Quantifying water evaporation from large reservoirs: Implications for water management in water-stressed regions
Nevermann, Hannes, Aminzade, Milad, Madani, Kaveh and Shokri, Nima, (2024). Quantifying water evaporation from large reservoirs: Implications for water management in water-stressed regions. Environmental Research, 262(1), 119860-n/a
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Article
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Sub-type Journal article Author Nevermann, Hannes
Aminzade, Milad
Madani, Kaveh
Shokri, NimaTitle Quantifying water evaporation from large reservoirs: Implications for water management in water-stressed regions Appearing in Environmental Research Volume 262 Issue No. 1 Publication Date 2024-09-07 Place of Publication Amesterdam Publisher Elsevier B.V. Start page 119860 End page n/a Language eng Abstract Dam reservoirs are at the core of local water storage and supply, especially in water-stressed regions of the world with acute water shortage problems. However, evaporative losses from these reservoirs and their storage efficiency are often overlooked in water budgeting. We offer a mechanistic approach that combines physically-based modeling with remote sensing information of reservoir characteristics to reliably predict evaporative losses from dam reservoirs. The developed framework is used to predict evaporative water losses from potential dam reservoirs in different basins worldwide. We apply this framework to 10 of the largest dam reservoirs in the world's water-stressed regions to quantify evaporative water losses. Our analysis, spanning from 2000 to 2020, reveals considerable variations in annual evaporation rates in the reservoirs located in water-deprived regions exceeding 3200 mm/year during the study period with the total evaporative loss reaching 26.5 km3/year. The evaporative water loss accounts up to 15.8% of the storage capacity in one of the dam reservoirs, posing significant challenges for water allocation and conservation strategies, with notable economic and environmental consequences in regions already suffering from water scarcity. Copyright Holder author(s) Copyright Year 2024 Copyright type All rights reserved DOI https://doi.org/10.1016/j.envres.2024.119860 -
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