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Intensity-duration-frequency (IDF) rainfall curves in Senegal

机译:塞内加尔的强度持续时间频率(IDF)降雨曲线

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摘要

Urbanization resulting from sharply increasing demographic pressure and infrastructure development has made the populations of many tropical areas more vulnerable to extreme rainfall hazards. Characterizing extreme rainfall distribution in a coherent way in space and time is thus becoming an overarching need that requires using appropriate models of intensity-duration-frequency (IDF) curves. Using a 14 series of 5 min rainfall records collected in Senegal, a comparison of two generalized extreme value (GEV) and scaling models is carried out, resulting in the selection of the more parsimonious one (four parameters), as the recommended model for use. A bootstrap approach is proposed to compute the uncertainty associated with the estimation of these four parameters and of the related rainfall return levels for durations ranging from 1 to 24 h. This study confirms previous works showing that simple scaling holds for characterizing the temporal scaling of extreme rainfall in tropical regions such as sub-Saharan Africa. It further provides confidence intervals for the parameter estimates and shows that the uncertainty linked to the estimation of the GEV parameters is 3 to 4 times larger than the uncertainty linked to the inference of the scaling parameter. From this model, maps of IDF parameters over Senegal are produced, providing a spatial vision of their organization over the country, with a north to south gradient for the location and scale parameters of the GEV. An influence of the distance from the ocean was found for the scaling parameter. It is acknowledged in conclusion that climate change renders the inference of IDF curves sensitive to increasing non-stationarity effects, which requires warning end-users that such tools should be used with care and discernment.
机译:城市化因人口压力和基础设施发展急剧增加,使许多热带地区的人口更容易受到极端降雨危害。在空间和时间的相干方式中表征极端降雨分布,因此成为使用适当模型的强度持续时间(IDF)曲线的总体需要。使用在塞内加尔收集的14系列5分钟的降雨记录,进行了两个广义极值(GEV)和缩放模型的比较,导致选择更加令人垂涎的一个(四个参数),作为推荐的使用模型。提出了一种自举方法来计算与估计这四个参数的不确定性,并且与1至24小时的持续时间的相关降雨返回水平。本研究证实了以前的作品,表明简单的缩放持有,用于表征热带地区的热带地区的颞缩放,如撒哈拉以南非洲。它还提供了参数估计的置信区间,并表明与GEV参数的估计相关的不确定性比链接到缩放参数的推断的不确定性大3〜4倍。从该模型来看,生产塞内加尔的IDF参数地图,为其组织的空间愿景提供了全国,北朝南梯度,用于GEV的位置和比例参数。找到了缩放参数的距离的影响。它得到了认可,即气候变化使IDF曲线推断致敏对增加的非公平性效应,这需要警告最终用户应该与护理和辨别使用这种工具。

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