Dataset of 100-year flood susceptibility maps for the continental U.S. derived with a geomorphic method
Efficient strategies for preparing communities to protect against, respond to, recover from, and mitigate flood hazard are often hampered by the lack of information about the position and extent of flood-prone areas. Hydrologic and hydraulic analyses allow to obtain detailed flood hazard maps, but are a computationally intensive exercise requiring a significant amount of input data, which are rarely available both in developing and developed countries. As a consequence, even in data-rich environments, official flood hazard graduations are often affected by extensive gaps. In the U.S., for instance, the detailed floodplain delineation produced by the Federal Emergency Management Agency (FEMA) is incomplete, with many counties having no floodplain mapping at all. In this article we present a mapping dataset containing 100-year flood susceptibility maps for the continental U.S. with a 90 m resolution. They have been obtained performing a linear binary classification based on the Geomorphic Flood Index (GFI). To the best knowledge of the authors, there are no available flood-prone areas maps for the entire continental U.S. with resolution lower that 30׳׳×30׳׳ (approximatively 1 km at the equator).
A GIS tool for cost-effective delineation of flood-prone areas
Abstract Delineation of flood hazard and flood risk areas is a critical issue, but practical difficulties regularly make complete achievement of the task a challenge. In data-scarce environments (e.g. ungauged basins, large-scale analyses), useful information about flood hazard exposure can be obtained using geomorphic methods. In order to advance this field of research, we implemented in the QGIS environment an automated DEM-based procedure that exhibited high accuracy and reliability in identifying the flood-prone areas in several test sites located in Europe, the United States and Africa. This tool, named Geomorphic Flood Area tool (GFA tool), enables rapid and cost-effective flood mapping by performing a linear binary classification based on the recently proposed Geomorphic Flood Index (GFI). The GFA tool provides a user-friendly strategy to map flood exposure over large areas. A demonstrative application of the GFA tool is presented in which a detailed flood map was derived for Romania.
The MultiRISK platform: The technical concept and application of a regional-scale multihazard exposure analysis tool
Many regions worldwide are threatened by multiple natural hazards with the potential to cause high damages and losses. However, the modeling of multiple hazards in a joint analysis scheme is still in the early stages of development as a range of serious challenges emerges in the multihazard context such as differing modeling approaches in use for contrasting hazards; the time- and data-demanding conduct of each single preparative, intermediate and analysis step; and the clear visualization of the modeling outcome. Under consideration of these difficulties, a regional multihazard exposure analysis concept is developed for five natural hazards: debris flows, rock falls, shallow landslides, avalanches, and river floods, complemented by a visualization scheme to present the modeling outcome. An automation of the two schemes resulted in a beta version of the MultiRISK modeling and the MultiRISK visualization software tool forming together the MultiRISK platform. To test the analysis scheme and the software implementation of MultiRISK a case study is performed in the Barcelonnette basin in France with a worst-case parameterization of the models on the basis of extensive literature reviews. Experiences from this case study offered many insights into the multihazard topic and even more questions, e.g. with respect to coherent multihazard model parameterization, validation or the comparability and interpretation of single-hazard modeling results, respectively. Although analysis schemes can be proposed and software tools can be provided to facilitate many steps, a well-conceived and reflective approach to multihazard settings is essential. The worst-case analysis based on literature values apparently leads to an overestimation of the susceptible areas and the number of exposed elements. Nevertheless, depending on the data situation of an area, especially in areas without any information on past events, this approach may offer the determination of general hazard distributions, overlaps, and areas of potential risk without data-demanding calibration.