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Stochastic Generation of Spatially Consistent Monthly Rainfall Using SCL

Rahman Abdul A

Rainfall is the primary and most important component of any hydrological event. There is some amount of uncertainty in the future prediction of rainfall. The purpose of using SCL is the quantification of uncertainty involved in the prediction of rainfall. In the last few decades a considerable variation in the rainfall of the northern Pakistan has occurred. This might be due to the increase in temperature which is going to be threat for the water resources of Pakistan. So there is need to estimate the uncertainties involved in the estimation of the rainfall. In this paper an effort is being carried out to quantify the uncertainties in the average monthly rainfall for UIB using SCL (Stochastic Climate Library). In this paper an effort is being done to quantify the uncertainty involved in the average monthly rainfall data of rain gauge in Astor. Using the SCL the stochastic data is generated based upon the previous average monthly rainfall data of Astor from (1954 to 2000). Several statistics (annual and monthly) are computed to determine the behavior of the model and to compare them with the stochastic data produced.

索引于

化学文摘社 (CAS)
谷歌学术
打开 J 门
学术钥匙
研究圣经
引用因子
宇宙IF
开放学术期刊索引 (OAJI)
参考搜索
哈姆达大学
印度科学网
学者指导
国际创新期刊影响因子(IIJIF)
国际组织研究所 (I2OR)
宇宙
日内瓦医学教育与研究基金会
秘密搜索引擎实验室

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