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A stochastic space-time rainfall forecasting system for real time flow forecasting II: Application of SHETRAN and ARNO rainfall runoff models to the Brue catchment

机译:用于实时流量预报的随机时空降雨预报系统II:SHETRAN和ARNO降雨径流模型在Brue流域的应用

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Key issues involved in converting MTB ensemble forecasts of rainfall into ensemble forecasts of runoff are addressed. The physically-based distributed modelling system, SHETRAN, is parameterised for the Brue catchment, and used to assess the impact of averaging spatially variable MTB rainfall inputs on the accuracy of simulated runoff response. Averaging is found to have little impact for wet antecedent conditions and to lead to some underestimation of peak discharge under dry catchment conditions. The simpler ARNO modelling system is also parameterised for the Brue and SHETRAN and ARNO calibration and validation results are found to be similar. Ensemble forecasts of runoff generated using both SHETRAN and the simpler ARNO modelling system are compared. The ensemble is more spread out with the SHETRAN model, and a likely explanation is that the ARNO model introduces too much smoothing. Nevertheless, the forecasting performance of the simpler model could be adequate for flood warning purposes.
机译:解决了将MTB降雨总预报转换为径流总预报时涉及的关键问题。基于物理的分布式建模系统SHETRAN已针对Brue流域进行了参数化,并用于评估平均空间可变MTB降雨输入对模拟径流响应精度的影响。发现平均对湿前条件几乎没有影响,并且导致在干流域条件下峰值流量的一些低估。还针对Brue和SHETRAN对更简单的ARNO建模系统进行了参数设置,并且ARNO校准和验证结果相似。比较了使用SHETRAN和更简单的ARNO建模系统生成的径流的整体预测。用SHETRAN模型可以更广泛地分布该集合,并且可能的解释是ARNO模型引入了过多的平滑处理。但是,较简单的模型的预测性能可能足以满足洪水预警的目的。

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