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Extreme precipitation events simulation under plausible scenarios of climate change in Satluj River basin, India

机译:印度萨特鲁日河流域气候变化情景下的极端降水事件模拟

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摘要

A K-nearest neighbour weather-generating model is applied to simulate: 1) total precipitation during extreme precipitation events; 2) duration of extreme wet spells; 3) duration of extreme dry spells in the Satluj River basin - a key basin in the central Himalayas under climate change scenarios projected by 15 different combinations of global climate models (GCMs) and emission scenarios. The intent is to assess the vulnerability of the basin to extreme hydrological events, including floods and droughts, resulting from extreme precipitation events. The driving data set for the K-NN model was obtained by applying the precipitation change fields obtained from different combinations of the GCM and emission scenarios to the observed data. Results indicate that several extreme wet and dry spells that were more severe than the observed were simulated. Results of frequency analysis of storm depths indicated that ECHAM5 model under A2 scenario produced the highest one-day precipitation maxima for each return period considered.
机译:应用K近邻天气生成模型来模拟:1)极端降水事件期间的总降水; 2)极端潮湿的持续时间; 3)由全球气候模型(GCM)和排放情景的15种不同组合预测的气候变化情景下,喜马拉雅中部的关键盆地萨特鲁日河流域的极端干旱时期的持续时间。目的是评估流域易受极端降水事件导致的极端水文事件(包括洪水和干旱)的影响。通过将从GCM和排放情景的不同组合获得的降水变化场应用于观测数据,获得了K-NN模型的驱动数据集。结果表明,模拟了一些比所观察到的更为严重的极端干湿法术。风暴深度的频率分析结果表明,在A2情景下,ECHAM5模型在所考虑的每个返回期都产生了最高的一日降水最大值。

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