摘要
在太子河流域建立了SWAT(Soil and Water Assessment Tool)分布式水文模型,并采用SUFI-2算法进行参数敏感性分析以及参数率定、模型验证与不确定性分析,对太子河流域的1956—2016年水文过程进行了模拟.研究结果显示:①模型运行时所用的一些水文参数,会影响模型的模拟结果,如基流α系数ALPHA_BF、地下水延迟时间GW_DELAY、土壤蒸发补偿系数ESCO、浅层地下水再蒸发系数GW_REVAP、最大冠层蓄水量CANMX、生物混合效率系数BIOMIX、SCS径流曲线系数CN2、饱和水力传导系数SOL_K、土壤饱和容重SOL_BD、土壤表层到底层的深度SOL_Z这几个参数最敏感;②太子河流域所有水文站的月径流模拟线与实测径流线较接近,率定期和验证期水文站的决定系数R2值均大于0.5,Nash-Sutcliffe系数(ENS)均大于0.5,太子河流域SWAT模型月径流模拟效果较好;③太子河流域实际蒸散发量的空间分布呈现由西向东递减的趋势,西部平均蒸散发量约为550 mm,东部平均实际蒸散发量约为431 mm.太子河流域产水量的空间分布呈现由西向东递增的趋势,东部平均产水量约为547 mm,西部平均产水量约为149 mm.
In this paper,SWAT(Soil and Water Assessment Tool)distributed hydrological model is established in Taizi River basin.The SUFI-2 algorithm is used to analyze the sensitivity of parameters and verify the model to simulate the hydrological process of Taizi River Basin from 1956 to 2016.The results show that:①Some hydrological parameters used in the operation of the model will affect the simulation results of the model,such as ALPHA_BF,GW_DELAY,ESCO,GW_REVAP,CANMX,BIOMIX,CN2,SOL_K,SOL_BD,SOL_Z is the most sensitive parameter.②The monthly runoff simulation lines of all hydrological stations in Taizi River basin are close to the measured runoff lines.The determination coefficient R2 values of hydrological stations in the periodic and verification periods are greater than 0.5,and the Nash-Sutcliffe coefficient(ENS)are greater than 0.5.The SWAT model of Taizi River basin has a good effect on monthly runoff simulation.③The spatial distribution of actual evapotranspiration in Taizi River basin shows a decreasing trend from west to east.The average evapotranspiration in the west is about 550 mm,and that in the east is about 431 mm.The spatial distribution of water yield in Taizi River basin shows an increasing trend from west to east,with the average water yield of 547 mm in the east and 149 mm in the west.
作者
朱正如
苑晨
吕乐婷
ZHU Zhengru;YUAN Chen;LV Leting(School of Geography, Liaoning Normal University, Dalian 116029, China)
出处
《辽宁师范大学学报(自然科学版)》
CAS
2021年第2期240-247,共8页
Journal of Liaoning Normal University:Natural Science Edition