Comparative Analyses of Rain-on-Mesh Flood Models for Predicting Urban Flooding under Climate Change Extremes

The frequency and intensity of extreme precipitation events around the globe are on the rise leading to severe urban flooding that aligns with the projections of the impact of greenhouse gas (GHG) emissions on future climates. As urban flood analysts seek to develop more resilient urban infrastructure against climate change face substantial uncertainty in forecasting the effects of climate change on future storm events. Addressing this uncertainty necessitates simulating numerous potential storm scenarios. Urban flood analysis increasingly relies on high-resolution digital elevation models (DEMs) with rain-on-mesh approaches and 2-D surface hydraulic simulations, which require high-capacity computer workstations and substantial computing time. Simulating many storms with high computing requirements can become a resource constraint for appropriate analyses of climate change resilient urban flood management. Therefore, it is essential to understand the trade-off between computing resources and the accuracy of flood model predictions. This study compared two open-source models (LISFLOOD-FP and Itzi) with a licensed commercial model (InfoWorks ICM) to assess flood risk for Cambridge, Massachusetts, using the rain-on-mesh approach. First, the models were used to predict surface flooding for Cambridge without incorporating any sub-surface drainage structures by comparing spatial resolutions of 1m, 2.5m, 3m, 5m, and 10m for rectangular grids (Itzi and LISFLOOD-FP) and irregular triangular meshes (InfoWorks ICM). Second, InfoWorks ICM and Itzi were compared by incorporating subsurface drainage networks into the study area. Model performances were evaluated using the Cohen’s Kappa statistic on maximum flood depth and the vulnerability of key urban infrastructure assets. InfoWorks ICM demonstrated higher efficiency at finer resolutions but required high-end computing devices with GPU (graphical processing unit) accessibility and only ran on a Windows environment. Results indicated that coarser resolution leads to reduced accuracy. However, what level of accuracy is sufficient for risk assessments? This study aims to provide a trade-off analysis of model accuracy, hardware and license costs, and simulation run times.

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