Feedback dynamics between precipitation, temperature, and soil moisture in China and their possible driving mechanisms under a changing environment

Abstract

Complex mutual feedback relationships exist between hydrological and meteorological elements in hydrological cycle processes, which may show dynamic changes in a changing environment. Nevertheless, the feedback dynamics between precipitation (P), temperature (T), and soil moisture (SM) and corresponding driving mechanisms remain unknown. And the mutual feedback types are different in space, the mutual feedback strength may change with time. To this end, the Granger causality test was adopted in this study to examine the feedback relationship between P, T, and SM in China. Then, the Sliding Window was used to explore the dynamic characteristics of their mutual feedback relationships. Finally, the Geographical Detector and Random Forest were applied to reveal their spatial and time dynamic driving forces, respectively. Results indicate: (1) generally, the feedback relationships among P, SM, and T are significant, in which the feedback relationship between P and SM is the most extensive in China; (2) the feedback strength between P, T, and SM generally show significant increasing trend, and different types of feedback relationship are different in spatial distribution. Specifically, the feedback strength between P and SM increased in the northwest and southwest of China; (3) the driving forces of the feedback relationships between P, T and SM were analyzed spatial driving forces, Evapotranspiration (ET) and P have strong driving effects, while Potential Evapotranspiration (PET), Wind speed (wind), and Leaf Area Index (LAI) have weaker driving effects, ET is the core hub of the mutual feedback relationship among multiple factors, and meteorological factors are the main driving factors for the time dynamic evolution of mutual feedback relationships between P, T, and SM, followed by circulation factors, and finally underlying surface factors. This study sheds new insights into hydrometeorological feedback, which will help improve understanding of how extreme events such as droughts, heat waves and floods develop, thus being beneficial for their precise defense.