Case Studies
Oct 11, 2017

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

Publication: Journal of Hydrologic Engineering
Volume 22, Issue 12

Abstract

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.

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Acknowledgments

This study was supported by grants from the National Natural Science Foundation of China (Nos. 41471019 and 61661136006) and the National Key Research and Development Program of China (No. 2016YFA0600103).

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Go to Journal of Hydrologic Engineering
Journal of Hydrologic Engineering
Volume 22Issue 12December 2017

History

Received: Jan 8, 2017
Accepted: Jun 9, 2017
Published online: Oct 11, 2017
Published in print: Dec 1, 2017
Discussion open until: Mar 11, 2018

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Authors

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Master, State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing Science and Engineering, Faculty of Geographical Science, Beijing Normal Univ., Beijing 100875, China. E-mail: [email protected]
Xianhong Xie [email protected]
Associate Professor, State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing Science and Engineering, Faculty of Geographical Science, Beijing Normal Univ., Beijing 100875, China (corresponding author). E-mail: [email protected]
Shanshan Meng [email protected]
Ph.D. Candidate, State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing Science and Engineering, Faculty of Geographical Science, Beijing Normal Univ., Beijing 100875, China. E-mail: [email protected]

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