Providing solutions for data scarcity in urban flood modeling through sensitivity analysis and DEM modifications

Abstract

Developing countries face significant challenges in accessing sufficient and reliable hydro-meteorological data, hindering the implementation of effective disaster management strategies. This research proposes solutions for these limitations on performing flood simulations through parameter sensitivity analysis and digital elevation model (DEM) modifications. The methodology provides alternatives to account for insufficient data for rainfall, roughness coefficient, infiltration in simulating large-scale rainfall-runoff, and high-resolution DEMs incorporating road and building networks for urban flood modeling. By applying the method to an extreme flood event in the Marikina Basin, Philippines, a combination of ground-based and remotely retrieved rainfall data, roughness (n = 0.3861–0.5005), and infiltration parameters (Δθ = 0.326–0.505 and ψ = 0.4547–1.565) set at the maximum range were found to replicate the increase in the upstream water level. Simulations were able to accurately capture the flood propagation along the natural and artificial barriers in the urban area compared to untreated digital terrain and surface model (DTM and DSM) data, with root-mean-square error range improvements from 0–7.13 (DTM) and 0.29–4.20 (DSM) to 0–0.63 (modified DEM). The proposed methodology significantly improved the accuracy of the simulations, which is crucial for proposing adequate flood action plans, despite the lack of high-resolution data available for under-developed nations.