评估利用卫星观测鉴定洪水模型的性能指标

Jean-Paul Travert, Sébastien Boyaval, Cédric Goeury, Vito Bacchi, Fabrice Zaoui
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引用次数: 0

摘要

这项工作讨论了如何选择性能指标来比较洪水事件的数值模拟与卫星图像,例如在模型校准或验证程序中。提出了一系列标准,以评估性能指标对洪水范围、卫星特征(位置、方向)和测量/处理误差(卫星原始值或洪水图提取)的敏感性。以一次洪水事件(2021 年 2 月在法国加龙河上)为例,使用由不确定摩擦场参数化的浅水模型模拟的水深分布,对其相关性进行了数值讨论。在确定最符合标准的性能指标后,进行了相关性分析,以确定各种性能指标的相似性。然后,提出了一种方法,对性能指标进行筛选,选出对观测误差最稳健的指标。在研究案例中,该方法有助于从 28 个性能指标中识别出 4 个。需要注意的是,在浅水模型的摩擦场方面,各种排名靠前的性能指标并不会导致相同的校准结果。该方法可用于任何洪水模型与任何洪水事件的比较。
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Evaluation of Performance Measures for Qualifying Flood Models with Satellite Observations
This work discusses how to choose performance measures to compare numerical simulations of a flood event with one satellite image, e.g., in a model calibration or validation procedure. A series of criterion are proposed to evaluate the sensitivity of performance measures with respect to the flood extent, satellite characteristics (position, orientation), and measurements/processing errors (satellite raw values or extraction of the flood maps). Their relevance is discussed numerically in the case of one flooding event (on the Garonne River in France in February 2021), using a distribution of water depths simulated from a shallow-water model parameterized by an uncertain friction field. After identifying the performance measures respecting the most criteria, a correlation analysis is carried out to identify how various performance measures are similar. Then, a methodology is proposed to rank performance measures and select the most robust to observation errors. The methodology is shown useful at identifying four performance measures out of 28 in the study case. Note that the various top-ranked performance measures do not lead to the same calibration result as regards the friction field of the shallow-water model. The methodology can be applied to the comparison of any flood model with any flood event.
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