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

Autor: Shuaijun Yue, Guangxing Ji, Junchang Huang, Mingyue Cheng, Yulong Guo, Weiqiang Chen
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: Land, Vol 12, Iss 8, p 1564 (2023)
Druh dokumentu: article
ISSN: 2073-445X
DOI: 10.3390/land12081564
Popis: 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.
Databáze: Directory of Open Access Journals