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Lost in calibration: why people still do not calibrate their models, and why they still should - a case study from urban drainage modelling

机译:丢失校准:为什么人们仍然不校准模型,为什么仍然应该校准-来自城市排水模型的案例研究

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摘要

From a scientific point of view, it is unquestioned that numerical models for technical systems need to be calibrated. However, in sufficiently calibrated models are still used in engineering practice. Case studies in the scientific literature that deal with urban water management are mostly large cities, while little attention is paid to the differing boundary conditions of smaller municipalities. Consequently, the aim of this paper is to discuss the calibration of a hydrodynamic model of a small municipality (15,000 inhabitants). To represent the spatial distribution of precipitation, three distributed rain gauges were used for model calibration. To show the uncertainties imminent to the calibration process, 17 scenarios, differing in assumptions for calibration, were distinguished. To compare the impact of the different calibration scenarios on actual design values, design rainfall events were applied. The comparison of the model results using the different typical design storm events from all the surrounding data points showed substantial differences for the assessment of the sewers regarding urban flooding, emphasizing the necessity of uncertainty analysis for hydrodynamic models. Furthermore, model calibration is of the utmost importance, because uncalibrated models tend to overestimate flooding volume and therefore result in larger diameters and retention volumes.
机译:从科学的角度来看,毫无疑问,需要对技术系统的数值模型进行校准。但是,在工程实践中仍然使用经过充分校准的模型。科学文献中有关城市水管理的案例研究大多是大城市,而很少关注较小城市的不同边界条件。因此,本文的目的是讨论一个小城市(15,000居民)的水动力模型的校准。为了表示降水的空间分布,使用了三个分布式雨量计进行模型校准。为了显示校准过程中即将出现的不确定性,我们区分了17种不同的校准假设场景。为了比较不同校准方案对实际设计值的影响,应用了设计降雨事件。使用来自周围所有数据点的不同典型设计暴风雨事件对模型结果进行的比较表明,在城市污水处理方面,下水道的评估存在很大差异,强调了对流体动力学模型进行不确定性分析的必要性。此外,模型校准至关重要,因为未校准的模型往往会高估洪水体积,因此会导致更大的直径和保留体积。

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