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Exploring the potential of SRTM topographic data for flood inundation modelling under uncertainty

机译：探索不确定条件下SRTM地形数据在洪水泛滥建模中的潜力

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The desirable data for model building and calibration to support the decision-making process in flood risk management are often not sufficient or unavailable. A potential opportunity is now offered by global remote sensing data, which can be freely (or at low cost) obtained from the internet, for example, Shuttle Radar Topography Mission (SRTM) topography. There is a general sense that inundation modelling performance will be degraded by using SRTM topography data. However, the actual effectiveness and usefulness of SRTM topography is still largely unexplored. To overcome this lack of knowledge, we have explored the value of SRTM topography to support flood inundation modelling under uncertainty. The study was performed on a 98 km reach of the River Po in northern Italy. The comparison between a hydraulic model based on high-quality topography and one based on SRTM topography was carried out by explicitly considering other sources of uncertainty (besides topography inaccuracy) that unavoidably affect hydraulic modelling, such as parameter and inflow uncertainties. The results of this study showed that the differences between the high-resolution topography-based model and the SRTM-based model are significant, but within the accuracy that is typically associated with large-scale flood studies.
机译：用于支持洪水风险管理中的决策过程的模型构建和校准所需的数据通常是不充分或不可用的。现在，全球遥感数据提供了潜在的机会，这些数据可以从互联网上免费（或以低成本）获得，例如，航天飞机雷达地形任务（SRTM）地形。通常，使用SRTM地形数据会降低淹没建模的性能。但是，SRTM地形的实际有效性和实用性仍未得到充分探索。为了克服这些知识的不足，我们探索了SRTM地形在不确定性下支持洪水淹没建模的价值。这项研究是在意大利北部Po河的98公里处进行的。通过明确考虑其他不可避免地影响水力建模的不确定性因素（除了地形不准确性），对基于高质量地形的水力模型与基于SRTM地形的水力模型进行了比较，例如参数和流入不确定性。这项研究的结果表明，基于高分辨率形貌的模型与基于SRTM的模型之间的差异是显着的，但在通常与大规模洪水研究相关的精度范围内。

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