Rapid Flood Inundation Mapping for Catastrophic Floods Due to Dam Failures - CUAHSI Summer Institute 2024

This data repository is connected with the CUAHSI Summer Institute 2024 program, SHARP FIM group. The data includes flood inundation maps developed using three models (HEC-RAS, OWP HAND-FIM, FLDPLN) for two dam break model scenarios of the Fall River Lake dam, Kansas. The first scenario considered the reservoir at full capacity (dam crest level) and the second scenario considered the reservoir was at the normal pool level (Sunny day failure). The title of the report: Rapid Flood Inundation Mapping for Catastrophic Floods Due to Dam Failures\". The abstract of the report: Dam operations and catastrophic failures can severely impact lives and properties. While conventional hydrodynamic models can generate flood inundation maps using numerical methods to solve shallow water equations, these models are complex and computationally intensive. This study uses two terrain-based models, OWP HAND-FIM and FLDPLN, to generate the inundation maps for near real-time operational applications. The dam-break flood hydrograph is empirically calculated as a function of the normal reservoir pool level. The Fall River Dam in Kansas is used as a case study. The peak discharges are attenuated along downstream reaches using a simple analytical solution derived from the diffusive wave equation. These are used to generate flood inundation maps using the two terrain-based models. The maps are evaluated using a benchmark HEC-RAS model with quantitative metrics and flood impacts are analyzed. The results show that terrain-based models can effectively generate flood inundation maps, with the OWP HAND-FIM model achieving an accuracy of 92.1% and the FLDPLN model with an accuracy of 87.5%. The computation runtime for the approach is very short, just a few minutes compared to 17 hours for HEC-RAS. The proposed approach of mapping dam-break inundation can provide near real-time flood impact assessment and scalability for dams across the USA. Acknowledgments: We thank CIROH, CUASHI, and the NOAA National Water Center (NWC) for their support during the NWC Innovators Program Summer Institute 2024.本数据集关联北美水科学进展联盟（CUAHSI）2024年夏季学院SHARP FIM研究组项目。 本数据集包含针对美国堪萨斯州福尔河湖大坝的两种溃坝情景，采用三款模型（HEC-RAS、OWP HAND-FIM、FLDPLN）生成的洪水淹没范围图。第一种情景为水库处于满库容（坝顶水位）状态，第二种情景为水库处于正常蓄水位（平日溃坝）状态。 本报告标题为《针对大坝溃决引发特大洪水的快速洪水淹没制图》（Rapid Flood Inundation Mapping for Catastrophic Floods Due to Dam Failures）。 本报告摘要如下： 大坝运行与灾难性溃坝事件会对生命财产造成严重威胁。传统水动力模型可通过数值方法求解浅水方程生成洪水淹没图，但这类模型结构复杂且计算成本高昂。本研究采用两款基于地形的模型——OWP HAND-FIM与FLDPLN，为近实时业务应用场景生成淹没范围图。研究以常规水库蓄水位为参数，通过经验公式计算溃坝洪水过程线，并以堪萨斯州福尔河大坝作为研究案例。采用基于扩散波方程推导的简易解析解，对下游河段的洪峰流量进行衰减修正，随后利用上述两款基于地形的模型生成洪水淹没图。以基准模型HEC-RAS的结果为参照，通过定量评价指标对生成的淹没图进行评估，并开展洪水影响分析。结果表明，基于地形的模型可高效生成洪水淹没图，其中OWP HAND-FIM模型精度达92.1%，FLDPLN模型精度达87.5%。该方法的计算运行时长极短，仅需数分钟，而HEC-RAS模型则需17小时。本研究提出的大坝溃决淹没制图方法，可为全美范围内的大坝提供近实时洪水影响评估与可扩展的应用方案。 致谢： 感谢CIROH、CUAHSI以及美国国家海洋和大气管理局（NOAA）国家水中心（NWC）在2024年NWC创新者项目夏季学院期间提供的支持。