岩溶地下河在SWAT中的概化方法——以毕节倒天河流域为例

岩溶地下河的存在严重影响了土壤和水评估工具（SWAT）在岩溶地区的普遍适用性。针对岩溶地下河在SWAT中的概化问题，提出基于数字高程模型（DEM）预处理结合SWAT流域自动识别功能的方法，将岩溶地下河暴露于地表，把岩溶区复杂的地表－地下二元结构简化为地表一元结构，并以贵州毕节地下河发育的倒天河流域为例进行应用。结果表明:① 对比未经概化地下河建立的模型，概化地下河建立的模型识别流域面积增大30.73%，子流域个数增加29.27%，水文响应单元（HRU）个数增加43.82%；② 参数取最大物理意义范围时，未经概化地下河建立的模型p因子=0.64，不满足建模条件，物理模型本身存在问题；③ 概化地下河建立的模型月步长模拟结果:校准期R2=0.96，NS=0.96，验证期R2=0.94，NS=0.93，月尺度模拟效果非常好。岩溶地下河概化方法使SWAT在流域划分方面更加合理，搭建的模型模拟更加合理。该研究拓展了SWAT模型在岩溶区的应用。 

Generalization method of karst underground river in SWAT:An example of the Daotian river watershed in Bijie,Guizhou

The existence of karst underground rivers seriously affect the general applicability of Soil and Water Assessment Tools (SWAT) in karst areas. To solve this problem, this paper proposes a method based on Digital Elevation Model (DEM) preprocessing combined with SWAT watershed automatic recognition function. It exposes the karst underground river to the surface, and simplifies the complex surface underground binary structure into a surface unitary structure. The application of this method is demonstrated by an example of the Daotian River watershed in Bijie, Guizhou Province. The results show that， (1) compared with the model established without generalization, the area of the basin identified by the model is increased by 30.73%, the number of subbasins increased by 29.27%, and the number of hydrological response units increased by 43.82%, respectively； (2)When the parameters are taken as the maximum range of physical significance, the p-factor of the model established without generalization is 0.64, showing a good SWAT model can not be established without using this method to generalize the underground river； (3) The SWAT model with the generalized underground river is used to perform simulation with a month step length. It yields calibration period R2 = 0.96, NS = 0.96, validation period R2 = 0.94, and NS= 0.93, indicating a good result. The generalization method of karst underground river makes SWAT both in watershed division and simulation more reasonable.