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Remote Sensing
Volume 13
Issue 11
10.3390/rs13112022
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Technical Note

Ex Post Analysis of Water Supply Demand in an Agricultural Basin by Multi-Source Data Integration

by
Mario Lillo-Saavedra
1,*,
Viviana Gavilán
1,
Angel García-Pedrero
2,3,
Consuelo Gonzalo-Martín
2,3,
Felipe de la Hoz
4,
Marcelo Somos-Valenzuela
5,6 and
Diego Rivera
7
1
Facultad de Ingeniería Agrícola, Universidad de Concepción, Chillán 3812120, Chile
2
Department of Computer Architecture and Technology, Universidad Politécnica de Madrid, 28660 Boadilla del Monte, Spain
3
Center for Biomedical Technology, Campus de Montegancedo, Universidad Politécnica de Madrid, 28233 Pozuelo de Alarcón, Spain
4
Centro del Agua para la Agricultura, Universidad de Concepción, San Fernando 3070000, Chile
5
Department of Forest Sciences, Faculty of Agriculture and Forest Sciences, Universidad de La Frontera, Av. Francisco Salazar 01145, Temuco 4780000, Chile
6
Butamallin Research Center for Global Change, Universidad de La Frontera, Av. Francisco Salazar 01145, Temuco 4780000, Chile
7
Centro de Sustentabilidad y Gestión Estratégica de Recursos (CiSGER), Facultad de Ingeniería, Universidad del Desarrollo, Las Condes 7610658, Chile
*
Author to whom correspondence should be addressed.
Remote Sens. 2021, 13(11), 2022; https://doi.org/10.3390/rs13112022
Submission received: 20 April 2021 / Revised: 13 May 2021 / Accepted: 14 May 2021 / Published: 21 May 2021
(This article belongs to the Special Issue Remote Sensing Data Fusion as a Strategy to Add Value to Earth Observation Data)
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Abstract

In this work, we present a new methodology integrating data from multiple sources, such as observations from the Landsat-8 (L8) and Sentinel-2 (S2) satellites, with information gathered in field campaigns and information derived from different public databases, in order to characterize the water demand of crops (potential and estimated) in a spatially and temporally distributed manner. This methodology is applied to a case study corresponding to the basin of the Longaví River, located in south-central Chile. Potential and estimated demands, aggregated at different spatio-temporal scales, are compared to the streamflow of the Longaví River, as well as extractions from the groundwater system. The results obtained allow us to conclude that the availability of spatio-temporal information on the water availability and demand pairing allows us to close the water gap—i.e., the difference between supply and demand—allowing for better management of water resources in a watershed.
Keywords: data integration; multi-source data; water management; crop water demand; water availability data integration; multi-source data; water management; crop water demand; water availability
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MDPI and ACS Style

Lillo-Saavedra, M.; Gavilán, V.; García-Pedrero, A.; Gonzalo-Martín, C.; de la Hoz, F.; Somos-Valenzuela, M.; Rivera, D. Ex Post Analysis of Water Supply Demand in an Agricultural Basin by Multi-Source Data Integration. Remote Sens. 2021, 13, 2022. https://doi.org/10.3390/rs13112022

AMA Style

Lillo-Saavedra M, Gavilán V, García-Pedrero A, Gonzalo-Martín C, de la Hoz F, Somos-Valenzuela M, Rivera D. Ex Post Analysis of Water Supply Demand in an Agricultural Basin by Multi-Source Data Integration. Remote Sensing. 2021; 13(11):2022. https://doi.org/10.3390/rs13112022

Chicago/Turabian Style

Lillo-Saavedra, Mario, Viviana Gavilán, Angel García-Pedrero, Consuelo Gonzalo-Martín, Felipe de la Hoz, Marcelo Somos-Valenzuela, and Diego Rivera. 2021. "Ex Post Analysis of Water Supply Demand in an Agricultural Basin by Multi-Source Data Integration" Remote Sensing 13, no. 11: 2022. https://doi.org/10.3390/rs13112022

APA Style

Lillo-Saavedra, M., Gavilán, V., García-Pedrero, A., Gonzalo-Martín, C., de la Hoz, F., Somos-Valenzuela, M., & Rivera, D. (2021). Ex Post Analysis of Water Supply Demand in an Agricultural Basin by Multi-Source Data Integration. Remote Sensing, 13(11), 2022. https://doi.org/10.3390/rs13112022

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