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Rainfall downscaling and flood forecasting: a case study in the Mediterranean area

机译:降雨镇压和洪水预测:地中海地区的案例研究

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The prediction of the small-scale spatial-temporal pattern of intense rainfall events is crucial for flood risk assessment in small catchments and urban areas. In the absence of a full deterministic modelling of small-scale rainfall, it is common practice to resort to the use of stochastic downscaling models to generate ensemble rainfall predictions to be used as inputs to rainfall-runoff models. In this work we present an application of a new spatial-temporal downscaling procedure, called RainFARM, to an intense precipitation event predicted by the limited-area meteorological model Lokal Model over north-west Italy. The uncertainty in flood prediction associated with the small unresolved scales of forecasted precipitation fields is evaluated by using an ensemble of downscaled fields to drive a semi-distributed rainfall-runoff model.
机译:预测大规模的降雨事件的小型空间模式对于小集水区和城市地区的洪水风险评估至关重要。在没有完全确定的小规模降雨的确定性建模中,常常诉诸使用随机缩小模型来生成与降雨径流模型的投入使用的集合降雨预测。在这项工作中,我们展示了一种新的空间次要缩小程序,称为Rainfarm,到意大利西北部地区气象模型Lokal模型预测的强烈降水事件。通过使用次要字段的集合来评估与预测降水场的小未解决方案相关的洪水预测的不确定性,以驱动半分布的降雨 - 径流模型。

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