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Federal Emergency Management Agency (FEMA) Flood Insurance Rate Maps portray the height and extent to which flooding is expected to occur, and they form the basis for setting flood insurance premiums and regulating development in the floodplain. As such, they are an important tool for individuals, businesses, communities, and government agencies to understand and deal with flood hazard and flood risk. Improving map accuracy is therefore not an academic question-better maps help everyone. Making and maintaining an accurate flood map is neither simple nor inexpensive. Even after an investment of more than $1 billion to take flood maps into the digital world, only 21 percent of the population has maps that meet or exceed national flood hazard data quality thresholds. Even when floodplains are mapped with high accuracy, land development and natural changes to the landscape or hydrologic systems create the need for continuous map maintenance and updates. Mapping the Zone examines the factors that affect flood map accuracy, assesses the benefits and costs of more accurate flood maps, and recommends ways to improve flood mapping, communication, and management of flood-related data.
Global Flood Hazard Subject Category Winner, PROSE Awards 2019, Earth Science Selected from more than 500 entries, demonstrating exceptional scholarship and making a significant contribution to the field of study. Flooding is a costly natural disaster in terms of damage to land, property and infrastructure. This volume describes the latest tools and technologies for modeling, mapping, and predicting large-scale flood risk. It also presents readers with a range of remote sensing data sets successfully used for predicting and mapping floods at different scales. These resources can enable policymakers, public planners, and developers to plan for, and respond to, flooding with greater accuracy and effectiveness. Describes the latest large-scale modeling approaches, including hydrological models, 2-D flood inundation models, and global flood forecasting models Showcases new tools and technologies such as Aqueduct, a new web-based tool used for global assessment and projection of future flood risk under climate change scenarios Features case studies describing best-practice uses of modeling techniques, tools, and technologies Global Flood Hazard is an indispensable resource for researchers, consultants, practitioners, and policy makers dealing with flood risk, flood disaster response, flood management, and flood mitigation.
Pt. I. Theory of tropical cyclones. ch. 1. Tropical cyclone structure and dynamics / Jeffrey D. Kepert. ch. 2. Tropical cyclone formation / Kevin J. Tory and William M. Frank. ch. 3. Air-sea interactions in tropical cyclones / Lynn K. Shay. ch. 4. Movement of tropical cyclones / Johnny C.L. Chan. ch. 5. The extratropical transition of tropical cyclones : structural characteristics, downstream impacts, and forecast challenges / Patrick A. Harr -- pt. II. Observations of tropical cyclones. ch. 6. Observing and analyzing the near-surface wind field in tropical cyclones / Mark D. Powell. ch. 7. Satellite observations of tropical cyclones / Christopher Velden and Jeffrey Hawkins. ch. 8. Aircraft observations of tropical cyclones / Sim D. Aberson [und weitere] -- pt. III. Climate variations of tropical cyclone activity. ch. 9. Tropical cyclones and climate change : a review / Thomas Knutson, Chris Landsea and Kerry Emanuel -- pt. IV. Forecasting of tropical cyclones. ch. 10. Track and structure forecasts of tropical cyclones / Julian Heming and Jim Goerss. ch. 11. The influence of natural climate variability on tropical cyclones, and seasonal forecasts of tropical cyclone activity / Suzana J. Camargo [und weitere] -- pt. V. Hydrological aspects of tropical cyclones. ch. 12. Storm surge modeling and applications in coastal areas / Shishir K. Dube [und weitere] -- pt. VI. Societal impacts of tropical cyclones. ch. 13. Disaster mitigation and societal impacts / David King, Jim Davidson and Linda Anderson-Berry
Flooding is the most threatening natural disaster worldwide considering the fatalities and property damage it causes. Recent flood disasters have raised concerns for accurate and responsive inundation forecast due to the rapid spread and astonishing destructive power of these events. Although recent development in large scale hydrologic simulation has enabled the real-time streamflow simulation operating on millions of river reaches, a framework for converting the forecast discharge into corresponding water surface elevation and inundation maps at a continental-scale is absent to better support local flood response. To accurately map flood inundation extent, a comprehensive description of the geometry of the channel is indispensable. As such, this dissertation presents an innovative approach for estimating river geometry and conducting inundation mapping at a continental-scale with a high spatial resolution. This approach is based on the concept of Height Above Nearest Drainage (HAND). Advanced hydrologic terrain analysis workflows have been designed to derive channel hydraulic properties, stage-discharge rating curves, and inundation extents using HAND. After the mechanism being presented, the implementation of this approach across the contiguous United States has been demonstrated using the 10-meter National Elevation Dataset. The integrity of the outputs has been validated through the comparison with best available references at multiple test sites. Considering the increasingly availability of high-resolution topographic data derived from lidar technology, the dissertation further presents how advanced geomorphic feature extraction tools are integrated into the proposed approach to overcome the challenges associated with the enrichment of terrain details. At last, this dissertation presents how banklines, an essential piece of river geometry characteristic as the boundary differentiates channel zone from floodplain, is detected with enhanced geomorphic feature extraction tools for improving large-scale hydrologic simulation and inundation mapping accuracy.
To address the uncertainties of river flood forecasting and to contribute a new visualization for flood mapping, this study outlines a methodology for creating dynamic probabilistic flood inundation maps for a floodplain which currently lacks dynamic flood maps of any kind. To create these maps, a hydrologic model is specially constructed using HEC-RAS for a segment of the Tonawanda Creek in western New York. The model is constructed using pre-existing, publically available data, including a LiDAR digital elevation model, real-time discharge observations from a USGS-maintained gauge on the creek, and other characteristics of the creek's bathymetry derived from previous flood insurance studies. The model is then used to create inundation rasters based on selected initial discharges. To determine probabilities, predicted peak discharges for the Tonawanda Creek are first collected from the Meteorological Model-based Ensemble Forecast System (MMEFS), which generates predictions of various hydrometeorological parameters in real-time, and are used to create a suite of inundation rasters, one for each individual peak discharge prediction. These inundation rasters are then overlaid and the probabilities are calculated by grid cell based on how many inundations overlap. The resulting map depicts the range of flooding extent probabilities based on the real-time forecast. An alternative probabilistic map is also devised to depict the depth of flooding given a flood event's probability. The 10th, 50th, and 90th percentiles are calculated for the forecast ensemble's peak discharge predictions. These percentiles correspond to benchmarks of flooding likelihood, such that the 10th percentile indicates a 90% likely flood event, 50th percentile a 50% event, and 90th percentile a 10% event. Once completed, the maps are qualitatively evaluated for potential applications in predicting flood events and mitigating flood-induced damages.
GeoFlood is a flood inundation mapping package that utilizes a geodesic, cost minimization algorithm to extract channel networks from high resolution terrain data along with National Water Model forecasts and a Height Above Nearest Drainage approach to create near real time flood inundation maps. Earlier work has applied the GeoFlood framework at the scale of a single Hydrologic Unit Code 12 watershed, but this work extended the application to seven counties across the state of Texas. One meter resolution lidar digital elevation models were generated for each county and segmented by watershed, resulting in approximately 400 gigabytes of input data. Two cost functions were found to improve the channel network extraction capabilities. The unique aspect of the first cost function was the inclusion of a cost threshold, which served to increase the penalty for pixels that had a cost above a given limit, thereby restricting the extracted channel to only the minimum cost path and preventing shortcuts. A second cost function, featuring a binary representation of the National Hydrography Data high resolution flowlines, was used to improve the performance of the threshold based cost function in the presence of artificial features or within low relief topography. Four variations of a channel bed slope calculation were tested, two that were end point based and two that utilized a linear regression. The end point based methods were shown to have synthetic rating curves with a smaller percent error and variance across the first three meters of stage height, as well as less area separation from the corresponding United States Geological Survey synthetic rating curves than the regression based methods. Identification of the reaches in which the slope calculation method was most significant was conducted by analyzing the variance and standard deviation across the four computed slopes. Artificial and canal reaches at a low level (1 - 2) and high stream order (5 - 7) were found to have the most variance across their computed slopes. A reach being hydro-flattened was determined to most likely not be the sole limiting factor when it comes to the accuracy of GeoFlood derived products. An approximately equal number of low and high error synthetic rating curves were produced from hydro-flattened reaches. While improvement to the model can always be made, the application of GeoFlood across seven counties in Texas, using high resolution terrain data, was a step forward in regard to showing that GeoFlood can be applied to larger study areas than just a single watershed, including the potential for statewide and or national implementation