干旱区生态环境知识资源中心

The WAVES model was used to simulate the effect of global warming on soil moisture on the semi-arid Taihang Mountain in China. Parameters of the WAVES model were first adjusted according to soil moisture data from a field global warming experiment. Then, the reliability of WAVES in predicting soil moisture changes induced by climatic change was confirmed by comparing the simulated and observed soil moisture values under different climatic conditions and plant growth rates of another field treatment. Next, 10 climate change scenarios incorporating increases in temperature and changes in precipitation were designed. When a simulation was conducted using the leaf area index (LAI) growth pattern from a field experiment under the present climatic conditions, the results suggested that the combination of temperature increase and precipitation decrease would greatly decrease soil water content throughout the entire simulation period. On the other hand, only when precipitation increased by 20% and temperature increased by 2 degreesC, the effect of precipitation increase on soil moisture was obviously positive. Although soil moisture conditions in the T2P1 (temperature increase by 2degreesC and precipitation increase by 10%) and T4P2 (temperature increase by 4degreesC and precipitation increase by 20%) scenarios were slightly better during the rainy season and not much changed before the rainy season, the positive effect of 10% precipitation increase on soil moisture was totally offset by moisture decrease caused by a 4degreesC temperature increase in the T4P1 scenario. At the same time, the trends of soil-moisture change were highly coincident with predicted changes in productivity. Finally, the predicted LAI values from other studies were combined with the climatic change scenarios and used in the simulation. The results showed that changes in LAI alleviated, at least to some extent, the effects of temperature and precipitation changes on soil moisture.