GeoFlood Enhancement for Robust Flood Inundation Mapping in Flat Terrain Zones

Flash floods in arid regions dictate a rapid flood inundation mapping for early warning. However, hydrodynamic models, such as HEC-RAS, provide accurate flood mapping but require extensive topographical data and high computational resources. The GeoFlood method offers a rapid alternative for early warning relying on terrain-driven framework and simple hydraulics. This study examined GeoFlood applicability on two arid catchments and tested its sensitivity for different return periods, Manning coefficients, and wadi length segmentations. The original GeoFlood method showed good consistency with HEC-RAS in well-defined wadis but relatively poor performance in flat areas, with segmentation and slope calculation significantly affecting GeoFlood accuracy and robustness. To overcome these limitations, slope calculation was improved using the Theil–Sen trend, and segmentation was automated using the penalized cost approach Continuous Piecewise Optimal Partitioning (CPOP) to detect slope breakpoints. CPOP provides superior and robust performance without prior knowledge of the best segmentation lengths, producing smoother slopes at accurate breakpoints with a Fowlkes–Mallows (FM) index of 0.88 in flat areas and an error bias of 1.05 compared to a variable FM from 0.72 to 0.88 and an error bias from 0.81 to 1.3 for the original GeoFlood. The enhanced GeoFlood provides reliable robust results in arid regions when data are scarce.