Assessing Spatio-Temporal Dynamics of Deep Percolation Using Crop Evapotranspiration Derived from Earth Observations through Google Earth Engine

Abstract

Excess irrigation may result in deep percolation and nitrate transport to groundwater. Furthermore, under Mediterranean climate conditions, heavy winter rains often result in high deep percolation, requiring the separate identification of the two sources of deep percolated water. An integrated methodology was developed to estimate the spatio-temporal dynamics of deep percolation, with the actual crop evapotranspiration (ETc act) being derived from satellite images data and processed on the Google Earth Engine (GEE) platform. GEE allowed to extract time series of vegetation indices derived from Sentinel-2 enabling to define the actual crop coefficient (Kc act) curves based on the observed lengths of crop growth stages. The crop growth stage lengths were then used to feed the soil water balance model ISAREG, and the standard Kc values were derived from the literature; thus, allowing the estimation of irrigation water requirements and deep drainage for independent Homogeneous Units of Analysis (HUA) at the Irrigation Scheme. The HUA are defined according to crop, soil type, and irrigation system. The ISAREG model was previously validated for diverse crops at plot level showing a good accuracy using soil water measurements and farmers’ irrigation calendars. Results show that during the crop season, irrigation caused 11 ± 3% of the total deep percolation. When the hotspots associated with the irrigation events corresponded to soils with low suitability for irrigation, the cultivated crop had no influence. However, maize and spring vegetables stood out when the hotspots corresponded to soils with high suitability for irrigation. On average, during the off-season period, deep percolation averaged 54 ± 6% of the annual precipitation. The spatial aggregation into the Irrigation Scheme scale provided a method for earth-observation-based accounting of the irrigation water requirements, with interest for the water user’s association manager, and at the same time for the detection of water losses by deep percolation and of hotspots within the irrigation scheme.

Methodologies for Water Accounting at the Collective Irrigation System Scale Aiming at Optimizing Water Productivity

“…Quantify/estimate the amount of water used/needed for irrigation within the irrigation perimeter (which we designate as irrigation requirements at the source, SIR) by identifying the water requirements of different crop patterns [106]. ii.…”

Framework for Assessing Collective Irrigation Systems Resilience to Climate Change—The Maiorga Case Study

“…Examples of application include those to field crops [54,55], pastures [56], vegetable crops [57,58], and orchards [59,60]. Furthermore, the model has been used for the assessment of climate change on irrigation water requirements (e.g., [61,62]) and for irrigation management at Collective Irrigation System [63,64] and basin level [65].…”