Rapidly declining surface and terrestrial water resources in Central Asia driven by socio-economic and climatic changes.

Sci Total Environ

State Key Laboratory of Desert & Oasis Ecology, Xinjiang Institute of Ecology & Geography, Chinese Academy of Sciences, Urumqi 830010, China.

Published: August 2021


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Article Abstract

A systematic understanding of the dynamics of surface water resources and terrestrial water storage (TWS) is extremely important for human survival in Central Asia (CA) and maintaining the balance of regional ecosystems. Although several remote sensing products have been used to map surface water, the spatial resolution of some of them (hundreds of meters) is not sufficient to identify small surface water bodies, with monitoring data only being available for a few years or less. Thus, long-term continuous monitoring of surface water dynamics has not yet been achieved. To address this, we used all available Landsat images and the adjacent-years interpolation method to describe the dynamics of surface water in CA with a 30-m spatial resolution during 1990-2019. Subsequently, based on the multiple stepwise regression model, the climatic changes and human activity drivers affecting the surface water were systematically assessed. The permanent surface water areas (PSWA) of downstream countries with water scarcity decreased over time. The PSWA of Kazakhstan continues to decline at a maximum rate of 1189 km/a. Additionally, human activities represented by population and reservoir areas are the dominant drivers affecting surface water resources in CA. The relationship between TWS and PSWA in CA and the constraints on social and economic development provided by the available water resources are discussed. The findings demonstrate that more than one-third of the croplands in CA are suffering from declining SWAs and TWS. The water crisis in CA has intensified, and the spatial mismatch between water and land resources is expected to remain one of the biggest challenges for future social and economic development in CA. Our dataset and findings provide high-precision surface water dynamics data that could be valuable for mitigating the water crisis in CA and provide a current scientific reference for achieving the United Nations' Sustainable Development Goals.

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http://dx.doi.org/10.1016/j.scitotenv.2021.147193DOI Listing

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