水文模型结构不确定性是影响水文预报精度的重要因素,如何量化并降低其影响是当前的研究热点问题.基于动态系统响应曲线方法(dynamic system response curve,DSRC),假设水文模型系统的误差仅来源于模型结构误差,推导模型结构误差与输入量的变化量之间的数学关系,结合经典概率论,提出了能够分辨模型结构不确定性来源的考虑模型结构不确定性的动态系统响应曲线校正方法(dynamic system response curve method considering the model structure uncertainty,UNDSRC).将该方法应用于大坡岭流域与富水流域检验UNDSRC方法的综合表现,并与DSRC方法进行比较.研究表明:1)在实际流域检验中,UNDSRC方法相较于DSRC方法具有更好的校正效果,校正效果评价系数分别为0.82与0.60;2)DSRC方法在2个实际流域均可以对新安江模型进行有效校正,且校正效果相似;3)UNDSRC方法校正效果优异且稳定,能够适应更复杂的流域下垫面情况,方法对洪峰流量的校正优于对径流深的校正;4)校正精度相同的情况下,UNDSRC方法相较于DSRC方法具有更小的岭系数.
A real-time correction method for dynamic system differential response with consideration of uncertainty in model structure
Structural uncertainty in hydrological models is an important factor affecting accuracy of hydrological forecasting.To quantify and reduce such effect is a hotly researched area.Dynamic system response curve(DSRC)method was used to deduce mathematical relationship between model structural errors and changes in input,and to propose a dynamic system response curve method with consideration of model structural uncertainty(UNDSRC),to distinguish source of model structural uncertainty.This method was applied to Dapoling and Fushui watersheds,for a test of comprehensive performance of UNDSRC algorithm and for comparison with DSRC algorithm.UNDSRC algorithm was found to perform better than DSRC algorithm in actual basin tests,with average correction effect evaluation coefficient of 0.82(UNDSRC)and 0.60(DSRC)respectively.Xinanjiang model data were effectively corrected by DSRC method in the two watersheds,with similar correction effects.UNDSRC algorithm is excellent and stable and can adapt to more complex surface conditions,the algorithm corrects flood peak better than runoff depth.With identical correction accuracy,ridge coefficient of UNDSRC method is much smaller than DSRC method.
dynamic system response curvemodel structural uncertaintyerror correctionridge regressionXinanjiang model
万方数据
维普
