Ex Post Analysis of Water Supply Demand in an Agricultural Basin by Multi-Source Data Integration
Journal
Remote Sensing
ISSN
2072-4292
Date Issued
2021
Author(s)
Mario Lillo-Saavedra
Viviana Gavilán
Angel García-Pedrero
Consuelo Gonzalo-Martín
Felipe de la Hoz
Marcelo Somos-Valenzuela
Type
Resource Types::text::journal::journal article
URL Institutional Repository
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.
Cite this document
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
Subjects
data integration
;
multi-source data
;
water management
;
crop water demand
;
water availability
;
data integration
;
distributed database systems
;
economics
;
groundwater
;
water management
;
water supply
;
ex post analysis
;
groundwater system
;
multi-source data integrations
;
spatio-temporal scale
;
spatiotemporal information
;
supply and demand
;
water availability and demand
;
water-supply demand
;
information management