摘要
以流域一阶线性径流模型为例，将模型中各参数扩展为随机变量，推导出基于马尔柯夫过程的可用于流域径流趋势分析的随机模型，并由Ｆｏｋｋｅｒ－Ｐｌａｎｃｋ－Ｋｏｌｍｏｇｏｒｏｖ（简写ＦＰＫ）方程产生径流概率密度函数．模型应用于洵河柴坪流域的经济趋势分析，验证了该方法的实用性．
The first-order linear streamflow model is studied to develop stochastic analysis model, based on Markovian process, for the probability of streamflow forecasting. First, the parameters in model are expanded to include stochastic terms. Second, an analytical solution for the probability density function are produced by using FokkerplanckKolmogorov equation. The method is then used to predict probability of streamflow in Caipin basin. The calculated results are in good agreement with historical streamflow data.
出处
《水电能源科学》
1997年第4期7-11,共5页
Water Resources and Power
关键词
马尔柯夫过程
随机模型
径流趋势分析
径流
流域
Markovian process, stochastic model, streamflow forecasting, probability density function, probability
