Assessing the evolution and attribution of watershed resilience in arid inland river basins, Northwest China

Yuehui Wang; Fengzhi Shi; Peng Yao; Yu Sheng; Chengyi Zhao

doi:10.1016/j.scitotenv.2023.167534

Assessing the evolution and attribution of watershed resilience in arid inland river basins, Northwest China

Sci Total Environ. 2024 Jan 1:906:167534. doi: 10.1016/j.scitotenv.2023.167534. Epub 2023 Oct 4.

Authors

Yuehui Wang¹, Fengzhi Shi², Peng Yao³, Yu Sheng³, Chengyi Zhao⁴

Affiliations

¹ State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China; Key Laboratory of Surficial Geochemistry, Ministry of Education, Department of Hydrosciences, School of Earth Sciences and Engineering, Nanjing University, Nanjing 210023, China.
² State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China; Akesu National Station of Observation and Research for Oasis Agro-ecosystem, Akesu 843017, Xinjiang, China; University of Chinese Academy of Sciences, Beijing 100049, China. Electronic address: shifz@ms.xjb.ac.cn.
³ State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China; Akesu National Station of Observation and Research for Oasis Agro-ecosystem, Akesu 843017, Xinjiang, China; University of Chinese Academy of Sciences, Beijing 100049, China.
⁴ School of Geographical Sciences, Nanjing University of Information Science and Technology, Nanjing 210044, China.

PMID: 37797763
DOI: 10.1016/j.scitotenv.2023.167534

Abstract

Water scarcity significantly limits the sustainable development of oasis economies in arid inland river basins. Quantifying watershed resilience and its drivers is a major focus in the fields of hydrology and water resources. In this study, the resilience indicator p_i represents watershed resilience, while meteorological, hydrological, socioeconomic, and ecological factors are used to investigate the spatial and temporal patterns of resilience and important driving factors in the Hotan River Basin from 1958 to 2020 by combining principal component analysis and random forest model. Results show that the overall resilience of the Hotan River Basin is low, decreasing from the upper (upstream) to the middle and lower (downstream) reaches, and that the intensity of human activities has a negative impact on resilience. Rivers are more likely to reach maximum resilience after experiencing periods of wet and dry conditions, although there is a lag in this progress. The random forest machine learning algorithm was used to accurately predict the resilience levels of the two upstream tributaries Yurungkash and Karakash Rivers, and the downstream Hotan River, with classification accuracies of 84.2 %, 71.4 %, and 87 %, respectively. The factors affecting the resilience of the Yurungkash River are the 30-day maximum, base flow index, low pulse duration, median streamflow in May, median streamflow in August, median streamflow in October, and 7-day maximum. The set of factors used to classify the resilience of the Karakash River include the 7-day maximum, 1-day maximum, median streamflow in June, 30-day maximum, 3-day maximum, median streamflow in February, and autumn temperature. The factors affecting the resilience of the Hotan River are the watershed inflow, Xiaota station runoff, population growth rate, and effective irrigated area. The findings of this study provide a theoretical basis for integrated water resource management and the sustainable development of the oasis economy in the Hotan River Basin.

Keywords: Driving mechanism; Hotan River Basin; Random forest (RF); Watershed resilience.