This study reports a new and significantly enhanced analysis of US flood hazard at 30 m spatial resolution. Specific improvements include updated hydrography data, new methods to determine channel depth, more rigorous flood frequency analysis, output downscaling to property tract level, and inclusion of the impact of local interventions in the flooding system. For the first time, we consider pluvial, fluvial, and coastal flood hazards within the same framework and provide projections for both current (rather than historic average) conditions and for future time periods centered on 2035 and 2050 under the RCP4.5 emissions pathway. Validation against high‐quality local models and the entire catalog of FEMA 1% annual probability flood maps yielded Critical Success Index values in the range 0.69–0.82. Significant improvements over a previous pluvial/fluvial model version are shown for high‐frequency events and coastal zones, along with minor improvements in areas where model performance was already good. The result is the first comprehensive and consistent national‐scale analysis of flood hazard for the conterminous US for both current and future conditions. Even though we consider a stabilization emissions scenario and a near‐future time horizon, we project clear patterns of changing flood hazard (3σ changes in 100 years inundated area of −3.8 to +16% at 1° scale), that are significant when considered as a proportion of the land area where human use is possible or in terms of the currently protected land area where the standard of flood defense protection may become compromised by this time.

Statistical characteristics of spatial variability in rain fields at the scales below 5 km2 are discussed based on experimental data from five locations worldwide. The work is motivated by the practical needs of remote sensing applications using radar and satellite technologies, and by the scientific needs of rainfall modelling. Two types of rain-field characteristics are described: spatial correlations and conditional probabilities of occurrence. The accumulation intervals range from 5 min to 1 h. The analysed data samples were collected in Brazil, Florida, Iowa, Oklahoma, and on Guam. Résumé Cet article s'intéresse à la variabilité de la pluie à des échelles d'espace inférieures à 5 km2, en s'appuyant sur des données expérimentales de différentes régions du monde. La motivation de ce travail est à la fois pratique, en vue de l'utilisation de la télédétection avec les technologies radar et satellitaires, et scientifique, au regard des besoins en modélisation de la pluie. Deux types de descripteurs de la pluie sont utilisés: la corrélation spatiale et la probabilité conditionnelle d'occurrence. Les périodes de cumul utilisées vont de 5 min à 1 h. Les échantillons de données proviennent du Brésil, de Floride, d'Iowa, d'Oklahoma et de l'île de Guam.

The Iowa Flood Center (IFC), established following the 2008 record floods, has developed a real-time flood forecasting and information dissemination system for use by all Iowans. The system complements the operational forecasting issued by the National Weather Service, is based on sound scientific principles of flood genesis and spatial organization, and includes many technological advances. At its core is a continuous rainfall–runoff model based on landscape decomposition into hillslopes and channel links. Rainfall conversion to runoff is modeled through soil moisture accounting at hillslopes. Channel routing is based on a nonlinear representation of water velocity that considers the discharge amount as well as the upstream drainage area. Mathematically, the model represents a large system of ordinary differential equations organized to follow river network topology. The IFC also developed an efficient numerical solver suitable for high-performance computing architecture. The solver allows the IFC to update forecasts every 15 min for over 1,000 Iowa communities. The input to the system comes from a radar-rainfall algorithm, developed in-house, that maps rainfall every 5 min with high spatial resolution. The algorithm uses Level II radar reflectivity and other polarimetric data from the Weather Surveillance Radar-1988 Dual-Polarimetric (WSR-88DP) radar network. A large library of flood inundation maps and real-time river stage data from over 200 IFC “stream-stage sensors” complement the IFC information system. The system communicates all this information to the general public through a comprehensive browser-based and interactive platform. Streamflow forecasts and observations from Iowa can provide support for a similar system being developed at the National Water Center through model intercomparisons, diagnostic analyses, and product evaluations.

Thirty years ago, Wilson and Brandes determined that radar data was “underutilized and both confusion and misunderstanding exist about the inherent ability of radar to measure rainfall, about factors that contribute to errors, and about the importance of careful calibration and signal processing.” In their seminal work, they addressed these issues by delineating the strengths and weaknesses of radar data and offering a detailed discussion of the different sources of uncertainties associated with radar-based estimates of rainfall. After three decades, we want to underscore the importance of Wilson and Brandes' paper by using it as a reference for discussing subsequent improvements in operational radar-rainfall technology in the United States. We replicated their analysis as closely as we could and present the results in this paper. Our results, which are based on an analysis of Weather Surveillance Radar-1988 Doppler (WSR-88D) data, indicate fairly substantial improvement in terms of the statistical measur... Thirty years ago, Wilson and Brandes determined that radar data was “underutilized and both confusion and misunderstanding exist about the inherent ability of radar to measure rainfall, about factors that contribute to errors, and about the importance of careful calibration and signal processing.” In their seminal work, they addressed these issues by delineating the strengths and weaknesses of radar data and offering a detailed discussion of the different sources of uncertainties associated with radar-based estimates of rainfall. After three decades, we want to underscore the importance of Wilson and Brandes' paper by using it as a reference for discussing subsequent improvements in operational radar-rainfall technology in the United States. We replicated their analysis as closely as we could and present the results in this paper. Our results, which are based on an analysis of Weather Surveillance Radar-1988 Doppler (WSR-88D) data, indicate fairly substantial improvement in terms of the statistical measur...