基于马尔可夫模型的河川径流丰枯状态预测  

Forecasting of the Runoff Based on the Markov Model

作　　者：韩贻强[1] 

机构地区：[1]滨州学院地理旅游系,山东滨州256603

出　　处：《安徽农业科学》2009年第1期1-2,共2页Journal of Anhui Agricultural Sciences

摘　　要：依据山东半岛丘陵区大沽夹河1966～2003年逐年径流量，根据有序聚类和时间序列分析的马尔可夫预报模型。对大沽夹河2004年的丰枯状态进行了模拟预测。结果显示，2004年径流量的状态2发生率最高，为0．517，即为偏枯水年，与2004年实际情况一致。这说明运用马尔可夫模型进行河径流量的丰枯状态预报是有效可行的。This study aims to simulate and forecast the runoff of Dagujia River in 2004, which locates in Jiaodong hilly area, on the basis of its yearly runoff from 1966 to 2003 with sequential clustering and Markov model. The result showed that the incidence rate of state 2 of the runoff in 2004 is the highest, i.e. 0.517, which means an inclined dry year and is consistent with the fact. So, it is practical to use the sequential clustering and Markov model to forecast the river runoff.

关 键 词：有序聚类 马尔可夫模型 河川径流 大沽夹河 

分 类 号：S119[农业科学—农业基础科学]