Simulation of actual evaporation and its multi-time scale attribution analysis for major rivers in China

Abstract

The water resources in various river basins across China are becoming increasingly severe due to the combined effects of climate change and human activities. Evaporation plays a crucial role in redistributing water resources within local areas. Analyzing the actual evapotranspiration (ETa) changes of six major rivers in China is essential for effective water resource management. This article first employed three mutation methods (the M−K analysis, the Pettitt analysis, and the Bernaola Galvan segmentation algorithm) to identify the runoff mutation years of six major rivers in China. Subsequently, the ABCD and DWBM hydrological models were utilized to estimate monthly, seasonal, and annual ETa scales. Then, the trend of ETa changes was analyzed using the Trend-Free Pre-Whitening Mann-Kendall (TFPW-MK) analysis method. Finally, a multi-time scale Budyko model was constructed to quantitatively assess the impacts of climate change and human activities on changes in ETa. The results indicated that: (1) The Nash coefficient and KGE coefficient for the ABCD and DWBM models during both the base and mutation periods of each watershed were generally above 0.7, with most values exceeding 0.8, signifying a high level of accuracy in the simulation results. (2) On a monthly scale, climate change was the primary factor influencing ETa changes in the Upper reaches of the Yangtze River Basin (UYRB) from January to May, the Middle and Upper reaches of the Songhua River Basin (MUSRB) from January to March, the Upper reaches of the Huaihe River Basin (UHRB) from January to June, and the Upper reaches of the Pearl River Basin (UPRB) from January to December. Human activities were the predominant driving force in the monthly ETa changes in the Source Regions of the Yellow River Basin (SRYRB). Except for April and May, ETa of the Source Regions of the Lancang River Basin (SRLRB) in other months were predominantly affected by human activities. (3) On a seasonal scale, climate change played a leading role on the spring and winter ETa changes in UYRB and the seasonal ETa changes in SRYRB were primarily driven by human activities. And the seasonal ETa changes in UPRB were predominantly affected by climate change. With the exception of winter, the ETa changes of MUSRB in other seasons were mainly attributed to human activities. In UHRB, except for autumn, climate change was the primary driving force in ETa changes in other seasons. In SRLRB, except for spring, human activities exhibited a dominant effect on ETa changes in other seasons. (4) On an annual scale, the impacts of climate change and human activities on annual ETa changes in UYRB were approximately equal. The annual ETa changes in SRYRB, MUSRB, and SRLRB were predominantly caused by human activities. In UHRB and UPRB, climate change played a leading role in annual ETa changes.