SWAT模型对高精度土壤信息的敏感性研究

土壤信息是SWAT模型的重要输入数据,通常认为,土壤信息的精度直接影响着模拟结果的准确性。本文以美国Brewery Creek流域(19.5km²)为例,在其他输入不变的情况下,通过比较不同精度土壤数据(美国农业部SSURGO土壤图与SoLIM方法获得的土壤图)的模拟径流,分析SWAT模型对高精度土壤信息的敏感性。应用结果显示,在模型的校正前后,两种土壤数据的径流模拟结果均近似,差别并不显著。这表明在小流域水文模拟中,SWAT模型的径流模拟对高精度土壤信息的敏感性较弱,模拟径流不能很好的体现一定精度基础上土壤信息的差别。本文将此现象主要归因于:SWAT模型所采用的SCS-CN径流计算方法,在计算CN值(Curve Number)时将不同土壤类型综合到四个土壤水文组的做法,概括了土壤信息,模糊了土壤之间的属性差别,损失了土壤精度信息。本研究发现了SCS-CN径流计算方法在利用高精度土壤数据时存在的问题,并进行了分析,为水文模拟中参数的确定和数据的准备提供了参考。

Sensitivity of SWAT Model to Detailed Soil Information

As an important component of input data, soil information directly impacts the accuracy of the simulation of hydrologic model. Sensitivity of SWAT model to detailed soil information was investigated through comparison of the simulated stream flow produced by using SSURGO and SoLIM as different soil input data. A case study was conducted in Brewery Creek, a 19.5km2 area catchment in Dane County, Wisconsin. The simulation results before and after model calibration both indicate that there is only slight difference between the simulated streamflow. This study reveals the weak sensitivity of SWAT model to detailed soil information in the hydrological modeling of a small watershed. The main reason for lack of insignificant difference is that soil information was highly aggregated in the model and that the use of Curve Number as means for representing soil variability in the model also muted the impact of detailed spatial information.