用相关函数优化法计算离散线性水文模型参数

An Auto/cross Covariance Approach for Parameter Estimation of the Discrete Linear Transfer Function Model

借助于日降雨和出流资料系列,采用相关函数优化方法确定离散线性水文模型参数是一种新的方法。文中选用4个流域8年日降雨和径流资料系列来检验相关函数优化法(6年作为率定期,2年作为验证期),所得结果与常规最小二乘法计算的结果进行比较表明:新方法计算精度比常规最小二乘法计算的精度有所提高,常规最小二乘法仅是相关函数优化法的一种特例。

An auto/cross covariance approach for parameter estimation of the discrete linear transfer function model is a new method. The daily rainfall and runoff data series on four catchments are chosen to examine the new method (4 years rainfall and runoff data series for calibration periods and 2 years for the verification periods). The comparison between the results from the new method and coven-Vional ordinary least squares method shows that the accuracy of the new method is better than those of the conventional least squares method and the latter is a special case of the former.