Literature DB >> 31771846

Using the Budyko hypothesis for detecting and attributing changes in runoff to climate and vegetation change in the soft sandstone area of the middle Yellow River basin, China.

Huijuan Li1, Changxing Shi2, Yusheng Zhang3, Tingting Ning4, Pengcheng Sun5, Xiaofei Liu1, Xiaoqing Ma1, Wei Liu1, Adrian L Collins3.   

Abstract

Understanding catchment hydrological response to intensive land use/cover change (LUCC) and climate change provides a basis for taking effective measures for the future. Runoff is a critical indicator of catchment hydrological processes that reflects the combined effects of climate changes and local human activities. In this study, three main tributary sub-catchments underlain by soft sandstone in the Yellow River basin, China, were chosen to attribute runoff variations to climatic change and human activities through improving the Budyko elasticity model. The results suggested that: (1) annual runoff exhibited a significant decreasing trend during the past 30 years (1981-2016, p < 0.01),with an average decline rate of 1.07 mm a-1; (2) the precipitation elasticity of runoff (εP) and that of potential evapotranspiration (εEo) varied from 2.42 to 2.96 and from -1.96 to -1.42, respectively, indicating that runoff is more sensitive to changes in P than those in Eo in the context of climate change; (3) the attribution analysis demonstrated that, on average, vegetation change (mainly anthropogenic vegetation coverage increase) accounted for 92% of the decline in runoff whereas climate change (including precipitation and potential evapotranspiration variations and consequent vegetation change) accounted for the rest 8%.
Copyright © 2019 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Attribution analysis; Climate change; LUCC; Runoff change; Vegetation variation

Mesh:

Year:  2019        PMID: 31771846     DOI: 10.1016/j.scitotenv.2019.135588

Source DB:  PubMed          Journal:  Sci Total Environ        ISSN: 0048-9697            Impact factor:   7.963


  2 in total

1.  Attribution Assessment and Prediction of Runoff Change in the Han River Basin, China.

Authors:  Mengru Wei; Zhe Yuan; Jijun Xu; Mengqi Shi; Xin Wen
Journal:  Int J Environ Res Public Health       Date:  2022-02-18       Impact factor: 3.390

2.  Quantifying the effects of human activities and climate variability on runoff changes using variable infiltration capacity model.

Authors:  Qingling Bao; Jianli Ding; Lijing Han
Journal:  PLoS One       Date:  2022-09-01       Impact factor: 3.752

  2 in total

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