黄淮海地区降水随机模拟模型及评价

Evaluation on Stochastic Precipitation Simulation Model in Huang-Huai-Hai Plain

利用黄淮海地区7个代表站连续42 a的实测降水资料,通过一阶马尔科夫链和伽玛分布函数的联合应用,建立了降水随机模拟模型。利用实测降水数据直接推求和回归模型间接获得的方法,分别模拟了7个代表站100 a的逐日降水过程。结果表明:模拟的降水量和降水天数均与实测值符合良好,两种方法月降水天数模拟值的平均相对误差分别为3.33%、4.01%,月降水量模拟值的平均相对误差分别为2.44%、2.36%;可以采用本文建立的回归模型估算转移概率和伽玛分布参数。

A stochastic precipitation simulation model was established using a combined application of first order Markov chain and Gamma distribution function based on a 42 years historical precipitation data at 7 representative stations in Huang-Huai-Hai plain. Daily precipitation over the future 100 years were predicted respectively for the 7 representative stations using direct calculation and indirect extrapolation from regression models based on observed precipitation data. The results show,that simulated precipitation amounts and day numbers are in good a-greement with observed data. The relative average errors between predicted and observed of monthly precipitation day number using the two methods are 3.33% and 4.01% respectively,whereas they are 2.44% and 2.36% between predicted and observed monthly precipitation a-mounts for the two methods. It was suggested that the regression model established in this study could be used to estimate transition probabili-ty and gamma distribution parameters to predict future precipitation in Huang-Huai-Hai plain.