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Quantitative Assessment of the Contribution of Climate and Underlying Surface Change to Multiscale Runoff Variation in the Jinsha River Basin, China

Shuaijun Yue, Guangxing Ji, Junchang Huang (huangjc1014@henau.edu.cn), Mingyue Cheng, Yulong Guo and Weiqiang Chen
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Shuaijun Yue: College of Resources and Environment, Henan Agricultural University, Zhengzhou 450046, China
Guangxing Ji: College of Resources and Environment, Henan Agricultural University, Zhengzhou 450046, China
Junchang Huang: College of Resources and Environment, Henan Agricultural University, Zhengzhou 450046, China
Mingyue Cheng: College of Resources and Environment, Henan Agricultural University, Zhengzhou 450046, China
Yulong Guo: College of Resources and Environment, Henan Agricultural University, Zhengzhou 450046, China
Weiqiang Chen: College of Resources and Environment, Henan Agricultural University, Zhengzhou 450046, China

Land, 2023, vol. 12, issue 8, 1-16

Abstract: Many studies quantify the impact of climate change and human activities on runoff changes on an annual scale, but few studies have examined this on multiple time scales. This paper quantifies the contribution of different factors to the variability of Jinsha River runoff at multiple time scales (annual, seasonal and monthly). First, the trend analysis of Jinsha River runoff is carried out, and the Mann–Kendall mutation test was then applied to the runoff data for mutation analysis. According to the mutation year, the research period is divided into the base period and the mutation period. By constructing an ABCD hydrological model simulation and monthly scale Budyko model, the contribution rate of human and climate factors to the multitime-scale runoff of Jinsha River is calculated. The results showed that: (1) The sudden year of change in the Jinsha River runoff is 1978, and the Nash coefficients of the ABCD hydrological model in the base period and sudden change period were 0.85 and 0.86, respectively. (2) Climate factors were the dominant factor affecting annual runoff changes (98.62%), while human factors were the secondary factor affecting annual runoff changes (1.38%). (3) The contribution rates of climate factors in spring, summer, autumn, and winter to runoff were 91.68%, 74.08%, 95.30%, and 96.15%, respectively. The contribution rates of human factors in spring, summer, autumn, and winter to runoff were 8.32%, 25.92%, 4.70%, and 3.85%, respectively. (4) The contribution rates of climate factors to runoff in May, June, and July were 95.14%, 102.15%, and 87.79%, respectively. The contribution rates of human factors to runoff in May, June, and July were 4.86%, −2.15%, and 12.21%, respectively.

Keywords: Jinsha River; runoff; climate; human; ABCD model; Budyko model (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2023
References: Add references at CitEc
Citations: View citations in EconPapers (1)

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