Irrigation is the most impacting and uncertain human intervention on the water resource. The possibility of retrieving information on irrigation practices through remote sensing technology opens unprecedented perspectives on the monitoring of anthropized basins. This study is aimed at assessing the impact of different approaches to model the contribution of the evapotranspiration in retrieving the amounts of water applied for irrigation through a soil-moisture-based (SM-based) inversion algorithm; such a contribution is conclusive especially over semi-arid regions. Three modeling approaches relying on both calculated and remotely sensed actual and potential evapotranspiration (ET and PET) data sets were implemented to represent the evapotranspiration rate within the SM-based inversion method, which allows backward estimation of irrigation through the soil water balance inversion. By combining the different evapotranspiration data sources and modeling approaches, seven experiments aimed at inverting DISPATCH (DISaggregation based on Physical And Theoretical scale CHange) downscaled SMAP (Soil Moisture Active Passive) soil moisture at 1 km to estimate irrigation over four heavily irrigated agricultural districts located in Spain (Aragon and Catalonia) were compared. The results highlighted that the application of the FAO56 guidelines parametrization relying on the use of optical data as proposed by the authors in a previous study remains the most reliable configuration. In fact, the implementation of a simplified approach not considering the transpiration component of the specific crop led to irrigation underestimates. Finally, it is interesting to note that the application of the method with remotely sensed ET from MODIS (MODerate-resolution Imaging Spectroradiometer) produced reliable district-aggregated irrigation estimates, thus opening the perspective of an algorithm configuration forced with remote sensing data only.

Irrigation estimates from space: Implementation of different approaches to model the evapotranspiration contribution within a soil-moisture-based inversion algorithm

Dari, Jacopo
Investigation
;
Morbidelli, Renato
Supervision
;
Saltalippi, Carla
Writing – Review & Editing
;
Flammini, Alessia
Writing – Review & Editing
;
2022

Abstract

Irrigation is the most impacting and uncertain human intervention on the water resource. The possibility of retrieving information on irrigation practices through remote sensing technology opens unprecedented perspectives on the monitoring of anthropized basins. This study is aimed at assessing the impact of different approaches to model the contribution of the evapotranspiration in retrieving the amounts of water applied for irrigation through a soil-moisture-based (SM-based) inversion algorithm; such a contribution is conclusive especially over semi-arid regions. Three modeling approaches relying on both calculated and remotely sensed actual and potential evapotranspiration (ET and PET) data sets were implemented to represent the evapotranspiration rate within the SM-based inversion method, which allows backward estimation of irrigation through the soil water balance inversion. By combining the different evapotranspiration data sources and modeling approaches, seven experiments aimed at inverting DISPATCH (DISaggregation based on Physical And Theoretical scale CHange) downscaled SMAP (Soil Moisture Active Passive) soil moisture at 1 km to estimate irrigation over four heavily irrigated agricultural districts located in Spain (Aragon and Catalonia) were compared. The results highlighted that the application of the FAO56 guidelines parametrization relying on the use of optical data as proposed by the authors in a previous study remains the most reliable configuration. In fact, the implementation of a simplified approach not considering the transpiration component of the specific crop led to irrigation underestimates. Finally, it is interesting to note that the application of the method with remotely sensed ET from MODIS (MODerate-resolution Imaging Spectroradiometer) produced reliable district-aggregated irrigation estimates, thus opening the perspective of an algorithm configuration forced with remote sensing data only.
2022
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11391/1502894
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