洪水概率内插工具（FLOPIT）：通过高分辨率绘图改进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
摘要：
了解洪水发生的可能性对于做出正确的洪水风险管理决策至关重要。许多人依靠洪水概率图来决定购买洪水保险，购买或出售房地产，防洪房屋或管理洪泛区开发。目前的洪水概率图通常使用洪水区（例如1/100或1/500年洪水区）来传达洪水概率。然而，这种沟通方式的选择可能会错过重要的细节，并导致有偏见的风险评估。在这里，我们开发，测试和演示的洪水概率插值工具（FLOPIT）。FLOPIT在水面高程之间插入洪水概率，以生成连续的洪水概率图。我们表明，FLOPIT可以相对容易地应用于现有的数据集用于创建洪水区。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位置产生连续的洪水概率图：休斯顿（德克萨斯州），曼西（宾夕法尼亚州）和Selinsgrove（PA）。我们发现，离散的洪水区一般沟通大大低于洪水的概率比连续的估计。
英文摘要：
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.
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