论文标题
洪水概率插值工具（Flopit）：通过更高的分辨率映射改善空间洪水概率量化和通信
The FLOod Probability Interpolation Tool (FLOPIT): Improving Spatial Flood Probability Quantification and Communication Through Higher Resolution Mapping
论文作者
论文摘要
了解洪水概率对于做出有关洪水风险管理的明智决定至关重要。许多人依靠洪水概率地图来告知有关购买洪水保险，购买或出售房地产，防洪或管理洪泛区开发的决策。当前的洪水概率地图通常使用洪水区（例如100或500年的洪水区中的1分之一）来传达洪水概率。但是，这种沟通格式的选择可能会错过重要的细节，并导致风险评估有偏见。在这里，我们开发，测试和演示洪水概率插值工具（Flopit）。 Flopit插入了水面高程之间的洪水概率，以产生连续的洪水概况图。我们表明，Flopit可以相对容易地应用于用于创建洪水区域的现有数据集。使用联邦紧急事务管理局（FEMA）洪水风险数据库以及州和国家数据集的公开数据，我们在美国的三个示例地点生产持续的洪水概率地图：休斯敦（TX）（TX），Muncy（PA）和Selinsgrove（PA）。我们发现，离散的洪水区通常传达的洪水概率大大低于连续估计。
Understanding flood probabilities is essential to making sound decisions about flood-risk management. Many people rely on flood probability maps to inform decisions about purchasing flood insurance, buying or selling real-estate, flood-proofing a house, or managing floodplain development. Current flood probability maps typically use flood zones (for example the 1 in 100 or 1 in 500-year flood zones) to communicate flooding probabilities. However, this choice of communication format can miss important details and lead to biased risk assessments. Here we develop, test, and demonstrate the FLOod Probability Interpolation Tool (FLOPIT). FLOPIT interpolates flood probabilities between water surface elevation to produce continuous flood-probability maps. We show that FLOPIT can be relatively easily applied to existing datasets used to create flood zones. Using publicly available data from the Federal Emergency Management Agency (FEMA) flood risk databases as well as state and national datasets, we produce continuous flood-probability maps at three example locations in the United States: Houston (TX), Muncy (PA), and Selinsgrove (PA). We find that the discrete flood zones generally communicate substantially lower flood probabilities than the continuous estimates.
