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 procedure for drainage network identification from geomorphology and its application to the prediction of the hydrologic response
Identifying channel initiation points is central to geomorphology and hydrology as they relate morphology, climate, and soil properties at the boundary between different surface runoff paths. Since catchment response is strongly influenced by the dynamics of water movement on the hillslope and in the channel, rainfall-runoff modeling is one of the fields in which improving the identification of channel initiation can lead to benefits. Among the various filtering criteria that can be found in the literature for channel recognition from digital elevation models, the one using contributing area and topographic slope shows interesting features in this context. Nevertheless, the area-slope criterion has been poorly applied. This is mainly due to the difficulties in objectively defining appropriate threshold values. This study proposes a new procedure to assess the area-slope threshold value. The resulting channel network is then used as input to a semi-distributed, event-based rainfall-runoff model able to describe severe rainfall events in small, steep basins. This model accounts for network and hillslope contributions to the total dispersion in the routing process, a key factor in determining the main features of the hydrologic response. In a geomorphologically homogeneous region, the set of model parameters shows interesting invariance properties with respect to storm and basin characteristics.
Comparison of model prediction with measurements of galactic background noise at L-band
The spectral window at L-band (1.413 GHz) is important for passive remote sensing of surface parameters such as soil moisture and sea surface salinity that are needed to understand the hydrological cycle and ocean circulation. Radiation from celestial sources (mostly galactic) is strong in this window, and an accurate accounting of this background radiation is often needed for calibration. This paper presents a comparison of the background radiation predicted by a model developed from modern radio astronomy measurements with measurements made with several modern L-band remote sensing radiometers. The comparison validates the model and illustrates the magnitude of the correction necessary in remote sensing applications.