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Article

Exploiting High-Resolution Remote Sensing Soil Moisture to Estimate Irrigation Water Amounts over a Mediterranean Region

1
Department of Civil and Environmental Engineering, University of Perugia, via G. Duranti 93, 06125 Perugia, Italy
2
National Research Council, Research Institute for Geo-Hydrological Protection, via Madonna Alta 126, 06128 Perugia, Italy
3
Observatori de l’Ebre (OE), Ramon Llull University—CSIC, 43520 Roquetes, Spain
4
isardSAT, Parc Tecnològic Barcelona Activa, Carrer de Marie Curie, 8, 08042 Barcelona, Spain
*
Author to whom correspondence should be addressed.
Remote Sens. 2020, 12(16), 2593; https://doi.org/10.3390/rs12162593
Received: 23 June 2020 / Revised: 15 July 2020 / Accepted: 8 August 2020 / Published: 12 August 2020
Despite irrigation being one of the main sources of anthropogenic water consumption, detailed information about water amounts destined for this purpose are often lacking worldwide. In this study, a methodology which can be used to estimate irrigation amounts over a pilot area in Spain by exploiting remotely sensed soil moisture is proposed. Two high-resolution DISPATCH (DISaggregation based on Physical And Theoretical scale CHange) downscaled soil moisture products have been used: SMAP (Soil Moisture Active Passive) and SMOS (Soil Moisture and Ocean Salinity) at 1 km. The irrigation estimates have been obtained through the SM2RAIN algorithm, in which the evapotranspiration term has been improved to adequately reproduce the crop evapotranspiration over irrigated areas according to the FAO (Food and Agriculture Organization) model. The experiment exploiting the SMAP data at 1 km represents the main work analyzed in this study and covered the period from January 2016 to September 2017. The experiment with the SMOS data at 1 km, for which a longer time series is available, allowed the irrigation estimates to be extended back to 2011. For both of the experiments carried out, the proposed method performed well in reproducing the magnitudes of the irrigation amounts that actually occurred in four of the five pilot irrigation districts. The SMAP experiment, for which a more detailed analysis was performed, also provided satisfactory results in representing the spatial distribution and the timing of the irrigation events. In addition, the investigation into which term of the SM2RAIN algorithm plays the leading role in determining the amount of water entering into the soil highlights the importance of correct representation of the evapotranspiration process. View Full-Text
Keywords: irrigation estimates; remote sensing; soil moisture irrigation estimates; remote sensing; soil moisture
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MDPI and ACS Style

Dari, J.; Brocca, L.; Quintana-Seguí, P.; Escorihuela, M.J.; Stefan, V.; Morbidelli, R. Exploiting High-Resolution Remote Sensing Soil Moisture to Estimate Irrigation Water Amounts over a Mediterranean Region. Remote Sens. 2020, 12, 2593. https://doi.org/10.3390/rs12162593

AMA Style

Dari J, Brocca L, Quintana-Seguí P, Escorihuela MJ, Stefan V, Morbidelli R. Exploiting High-Resolution Remote Sensing Soil Moisture to Estimate Irrigation Water Amounts over a Mediterranean Region. Remote Sensing. 2020; 12(16):2593. https://doi.org/10.3390/rs12162593

Chicago/Turabian Style

Dari, Jacopo, Luca Brocca, Pere Quintana-Seguí, María J. Escorihuela, Vivien Stefan, and Renato Morbidelli. 2020. "Exploiting High-Resolution Remote Sensing Soil Moisture to Estimate Irrigation Water Amounts over a Mediterranean Region" Remote Sensing 12, no. 16: 2593. https://doi.org/10.3390/rs12162593

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