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Statistical modeling of weekly rainfall: A case study in Colombo City in Sri Lanka

机译:每周降雨量的统计模型:以斯里兰卡科伦坡市为例

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The modeling of the weekly rainfall percentile is imperative for better understanding of rainfall patterns in any region. This study focuses on selecting the most appropriate probability distributions for weekly rainfall and use those to make reliable rainfall percentile with the 95% confidence intervals. Daily rainfall data of 56 years (1960-2015) during the South West Monsoon in Colombo City were used for this analysis. The three parameter Weibull distribution has been found most probable distribution for most of weekly rainfall totals. Weibull, two parameter Exponential, Exponential and Lognormal distributions were well fitted distributions for remaining totals. Based on the 95% confidence intervals of percentiles, the weeks 18-23, and 38-39 during SWM showed not only high rainfall, but also high rainfall variation results which caused high possibility to form extreme rainfall events. Heavy rainfall with great variation during the period of 30 April to 10 June and 17-30 of September was further confirmed by the result of running total of weekly rainfall.
机译:为了更好地了解任何地区的降雨模式,必须对每周降雨百分位数进行建模。这项研究的重点是为每周降雨选择最合适的概率分布,并使用这些概率分布以95%的置信区间得出可靠的降雨百分位数。该分析使用了科伦坡市西南季风期间56年(1960-2015年)的日降水量数据。对于每周大部分的降雨总量,发现三个参数的威布尔分布是最可能的分布。威布尔(Weibull),两个参数的指数分布,指数分布和对数正态分布是剩余总数的很好拟合的分布。基于百分位数的95%置信区间,SWM期间的第18-23周和第38-39周不仅显示出高降雨,而且还显示出高降雨变化结果,这很可能形成极端降雨事件。每周降雨总计的结果进一步证实了4月30日至6月10日以及9月17日至30日期间的强降雨变化很大。

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