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一种北江流域年降雨量的权马尔可夫链预测模型
  • 期刊名称:水文,2006,26(6)
  • 时间:0
  • 分类:P338.9[天文地球—水文科学;水利工程—水文学及水资源;天文地球—地球物理学]
  • 作者机构:[1]中山大学水资源与环境研究中心,广东广州510275
  • 相关基金:国家自然科学基金资助项目(50579078)
  • 相关项目:华南地区剧烈人类活动下枯水径流特征时空变异性研究
中文摘要:

根据北江流域的48个站点的年降雨量资料和泰森多边形计算方法,计算出北江流域的面降雨量。再结合丰、偏丰、平、偏枯、枯水年的频率标准,建立了适用于北江流域年降雨量的分级数值区间,同时,验证了该序列满足马尔可夫链的要求,并考虑该年降雨量序列是相依随机变量的特点,以规范化的各阶自相关系数为权,建立了北江流域年降雨量的权马尔可夫链预测模型.实例验证结果令人满意。

英文摘要:

Based on the annual precipitation data from 48 rain gauging stations in Beijiang River Basin and the method of Thiessen, no-point annual precipitation have been calculated. Combined the classification standard of precipitation, the numeral range of classification which is fitted to Beijiang River Basin has been established. Then based on the verification of the Markov chain characteristics of precipitation, the weighted Markov chain used for predicting the state of precipitation in Beijiang River Basin has been developed. And the results of prediction are satisfied.

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