Assessing the reliability of probabilistic flood inundation model predictions Reliability of Probabilistic Flood Inundation Predictions
Assessing the reliability of probabilistic flood inundation model predictions Reliability of Probabilistic Flood Inundation Predictions
复制标题
评估概率洪水淹没模型预测的可靠性 概率洪水淹没预测的可靠性
DOI：
10.1002/hyp.10451
复制
发表时间：
2015
影响因子：
3.2
通讯作者：
Stephens E
中科院分区：
文献类型：
--
作者：
Stephens E
概率洪水淹没预测的可靠性量化的能力是一个要求，不仅为指导模型的开发，但也为他们的成功应用。概率洪水淹没预测通常是通过选择一种方法来加权模型参数空间，但以前的研究表明，这种选择会导致明显的差异，淹没概率。本研究旨在解决这些概率预测的可靠性评估。然而，缺乏足够数量的观测洪水淹没的流域限制了应用传统的方法来评估预测的可靠性。因此，人们试图通过一次洪水事件的多个观测值来评估概率预测的可靠性。在此，我们构建了英国科克茅斯一次极端（>1/1000年）洪水事件的LISFLOOD-FP水力模型，并使用多个性能指标对该模型进行了校准，这些性能指标来自于峰值洪水残骸数据和峰值后拍摄的航拍照片。这些测量用于对参数空间进行加权，以产生事件的多个概率预测。两种方法评估这些概率预测的可靠性，使用有限的观察，现有的方法评估的二元模式的洪水，本文开发的方法来评估水面高程的预测。研究发现，水面高程法具有较好的诊断和判别能力，但该结果可能对上游边界条件中的未知不确定性敏感。版权所有© 2015约翰威利父子有限公司.
An ability to quantify the reliability of probabilistic flood inundation predictions is a requirement not only for guiding model development but also for their successful application. Probabilistic flood inundation predictions are usually produced by choosing a method of weighting the model parameter space, but previous study suggests that this choice leads to clear differences in inundation probabilities. This study aims to address the evaluation of the reliability of these probabilistic predictions. However, a lack of an adequate number of observations of flood inundation for a catchment limits the application of conventional methods of evaluating predictive reliability. Consequently, attempts have been made to assess the reliability of probabilistic predictions using multiple observations from a single flood event.Here, a LISFLOOD‐FP hydraulic model of an extreme (>1 in 1000 years) flood event in Cockermouth, UK, is constructed and calibrated using multiple performance measures from both peak flood wrack mark data and aerial photography captured post‐peak. These measures are used in weighting the parameter space to produce multiple probabilistic predictions for the event. Two methods of assessing the reliability of these probabilistic predictions using limited observations are utilized; an existing method assessing the binary pattern of flooding, and a method developed in this paper to assess predictions of water surface elevation. This study finds that the water surface elevation method has both a better diagnostic and discriminatory ability, but this result is likely to be sensitive to the unknown uncertainties in the upstream boundary condition. Copyright © 2015 John Wiley & Sons, Ltd.