State Key Laboratory of Desert & Oasis Ecology, Xinjiang Institute of Ecology & Geography, Chinese Academy of Sciences, Urumqi 830010, China; University of Chinese Academy of Sciences, Beijing 10049, China.
State Key Laboratory of Desert & Oasis Ecology, Xinjiang Institute of Ecology & Geography, Chinese Academy of Sciences, Urumqi 830010, China; University of Chinese Academy of Sciences, Beijing 10049, China.
Sci Total Environ. 2021 Aug 25;784:147193. doi: 10.1016/j.scitotenv.2021.147193. Epub 2021 Apr 18.
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.
系统地了解地表水和陆地水储量(TWS)的动态对于中亚(CA)地区人类的生存和维持区域生态系统的平衡至关重要。尽管已经使用了几种遥感产品来绘制地表水,但其中一些产品(数百米)的空间分辨率不足以识别小的地表水,而且监测数据仅可用几年或更短时间。因此,还没有实现对地表水动态的长期连续监测。为了解决这个问题,我们使用了所有可用的 Landsat 图像和相邻年份的插值方法,以 30 米的空间分辨率描述了 1990-2019 年 CA 地表水的动态。随后,基于多元逐步回归模型,系统评估了影响地表水的气候变化和人类活动驱动因素。下游水资源短缺国家的永久性地表水面积(PSWA)随时间减少。哈萨克斯坦的 PSWA 继续以每年 1189 公里的最大速度下降。此外,以人口和水库面积为代表的人类活动是影响 CA 地表水的主要驱动因素。CA 地区 TWS 与 PSWA 的关系以及可用水资源对社会经济发展的制约进行了讨论。研究结果表明,CA 地区超过三分之一的耕地正在遭受 SWAs 和 TWS 的减少。CA 的水危机加剧,水资源与土地资源之间的空间不匹配预计将成为 CA 未来社会经济发展的最大挑战之一。我们的数据集和研究结果提供了高精度的地表水动态数据,对于缓解 CA 的水危机可能具有重要价值,并为实现联合国可持续发展目标提供了当前的科学参考。