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An evaluation of three stochastic rainfall models

机译:3种随机降雨模式的评价

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Three stochastic rainfall models are evaluated in terms of their ability to reproduce the standard and extreme statistics derived from observed hourly point rainfall data obtained from three different sites in the UK. The models are: a modified version of the Eagleson Eagleson, P.S., 1972. Dynamics of flood frequency. Water Resources Research 8, 878-898 exponential model (or MEEM), a version of the data-based model of Cameron et al. Cameron, D.S., Beven, K.J., Tawn, J., Blazkova, S., Naden, P., 1999. Flood frequency estimation for a gauged upland catchment (with uncertainty). Journal of Hydrology 219, 169-187 (or CDFGPDM) and the random parameter Bartlett-Lewis gamma model (or RFBLGM) of Onof and Wheater Onof, C., Wheater H.S., 1994. Improvements to the modelling of British rainfall using a modified random parameter Bartlett-Lewis rectangular pulse model. Journal of Hydrology 157, 177-195. The sites are: Elmdon (Birmingham, England), Eskdalemuir (White Esk valley, Scotland), and the Wye (Plynlimon, Wales). For each site, the simulations are conducted on a seasonal (winter and summer) basis, with hourly timestep. For each season, a comparison of the spread of the 1 and 24 h simulated seasonal maximum rainfall totals with those obtained through a statistical analysis of the observed extreme rainfalls is also made. It is shown that the MEEM can effectively reproduce certain observed series standard statistics at each site. It is much poorer in its representation of extreme events, and, for two of the sites, dry periods. The CDFGPDM generally performs well under all the criteria, although it has a tendency to underestimate the observed I h seasonal maximum rainfalls for both seasons at Elmdon. The RPBLGM is shown to be reasonable at simulating the standard statistics but is often poorer with respect to the extremes. The implications for flood frequency estimation are highlighted. Possible improvements to each model are considered. (C) 2000 Elsevier Science B.V. All rights reserved. References: 34
机译:评估了三种随机降雨模型的能力,以重现从英国三个不同地点观测到的每小时点降雨数据得出的标准和极端统计数据。这些模型是:Eagleson的改进版本[Eagleson,P.S.,1972。洪水频率的动态。Water Resources Research 8, 878-898] 指数模型(或 MEEM),Cameron 等人基于数据的模型的一个版本 [Cameron, D.S., Beven, K.J., Tawn, J., Blazkova, S., Naden, P., 1999.测量高地集水区的洪水频率估计(不确定)。Journal of Hydrology 219, 169-187](或 CDFGPDM)和 Onof and Wheater 的随机参数 Bartlett-Lewis 伽马模型(或 RFBLGM)[Onof, C., Wheater H.S., 1994.使用修改后的随机参数 Bartlett-Lewis 矩形脉冲模型改进英国降雨模型。水文学报 157, 177-195]。这些地点是:埃尔姆登(英格兰伯明翰)、埃斯克代尔缪尔(苏格兰怀特埃斯克山谷)和怀伊(威尔士普林利蒙)。对于每个站点,模拟都是按季节(冬季和夏季)进行的,每小时进行一次。对于每个季节,还比较了1小时和24小时模拟的季节最大降雨总量的分布与通过对观测到的极端降雨量进行统计分析而获得的分布。结果表明,MEEM可以有效地再现每个站点的某些观测序列标准统计量。它在极端事件的表现方面要差得多,而且对于其中两个地点来说,干旱时期要差得多。CDFGPDM在所有标准下通常表现良好,尽管它倾向于低估埃尔姆登两个季节观测到的I h季节性最大降雨量。RPBLGM在模拟标准统计量方面被证明是合理的,但在极端情况下往往较差。强调了对洪水频率估计的影响。考虑了对每个模型的可能改进。(C) 2000 Elsevier Science B.V.保留所有权利。[参考文献: 34]

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