基于SUFI-2算法和SWAT模型的妫水河流域水文模拟及参数不确定性分析  

Hydrological Simulation and Parameter Uncertainty Analysis Using SWAT Model Based on SUIF-2 Algorithm for Guishuihe River Basin

作　　者：李谦[1,2,3] 张静[1,2,3] 宫辉力[1,2,3] 

机构地区：[1]首都师范大学城市环境过程与数字模拟国家重点实验室培育基地,北京100048 [2]首都师范大学资源环境与地理信息系统北京市重点实验室,北京100048 [3]首都师范大学三维信息获取与应用教育部重点实验室,北京100048

出　　处：《水文》2015年第3期43-48,共6页Journal of China Hydrology

基　　金：国家自然科学基金(4127004);北京市科技新星项目(2010B046);北京市自然科学基金(8123041)

摘　　要：敏感性分析和不确定性分析是分布式水文模型参数校准和模型应用的基础。本文以妫水河流域为例,基于SWAT模型和SUFI-2算法进行模型参数敏感性分析,结合手动调参和自动率定,通过SUFI-2的P因子和R因子进行模型不确定性分析,构建妫水河流域分布式水文模型。本次妫水河流域月尺度模拟中:率定期,确定系数R2=0.59,效率系数NSE=0.56;验证期,确定系数R2=0.82,效率系数NSE=0.80;P因子均大于0.5,R因子均小于0.5。结果表明,妫水河流域SWAT模型水文模拟效果较好。The application of distributed hydrological model is usually made depending on the sensitivity analysis and the uncertainty analysis. In order to simulate monthly hydrograph for the Guishuihe River Basin, a distributed hydrological model was developed with SWAT （soil and water assessment tool）, calibrated and validated with SUF1-2 （sequential uncertainty fitting program） manually and automatically. The sensitivity analysis was processed by LH-OAT using both SWAT and SUFI-2 and the uncertainty analysis was evaluated by SUFI-2. The criteria of the uncertainty results are P-factor and the R-factor. In this study, R^2=0.59, NSE=0.56 during the calibration period, and R^2=0.82, NSE=0.80 during the validation period. In the both periods, the P-factor is greater than 0.5 and the R-factor is smaller than 0.5.

关 键 词：SWAT SUFI-2 敏感性分析 不确定性分析 

分 类 号：P338[天文地球—水文科学]