Flood-Risk Analysis on Terrains

An important problem in terrain analysis is modeling how water flows across a terrain and creates floods by filling up depressions. In this paper, we study a number of flood-risk related problems: given a terrain Σ, represented as a triangulated xy-monotone surface with n vertices, a rain distribution R, and a volume of rain Ψ, determine which portions of Σ are flooded. We give an overview of efficient algorithms for these problems as well as explore the efficacy and efficiency of these algorithms on real terrains. Flooding can be extremely dangerous and damaging. The United States experienced the wettest 12-month period from June 2018 to May 2019, with major flooding in the Midwest affecting millions of people and causing several billion dollars in damages. Being able to accurately and quickly model flooding can help predict and prepare for the risks. Flood-risk analysis has been studied widely across multiple research communities including environmental science, engineering, machine learning, and GIS communities: see Section 7. Flood risk analysis also has been a focus of a number of companies as well. SCALGO22 is a software development and services company that uses massive terrain dataprocessing technology to provide a flood risk platform for Scandinavian countries. Fathom13 uses high-resolution global data-sets and hydrological modeling to provide flood hazard data for many applications, including insurance and disaster response. Terrain-flood query: given a terrain Σ and a rain pattern, determine which portions of Σ will be flooded. The areas marked in blue are flooded, with regions that water flows over marked in orange. Point-flood query: In some applications, the terrain Σ is fixed and we wish to know whether a query point on Σ will be flooded for a given rain pattern.