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1 Hu, Z.; Zhang, Z.; Sang, Y.-F.; Qian, J.; Feng, W.; Chen, X.; Zhou, Q. 2021. Temporal and spatial variations in the terrestrial water storage across Central Asia based on multiple satellite datasets and global hydrological models. Journal of Hydrology, 596:126013. [doi: https://doi.org/10.1016/j.jhydrol.2021.126013]
Water storage ; Datasets ; Satellite observation ; Hydrology ; Models ; Precipitation ; Temperature ; Evapotranspiration ; Soil moisture ; Arid regions ; Water resources ; Sustainable Development Goals ; River basins ; Lakes ; Spatial distribution ; Forecasting ; Uncertainty / Central Asia / Kazakhstan / Turkmenistan / Uzbekistan / Tajikistan / Kyrgyzstan / Aral Sea Basin / Balkhash Lake / Issyk-Kul Lake
(Location: IWMI HQ Call no: e-copy only Record No: H050341)
(7.60 MB)
Arid regions of Central Asia have sensitive ecosystems that rely heavily on terrestrial water storage which is composed of surface water storage, soil moisture storage and groundwater storage. Therefore, we employed three Gravity Recovery and Climate Experiment (GRACE) satellite datasets and five global hydrological models (GHMs) to explore the terrestrial water storage (TWS) changes over arid regions of Central Asia from 2003 to 2014. We observed significantly decreasing water storage trends in the GRACE data, which were underestimated by the GHMs. After averaging the three GRACE satellite datasets, we found that the water storage was decreasing at a rate of -4.74 mm/year. Contrary to the prevailing declining water storage trends, northeastern Kazakhstan (KAZ), and southern Xinjiang increased their water storage over the same period. The GRACE data showed that Turkmenistan (TKM), Uzbekistan (UZB) and KAZ experienced the most severe water depletions, while Tajikistan (TJK) and northwest China (NW) experienced the least significant depletions. With respect to the major river and lake basins, the Aral Sea Basin exhibited the most serious water loss (-0.60 mm/month to -0.38 mm/month). The water storage positively correlates with the precipitation; and negatively correlates, with a three-month lag, with temperature and potential evapotranspiration (PET). Partial least square regression (PLSR) had the high capability in simulating and predicting the TWS. These results provide scientific evidence and guidance for local policy makers working toward sustainable water resource management, and the resolution of international water resource disputes among Central Asian countries.
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