Generator of Synthetic Rainfall Time Series through Markov Hidden States
Generator of Synthetic Rainfall Time Series through Markov Hidden States
复制标题
通过马尔可夫隐藏状态合成降雨时间序列的生成器
DOI：
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发表时间：
2008
期刊：
影响因子：
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通讯作者：
Yolanda Solís
中科院分区：
文献类型：
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作者：
H. S. Sánchez;Yolanda Solís
本文提出了一种方法，用于生成合成的日降雨量时间序列使用马尔可夫隐状态，保持时间，空间和降雨量的相关性在一个气候网络站或在一个流域划分为集水区。该方法不要求降雨量时间序列必须服从正态分布，并且季节性降雨量依赖性通过非齐次马尔可夫过程来管理。由于计算机实现不需要大量的资源，它是快速和准确地产生合成时间序列。为墨西哥莱尔马河流域开发的模拟和规划的水文模型，用这种方法产生的合成降雨时间序列。
This paper presents a method for generating synthetic daily rainfall time-series using Markov hidden states that preserve the temporal, spatial and rainfall quantity correlation in a climatologic network station or in a basin divided into catchments. The method does not require that the rainfall time series must be normally distributed and the seasonal rainfall dependence is managed with a non-homogeneous Markov process. Because the computer implementation does not require a large amount of resources, it is fast and accurately produces synthetic time series. The hydrologic model for simulation and planning developed for the Lerma river basin in Mexico was fed with synthetic rainfall time series generated with this method.