将DBM(Data Based Mechanistic)模型应用到辽东森林小流域——大湖沟,分别以其2006年6月和2007年7月数据构建研究区丰水期和枯水期的DBM模型,拟合效率系数分别为0.952 8和0.837 8,模型拟合效果在验证期的不同时段表现出明显的差异性.对丰水期模型参数用固定时间间隔法(FIS)进行时变性分析,发现参数b的取值随时间产生变化.对枯水期的二阶DBM模型进行快、慢流分解,得出了连续时间当量的快、慢流的平均滞后时间分别为5.3h和243.3h.
A Data-based Mechanism Model and Its Application
Data-based mechanism (DBM) hydrological model is a simulated method with some physical basis that data determines model structure. The models for wet season and dry season were respectively built on the data in June 2006 and July 2007 in the Dahugou Basin in the east of Liaoning Province. The Nash efficiency coefficients of the two models are 0.9528 and 0.8378. But the coefficients show differences in different validation periods. The time-varying property of the parameters in wet period was analyzed using FIS algorithm, discovered that the parameter b changed with time. The second-order model in dry period was decomposed into a fast flow model and a slow flow model, and obtained the average residence time of continuous time equivalent of fast flow and slow flow are 5.3 hours and 243.3 hours respectively.
DBMrainfall-runoff simulationtime variablerunoff decompositionfitting coefficient of efficiency
NETL
NSTL
万方数据
维普
