基于SHAW模型的青海湖流域土壤温度模拟

Simulation of Soil Temperature in Qinghai Lake Watershed by SHAW Model

土壤温度与地气间能量交换、水分循环密切相关,影响着植被生长乃至区域生态安全。本文首先分析了青海湖流域2018年10月至2020年7月实测的不同深度土壤温度变化特征,然后结合2018年10月至2019年8月土壤温度对SHAW模型进行了率定,并根据2019年9月至2020年7月观测数据对率定参数进行了验证,在此基础上探究了植被和土壤参数对土壤温度变化的影响。结果表明:①伴随深度增加,土壤温度的变化幅度逐渐减小,5 cm深度逐日平均土壤温度的极差达到25.50℃,而35 cm深度极差为20.19℃,均远低于相同时期气温的极差(36.32℃);②率定期各层土壤温度的纳什效率系数(NSE)均高于0.94,均方根误差(RMSE)由表层(1.91℃)至深层(0.86℃)逐渐减小,模型模拟精度随着土层深度增加而提高;验证期各评价指标略低于率定期,但各层NSE均超过0.93,RMSE由浅层的1.98℃降低至最深层的0.98℃,说明SHAW模型可以模拟青海湖流域土壤温度的动态变化;③土壤温度变化与叶面积指数、土壤容重均呈负相关关系,饱和导水率、孔径指数和进气势分别降低60%、40%和30%以后,土壤温度才有明显响应。

Soil temperature is closely related to energy exchange and water cycle between land surface and atmosphere, and further affects the vegetation growth and regional ecological security. This study first analyzed the change characteristics of measured soil temperature at different soil depths from October 2018 to July 2020 in Qinghai Lake watershed, then calibrated the SHAW model based on the soil temperature from October 2018 to August 2019 and further verified it using the measured data from September 2019 to July 2020. At last, the effects of vegetation and soil parameters on soil temperature change were explored.The results showed that: 1) The change range of soil temperature decreased with increasing soil depth, i.e., the range of mean daily soil temperature was 25.50 ℃ at 5 cm depth, and 20.19 ℃ at 35 cm depth, both of which were much lower than the corresponding range of air temperature(36.32 ℃). 2) During the calibration period of the SHAW model, the Nash-Sutcliffe efficiency coefficient(NSE) of soil temperature was higher than 0.94 at all layers, and the root mean square error(RMSE)gradually decreased from the surface(1.91 ℃) to the deep layer(0.86 ℃). In general, the simulation accuracy of the model increased with the increase of soil depth. The evaluation indexes during the validation period were all slightly lower than those in the calibration period. However, the NSE of each layer exceeded 0.93, and the RMSE reduced from 1.98 ℃ in the shallowest layer to 0.98 ℃ in the deepest layer, indicating that the SHAW model could be used to simulate the change of soil temperature in the Qinghai Lake watershed. 3) The change of soil temperature was negatively correlated with the leaf area index and soil bulk density. In addition, soil temperature responded significantly to saturated conductivity, pore-size distribution index and air-entry potential only when they decreased by 60%, 40% and 30%, respectively.