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).
Geomorphic classifiers for flood-prone areas delineation for data-scarce environments
Abstract Knowing the location and the extent of the areas exposed to flood hazards is essential to any strategy for minimizing the risk. Unfortunately, in ungauged basins the use of traditional floodplain mapping techniques is prevented by the lack of the extensive data required. The present work aims to overcome this limitation by defining an alternative simplified procedure for a preliminary floodplain delineation based on the use of geomorphic classifiers. To validate the method in a data-rich environment, eleven flood-related morphological descriptors derived from remotely sensed elevation data have been used as linear binary classifiers over the Ohio River basin and its sub-catchments. Their performances have been measured at the change of the topography and the size of the calibration area, allowing to explore the transferability of the calibrated parameters, and to define the minimum extent of the calibration area. The best performing classifiers among those analysed have been applied and validated across the continental U.S. The results suggest that the classifier based on the Geomorphic Flood Index (GFI), is the most suitable to detect the flood-prone areas in data-scarce regions and for large-scale applications, providing good accuracies with low requirements in terms of data and computational costs. This index is defined as the logarithm of the ratio between the water depth in the element of the river network closest to the point under exam (estimated using a hydraulic scaling function based on contributing area) and the elevation difference between these two points.
Observations of nearshore infragravity waves: Seaward and shoreward propagating components
[1] The variation of seaward and shoreward infragravity energy fluxes across the shoaling and surf zones of a gently sloping sandy beach is estimated from field observations and related to forcing by groups of sea and swell, dissipation, and shoreline reflection. Data from collocated pressure and velocity sensors deployed between 1 and 6 m water depth are combined, using the assumption of cross-shore propagation, to decompose the infragravity wave field into shoreward and seaward propagating components. Seaward of the surf zone, shoreward propagating infragravity waves are amplified by nonlinear interactions with groups of sea and swell, and the shoreward infragravity energy flux increases in the onshore direction. In the surf zone, nonlinear phase coupling between infragravity waves and groups of sea and swell decreases, as does the shoreward infragravity energy flux, consistent with the cessation of nonlinear forcing and the increased importance of infragravity wave dissipation. Seaward propagating infragravity waves are not phase coupled to incident wave groups, and their energy levels suggest strong infragravity wave reflection near the shoreline. The cross-shore variation of the seaward energy flux is weaker than that of the shoreward flux, resulting in cross-shore variation of the squared infragravity reflection coefficient (ratio of seaward to shoreward energy flux) between about 0.4 and 1.5.