An Integrative Framework for Assessment of Urban Flood Response to Changing Climate

Abstract

Increasing frequency of extreme rainfall induced catastrophic urban flood events in recent decades demands proactive efforts to assess flood risk and vulnerability. Here, we develop an integrative framework for fine spatiotemporal scale assessment of urban flood response to historical and future projected changes in extreme precipitation. The framework includes three main components – nonstationary modelling of historical extreme precipitation, modelling of future precipitation, and urban flood simulations. It also provides robust estimates of uncertainty in design precipitation from statistical modelling, multiple climate models and stochastic uncertainty, estimated using machine learning techniques. We demonstrate the proposed framework for White Oak Bayou watershed in Houston, Texas, US. Two‐dimensional hydrologic‐hydraulic Interconnected Channel and Pond Routing (ICPR) model is used to simulate flood response from design precipitation for historical (1986–2020) and two future (2021–2050 & 2071–2100) periods in three (SSP1‐2.5, SSP2‐4.5 and SSP5‐8.5) future climate scenarios. Results show that nonstationary design estimates for historical precipitation are 14–25% higher than the stationary estimates for 100‐year event of 1‐hour to 24‐hour duration. Contrary to general global trends, we found a significant reduction in future design precipitation in all three emission scenarios. Additionally, stochastic uncertainty in future design precipitations is found to be larger than the modelling uncertainty in historical estimates and climate model uncertainty in future estimates. Flood response in terms of peak flood and total flood volume suggests that the difference in stationary vs. nonstationary historical and future design precipitation are substantial to cause considerable change in simulated flood.