文章基本信息

标题：Climate Change Impacts on Extreme Flows Under IPCC RCP Scenarios in the Mountainous Kaidu Watershed, Tarim River Basin
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作者：Yue Huang ; Yonggang Ma ; Tie Liu 等
期刊名称：Sustainability
印刷版ISSN：2071-1050
出版年度：2020
卷号：12
期号：5
页码：2090
DOI：10.3390/su12052090
语种：English
出版社：MDPI, Open Access Journal
摘要：In the 21st century, heavier rainfall events and warmer temperatures in mountainous regions have significant impacts on hydrological processes and the occurrence of flood/drought extremes. Long-term modeling and peak flow detection of streamflow series are crucial in understanding the behavior of flood and drought. This study was conducted to analyze the impacts of future climate change on extreme flows in the Kaidu River Basin, northwestern China. The soil water assessment tool (SWAT) was used for hydrological modeling. The projected future precipitation and temperature under Intergovernmental Panel on Climate Change (IPCC) representative concentration pathway (RCP) scenarios were downscaled and used to drive the validated SWAT model. A generalized extreme value (GEV) distribution was employed to assess the probability distribution of flood events. The modeling results showed that the simulated discharge well matched the observed ones both in the calibration and validation periods. Comparing with the historical period, the ensemble with 15 general circulation models (GCMs) showed that the annual precipitation will increase by 7.9#8722;16.1% in the future, and extreme precipitation events will increase in winter months. Future temperature will increase from 0.42 #176;C/10 a to 0.70 #176;C/10 a. However, with respect to the hydrological response to climate change, annual mean runoff will decrease by 21.5#8722;40.0% under the mean conditions of the four RCP scenarios. A reduction in streamflow will occur in winter, while significantly increased discharge will occur from April to May. In addition, designed floods for return periods of five, 10 and 20 years in the future, as predicted by the GEV distribution, will decrease by 3#8722;20% over the entire Kaidu watershed compared to those in the historical period. The results will be used to help local water resource management with hazard warning and flood control.