GeoFlood: Large‐Scale Flood Inundation Mapping Based on High‐Resolution Terrain Analysis

Abstract

Recent floods from intense storms in the southern United States and the unusually active 2017Atlantic hurricane season have highlighted the need for real-time flood inundation mapping using high-resolution topography. High-resolution topographic data derived from lidar technology reveal unprecedented topographic details and are increasingly available, providing extremely valuable information for improving inundation mapping accuracy. The enrichment of terrain details from these data sets, however, also brings challenges to the application of many classic approaches designed for lower-resolution data. Advanced methods need to be developed to better use lidar-derived terrain data for inundation mapping. We present a new workflow, GeoFlood, for flood inundation mapping using high-resolution terrain inputs that is simple and computationally efficient, thus serving the needs of emergency responders to rapidly identify possibly flooded locations. First, GeoNet, a method for automatic channel network extraction from high-resolution topographic data, is modified to produce a low-density, high-fidelity river network. Then, a Height Above Nearest Drainage (HAND) raster is computed to quantify the elevation difference between each land surface cell and the stream bed cell to which it drains, using the network extracted from high-resolution terrain data. This HAND raster is then used to compute reach-average channel hydraulic parameters and synthetic stage-discharge rating curves. Inundation maps are generated from the HAND raster by obtaining a water depth for a given flood discharge from the synthetic rating curve. We evaluate our approach by applying it in the Onion Creek Watershed in Central Texas, comparing the inundation extent results to Federal Emergency Management Agency 100-yr floodplains obtained with detailed local hydraulic studies. We show that the inundation extent produced by GeoFlood overlaps with 60%~90% of the Federal Emergency Management Agency floodplain coverage demonstrating that it is able to capture the general inundation patterns and shows significant potential for informing real-time flood disaster preparedness and response.Plain Language Summary Simple and computationally efficient flood inundation mapping methods are needed to take advantage of increasingly available high-resolution topography data. In this work, we present a new approach, called GeoFlood, for flood inundation mapping using high-resolution topographic data. This approach combines GeoNet, an advanced method for high-resolution terrain data analysis, and the Height Above Nearest Drainage. GeoFlood can rapidly convert real-time forecasted river flow conditions to corresponding flood maps. A case study in central Texas demonstrated that the flood maps generated with our approach capture the majority of the inundated extent reported by detailed Federal Emergency Management Agency flood studies. Our results show that GeoFlood is a valuable solution for rapid inundation mapping. ZHENG ET AL.10,013

An integrated evaluation of the National Water Model (NWM)–Height Above Nearest Drainage (HAND) flood mapping methodology

“…A number of studies have shown the HAND methodology can produce accurate inundation maps from a known streamflow and carefully created HAND layers (Afshari et al, 2018;Rennó et al, 2008;Rodda, 2005;Zheng et al, 2018b). There has not been, however, an exploration of how errors in the NWM-HAND methodology, and its individual components, might compound and propagate through flood simulation.…”

Terrain Analysis Enhancements to the Height Above Nearest Drainage Flood Inundation Mapping Method

“…These distances may be evaluated horizontally or vertically using the D∞ flow model with weighted averaging applied where flow is proportioned between multiple grid cells. The D∞ distance down function, calculated vertically with the target grid cells being stream grid cells, may be used to calculate HAND (Zheng, Maidment, et al, ). This D∞ distance down evaluation of HAND differs from earlier HAND approaches (Nobre et al, ; Nobre et al, ) that use D8.…”

“…Each reach in the National Hydrography Dataset (NHDPlus medium resolution; McKay et al, ) has a separate forecast discharge, and HAND is used to evaluate rating curves and map inundation for the NHDPlus catchment draining into each reach. In another recent study, Zheng, Maidment, et al () implemented the HAND approach with high‐resolution topographic data derived from light detection and ranging using a geodesic minimization technique to map the streams (Passalacqua et al, ; Sangireddy et al, ). This approach maps streams by selecting a flow path to minimize a metric that is a combination of contributing area, curvature, and distance from NHDPlus (medium resolution) streams.…”

Delineation of flood-prone areas using modified topographic index for a river basin

“…Papaioannou et al (2015) studied a multicriteria perspective for delineation of potential floodprone areas for the Xerias River watershed, Greece. Zheng et al (2018) performed similar studies on high-resolution terrain analysis for Onion Creek watershed, central Texas.…”