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Advisor(s)
Abstract(s)
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
Description
Keywords
crop coefficient irrigation water requirements irrigation scheme Sentinel-2 soil water balance model vegetation indices
Pedagogical Context
Citation
Ferreira, A.; Rolim, J.; Paredes, P.; Cameira, M.d.R. Assessing Spatio-Temporal Dynamics of Deep Percolation Using Crop Evapotranspiration Derived from Earth Observations through Google Earth Engine. Water 2022, 14, 2324
Publisher
MDPI