{"title":"Climate warming positively affects hydrological connectivity of typical inland river in arid Central Asia","authors":"Chuanxiu Liu, Yaning Chen, Wenjing Huang, Gonghuan Fang, Zhi Li, Chenggang Zhu, Yongchang Liu","doi":"10.1038/s41612-024-00800-4","DOIUrl":null,"url":null,"abstract":"Hydrological connectivity is crucial for understanding water-ecosystem dynamics, as it serves as a key link between different landscape units. However, the variability of hydrological connectivity in Central Asia remains unexplored, which poses challenges to a comprehensive understanding of ecohydrological processes. This study investigates the spatiotemporal patterns and driving mechanisms of hydrological connectivity in the Tarim River Basin (TRB), Central Asia, from 1990 to 2020, employing a novel approach that integrates remote sensing and reanalysis data. The results indicate an increasing trend in the hydrological connectivity index (HCI), with approximately 60% of the TRB exhibiting significant increases. Climate change exerts the greatest direct (0.59) and total (0.64) effects on HCI, with potential evapotranspiration (19.2%) and temperature (12.6%) being the dominant factors. In mountainous regions, climate change (0.65) is the primary driver, while human activities have a greater impact in the plains (−0.27). These findings offer a new framework for studying ecohydrological processes in arid regions.","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":" ","pages":"1-12"},"PeriodicalIF":8.5000,"publicationDate":"2024-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41612-024-00800-4.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"npj Climate and Atmospheric Science","FirstCategoryId":"89","ListUrlMain":"https://www.nature.com/articles/s41612-024-00800-4","RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"METEOROLOGY & ATMOSPHERIC SCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
Hydrological connectivity is crucial for understanding water-ecosystem dynamics, as it serves as a key link between different landscape units. However, the variability of hydrological connectivity in Central Asia remains unexplored, which poses challenges to a comprehensive understanding of ecohydrological processes. This study investigates the spatiotemporal patterns and driving mechanisms of hydrological connectivity in the Tarim River Basin (TRB), Central Asia, from 1990 to 2020, employing a novel approach that integrates remote sensing and reanalysis data. The results indicate an increasing trend in the hydrological connectivity index (HCI), with approximately 60% of the TRB exhibiting significant increases. Climate change exerts the greatest direct (0.59) and total (0.64) effects on HCI, with potential evapotranspiration (19.2%) and temperature (12.6%) being the dominant factors. In mountainous regions, climate change (0.65) is the primary driver, while human activities have a greater impact in the plains (−0.27). These findings offer a new framework for studying ecohydrological processes in arid regions.
期刊介绍:
npj Climate and Atmospheric Science is an open-access journal encompassing the relevant physical, chemical, and biological aspects of atmospheric and climate science. The journal places particular emphasis on regional studies that unveil new insights into specific localities, including examinations of local atmospheric composition, such as aerosols.
The range of topics covered by the journal includes climate dynamics, climate variability, weather and climate prediction, climate change, ocean dynamics, weather extremes, air pollution, atmospheric chemistry (including aerosols), the hydrological cycle, and atmosphere–ocean and atmosphere–land interactions. The journal welcomes studies employing a diverse array of methods, including numerical and statistical modeling, the development and application of in situ observational techniques, remote sensing, and the development or evaluation of new reanalyses.