Sensitivity of water reallocation performance assessments to water use data

[EN] The lack of detailed and reliable data on the estimates of water use has been a key limitation in informing sustainable, equitable and efficient water reallocations in the agricultural sector. Conventional water use data have been commonly obtained from surveys or agronomic models, which have limitations on accurately reflecting the actual water use. This paper integrates cutting-edge satellite-based water use data with an ensemble of four Calibrated Mathematical Programming Models (CMPM) (one Positive Multi-Attribute Utility Programming model, one Weighted Goal Programming model, and two Positive Mathematical Programming models) to assess and compare the performance of water reallocations under satellite-based versus conventional water use estimates. We apply these methods to the water-stressed Mancha Oriental Aquifer (MOA) in central Spain, where we simulate the impacts of a hypothetical temporary water reacquisition policy in 2017, the last dry year in record. We find that water use estimates obtained with conventional approaches (which range between 4916 m3/ha and 4510m3/ha, on average) are 13–24 % lower than satellite-based estimates (5577 m3/ha on average) during the dry year. Moreover, the water reacquisition simulation using the CMPM ensemble shows that the reserve prices (25–66 % higher) and buyback costs (26–67 % higher) derived from conventional water use data approaches are consistently and significantly higher than those derived from satellite-based water use estimates for all the elements of the ensemble, suggesting that a policy informed with satellite-based data could significantly reduce the costs of the reallocation.

Authors

Publication Details

Journal
Water Resources and Economics
Published
2024-09-04
DOI
https://doi.org/10.1016/j.wre.2024.100252
Citations
2
Primary Topic
Water resources management and optimization
Type
article
Field-Weighted Citation Impact
0.67

Funders

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article

Sensitivity of water reallocation performance assessments to water use data

Jesús Garrido-Rubio, Ángel Sánchez Daniel, José González-Piqueras, Francesco Sapino et al.
2 citations
Water Resources and Economics
Water resources management and optimization
0.67
article

Sensitivity of water reallocation performance assessments to water use data

Jesús Garrido-Rubio, Ángel Sánchez Daniel, José González-Piqueras, Francesco Sapino, C. Dionisio Pérez‐Blanco, Laura Gil-García, Antonio Jesús Molina-Medina
article en
2 citations

Abstract

[EN] The lack of detailed and reliable data on the estimates of water use has been a key limitation in informing sustainable, equitable and efficient water reallocations in the agricultural sector. Conventional water use data have been commonly obtained from surveys or agronomic models, which have limitations on accurately reflecting the actual water use. This paper integrates cutting-edge satellite-based water use data with an ensemble of four Calibrated Mathematical Programming Models (CMPM) (one Positive Multi-Attribute Utility Programming model, one Weighted Goal Programming model, and two Positive Mathematical Programming models) to assess and compare the performance of water reallocations under satellite-based versus conventional water use estimates. We apply these methods to the water-stressed Mancha Oriental Aquifer (MOA) in central Spain, where we simulate the impacts of a hypothetical temporary water reacquisition policy in 2017, the last dry year in record. We find that water use estimates obtained with conventional approaches (which range between 4916 m3/ha and 4510m3/ha, on average) are 13–24 % lower than satellite-based estimates (5577 m3/ha on average) during the dry year. Moreover, the water reacquisition simulation using the CMPM ensemble shows that the reserve prices (25–66 % higher) and buyback costs (26–67 % higher) derived from conventional water use data approaches are consistently and significantly higher than those derived from satellite-based water use estimates for all the elements of the ensemble, suggesting that a policy informed with satellite-based data could significantly reduce the costs of the reallocation.

Water Resources and EconomicsVol. 48
Ministerio de Ciencia e Innovación, Horizon 2020, Partnership for Research and Innovation in the Mediterranean Area
Clean water and sanitation
Openalex Percentile: Top 32%
Water resources management and optimization
0.67
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