**2. Irrigation scheduling interactive platform**

The interactive platform developed integrates soil hydrodynamic characteristics relevant to irrigation scheduling, with crop water requirements, based on atmospheric evaporative demand and the evolution of crop leaf area index throughout the irrigation season, as well as with the irrigation system daily effective operation, in terms of actual water depths (expressed in mm or m3 /hectare, being 1 mm = 10 m3 /hectare) applied to each irrigated sector. Independently, information on the evolution of soil water content is also integrated, allowing next 5 days' irrigation schedules to be automatically modified, aiming to maintain continuous soil water availability conditions to the crop, if the soil profile water content trend is increasing or decreasing with respect to a specific target range [6, 9, 11, 18–20].

#### **2.1 Soil hydrodynamic properties relevant to irrigation scheduling**

The platform calculates the soil volume effectively providing water to crop roots, considering soil stratification depths and textures, and the integrated water volume stored at field capacity, calculated using the "Soil Water Characteristics Hydraulic Properties Calculator" [21], assuming that water distribution in the soil below each irrigation emitter forms an ellipsoid, with specific a, b, and c radii measured in soil observation trenches at the onset of the irrigation season [22, 23] (**Figure 1**). We have repeated soil water distribution field observations on a bimonthly basis, and for most soils, a, b, and c values remain fairly constant throughout the irrigation season.

Management of the allowed soil water depletion (MAD) by ETc [8, 9], defined as the percentage of soil water stored at field capacity in the effective soil water volume, is the threshold to initiate the next irrigation event; it considers soil root crop distribution and its water extraction pattern, rootstock relative drought resistance, as well as soil major texture class, crop value, and water costs; this threshold can also be modified according to specific crop phenology stages [19, 20].

The platform is programmed to schedule irrigation based on the "*variable frequency*—*variable water depth*" approach [4, 6, 7, 9, 13]; however, a maximal irrigation time value for each irrigation cycle is defined for each soil dominant structure, to avoid water percolation in lighter soils and to avoid surface water ponding or partial soil saturation in heavier soils. Thus, during high atmospheric evaporative demand periods, irrigation water depth equivalent to daily ETc in sandy soils determines the need of several watering events or cycles throughout the day, and in clay soils, irrigation is applied in 2–3 days cycle intervals, to replace the total water depth corresponding to Σ (daily ETc since the last irrigation event).

#### *Irrigation - Water Productivity and Operation, Sustainability and Climate Change*

#### **Figure 1.**

*Ellipsoid representing soil water distribution below a dripper.*

#### **2.2 Crop evapotranspiration (ETc) assessment**

The platform makes use of the modified FAO Penman-Monteith model [8, 9, 10, 13, 19, 24, 25] to define actual daily crop water use, as the product of site-specific atmospheric evaporative demand maximum value, assuming: (1) unlimited moisture availability and ambient atmospheric conditions, or potential evapotranspiration (ETp) [26] and (2) actual crop leaf area index, expressed as a crop coefficient function (Kc) [27–29].

#### *2.2.1 Potential ET (ETp)*

Daily potential ETp data are widely provided by government or private meteorological weather station services in significantly large irrigated areas around the world [8, 14]; additionally, the use of automatic weather stations at the farm is growing rapidly in many countries, because it represents a marginal additional investment in the context of pressurized irrigation systems. Weather stations world nets, like Climwat provided by FAO [30], or regional nets are useful sources of ETp major components' information (air temperature and humidity, solar radiation, and wind direction and intensity). Routine use of ETp data by farmers for irrigation scheduling purposes has not being widely adopted; extensive farm extension work on the subject is urgently needed, especially in areas with restricted water resources.

The representativeness of a single weather station to provide accurate ETp data is highly dependent on topography, crop surrounding areas cultivation pattern, due to albedo effects, as well as on microatmospheric specific conditions. Installation of at least one weather station every 100 hectares is highly recommended; moreover, daily ETp differences in relatively close spots within the irrigated field are highly correlated to one or two climatic parameters (i.e., maximal day temperature, or solar radiation), thus the use of single sensors adequately located, instead of complete weather stations, can be used accordingly [10, 12, 19].

Accurate ETp assessment using weather stations requires keeping adequate maintenance protocols, regarding sensor periodic cleaning and at least a yearly calibration [31]; the extended amount of data provided daily by a specific weather station must be addressed using big data analysis tools and models [16, 20], coupling it with actual data on the irrigation system operation, as well with soil water dynamics in the wetted soil volume, to fully achieve its potential aimed to provide continuous optimal conditions of soil water availability, coupled with water and energy savings.

**15**

**Figure 2.**

*The Kc = ƒ (phenology stage) function.*

*Agronomic Operation and Maintenance of Field Irrigation Systems*

Incorporating online, real-time weather sensors, with irrigation system sensors data (pressure and discharge, water pH and salinity) and soil water content data, is a useful example of the Internet of Things applied into farming decision-making processes; its rapid adoption by large number of farmers within a specific agriculture area could account for a positive and sound impact in smart water management [5, 11, 19, 20].

Actual water evapotranspirated by a crop (ETc) is not only determined by ETp; an estimation of transpiration canopy is also needed. This estimation corresponds to

[23, 28, 32]; for irrigation scheduling purposes, this concept is generally expressed as the "crop coefficient" (Kc) [27, 29, 33–35] which in fact is a time function, since IAF varies from bare soils at the end of winter (Kcinitial = 0.1–0.15), representing direct soil surface evaporation, up to Kcmax = 0.8–1.2), when the maximal IAF is attained. The Kc = (t) function can be represented by a double sigmoid curve (**Figure 2**) for the initial three crop phenology stages (budbreak, flowering, and veraison) [36, 37]; a constant maximal value from veraison to harvest, and a linear decline for the postharvest irrigation stage, reaching a Kcfinal = Kcinitial [37]. The maximal Kcmax value has been widely reported for most irrigated crops [27]; at

For irrigation scheduling, the Kc daily value is obtained from **Figure 2** or from an equivalent table; the main concern is related to the onset data for each phenology stage, which seldom can be predicted accurately from crop models and needs periodic field observations throughout the irrigation season. Modifying these dates on the platform is a very simple procedure and the Kc = ƒ (t) function is easily recalculated. Different crops and/or different cultivation locations for the same crop can have quite different Kc curve (**Figure 2**) shapes, due to the relative onset date and duration of each phenology stage, but essentially, this schematic representation

Data on the evolution of soil water content at specific depths and distances from the irrigation lateral enable the platform to automatically adjust Kc values for the next 5 days, with the aim to increment or reduce recommendations for next irrigation dates and water depths to be applied, in order to keep a constant soil water

**2.3 Automatic Kc value adjustments, based on soil water content data**

of transpiring leaves/m<sup>2</sup>

of cultivated land)

*DOI: http://dx.doi.org/10.5772/intechopen.84997*

*2.2.2 Crop ET coefficients [Kc = ƒ(crop phenology)]*

flowering [Kcflower = (Kcmax/Kcinitial)/2] [26, 38].

can be adapted to these differences.

the concept of leaf area index (IAF; m2

*Agronomic Operation and Maintenance of Field Irrigation Systems DOI: http://dx.doi.org/10.5772/intechopen.84997*

*Irrigation - Water Productivity and Operation, Sustainability and Climate Change*

**2.2 Crop evapotranspiration (ETc) assessment**

*Ellipsoid representing soil water distribution below a dripper.*

*2.2.1 Potential ET (ETp)*

**Figure 1.**

The platform makes use of the modified FAO Penman-Monteith model [8, 9, 10, 13, 19, 24, 25] to define actual daily crop water use, as the product of site-specific atmospheric evaporative demand maximum value, assuming: (1) unlimited moisture availability and ambient atmospheric conditions, or potential evapotranspiration (ETp) [26] and (2) actual crop leaf area index, expressed as a crop coefficient function (Kc) [27–29].

Daily potential ETp data are widely provided by government or private meteorological weather station services in significantly large irrigated areas around the world [8, 14]; additionally, the use of automatic weather stations at the farm is growing rapidly in many countries, because it represents a marginal additional investment in the context of pressurized irrigation systems. Weather stations world nets, like Climwat provided by FAO [30], or regional nets are useful sources of ETp major components' information (air temperature and humidity, solar radiation, and wind direction and intensity). Routine use of ETp data by farmers for irrigation scheduling purposes has not being widely adopted; extensive farm extension work on the subject is urgently needed, especially in areas with restricted water resources. The representativeness of a single weather station to provide accurate ETp data is highly dependent on topography, crop surrounding areas cultivation pattern, due to albedo effects, as well as on microatmospheric specific conditions. Installation of at least one weather station every 100 hectares is highly recommended; moreover, daily ETp differences in relatively close spots within the irrigated field are highly correlated to one or two climatic parameters (i.e., maximal day temperature, or solar radiation), thus the use of single sensors adequately located, instead of

complete weather stations, can be used accordingly [10, 12, 19].

Accurate ETp assessment using weather stations requires keeping adequate maintenance protocols, regarding sensor periodic cleaning and at least a yearly calibration [31]; the extended amount of data provided daily by a specific weather station must be addressed using big data analysis tools and models [16, 20], coupling it with actual data on the irrigation system operation, as well with soil water dynamics in the wetted soil volume, to fully achieve its potential aimed to provide continuous optimal conditions of soil water availability, coupled with water and

**14**

energy savings.

Incorporating online, real-time weather sensors, with irrigation system sensors data (pressure and discharge, water pH and salinity) and soil water content data, is a useful example of the Internet of Things applied into farming decision-making processes; its rapid adoption by large number of farmers within a specific agriculture area could account for a positive and sound impact in smart water management [5, 11, 19, 20].
