the geology of the basin is presented by eight rock units dominated by Cenomanian carbonate rocks (70%) followed by the Jurassic (20%), with outcropping stratigraphic sequences revealing rock formations spanning from the Middle Jurassic to the recent epoch. Socioeconomically, and as other regions of Lebanon, the Nahr Ibrahim basin presents a densely populated lower portion corresponding to its coastal area in contrast to a less populated upper mountainous region [10]. In addition to urbanization in its lower part, the Nahr Ibrahim basin suffers from intensive industrial development [84] as opposed to a

As a result of its complex topography, abrupt climatic conditions and pedological composition, the Nahr Ibrahim basin has been reported by Abdallah and Faour

Since a comparative framework is targeted in this study, **Figure 1** presents the

settings of both study areas, while **Table 1** presents a general comparison.

<sup>1</sup> Calcaric Leptosols, Haplic Leptosols, Skeletic Regosols, Leptic Luvisols and Lithic Luvisols.

the dominance of Leptosols extending over Cenomanian (C4) and Jurassic (J4) formations, generally found over karstic and sloped areas, thus rendering them vulnerable to erosion. Further, as a result of extensive anthropogenic activity, the basin has been reported to be an area of intensive sloping runoff with increasing vulnerability to erosion [12] in addition to increasing trends of land degradation

, Leptosols,

of its area due to

soil groups in descending order of spatial coverage: Soil Associations1

[62] to be a region of intensive landslides that cover up to 7.6 km<sup>2</sup>

much less populated mountainous upper part.

[61], thus making it a suitable target for this study.

*DOI: http://dx.doi.org/10.5772/intechopen.89088*

Geology Dominated by Cenomanian,

Pedology Quasi-impermeable soil groups

Hydrological network

Land use/Land cover

Anthropogenic pressure

*Comparison of study area characteristics.*

**Table 1.**

*Evaluating Differences of Erosion Patterns in Natural and Anthropogenic Basins… DOI: http://dx.doi.org/10.5772/intechopen.89088*


#### **Table 1.**

*Soil Erosion - Rainfall Erosivity and Risk Assessment*

associated impact of anthropogenic activity.

investigation of the pond-impact on basin erosion risks.

**2.2 The Nahr Ibrahim basin: a representative Mediterranean basin**

at the end of the Tertiary era.

km2

an area of 309 km<sup>2</sup>

507 million m3

corresponds to the degraded oceanic continental climate with high oceanic influence having annual average temperatures of 11°C, 8–14 days of temperatures below −5°C and annual cumulative precipitations in the order of 700 mm [71]. However, Nedjai et al. [57] have shown that the pond dense zone possesses the ability to create a local microclimate quite different from its surrounding. In terms of topography, the Claise basin can be described as a flat area with an altitude range of 76–181 m. According to Fischer et al. [72], six soil groups are present in the basin; these are in descending order of spatial coverage: Luvisols, Podzols, Leptosols, Cambisols, Fluvisols and Arenosols. According to Barrier and Gagnaison [73], the geological setting is dominated by Cenomanian, Jurassic and clay deposits and was completed

As a result of its poor hydrographic network, quasi-impermeable pedological setting, litho-stratigraphic composition, flat topography and abundant rainfall, stagnation of incoming water in the basin resulted in the formation of ponds [57, 74]. However, the proliferation of ponds in great numbers is not only due to natural origins, but also a translation of significant anthropogenic interference to overcome economic restraints imposed by the challenging soil productive capacity for use for extensive aquaculture [57, 75]. Despite the proficiency of aquaculture in the region, the Brenne Regional Natural Park displays a population density of 17.9 inhabitants/

, which has been considered as one of the lowest in the Région Centre [76] and has been engaging in decreasing trends since the year 2006 [77]. This state leads to a population exodus in the study area, thus constricting further the presence and

Overall, the presence of a dominantly natural vegetated land cover and the absence of sloping areas generally imply a low erosive setting. However, given the questions raised regarding the impact of ponds, known to be modifiers of the hydro-sedimentary response of basins, particularly due to their presence in significant numbers and their position as a chain setting, this basin was chosen for

The Nahr Ibrahim basin is one of the 11 coastal basins of Lebanon. It describes

34° 12′ 46″ N and 35° 38′ 35″ E, 33° 59′ 36″ N [62] and represents one of the most important Lebanese basins. The basin houses the perennial Nahr Ibrahim River, one of the 17 rivers protected by the Lebanese Ministry of Environment [78] given its biological and ecological significance and its role as a vital input for the local economy [79], primarily for agricultural irrigation, freshwater supplies and eco-tourism services [80]. The basin is characterized by a rich hydrological network consisting of several effluents feeding the 27-km-long river that originates from the Afqa and Roueiss springs at an altitude of 1200 m and 1265 m, respectively [62], and flows at

pation pattern consisting of a heavily urbanized lower part, a semi-natural middle section and a mountainous upper basin accounting for nearly 60% of the basin is observed within. As many other regions of Lebanon, land occupation dynamics have occurred under a lack of governance, regulations, restraints and management plans [17] leading to an unequal repartition in the same landscape, thus giving rise to a heterogeneity of basin processes within. A typical Mediterranean climate showing increasing tendency toward prolonged droughts and more erratic intense rainfall events dominates the study area. Precipitations occur in the form of rainfall ranging from 900 mm to over 1400 mm, while in the upper mountainous part, snowfall is prevalent during the November–March period with a snow cover

accounting for 3% of the country's area between 36° 2′ 46″ E,

/year [81]. A typical heterogeneous Mediterranean basin land occu-

**62**

*Comparison of study area characteristics.*

often lasting until late summer [62]. Geomorphologically, the basin corresponds to a mountainous area characterized by a varied topography consisting of hills and valleys with an upward slope gradient of nearly 20–25 m/km, along with a moderately sharp surface relief extending between the coast and 2600 m of altitude [61]. According to Darwish et al. [82], the Nahr Ibrahim basin is comprised of 11 soil groups in descending order of spatial coverage: Soil Associations1 , Leptosols, Andosols, Regosols, Anthrosols, Arenosols, Luvisols, cliffs, Cambisols, Gleysols and Fluvisols. According to Dubertret [83], the geology of the basin is presented by eight rock units dominated by Cenomanian carbonate rocks (70%) followed by the Jurassic (20%), with outcropping stratigraphic sequences revealing rock formations spanning from the Middle Jurassic to the recent epoch. Socioeconomically, and as other regions of Lebanon, the Nahr Ibrahim basin presents a densely populated lower portion corresponding to its coastal area in contrast to a less populated upper mountainous region [10]. In addition to urbanization in its lower part, the Nahr Ibrahim basin suffers from intensive industrial development [84] as opposed to a much less populated mountainous upper part.

As a result of its complex topography, abrupt climatic conditions and pedological composition, the Nahr Ibrahim basin has been reported by Abdallah and Faour [62] to be a region of intensive landslides that cover up to 7.6 km<sup>2</sup> of its area due to the dominance of Leptosols extending over Cenomanian (C4) and Jurassic (J4) formations, generally found over karstic and sloped areas, thus rendering them vulnerable to erosion. Further, as a result of extensive anthropogenic activity, the basin has been reported to be an area of intensive sloping runoff with increasing vulnerability to erosion [12] in addition to increasing trends of land degradation [61], thus making it a suitable target for this study.

Since a comparative framework is targeted in this study, **Figure 1** presents the settings of both study areas, while **Table 1** presents a general comparison.

<sup>1</sup> Calcaric Leptosols, Haplic Leptosols, Skeletic Regosols, Leptic Luvisols and Lithic Luvisols.

## **3. Methodological workflow and theoretical aspects of the study**

## **3.1 The CORINE erosion risk model framework: basis and concepts**

Despite the prevalence of soil erosion assessment models, data availability limits the choice of sought models; therefore, given the data-sparse nature of the Nahr Ibrahim basin and the absence of quantitative soil loss studies in the country [42], the use of a process-based model is not possible. Therefore, a robust reliable model with relatively simple data requirement is sought. Accordingly, the semi-qualitative empirical CORINE erosion model has been chosen given its capability of accurately predicting the spatial distribution of erosion risks with relatively simple data requirement and ease of parameterization [63]. Despite its empirical nature which may provide it with an accuracy less than that of physical or process-based models, the CORINE model was chosen since empirical models are of adequate use for soil conservation studies [85]. Further, several successful applications of the model have been documented in different regions of the world (e.g., [86–88]), therefore giving it adequate reliability, particularly for the Mediterranean and data-sparse regions [89].

For erosion risk assessment using the CORINE model, several factors are required. These, according to Vertessy et al. [48], are:


The respective input layers were extracted from the databases and inputted into the Raster Calculator tool of ArcGIS for computation and application of the basis, equations and workflow for the CORINE presented in **Figure 2**. Each index was computed after classification into the corresponding CORINE categories, into the erodibility, erosivity and topography components which in turn are part of the potential soil erosion risk formula (**Figure 2**). Having obtained the potential soil erosion risk map, overlaying the vegetation cover layer allowed the computation of the actual soil erosion risk maps. Through scenario testing using a study adapted vegetation cover as an alternative input to the CORINE model, land degradation under the form of soil loss (here erosion) was determined. By quantitatively determining erosion risks using equations presented in **Figure 2**, an accurate representation of soil loss by erosion under current conditions is obtained. This step in turn serves as a reference or a baseline indicator for comparison with alternative scenarios. In the case of Nahr Ibrahim, for elaboration of measures to counterbalance the negative effects of land degradation, and balance land losses by land gains through application of the LDN concept, the CORINE model was used to reveal changes in erosion risks after LDN implementation. The latter is a new concept proposed in 2015 by the UNCCD to protect stable lands, halt ongoing degradation and restore

**65**

**Figure 2.**

*Evaluating Differences of Erosion Patterns in Natural and Anthropogenic Basins…*

degraded lands. At the quantitative scale, by computing erosion risks at the current state (reflected by current land occupation) versus LDN state, the quantitative link between the LDN concept and soil erosion by modification of erosion risks after LDN implementation was revealed. For the Claise basin, by means of alternative vegetation cover simulation, the role of ponds on erosion risks was highlighted by

*CORINE model methodology, adapted and modified from CORINE (1992); C: clay, S: sand, Si: silt, L: loam, Pi: total precipitation in month i, Pi: mean annual total precipitation, ti: mean temperature for the month i,* 

Data availability and quality are one of the main governing factors for any modeling study. The main reason behind the choice of the CORINE model is the data-scarcity state of Nahr Ibrahim where several input data for physical modeling are either lacking or insufficient. Therefore, with respect to the data requirements of the CORINE model, **Table 2** presents the input data for each study area.

revealing changes induced in the shades of their absence or drying.

**3.2 Input data and database description**

*and ki defined as the proportion of the month in which 2ti – Pi > 0.*

*DOI: http://dx.doi.org/10.5772/intechopen.89088*

*Evaluating Differences of Erosion Patterns in Natural and Anthropogenic Basins… DOI: http://dx.doi.org/10.5772/intechopen.89088*

#### **Figure 2.**

*Soil Erosion - Rainfall Erosivity and Risk Assessment*

required. These, according to Vertessy et al. [48], are:

**3. Methodological workflow and theoretical aspects of the study**

Despite the prevalence of soil erosion assessment models, data availability limits the choice of sought models; therefore, given the data-sparse nature of the Nahr Ibrahim basin and the absence of quantitative soil loss studies in the country [42], the use of a process-based model is not possible. Therefore, a robust reliable model with relatively simple data requirement is sought. Accordingly, the semi-qualitative empirical CORINE erosion model has been chosen given its capability of accurately predicting the spatial distribution of erosion risks with relatively simple data requirement and ease of parameterization [63]. Despite its empirical nature which may provide it with an accuracy less than that of physical or process-based models, the CORINE model was chosen since empirical models are of adequate use for soil conservation studies [85]. Further, several successful applications of the model have been documented in different regions of the world (e.g., [86–88]), therefore giving it adequate reliability, particularly for the Mediterranean and data-sparse regions [89]. For erosion risk assessment using the CORINE model, several factors are

1.*soil erodibility*, computed from three attributes—soil texture where fine particle fractions are more readily removed than coarser fractions [90], soil depth where deeper soils resist erosion as function of higher water-holding capacities [48] and stoniness given their protective role in the pre-surface runoff stage [87];

2. s*oil erosivity*, computed from two climatic indices—the Modified Fournier Index (MFI) to determine rainfall variability [91] and the Bagnouls-Gaussen aridity Index (BGI) [92] to reveal the possibility of abrupt short-storm events

3.*topography*, obtained through slope angle calculation given its pronounced effect on soil erosion, particularly when a certain critical threshold is exceeded [48];

4. *vegetation cover*, obtained from Land Use and Land Cover (LU/LC) maps given their effect on soil fixation via their roots and by reducing rainfall splash effect [5, 93].

The respective input layers were extracted from the databases and inputted into the Raster Calculator tool of ArcGIS for computation and application of the basis, equations and workflow for the CORINE presented in **Figure 2**. Each index was computed after classification into the corresponding CORINE categories, into the erodibility, erosivity and topography components which in turn are part of the potential soil erosion risk formula (**Figure 2**). Having obtained the potential soil erosion risk map, overlaying the vegetation cover layer allowed the computation of the actual soil erosion risk maps. Through scenario testing using a study adapted vegetation cover as an alternative input to the CORINE model, land degradation under the form of soil loss (here erosion) was determined. By quantitatively determining erosion risks using equations presented in **Figure 2**, an accurate representation of soil loss by erosion under current conditions is obtained. This step in turn serves as a reference or a baseline indicator for comparison with alternative scenarios. In the case of Nahr Ibrahim, for elaboration of measures to counterbalance the negative effects of land degradation, and balance land losses by land gains through application of the LDN concept, the CORINE model was used to reveal changes in erosion risks after LDN implementation. The latter is a new concept proposed in 2015 by the UNCCD to protect stable lands, halt ongoing degradation and restore

during normally dry seasons [48] leading to intensive erosion;

**3.1 The CORINE erosion risk model framework: basis and concepts**

**64**

*CORINE model methodology, adapted and modified from CORINE (1992); C: clay, S: sand, Si: silt, L: loam, Pi: total precipitation in month i, Pi: mean annual total precipitation, ti: mean temperature for the month i, and ki defined as the proportion of the month in which 2ti – Pi > 0.*

degraded lands. At the quantitative scale, by computing erosion risks at the current state (reflected by current land occupation) versus LDN state, the quantitative link between the LDN concept and soil erosion by modification of erosion risks after LDN implementation was revealed. For the Claise basin, by means of alternative vegetation cover simulation, the role of ponds on erosion risks was highlighted by revealing changes induced in the shades of their absence or drying.

#### **3.2 Input data and database description**

Data availability and quality are one of the main governing factors for any modeling study. The main reason behind the choice of the CORINE model is the data-scarcity state of Nahr Ibrahim where several input data for physical modeling are either lacking or insufficient. Therefore, with respect to the data requirements of the CORINE model, **Table 2** presents the input data for each study area.

## **3.3 General workflow: a dual approach between current and simulated conditions**

The methodological workflow for this study consists of a two-fold approach:


For the LDN approach, the established LU/LC map was intersected under GIS environment with the Lebanese national land capability classification map [95] and the national organic C maps [96] clipped to the Nahr Ibrahim basin in analogy to the LDN indicators. The integration of land capability classification is performed given its importance as an indicator for better use of land, optimization of current LU/LC and for providing insights for future land planning [97, 98]. This step allows a relatively simple yet meaningful tool for land owners and decision-makers for revealing sustainability distribution [66], thus addressing the LDN challenges of land stewardship, and implementing integrated planning approaches for sustainable use of the land and soil resources. After establishing the proposed LDN scenario, based on the concept's response strategy, the LDN-based LU/LC map was used as an alternative input to the CORINE model to compare erosion patterns with those reflecting current conditions in order to reveal LDN's effect on soil erosion in analogy to the work done by Al Sayah et al. [20].

For the Claise basin, study of SAFRAN records for the period 1970–2018, through trend analysis, revealed decreasing precipitations coupled to increases in temperature. Therefore, an alternative scenario assuming that ponds were to be dried was established and inputted again to the CORINE model for comparison with current conditions.


**67**

workflow.

**Figure 3.**

*Methodological workflow.*

**components for both basins**

*Evaluating Differences of Erosion Patterns in Natural and Anthropogenic Basins…*

The produced actual soil erosion map for Nahr Ibrahim was validated on field after a storm event, while for the Claise basin, the actual soil erosion map was validated with ancillary soil erosion maps. **Figure 3** presents the adapted

**4. Results and discussion: comparative analysis of the CORINE's model** 

In this section, a detailed comparison between the two study areas in terms of soil erodibility, erosivity, topography and vegetation cover is first presented. As a second step, the alternative scenarios for both study areas and a comparison with

With reference to the pedological composition of the study areas, the Claise basin possesses six soil types: Luvisols, Podzols, Leptosols, Cambisols, Fluvisols and Arenosols. On the other hand, the Nahr Ibrahim basin possesses 11 soil types: Leptosols, Andosols, Regosols, Anthrosols, Arenosols, Luvisols, cliffs, Cambisols, Gleysols and Fluvisols. **Tables 3** and **4** present a pedological comparison of the

the current conditions for revealing change effects are explained.

**4.1 Soil erodibility and pedologic structure of the study areas**

study areas in terms of composition and texture.

*DOI: http://dx.doi.org/10.5772/intechopen.89088*

### **Table 2.**

*Input data for the CORINE model and source.*

*Evaluating Differences of Erosion Patterns in Natural and Anthropogenic Basins… DOI: http://dx.doi.org/10.5772/intechopen.89088*

**Figure 3.** *Methodological workflow.*

*Soil Erosion - Rainfall Erosivity and Risk Assessment*

differences and inferring their sources.

analogy to the work done by Al Sayah et al. [20].

DEM 25 m raster; source: Institut

*Input data for the CORINE model and source.*

Weather data Système d'Analyse Fournissant des

with current conditions.

Land use and land cover maps (classified according to the CORINE

classification)

absence effect in the Claise.

**3.3 General workflow: a dual approach between current and simulated conditions**

The methodological workflow for this study consists of a two-fold approach:

1.Establishment of erosion maps for both study areas under current land occupation settings in order to establish a comparative framework for revealing

For the LDN approach, the established LU/LC map was intersected under GIS environment with the Lebanese national land capability classification map [95] and the national organic C maps [96] clipped to the Nahr Ibrahim basin in analogy to the LDN indicators. The integration of land capability classification is performed given its importance as an indicator for better use of land, optimization of current LU/LC and for providing insights for future land planning [97, 98]. This step allows a relatively simple yet meaningful tool for land owners and decision-makers for revealing sustainability distribution [66], thus addressing the LDN challenges of land stewardship, and implementing integrated planning approaches for sustainable use of the land and soil resources. After establishing the proposed LDN scenario, based on the concept's response strategy, the LDN-based LU/LC map was used as an alternative input to the CORINE model to compare erosion patterns with those reflecting current conditions in order to reveal LDN's effect on soil erosion in

For the Claise basin, study of SAFRAN records for the period 1970–2018, through trend analysis, revealed decreasing precipitations coupled to increases in temperature. Therefore, an alternative scenario assuming that ponds were to be dried was established and inputted again to the CORINE model for comparison

**Data Claise basin Nahr Ibrahim basin**

Digitized from ortho-rectified aerial photography 2014, at 0.50 m resolution (R. Nedjai) and verified with ancillary CORINE land use/land cover maps

Soil maps Harmonized World Soil Database [72] Soil map of Lebanon 1:50000 [82]

Géographique National (IGN) - France

Renseignements Adaptés à la Nivologie

(SAFRAN) model [94]

Digitized from SPOT (2018, 1.5 m) satellite imagery and verified on field—National Council for Scientific Research— Remote Sensing Center

10 m raster, National Council for Scientific Research—Remote

Lebanese Agricultural Research Institute's Akkoura Weather

Sensing Center

Station

2.Establishment of alternative land use and land cover (LU/LC) scenarios for comparison with current settings: for Nahr Ibrahim based on the LDN concept, and for the Claise basin by means of alternative scenario testing by simulation of pond drying (empty ponds). Alternative simulations are carried out in order to prospect the potential of LDN through land use planning to reduce soil erosion for Nahr Ibrahim, and for determining the pond presence/

**66**

**Table 2.**

The produced actual soil erosion map for Nahr Ibrahim was validated on field after a storm event, while for the Claise basin, the actual soil erosion map was validated with ancillary soil erosion maps. **Figure 3** presents the adapted workflow.

## **4. Results and discussion: comparative analysis of the CORINE's model components for both basins**

In this section, a detailed comparison between the two study areas in terms of soil erodibility, erosivity, topography and vegetation cover is first presented. As a second step, the alternative scenarios for both study areas and a comparison with the current conditions for revealing change effects are explained.

## **4.1 Soil erodibility and pedologic structure of the study areas**

With reference to the pedological composition of the study areas, the Claise basin possesses six soil types: Luvisols, Podzols, Leptosols, Cambisols, Fluvisols and Arenosols. On the other hand, the Nahr Ibrahim basin possesses 11 soil types: Leptosols, Andosols, Regosols, Anthrosols, Arenosols, Luvisols, cliffs, Cambisols, Gleysols and Fluvisols. **Tables 3** and **4** present a pedological comparison of the study areas in terms of composition and texture.

With respect to the components of soil erodibility, soil texture in the Claise basin was found to be 68.5% loam, 28.8% loamy sand, 2.5% of clay and the remainder percentage is made of sand. The Nahr Ibrahim basin on the other hand, as function of its more diverse pedological composition, was found to possess more textural classes. These are in descending order of spatial coverage: clay (32.5%), sandy clay loam (26.6%), loamy sand (14.4%), clay loam (10.9%), loam, sandy loam, silty clay loam, silt loam and silty clay. With respect to the CORINE textural classification, the Claise basin mostly corresponds to the highly and moderately erodible texture classes, while Nahr Ibrahim mainly corresponds to the slightly erodible classes. Therefore, in terms of soil texture, the Nahr Ibrahim basin is more erosion resistant than the Claise.

Regarding soil depth, the Claise basin fits to the slightly erodible class with more than 90% of its soils corresponding to the deep (>75 cm) category and the moderately erodible class for its remainder 10%. On the other hand, the Nahr Ibrahim basin presents less than 20% of deep soil classes and more than 40% of shallow depths. Therefore, in terms of soil depth, the Claise basin soils are more resistant to erosion than those of Nahr Ibrahim.

The stone cover of the Claise basin, however, dominantly corresponds to the not fully protected class, while most of the Nahr Ibrahim basin corresponds to the fully protected class, thus giving it a more or less protective stone cover. Globally, the pedological setting of the Nahr Ibrahim basin was found to be more erosion resistant than the Claise.

### **4.2 Erosivity under different climatic contexts**

Since erosivity depends on rainfall, a comparison between the climatic contexts of both study area is presented in **Tables 5** and **6**. As seen, no dry months exist in the Claise and rainfall is much more pronounced than in Nahr Ibrahim. This is observed particularly during summer since rainfall is at its lowest in Nahr Ibrahim as opposed to the Claise where it reaches its maximal values.

At this point, it is important to account for the differences in the climatic settings of both basins, where the Claise corresponds to the degraded oceanic climate, while Nahr Ibrahim is of the Mediterranean type. Therefore, a greater rainfall variability and more prolonged aridity periods are expected for the Nahr Ibrahim, which are characteristic of the Mediterranean climate. This speculation was verified by the Modified Fournier Index (MFI) which was found to be 217 for Nahr Ibrahim (corresponding to the very high erodibility class indexed as 5) and 80 (very low, class 1) for the Claise basin. On the other hand, the Bagnouls-Gaussen aridity index (BGI) further revealed differences between the study areas, where Nahr Ibrahim's BGI is


**69**

**Table 4.**

climate-induced erosion risks.

*Pedological composition of the Nahr Ibrahim basin.*

model classification.

*Evaluating Differences of Erosion Patterns in Natural and Anthropogenic Basins…*

Soil Associations 154.05 50.52 Areno-Eutric Leptosols 16.33 5.36 Calcaric Fluvisols 0.92 0.30 Calcaric Leptosols 1.43 0.47 Calcaric Regosols 3.31 1.08 Calcaro-Hortic Anthrosols 8.18 2.68 Calcaro-Mollic Leptosols 25.29 8.29 Endogleyic Anthrosols 0.25 0.08 Endoskeletic Regosols 6.40 2.10 Eutric Arenosols 0.16 0.05 Eutric Cambisols 1.34 0.44 Eutric Fluvisols 0.46 0.15 Eutric Leptosols 51.78 16.98 Gleyic Leptosols 3.05 1.00 Haplic Arenosols 7.36 2.42 Haplic Luvisols 0.18 0.06 Hypoluvic Arenosols 0.72 0.24 Leptic Andosols 13.34 4.37 Leptic Luvisols 4.09 1.34 Luvic Calcisols 0.02 0.01 Mollic Andosols 0.18 0.06 Mollic Gleysols 1.05 0.35 Rendzic Leptosols 4.82 1.58 Skeletic Regosols 0.16 0.05 Vertic Cambisols 0.05 0.02

**) Percentage (%)**

**Nahr Ibrahim soil classes Area (km2**

49 (corresponding to the moist class 2) and it is 0 for the Claise corresponding to a humid area with respect to the CORINE BGI classification. In analogy to CORINE's erosivity formula, the Claise basin has an erosivity factor of 1, while for Nahr Ibrahim, the erosivity index is 10. Despite the much more pronounced rainfall in the Claise, the even precipitation distribution in the region resulted in a reduction of climate-induced soil erosion [99] as opposed to Nahr Ibrahim, signifying higher

**4.3 Effect of topography: a contrast between a mountainous and a flat basin**

**Table 7** presents the slopes of both study areas with respect to the CORINE's

Topography is one of the most pronounced differences between the study areas, due to differences in the topographic and orographic composition since the Nahr Ibrahim basin presents a Mediterranean mountainous basin. Accordingly, computing the slope from the DEM rasters of each study area using the slope

*DOI: http://dx.doi.org/10.5772/intechopen.89088*

#### **Table 3.**

*Pedological composition of the Claise basin.*


#### *Evaluating Differences of Erosion Patterns in Natural and Anthropogenic Basins… DOI: http://dx.doi.org/10.5772/intechopen.89088*

#### **Table 4.**

*Soil Erosion - Rainfall Erosivity and Risk Assessment*

than the Claise.

erosion than those of Nahr Ibrahim.

**4.2 Erosivity under different climatic contexts**

as opposed to the Claise where it reaches its maximal values.

**Claise soil classes Area (km2**

resistant than the Claise.

With respect to the components of soil erodibility, soil texture in the Claise basin

Regarding soil depth, the Claise basin fits to the slightly erodible class with more

than 90% of its soils corresponding to the deep (>75 cm) category and the moderately erodible class for its remainder 10%. On the other hand, the Nahr Ibrahim basin presents less than 20% of deep soil classes and more than 40% of shallow depths. Therefore, in terms of soil depth, the Claise basin soils are more resistant to

The stone cover of the Claise basin, however, dominantly corresponds to the not fully protected class, while most of the Nahr Ibrahim basin corresponds to the fully protected class, thus giving it a more or less protective stone cover. Globally, the pedological setting of the Nahr Ibrahim basin was found to be more erosion

Since erosivity depends on rainfall, a comparison between the climatic contexts

At this point, it is important to account for the differences in the climatic settings of both basins, where the Claise corresponds to the degraded oceanic climate, while Nahr Ibrahim is of the Mediterranean type. Therefore, a greater rainfall variability and more prolonged aridity periods are expected for the Nahr Ibrahim, which are characteristic of the Mediterranean climate. This speculation was verified by the Modified Fournier Index (MFI) which was found to be 217 for Nahr Ibrahim (corresponding to the very high erodibility class indexed as 5) and 80 (very low, class 1) for the Claise basin. On the other hand, the Bagnouls-Gaussen aridity index (BGI) further revealed differences between the study areas, where Nahr Ibrahim's BGI is

**) Percentage (%)**

of both study area is presented in **Tables 5** and **6**. As seen, no dry months exist in the Claise and rainfall is much more pronounced than in Nahr Ibrahim. This is observed particularly during summer since rainfall is at its lowest in Nahr Ibrahim

Calcaric Cambisols 17.38 2.49 Calcaric Fluvisols 4.79 0.69 Cambic Podzols 195.95 28.07 Gleyic Luvisols 439.70 62.99 Luvic Arenosols 2.43 0.35 Rendzic Leptosols 37.83 5.42

was found to be 68.5% loam, 28.8% loamy sand, 2.5% of clay and the remainder percentage is made of sand. The Nahr Ibrahim basin on the other hand, as function of its more diverse pedological composition, was found to possess more textural classes. These are in descending order of spatial coverage: clay (32.5%), sandy clay loam (26.6%), loamy sand (14.4%), clay loam (10.9%), loam, sandy loam, silty clay loam, silt loam and silty clay. With respect to the CORINE textural classification, the Claise basin mostly corresponds to the highly and moderately erodible texture classes, while Nahr Ibrahim mainly corresponds to the slightly erodible classes. Therefore, in terms of soil texture, the Nahr Ibrahim basin is more erosion resistant

**68**

**Table 3.**

*Pedological composition of the Claise basin.*

*Pedological composition of the Nahr Ibrahim basin.*

49 (corresponding to the moist class 2) and it is 0 for the Claise corresponding to a humid area with respect to the CORINE BGI classification. In analogy to CORINE's erosivity formula, the Claise basin has an erosivity factor of 1, while for Nahr Ibrahim, the erosivity index is 10. Despite the much more pronounced rainfall in the Claise, the even precipitation distribution in the region resulted in a reduction of climate-induced soil erosion [99] as opposed to Nahr Ibrahim, signifying higher climate-induced erosion risks.

## **4.3 Effect of topography: a contrast between a mountainous and a flat basin**

**Table 7** presents the slopes of both study areas with respect to the CORINE's model classification.

Topography is one of the most pronounced differences between the study areas, due to differences in the topographic and orographic composition since the Nahr Ibrahim basin presents a Mediterranean mountainous basin. Accordingly, computing the slope from the DEM rasters of each study area using the slope


**Table 5.**

*Average temperature and precipitation for the Claise basin (1970–2018).*


#### **Table 6.**

*Average temperature and precipitation for the Nahr Ibrahim basin (2009–2018).*

tool of ArcGIS, the Claise basin corresponds entirely to the flat topography class in contrast to the 85% dominance of steep classes in the Nahr Ibrahim basin. For that reason, a significant difference in erosion patterns is expected given the very pronounced role of slope on erosion risks [100], particularly in the Nahr Ibrahim basin, where its slopes, as reported in Ref. [12, 62], were the main reasons behind its high rates of erosion and landslide occurrences as opposed to the predominantly flat Claise basin.

## **4.4 Vegetation cover: a pronounced difference between a natural and an anthropogenically managed basin**

Given its integral role as the most crucial element for erosion risk assessment in the CORINE erosion model, a particular focus is given to the vegetation cover under a setting of natural versus managed basin. This difference is particularly observed when comparing the land use and land cover settings of both study areas. The 707 km<sup>2</sup> Claise basin displays a homogeneous distribution of 21 land occupation classes throughout its area (**Table 8**), while the 309 km<sup>2</sup> Nahr Ibrahim basin occupying an area less than half the area of the Claise presents 43 land use/land cover classes (**Table 9**), which is nearly double the categories of the Claise.


**71**

**Table 8.**

*Distribution of the Claise's land occupation classes.*

*Evaluating Differences of Erosion Patterns in Natural and Anthropogenic Basins…*

**Claise land occupation Area (km2**

Agricultural areas 0.15 0.02 Clear broad-leaved forest 2.21 0.31 Clear mixed forest 0.90 0.13 Coniferous forest 26.94 3.70 Dense broad-leaved forest 163.58 23.14 Dense mixed forest 27.00 3.82 Field crops in medium to large terraces 19.14 2.71 Fruit trees 0.20 0.03 Grassland 207.04 29.28 Inland marshes 4.01 0.57 Low-density urban tissue 3.24 0.46 Medium-density urban tissue 1.76 0.25 Mineral extraction site 0.10 0.02 Non-irrigated field crops 151.02 21.36 Pond 79.47 11.24 River 0.55 0.08 Scrubland 2.80 0.40 Scrubland with some bigger dispersed trees 15.36 2.17 Urban expansion site 0.01 0.00 Urban sprawl on clear wooded lands 0.01 0.00 Urban sprawl on field crops 1.01 0.14 Urban sprawl on grassland 1.20 0.17

**) Percentage (%)**

The land occupation setting of both study areas not only reveals a significant difference between two contexts, but also highlights the effect of management strategies on the studied process. With reference to **Figure 1** and by grouping LU/LC classes into urban/unproductive, agricultural and vegetated (grass, scrublands and forests) areas, a 1.05, 24.07 and 63.01% distribution is observed in the Claise basin, while a 62, 10.27 and 27.73% distribution of the listed class is seen in Nahr Ibrahim. In the Claise, the remainder 11.87% corresponds to water bodies (the Claise River and ponds). Accordingly, with respect to the CORINE erosion model classification, the Claise basin's land occupation pattern corresponds to a 63.58% protected cover and 25.12% not fully protected, while the Nahr Ibrahim basin shows a 29% fully protected cover and a 71% not fully protected. At this point, pronounced differences of topography, climate and vegetation cover are expected to be translated in the erosion maps.

**4.5 Actual soil erosion risk maps: a result of contrasting pedological, climatological, topographic and vegetation cover factors**

the actual soil erosion risk maps of the studied areas (**Figure 4**).

After establishment of the potential soil erosion risk maps in analogy to **Figure 2**, land use and land cover maps of the study areas were intersected to yield

*DOI: http://dx.doi.org/10.5772/intechopen.89088*

**Table 7.** *Slope distribution in the study areas.*


#### *Evaluating Differences of Erosion Patterns in Natural and Anthropogenic Basins… DOI: http://dx.doi.org/10.5772/intechopen.89088*

#### **Table 8.**

*Soil Erosion - Rainfall Erosivity and Risk Assessment*

*Average temperature and precipitation for the Nahr Ibrahim basin (2009–2018).*

*Average temperature and precipitation for the Claise basin (1970–2018).*

**anthropogenically managed basin**

tool of ArcGIS, the Claise basin corresponds entirely to the flat topography class in contrast to the 85% dominance of steep classes in the Nahr Ibrahim basin. For that reason, a significant difference in erosion patterns is expected given the very pronounced role of slope on erosion risks [100], particularly in the Nahr Ibrahim basin, where its slopes, as reported in Ref. [12, 62], were the main reasons behind its high rates of erosion and landslide occurrences as opposed to the predominantly

**Claise month Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec**

**4.4 Vegetation cover: a pronounced difference between a natural and an** 

land occupation classes throughout its area (**Table 8**), while the 309 km<sup>2</sup>

Ibrahim basin occupying an area less than half the area of the Claise presents 43 land use/land cover classes (**Table 9**), which is nearly double the categories of

**Slope class Claise (%) Nahr Ibrahim (%)**

Very gentle to flat 99.3 2 Gentle 0.7 13 Steep — 28 Very steep — 57

Given its integral role as the most crucial element for erosion risk assessment in the CORINE erosion model, a particular focus is given to the vegetation cover under a setting of natural versus managed basin. This difference is particularly observed when comparing the land use and land cover settings of both study

Claise basin displays a homogeneous distribution of 21

Nahr

**Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec**

4.7 5.2 7.8 10.4 14.3 17.9 20.1 19.7 16.1 11.8 7.7 4.8

416 677 1106 1526 1782 2045 2108 1826 1356 818 482 361

4.5 6.1 8. 11.7 15. 18.3 20.6 21 18.4 15.3 10.5 6.8

181 125 127 56 33 6 0.16 1 19 55 106 197

**Nahr Ibrahim month**

Average temp. (°C)

Precipitation (mm)

**Table 5.**

Average temp. (°C)

Precipitation (mm)

flat Claise basin.

areas. The 707 km<sup>2</sup>

the Claise.

**Table 6.**

**70**

**Table 7.**

*Slope distribution in the study areas.*

*Distribution of the Claise's land occupation classes.*

The land occupation setting of both study areas not only reveals a significant difference between two contexts, but also highlights the effect of management strategies on the studied process. With reference to **Figure 1** and by grouping LU/LC classes into urban/unproductive, agricultural and vegetated (grass, scrublands and forests) areas, a 1.05, 24.07 and 63.01% distribution is observed in the Claise basin, while a 62, 10.27 and 27.73% distribution of the listed class is seen in Nahr Ibrahim. In the Claise, the remainder 11.87% corresponds to water bodies (the Claise River and ponds). Accordingly, with respect to the CORINE erosion model classification, the Claise basin's land occupation pattern corresponds to a 63.58% protected cover and 25.12% not fully protected, while the Nahr Ibrahim basin shows a 29% fully protected cover and a 71% not fully protected. At this point, pronounced differences of topography, climate and vegetation cover are expected to be translated in the erosion maps.

## **4.5 Actual soil erosion risk maps: a result of contrasting pedological, climatological, topographic and vegetation cover factors**

After establishment of the potential soil erosion risk maps in analogy to **Figure 2**, land use and land cover maps of the study areas were intersected to yield the actual soil erosion risk maps of the studied areas (**Figure 4**).


**73**

**Figure 4.**

*Evaluating Differences of Erosion Patterns in Natural and Anthropogenic Basins…*

The produced maps were in turn verified by field campaigns for the Nahr Ibrahim basin and by cross-validation with ancillary erosion risk maps for the Claise basin. Both maps showed adequate representativity and accuracy in the validation stage. As seen from **Figure 4**, significant differences were observed between the two

for moderate risks and 56.42% for high erosion risk zones.

I.Through graphical comparison, the distribution of erosion risks in the two basins is clearly contrasted. The dominance of high erosion risk zones in the Nahr Ibrahim basin is opposed by the prevalence of low erosion risks in the Claise. In the latter, low erosion risks account for 65.6%, moderate risks account for 21.68%, while high erosion risks account for 0.18%. In contrast, the zonal distribution in the Nahr Ibrahim basin is 4% for low risk, 39.5%

II.The significant difference of erosion patterns between the study areas can be mainly attributed to Nahr Ibrahim's topographic complexity, significant slope steepness, heterogeneous pedological context, dense hydrographic network [31] and its vegetation cover which possesses the most important effect on the CORINE model. Given its status as the only human-controllable input factor, the effect of land management induced by the type of land occupation is also highlighted [101], since a natural setting basin corresponding to a well-managed natural park shows low erosion risks, while a randomly managed basin presents significant ero-

III.In the Claise basin, a no erosion zone is graphically noticed. The latter corresponds to the pond dense zone. At the individual scale, ponds are known for trapping incoming water, increasing its concentration time, decreasing runoff and retaining water, soil and debris by settling, thus trapping eroding soils [102]. At the scale of the Claise, the individual pond effect is much more amplified given the presence of ponds in such large numbers (2179) in a connected matrix, thus increasingly trapping soil/sediment in a collective manner. Their presence as a land occupation class capable of trapping soil and water gives them the role of a protective cover from which soil loss cannot occur, therefore leading to a "no erosion" zone. The collective effect

*Actual soil erosion risk for the study areas under current land occupation conditions.*

*DOI: http://dx.doi.org/10.5772/intechopen.89088*

sion levels.

basins, therefore allowing us to infer several points:

#### **Table 9.**

*Distribution of the Nahr Ibrahim's land occupation classes.*

### *Evaluating Differences of Erosion Patterns in Natural and Anthropogenic Basins… DOI: http://dx.doi.org/10.5772/intechopen.89088*

The produced maps were in turn verified by field campaigns for the Nahr Ibrahim basin and by cross-validation with ancillary erosion risk maps for the Claise basin. Both maps showed adequate representativity and accuracy in the validation stage. As seen from **Figure 4**, significant differences were observed between the two basins, therefore allowing us to infer several points:


**Figure 4.** *Actual soil erosion risk for the study areas under current land occupation conditions.*

*Soil Erosion - Rainfall Erosivity and Risk Assessment*

**Nahr Ibrahim land occupation Area (km2**

Medium-density urban tissue 1.7 0.55 Low-density urban tissue 4.16 1.35 Urban expansion sites 0.61 0.2 Industrial or commercial zone 0.31 0.1 Mineral extraction sites 3.18 0.96 Diverse equipment 0.04 0.01 Tourist resorts 0.02 0.01 Field crops in small fields/terraces 4.01 1.02 Urban sprawl on field crops 0.05 0.02 Olives 0.6 0.19 Fruit trees 24.08 7.79 Citrus trees 0.02 0.01 Banana 0.04 0.01 Urban sprawl on permanent crops 2.34 0.76 Greenhouses 0.62 0.2 Dense pine forests 4.42 1.43 Dense oak forests 6.03 1.95 Dense cypress forests 0.08 0.03 Dense juniper forests 0.3 0.1 Dense mixed forests 34.38 11.13 Urban sprawl on dense wooded lands 1.05 0.34 Clear pine forests 1.23 0.4 Clear cypress forests 0.04 0.01 Clear oak forests 9.2 2.98 Clear mixed wooded lands 8.03 2.6 Clear fir forests 0.45 0.15 Clear juniper forests 5.75 1.86 Other type of clear forests 0.05 0.02 Scrublands 2.48 0.8 Scrublands with some bigger dispersed trees 6.34 2.05 Urban sprawl on scrublands 0.0298 0.01 Hill lakes 0.15 0.05 Sand beach 0.03 0.01 Unproductive areas 181.43 58.72 Burnt areas 0.1141 0.04 Abandoned agricultural land 0.74 0.24 Grasslands 5.86 1.9

**) Percentage (%)**

**72**

**Table 9.**

*Distribution of the Nahr Ibrahim's land occupation classes.*

of aggregated ponds as a result of their setting as a conceptual large surface was discussed by Downing [59]; he reports that, as a result of large numbers in an interlocking setting, individual retention capacities and trapping processes are amplified to rates even greater than those of larger water bodies, such as lakes, making these ponds very effective in the process of soil erosion.


#### **4.6 Alternative simulations for comparison**

Analyzing trends obtained from SAFRAN database and applied to the Claise revealed a decreasing trend of precipitation and increasing trend of temperatures. Given the evaporative regime of ponds, an alternative scenario simulating the absence of ponds was obtained. The latter was input, as the alternative vegetation cover, into the CORINE model for comparison with the current condition erosion map in order to determine the impact of pond presence/absence.

For the Nahr Ibrahim basin, the CORINE erosion map provided a tool for land degradation mapping. In analogy to the LDN concept at the scale of soil loss, the land use/land cover, actual soil erosion, national land capability classification and organic C map were intersected to reveal sustainability distribution. The latter was determined following the methodology for sustainability mapping in Al Sayah et al. (2019a) where the adequacy or inadequacy of the already present LU/LC distribution over the different land capability groups (I–IV representing the arable lands and an additional group V combining the USDA's groups V–VIII) allowed the categorization into sustainable and non-sustainable development zones. **Figure 5** shows sustainability distribution in the Nahr Ibrahim basin.

**75**

**Table 10.**

*Evaluating Differences of Erosion Patterns in Natural and Anthropogenic Basins…*

Noticeably, the prevalence of unsustainable development areas is apparent; these account for 66% of the study area [20]. By optimization of land use and land cover categories covering the soil classes IV and V (19.35% of the basin), an alternative LDN-based scenario was obtained by increasing natural cover (grass,

*Sustainability distribution of the Nahr Ibrahim basin obtained from intersecting land use and land cover maps* 

By re-using the two alternative vegetation cover scenarios in the CORINE model,

**Table 10** shows significant shifts of erosion patterns; for Nahr Ibrahim, high erosion risks decreased by 13.9%, low and moderate risks increased by 3 and 10.8%, respectively [20], while for the Claise basin, the opposite was observed with decreases in the no and low erosion risks as compared to increases in the moderate and high erosion risk categories. Thus, the contribution of LDN in reducing erosion highlights the importance of land planning and the effect of management on soil erosion, confining the LDN concept as an effective counter-erosion measure. For the Claise basin, changes in erosion patterns also reveal the importance of ponds as efficient counter-erosion structures that can be used to control areas of significant

> **Nahr Ibrahim LDN (%)**

None 0 0 12.48 1.12 Low 4 7.1 65.66 0.52 Moderate 39.5 50.4 21.68 76.8 High 56.47 42.54 0.18 21.56

**Claise current (%)** **Claise simulation (%)**

*DOI: http://dx.doi.org/10.5772/intechopen.89088*

scrublands and forests) over these soils.

*with land capability classification layers.*

**Table 10** was obtained.

**Figure 5.**

runoff and excessive erosion.

**Nahr Ibrahim current (%)**

*Erosion risks of the study areas under current and simulated conditions.*

**Erosion risk**

*Evaluating Differences of Erosion Patterns in Natural and Anthropogenic Basins… DOI: http://dx.doi.org/10.5772/intechopen.89088*

#### **Figure 5.**

*Soil Erosion - Rainfall Erosivity and Risk Assessment*

even within a natural setting.

degradation mapping.

**4.6 Alternative simulations for comparison**

soil erosion.

of aggregated ponds as a result of their setting as a conceptual large surface was discussed by Downing [59]; he reports that, as a result of large numbers in an interlocking setting, individual retention capacities and trapping processes are amplified to rates even greater than those of larger water bodies, such as lakes, making these ponds very effective in the process of

IV.Within the Claise basin, moderate erosion risk zones are observed in the agricultural areas. These observations are concurrent with those of Verheijen et al. [8] who report, despite the similarity of the pedological context along with the topographic factor and climatic conditions, soil erosion is ultimately influenced by the vegetation cover and particularly by the presence of agricultural classes (crops) that have been attributed to the highest erosion rates in Europe [4, 103]. Accordingly, despite the homogeneity of the Claise basin and its natural state, agricultural parcels are seen to have higher erosion risks than their surroundings. This further solidifies the role of human-induced LU/LC management in affecting natural processes

V.The alarming erosion risk map of Nahr Ibrahim, not only provides an informative tool for erosion, but also highlights the need for intervention, since the basin is severely subjected to soil loss and consequent land degradation. By pin-pointing zones of different erosion risks, an insight toward a priority-based land use planning, targeting zones of higher threats, is achieved. Therefore, in the case of Nahr Ibrahim, soil erosion mapping revealed the spatial distribution of erosion risks as a first step, and served as a land planning decision-oriented tool by pin-pointing zones at high risks as a second step. Through this dual insight provided from the integration of erosion maps, a holistic approach toward land degradation mapping was achieved. Consequently, a proper understanding regarding the types of foreseen soil conservation measures and optimal land occupation classes [104] is made possible, which reiterates the importance of the integration of soil erosion into soil conservation planning [105] and land

Analyzing trends obtained from SAFRAN database and applied to the Claise revealed a decreasing trend of precipitation and increasing trend of temperatures. Given the evaporative regime of ponds, an alternative scenario simulating the absence of ponds was obtained. The latter was input, as the alternative vegetation cover, into the CORINE model for comparison with the current condition erosion

For the Nahr Ibrahim basin, the CORINE erosion map provided a tool for land degradation mapping. In analogy to the LDN concept at the scale of soil loss, the land use/land cover, actual soil erosion, national land capability classification and organic C map were intersected to reveal sustainability distribution. The latter was determined following the methodology for sustainability mapping in Al Sayah et al. (2019a) where the adequacy or inadequacy of the already present LU/LC distribution over the different land capability groups (I–IV representing the arable lands and an additional group V combining the USDA's groups V–VIII) allowed the categorization into sustainable and non-sustainable development zones. **Figure 5**

map in order to determine the impact of pond presence/absence.

shows sustainability distribution in the Nahr Ibrahim basin.

**74**

*Sustainability distribution of the Nahr Ibrahim basin obtained from intersecting land use and land cover maps with land capability classification layers.*

Noticeably, the prevalence of unsustainable development areas is apparent; these account for 66% of the study area [20]. By optimization of land use and land cover categories covering the soil classes IV and V (19.35% of the basin), an alternative LDN-based scenario was obtained by increasing natural cover (grass, scrublands and forests) over these soils.

By re-using the two alternative vegetation cover scenarios in the CORINE model, **Table 10** was obtained.

**Table 10** shows significant shifts of erosion patterns; for Nahr Ibrahim, high erosion risks decreased by 13.9%, low and moderate risks increased by 3 and 10.8%, respectively [20], while for the Claise basin, the opposite was observed with decreases in the no and low erosion risks as compared to increases in the moderate and high erosion risk categories. Thus, the contribution of LDN in reducing erosion highlights the importance of land planning and the effect of management on soil erosion, confining the LDN concept as an effective counter-erosion measure. For the Claise basin, changes in erosion patterns also reveal the importance of ponds as efficient counter-erosion structures that can be used to control areas of significant runoff and excessive erosion.


#### **Table 10.**

*Erosion risks of the study areas under current and simulated conditions.*

## **5. Conclusions**

As a first step, a simple data demanding CORINE model was used to assess erosion risks of two different geographical settings represented by the Claise and Nahr Ibrahim basins. Several pronounced differences between the two settings were observed as a result of a completely different natural setting and opposing land cover/management practices. A number of conclusions may be drawn from this study; these are listed under fundamental and contextual settings.


Contextually, and by comparing both study areas, several aspects can be pointed out. Despite differences in the geographical setting, the impact of adequate versus random land use planning can be first concluded. This statement is particularly justified in the Claise basin, where despite its challenging pedological settings in terms of weak structure and cover, low and moderate erosion risks are prevalent due to its natural setting that provides the basin a protective cover against erosion. Further, due to the presence of ponds in large numbers, an amplified counter-erosion effect is observed. Their role was solidified by fixing erosivity, erodibility and topographic factors of the model and inputting an alternative scenario with dredged ponds. By comparison with the current actual soil erosion risk map, not only a shift in local erosion risks was observed, but also a complete shift within the basin was shown, thus confining the low erosion state of the Claise to its natural and pond cover and further indicating the efficiency of projecting ponds as an effective counter-erosion measure in basins with high erosion risks such as the Nahr Ibrahim basin.

**77**

landscape.

**Acknowledgements**

**Conflict of interest**

The authors declare no conflict of interest.

*Evaluating Differences of Erosion Patterns in Natural and Anthropogenic Basins…*

upper section and moderate to low risks in its middle and lower parts.

When comparing the erosive setting of the Claise with Nahr Ibrahim, significant differences were observed namely in high erosion risk zones. This, in turn, is attributed to the climatic, topographic and vegetation cover factors of Nahr Ibrahim where increased climate-induced erosion combined with the very steep slope and anthropogenically induced erosion from alteration of the vegetation cover is prevalent. Under current conditions, the land occupation pattern of Nahr Ibrahim was shown to be unsustainable in terms of distribution above lands of different capabilities and distribution along high erosion risk areas. The most striking difference between the two basins is that the Nahr Ibrahim accounts for nearly double the number of land occupation classes in the Claise basin for an area less than its half. Further, the unequal repartition of land use/land cover classes in the Nahr Ibrahim basin caused a gradient of soil erosion risk patterns, consisting mainly of high erosion risks in its

Despite its (the Nahr Ibrahim basin's) pedological and topographic settings, when vegetation cover was optimized through the application of the LDN concept, erosion risks significantly shifted. This is attributed to its highly erosive state and to its land occupation and management pattern in contrast to the well-controlled Claise basin. Conversely, the use of LDN as a basis for land planning and the use of land planning for implementation of the LDN concept not only allowed sustainability restoration but also proved to be an effective counter-erosion tool given its effect on decreasing high erosion risks and increasing low and moderate ones. The coupling of the CORINE erosion model and LDN concept can play a role in decision-making regarding land use planning, thus highlighting the importance of their implementation at the scale of the Mediterranean landscape. However, a basin like Nahr Ibrahim cannot be converted into a setting similar to the Claise, but a balanced land use plan accounting for the trade-off between natural

resources and urban expansion may be the solution for restoring the Nahr Ibrahim

Finally, through a simple methodological approach, this work can be listed as a response to the European framework for the Thematic Strategy on Soil Protection, recommendations of the DCE for revealing the role of hydromorphological alternating structures on erosion patterns in basins and UNCCD's recommendations for implementation of the LDN concept. Despite the differences between the Thematic Strategy on Soil Protection, DCE and LDN concepts, the common effect of land occupation within these frameworks can be used as a platform to study the extent of anthropogenic influence at the basin scale in an attempt to promote sustainable

This research is part of a PhD thesis funded by the National Council of Scientific

Research-Lebanon (CNRS-L), Agence Universitaire de la Francophonie (AUF), Lebanon and the Lebanese University. It is also part of the Dynétangs project funded by the Centre-Val-de-Loire region. The Authors would like to extend their gratitude to the editors of the book and to the Brenne Regional Natural Park for their help in weather station maintenance, and to Dr. Ihab Jomaa of the Lebanese Agricultural Research Institute (LARI) for providing weather station data.

development and to integrate soil erosion into land planning.

*DOI: http://dx.doi.org/10.5772/intechopen.89088*

*Evaluating Differences of Erosion Patterns in Natural and Anthropogenic Basins… DOI: http://dx.doi.org/10.5772/intechopen.89088*

When comparing the erosive setting of the Claise with Nahr Ibrahim, significant differences were observed namely in high erosion risk zones. This, in turn, is attributed to the climatic, topographic and vegetation cover factors of Nahr Ibrahim where increased climate-induced erosion combined with the very steep slope and anthropogenically induced erosion from alteration of the vegetation cover is prevalent. Under current conditions, the land occupation pattern of Nahr Ibrahim was shown to be unsustainable in terms of distribution above lands of different capabilities and distribution along high erosion risk areas. The most striking difference between the two basins is that the Nahr Ibrahim accounts for nearly double the number of land occupation classes in the Claise basin for an area less than its half. Further, the unequal repartition of land use/land cover classes in the Nahr Ibrahim basin caused a gradient of soil erosion risk patterns, consisting mainly of high erosion risks in its upper section and moderate to low risks in its middle and lower parts.

Despite its (the Nahr Ibrahim basin's) pedological and topographic settings, when vegetation cover was optimized through the application of the LDN concept, erosion risks significantly shifted. This is attributed to its highly erosive state and to its land occupation and management pattern in contrast to the well-controlled Claise basin. Conversely, the use of LDN as a basis for land planning and the use of land planning for implementation of the LDN concept not only allowed sustainability restoration but also proved to be an effective counter-erosion tool given its effect on decreasing high erosion risks and increasing low and moderate ones. The coupling of the CORINE erosion model and LDN concept can play a role in decision-making regarding land use planning, thus highlighting the importance of their implementation at the scale of the Mediterranean landscape. However, a basin like Nahr Ibrahim cannot be converted into a setting similar to the Claise, but a balanced land use plan accounting for the trade-off between natural resources and urban expansion may be the solution for restoring the Nahr Ibrahim landscape.

Finally, through a simple methodological approach, this work can be listed as a response to the European framework for the Thematic Strategy on Soil Protection, recommendations of the DCE for revealing the role of hydromorphological alternating structures on erosion patterns in basins and UNCCD's recommendations for implementation of the LDN concept. Despite the differences between the Thematic Strategy on Soil Protection, DCE and LDN concepts, the common effect of land occupation within these frameworks can be used as a platform to study the extent of anthropogenic influence at the basin scale in an attempt to promote sustainable development and to integrate soil erosion into land planning.

### **Acknowledgements**

This research is part of a PhD thesis funded by the National Council of Scientific Research-Lebanon (CNRS-L), Agence Universitaire de la Francophonie (AUF), Lebanon and the Lebanese University. It is also part of the Dynétangs project funded by the Centre-Val-de-Loire region. The Authors would like to extend their gratitude to the editors of the book and to the Brenne Regional Natural Park for their help in weather station maintenance, and to Dr. Ihab Jomaa of the Lebanese Agricultural Research Institute (LARI) for providing weather station data.

#### **Conflict of interest**

The authors declare no conflict of interest.

*Soil Erosion - Rainfall Erosivity and Risk Assessment*

As a first step, a simple data demanding CORINE model was used to assess erosion risks of two different geographical settings represented by the Claise and Nahr Ibrahim basins. Several pronounced differences between the two settings were observed as a result of a completely different natural setting and opposing land cover/management practices. A number of conclusions may be drawn from this

1.Fundamentally, despite the abundance of several erosion models, given the data-scarcity of Nahr Ibrahim and for the purpose of comparison between the two study areas, the relatively simple data demanding CORINE model was used. As a first step, the CORINE erosion model proved to be a robust tool for evaluation of the spatial distribution of erosion risks despite its empirical nature where CORINE established maps have shown sufficient accuracy when

2.In addition to erosion assessment, the CORINE model serves as a proficient tool for land occupation and land management adequacy assessment given its vegetation cover input that reveals the actual erosion risk settings of basins under current conditions. This statement was justified by intersecting land use and land cover maps with the actual soil erosion risk map in Nahr Ibrahim revealing the extent of mismanagement as function of inadequate allocation. In addition, by highlighting zones of high risks, an insight towards prioritized treatment measures is obtained. Moreover, by revealing zones of different risk levels, the CORINE model provides insight for land use planning, thus promoting optimal land occupation allocation. Further, by changing the vegetation cover input as the human-controllable factor and stabilizing all other components, the CORINE model serves also as a tool for alternative scenario assessment by revealing changes of erosion patterns under different scenarios when compared with the current baseline conditions of the studied area, thus revealing the needed steps to

follow in terms of land planning or soil and water conservation measures.

promoting sustainable land use planning [64, 106, 107].

measure in basins with high erosion risks such as the Nahr Ibrahim basin.

3.In Mediterranean settings such as the Nahr Ibrahim basin, the CORINE model can provide a starting point for combatting land degradation, thus filling gaps of LDN application in the Mediterranean basin by contributing to land degradation mapping, integration of site-specific land degradation drivers and

Contextually, and by comparing both study areas, several aspects can be pointed out. Despite differences in the geographical setting, the impact of adequate versus random land use planning can be first concluded. This statement is particularly justified in the Claise basin, where despite its challenging pedological settings in terms of weak structure and cover, low and moderate erosion risks are prevalent due to its natural setting that provides the basin a protective cover against erosion. Further, due to the presence of ponds in large numbers, an amplified counter-erosion effect is observed. Their role was solidified by fixing erosivity, erodibility and topographic factors of the model and inputting an alternative scenario with dredged ponds. By comparison with the current actual soil erosion risk map, not only a shift in local erosion risks was observed, but also a complete shift within the basin was shown, thus confining the low erosion state of the Claise to its natural and pond cover and further indicating the efficiency of projecting ponds as an effective counter-erosion

study; these are listed under fundamental and contextual settings.

verified on field and crossed with ancillary maps.

**5. Conclusions**

**76**

## **Author details**

Mario J. Al Sayah1,2,3\*, Rachid Nedjai3 , Chadi Abdallah1 , Michel Khouri2 , Talal Darwish1 and François Pinet4

1 National Council for Scientific Research, Remote Sensing Center, Beirut, Lebanon

2 Centre de Recherches en Sciences et Ingénierie, Lebanese University Faculty of Engineering II, Roumieh, Lebanon

3 Centre d'Études et de Développement des Territoires et de l'Environnement, Université d'Orléans, Orléans, France

4 Brenne Regional Natural Park, Rosnay, France

\*Address all correspondence to: mario\_sayah94@hotmail.com

© 2019 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

**79**

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**Author details**

Talal Darwish1

Mario J. Al Sayah1,2,3\*, Rachid Nedjai3

Engineering II, Roumieh, Lebanon

Université d'Orléans, Orléans, France

provided the original work is properly cited.

4 Brenne Regional Natural Park, Rosnay, France

\*Address all correspondence to: mario\_sayah94@hotmail.com

and François Pinet4

, Chadi Abdallah1

1 National Council for Scientific Research, Remote Sensing Center, Beirut, Lebanon

2 Centre de Recherches en Sciences et Ingénierie, Lebanese University Faculty of

3 Centre d'Études et de Développement des Territoires et de l'Environnement,

© 2019 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium,

, Michel Khouri2

,

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[100] Zhang Z, Sheng L, Yang J, Chen XA, Kong L, Wagan B. Effects of land use and slope gradient on soil erosion in a red soil hilly watershed of southern China. Sustainability.

[101] Jinren RN, Yingkui KL. Approach to soil erosion assessment in terms of land-use structure changes. Journal of Soil and Water Conservation.

[102] Ismail T, Othman MA, Fadzil AB, Zainuddin ZM. Deposition of sediments in detention pond. Malaysian Journal of Civil Engineering. 2010;**22**(1):95-118

[103] Panagos P, Standardi G, Borrelli P, Lugato E, Montanarella L, Bosello F. Cost of agricultural productivity loss due to soil erosion in the European Union: From direct cost evaluation approaches to the use of macroeconomic models. Land Degradation and Development.

[104] Duan X, Shi X, Li Y, Li R, Fen D. A new method to calculate soil loss tolerance for sustainable soil productivity in farmland. Agronomy for Sustainable

[105] Dutta S. Soil erosion, sediment yield and sedimentation of reservoir: A review. Modeling Earth Systems and

[106] Chasek P, Safriel U, Shikongo S, Fuhrman VF. Operationalizing zero net land degradation: The next stage ininternational efforts to combat

Development. 2017;**37**(1):1-13

Environment. 2016;**2**(123):1-18

2012;**2012**:1-7

2015;**7**:14309-14325

2003;**58**(3):158-169

2018;**29**:471-484

[98] Gashaw T, Tulu T, Argaw M, Worqlul AW. Land capability

*Evaluating Differences of Erosion Patterns in Natural and Anthropogenic Basins… DOI: http://dx.doi.org/10.5772/intechopen.89088*

classification for planning land uses in the Geleda watershed, Blue Nile Basin, Ethiopia. Modeling Earth Systems and Environment. 2018;**4**(2):489-499

*Soil Erosion - Rainfall Erosivity and Risk Assessment*

and Management for Sustainable Development. Encyclopedia. Vol. III. Italy: Università di Torino; 2009. p. 27

[90] Wang D, Fu B, Zhao W, Hu H, Wang Y. Multifractal characteristics of soil particle size distribution under different land-use types on the Loess Plateau, China. Catena. 2008;**72**:29-36

[91] Fournier F. Climat et Erosion: La Relation Entre L'Erosion Du Sol Par L'Eau Et Les Précipitations Atmospheriques. Presses Universitaires De France, editor. Paris: Publication de l'Institut d'Études

[92] Gaussen H. Bioclimatic Map of Mediterranean Zone. Paris, France;

characteristics of representative Mediterranean plant species and their erosion-reducing potential during concentrated runoff. Plant and Soil.

Knapen A, Barberá GG, Navarro JA. Root

[94] MétéoFrance. Présentation générale

Roumaines; 1960. 201 p

[93] De Baets S, Poesen J,

du modèle de surface; 2016

[95] Darwish T, Jomaa I, Awad M, AbouDaher M, Msann J. Inventory and management of Lebanese soils integrating the soil geographical database

of Euro-Mediterranean countries. Lebanese Science Journal. 2005;**6**(2):15

[96] Darwish T, Fadel A. Mapping of soil organic carbon stock in the Arab countries to mitigate land degradation. Arabian Journal of Geosciences.

[97] Abou-Najem S, Palacios-Rodríguez G, Darwish T, Faour G, Kattar S, Clavero Rumbao I, et al. Land capability for agriculture, Hermel District, Lebanon.

Journal of Maps. 2019;**15**:1-10

[98] Gashaw T, Tulu T, Argaw M, Worqlul AW. Land capability

2007;**294**:169-183

2017;**10**(474):1-11

1963

Fleuve Ibrahim: Un Observatoire du Fonctionnement de la Zone Critique au Liban [Internet]. France: Université de Toulouse; France. 2016. Available from: https://oatao.univtoulouse. fr/15610/1/

[82] Darwish T, Khawlie M, Jomaa I, Abou Daher M, Awad M, Masri T, et al.

[83] Dubertret L. Cartes geologiques du

[84] Hreiche A, Najem W, Bocquillon C. Hydrological impact simulations of climate change on Lebanese coastal rivers. Hydrological Sciences Journal.

[85] Liu BY, Nearing M, Shi PJ, Jia ZW. Slope length effects on soil loss for steep slopes. Soil Science Society of America

[86] Gurebiyaw K, Addis HK, Teklay A. Assessment of spatial soil erosion susceptibility based on the CORINE model in the Gumara-Maksegnit watershed, Ethiopia. Journal of Natural Resources and Development.

[87] Yuksel A, Gundogan R, Akay AE. Using the remote sensing and GIS technology for erosion risk mapping of Kartalkaya dam watershed in Kahramanmaras, Turkey. Sensors.

[88] Tayebi M, Tayebi MH, Samenim A. Soil erosion risk assessment using GIS and CORINE model: A case study from western Shiraz, Iran. Archives of Agronomy and Soil Science.

Soil Map of Lebanon: 1:50 000. Monograph. Beirut, Lebanon: CNRS, Remote Sensing Center; 2006. 367 p

Liban à l'echelle 1 :50000; 1955

2007;**52**(6):1119-1133

2018;**8**:38-45

2008;**8**:4851-4865

2017;**63**(8):1163-1175

[89] Giordano A. The CORINE project on soil erosion risk and land quality. Land use, land cover and soil sciences. In: Systems Engineering

Journal. 2000;**64**:1759-1763

ASSAKER.pdf

**84**

[99] Ahmed SI, Rudra RP, Gharabaghi B, Mackenzie K, Dickinson WT. Withinstorm rainfall distribution effect on soil erosion rate. ISRN Soil Science. 2012;**2012**:1-7

[100] Zhang Z, Sheng L, Yang J, Chen XA, Kong L, Wagan B. Effects of land use and slope gradient on soil erosion in a red soil hilly watershed of southern China. Sustainability. 2015;**7**:14309-14325

[101] Jinren RN, Yingkui KL. Approach to soil erosion assessment in terms of land-use structure changes. Journal of Soil and Water Conservation. 2003;**58**(3):158-169

[102] Ismail T, Othman MA, Fadzil AB, Zainuddin ZM. Deposition of sediments in detention pond. Malaysian Journal of Civil Engineering. 2010;**22**(1):95-118

[103] Panagos P, Standardi G, Borrelli P, Lugato E, Montanarella L, Bosello F. Cost of agricultural productivity loss due to soil erosion in the European Union: From direct cost evaluation approaches to the use of macroeconomic models. Land Degradation and Development. 2018;**29**:471-484

[104] Duan X, Shi X, Li Y, Li R, Fen D. A new method to calculate soil loss tolerance for sustainable soil productivity in farmland. Agronomy for Sustainable Development. 2017;**37**(1):1-13

[105] Dutta S. Soil erosion, sediment yield and sedimentation of reservoir: A review. Modeling Earth Systems and Environment. 2016;**2**(123):1-18

[106] Chasek P, Safriel U, Shikongo S, Fuhrman VF. Operationalizing zero net land degradation: The next stage ininternational efforts to combat

desertification? Journal of Arid Environments. 2015;**112**(A):5-13

[107] Wunder S, Kaphengst T, Larsen AF. Implementing land degradation neutrality (SDG 15.3) at National Level: General approach, indicator selection and experiences from Germany. In: Ginzky H, Dooley E, Heuser IL, Kasimbazi E, Markus T, Qin T, editors. International Yearbook of Soil Law and Policy. Germany: Springer; 2017. pp. 191-219

**87**

**Chapter 5**

*Rabii El Gaatib*

of El Kansra dam (−3.03 million m3

requiring priority planning (hot spots).

age capacities of dams with 50 million m3

high density of rural population [2, 3].

risk management

**1. Introduction**

**Abstract**

Spatial Analysis of the Erosive

of Reservoir Siltation

Hazard of Soils and Natural Risks

The initial state of several watersheds, in West Africa, is characterized by a socio-ecological vulnerability linked to the water erosion risks. Thus, the Oued Beht watershed (430,728 ha), which is located in Morocco, reveals the extent of impact of soil erosion and water quality degradations. Especially, the consequences of soil loss alter its hydrological behavior in terms of efficiency to produce good water quality and include damages to the functional activities (agricultural and forestry) and structural challenges (lands and dams). This study suggests a methodology, reproducible and generalizable, to assess the water erosion risks. The results show that the erosion process is characterized by the combination of several types of erosion including sheet, rill, and gully. Therefore, the soil erosion is active and visible on more than 3/4 of the Oued Beht watershed, and the spatial analysis evaluates the soil loss which generates a decrease in the storage capacity

ated by combining susceptibility maps with an analysis of potential consequences. Moreover, the interactive mode obtained from this work is based on a statistical autocorrelation approach concerning risk factors in order to delimit the areas

The soil erosion characterizes the majority of Morocco reliefs, and a spectacular

expansion of erosion processes reveals more disturbing aspects. Thus, the soils degradation upstream is the origin of siltation phenomenon and decreasing stor-

imposes significant costs on the Moroccan economy by reducing soil productivity

In this sense, the results obtained in the first phase of this study have shown the importance of erosion in Oued Beht watershed revealing that combined forms are meaningful (sheet, rill, and gully) and many factors, both physical and human, promote erosion risk. Moreover, the human context is generally characterized by

**Keywords:** soil erosion, watershed, hot spots, spatial autocorrelation,

and the consequences are manifested by dam siltation downstream.

/year). The erosion risk management is evalu-

/year [1]. Particularly, the erosion hazard

## **Chapter 5**

## Spatial Analysis of the Erosive Hazard of Soils and Natural Risks of Reservoir Siltation

*Rabii El Gaatib and Abdelkader Larabi*

### **Abstract**

The initial state of several watersheds, in West Africa, is characterized by a socio-ecological vulnerability linked to the water erosion risks. Thus, the Oued Beht watershed (430,728 ha), which is located in Morocco, reveals the extent of impact of soil erosion and water quality degradations. Especially, the consequences of soil loss alter its hydrological behavior in terms of efficiency to produce good water quality and include damages to the functional activities (agricultural and forestry) and structural challenges (lands and dams). This study suggests a methodology, reproducible and generalizable, to assess the water erosion risks. The results show that the erosion process is characterized by the combination of several types of erosion including sheet, rill, and gully. Therefore, the soil erosion is active and visible on more than 3/4 of the Oued Beht watershed, and the spatial analysis evaluates the soil loss which generates a decrease in the storage capacity of El Kansra dam (−3.03 million m3 /year). The erosion risk management is evaluated by combining susceptibility maps with an analysis of potential consequences. Moreover, the interactive mode obtained from this work is based on a statistical autocorrelation approach concerning risk factors in order to delimit the areas requiring priority planning (hot spots).

**Keywords:** soil erosion, watershed, hot spots, spatial autocorrelation, risk management

### **1. Introduction**

The soil erosion characterizes the majority of Morocco reliefs, and a spectacular expansion of erosion processes reveals more disturbing aspects. Thus, the soils degradation upstream is the origin of siltation phenomenon and decreasing storage capacities of dams with 50 million m3 /year [1]. Particularly, the erosion hazard imposes significant costs on the Moroccan economy by reducing soil productivity and the consequences are manifested by dam siltation downstream.

In this sense, the results obtained in the first phase of this study have shown the importance of erosion in Oued Beht watershed revealing that combined forms are meaningful (sheet, rill, and gully) and many factors, both physical and human, promote erosion risk. Moreover, the human context is generally characterized by high density of rural population [2, 3].

In this perspective, this study provides a roadmap relating to biophysical, hydrological, and socio-economic backgrounds to develop a dynamic methodology that will identify and visualize development scenarios. The specific objectives that are identified include the following:


## **2. Study area**

The Oued Beht watershed is located upstream of El Kansra dam (85 km east from Rabat), which crosses the Central Highlands and the Middle Atlas of Morocco (**Figure 1**). The main stream is Oued Beht, affluent of Sebou river, one of the most important watersheds in the kingdom. Thus, the watershed overlaps the administrative territory erected into 5 provinces and 26 rural communes (**Figure 2**).

The delimitation of the watershed in the geographic information system (GIS) provides a total area of 430,728 ha with an elongated form (**Figure 2**). It owns a developed urban system, occupying a central place in socio-economic

**89**

and a dry summer [5].

**Figure 2.**

**3. Materials and methods**

Y1 = 282,142) and (X2 = 527,857, Y2 = 383,572).

*Distribution map of rural communes in the Oued Beht watershed.*

*Spatial Analysis of the Erosive Hazard of Soils and Natural Risks of Reservoir Siltation*

activities; it is Khemisset city (542,000 inhabitants), Azrou (47,540 inhabitants), and urban centers of Agourai and Ain Leuh [4]. Concerning climate context, the watershed presents characteristics of Mediterranean climate with a rainy winter

The coordinates of the map (longitude is x and latitude is y) are described in a map projection. Thus, the cartographic representation of the whole watershed surface on a two-dimensional map (X, Y) is based on the use of the Lambert conformal conic projection. Consequently, the Oued Beht watershed is located between the rectangle designated by the following Lambert coordinates: (X1 = 430,347,

The adopted methodological framework allows meeting the specific objectives of this study. Indeed, the guidelines of this strategic watershed management are based on critical analysis of the current situation and the definition of predictive interventions to revitalize natural ecosystems and to develop pastoral resources in

In this perspective, the spatial aggregate functions are used to identify priority areas by statistics combination of significant values in the GIS database obtained in

order to support the local population needs of forage and fuelwood.

*DOI: http://dx.doi.org/10.5772/intechopen.89748*

**Figure 1.** *Localization of the study area inside Morocco country.*

*Spatial Analysis of the Erosive Hazard of Soils and Natural Risks of Reservoir Siltation DOI: http://dx.doi.org/10.5772/intechopen.89748*

#### **Figure 2.** *Distribution map of rural communes in the Oued Beht watershed.*

activities; it is Khemisset city (542,000 inhabitants), Azrou (47,540 inhabitants), and urban centers of Agourai and Ain Leuh [4]. Concerning climate context, the watershed presents characteristics of Mediterranean climate with a rainy winter and a dry summer [5].

The coordinates of the map (longitude is x and latitude is y) are described in a map projection. Thus, the cartographic representation of the whole watershed surface on a two-dimensional map (X, Y) is based on the use of the Lambert conformal conic projection. Consequently, the Oued Beht watershed is located between the rectangle designated by the following Lambert coordinates: (X1 = 430,347, Y1 = 282,142) and (X2 = 527,857, Y2 = 383,572).

## **3. Materials and methods**

The adopted methodological framework allows meeting the specific objectives of this study. Indeed, the guidelines of this strategic watershed management are based on critical analysis of the current situation and the definition of predictive interventions to revitalize natural ecosystems and to develop pastoral resources in order to support the local population needs of forage and fuelwood.

In this perspective, the spatial aggregate functions are used to identify priority areas by statistics combination of significant values in the GIS database obtained in

*Soil Erosion - Rainfall Erosivity and Risk Assessment*

are identified include the following:

alities and constraints.

potential soil loss.

**2. Study area**

In this perspective, this study provides a roadmap relating to biophysical, hydrological, and socio-economic backgrounds to develop a dynamic methodology that will identify and visualize development scenarios. The specific objectives that

• Developing the spatial modeling of soil and water degradation processes with integration of empirical models in a GIS environment to determine the

sustainability of the main actions linked to erosion control.

order to mitigate negative effects of erosion hazard.

• Analyzing the biophysical context and highlighting the environmental potenti-

• Prescribing the strategic orientations of Master Plan Management to allow the

• Defining the action plan to be used in priority areas and identify the biological measures and appropriate soil conservation practices to be implemented in

The Oued Beht watershed is located upstream of El Kansra dam (85 km east from Rabat), which crosses the Central Highlands and the Middle Atlas of Morocco (**Figure 1**). The main stream is Oued Beht, affluent of Sebou river, one of the most important watersheds in the kingdom. Thus, the watershed overlaps the administrative territory erected into 5 provinces and 26 rural communes (**Figure 2**). The delimitation of the watershed in the geographic information system (GIS) provides a total area of 430,728 ha with an elongated form (**Figure 2**). It owns a developed urban system, occupying a central place in socio-economic

**88**

**Figure 1.**

*Localization of the study area inside Morocco country.*

previous work on this study linked to biophysical and hydrological environments. The hot spot analysis is used to calculate the Getis-Ord Gi\* statistics for each feature related to erosion hazard zoning from neighboring entities in spatial data set [6].

#### **3.1 Mapping of erosion susceptibility**

The input data preparation and spatial analysis of projected actions to control soil loss hazard are performed in the GIS environment (ArcGIS 9.3). Thus, the biophysical and hydrometeorological data assessment is based on empirical models to produce decisional maps of the priority areas to be developed.

#### *3.1.1 Biophysical and hydrometeorological data*

The data used for the soils susceptibility analysis are divided into five groups of explanatory variables (R, K, LS, C, and P). These are climatic, geomorphology, topography (gradient and length slopes), geological and geomorphological data, hydrographic parameters (river density, distance to streams), and soil occupation. Thus, thematic maps are produced by geoprocessing of information obtained.

The map of climatic aggressiveness is extrapolated from climatic data available in the stations characterized by long observation periods more than 20 years. Therefore, the topographic parameters (LS) are derived from the Digital Terrain Model DTM Aster, and planimetric and altimetric accuracies are, respectively, 30 and 20 m. The interpretation of the soil characteristics is used also to classify soils in the Wischmeier Abacus and to approach erodibility factor [7, 8]. Furthermore, the land cover map is extracted from SPOT satellite images (resolution is 20 m) combined with recent Landsat ETM+ imagery through the supervised classification method and field observations.

#### *3.1.2 Decisional maps*

Soils susceptibility assessment corresponds to the spatial occurrence of soil loss (number of representative pixels) that has taken place under the impact of local environmental conditions. Thus, the analytical approach adopted is based on simulation models integrated with GIS tools in order to evaluate the behavior of the dependent variable (land loss location) from a spatial combination of predictive variables in homogeneous geomorphic units (pixels). The soils susceptibility is simulated by the Universal Soil Loss model [9, 10], considered the most robust approach for spatial assessment of the soil erosion hazard (A). Moreover, the basic hypothesis is that the potential soil loss will be triggered under the same conditions as in the past.

$$\mathbf{A} = \mathbf{R} \times \mathbf{K} \times \mathbf{L} \mathbf{S} \times \mathbf{C} \times \mathbf{P} \tag{1}$$

**91**

*Spatial Analysis of the Erosive Hazard of Soils and Natural Risks of Reservoir Siltation*

of passive and active flood protection provide rational protection for people and property within watersheds. Consequently, the refinement of probabilistic and

The flood analysis is based on the dependence applied in the Francou-Rodier model [11] and on the distribution function characteristic of the extreme values. This approach is the most widely used in Morocco, as a regional empirical formula that has the advantage of making the flow value, with the defined exceedance prob-

The possibility to estimate the biggest possible flood that could appear during the extreme conditions is the significant element of the estimation of the potential hazard. Therefore, the Gradex model determines the flood flow characteristics and the regional parameter (kt) in a gauged station located in the Oued Beht watershed [12]. Subsequently, the data obtained are extrapolated to the other sub-catchments by Francou-Rodier method, based on the regional coefficient (kt) calculated in the

Below, the two significant formulas, which enable the estimation of the form of

where Q(t) is the maximum flow value in the ungauged sub-catchment (m3

the parameter of Francou-Rodier, which is a regional parameter in the right of the

Therefore, the first step consists in calculating the Francou-Rodier parameter (kt), by using the flow QA for a determined return period, in the Ouljet Soltane gauged basin, whose area is SA. Considering the data available on the gauged basin,

> 1 − ln \_ QA 10<sup>6</sup> \_

The final map is the result of geoprocessing by spatial crossing of information linked to soils degradation by natural erosion and flood power to contribute to El Kansra dam siltation. As a result, the production of this qualitative map is used to provide a systematic vision to identify priority areas with homogeneous environmental characteristics and to study the alternatives of development upstream/downstream.

The methodological protocol used to characterize the socio-economic aspect is based on survey data [2, 3]. Thus, the analysis of mechanisms essentially linked to lifestyle needs and household income is used to better understand the socioeconomic vulnerability in the watershed. The aim is to prepare a reference situation

The surveys are conducted in homogeneous areas using some direct conversations with groups surveyed (focus-group), with a freedom to structure the interview to better understand the population profile, their real needs, and to identify constraints that limit wealth production (natural, financial and commercial

ln \_ SA 10<sup>8</sup> 

).

), Q0: 106

m3

/s, S0: 108

] (3)

/s) and SA is the area

km2

(2)

/s),

, and kt is

\_ Q(t) Q0 = ( \_S S0 ) 1−\_ kt 10

kt <sup>=</sup> <sup>10</sup> <sup>×</sup>[

where QA is the flood flow in the gauged sub-catchment (m3

*DOI: http://dx.doi.org/10.5772/intechopen.89748*

technical methods is totally justified.

ability, dependent on the basin area function.

gauged station called Ouljet Soltane [11].

the maximum flows envelopes, are described:

S is the area of ungauged sub-catchment (km2

gauged station (called Ouljet Soltane station).

the flow QA is calculated by the Gradex method.

of the gauged sub-catchment of Ouljet Soltane (km2

for the future socio-economic or environmental project.

**3.2 Socio-economic analysis**

where A is the mean annual soil loss (t ha<sup>−</sup><sup>1</sup> year<sup>−</sup><sup>1</sup> ), R is the rainfall erosivity factor (MJ.mm.ha<sup>−</sup><sup>1</sup> .h<sup>−</sup><sup>1</sup> .year<sup>−</sup><sup>1</sup> ), K is soil erodibility factor (t.h.MJ<sup>−</sup><sup>1</sup> .mm<sup>−</sup><sup>1</sup> ), L and S are the slope-length and the slope-steepness factors (dimensionless), C is the cover and management factor (dimensionless), and P is the support practice factor (dimensionless).

Second, hydrometeorological study is used for flood sites. The flood hazard is one of the most destructive natural hazards of the environment that can cause severe social as well as economic losses. In majority situations, the modern methods *Spatial Analysis of the Erosive Hazard of Soils and Natural Risks of Reservoir Siltation DOI: http://dx.doi.org/10.5772/intechopen.89748*

of passive and active flood protection provide rational protection for people and property within watersheds. Consequently, the refinement of probabilistic and technical methods is totally justified.

The flood analysis is based on the dependence applied in the Francou-Rodier model [11] and on the distribution function characteristic of the extreme values. This approach is the most widely used in Morocco, as a regional empirical formula that has the advantage of making the flow value, with the defined exceedance probability, dependent on the basin area function.

The possibility to estimate the biggest possible flood that could appear during the extreme conditions is the significant element of the estimation of the potential hazard. Therefore, the Gradex model determines the flood flow characteristics and the regional parameter (kt) in a gauged station located in the Oued Beht watershed [12]. Subsequently, the data obtained are extrapolated to the other sub-catchments by Francou-Rodier method, based on the regional coefficient (kt) calculated in the gauged station called Ouljet Soltane [11].

Below, the two significant formulas, which enable the estimation of the form of the maximum flows envelopes, are described:

$$\frac{\mathbf{described:}}{\mathbf{Q}\_0} = \left(\frac{\mathbf{S}}{\mathbf{S}\_0}\right)^{1-\frac{\mathbf{k}\_c}{10}}\tag{2}$$

where Q(t) is the maximum flow value in the ungauged sub-catchment (m3 /s), S is the area of ungauged sub-catchment (km2 ), Q0: 106 m3 /s, S0: 108 km2 , and kt is the parameter of Francou-Rodier, which is a regional parameter in the right of the gauged station (called Ouljet Soltane station).

Therefore, the first step consists in calculating the Francou-Rodier parameter (kt), by using the flow QA for a determined return period, in the Ouljet Soltane gauged basin, whose area is SA. Considering the data available on the gauged basin, the flow QA is calculated by the Gradex method.

$$\mathbf{k}\_{\mathbf{t}} = \mathbf{10} \times \left[ \mathbf{1} - \frac{\ln \frac{\mathbf{Q}\_{\mathbf{A}}}{\mathbf{10}^6}}{\ln \frac{\mathbf{S}\_{\mathbf{A}}}{\mathbf{10}^6}} \right] \tag{3}$$

where QA is the flood flow in the gauged sub-catchment (m3 /s) and SA is the area of the gauged sub-catchment of Ouljet Soltane (km2 ).

The final map is the result of geoprocessing by spatial crossing of information linked to soils degradation by natural erosion and flood power to contribute to El Kansra dam siltation. As a result, the production of this qualitative map is used to provide a systematic vision to identify priority areas with homogeneous environmental characteristics and to study the alternatives of development upstream/downstream.

#### **3.2 Socio-economic analysis**

The methodological protocol used to characterize the socio-economic aspect is based on survey data [2, 3]. Thus, the analysis of mechanisms essentially linked to lifestyle needs and household income is used to better understand the socioeconomic vulnerability in the watershed. The aim is to prepare a reference situation for the future socio-economic or environmental project.

The surveys are conducted in homogeneous areas using some direct conversations with groups surveyed (focus-group), with a freedom to structure the interview to better understand the population profile, their real needs, and to identify constraints that limit wealth production (natural, financial and commercial

*Soil Erosion - Rainfall Erosivity and Risk Assessment*

**3.1 Mapping of erosion susceptibility**

*3.1.1 Biophysical and hydrometeorological data*

method and field observations.

where A is the mean annual soil loss (t ha<sup>−</sup><sup>1</sup>

.year<sup>−</sup><sup>1</sup>

.h<sup>−</sup><sup>1</sup>

*3.1.2 Decisional maps*

as in the past.

factor (MJ.mm.ha<sup>−</sup><sup>1</sup>

(dimensionless).

obtained.

previous work on this study linked to biophysical and hydrological environments. The hot spot analysis is used to calculate the Getis-Ord Gi\* statistics for each feature related to erosion hazard zoning from neighboring entities in spatial data set [6].

The input data preparation and spatial analysis of projected actions to control soil loss hazard are performed in the GIS environment (ArcGIS 9.3). Thus, the biophysical and hydrometeorological data assessment is based on empirical models

The data used for the soils susceptibility analysis are divided into five groups of explanatory variables (R, K, LS, C, and P). These are climatic, geomorphology, topography (gradient and length slopes), geological and geomorphological data, hydrographic parameters (river density, distance to streams), and soil occupation. Thus, thematic maps are produced by geoprocessing of information

The map of climatic aggressiveness is extrapolated from climatic data available in the stations characterized by long observation periods more than 20 years. Therefore, the topographic parameters (LS) are derived from the Digital Terrain Model DTM Aster, and planimetric and altimetric accuracies are, respectively, 30 and 20 m. The interpretation of the soil characteristics is used also to classify soils in the Wischmeier Abacus and to approach erodibility factor [7, 8]. Furthermore, the land cover map is extracted from SPOT satellite images (resolution is 20 m) combined with recent Landsat ETM+ imagery through the supervised classification

Soils susceptibility assessment corresponds to the spatial occurrence of soil loss (number of representative pixels) that has taken place under the impact of local environmental conditions. Thus, the analytical approach adopted is based on simulation models integrated with GIS tools in order to evaluate the behavior of the dependent variable (land loss location) from a spatial combination of predictive variables in homogeneous geomorphic units (pixels). The soils susceptibility is simulated by the Universal Soil Loss model [9, 10], considered the most robust approach for spatial assessment of the soil erosion hazard (A). Moreover, the basic hypothesis is that the potential soil loss will be triggered under the same conditions

A = R × K × LS × C × P (1)

), R is the rainfall erosivity

.mm<sup>−</sup><sup>1</sup>

), L and

year<sup>−</sup><sup>1</sup>

), K is soil erodibility factor (t.h.MJ<sup>−</sup><sup>1</sup>

S are the slope-length and the slope-steepness factors (dimensionless), C is the cover and management factor (dimensionless), and P is the support practice factor

Second, hydrometeorological study is used for flood sites. The flood hazard is one of the most destructive natural hazards of the environment that can cause severe social as well as economic losses. In majority situations, the modern methods

to produce decisional maps of the priority areas to be developed.

**90**

constraints, land structures, and incomes). Moreover, spatial distribution of the farms (units to investigate) is selected using a stratified sampling plan with 5% error and 95% confidence level. The randomness of the villages (sampling units) is made from the list available in the general agricultural census [13]. Based on the number of households in the watershed studied (19,987 farmers), the number of farmers to be interviewed is 378 in 50 villages.

Consequently, in order to reduce the heterogeneity linked to utilized agricultural land (UAL), which represents a discriminatory factor for management techniques and income sources, the stratification is performed according to farm size, and three classes are selected (UAL < 5 ha, 5 ha < UAL < 15 ha, and UAL > 15 ha).

#### **3.3 Potential consequences**

The potential consequences are evaluated by an analytical approach based on the identification of the exposed elements and the assessment of their vulnerabilities. In this approach, the potential damages are not expressed in numerical values but in hierarchical classes (qualitative assessment). The consequence typology differs: (1) direct structural damages (CS) affecting the land goods and the El Kansra dam and (2) direct functional damages (CF) related to disruption of agricultural activities with local and immediate consequences.

The consequence assessment is a fundamental part of erosion risk analysis. Thus, the various components of the vulnerability are structured according to a decreasing exponential function. Moreover, the vulnerability analysis is based on the observation protocol of damage, original and reproducible, applicable to the soil loss analysis due to past erosion events. The erosion cost is defined by the difference between the initial net revenue per hectare and the net revenue with the effect of erosion:

$$\mathbf{R\_t = R\_0 e^{-\mathbf{x}\mathbf{p}\cdot(t)}}\tag{4}$$

**93**

follows:

**Figure 3.**

siltation.

*3.5.1 Strategic planning*

*Spatial Analysis of the Erosive Hazard of Soils and Natural Risks of Reservoir Siltation*

Using the analysis of the existing opportunities in Oued Beht watershed, the present master plan is based on an action program focused on erosion control. Indeed, the identification of the package of management actions is based on the diagnosis results of biophysical and socio-economic backgrounds. Thus, the management approach of priority areas is based on operational actions (biological and technical treatments) that are compatible with the intrinsic characteristics of the watershed studied. In this sense, the objectives that promote the action plan are as

*The methodological flowchart to identify priority areas and evaluate soil erosion risk.*

• Bioengineering techniques for soil erosion protection and slope stabilization to conserve natural resources upstream and to protect El Kansra dam against

• Reconstruction of degraded ecosystems to promote biodiversity conservation.

The long-term planning is used to establish the framework and key elements of Oued Beht watershed and to reflect a clear vision created in an open process. Guidelines for the many departments which will draw up specific plans will be

*DOI: http://dx.doi.org/10.5772/intechopen.89748*

**3.5 Watershed management plan**

where Rt is the yield in the year t (t/ha), R0 is the initial yield (t/ha), x is the damage coefficient (yield loss parameter), and p(t) is the cumulative land loss in the year t (t/ha).

The vulnerability input is based on the results of socio-economic surveys describing the current yields (or revenue) and the latest census data available in the Office of the High Commissioner for Planning (HCP), the government agency in charge of producing statistics [3, 14–16]. Thus, the damage process typology helps to prioritize the consequences classes: low (C1), moderate (C2), high (C3), and very high (C4).

#### **3.4 Erosion risk assessment**

On the technical side, the terms "risk" and "hazard" are linked to each other but should be clearly distinguished. The risk mainly signifies a probability of the occurrence of (negative) impacts and expected losses resulting from a given hazard to a given element at danger or peril, over a specified time period.

Therefore, the purpose is to hierarchy the erosion menace that compromises land goods, human activities, and property of people. Thus, the analysis of the soil degradation levels obtained allows to prioritize the susceptibility classes: low (S1), moderate (S2), high (S3), and very high (S4).

In addition, the spatial combination of susceptibility (S1 < S2 < S3 < S4) and potential consequence (C1 < C2 < C3 < C4) are translated into risk classes using a correlation matrix of double entries [17]. Consequently, the erosion risk classes are prioritized in order to guide planning decisions (**Figure 3**): low (R1), moderate (R2), and strong (R3). *Spatial Analysis of the Erosive Hazard of Soils and Natural Risks of Reservoir Siltation DOI: http://dx.doi.org/10.5772/intechopen.89748*

**Figure 3.** *The methodological flowchart to identify priority areas and evaluate soil erosion risk.*

## **3.5 Watershed management plan**

Using the analysis of the existing opportunities in Oued Beht watershed, the present master plan is based on an action program focused on erosion control. Indeed, the identification of the package of management actions is based on the diagnosis results of biophysical and socio-economic backgrounds. Thus, the management approach of priority areas is based on operational actions (biological and technical treatments) that are compatible with the intrinsic characteristics of the watershed studied. In this sense, the objectives that promote the action plan are as follows:


## *3.5.1 Strategic planning*

The long-term planning is used to establish the framework and key elements of Oued Beht watershed and to reflect a clear vision created in an open process. Guidelines for the many departments which will draw up specific plans will be

*Soil Erosion - Rainfall Erosivity and Risk Assessment*

farmers to be interviewed is 378 in 50 villages.

**3.3 Potential consequences**

the year t (t/ha).

**3.4 Erosion risk assessment**

with local and immediate consequences.

constraints, land structures, and incomes). Moreover, spatial distribution of the farms (units to investigate) is selected using a stratified sampling plan with 5% error and 95% confidence level. The randomness of the villages (sampling units) is made from the list available in the general agricultural census [13]. Based on the number of households in the watershed studied (19,987 farmers), the number of

Consequently, in order to reduce the heterogeneity linked to utilized agricultural land (UAL), which represents a discriminatory factor for management techniques and income sources, the stratification is performed according to farm size, and three classes are selected (UAL < 5 ha, 5 ha < UAL < 15 ha, and UAL > 15 ha).

The potential consequences are evaluated by an analytical approach based on the identification of the exposed elements and the assessment of their vulnerabilities. In this approach, the potential damages are not expressed in numerical values but in hierarchical classes (qualitative assessment). The consequence typology differs: (1) direct structural damages (CS) affecting the land goods and the El Kansra dam and (2) direct functional damages (CF) related to disruption of agricultural activities

The consequence assessment is a fundamental part of erosion risk analysis. Thus, the various components of the vulnerability are structured according to a decreasing exponential function. Moreover, the vulnerability analysis is based on the observation protocol of damage, original and reproducible, applicable to the soil loss analysis due to past erosion events. The erosion cost is defined by the difference between the initial net revenue per hectare and the net revenue with the effect of erosion:

where Rt is the yield in the year t (t/ha), R0 is the initial yield (t/ha), x is the damage coefficient (yield loss parameter), and p(t) is the cumulative land loss in

On the technical side, the terms "risk" and "hazard" are linked to each other but should be clearly distinguished. The risk mainly signifies a probability of the occurrence of (negative) impacts and expected losses resulting from a given hazard

Therefore, the purpose is to hierarchy the erosion menace that compromises land goods, human activities, and property of people. Thus, the analysis of the soil degradation levels obtained allows to prioritize the susceptibility classes: low (S1),

In addition, the spatial combination of susceptibility (S1 < S2 < S3 < S4) and potential consequence (C1 < C2 < C3 < C4) are translated into risk classes using a correlation matrix of double entries [17]. Consequently, the erosion risk classes are prioritized in order to guide planning decisions (**Figure 3**): low (R1), moderate (R2), and strong (R3).

to a given element at danger or peril, over a specified time period.

moderate (S2), high (S3), and very high (S4).

The vulnerability input is based on the results of socio-economic surveys describing the current yields (or revenue) and the latest census data available in the Office of the High Commissioner for Planning (HCP), the government agency in charge of producing statistics [3, 14–16]. Thus, the damage process typology helps to prioritize the consequences classes: low (C1), moderate (C2), high (C3), and very high (C4).

Rt = R0 e−xp(t) (4)

**92**

established. Thus, the key elements are reviewed for potential effects with uniform land uses (agricultural, rangelands, and forest).

The interventions program includes the conservation actions and environmental rehabilitation. The measures selected are grouped into the following categories: agricultural land use, rangelands management, forest management, river system protection, and ravines treatment.

#### *3.5.2 Priority planning*

The Hot Spot Analysis tool calculates the Getis-Ord Gi\* statistic for each feature in a spatial data. The resultant "z-score" (standard deviation) tells us where features with either high or low values cluster spatially. This tool works by looking at each feature within the context of neighboring features. A feature with a high value is interesting, but may not be a statistically significant hot spot. Thus, to be a statistically significant hot spot, a feature will have a high value and be surrounded by other features with high values as well. The local sum for a feature and its neighbors is compared proportionally to the sum of all features; when the local sum is much different than the expected local sum, and that difference is too large to be the result of random chance, a statistically significant "z-score" results.

The Gi\* statistic returned for each feature in the dataset is a "z-score." For statistically significant positive "z-score," the larger the "z-score" is, the more intense the clustering of high values (hot spot); and for statistically significant negative "z-score," the smaller the "z-score" is, the more intense the clustering of low values (cold spot).

In this study, the use of the statistical method "Getis-Ord Gi\*" allows the analysis of each entity (pixel) in relation with neighborhood in the spatial dataset [6]. The nearest neighbor analysis is based on comparing the distribution of the distances from each data point to its nearest neighbor in a given dataset with a randomly distributed dataset.

Indeed, this statistical approach tells us if we may reject or not the null hypothesis CSR (complete spatial randomness) that expresses the absence of spatial correlation between the following events: 1) significant soil loss and degraded vegetation cover and (2) soil erosion and steep slopes. Thus, the results, expressed in "z-score" (standard deviation) and "p-value" (independence probability), are used to measure the statistical significance of spatial autocorrelation (**Figure 4**).

**95**

**Figure 5.** *Hypsometric map.*

*Spatial Analysis of the Erosive Hazard of Soils and Natural Risks of Reservoir Siltation*

hazard and topographic factors that will be modified by the action plan.

The topography of the Oued Beht watershed is the result of factors with a combination involving topographic effect of altitudinal amplitudes, exposure, slope

has a regularly altitudinal distribution along its elongated form. Thus, altitudes classes obtained follow a decreasing gradient, from upstream to downstream, in perpendicular bands to the axis, which coincides with the flow direction of Oued

The spatial analysis of the digital terrain model (DTM) shows that the watershed

Furthermore, for confidence level 90%, if the z-score obtained is between −1.65 and +1.65, the probability of independence (p-value) will be automatically higher than 0.10 and the null hypothesis of independence is not rejected [18]. Thus, the biological actions are programmed in areas with strong spatial autocorrelation (hot spot) between erosion hazard and vegetation cover; and technical measures correspond specially to areas with high spatial autocorrelation between the natural

*DOI: http://dx.doi.org/10.5772/intechopen.89748*

**4. Results and discussion**

*4.1.1 Topographic context*

gradient, and slope length.

*4.1.1.1 Hypsometric analysis*

Beht (**Figure 5**).

**4.1 Biophysical factors analysis**

**Figure 4.** *Distribution of spatial autocorrelation indicators (adapted from [18]).*

*Spatial Analysis of the Erosive Hazard of Soils and Natural Risks of Reservoir Siltation DOI: http://dx.doi.org/10.5772/intechopen.89748*

Furthermore, for confidence level 90%, if the z-score obtained is between −1.65 and +1.65, the probability of independence (p-value) will be automatically higher than 0.10 and the null hypothesis of independence is not rejected [18]. Thus, the biological actions are programmed in areas with strong spatial autocorrelation (hot spot) between erosion hazard and vegetation cover; and technical measures correspond specially to areas with high spatial autocorrelation between the natural hazard and topographic factors that will be modified by the action plan.

## **4. Results and discussion**

#### **4.1 Biophysical factors analysis**

#### *4.1.1 Topographic context*

*Soil Erosion - Rainfall Erosivity and Risk Assessment*

land uses (agricultural, rangelands, and forest).

protection, and ravines treatment.

randomly distributed dataset.

*3.5.2 Priority planning*

established. Thus, the key elements are reviewed for potential effects with uniform

rehabilitation. The measures selected are grouped into the following categories: agricultural land use, rangelands management, forest management, river system

result of random chance, a statistically significant "z-score" results.

The interventions program includes the conservation actions and environmental

The Hot Spot Analysis tool calculates the Getis-Ord Gi\* statistic for each feature in a spatial data. The resultant "z-score" (standard deviation) tells us where features with either high or low values cluster spatially. This tool works by looking at each feature within the context of neighboring features. A feature with a high value is interesting, but may not be a statistically significant hot spot. Thus, to be a statistically significant hot spot, a feature will have a high value and be surrounded by other features with high values as well. The local sum for a feature and its neighbors is compared proportionally to the sum of all features; when the local sum is much different than the expected local sum, and that difference is too large to be the

The Gi\* statistic returned for each feature in the dataset is a "z-score." For statistically significant positive "z-score," the larger the "z-score" is, the more intense the clustering of high values (hot spot); and for statistically significant negative "z-score," the smaller the "z-score" is, the more intense the clustering of low values (cold spot). In this study, the use of the statistical method "Getis-Ord Gi\*" allows the analysis of each entity (pixel) in relation with neighborhood in the spatial dataset [6]. The nearest neighbor analysis is based on comparing the distribution of the distances from each data point to its nearest neighbor in a given dataset with a

Indeed, this statistical approach tells us if we may reject or not the null hypoth-

esis CSR (complete spatial randomness) that expresses the absence of spatial correlation between the following events: 1) significant soil loss and degraded vegetation cover and (2) soil erosion and steep slopes. Thus, the results, expressed in "z-score" (standard deviation) and "p-value" (independence probability), are used to measure the statistical significance of spatial autocorrelation (**Figure 4**).

**94**

**Figure 4.**

*Distribution of spatial autocorrelation indicators (adapted from [18]).*

The topography of the Oued Beht watershed is the result of factors with a combination involving topographic effect of altitudinal amplitudes, exposure, slope gradient, and slope length.

#### *4.1.1.1 Hypsometric analysis*

The spatial analysis of the digital terrain model (DTM) shows that the watershed has a regularly altitudinal distribution along its elongated form. Thus, altitudes classes obtained follow a decreasing gradient, from upstream to downstream, in perpendicular bands to the axis, which coincides with the flow direction of Oued Beht (**Figure 5**).

**Figure 5.** *Hypsometric map.*

**Figure 6.** *Aspect map.*

The watershed presents a high altitudinal range, between the highest point 2121 m and the lowest point 108 m, which coincides with the level of the El Kansra dam. Thus, the total length midline crossing the watershed is 177 km, and the altitude difference of 2013 m represents a real hydrologic indicator that promotes erosive process.

### *4.1.1.2 Soil aspects*

The aspect map is used to establish the slope exposure of the watershed and to give an idea about the relief forms and the cover land. The distribution of soil aspects shows that east facing slopes dominate, particularly at upstream part of Oued Beht watershed (38%). However, the other exposures are equal, almost 20%, while specifying that the investigations show that the north and west slopes present a humid character. Furthermore, the areas representing a flat field (with 0% of slope) are limited and localized mainly in the small depressions or hilltops (**Figure 6**).

## *4.1.1.3 Slope gradient analysis*

The DTM spatial analysis shows that the low slopes (less than 15%) are dispersed and occupy more than half of the watershed (57%). Thus, steep slopes are concentrated in central and upstream areas. The map of the slope length classes gives an indication of the transport distance traveled by soil particles detached. The slope lengths distribution shows that almost half of the watershed (55%) is less than 1000 m with a majority (30%) lower than 500 m (**Figure 7**).

In this sense, the digital terrain model (DTM) is the main source of data for the extraction of many parameters used such as slope lengths, direction of flow of

**97**

**Figure 8.** *Slope length map.*

**Figure 7.**

*Slope gradient map of the study area.*

*Spatial Analysis of the Erosive Hazard of Soils and Natural Risks of Reservoir Siltation*

*DOI: http://dx.doi.org/10.5772/intechopen.89748*

*Spatial Analysis of the Erosive Hazard of Soils and Natural Risks of Reservoir Siltation DOI: http://dx.doi.org/10.5772/intechopen.89748*

#### **Figure 7.** *Slope gradient map of the study area.*

*Soil Erosion - Rainfall Erosivity and Risk Assessment*

The watershed presents a high altitudinal range, between the highest point 2121 m and the lowest point 108 m, which coincides with the level of the El Kansra dam. Thus, the total length midline crossing the watershed is 177 km, and the altitude difference of 2013 m represents a real hydrologic indicator that promotes

The aspect map is used to establish the slope exposure of the watershed and to give an idea about the relief forms and the cover land. The distribution of soil aspects shows that east facing slopes dominate, particularly at upstream part of Oued Beht watershed (38%). However, the other exposures are equal, almost 20%, while specifying that the investigations show that the north and west slopes present a humid character. Furthermore, the areas representing a flat field (with 0% of slope) are limited and localized mainly in the small depressions or

The DTM spatial analysis shows that the low slopes (less than 15%) are dispersed and occupy more than half of the watershed (57%). Thus, steep slopes are concentrated in central and upstream areas. The map of the slope length classes gives an indication of the transport distance traveled by soil particles detached. The slope lengths distribution shows that almost half of the watershed (55%) is less than 1000 m with a majority (30%) lower than 500 m

In this sense, the digital terrain model (DTM) is the main source of data for the extraction of many parameters used such as slope lengths, direction of flow of

**96**

(**Figure 7**).

erosive process.

**Figure 6.** *Aspect map.*

*4.1.1.2 Soil aspects*

hilltops (**Figure 6**).

*4.1.1.3 Slope gradient analysis*

**Figure 8.** *Slope length map.*

water, topographic index, etc. The spatial distribution of the slope length classes is heterogeneous, and no zone is characterized by a single slope length class (**Figure 8**). Also, their importance decreases to a minimum corresponding to the class exceeding 5000 m with only 1%.

In conclusion, the topographic factor analysis reveals the combination of slope length effects with slope gradient characterizing Oued Beht watershed.

#### *4.1.2 Soil resources*

The soil analysis in Oued Beht watershed shows a strong dominance (45%) of slightly developed soils (PE). This soil type is dispersed and used not only for agriculture and forestry but also in rangelands. Moreover, Brown soils (B) and Forest Brown (BF) soils are concentrated at the upstream where the forests are developed (6%). Thus, this kind of soil is enriched by the litter decomposition (**Figure 9**). Specially, the poor soils, characterized by the bedrock outcrop, are located near El Kansra dam and at the extreme south of watershed (upstream).

In conclusion, the watershed soils analysis shows the diversity and heterogeneity of pedogenesis factors. Thus, this diversification of soils is mainly due to bedrock types and their degree of friability, morphology, topography, climate aggression, and land use (**Figure 10**).

#### *4.1.3 Hydrometeorological analysis*

The geographical distribution of climate stations selected presents good spatial coverage and long periods of observation that allow an eminent climate analysis in Oued Beht watershed. The weather stations used to characterize the thermal regime and deduct bioclimatic classes are the stations of El Kansra, Khemisset, and Ifrane (**Figure 11**). In this way, the continentality is quite significant with a neat decrease

**99**

**Figure 11.**

*Distribution of climate stations.*

**Figure 10.**

*Soil erodibility distribution.*

*Spatial Analysis of the Erosive Hazard of Soils and Natural Risks of Reservoir Siltation*

*DOI: http://dx.doi.org/10.5772/intechopen.89748*

*Spatial Analysis of the Erosive Hazard of Soils and Natural Risks of Reservoir Siltation DOI: http://dx.doi.org/10.5772/intechopen.89748*

**Figure 10.** *Soil erodibility distribution.*

*Soil Erosion - Rainfall Erosivity and Risk Assessment*

water, topographic index, etc. The spatial distribution of the slope length classes is heterogeneous, and no zone is characterized by a single slope length class (**Figure 8**). Also, their importance decreases to a minimum corresponding to the class exceeding

In conclusion, the topographic factor analysis reveals the combination of slope

The soil analysis in Oued Beht watershed shows a strong dominance (45%) of slightly developed soils (PE). This soil type is dispersed and used not only for agriculture and forestry but also in rangelands. Moreover, Brown soils (B) and Forest Brown (BF) soils are concentrated at the upstream where the forests are developed (6%). Thus, this kind of soil is enriched by the litter decomposition (**Figure 9**). Specially, the poor soils, characterized by the bedrock outcrop, are located near El

In conclusion, the watershed soils analysis shows the diversity and heterogeneity of pedogenesis factors. Thus, this diversification of soils is mainly due to bedrock types and their degree of friability, morphology, topography, climate aggression,

The geographical distribution of climate stations selected presents good spatial coverage and long periods of observation that allow an eminent climate analysis in Oued Beht watershed. The weather stations used to characterize the thermal regime and deduct bioclimatic classes are the stations of El Kansra, Khemisset, and Ifrane (**Figure 11**). In this way, the continentality is quite significant with a neat decrease

length effects with slope gradient characterizing Oued Beht watershed.

Kansra dam and at the extreme south of watershed (upstream).

**98**

5000 m with only 1%.

**Figure 9.** *Soils map.*

*4.1.2 Soil resources*

and land use (**Figure 10**).

*4.1.3 Hydrometeorological analysis*

**Figure 11.** *Distribution of climate stations.*

**Figure 12.**

*Distribution of average monthly rainfall data by station.*

in temperature associated with increasing altitude. Moreover, the thermal regime is characterized by average temperatures that vary between 10°C in the east and 26°C in the north and north-west. Thus, the studied watershed is influenced by altitude and latitude factors.

On the other hand, the rainfall regime is irregular and the rainy period is concentrated between October and May (**Figure 12**). As a result, the precipitation distribution analysis shows that the watershed has a rainy winter and a dry summer period. Therefore, the upland areas (mountains) are wetter than the areas that are close to the sea. Thus, the altitude effect on rainfall (R-factor) is more dominant than the approximation of the sea.

#### *4.1.3.1 Bioclimatic synthesis*

Bioclimatic data analysis is based on quotient Emberger index (Q2). This quotient, especially adapted to the Mediterranean regions, is based on the annual rainfall, the average maximum temperatures of the warmest month (M °C), and the average minimum temperatures of the coldest month (m °C) [19]. Thus, Oued Beht watershed is characterized by several bioclimatic architectures:


In addition to the data mentioned above, linked to altitudinal impact (2013 m), the watershed hydrological behavior is conditioned also by the bioclimatic changes affecting inevitably the nature of the developed vegetation, the resilience of different ecosystems, and intensity of erosion hazard.

#### *4.1.3.2 Rainfall aggressiveness (R)*

The rainfall erosive power, or the rainfall erosivity factor (MJ mm ha<sup>−</sup><sup>1</sup> h<sup>−</sup><sup>1</sup> year<sup>−</sup><sup>1</sup> ), is calculated by the application of the formula using data of average monthly and annual rainfall in the selected meteorological stations [17, 20]. Thus, the rainfall aggressiveness values (R) are between 64 and 130, respectively, recorded at El Kansra and Ifrane stations. Moreover, in the east, the rains are more aggressive than in the north and west. Also, the upstream area shows the higher rainfall aggressiveness indexes (**Figure 13**).

In conclusion, the rainfall aggressiveness, associated with the heterogeneity of the rainfall distribution, is spatially variable and adheres to erosion processes [21, 22].

**101**

*4.1.4 Land uses*

**Figure 13.** *R-factor distribution.*

*4.1.5 Vegetation index*

*Spatial Analysis of the Erosive Hazard of Soils and Natural Risks of Reservoir Siltation*

The watershed has a variety of land uses related to the bioclimatic variation and topo-edaphical diversity. Thus, the rangelands area is the most common type of land cover (44%). Forests represent second place with 29%, reflecting the pastoral character of the watershed (**Figure 14**). Moreover, the forestry formations are concentrated mainly in the central and upstream. Furthermore, we note the presence of unplanted lands, covered by rocks, which are generally concentrated near the dam El Kansra.

Normalized difference vegetation index (NDVI) is the most common measurement used for measuring vegetation cover. NDVI calculation allows to quantify vegetation by measuring the difference between near-infrared "NIR" (which vegetation strongly reflects) and red light (which vegetation absorbs), according to the following formula: NDVI = \_

(NIR − Red) (NIR + Red)

The NDVI will be computed temporally to understand the change of land cover

during the study period. It ranges from values −1 to +1. Thus, very low values of NDVI (−0.1 and below) correspond to barren areas of rock, sand, or urban/ built-up. Zero indicates the water cover. Moderate values represent low density of

vegetation (0.1–0.3), while high values indicate vegetation (0.6–0.8).

(5)

*DOI: http://dx.doi.org/10.5772/intechopen.89748*

*Spatial Analysis of the Erosive Hazard of Soils and Natural Risks of Reservoir Siltation DOI: http://dx.doi.org/10.5772/intechopen.89748*

**Figure 13.** *R-factor distribution.*

*Soil Erosion - Rainfall Erosivity and Risk Assessment*

*Distribution of average monthly rainfall data by station.*

and latitude factors.

**Figure 12.**

than the approximation of the sea.

*4.1.3.1 Bioclimatic synthesis*

in temperature associated with increasing altitude. Moreover, the thermal regime is characterized by average temperatures that vary between 10°C in the east and 26°C in the north and north-west. Thus, the studied watershed is influenced by altitude

On the other hand, the rainfall regime is irregular and the rainy period is concentrated between October and May (**Figure 12**). As a result, the precipitation distribution analysis shows that the watershed has a rainy winter and a dry summer period. Therefore, the upland areas (mountains) are wetter than the areas that are close to the sea. Thus, the altitude effect on rainfall (R-factor) is more dominant

Bioclimatic data analysis is based on quotient Emberger index (Q2). This quotient, especially adapted to the Mediterranean regions, is based on the annual rainfall, the average maximum temperatures of the warmest month (M °C), and the average minimum temperatures of the coldest month (m °C) [19]. Thus, Oued Beht

• In the north and northwest, the climate is semi-arid with temperate winter.

In addition to the data mentioned above, linked to altitudinal impact (2013 m), the watershed hydrological behavior is conditioned also by the bioclimatic changes affecting inevitably the nature of the developed vegetation, the resilience of differ-

), is calculated by the application of the formula using data of aver-

watershed is characterized by several bioclimatic architectures:

ent ecosystems, and intensity of erosion hazard.

rainfall aggressiveness indexes (**Figure 13**).

*4.1.3.2 Rainfall aggressiveness (R)*

year<sup>−</sup><sup>1</sup>

• In the center, the climate is sub-humid with temperate winter.

• The east of the watershed presents a humid climate with cold winter.

The rainfall erosive power, or the rainfall erosivity factor (MJ mm

age monthly and annual rainfall in the selected meteorological stations [17, 20]. Thus, the rainfall aggressiveness values (R) are between 64 and 130, respectively, recorded at El Kansra and Ifrane stations. Moreover, in the east, the rains are more aggressive than in the north and west. Also, the upstream area shows the higher

In conclusion, the rainfall aggressiveness, associated with the heterogeneity of the rainfall distribution, is spatially variable and adheres to erosion processes [21, 22].

**100**

ha<sup>−</sup><sup>1</sup> h<sup>−</sup><sup>1</sup>

#### *4.1.4 Land uses*

The watershed has a variety of land uses related to the bioclimatic variation and topo-edaphical diversity. Thus, the rangelands area is the most common type of land cover (44%). Forests represent second place with 29%, reflecting the pastoral character of the watershed (**Figure 14**). Moreover, the forestry formations are concentrated mainly in the central and upstream. Furthermore, we note the presence of unplanted lands, covered by rocks, which are generally concentrated near the dam El Kansra.

#### *4.1.5 Vegetation index*

Normalized difference vegetation index (NDVI) is the most common measurement used for measuring vegetation cover. NDVI calculation allows to quantify vegetation by measuring the difference between near-infrared "NIR" (which vegetation strongly reflects) and red light (which vegetation absorbs), according to the following formula: NDVI = \_

$$\text{NDVI} = \frac{\text{(NIR - Red)}}{\text{(NIR + Red)}} \tag{5}$$

The NDVI will be computed temporally to understand the change of land cover during the study period. It ranges from values −1 to +1. Thus, very low values of NDVI (−0.1 and below) correspond to barren areas of rock, sand, or urban/ built-up. Zero indicates the water cover. Moderate values represent low density of vegetation (0.1–0.3), while high values indicate vegetation (0.6–0.8).

#### **Figure 14.** *Land use map.*

The results obtained from the NDVI analysis show that the recovery rate is characterized by dominance of the low class, grouping generally rangelands and crop fields. Thus, both classes "low" and "very low" represent 72% of the total area. Consequently, this indicator reflects the low coverage capacity even if the land cover is almost complete and denuded soils rate is only 9.5% (**Figure 15**).

Moreover, agricultural lands are specially based on cereals and annual crops with short growing cycles. Thus, the rangelands consist of perennial grass vegetation with short development cycle. In conclusion, the land use duration is short, especially during periods of heavy rain.

The analysis of vegetation cover (C-factor) also confirms the low recovery rate. Thus, more than half of the watershed (55%) has a C-factor exceeding 0.5 and 72% has values greater than 0.2 (**Figure 16**). Therefore, these results are consistent with the biophysical analysis describing the low recovery rate.

In conclusion, this factor has a detrimental effect on the erosion process by promoting the sediments production in low soil coverage, and especially if it is combined with other determinant factors.

#### *4.1.6 Hydrological behavior*

The establishment of the hydrological system map, based on DTM spatial analysis, allows to determine the rivers' directions and the accumulation of their flow (flow accumulation). Indeed, the river system obtained is ramified along the entire watershed. Thus, it consists of the main stream named Oued Beht, which

**103**

**Figure 16.** *C-factor distribution.*

**Figure 15.**

*Normalized difference vegetation index map.*

*Spatial Analysis of the Erosive Hazard of Soils and Natural Risks of Reservoir Siltation*

*DOI: http://dx.doi.org/10.5772/intechopen.89748*

*Spatial Analysis of the Erosive Hazard of Soils and Natural Risks of Reservoir Siltation DOI: http://dx.doi.org/10.5772/intechopen.89748*

**Figure 15.** *Normalized difference vegetation index map.*

*Soil Erosion - Rainfall Erosivity and Risk Assessment*

The results obtained from the NDVI analysis show that the recovery rate is characterized by dominance of the low class, grouping generally rangelands and crop fields. Thus, both classes "low" and "very low" represent 72% of the total area. Consequently, this indicator reflects the low coverage capacity even if the land cover

Moreover, agricultural lands are specially based on cereals and annual crops with short growing cycles. Thus, the rangelands consist of perennial grass vegetation with short development cycle. In conclusion, the land use duration is short,

The analysis of vegetation cover (C-factor) also confirms the low recovery rate. Thus, more than half of the watershed (55%) has a C-factor exceeding 0.5 and 72% has values greater than 0.2 (**Figure 16**). Therefore, these results are consistent with

In conclusion, this factor has a detrimental effect on the erosion process by promoting the sediments production in low soil coverage, and especially if it is

The establishment of the hydrological system map, based on DTM spatial analysis, allows to determine the rivers' directions and the accumulation of their flow (flow accumulation). Indeed, the river system obtained is ramified along the entire watershed. Thus, it consists of the main stream named Oued Beht, which

is almost complete and denuded soils rate is only 9.5% (**Figure 15**).

the biophysical analysis describing the low recovery rate.

especially during periods of heavy rain.

combined with other determinant factors.

*4.1.6 Hydrological behavior*

**102**

**Figure 14.** *Land use map.*

**Figure 16.** *C-factor distribution.*

**Figure 17.** *Sub-catchment delimitation.*

is powered by the waters of several tributaries: Beht, Tigrigra, Ifrane, El Kell, Ouchket, Kharrouba, Beregline, and El Kour (**Figure 17**).

#### *4.1.6.1 Drainage density*

The surface drainage in the Oued Beht watershed is assured by a hierarchical arsenal of rivers. Thus, the density is influenced by its topo-geological structure and relief. Indeed, the river system is characterized by the importance of its elements, since their original ramifications upstream, domiciled in the Middle Atlas chain, to the main collector which is the El Kansra dam. Therefore, the river system is characterized by a total length about 667.77 km and an average density 0.16 km/km<sup>2</sup> .

#### *4.1.6.2 Concentration time*

The time (tc) that is necessary for the farthest water particle to arrive at watershed outlet, is estimated by the formula of Passini [23], which is presented as follows: 3 \_

$$\mathbf{t}\_{\mathbf{c}} = \mathbf{0}.\mathbf{108} \times \frac{(\mathbf{S} \times \mathbf{L})^{\frac{1}{3}}}{\mathbf{I}^{\frac{1}{2}}} \tag{6}$$

**105**

**Table 1.**

*Spatial Analysis of the Erosive Hazard of Soils and Natural Risks of Reservoir Siltation*

Therefore, the concentration time (tc) is relatively low at the majority of sub-catchments (SBC) and varies from 2:30 hours (in SBC/Kharrouba) to almost

In conclusion, the elongated form of the Oued Beht watershed and the low concentration time for the majority of sub-basins are favorable conditions for the development of flood and river flows that cause sediment deposits in the stream

The bathymetric data analysis implemented since the construction of the El Kansra dam is used to assess the quantity of soil loss which compromises the storage capacity and quality of water flow. Thus, for a period of 23 years (1981–2004), the

The central objective is the prioritization of sub-catchments presenting high flood risk and soil erosion. The data linked to maximum flood flows are obtained by calculating the extreme gradient values (Gradex method) from the decennial flow in the reference station of Ouljet Soltane (**Table 1**). Thus, the hydrological analysis involved determination of design floods for a large number of sub-catchments by

• First, samples of annual maximum daily rainfall were used to calculate

• The Gradex method was next used, with a daily time-step, applied to all stream gauging stations available. Thus, the pivot point was taken as T\* = 10 years. Conversion from daily discharge Qj(T) into peak discharge Qp(T) was done by considering the mean Qp/Qj ratio from a small sample of

(P0 = ordinate of origin and G = slope or gradex).

where Gd is Gradex flow, defined by the following formula:

*Statistical adjustment of annual maximum flows, in the gauging station of Ouljet Soltane.*

parameters P0 and G of Gumbel distribution for the various raingauge stations

• Lastly, the results obtained (**Table 2**) are synthesized using the following equation for calculating the maximum instantaneous flow Qp(T), for the return

**Return period T (years)** 10 20 50 100 1000 **Q (m3/s)** 488 586 712 807 1121

Qp (T) = Q(T\* = 10 years) + Cp \* Gd \* (u(T) – u(T\*)) (7)

Gd = Gp \* S/(3.6 \* t c) (8)

/year.

*DOI: http://dx.doi.org/10.5772/intechopen.89748*

5 hours (in SBC/Tigrigra).

beds and El Kansra dam.

*4.1.6.4 Floods study*

the Gradex method:

hydrographs.

period T:

*4.1.6.3 El Kansra dam siltation*

average El Kansra dam siltation is 3 million m3

where tc is the concentration time (h), S is the surface of the sub-catchment (km2 ), I is the average slope of the sub-catchment (%), and L is the length of the longest path flow (km).

*Spatial Analysis of the Erosive Hazard of Soils and Natural Risks of Reservoir Siltation DOI: http://dx.doi.org/10.5772/intechopen.89748*

Therefore, the concentration time (tc) is relatively low at the majority of sub-catchments (SBC) and varies from 2:30 hours (in SBC/Kharrouba) to almost 5 hours (in SBC/Tigrigra).

In conclusion, the elongated form of the Oued Beht watershed and the low concentration time for the majority of sub-basins are favorable conditions for the development of flood and river flows that cause sediment deposits in the stream beds and El Kansra dam.

### *4.1.6.3 El Kansra dam siltation*

The bathymetric data analysis implemented since the construction of the El Kansra dam is used to assess the quantity of soil loss which compromises the storage capacity and quality of water flow. Thus, for a period of 23 years (1981–2004), the average El Kansra dam siltation is 3 million m3 /year.

### *4.1.6.4 Floods study*

*Soil Erosion - Rainfall Erosivity and Risk Assessment*

is powered by the waters of several tributaries: Beht, Tigrigra, Ifrane, El Kell,

The surface drainage in the Oued Beht watershed is assured by a hierarchical arsenal of rivers. Thus, the density is influenced by its topo-geological structure and relief. Indeed, the river system is characterized by the importance of its elements, since their original ramifications upstream, domiciled in the Middle Atlas chain, to the main collector which is the El Kansra dam. Therefore, the river system is characterized by a total length about 667.77 km and an average density 0.16 km/km<sup>2</sup>

The time (tc) that is necessary for the farthest water particle to arrive at watershed outlet, is estimated by the formula of Passini [23], which is presented as follows:

where tc is the concentration time (h), S is the surface of the sub-catchment

), I is the average slope of the sub-catchment (%), and L is the length of the

(S × L) \_1 3 \_ 

I \_1 2 

tc = 0.108 ×

.

(6)

Ouchket, Kharrouba, Beregline, and El Kour (**Figure 17**).

*4.1.6.1 Drainage density*

*Sub-catchment delimitation.*

**Figure 17.**

*4.1.6.2 Concentration time*

longest path flow (km).

**104**

(km2

The central objective is the prioritization of sub-catchments presenting high flood risk and soil erosion. The data linked to maximum flood flows are obtained by calculating the extreme gradient values (Gradex method) from the decennial flow in the reference station of Ouljet Soltane (**Table 1**). Thus, the hydrological analysis involved determination of design floods for a large number of sub-catchments by the Gradex method:


$$\mathbf{Q\_{p} \text{ (T)} = Q(T^\* = 10 \text{ years)} + C\_{p} \text{ \* G}\_{d} \text{ \* (u/T)} - u(T^\*)} \text{ \*} \tag{7}$$

where Gd is Gradex flow, defined by the following formula:

$$\mathbf{G\_d = G\_p \text{ \* } S/(3.6 \text{ \* } t\_c)}\tag{8}$$


**Table 1.**

*Statistical adjustment of annual maximum flows, in the gauging station of Ouljet Soltane.*


**Table 2.**

*Flood flows Qp of the principal rivers (m3 /s).*

where Gp is the Gradex rainfall, S is the area of the watershed (km2 ), t c is the concentration time (h) (Eq. (5)), Cp is the pivot point, and u(T) is the variable of Gumbel.

For the other neighboring ungauged sub-watersheds, the application of Francou-Rodier formula gives the following results (Eq. (2)):

#### *4.1.7 Potential erosion*

Compared to Eq. (1), the potential erosion allows to evaluate the power of soils to produce sediments under the effect of rainfall and topological factors, without considering land cover (C-factor) and erosion control practices (P-factor). The crossing of thematic layers of rainfall aggressiveness (R), soil erodibility (K), and the topographic data (LS) is used to synthesize potential impacts according to the formula defined as follows [9, 10]:

$$\mathbf{E\_{P}} = \mathbf{R} \times \mathbf{K} \times \mathbf{L} \,\mathbf{S} \tag{9}$$

**107**

**Figure 18.**

*Potential erosion map.*

*Spatial Analysis of the Erosive Hazard of Soils and Natural Risks of Reservoir Siltation*

Furthermore, the investigative visits show that the upstream part is very sensitive to the potential erosion, but it should be noted, by location, the presence of medium and high levels of vegetation cover that can reduce the erosive potential. The priority areas delimitation is performed through the spatial crossing of the specific degradation map, the map of sub-catchment contribution to dam siltation, and flood generation. This analysis is further developed by the socio-economic vulnerability map (**Figure 18**). Thus, we note that the results obtained reveal that the majority of areas identified and delineated as priority areas are occupied generally by soils with strong erosion risks. Consequently, the vulnerability linked to soil

degradation characterizes 32% of Oued Beht watershed (**Figure 19**).

pixels) define four susceptibility classes in the Oued Beht watershed:

uses (agriculture, livestock, and forests).

**4.2 Mapping erosion susceptibility**

In conclusion, 24 rural communes know high contribution to dam siltation and include areas with high erosion risks and high poverty level. Therefore, urgent biological and technical actions are needed in this region to control erosion impact [25]. Therefore, these rural communes are concerned by action plans linked to land

The hazard zoning obtained and the analysis of cumulative curves (number of

• Low susceptibility (S1): The start of the erosion is negligible in almost half of the watershed (44.5%). In fact, local conditions contribute to the stability of

*DOI: http://dx.doi.org/10.5772/intechopen.89748*

where E p is the potential average annual soil loss (t/ha/year), R is the rainfall aggressiveness index (MJ.mm.ha<sup>−</sup><sup>1</sup> .h<sup>−</sup><sup>1</sup> .year<sup>−</sup><sup>1</sup> ), K is the soil erodibility (t.h.MJ<sup>−</sup><sup>1</sup> . mm<sup>−</sup><sup>1</sup> ), and LS is the topographical factor (dimensionless).

The results analysis shows that the potential average annual soil loss is 54 t/ha, and the average annual quantity is 23.25 million t/year. Moreover, the importance of soil loss differences between extreme values obtained (pixels) shows the power of eminent soil units to produce sediments under the rainfall aggressiveness [24].

Two-thirds of the Oued Beht watershed are characterized by soil loss quantity, which is less than 50 t/ha/year, and almost 30% corresponds to the potential erosion class between 50 and 300 t/ha/year. Thus, on the broken reliefs located in the upstream part (in Tigrigra and Ifrane sub-catchments), with steep slopes, generally exceeding 25%, the potential erosion is high with values that may exceed 200 t/ha/year (**Figure 18**). Moreover, these erodible areas are characterized particularly by high and medium soil friability.

Second, some areas near El Kansra dam present high values of the potential erosion exceeding 200 t/ha/year. These vulnerable sectors correspond mainly to northern sub-catchments with low altitudes (less than 400 m) with high soil friability. Therefore, the great erosive power of adjacent areas to El Kansra dam is a real danger involving the dam siltation and compromising its service life.

*Spatial Analysis of the Erosive Hazard of Soils and Natural Risks of Reservoir Siltation DOI: http://dx.doi.org/10.5772/intechopen.89748*

#### **Figure 18.** *Potential erosion map.*

*Soil Erosion - Rainfall Erosivity and Risk Assessment*

where Gp is the Gradex rainfall, S is the area of the watershed (km2

*/s).*

Francou-Rodier formula gives the following results (Eq. (2)):

concentration time (h) (Eq. (5)), Cp is the pivot point, and u(T) is the variable of

**Streams Area (km2) Q p Q p Q p Q p Q p**

Tigrigra 909.37 241 294 364 417 597 Ifrane 1019.6 261 318 394 451 643 El Kell 487.2 154 190 238 275 401 Ouchket 326.53 115 143 181 210 310 El Kour 413.2 137 169 213 246 361 Kharrouba 798.12 219 268 333 382 549 Beregline 353.26 122 152 191 221 326

**T= 10years T= 20years T= 50years T= 100years T= 1000years**

Compared to Eq. (1), the potential erosion allows to evaluate the power of soils to produce sediments under the effect of rainfall and topological factors, without considering land cover (C-factor) and erosion control practices (P-factor). The crossing of thematic layers of rainfall aggressiveness (R), soil erodibility (K), and the topographic data (LS) is used to synthesize potential impacts according to the

where E p is the potential average annual soil loss (t/ha/year), R is the rainfall

The results analysis shows that the potential average annual soil loss is 54 t/ha, and the average annual quantity is 23.25 million t/year. Moreover, the importance of soil loss differences between extreme values obtained (pixels) shows the power of eminent soil units to produce sediments under the rainfall aggressiveness [24]. Two-thirds of the Oued Beht watershed are characterized by soil loss quantity, which is less than 50 t/ha/year, and almost 30% corresponds to the potential erosion class between 50 and 300 t/ha/year. Thus, on the broken reliefs located in the upstream part (in Tigrigra and Ifrane sub-catchments), with steep slopes, generally exceeding 25%, the potential erosion is high with values that may exceed 200 t/ha/year (**Figure 18**). Moreover, these erodible areas are characterized particularly by high

.year<sup>−</sup><sup>1</sup>

Second, some areas near El Kansra dam present high values of the potential erosion exceeding 200 t/ha/year. These vulnerable sectors correspond mainly to northern sub-catchments with low altitudes (less than 400 m) with high soil friability. Therefore, the great erosive power of adjacent areas to El Kansra dam is a

real danger involving the dam siltation and compromising its service life.

.h<sup>−</sup><sup>1</sup>

), and LS is the topographical factor (dimensionless).

Ep = R × K × LS (9)

), K is the soil erodibility (t.h.MJ<sup>−</sup><sup>1</sup>

For the other neighboring ungauged sub-watersheds, the application of

), t c is the

.

**106**

Gumbel.

**Table 2.**

mm<sup>−</sup><sup>1</sup>

*4.1.7 Potential erosion*

formula defined as follows [9, 10]:

*Flood flows Qp of the principal rivers (m3*

aggressiveness index (MJ.mm.ha<sup>−</sup><sup>1</sup>

and medium soil friability.

Furthermore, the investigative visits show that the upstream part is very sensitive to the potential erosion, but it should be noted, by location, the presence of medium and high levels of vegetation cover that can reduce the erosive potential.

The priority areas delimitation is performed through the spatial crossing of the specific degradation map, the map of sub-catchment contribution to dam siltation, and flood generation. This analysis is further developed by the socio-economic vulnerability map (**Figure 18**). Thus, we note that the results obtained reveal that the majority of areas identified and delineated as priority areas are occupied generally by soils with strong erosion risks. Consequently, the vulnerability linked to soil degradation characterizes 32% of Oued Beht watershed (**Figure 19**).

In conclusion, 24 rural communes know high contribution to dam siltation and include areas with high erosion risks and high poverty level. Therefore, urgent biological and technical actions are needed in this region to control erosion impact [25]. Therefore, these rural communes are concerned by action plans linked to land uses (agriculture, livestock, and forests).

#### **4.2 Mapping erosion susceptibility**

The hazard zoning obtained and the analysis of cumulative curves (number of pixels) define four susceptibility classes in the Oued Beht watershed:

• Low susceptibility (S1): The start of the erosion is negligible in almost half of the watershed (44.5%). In fact, local conditions contribute to the stability of

**Figure 19.** *Distribution of vulnerable areas.*

the land. Gradients of the slopes are very low (lower than 5%) on agricultural land which is well maintained and well drained.


In conclusion, this exploratory procedure shows amply the system capacity to generate automatically the hazard zoning. Almost a third (31%) of the Oued Beht watershed presents high to very strong susceptibility. The four hazard levels can

**109**

*Spatial Analysis of the Erosive Hazard of Soils and Natural Risks of Reservoir Siltation*

be combined with vulnerability with four levels. This integrated analysis would

The analysis of the socio-economic vulnerability of the watershed is based on the assessment of damage related to the effect of past erosive events on the profitability of soil resources and the income of the farmers surveyed in this study. Thus, the preparation of input data is based on the results of socio-economic surveys

As a result, the yield loss parameters that tell us the annual cost of erosion are defined by the differences between the net initial income per hectare and the net

• Low consequences (C1): Minor damages to these lands are obsolete (1%) and

In addition, the results of the socio-economic surveys show that the local economy is mainly represented by the primary sector (farming and poly-culture). The structural and functional damage map (CSF) describes the combination of damages due to land loss and El Kansra dam siltation that affect human activities. Therefore, the potential damage map (**Figure 20**) is obtained from the qualitative assessment of the state of land degradation (the importance of sheet, rill, and gully erosion) and this, to structure the cost of erosion and to highlight the homogeneous areas of vulnerability. Indeed, the analysis of cumulative curves (number of pixels)

produce risk maps, or rather the existing deficit protection.

describing the decline in land yield year after year (income loss).

has identified four consequences classes for the Oued Beht watershed.

hazard causes as much damage to human activities.

**4.3 Potential consequences analysis**

**Figure 20.**

*Potential consequences map.*

income with the effect of erosion (Eq. (4)).

*DOI: http://dx.doi.org/10.5772/intechopen.89748*

*Spatial Analysis of the Erosive Hazard of Soils and Natural Risks of Reservoir Siltation DOI: http://dx.doi.org/10.5772/intechopen.89748*

**Figure 20.** *Potential consequences map.*

*Soil Erosion - Rainfall Erosivity and Risk Assessment*

the land. Gradients of the slopes are very low (lower than 5%) on agricultural

• Moderate susceptibility (S2): Local environmental conditions are also favorable to the onset of low land loss in almost a quarter of the watershed (24.4%). It is protected by forest areas and the slope gradients are low to moderate (5–25%). However, the abandonment of the reservation land or the local pres-

• High susceptibility (S3): Local environmental conditions are favorable for triggering erosion (11.4%). It is rangeland and unprotected forest formations located on moderately degraded soils and characterized by poor soil drainage

• Very high susceptibility (S4): The possibilities of the start of erosion are strong and the local environmental conditions are very favorable for that in 19.7% of the watershed. Soils are severely degraded, poorly maintained, and managed. The general appearance is marked by the absence of vegetation or forests. Thus, the erosion is very active with a significant soil loss with strong slope

In conclusion, this exploratory procedure shows amply the system capacity to generate automatically the hazard zoning. Almost a third (31%) of the Oued Beht watershed presents high to very strong susceptibility. The four hazard levels can

techniques. The degrees of slopes are moderate to strong (25–45%).

land which is well maintained and well drained.

ence of slope failure could lead to destabilization.

gradient (more than 45%).

**108**

**Figure 19.**

*Distribution of vulnerable areas.*

be combined with vulnerability with four levels. This integrated analysis would produce risk maps, or rather the existing deficit protection.

#### **4.3 Potential consequences analysis**

The analysis of the socio-economic vulnerability of the watershed is based on the assessment of damage related to the effect of past erosive events on the profitability of soil resources and the income of the farmers surveyed in this study. Thus, the preparation of input data is based on the results of socio-economic surveys describing the decline in land yield year after year (income loss).

As a result, the yield loss parameters that tell us the annual cost of erosion are defined by the differences between the net initial income per hectare and the net income with the effect of erosion (Eq. (4)).

In addition, the results of the socio-economic surveys show that the local economy is mainly represented by the primary sector (farming and poly-culture). The structural and functional damage map (CSF) describes the combination of damages due to land loss and El Kansra dam siltation that affect human activities. Therefore, the potential damage map (**Figure 20**) is obtained from the qualitative assessment of the state of land degradation (the importance of sheet, rill, and gully erosion) and this, to structure the cost of erosion and to highlight the homogeneous areas of vulnerability. Indeed, the analysis of cumulative curves (number of pixels) has identified four consequences classes for the Oued Beht watershed.

• Low consequences (C1): Minor damages to these lands are obsolete (1%) and hazard causes as much damage to human activities.


## **4.4 Erosion risk management**

The risk map (**Figure 21**), derived from a spatial combination of susceptibility and potential consequences classes, shows that high-risk areas (R3) are developed on 6% of the territory. These sites identify the major risks and disruptions of human activities. The warning areas correspond to areas with high consequences (C3), located immediately in the upstream side and locally to the center, presenting a very high to moderate

**111**

**Figure 22.**

*Spatial Analysis of the Erosive Hazard of Soils and Natural Risks of Reservoir Siltation*

susceptibility (S2, S3, and S4). Thus, appropriate precaution measures must be established (protected areas) and a risk prevention plan (RPP) must be implemented. Elsewhere, outside large spaces present a low risk (R1) on 72% of watershed, representing the concept of acceptable risk. The risk level is moderate (R2) in 22% of the watershed (e.g., steep slopes but with low to moderate consequences). This menace presents a moderate disruption to human activities and serious damage to infrastructure including El Kansra dam. In conclusion, if improper resource management is implemented, this part of the watershed affected by moderate risk (22%) can be aggravated. Therefore, the potential risk can meet 28% of the watershed. Certainly, the development of management scenarios can complete this

The formulation of Strategic Action Program (SAP) is based on the results of erosion risk mapping (**Figure 21**) to identify priority areas, where measures against soil erosion or reservoir siltation should be taken. The approach used is translated into operational actions (biological and technical), which are compatible with the intrinsic possibilities of the studied watershed (**Figure 22**). Thus, the Strategic

• Measuring and monitoring soil erosion in order to preserve the natural

mapping study to improve the prevention of erosion risk.

Action Plan aims to achieve the priority objectives as follows:

resources and control El Kansra dam siltation.

**4.5 Master plan for strategic planning**

*Master plan of the Oued Beht watershed management.*

*DOI: http://dx.doi.org/10.5772/intechopen.89748*

**Figure 21.** *Natural erosion risks.*

*Spatial Analysis of the Erosive Hazard of Soils and Natural Risks of Reservoir Siltation DOI: http://dx.doi.org/10.5772/intechopen.89748*

**Figure 22.** *Master plan of the Oued Beht watershed management.*

susceptibility (S2, S3, and S4). Thus, appropriate precaution measures must be established (protected areas) and a risk prevention plan (RPP) must be implemented.

Elsewhere, outside large spaces present a low risk (R1) on 72% of watershed, representing the concept of acceptable risk. The risk level is moderate (R2) in 22% of the watershed (e.g., steep slopes but with low to moderate consequences). This menace presents a moderate disruption to human activities and serious damage to infrastructure including El Kansra dam. In conclusion, if improper resource management is implemented, this part of the watershed affected by moderate risk (22%) can be aggravated. Therefore, the potential risk can meet 28% of the watershed. Certainly, the development of management scenarios can complete this mapping study to improve the prevention of erosion risk.

#### **4.5 Master plan for strategic planning**

The formulation of Strategic Action Program (SAP) is based on the results of erosion risk mapping (**Figure 21**) to identify priority areas, where measures against soil erosion or reservoir siltation should be taken. The approach used is translated into operational actions (biological and technical), which are compatible with the intrinsic possibilities of the studied watershed (**Figure 22**). Thus, the Strategic Action Plan aims to achieve the priority objectives as follows:

• Measuring and monitoring soil erosion in order to preserve the natural resources and control El Kansra dam siltation.

*Soil Erosion - Rainfall Erosivity and Risk Assessment*

ing toward the center and south.

**4.4 Erosion risk management**

and prevention authorities concerned.

tion of socio-economic activities is also moderate.

• Moderate consequences (C2): Mild to serious damage to soils and to infrastructures, which are characterized by half of the watershed (49%), mainly in the south watershed (upstream side) and partly downstream. Moreover, disrup-

• High consequences (C3): Moderate to severe disturbances of human activities. Thus, strong and direct consequences are confined in space, but can be felt over the agricultural seasons; also, they represent almost half of Oued Beht watershed (50%). These consequences are partly located in the north watershed (downstream) and mainly around the El Kansra dam but locally extend-

• Very high consequences (C4): The very strong damage is minimal and negligible (0.02%); this kind of erosion events would exceed the human capacity

The risk map (**Figure 21**), derived from a spatial combination of susceptibility and potential consequences classes, shows that high-risk areas (R3) are developed on 6% of the territory. These sites identify the major risks and disruptions of human activities. The warning areas correspond to areas with high consequences (C3), located immediately in the upstream side and locally to the center, presenting a very high to moderate

**110**

**Figure 21.** *Natural erosion risks.*


## *4.5.1 Agricultural land management*

The agricultural development board assists rural households in the Oued Beht watershed to develop their agricultural business according to the lithological formations, and topographical and climatic constraints. Indeed, the agricultural lands, including arboriculture, cover an area of 74,577 ha, nearly 17% of the watershed area. Moreover, the operating systems are basically extensive with the cultivation of a maximum surface whatever the slope (even in the steep slopes).

On the other hand, the production systems adopted are characterized generally by inappropriate farming practices that promote soil erosion. Thus, the socioeconomic study shows that 96% of rural population is conscious of the water and soils degradation.

In this sense, the selected actions aim to achieve a progressive evolution of production systems and land uses in accordance with soils vocation, with limitation of annual crops on steep slopes, the development of arboriculture, and improvement of forage production for livestock. Therefore, the implementation of actions mentioned below will lead to the increase of agricultural incomes and the establishment of a space management model to ensure local sustainability according to the following practices:

• Low to medium slopes (0–15%): The biophysical data analysis shows that the lands with low to medium slopes (0–15%) are subject to an erosive process generally manifested by sheet, rill, and rarely gully erosion. Thus, the aggressive rainfall and inappropriate farming practices (soil tillage in the direction of the slope, overgrazing) are the main factors that increase soil erosion.

The correctional measures include improving productivity through appropriate use of culture techniques. Thus, on low to medium slopes, the soil tillage must follow the contours and be combined with cultures in alternate bands.

In conclusion, to maintain this type of soil vegetation cover as long as possible during the year, it is necessary to promote culture associations. The rotations of "cereal-legume-forage" or "cereal-legume-cereal" are retained. For rangeland improvement, the vetch-oats, alfalfa, and clover present important opportunities for pastoral production and contribute significantly to soil protection.

• Steep slopes (higher than 15%): The results analysis shows that higher slopes are commonly used by cereal cultures that give low yields. Especially, in this case, the soil tillage in the direction of slopes causes ridges that eventually become water runoff channels (gullies) that quickly develop the gullies and ravines. Moreover, the tillage soils according to the slope direction increase erosion.

In conclusion, a sustainable soil management on steep slopes is necessary through the restoration of vegetation cover by the planting of multiple use species following the contours. This plantation technique must be combined with isohypse structures (benches, ditches, and cords) to conserve water and soil.

**113**

*Spatial Analysis of the Erosive Hazard of Soils and Natural Risks of Reservoir Siltation*

In the case of the Oued Beht watershed, fruit trees cultivation presents a promoter axis of the erosion control in the difficult terrain. The tree species proposed depend on agro-ecological areas. This operation needs also the consultation with the farmers concerned to choose trees species. Moreover, the olive, fig, and almond trees seem the most desired fruit trees by the population and the best adapted to the ecological conditions in the watershed. Second, the interline space will be used for the practice of the usual cultures respecting the principles of tillage soils following contour lines.

The socio-economic study shows that the actual animal demand is high compared to production potential. Thus, the confrontation of the rangeland offers and

The results analysis shows that the three livestock types (sheep, cattle, and goats) use rangelands intensively and continuously. Generally, the state of rangelands presents advanced degradation of vegetation resources. In addition, this usage mode is accentuated first by the severity of soil and climatic conditions which are often unfavorable and second by the nature land status that promotes non-rational

In this situation, the pastoral improvement is fully justified by the need to implement an intervention program to save the pastoral resources in the Oued Beht watershed. Thus, short-term actions are based particularly on the development and rational management of pastoral space, and then, in the medium term, the program can implement actions linked to improving driving livestock. Normally, the proposed actions tend to change the pastoralist habits and to support the incentive mechanisms related to fattening to reduce the pressure on the pastoral spaces.

• Rangeland users organization: The users organization into pastoral associations (or cooperatives) is a central action to be taken in parallel with the

• Deferred rotation grazing: In this case, the deferred rotation grazing is the technique used to enhance and restore the herbaceous and shrubs potential. It consists of prohibiting grazing in degraded areas in order to allow the natural regeneration with the development of herbaceous species richness and of

The duration of the deferred grazing depends on pastoral species. A short duration grazing is a rotation on 2–4 years, which is sufficient for the regeneration of herbaceous species and for the improvement of pastoral potential. However, the limitation of rights to use rangelands will be able to generate a forage imbalance that will directly increase the pressure on the surrounding lands and cause the accentuation of their degradation. Thus, to anticipate this problem, it is imperative to choose pastoral species with high nutrient supplies and to provide accompanying measures for population like compensation system linked to unexploited forage units and

• Planting shrubs: In the case of the studied watershed, the survey analysis shows clearly that fodder shrubs are highly attractive to farmers. Thus, the

technical actions (plantation, closing and deferred grazing, and water point for livestock) in order to ensure sustainable use of rangelands. This organizational approach is the population interface with all partners to monitor actions and to

*DOI: http://dx.doi.org/10.5772/intechopen.89748*

livestock demand reveals an important deficit −31%.

defend the pastoral potential of the watershed.

exploitation of forage justified by its gratuity.

*4.5.2 Rangeland management*

forage quantity.

development of forage crops irrigated.

#### *Spatial Analysis of the Erosive Hazard of Soils and Natural Risks of Reservoir Siltation DOI: http://dx.doi.org/10.5772/intechopen.89748*

In the case of the Oued Beht watershed, fruit trees cultivation presents a promoter axis of the erosion control in the difficult terrain. The tree species proposed depend on agro-ecological areas. This operation needs also the consultation with the farmers concerned to choose trees species. Moreover, the olive, fig, and almond trees seem the most desired fruit trees by the population and the best adapted to the ecological conditions in the watershed. Second, the interline space will be used for the practice of the usual cultures respecting the principles of tillage soils following contour lines.

## *4.5.2 Rangeland management*

*Soil Erosion - Rainfall Erosivity and Risk Assessment*

tion in degraded areas.

soils degradation.

following practices:

*4.5.1 Agricultural land management*

including the El Kansra dam and the land goods.

a maximum surface whatever the slope (even in the steep slopes).

• Flood analysis in order to reduce the flood risks with implementation of technical actions and Hydro-Agricultural Infrastructure Protection Plan (HIPP)

• Implementation of biological actions, which consist of plantation and reforesta-

The agricultural development board assists rural households in the Oued Beht watershed to develop their agricultural business according to the lithological formations, and topographical and climatic constraints. Indeed, the agricultural lands, including arboriculture, cover an area of 74,577 ha, nearly 17% of the watershed area. Moreover, the operating systems are basically extensive with the cultivation of

On the other hand, the production systems adopted are characterized generally

by inappropriate farming practices that promote soil erosion. Thus, the socioeconomic study shows that 96% of rural population is conscious of the water and

In this sense, the selected actions aim to achieve a progressive evolution of production systems and land uses in accordance with soils vocation, with limitation of annual crops on steep slopes, the development of arboriculture, and improvement of forage production for livestock. Therefore, the implementation of actions mentioned below will lead to the increase of agricultural incomes and the establishment of a space management model to ensure local sustainability according to the

• Low to medium slopes (0–15%): The biophysical data analysis shows that the lands with low to medium slopes (0–15%) are subject to an erosive process generally manifested by sheet, rill, and rarely gully erosion. Thus, the aggressive rainfall and inappropriate farming practices (soil tillage in the direction of

the slope, overgrazing) are the main factors that increase soil erosion.

follow the contours and be combined with cultures in alternate bands.

for pastoral production and contribute significantly to soil protection.

structures (benches, ditches, and cords) to conserve water and soil.

The correctional measures include improving productivity through appropriate use of culture techniques. Thus, on low to medium slopes, the soil tillage must

In conclusion, to maintain this type of soil vegetation cover as long as possible during the year, it is necessary to promote culture associations. The rotations of "cereal-legume-forage" or "cereal-legume-cereal" are retained. For rangeland improvement, the vetch-oats, alfalfa, and clover present important opportunities

• Steep slopes (higher than 15%): The results analysis shows that higher slopes are commonly used by cereal cultures that give low yields. Especially, in this case, the soil tillage in the direction of slopes causes ridges that eventually become water runoff channels (gullies) that quickly develop the gullies and ravines. Moreover, the tillage soils according to the slope direction increase erosion.

In conclusion, a sustainable soil management on steep slopes is necessary through the restoration of vegetation cover by the planting of multiple use species following the contours. This plantation technique must be combined with isohypse

**112**

The socio-economic study shows that the actual animal demand is high compared to production potential. Thus, the confrontation of the rangeland offers and livestock demand reveals an important deficit −31%.

The results analysis shows that the three livestock types (sheep, cattle, and goats) use rangelands intensively and continuously. Generally, the state of rangelands presents advanced degradation of vegetation resources. In addition, this usage mode is accentuated first by the severity of soil and climatic conditions which are often unfavorable and second by the nature land status that promotes non-rational exploitation of forage justified by its gratuity.

In this situation, the pastoral improvement is fully justified by the need to implement an intervention program to save the pastoral resources in the Oued Beht watershed. Thus, short-term actions are based particularly on the development and rational management of pastoral space, and then, in the medium term, the program can implement actions linked to improving driving livestock. Normally, the proposed actions tend to change the pastoralist habits and to support the incentive mechanisms related to fattening to reduce the pressure on the pastoral spaces.


The duration of the deferred grazing depends on pastoral species. A short duration grazing is a rotation on 2–4 years, which is sufficient for the regeneration of herbaceous species and for the improvement of pastoral potential. However, the limitation of rights to use rangelands will be able to generate a forage imbalance that will directly increase the pressure on the surrounding lands and cause the accentuation of their degradation. Thus, to anticipate this problem, it is imperative to choose pastoral species with high nutrient supplies and to provide accompanying measures for population like compensation system linked to unexploited forage units and development of forage crops irrigated.

• Planting shrubs: In the case of the studied watershed, the survey analysis shows clearly that fodder shrubs are highly attractive to farmers. Thus, the shrubs present the advantage to provide their production in a late period of the year when other forage crops (including herbaceous vegetation) are low or zero. The introduction of tree plantations consists of soil tillage in the autumn before the first rains with the digging holes along the contour lines for planting shrubs and installing bleachers for planting cactus.

In conclusion, this technique aims to improve water balance and fight against erosion. The shrubs species that are recommended are Atriplex nummularia, *Medicago arborea*, Chamaecytisus albidus, and *Opuntia ficus-indica*. Moreover, the use of cactus plantations presents his pastoral role with the advantage of producing highly appreciated fruit that can provide substantial revenue for the users.

• Livestock watering points: The analysis of the surveys data shows that water shortage presents a major constraint, especially as the dry spells became frequent. In the summer, water resources become scarce and fail to cover the livestock needs. Several techniques for collecting and mobilization of water when they are available (in winters and flood periods) are proposed based on the watershed characteristics.

The proposed actions present great social utility and do not require large investments; they are adapted either to an individual or collective use. Thus, the actions include the preparation of water reservoirs, the capture from surface water sources, the development of existing wells, and the digging of new wells.

## *4.5.3 Forest management*

Implementation of action plan linked to watershed forestry resource consists to restore degraded natural ecosystems (evergreen oak and thuya), which represent an economic and ecological importance. Thus, these actions aim to improve the vegetation cover, to protect the soil against erosion, and finally to halt the forest degradation.

• Forest rehabilitation: The biophysical analysis shows that watershed forests are located generally in difficult areas upstream. These ligneous formations have good adaptability and resistance to the negative impacts of climate and anthropogenic pressure. Thus, most of these forests suffer from a lack of natural regeneration.

Therefore, this difficult situation requires efforts in terms of natural regeneration with native species to ensure sustainability of these natural areas. Thus, the intervention program gives priority to the parties that have the potential for regeneration.

These actions are accompanied by water and soil conservation measures to reduce erosion and increase water storage capacity (step elements, benches, and terracing).

• Reforestation protection: The introduction of artificial plantations aims at the protection of degraded forests. Thus, the reforestation of denuded lands and badlands, with forest vocation, allows the soil protection, the runoff quality and quantity improvement, and production of wood products.

Considering the watershed bioclimatic conditions, the spectrum obtained from tree species proposed for reforestation is maritime pine, Aleppo pine, brutia pine, cypress, and eucalyptus trees.

**115**

**Figure 23.** *Social vulnerability.*

*Spatial Analysis of the Erosive Hazard of Soils and Natural Risks of Reservoir Siltation*

• River system and badlands development: The hydrographic network is characterized by high density ratio of river and lakes; the soil losses are accentuated by this river system, and the erosion is generally active on soft to moderately vulnerable areas. This phenomenon is strongly observed in the central part of the watershed where the river system becomes increasingly ramified and individualized (**Figure 11**). This regressive evolution leads to a densification of ravines that can achieve the generalized gully erosion. This situation is clearly illustrated in the downstream part at the El Kansra dam. The sediment quantities resulting from this erosion are mainly transported downstream and

Finally, the proposed management strategy for vulnerable areas is based on a combination of two main actions: biological fixation and mechanical ravine correction. Thus, the two integrated actions stimulate vegetation installation and slope correction. The chosen technique combines the advantages, not only to limit sediment yield but also to promote the defense of infrastructure, good land, and public

This socio-ecological development program gives special attention to aspects of social vulnerability, a major dimension of vulnerability to multiple factors including: low incomes, social exclusion, and natural hazards. Referring to this approach,

*DOI: http://dx.doi.org/10.5772/intechopen.89748*

and private properties.

contribute significantly to the dam siltation.

*Spatial Analysis of the Erosive Hazard of Soils and Natural Risks of Reservoir Siltation DOI: http://dx.doi.org/10.5772/intechopen.89748*

• River system and badlands development: The hydrographic network is characterized by high density ratio of river and lakes; the soil losses are accentuated by this river system, and the erosion is generally active on soft to moderately vulnerable areas. This phenomenon is strongly observed in the central part of the watershed where the river system becomes increasingly ramified and individualized (**Figure 11**). This regressive evolution leads to a densification of ravines that can achieve the generalized gully erosion. This situation is clearly illustrated in the downstream part at the El Kansra dam. The sediment quantities resulting from this erosion are mainly transported downstream and contribute significantly to the dam siltation.

Finally, the proposed management strategy for vulnerable areas is based on a combination of two main actions: biological fixation and mechanical ravine correction. Thus, the two integrated actions stimulate vegetation installation and slope correction. The chosen technique combines the advantages, not only to limit sediment yield but also to promote the defense of infrastructure, good land, and public and private properties.

This socio-ecological development program gives special attention to aspects of social vulnerability, a major dimension of vulnerability to multiple factors including: low incomes, social exclusion, and natural hazards. Referring to this approach,

**Figure 23.** *Social vulnerability.*

*Soil Erosion - Rainfall Erosivity and Risk Assessment*

the watershed characteristics.

*4.5.3 Forest management*

regeneration.

cypress, and eucalyptus trees.

regeneration.

terracing).

shrubs and installing bleachers for planting cactus.

shrubs present the advantage to provide their production in a late period of the year when other forage crops (including herbaceous vegetation) are low or zero. The introduction of tree plantations consists of soil tillage in the autumn before the first rains with the digging holes along the contour lines for planting

In conclusion, this technique aims to improve water balance and fight against erosion. The shrubs species that are recommended are Atriplex nummularia, *Medicago arborea*, Chamaecytisus albidus, and *Opuntia ficus-indica*. Moreover, the use of cactus plantations presents his pastoral role with the advantage of producing

• Livestock watering points: The analysis of the surveys data shows that water shortage presents a major constraint, especially as the dry spells became frequent. In the summer, water resources become scarce and fail to cover the livestock needs. Several techniques for collecting and mobilization of water when they are available (in winters and flood periods) are proposed based on

The proposed actions present great social utility and do not require large investments; they are adapted either to an individual or collective use. Thus, the actions include the preparation of water reservoirs, the capture from surface water sources,

Implementation of action plan linked to watershed forestry resource consists to restore degraded natural ecosystems (evergreen oak and thuya), which represent an economic and ecological importance. Thus, these actions aim to improve the vegetation cover, to protect the soil against erosion, and finally to halt the forest degradation.

• Forest rehabilitation: The biophysical analysis shows that watershed forests are located generally in difficult areas upstream. These ligneous formations have good adaptability and resistance to the negative impacts of climate and anthropogenic pressure. Thus, most of these forests suffer from a lack of natural

Therefore, this difficult situation requires efforts in terms of natural regeneration with native species to ensure sustainability of these natural areas. Thus, the intervention program gives priority to the parties that have the potential for

These actions are accompanied by water and soil conservation measures to reduce erosion and increase water storage capacity (step elements, benches, and

• Reforestation protection: The introduction of artificial plantations aims at the protection of degraded forests. Thus, the reforestation of denuded lands and badlands, with forest vocation, allows the soil protection, the runoff quality

Considering the watershed bioclimatic conditions, the spectrum obtained from tree species proposed for reforestation is maritime pine, Aleppo pine, brutia pine,

and quantity improvement, and production of wood products.

highly appreciated fruit that can provide substantial revenue for the users.

the development of existing wells, and the digging of new wells.

**114**

all people whose consumption expenditure is below the poverty line, which represents the minimum income considered adequate for each person, are considered vulnerable. In Morocco, on average, the poverty line is US \$ 2.4 per person per day in rural areas [14, 15].

In fact, the survey design conducted in this study allowed us to exploit the income data of sampled individuals and to develop a simplified map representing, by homogeneous area, the percentage of individuals with an income below the minimum income deemed appropriate for each person (**Figure 23**).

## **4.6 Operational management program**

The autocorrelation maps obtained (z-score) are used to delineate the priority interventions which correspond to the z-scores, statistically significant with values higher than 1.65 or less than −1.65 (**Figure 13**). Furthermore, the biological actions in degraded areas (by fruit plantation, regeneration, and reforestation) are materialized in spaces that express high spatial aggregation between soil loss and degraded vegetation cover. Consequently, the total area covered by this type of intervention

**117**

*Spatial Analysis of the Erosive Hazard of Soils and Natural Risks of Reservoir Siltation*

is 87,351 ha, which represents 20% of the Oued Beht watershed. These biological interventions are concentrated mainly in the priority sub-catchments of Tigrigra,

On the other hand, the technical actions designed to reduce the slope effect consist in the establishment of benches, ditches, and terracing. These structures are programmed in high spatial aggregation between soil erosion and steep slopes. The total area covered by technical intervention is 22,753 ha, and a quarter of biological interventions is combined with technical measures, especially in the upstream part

In conclusion, the package of techniques of soil conservation and erosion control

This research paper proposes the development of a methodology analysis for soil erosion hazard and risk administration, especially a very few studies are dedicated to the mapping of soil loss risks. The use of analytical models based on space technology information processing has developed a GIS database on biophysical and topoclimatic parameters in Oued Beht watershed. Thus, the procedure described evaluates the soil loss risk and siltation of El Kansra dam, located in the

The present study has implemented a cartographic approach based on the integration of spatial remote sensing tools (GIS) and spatial analysis functionalities linked to the initial state of the studied watershed. Thus, the central objective is to define the guidelines of the strategic spatial planning dedicated to erosion risk management. Moreover, although some studies have combined biophysical data and the constraints identified in the socio-economic analysis in order to understand the conditions of water erosion, they generally do not consider the statistical autocorrelation to develop strategy for priority management of watersheds. In this perspective, the cartographic restitution of spatial clusters obtained identifies priority areas

The results obtained from the spatial autocorrelation analysis concerning socio-ecological components show that the priority actions are needed for almost 20% of the Oued Beht watershed. Thus, all priority areas identified are affected by the biological techniques (fruit plantation, regeneration, and reforestation in

In addition to that, the spatial aggregation map shows also that the appropriate soil conservation practices (terracing) correspond to a quarter (15%) of the priority areas. Thus, this category of intervention aims to reduce the negative effects of the topographic factor with the establishment of terracing structures (**Figure 13**). The main purpose of the terracing application is to improve the usefulness of steep slopes and to increase their agricultural potential. This function is realized by creating the level surfaces according to contour lines of transformed slopes. The level, bench platform allows spreading the surface runoff water, decreases its speed, and

adequate slopes) that mitigate the factor, which expresses the lack of

and establishes the first interventions across the watershed.

thus allows more time for water infiltration into soil profile.

is developed in agricultural and sylvopastoral areas, starting from various types of soil tillage and vegetation cover, to different types of terraces, check dams, and stone bunds. Thus, the terracing is the selected agricultural technique for collecting surface runoff water, thus increasing infiltration and controlling water erosion used to transform landscape to steeped agrosystems in the mountainous regions

*DOI: http://dx.doi.org/10.5772/intechopen.89748*

Ifrane, and Kharrouba (**Figure 24**).

of the watershed (**Figure 24**).

(upstream).

**5. Conclusion**

upstream side.

vegetation cover.

**Figure 24.** *Biological interventions.*

*Spatial Analysis of the Erosive Hazard of Soils and Natural Risks of Reservoir Siltation DOI: http://dx.doi.org/10.5772/intechopen.89748*

is 87,351 ha, which represents 20% of the Oued Beht watershed. These biological interventions are concentrated mainly in the priority sub-catchments of Tigrigra, Ifrane, and Kharrouba (**Figure 24**).

On the other hand, the technical actions designed to reduce the slope effect consist in the establishment of benches, ditches, and terracing. These structures are programmed in high spatial aggregation between soil erosion and steep slopes. The total area covered by technical intervention is 22,753 ha, and a quarter of biological interventions is combined with technical measures, especially in the upstream part of the watershed (**Figure 24**).

In conclusion, the package of techniques of soil conservation and erosion control is developed in agricultural and sylvopastoral areas, starting from various types of soil tillage and vegetation cover, to different types of terraces, check dams, and stone bunds. Thus, the terracing is the selected agricultural technique for collecting surface runoff water, thus increasing infiltration and controlling water erosion used to transform landscape to steeped agrosystems in the mountainous regions (upstream).

### **5. Conclusion**

*Soil Erosion - Rainfall Erosivity and Risk Assessment*

**4.6 Operational management program**

in rural areas [14, 15].

all people whose consumption expenditure is below the poverty line, which represents the minimum income considered adequate for each person, are considered vulnerable. In Morocco, on average, the poverty line is US \$ 2.4 per person per day

In fact, the survey design conducted in this study allowed us to exploit the income data of sampled individuals and to develop a simplified map representing, by homogeneous area, the percentage of individuals with an income below the

The autocorrelation maps obtained (z-score) are used to delineate the priority interventions which correspond to the z-scores, statistically significant with values higher than 1.65 or less than −1.65 (**Figure 13**). Furthermore, the biological actions in degraded areas (by fruit plantation, regeneration, and reforestation) are materialized in spaces that express high spatial aggregation between soil loss and degraded vegetation cover. Consequently, the total area covered by this type of intervention

minimum income deemed appropriate for each person (**Figure 23**).

**116**

**Figure 24.**

*Biological interventions.*

This research paper proposes the development of a methodology analysis for soil erosion hazard and risk administration, especially a very few studies are dedicated to the mapping of soil loss risks. The use of analytical models based on space technology information processing has developed a GIS database on biophysical and topoclimatic parameters in Oued Beht watershed. Thus, the procedure described evaluates the soil loss risk and siltation of El Kansra dam, located in the upstream side.

The present study has implemented a cartographic approach based on the integration of spatial remote sensing tools (GIS) and spatial analysis functionalities linked to the initial state of the studied watershed. Thus, the central objective is to define the guidelines of the strategic spatial planning dedicated to erosion risk management. Moreover, although some studies have combined biophysical data and the constraints identified in the socio-economic analysis in order to understand the conditions of water erosion, they generally do not consider the statistical autocorrelation to develop strategy for priority management of watersheds. In this perspective, the cartographic restitution of spatial clusters obtained identifies priority areas and establishes the first interventions across the watershed.

The results obtained from the spatial autocorrelation analysis concerning socio-ecological components show that the priority actions are needed for almost 20% of the Oued Beht watershed. Thus, all priority areas identified are affected by the biological techniques (fruit plantation, regeneration, and reforestation in adequate slopes) that mitigate the factor, which expresses the lack of vegetation cover.

In addition to that, the spatial aggregation map shows also that the appropriate soil conservation practices (terracing) correspond to a quarter (15%) of the priority areas. Thus, this category of intervention aims to reduce the negative effects of the topographic factor with the establishment of terracing structures (**Figure 13**). The main purpose of the terracing application is to improve the usefulness of steep slopes and to increase their agricultural potential. This function is realized by creating the level surfaces according to contour lines of transformed slopes. The level, bench platform allows spreading the surface runoff water, decreases its speed, and thus allows more time for water infiltration into soil profile.

In conclusion, this approach has allowed developing a planning program with successful techniques for soil erosion control in degraded areas linked to steep slopes, climatic conditions, and erodible soils.

It is obvious that this approach, based on ground measurements combined with geographic information systems, must be accompanied by a regular monitoring system by updating continuously the part of the spatial model derived from remote sensing. Furthermore, the stable part of the geospatial database consists of intrinsic factors (lithology, soil, drainage density, etc.) and the dynamic part to control includes biotic factors related to the soil occupation and needs evolution of the local population.

Although this analysis was conducted to the master plan of watershed development and has identified environmental constraints (soil and water degradation) characterizing priority areas, it is necessary to refine this analysis through a participatory action plan. Thus, this zonal analysis will specify for each year the interventions to be implemented and the financial package, by considering the needs and perspectives of the rural population. Moreover, the effectiveness of the proposed techniques can be limited especially if the local population is opposed or, in some cases, found to be expensive to build and maintain.

Finally, this research work demonstrates the potential and merits of spatial analysis techniques to evaluate the erosion risks. An indicative mapping designed for the management and risk prevention is obtained, to control the source and quality of input and to characterize the conditions of validity of the models. However, the difficulties encountered in the collection of quantitative damage data, usually, due to the lack of historical information, refer to the idea that it would be necessary to create an observatory and full database related to water erosion damage. Thus, research is needed to introduce also the temporal component (probability of erosion and return period) in a decision support perspective to implement a regional sustainable planning.

### **Acknowledgements**

This research paper was partially supported by the Identification and Modeling Laboratory of Natural Environment (LIMEN), Mohammadia School of Engineers in Mohammed V University (Morocco). I would also like to express my gratitude to some of my colleagues who were generous in providing guidance, and without their help, this project could not have been accomplished.

## **Dedication**

I dedicate this paper to my parents Ahmed and Jamila, my sisters and my nephew Mouad, my dear family, and to the soul of my uncle Hassan Touissate. I also dedicate this modest work to my dear wife Ihsane, friends, and colleagues, and without their encouragement, I could not have written this.

**119**

**Author details**

Rabii El Gaatib

Morocco

*Spatial Analysis of the Erosive Hazard of Soils and Natural Risks of Reservoir Siltation*

Ministry of Agriculture, Fisheries, Rural Development, Water and Forests, Rabat,

© 2019 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium,

\*Address all correspondence to: rabii\_elgaatib@yahoo.fr

provided the original work is properly cited.

*DOI: http://dx.doi.org/10.5772/intechopen.89748*

*Spatial Analysis of the Erosive Hazard of Soils and Natural Risks of Reservoir Siltation DOI: http://dx.doi.org/10.5772/intechopen.89748*

## **Author details**

*Soil Erosion - Rainfall Erosivity and Risk Assessment*

slopes, climatic conditions, and erodible soils.

cases, found to be expensive to build and maintain.

help, this project could not have been accomplished.

without their encouragement, I could not have written this.

population.

sustainable planning.

**Acknowledgements**

**Dedication**

In conclusion, this approach has allowed developing a planning program with successful techniques for soil erosion control in degraded areas linked to steep

It is obvious that this approach, based on ground measurements combined with geographic information systems, must be accompanied by a regular monitoring system by updating continuously the part of the spatial model derived from remote sensing. Furthermore, the stable part of the geospatial database consists of intrinsic factors (lithology, soil, drainage density, etc.) and the dynamic part to control includes biotic factors related to the soil occupation and needs evolution of the local

Although this analysis was conducted to the master plan of watershed development and has identified environmental constraints (soil and water degradation) characterizing priority areas, it is necessary to refine this analysis through a participatory action plan. Thus, this zonal analysis will specify for each year the interventions to be implemented and the financial package, by considering the needs and perspectives of the rural population. Moreover, the effectiveness of the proposed techniques can be limited especially if the local population is opposed or, in some

Finally, this research work demonstrates the potential and merits of spatial analysis techniques to evaluate the erosion risks. An indicative mapping designed for the management and risk prevention is obtained, to control the source and quality of input and to characterize the conditions of validity of the models. However, the difficulties encountered in the collection of quantitative damage data, usually, due to the lack of historical information, refer to the idea that it would be necessary to create an observatory and full database related to water erosion damage. Thus, research is needed to introduce also the temporal component (probability of erosion and return period) in a decision support perspective to implement a regional

This research paper was partially supported by the Identification and Modeling Laboratory of Natural Environment (LIMEN), Mohammadia School of Engineers in Mohammed V University (Morocco). I would also like to express my gratitude to some of my colleagues who were generous in providing guidance, and without their

I dedicate this paper to my parents Ahmed and Jamila, my sisters and my nephew Mouad, my dear family, and to the soul of my uncle Hassan Touissate. I also dedicate this modest work to my dear wife Ihsane, friends, and colleagues, and

**118**

Rabii El Gaatib1 \* and Abdelkader Larabi2

1 Ministry of Agriculture, Fisheries, Rural Development, Water and Forests, Rabat, Morocco

2 Regional Water Centre of Maghreb, Ecole Mohammadia d'Ingénieurs, Mohammed V University, Rabat, Morocco

\*Address all correspondence to: rabii\_elgaatib@yahoo.fr

© 2019 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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*Spatial Analysis of the Erosive Hazard of Soils and Natural Risks of Reservoir Siltation*

Available from: https://ecitydoc.com/ download/geo-observateur-n-21-centreroyal-de-teledetection-spatiale\_pdf

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*Spatial Analysis of the Erosive Hazard of Soils and Natural Risks of Reservoir Siltation DOI: http://dx.doi.org/10.5772/intechopen.89748*

[14] HCP High Commission for Planning. Evolution of Living Standards, Inequality and Poverty in Morocco; 2009. Available from: www. hcp.ma/file/111826 [Accessed: June 05, 2016]

[15] HCP High Commission for Planning. Socio-Demographic Indicators; 2010. Available from: www. hcp.ma/file/103089 [Accessed: June 05, 2016]

[16] High Commission for Planning. Regions of Morocco; 2010. Available from: www.hcp.ma/file/129637 [Accessed: June 05, 2016]

[17] Rabarimanana M,

Andriamasimanana R, Rasolomanana E, Robison L. Study of Vulnerability in Ihotry Watershed to Sheet Erosion. Madamines, ISSN 2220-0681, Vol. 4; 2012. 55p. Available from: https://www. scribd.com/document/362612713/ Madamines4-5 [Accessed: August 12, 2016]

[18] ESRI. ArcGIS Desktop: Tool Reference, Spatial Statistics Toolbox; 2014. Available from: http://help. arcgis.com/fr/arcgisdesktop/10.0/ help/005p/005p00000006000000.htm [Accessed: March 08, 2016]

[19] Emberger L. Climate Biogeographic Classification. Vol. 7. Collection of Botanical Geological and Zoological Laboratories Works, Montpellier Faculty of Sciences. 1945;**7**:3-43

[20] Rango A, Arnoldus HMJ Watershed Management. In: FAO Technical Manual; 1987. pp. 1-11

[21] El Gaatib R, Larabi A. Soil erosion effects on the natural resources of watersheds and the siltation condition of dam reservoirs: Application to OuedBeht watershed upstream of El Kansra dam (Morocco). Géo Observateur No. 21. Rabat; 2014:35-45. Available from: https://ecitydoc.com/ download/geo-observateur-n-21-centreroyal-de-teledetection-spatiale\_pdf

[22] El Gaatib R, Larabi A. Integrated evaluation of soil erosion hazard and risk management in the Oued Beht watershed using remote sensing and GIS techniques: Impacts on El Kansra dam siltation (Morocco). Journal of Geographic Information System. 2014;**6**:677-689. DOI: 10.4236/ jgis.2014.66056

[23] HydroEurope. Final Engineering Report. 2012. pp. 20-32. Available from: http://www. hydroeurope-team1.jennylestil. com/FinalEngineeringReport. pdf?forcedownload

[24] Roose E. Use of the universal soil loss equation to predict erosion in West Africa. In: Soil Erosion: Prediction and Control, Soil Conservation Society of America, Ankeny, Iowa, Special Publication No. 21; 1976. pp. 60-74. Available from: https://core.ac.uk/ download/pdf/39881180.pdf [Accessed: August 02, 2016]

[25] Roose E. Conservation des sols en zone méditarrénenne. Synthèse et proposition d'une nouvelle stratégie de lutte antiérosive: La Gestion et Conservation des Eaux et Sols (GCES). Centre ORSTOM Série Pédologie, Montpellier. 1991;**26**:145-181

**120**

*Soil Erosion - Rainfall Erosivity and Risk Assessment*

Tra\_d\_cm/09011.pdf [Accessed: August

[8] Roose E. Soil and water conservation lessons from steep slopes farming in French speaking countries of Africa. In: Moldenhauer WC, Hudson NW, editors. Conservation Farming on Steep Lands, Soil Conservation Society of America, Ankeny, Iowa; 1988. pp. 129-139. DOI:

10.1017/S0889189300003489

Washington DC; 1965

Washington DC; 1978

ird.fr/exl- doc/pleins\_textes/

[Accessed: August 11, 2016]

10.1051/lhb/1971014

[9] Wischmeier WH, Smith DD. Prediction rainfall erosion losses from cropland east of the Rocky Mountains: A guide for selection of practices for soil and water conservation. U.S. Department of Agriculture,

[10] Wischmeier W.H., Smith D.D. Prediction rainfall erosion losses, a guide to conservation planning science. U.S. Department of Agriculture,

[11] Francou J, Rodier JA. Classification Test of Maximum Floods Observed in the World. In: Cah. ORSTOM. ser. Hydrol, vol. IV(3). Paris; 1967. Available from: http://horizon.documentation.

pleins\_textes\_4/hydrologie/14846.pdf

[12] Guillot P, Duband D. The GRADEX Method for Calculating the Flood Probability from Rainfall, SHF, 10th Hydraulics Day, Question 1, Report 7, Paris; 1968. In: Guillot P, La Houille Blanche, N°3, 1971. pp. 209-218. DOI:

[13] MMAMF Moroccan Ministry of Agriculture and Marine Fisheries. General Census of Agriculture, Rabat; 1996. In: MMAMF. Atlas of Moroccan agriculture, Rabat; 2018. Available from: http://www.agriculture.gov.ma/sites/ default/files/ATLASsynthese.pdf

11, 2016]

[1] HCWFFAD High Commission for Water, Forest and Fight Against Desertification. National Watershed Management Plan. Rabat; 1996

[Accessed: August 15, 2016]

21, 2016]

18, 2016]

August 10, 2016]

[2] HCP High Commission for Planning. Socio-economic and Demographic Characteristics of the Population Based on the General Census Population and Housing. Rabat; 1994. Available from: http://bibliotheque.insee.net/index. php?lvl=notice\_display&id=147899

[3] HCP High Commission for Planning. General Census of Population and Housing; 2004. Available from: www. hcp.ma/file/111366 [Accessed: August

[4] HCP High Commission for Planning. Moroccan Statistical Yearbook; 2011. Available from: http://www.hcp.ma/ downloads/Annuaires-statistiquesregionaux\_t11956.html [Accessed: June

[5] WBAS Water Basin Agency of

Management Plan in the Sebou Watershed. Rabat; 2011. Available from: http://www.abhsebou.ma/ wp-content/uploads/2018/01/Pdairesebou-22-10-2015-.doc [Accessed:

Sebou ABHS. Integrated Water Resource

[6] Getis A, Ord JK. Analysis of Spatial Association by Use of Distance Statistics, Geographical Analysis. 1992; pp. 189- 206. Available from: www.archive. nefmc.org/tech/.../Getis-Ord%20 statistic.pdf [Accessed: August 10, 2016]

[7] Roose E. Erosion and Runoff in West Africa: Twenty Years of Measurements in Small Areas, Works and documents ORSTOM no. 78. Paris; 1977. ISBN 2-7099-0480-2. Available from: http:// horizon.documentation.ird.fr/exldoc/pleins\_textes/pleins\_textes\_6/

**References**

*Edited by Vlassios Hrissanthou and Konstantinos Kaffas*

In the first section of this book on soil erosion, an introduction to the soil erosion problem is presented. In the first part of the second section, rainfall erosivity is estimated on the basis of pluviograph records and cumulative rainfall depths by means of empirical equations and machine learning methods. In the second part of the second section, a physically-based, hydrodynamic, finite element model is described for the computation of surface runoff and channel flows. In the first part of the third section, the soil erosion risk is assessed in two different basins. In the second part of the third section, the soil erosion risk management in a basin is evaluated, and the delimitation of the areas requiring priority planning is achieved.

Published in London, UK © 2019 IntechOpen © rasikabendre / iStock

Soil Erosion - Rainfall Erosivity and Risk Assessment

Soil Erosion

Rainfall Erosivity and Risk Assessment

*Edited by Vlassios Hrissanthou* 

*and Konstantinos Kaffas*