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首页> 外文期刊>Journal of the American Water Resources Association >STOCHASTIC MODELING OF MONTHLY AND DAILY RAINFALL SEQUENCES1
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STOCHASTIC MODELING OF MONTHLY AND DAILY RAINFALL SEQUENCES1

机译:月降雨量和日降雨量SEQUENCES1的随机建模

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ABSTRACT:A monthly model and two daily models (I and II) are presented for the purpose of generating monthly and daily rainfall sequences in the Quae Yai river basin in Thailand. Performance of the models are evaluated by comparing the statistical parameters of the generated sequences with those from historical data. For monthly generation, Thomas‐Fiering model worked satisfactorily in spite of the monthly correlations being weak, if any. Daily Model I, which assumes no persistence between daily rainfall amounts within the wet spells, could not preserve some important parameters regardless of the simplicity in model construction. Application of multi‐state transition probability matrix model gave good results, although the user has to modify some parameters looking at the performance of the model for each historical rec
机译:摘要:提出了月度模式和两个日模式(I和II),用于生成泰国Quae Yai河流域的月和日降雨序列。通过将生成序列的统计参数与历史数据中的统计参数进行比较来评估模型的性能。对于月度生成,Thomas-Fiering模型尽管月度相关性较弱(如果有的话)但效果令人满意。日模型I假设雨季内日降雨量之间没有持续性,无论模型构建多么简单,都无法保留一些重要参数。多态转移概率矩阵模型的应用给出了良好的结果,尽管用户必须修改一些参数,以查看每个历史记录的模型性能

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