**1. Introduction**

Soil is a prerequisite for food production [1] especially at the wake of rapidly increasing world population placing a high demand for food resulting to agricultural intensification globally. However, food productivity is fast declining due to increased soil degradation [2]. Often, rapid land use transformation, for example, conversion of forests to agricultural land results to soil degradation which normally takes four main forms: water erosion; wind erosion; chemical degradation; and physical degradation. Each form of soil degradation, occurring both individually and in combination with the other forms, can result in the loss or damage to key ecosystem functions and processes [3–5]. Among the four forms of soil degradation, erosion by water is the most common which occurs in all agro-climatic zones and is widely considered to be a serious threat to the long-term agricultural production in many parts of the world [6–8]. It is a primary

agent of soil degradation [9], affecting 1094 million ha, or roughly 56% of the land experiencing human-induced degradation worldwide [2, 10, 11]. Soil erosion has also been recognised to be the major non-point pollution source in many areas, which causes a large amount of damage every year [6, 12].

Soil erosion, considered as the most widespread form of soil degradation, has greatly affected agricultural production globally and in particular, Sub Saharan Africa [2, 6, 11, 13–16]. One-third of arable land globally has been estimated to have been lost over the last four decades due to soil erosion [2, 11] at a rate of over 10 million hectares per year [4]. Soil erosion by water dislodges soil particles from the surface due to impact of rain drops [14, 17, 18] which generate enough power to carry the particles far away causing sedimentation of water bodies [16, 19] and other environmental hazards [4, 20, 21]. These negative environmental effects usually deprive soil its capacity to perform its functions and the links between soil and other ecosystem components [2].

Soil erosion by water is sometimes considered to be a purely natural process caused by rainfall and water flow [4]; however human activities greatly aggravate the erosion through alteration of land cover and disturbance of soil structure through cultivation [2, 5, 11].

The main physical parameters influencing the intensity of erosion processes are climate regime, soil characteristics, topography and vegetation. Apart from these physical parameters, man and man-induced land use often have a significant influence on erosion intensity. When the protection of the natural vegetation cover is replaced by a temporary cover such as during the cultivation cycle, the erosion intensity might increase significantly [22]. Wischmeier and Smith [23] noted six (6) factors that affect soil erosion which include rainfall erosivity, soil erodibility, slope length and angle, crop management and conservation practices.

Assessment of soil erosion remains critical as it enables different players to formulate mitigation measures [4]. Various methods employed in assessing soil erosion either by water or wind - vary depending on the causes, magnitude of erosion and on the scale of assessment as well as the applicability of the methods in different environments [8, 21, 24]. The most common methods of assessment are: expert opinions, land users' opinions [25, 26], field monitoring, observations and measurement, modelling [27, 28], estimates of productivity changes and remote sensing [29, 30].

The soil loss prediction models include Universal Soil Loss Equation (USLE), Revised Universal Soil Loss Equation (RUSLE), and Soil Loss Estimation Model for Southern Africa (SLEMSA) and can be helpful in designing sustainable land use practices in order to curb soil erosion menace [6, 11, 20]. These methods differ in their use and application depending on various factors such as the intentions for use; characteristics of study area; data requirement and availability; validity and reliability of the method [16, 21, 26]. These mathematical models are continually being improved and scientists from many countries have adopted them to meet the requirements of their local conditions [24, 31].

The USLE model is widely used to predict average annual rate of soil erosion based on rainfall intensity, type of soil, slope steepness, crop and soil management practices [7, 8, 16, 21, 24, 28, 31]. It is based on the product of rainfall-runoff erosivity (R), soil erodibility (K), slope length and steepness (LS), surface cover and management (C) and supporting conservation practices (P) [7, 21]. Nontananandh and Changnoi [10] noted that USLE requires relatively simple data and it is compatible with a geographic information system (GIS). Several studies point out that USLE remains the best available model that has been tested in virtually all environments of the world in spite *Spatial Soil Loss Assessment Using USLE in Lake Ol Bolossat Catchment DOI: http://dx.doi.org/10.5772/intechopen.112129*

of having been criticised and accused of giving erroneous results [17, 19, 28, 31]. The main criticism of the USLE has emanated from people having applied the model in environments in which it was not intended to be used [31]. This study aimed at assessing spatial soil loss using USLE model and GIS in Lake Ol Bolossat Catchment.
