Modeling the Responses of Water and Sediment Discharge to Climate Change in the Upper Yellow River Basin, China

作者:Yu, X (Yu, Xiao)[ 1 ] ; Xie, XH (Xie, Xianhong)[ 1 ] ; Meng, SS (Meng, Shanshan)[ 1 ]

JOURNAL OF HYDROLOGIC ENGINEERING

卷: 22  期: 12

文献号: 05017026

DOI: 10.1061/(ASCE)HE.1943-5584.0001590

出版年: DEC 2017

摘要

The Yellow River is the largest sandy river in the world with an annual transport capacity of approximately 1.6 billion tons. There is growing concern of water availability and soil erosion in this basin. Understanding the runoff regime and sediment transport in the upper Yellow River basin (UYRB), especially in the context of climate change, is crucial for sustainable water resource management and soil-water conservation. Herein, the authors attempt to quantify the response of water and sediment discharge to climate change in the UYRB. The authors employed a distributed hydrological model, i.e., the Soil and Water Assessment Tool (SWAT), to simulate the runoff and sediment load under different scenarios, including climate change and detrended climate conditions. To predict the future trend, the authors designed scenarios based on downscaled forcing data from three global climate models (GCMs) which are with respect to the representative concentration pathway 8.5 (RCP8.5) of the Coupled Model Intercomparison Project Phase 5 (CMIP5). In response to the decrease in precipitation and increase in temperature from 1966 to 2009, annual runoff and sediment load have significantly decreased at a rate of -11.6 mm/decade and -1.3 Mt/decade, respectively. Precipitation plays a dominant role in reshaping these trends, with a contribution more than four times greater than that of temperature. Moreover, sediment yields may decline in the near future (2049-2064), especially during late summer and early fall. Runoff change holds substantial uncertainty owing to the different projection based on the GCMs. (C) 2017 American Society of Civil Engineers.

通讯作者地址: Xie, XH (通讯作者)

       Beijing Normal Univ, Inst Remote Sensing Sci & Engn, Fac Geog Sci, State Key Lab Remote Sensing Sci, Beijing 100875, Peoples R China.

地址:

       [ 1 ] Beijing Normal Univ, Inst Remote Sensing Sci & Engn, Fac Geog Sci, State Key Lab Remote Sensing Sci, Beijing 100875, Peoples R China