Simulation and Multi-Time Scale Attribution Analysis of Actual Evapotranspiration in the Source Region of the Yangtze River, China

Abstract

The Yangtze River Basin is a critical water supply region in China. To quantify the contributions of climate change and human activities to water resources across multiple temporal scales, this study focuses on actual evapotranspiration (AET), which directly influences water availability. Monthly runoff data from the Zhimenda Hydrological Station in the source region of the Yangtze River for the period 1982–2019 were analyzed using the Mann–Kendall (M-K) abrupt change test and the Bernaola–Galván (B-G) segmentation algorithm to identify the change point in runoff depth. The study period was subsequently divided into a baseline period and a post-change period. The ABCD hydrological model was employed to simulate monthly runoff variations during both periods, and the simulated results were used to calculate intra-annual (seasonal and monthly) AET. The Trend-Free Pre-Whitening Mann–Kendall (TFPW-MK) test was then applied to the AET series derived from the ABCD model to analyze temporal trends and intra-annual distribution characteristics. Finally, a multi-time scale Budyko framework was constructed to conduct attribution analysis based on AET data, quantifying the respective contributions of climate change and human activities to AET variation. The results indicate that: (1) The change point in the runoff series was detected in 2008. The Nash–Sutcliffe efficiency coefficients for both the baseline and post-change periods exceeded 0.88. (2) At the monthly scale, AET showed an increasing trend in January, February, July, September, November, and December. At the seasonal scale, AET exhibited a decreasing trend in spring and summer and an increasing trend in autumn and winter, though these trends were not statistically significant. Despite the varying directional trends observed across individual months and seasons, AET showed no statistically significant changes at either the seasonal or monthly intra-annual scale. (3) The intra-annual distribution of AET in the source region of the Yangtze River was highly consistent with precipitation patterns, showing significant synchronous variation. (4) Attribution analysis revealed that human activities played a dominant role in driving the observed trends in AET.