Irrigation represents a primary source of anthropogenic water consumption, whose effects impact on the natural distribution of water on the Earth’s surface and on food production. Over anthropized basins, irrigation often represents the missing variable to properly close the hydrological balance. Despite this, detailed information on the amounts of water actually applied for irrigation is lacking worldwide. In this study, a method to estimate irrigation volumes applied over a heavily irrigated area in the North East of Spain through high-resolution (1 km) remote sensing soil moisture is presented. Two DISPATCH (DISaggregation based on Physical And Theoretical scale CHange) downscaled data sets have been used: SMAP (Soil Moisture Active Passive) and SMOS (Soil Moisture and Ocean Salinity). The SMAP experiment covers the period from January 2016 to September 2017, while the SMOS experiment is referred to the time span from January 2011 to September 2017. The irrigation amounts have been retrieved through the SM2RAIN algorithm, in which the guidelines provided in the FAO (Food and Agriculture Organization) paper n.56 about the crop evapotranspiration have been implemented for a proper modeling of the crop evapotranspiration. A more detailed analysis has been performed in the context of the SMAP experiment. In fact, the spatial distribution and the temporal occurrence of the irrigation events have been investigated. Furthermore, the loss of accuracy of the irrigation estimates when using different sources for the evapotranspiration data has been assessed. In order to do this, the SMAP experiment has been repeated by forcing the SM2RAIN algorithm with several evapotranspiration data sets, both calculated and observed. Finally, the merging of the results obtained through the two experiments has produced a data set of almost 7 years of irrigation estimated from remote sensing soil moisture.

Irrigation Estimates from Remote Sensing Soil Moisture: A District-Scale Analysis in Spain

DARI J.
;
MORBIDELLI R.;SALTALIPPI C.;FLAMMINI A.;
2021

Abstract

Irrigation represents a primary source of anthropogenic water consumption, whose effects impact on the natural distribution of water on the Earth’s surface and on food production. Over anthropized basins, irrigation often represents the missing variable to properly close the hydrological balance. Despite this, detailed information on the amounts of water actually applied for irrigation is lacking worldwide. In this study, a method to estimate irrigation volumes applied over a heavily irrigated area in the North East of Spain through high-resolution (1 km) remote sensing soil moisture is presented. Two DISPATCH (DISaggregation based on Physical And Theoretical scale CHange) downscaled data sets have been used: SMAP (Soil Moisture Active Passive) and SMOS (Soil Moisture and Ocean Salinity). The SMAP experiment covers the period from January 2016 to September 2017, while the SMOS experiment is referred to the time span from January 2011 to September 2017. The irrigation amounts have been retrieved through the SM2RAIN algorithm, in which the guidelines provided in the FAO (Food and Agriculture Organization) paper n.56 about the crop evapotranspiration have been implemented for a proper modeling of the crop evapotranspiration. A more detailed analysis has been performed in the context of the SMAP experiment. In fact, the spatial distribution and the temporal occurrence of the irrigation events have been investigated. Furthermore, the loss of accuracy of the irrigation estimates when using different sources for the evapotranspiration data has been assessed. In order to do this, the SMAP experiment has been repeated by forcing the SM2RAIN algorithm with several evapotranspiration data sets, both calculated and observed. Finally, the merging of the results obtained through the two experiments has produced a data set of almost 7 years of irrigation estimated from remote sensing soil moisture.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11391/1492565
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