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Flash flood forecasting using Data-Based Mechanistic models and radar rainfall forecasts

机译:使用基于数据的机械模型和雷达降雨预报进行山洪预报

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摘要

The parsimonious time series models used within the Data-Based Mechanistic (DBM) modelling framework have been shown to provide reliable accurate forecasts in many hydrological situations. In this work the DBM methodology is applied to forecast discharges during a flash flood in a small Alpine catchment. In comparison to previous work this catchment responds rapidly to rainfall. It is demonstrated, by example, that the use of a radar-derived ensemble quantitative precipitation forecast coupled to a DBM model allows the forecast horizon to be increased to a level useful for emergency response. A treatment of the predictive uncertainty in the resulting hydrological forecasts is discussed and illustrated.
机译:已证明在基于数据的力学(DBM)建模框架中使用的简约时间序列模型可在许多水文情况下提供可靠的准确预测。在这项工作中,DBM方法被用于预测小型高山流域的山洪暴发期间的流量。与以前的工作相比,该流域对降雨的响应迅速。通过示例证明,结合DBM模型使用雷达综合雨量定量预报可以使预报范围增加到对应急响应有用的水平。讨论并说明了对所得水文预报中预测不确定性的处理方法。

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