Application-Oriented Methods for Obtaining Geometrically Robust Digital Surface Models for Flood Hazard Assessment

Digital surface models (DSMs) play a critical role in obtaining reliable flood hazard maps for urban areas. Widespread availability of LiDAR data (where available) greatly facilitates obtaining geometrically sound DSMs. However, to date, insufficient attention has been paid to generating methodological approaches to obtain geometrically consistent DSMs. Here, we propose an application-oriented protocol to obtain a geometrically robust DSM (DSM1 hereafter). Additionally, two further DSMs were produced considering, firstly, depiction of streets using breaklines as ancillary information (DSM2) and, secondly, direct interpolation of LiDAR data (DSM3). Geometric robustness of these DSMs was evaluated qualitatively, by plotting longitudinal profiles and cross sections to dominant runoff pathways, as well as quantitatively, through assessing DSMs vertical accuracy. We also assessed impact on hazard maps depending on geometric consistency of DSMs employed. To do so, hydraulic outputs resulting from DSM1 were used as a benchmark to compare hydraulic outputs obtained from DSM2 and DSM3. This comparison was made at two spatial resolution levels: i) considering total area flooded in each case through determining the F statistic; and ii) at the level of each pixel by calculating the kappa statistic from a confusion matrix. Our results revealed that: 1) DSM1 defined geometrically consistent configurations for main runoff pathways; 2) in urban areas with higher street and building density DSM1 provided better vertical accuracies than DSM2 and DSM3; and 3) reliability of flood hazard maps strongly depend on geometric quality of the DSMs produced. Findings deployed here, might be very valuable in achieving further reduction and better flood risk management.