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Projected climate change impacts on water resources in northern Morocco with an ensemble of regional climate models

机译:结合区域气候模式预测的气候变化对摩洛哥北部水资源的影响

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The Mediterranean region is considered as a hot spot of climate change, where precipitation is likely to decrease with the rise of temperature. These changes could have a strong effect in north Africa and notably in Morocco where the agricultural sector is of high importance and very dependent on surface water resources. Therefore, there is a need to quantify the possible climate change impacts on water resources of this region. The most common approach to conduct hydrological impact studies of climate change is to run hydrological models with climate scenarios, usually provided by climate model outputs downscaled to the catchment of interest. In the present study an ensemble of six regional climate model (RCM) simulations from the European project ENSEMBLES at a 25 km resolution is considered to evaluate the climate change impacts on the inflows of the sixth largest dam located in northern Morocco. A quantile perturbation method is used to generate future temperature and precipitation series under the emission scenario A1B. The GR4J hydrological model is first calibrated on different climatic conditions to assess the temporal transferability of its parameters and then run with the perturbed temperature and precipitation series. The ensemble approach allows the projection uncertainties to be evaluated from the spread in the individual RCM simulations. All RCM simulations project a decrease in surface water resources during the extended winter season (November to May), from -9% to -54% depending on the model.
机译:地中海地区被认为是气候变化的热点,那里的降水可能会随着温度的升高而减少。这些变化可能会在北非产生巨大影响,特别是在摩洛哥,那里的农业部门非常重要,并且非常依赖地表水资源。因此,需要量化可能的气候变化对该地区水资源的影响。进行气候变化的水文影响研究的最常用方法是在气候情景下运行水文模型,通常由缩小到感兴趣的流域的气候模型输出提供。在本研究中,以欧洲项目ENSEMBLES以25 km的分辨率对六个区域气候模型(RCM)进行了模拟,以评估气候变化对位于摩洛哥北部的第六大水坝流入的影响。在发射情景A1B下,采用分位数扰动方法生成未来的温度和降水序列。首先在不同的气候条件下对GR4J水文模型进行校准,以评估其参数在时间上的可传递性,然后在摄动的温度和降水序列下运行。集成方法允许根据单个RCM模拟中的分布评估投影不确定性。所有RCM模拟都预测,在延长的冬季(11月至5月)期间,地表水资源量将从-9%降低到-54%(取决于模型)。

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