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Sample records for flood hazard map

  1. Mapping flood hazards under uncertainty through probabilistic flood inundation maps

    Science.gov (United States)

    Stephens, T.; Bledsoe, B. P.; Miller, A. J.; Lee, G.

    2017-12-01

    Changing precipitation, rapid urbanization, and population growth interact to create unprecedented challenges for flood mitigation and management. Standard methods for estimating risk from flood inundation maps generally involve simulations of floodplain hydraulics for an established regulatory discharge of specified frequency. Hydraulic model results are then geospatially mapped and depicted as a discrete boundary of flood extents and a binary representation of the probability of inundation (in or out) that is assumed constant over a project's lifetime. Consequently, existing methods utilized to define flood hazards and assess risk management are hindered by deterministic approaches that assume stationarity in a nonstationary world, failing to account for spatio-temporal variability of climate and land use as they translate to hydraulic models. This presentation outlines novel techniques for portraying flood hazards and the results of multiple flood inundation maps spanning hydroclimatic regions. Flood inundation maps generated through modeling of floodplain hydraulics are probabilistic reflecting uncertainty quantified through Monte-Carlo analyses of model inputs and parameters under current and future scenarios. The likelihood of inundation and range of variability in flood extents resulting from Monte-Carlo simulations are then compared with deterministic evaluations of flood hazards from current regulatory flood hazard maps. By facilitating alternative approaches of portraying flood hazards, the novel techniques described in this presentation can contribute to a shifting paradigm in flood management that acknowledges the inherent uncertainty in model estimates and the nonstationary behavior of land use and climate.

  2. Flood Risk and Flood hazard maps - Visualisation of hydrological risks

    International Nuclear Information System (INIS)

    Spachinger, Karl; Dorner, Wolfgang; Metzka, Rudolf; Serrhini, Kamal; Fuchs, Sven

    2008-01-01

    Hydrological models are an important basis of flood forecasting and early warning systems. They provide significant data on hydrological risks. In combination with other modelling techniques, such as hydrodynamic models, they can be used to assess the extent and impact of hydrological events. The new European Flood Directive forces all member states to evaluate flood risk on a catchment scale, to compile maps of flood hazard and flood risk for prone areas, and to inform on a local level about these risks. Flood hazard and flood risk maps are important tools to communicate flood risk to different target groups. They provide compiled information to relevant public bodies such as water management authorities, municipalities, or civil protection agencies, but also to the broader public. For almost each section of a river basin, run-off and water levels can be defined based on the likelihood of annual recurrence, using a combination of hydrological and hydrodynamic models, supplemented by an analysis of historical records and mappings. In combination with data related to the vulnerability of a region risk maps can be derived. The project RISKCATCH addressed these issues of hydrological risk and vulnerability assessment focusing on the flood risk management process. Flood hazard maps and flood risk maps were compiled for Austrian and German test sites taking into account existing national and international guidelines. These maps were evaluated by eye-tracking using experimental graphic semiology. Sets of small-scale as well as large-scale risk maps were presented to test persons in order to (1) study reading behaviour as well as understanding and (2) deduce the most attractive components that are essential for target-oriented risk communication. A cognitive survey asking for negative and positive aspects and complexity of each single map complemented the experimental graphic semiology. The results indicate how risk maps can be improved to fit the needs of different user

  3. Going beyond the flood insurance rate map: insights from flood hazard map co-production

    Directory of Open Access Journals (Sweden)

    A. Luke

    2018-04-01

    Full Text Available Flood hazard mapping in the United States (US is deeply tied to the National Flood Insurance Program (NFIP. Consequently, publicly available flood maps provide essential information for insurance purposes, but they do not necessarily provide relevant information for non-insurance aspects of flood risk management (FRM such as public education and emergency planning. Recent calls for flood hazard maps that support a wider variety of FRM tasks highlight the need to deepen our understanding about the factors that make flood maps useful and understandable for local end users. In this study, social scientists and engineers explore opportunities for improving the utility and relevance of flood hazard maps through the co-production of maps responsive to end users' FRM needs. Specifically, two-dimensional flood modeling produced a set of baseline hazard maps for stakeholders of the Tijuana River valley, US, and Los Laureles Canyon in Tijuana, Mexico. Focus groups with natural resource managers, city planners, emergency managers, academia, non-profit, and community leaders refined the baseline hazard maps by triggering additional modeling scenarios and map revisions. Several important end user preferences emerged, such as (1 legends that frame flood intensity both qualitatively and quantitatively, and (2 flood scenario descriptions that report flood magnitude in terms of rainfall, streamflow, and its relation to an historic event. Regarding desired hazard map content, end users' requests revealed general consistency with mapping needs reported in European studies and guidelines published in Australia. However, requested map content that is not commonly produced included (1 standing water depths following the flood, (2 the erosive potential of flowing water, and (3 pluvial flood hazards, or flooding caused directly by rainfall. We conclude that the relevance and utility of commonly produced flood hazard maps can be most improved by illustrating

  4. Going beyond the flood insurance rate map: insights from flood hazard map co-production

    Science.gov (United States)

    Luke, Adam; Sanders, Brett F.; Goodrich, Kristen A.; Feldman, David L.; Boudreau, Danielle; Eguiarte, Ana; Serrano, Kimberly; Reyes, Abigail; Schubert, Jochen E.; AghaKouchak, Amir; Basolo, Victoria; Matthew, Richard A.

    2018-04-01

    Flood hazard mapping in the United States (US) is deeply tied to the National Flood Insurance Program (NFIP). Consequently, publicly available flood maps provide essential information for insurance purposes, but they do not necessarily provide relevant information for non-insurance aspects of flood risk management (FRM) such as public education and emergency planning. Recent calls for flood hazard maps that support a wider variety of FRM tasks highlight the need to deepen our understanding about the factors that make flood maps useful and understandable for local end users. In this study, social scientists and engineers explore opportunities for improving the utility and relevance of flood hazard maps through the co-production of maps responsive to end users' FRM needs. Specifically, two-dimensional flood modeling produced a set of baseline hazard maps for stakeholders of the Tijuana River valley, US, and Los Laureles Canyon in Tijuana, Mexico. Focus groups with natural resource managers, city planners, emergency managers, academia, non-profit, and community leaders refined the baseline hazard maps by triggering additional modeling scenarios and map revisions. Several important end user preferences emerged, such as (1) legends that frame flood intensity both qualitatively and quantitatively, and (2) flood scenario descriptions that report flood magnitude in terms of rainfall, streamflow, and its relation to an historic event. Regarding desired hazard map content, end users' requests revealed general consistency with mapping needs reported in European studies and guidelines published in Australia. However, requested map content that is not commonly produced included (1) standing water depths following the flood, (2) the erosive potential of flowing water, and (3) pluvial flood hazards, or flooding caused directly by rainfall. We conclude that the relevance and utility of commonly produced flood hazard maps can be most improved by illustrating pluvial flood hazards

  5. Flood Hazard Mapping by Applying Fuzzy TOPSIS Method

    Science.gov (United States)

    Han, K. Y.; Lee, J. Y.; Keum, H.; Kim, B. J.; Kim, T. H.

    2017-12-01

    There are lots of technical methods to integrate various factors for flood hazard mapping. The purpose of this study is to suggest the methodology of integrated flood hazard mapping using MCDM(Multi Criteria Decision Making). MCDM problems involve a set of alternatives that are evaluated on the basis of conflicting and incommensurate criteria. In this study, to apply MCDM to assessing flood risk, maximum flood depth, maximum velocity, and maximum travel time are considered as criterion, and each applied elements are considered as alternatives. The scheme to find the efficient alternative closest to a ideal value is appropriate way to assess flood risk of a lot of element units(alternatives) based on various flood indices. Therefore, TOPSIS which is most commonly used MCDM scheme is adopted to create flood hazard map. The indices for flood hazard mapping(maximum flood depth, maximum velocity, and maximum travel time) have uncertainty concerning simulation results due to various values according to flood scenario and topographical condition. These kind of ambiguity of indices can cause uncertainty of flood hazard map. To consider ambiguity and uncertainty of criterion, fuzzy logic is introduced which is able to handle ambiguous expression. In this paper, we made Flood Hazard Map according to levee breach overflow using the Fuzzy TOPSIS Technique. We confirmed the areas where the highest grade of hazard was recorded through the drawn-up integrated flood hazard map, and then produced flood hazard map can be compared them with those indicated in the existing flood risk maps. Also, we expect that if we can apply the flood hazard map methodology suggested in this paper even to manufacturing the current flood risk maps, we will be able to make a new flood hazard map to even consider the priorities for hazard areas, including more varied and important information than ever before. Keywords : Flood hazard map; levee break analysis; 2D analysis; MCDM; Fuzzy TOPSIS

  6. Scoping of flood hazard mapping needs for Cumberland County, Maine

    Science.gov (United States)

    Dudley, Robert W.; Schalk, Charles W.

    2006-01-01

    This report was prepared by the U.S. Geological Survey (USGS) Maine Water Science Center as the deliverable for scoping of flood hazard mapping needs for Cumberland County, Maine, under Federal Emergency Management Agency (FEMA) Inter-Agency Agreement Number HSFE01-05-X-0018. This section of the report explains the objective of the task and the purpose of the report. The Federal Emergency Management Agency (FEMA) developed a plan in 1997 to modernize the FEMA flood mapping program. FEMA flood maps delineate flood hazard areas in support of the National Flood Insurance Program (NFIP). FEMA's plan outlined the steps necessary to update FEMA's flood maps for the nation to a seamless digital format and streamline FEMA's operations in raising public awareness of the importance of the maps and responding to requests to revise them. The modernization of flood maps involves conversion of existing information to digital format and integration of improved flood hazard data as needed. To determine flood mapping modernization needs, FEMA has established specific scoping activities to be done on a county-by-county basis for identifying and prioritizing requisite flood-mapping activities for map modernization. The U.S. Geological Survey (USGS), in cooperation with FEMA and the Maine State Planning Office Floodplain Management Program, began scoping work in 2005 for Cumberland County. Scoping activities included assembling existing data and map needs information for communities in Cumberland County, documentation of data, contacts, community meetings, and prioritized mapping needs in a final scoping report (this document), and updating the Mapping Needs Update Support System (MNUSS) Database or its successor with information gathered during the scoping process. The average age of the FEMA floodplain maps in Cumberland County, Maine is 21 years. Most of these studies were in the early to mid 1980s. However, in the ensuing 20-25 years, development has occurred in many of the

  7. Scoping of flood hazard mapping needs for Kennebec County, Maine

    Science.gov (United States)

    Dudley, Robert W.; Schalk, Charles W.

    2006-01-01

    This report was prepared by the U.S. Geological Survey (USGS) Maine Water Science Center as the deliverable for scoping of flood hazard mapping needs for Kennebec County, Maine, under Federal Emergency Management Agency (FEMA) Inter-Agency Agreement Number HSFE01-05-X-0018. This section of the report explains the objective of the task and the purpose of the report. The Federal Emergency Management Agency (FEMA) developed a plan in 1997 to modernize the FEMA flood mapping program. FEMA flood maps delineate flood hazard areas in support of the National Flood Insurance Program (NFIP). FEMA's plan outlined the steps necessary to update FEMA's flood maps for the nation to a seamless digital format and streamline FEMA's operations in raising public awareness of the importance of the maps and responding to requests to revise them. The modernization of flood maps involves conversion of existing information to digital format and integration of improved flood hazard data as needed. To determine flood mapping modernization needs, FEMA has established specific scoping activities to be done on a county-by-county basis for identifying and prioritizing requisite flood-mapping activities for map modernization. The U.S. Geological Survey (USGS), in cooperation with FEMA and the Maine State Planning Office Floodplain Management Program, began scoping work in 2005 for Kennebec County. Scoping activities included assembling existing data and map needs information for communities in Kennebec County (efforts were made to not duplicate those of pre-scoping completed in March 2005), documentation of data, contacts, community meetings, and prioritized mapping needs in a final scoping report (this document), and updating the Mapping Needs Update Support System (MNUSS) Database or its successor with information gathered during the scoping process. The average age of the FEMA floodplain maps in Kennebec County, Maine is 16 years. Most of these studies were in the late 1970's to the mid 1980s

  8. Scoping of flood hazard mapping needs for Somerset County, Maine

    Science.gov (United States)

    Dudley, Robert W.; Schalk, Charles W.

    2006-01-01

    This report was prepared by the U.S. Geological Survey (USGS) Maine Water Science Center as the deliverable for scoping of flood hazard mapping needs for Somerset County, Maine, under Federal Emergency Management Agency (FEMA) Inter-Agency Agreement Number HSFE01-05-X-0018. This section of the report explains the objective of the task and the purpose of the report. The Federal Emergency Management Agency (FEMA) developed a plan in 1997 to modernize the FEMA flood mapping program. FEMA flood maps delineate flood hazard areas in support of the National Flood Insurance Program (NFIP). FEMA's plan outlined the steps necessary to update FEMA's flood maps for the nation to a seamless digital format and streamline FEMA's operations in raising public awareness of the importance of the maps and responding to requests to revise them. The modernization of flood maps involves conversion of existing information to digital format and integration of improved flood hazard data as needed. To determine flood mapping modernization needs, FEMA has established specific scoping activities to be done on a county-by-county basis for identifying and prioritizing requisite flood-mapping activities for map modernization. The U.S. Geological Survey (USGS), in cooperation with FEMA and the Maine State Planning Office Floodplain Management Program, began scoping work in 2005 for Somerset County. Scoping activities included assembling existing data and map needs information for communities in Somerset County (efforts were made to not duplicate those of pre-scoping completed in March 2005), documentation of data, contacts, community meetings, and prioritized mapping needs in a final scoping report (this document), and updating the Mapping Needs Update Support System (MNUSS) Database or its successor with information gathered during the scoping process. The average age of the FEMA floodplain maps in Somerset County, Maine is 18.1 years. Most of these studies were in the late 1970's to the mid 1980

  9. Flood Impacts on People: from Hazard to Risk Maps

    Science.gov (United States)

    Arrighi, C.; Castelli, F.

    2017-12-01

    The mitigation of adverse consequences of floods on people is crucial for civil protection and public authorities. According to several studies, in the developed countries the majority of flood-related fatalities occurs due to inappropriate high risk behaviours such as driving and walking in floodwaters. In this work both the loss of stability of vehicles and pedestrians in floodwaters are analysed. Flood hazard is evaluated, based on (i) a 2D inundation model of an urban area, (ii) 3D hydrodynamic simulations of water flows around vehicles and human body and (iii) a dimensional analysis of experimental activity. Exposure and vulnerability of vehicles and population are assessed exploiting several sources of open GIS data in order to produce risk maps for a testing case study. The results show that a significant hazard to vehicles and pedestrians exists in the study area. Particularly high is the hazard to vehicles, which are likely to be swept away by flood flow, possibly aggravate damages to structures and infrastructures and locally alter the flood propagation. Exposure and vulnerability analysis identifies some structures such as schools and public facilities, which may attract several people. Moreover, some shopping facilities in the area, which attract both vehicular and pedestrians' circulation are located in the highest flood hazard zone.The application of the method demonstrates that, at municipal level, such risk maps can support civil defence strategies and education to active citizenship, thus contributing to flood impact reduction to population.

  10. 44 CFR 65.11 - Evaluation of sand dunes in mapping coastal flood hazard areas.

    Science.gov (United States)

    2010-10-01

    ... mapping coastal flood hazard areas. 65.11 Section 65.11 Emergency Management and Assistance FEDERAL... Insurance Program IDENTIFICATION AND MAPPING OF SPECIAL HAZARD AREAS § 65.11 Evaluation of sand dunes in mapping coastal flood hazard areas. (a) General conditions. For purposes of the NFIP, FEMA will consider...

  11. Evaluation of flood hazard maps in print and web mapping services as information tools in flood risk communication

    Science.gov (United States)

    Hagemeier-Klose, M.; Wagner, K.

    2009-04-01

    Flood risk communication with the general public and the population at risk is getting increasingly important for flood risk management, especially as a precautionary measure. This is also underlined by the EU Flood Directive. The flood related authorities therefore have to develop adjusted information tools which meet the demands of different user groups. This article presents the formative evaluation of flood hazard maps and web mapping services according to the specific requirements and needs of the general public using the dynamic-transactional approach as a theoretical framework. The evaluation was done by a mixture of different methods; an analysis of existing tools, a creative workshop with experts and laymen and an online survey. The currently existing flood hazard maps or web mapping services or web GIS still lack a good balance between simplicity and complexity with adequate readability and usability for the public. Well designed and associative maps (e.g. using blue colours for water depths) which can be compared with past local flood events and which can create empathy in viewers, can help to raise awareness, to heighten the activity and knowledge level or can lead to further information seeking. Concerning web mapping services, a linkage between general flood information like flood extents of different scenarios and corresponding water depths and real time information like gauge levels is an important demand by users. Gauge levels of these scenarios are easier to understand than the scientifically correct return periods or annualities. The recently developed Bavarian web mapping service tries to integrate these requirements.

  12. Flood Hazard Area

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The National Flood Hazard Layer (NFHL) data incorporates all Digital Flood Insurance Rate Map(DFIRM) databases published by FEMA, and any Letters Of Map Revision...

  13. Flood Hazard Boundaries

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The National Flood Hazard Layer (NFHL) data incorporates all Digital Flood Insurance Rate Map(DFIRM) databases published by FEMA, and any Letters Of Map Revision...

  14. Assessment of Three Flood Hazard Mapping Methods: A Case Study of Perlis

    Science.gov (United States)

    Azizat, Nazirah; Omar, Wan Mohd Sabki Wan

    2018-03-01

    Flood is a common natural disaster and also affect the all state in Malaysia. Regarding to Drainage and Irrigation Department (DID) in 2007, about 29, 270 km2 or 9 percent of region of the country is prone to flooding. Flood can be such devastating catastrophic which can effected to people, economy and environment. Flood hazard mapping can be used is an important part in flood assessment to define those high risk area prone to flooding. The purposes of this study are to prepare a flood hazard mapping in Perlis and to evaluate flood hazard using frequency ratio, statistical index and Poisson method. The six factors affecting the occurrence of flood including elevation, distance from the drainage network, rainfall, soil texture, geology and erosion were created using ArcGIS 10.1 software. Flood location map in this study has been generated based on flooded area in year 2010 from DID. These parameters and flood location map were analysed to prepare flood hazard mapping in representing the probability of flood area. The results of the analysis were verified using flood location data in year 2013, 2014, 2015. The comparison result showed statistical index method is better in prediction of flood area rather than frequency ratio and Poisson method.

  15. Modelling Inland Flood Events for Hazard Maps in Taiwan

    Science.gov (United States)

    Ghosh, S.; Nzerem, K.; Sassi, M.; Hilberts, A.; Assteerawatt, A.; Tillmanns, S.; Mathur, P.; Mitas, C.; Rafique, F.

    2015-12-01

    Taiwan experiences significant inland flooding, driven by torrential rainfall from plum rain storms and typhoons during summer and fall. From last 13 to 16 years data, 3,000 buildings were damaged by such floods annually with a loss US$0.41 billion (Water Resources Agency). This long, narrow island nation with mostly hilly/mountainous topography is located at tropical-subtropical zone with annual average typhoon-hit-frequency of 3-4 (Central Weather Bureau) and annual average precipitation of 2502mm (WRA) - 2.5 times of the world's average. Spatial and temporal distributions of countrywide precipitation are uneven, with very high local extreme rainfall intensities. Annual average precipitation is 3000-5000mm in the mountainous regions, 78% of it falls in May-October, and the 1-hour to 3-day maximum rainfall are about 85 to 93% of the world records (WRA). Rivers in Taiwan are short with small upstream areas and high runoff coefficients of watersheds. These rivers have the steepest slopes, the shortest response time with rapid flows, and the largest peak flows as well as specific flood peak discharge (WRA) in the world. RMS has recently developed a countrywide inland flood model for Taiwan, producing hazard return period maps at 1arcsec grid resolution. These can be the basis for evaluating and managing flood risk, its economic impacts, and insured flood losses. The model is initiated with sub-daily historical meteorological forcings and calibrated to daily discharge observations at about 50 river gauges over the period 2003-2013. Simulations of hydrologic processes, via rainfall-runoff and routing models, are subsequently performed based on a 10000 year set of stochastic forcing. The rainfall-runoff model is physically based continuous, semi-distributed model for catchment hydrology. The 1-D wave propagation hydraulic model considers catchment runoff in routing and describes large-scale transport processes along the river. It also accounts for reservoir storage

  16. Evaluation of flood hazard maps in print and web mapping services as information tools in flood risk communication

    Directory of Open Access Journals (Sweden)

    M. Hagemeier-Klose

    2009-04-01

    Full Text Available Flood risk communication with the general public and the population at risk is getting increasingly important for flood risk management, especially as a precautionary measure. This is also underlined by the EU Flood Directive. The flood related authorities therefore have to develop adjusted information tools which meet the demands of different user groups. This article presents the formative evaluation of flood hazard maps and web mapping services according to the specific requirements and needs of the general public using the dynamic-transactional approach as a theoretical framework. The evaluation was done by a mixture of different methods; an analysis of existing tools, a creative workshop with experts and laymen and an online survey.

    The currently existing flood hazard maps or web mapping services or web GIS still lack a good balance between simplicity and complexity with adequate readability and usability for the public. Well designed and associative maps (e.g. using blue colours for water depths which can be compared with past local flood events and which can create empathy in viewers, can help to raise awareness, to heighten the activity and knowledge level or can lead to further information seeking. Concerning web mapping services, a linkage between general flood information like flood extents of different scenarios and corresponding water depths and real time information like gauge levels is an important demand by users. Gauge levels of these scenarios are easier to understand than the scientifically correct return periods or annualities. The recently developed Bavarian web mapping service tries to integrate these requirements.

  17. Stochastic Urban Pluvial Flood Hazard Maps Based upon a Spatial-Temporal Rainfall Generator

    Directory of Open Access Journals (Sweden)

    Nuno Eduardo Simões

    2015-06-01

    Full Text Available It is a common practice to assign the return period of a given storm event to the urban pluvial flood event that such storm generates. However, this approach may be inappropriate as rainfall events with the same return period can produce different urban pluvial flooding events, i.e., with different associated flood extent, water levels and return periods. This depends on the characteristics of the rainfall events, such as spatial variability, and on other characteristics of the sewer system and the catchment. To address this, the paper presents an innovative contribution to produce stochastic urban pluvial flood hazard maps. A stochastic rainfall generator for urban-scale applications was employed to generate an ensemble of spatially—and temporally—variable design storms with similar return period. These were used as input to the urban drainage model of a pilot urban catchment (~9 km2 located in London, UK. Stochastic flood hazard maps were generated through a frequency analysis of the flooding generated by the various storm events. The stochastic flood hazard maps obtained show that rainfall spatial-temporal variability is an important factor in the estimation of flood likelihood in urban areas. Moreover, as compared to the flood hazard maps obtained by using a single spatially-uniform storm event, the stochastic maps generated in this study provide a more comprehensive assessment of flood hazard which enables better informed flood risk management decisions.

  18. Sustainability-Based Flood Hazard Mapping of the Swannanoa River Watershed

    Directory of Open Access Journals (Sweden)

    Ebrahim Ahmadisharaf

    2017-09-01

    Full Text Available An integrated framework is presented for sustainability-based flood hazard mapping of the Swannanoa River watershed in the state of North Carolina, U.S. The framework uses a hydrologic model for rainfall–runoff transformation, a two-dimensional unsteady hydraulic model flood simulation and a GIS-based multi-criteria decision-making technique for flood hazard mapping. Economic, social, and environmental flood hazards are taken into account. The importance of each hazard is quantified through a survey to the experts. Utilizing the proposed framework, sustainability-based flood hazard mapping is performed for the 100-year design event. As a result, the overall flood hazard is provided in each geographic location. The sensitivity of the overall hazard with respect to the weights of the three hazard components were also investigated. While the conventional flood management approach is to assess the environmental impacts of mitigation measures after a set of feasible options are selected, the presented framework incorporates the environmental impacts into the analysis concurrently with the economic and social influences. Thereby, it provides a more sustainable perspective of flood management and can greatly help the decision makers to make better-informed decisions by clearly understanding the impacts of flooding on economy, society and environment.

  19. The Use of Geospatial Technologies in Flood Hazard Mapping and Assessment: Case Study from River Evros

    Science.gov (United States)

    Mentzafou, Angeliki; Markogianni, Vasiliki; Dimitriou, Elias

    2017-02-01

    Many scientists link climate change to the increase of the extreme weather phenomena frequency, which combined with land use changes often lead to disasters with severe social and economic effects. Especially floods as a consequence of heavy rainfall can put vulnerable human and natural systems such as transboundary wetlands at risk. In order to meet the European Directive 2007/60/EC requirements for the development of flood risk management plans, the flood hazard map of Evros transboundary watershed was produced after a grid-based GIS modelling method that aggregates the main factors related to the development of floods: topography, land use, geology, slope, flow accumulation and rainfall intensity. The verification of this tool was achieved through the comparison between the produced hazard map and the inundation maps derived from the supervised classification of Landsat 5 and 7 satellite imageries of four flood events that took place at Evros delta proximity, a wetland of international importance. The comparison of the modelled output (high and very high flood hazard areas) with the extent of the inundated areas as mapped from the satellite data indicated the satisfactory performance of the model. Furthermore, the vulnerability of each land use against the flood events was examined. Geographically Weighted Regression has also been applied between the final flood hazard map and the major factors in order to ascertain their contribution to flood events. The results accredited the existence of a strong relationship between land uses and flood hazard indicating the flood susceptibility of the lowlands and agricultural land. A dynamic transboundary flood hazard management plan should be developed in order to meet the Flood Directive requirements for adequate and coordinated mitigation practices to reduce flood risk.

  20. Flood Hazard Mapping by Using Geographic Information System and Hydraulic Model: Mert River, Samsun, Turkey

    Directory of Open Access Journals (Sweden)

    Vahdettin Demir

    2016-01-01

    Full Text Available In this study, flood hazard maps were prepared for the Mert River Basin, Samsun, Turkey, by using GIS and Hydrologic Engineering Centers River Analysis System (HEC-RAS. In this river basin, human life losses and a significant amount of property damages were experienced in 2012 flood. The preparation of flood risk maps employed in the study includes the following steps: (1 digitization of topographical data and preparation of digital elevation model using ArcGIS, (2 simulation of flood lows of different return periods using a hydraulic model (HEC-RAS, and (3 preparation of flood risk maps by integrating the results of (1 and (2.

  1. Hydrology Analysis and Modelling for Klang River Basin Flood Hazard Map

    Science.gov (United States)

    Sidek, L. M.; Rostam, N. E.; Hidayah, B.; Roseli, ZA; Majid, W. H. A. W. A.; Zahari, N. Z.; Salleh, S. H. M.; Ahmad, R. D. R.; Ahmad, M. N.

    2016-03-01

    Flooding, a common environmental hazard worldwide has in recent times, increased as a result of climate change and urbanization with the effects felt more in developing countries. As a result, the explosive of flooding to Tenaga Nasional Berhad (TNB) substation is increased rapidly due to existing substations are located in flood prone area. By understanding the impact of flood to their substation, TNB has provided the non-structure mitigation with the integration of Flood Hazard Map with their substation. Hydrology analysis is the important part in providing runoff as the input for the hydraulic part.

  2. Scoping of Flood Hazard Mapping Needs for Coos County, New Hampshire

    National Research Council Canada - National Science Library

    Flynn, Robert H

    2006-01-01

    This report was prepared by the U.S. Geological Survey (USGS) New Hampshire/Vermont Water Science Center for scoping of flood-hazard mapping needs for Coos County, New Hampshire, under Federal Emergency Management Agency (FEMA...

  3. Scoping of Flood Hazard Mapping Needs for Belknap County, New Hampshire

    National Research Council Canada - National Science Library

    Flynn, Robert H

    2006-01-01

    This report was prepared by the U.S. Geological Survey (USGS) New Hampshire/Vermont Water Science Center for scoping of flood-hazard mapping needs for Belknap County, New Hampshire, under Federal Emergency Management Agency (FEMA...

  4. Scoping of Flood Hazard Mapping Needs for Merrimack County, New Hampshire

    National Research Council Canada - National Science Library

    Flynn, Robert H

    2006-01-01

    This report was prepared by the U.S. Geological Survey (USGS) New Hampshire/VermontWater Science Center for scoping of flood-hazard mapping needs for Merrimack County, New Hampshire, under Federal Emergency Management Agency (FEMA...

  5. Flood hazard mapping of Palembang City by using 2D model

    Science.gov (United States)

    Farid, Mohammad; Marlina, Ayu; Kusuma, Muhammad Syahril Badri

    2017-11-01

    Palembang as the capital city of South Sumatera Province is one of the metropolitan cities in Indonesia that flooded almost every year. Flood in the city is highly related to Musi River Basin. Based on Indonesia National Agency of Disaster Management (BNPB), the level of flood hazard is high. Many natural factors caused flood in the city such as high intensity of rainfall, inadequate drainage capacity, and also backwater flow due to spring tide. Furthermore, anthropogenic factors such as population increase, land cover/use change, and garbage problem make flood problem become worse. The objective of this study is to develop flood hazard map of Palembang City by using two dimensional model. HEC-RAS 5.0 is used as modelling tool which is verified with field observation data. There are 21 sub catchments of Musi River Basin in the flood simulation. The level of flood hazard refers to Head Regulation of BNPB number 2 in 2012 regarding general guideline of disaster risk assessment. The result for 25 year return per iod of flood shows that with 112.47 km2 area of inundation, 14 sub catchments are categorized in high hazard level. It is expected that the hazard map can be used for risk assessment.

  6. A national scale flood hazard mapping methodology: The case of Greece - Protection and adaptation policy approaches.

    Science.gov (United States)

    Kourgialas, Nektarios N; Karatzas, George P

    2017-12-01

    The present work introduces a national scale flood hazard assessment methodology, using multi-criteria analysis and artificial neural networks (ANNs) techniques in a GIS environment. The proposed methodology was applied in Greece, where flash floods are a relatively frequent phenomenon and it has become more intense over the last decades, causing significant damages in rural and urban sectors. In order the most prone flooding areas to be identified, seven factor-maps (that are directly related to flood generation) were combined in a GIS environment. These factor-maps are: a) the Flow accumulation (F), b) the Land use (L), c) the Altitude (A), b) the Slope (S), e) the soil Erodibility (E), f) the Rainfall intensity (R), and g) the available water Capacity (C). The name to the proposed method is "FLASERC". The flood hazard for each one of these factors is classified into five categories: Very low, low, moderate, high, and very high. The above factors are combined and processed using the appropriate ANN algorithm tool. For the ANN training process spatial distribution of historical flooded points in Greece within the five different flood hazard categories of the aforementioned seven factor-maps were combined. In this way, the overall flood hazard map for Greece was determined. The final results are verified using additional historical flood events that have occurred in Greece over the last 100years. In addition, an overview of flood protection measures and adaptation policy approaches were proposed for agricultural and urban areas located at very high flood hazard areas. Copyright © 2017 Elsevier B.V. All rights reserved.

  7. Analysis and GIS Mapping of Flooding Hazards on 10 May 2016, Guangzhou, China

    Directory of Open Access Journals (Sweden)

    Hai-Min Lyu

    2016-10-01

    Full Text Available On 10 May 2016, Guangdong Province, China, suffered a heavy rainstorm. This rainstorm flooded the whole city of Guangzhou. More than 100,000 people were affected by the flooding, in which eight people lost their lives. Subway stations, cars, and buses were submerged. In order to analyse the influential factors of this flooding, topographical characteristics were mapped using Digital Elevation Model (DEM by the Geographical Information System (GIS and meteorological conditions were statistically summarised at both the whole city level and the district level. To analyse the relationship between flood risk and urbanization, GIS was also adopted to map the effect of the subway system using the Multiple Buffer operator over the flooding distribution area. Based on the analyses, one of the significant influential factors of flooding was identified as the urbanization degree, e.g., construction of a subway system, which forms along flood-prone areas. The total economic loss due to flooding in city centers with high urbanization has become very serious. Based on the analyses, the traditional standard of severity of flooding hazards (rainfall intensity grade was modified. Rainfall intensity for severity flooding was decreased from 50 mm to 30 mm in urbanized city centers. In order to protect cities from flooding, a “Sponge City” planning approach is recommended to increase the temporary water storage capacity during heavy rainstorms. In addition, for future city management, the combined use of GIS and Building Information Modelling (BIM is recommended to evaluate flooding hazards.

  8. Flood Hazard Mapping using Hydraulic Model and GIS: A Case Study in Mandalay City, Myanmar

    Directory of Open Access Journals (Sweden)

    Kyu Kyu Sein

    2016-01-01

    Full Text Available This paper presents the use of flood frequency analysis integrating with 1D Hydraulic model (HECRAS and Geographic Information System (GIS to prepare flood hazard maps of different return periods in Ayeyarwady River at Mandalay City in Myanmar. Gumbel’s distribution was used to calculate the flood peak of different return periods, namely, 10 years, 20 years, 50 years, and 100 years. The flood peak from frequency analysis were input into HEC-RAS model to find the corresponding flood level and extents in the study area. The model results were used in integrating with ArcGIS to generate flood plain maps. Flood depths and extents have been identified through flood plain maps. Analysis of 100 years return period flood plain map indicated that 157.88 km2 with the percentage of 17.54% is likely to be inundated. The predicted flood depth ranges varies from greater than 0 to 24 m in the flood plains and on the river. The range between 3 to 5 m were identified in the urban area of Chanayetharzan, Patheingyi, and Amarapua Townships. The highest inundated area was 85 km2 in the Amarapura Township.

  9. 2013 FEMA Flood Hazard Boundaries

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The National Flood Hazard Layer (NFHL) data incorporates all Digital Flood Insurance Rate Map(DFIRM) databases published by FEMA, and any Letters Of Map Revision...

  10. National Flood Hazard Layer (NFHL)

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The National Flood Hazard Layer (NFHL) is a compilation of GIS data that comprises a nationwide digital Flood Insurance Rate Map. The GIS data and services are...

  11. Global river flood hazard maps: hydraulic modelling methods and appropriate uses

    Science.gov (United States)

    Townend, Samuel; Smith, Helen; Molloy, James

    2014-05-01

    Flood hazard is not well understood or documented in many parts of the world. Consequently, the (re-)insurance sector now needs to better understand where the potential for considerable river flooding aligns with significant exposure. For example, international manufacturing companies are often attracted to countries with emerging economies, meaning that events such as the 2011 Thailand floods have resulted in many multinational businesses with assets in these regions incurring large, unexpected losses. This contribution addresses and critically evaluates the hydraulic methods employed to develop a consistent global scale set of river flood hazard maps, used to fill the knowledge gap outlined above. The basis of the modelling approach is an innovative, bespoke 1D/2D hydraulic model (RFlow) which has been used to model a global river network of over 5.3 million kilometres. Estimated flood peaks at each of these model nodes are determined using an empirically based rainfall-runoff approach linking design rainfall to design river flood magnitudes. The hydraulic model is used to determine extents and depths of floodplain inundation following river bank overflow. From this, deterministic flood hazard maps are calculated for several design return periods between 20-years and 1,500-years. Firstly, we will discuss the rationale behind the appropriate hydraulic modelling methods and inputs chosen to produce a consistent global scaled river flood hazard map. This will highlight how a model designed to work with global datasets can be more favourable for hydraulic modelling at the global scale and why using innovative techniques customised for broad scale use are preferable to modifying existing hydraulic models. Similarly, the advantages and disadvantages of both 1D and 2D modelling will be explored and balanced against the time, computer and human resources available, particularly when using a Digital Surface Model at 30m resolution. Finally, we will suggest some

  12. Flash Flood Hazard Susceptibility Mapping Using Frequency Ratio and Statistical Index Methods in Coalmine Subsidence Areas

    Directory of Open Access Journals (Sweden)

    Chen Cao

    2016-09-01

    Full Text Available This study focused on producing flash flood hazard susceptibility maps (FFHSM using frequency ratio (FR and statistical index (SI models in the Xiqu Gully (XQG of Beijing, China. First, a total of 85 flash flood hazard locations (n = 85 were surveyed in the field and plotted using geographic information system (GIS software. Based on the flash flood hazard locations, a flood hazard inventory map was built. Seventy percent (n = 60 of the flooding hazard locations were randomly selected for building the models. The remaining 30% (n = 25 of the flooded hazard locations were used for validation. Considering that the XQG used to be a coal mining area, coalmine caves and subsidence caused by coal mining exist in this catchment, as well as many ground fissures. Thus, this study took the subsidence risk level into consideration for FFHSM. The ten conditioning parameters were elevation, slope, curvature, land use, geology, soil texture, subsidence risk area, stream power index (SPI, topographic wetness index (TWI, and short-term heavy rain. This study also tested different classification schemes for the values for each conditional parameter and checked their impacts on the results. The accuracy of the FFHSM was validated using area under the curve (AUC analysis. Classification accuracies were 86.61%, 83.35%, and 78.52% using frequency ratio (FR-natural breaks, statistical index (SI-natural breaks and FR-manual classification schemes, respectively. Associated prediction accuracies were 83.69%, 81.22%, and 74.23%, respectively. It was found that FR modeling using a natural breaks classification method was more appropriate for generating FFHSM for the Xiqu Gully.

  13. Data assimilation of citizen collected information for real-time flood hazard mapping

    Science.gov (United States)

    Sayama, T.; Takara, K. T.

    2017-12-01

    Many studies in data assimilation in hydrology have focused on the integration of satellite remote sensing and in-situ monitoring data into hydrologic or land surface models. For flood predictions also, recent studies have demonstrated to assimilate remotely sensed inundation information with flood inundation models. In actual flood disaster situations, citizen collected information including local reports by residents and rescue teams and more recently tweets via social media also contain valuable information. The main interest of this study is how to effectively use such citizen collected information for real-time flood hazard mapping. Here we propose a new data assimilation technique based on pre-conducted ensemble inundation simulations and update inundation depth distributions sequentially when local data becomes available. The propose method is composed by the following two-steps. The first step is based on weighting average of preliminary ensemble simulations, whose weights are updated by Bayesian approach. The second step is based on an optimal interpolation, where the covariance matrix is calculated from the ensemble simulations. The proposed method was applied to case studies including an actual flood event occurred. It considers two situations with more idealized one by assuming continuous flood inundation depth information is available at multiple locations. The other one, which is more realistic case during such a severe flood disaster, assumes uncertain and non-continuous information is available to be assimilated. The results show that, in the first idealized situation, the large scale inundation during the flooding was estimated reasonably with RMSE effective. Nevertheless, the applications of the proposed data assimilation method demonstrated a high potential of this method for assimilating citizen collected information for real-time flood hazard mapping in the future.

  14. FLOOD HAZARD MAP IN THE CITY OF BATNA (ALGERIA BY HYDRAULIC MODELING APPROCH

    Directory of Open Access Journals (Sweden)

    Guellouh SAMI

    2016-06-01

    Full Text Available In the light of the global climatic changes that appear to influence the frequency and the intensity of floods, and whose damages are still growing; understanding the hydrological processes, their spatiotemporal setting and their extreme shape, became a paramount concern to local communities in forecasting terms. The aim of this study is to map the floods hazard using a hydraulic modeling method. In fact, using the operating Geographic Information System (GIS, would allow us to perform a more detailed spatial analysis about the extent of the flooding risk, through the approval of the hydraulic modeling programs in different frequencies. Based on the results of this analysis, decision makers can implement a strategy of risk management related to rivers overflowing through the city of Batna.

  15. Flood Hazard Mapping Assessment for El-Awali River Catchment-Lebanon

    Science.gov (United States)

    Hdeib, Rouya; Abdallah, Chadi; Moussa, Roger; Hijazi, Samar

    2016-04-01

    River flooding prediction and flood forecasting has become an essential stage in the major flood mitigation plans worldwide. Delineation of floodplains resulting from a river flooding event requires coupling between a Hydrological rainfall-runoff model to calculate the resulting outflows of the catchment and a hydraulic model to calculate the corresponding water surface profiles along the river main course. In this study several methods were applied to predict the flood discharge of El-Awali River using the available historical data and gauging records and by conducting several site visits. The HEC-HMS Rainfall-Runoff model was built and applied to calculate the flood hydrographs along several outlets on El-Awali River and calibrated using the storm that took place on January 2013 and caused flooding of the major Lebanese rivers and by conducting additional site visits to calculate proper river sections and record witnesses of the locals. The Hydraulic HEC-RAS model was then applied to calculate the corresponding water surface profiles along El-Awali River main reach. Floodplain delineation and Hazard mapping for 10,50 and 100 years return periods was performed using the Watershed Modeling System WMS. The results first show an underestimation of the flood discharge recorded by the operating gauge stations on El-Awali River, whereas, the discharge of the 100 years flood may reach up to 506 m3/s compared by lower values calculated using the traditional discharge estimation methods. Second any flooding of El-Awali River may be catastrophic especially to the coastal part of the catchment and can cause tragic losses in agricultural lands and properties. Last a major floodplain was noticed in Marj Bisri village this floodplain can reach more than 200 meters in width. Overall, performance was good and the Rainfall-Runoff model can provide valuable information about flows especially on ungauged points and can perform a great aid for the floodplain delineation and flood

  16. High resolution global flood hazard map from physically-based hydrologic and hydraulic models.

    Science.gov (United States)

    Begnudelli, L.; Kaheil, Y.; McCollum, J.

    2017-12-01

    The global flood map published online at http://www.fmglobal.com/research-and-resources/global-flood-map at 90m resolution is being used worldwide to understand flood risk exposure, exercise certain measures of mitigation, and/or transfer the residual risk financially through flood insurance programs. The modeling system is based on a physically-based hydrologic model to simulate river discharges, and 2D shallow-water hydrodynamic model to simulate inundation. The model can be applied to large-scale flood hazard mapping thanks to several solutions that maximize its efficiency and the use of parallel computing. The hydrologic component of the modeling system is the Hillslope River Routing (HRR) hydrologic model. HRR simulates hydrological processes using a Green-Ampt parameterization, and is calibrated against observed discharge data from several publicly-available datasets. For inundation mapping, we use a 2D Finite-Volume Shallow-Water model with wetting/drying. We introduce here a grid Up-Scaling Technique (UST) for hydraulic modeling to perform simulations at higher resolution at global scale with relatively short computational times. A 30m SRTM is now available worldwide along with higher accuracy and/or resolution local Digital Elevation Models (DEMs) in many countries and regions. UST consists of aggregating computational cells, thus forming a coarser grid, while retaining the topographic information from the original full-resolution mesh. The full-resolution topography is used for building relationships between volume and free surface elevation inside cells and computing inter-cell fluxes. This approach almost achieves computational speed typical of the coarse grids while preserving, to a significant extent, the accuracy offered by the much higher resolution available DEM. The simulations are carried out along each river of the network by forcing the hydraulic model with the streamflow hydrographs generated by HRR. Hydrographs are scaled so that the peak

  17. Exploring local risk managers' use of flood hazard maps for risk communication purposes in Baden-Württemberg

    Directory of Open Access Journals (Sweden)

    S. Kjellgren

    2013-07-01

    Full Text Available In response to the EU Floods Directive (2007/60/EC, flood hazard maps are currently produced all over Europe, reflecting a wider shift in focus from "flood protection" to "risk management", for which not only public authorities but also populations at risk are seen as responsible. By providing a visual image of the foreseen consequences of flooding, flood hazard maps can enhance people's knowledge about flood risk, making them more capable of an adequate response. Current literature, however, questions the maps' awareness raising capacity, arguing that their content and design are rarely adjusted to laypeople's needs. This paper wants to complement this perspective with a focus on risk communication by studying how these tools are disseminated and marketed to the public in the first place. Judging from communication theory, simply making hazard maps publicly available is unlikely to lead to attitudinal or behavioral effects, since this typically requires two-way communication and material or symbolic incentives. Consequently, it is relevant to investigate whether and how local risk managers, who are well positioned to interact with the local population, make use of flood hazard maps for risk communication purposes. A qualitative case study of this issue in the German state of Baden-Württemberg suggests that many municipalities lack a clear strategy for using this new information tool for hazard and risk communication. Four barriers in this regard are identified: perceived disinterest/sufficient awareness on behalf of the population at risk; unwillingness to cause worry or distress; lack of skills and resources; and insufficient support. These barriers are important to address – in research as well as in practice – since it is only if flood hazard maps are used to enhance local knowledge resources that they can be expected to contribute to social capacity building.

  18. Exploring local risk managers' use of flood hazard maps for risk communication purposes in Baden-Württemberg

    Science.gov (United States)

    Kjellgren, S.

    2013-07-01

    In response to the EU Floods Directive (2007/60/EC), flood hazard maps are currently produced all over Europe, reflecting a wider shift in focus from "flood protection" to "risk management", for which not only public authorities but also populations at risk are seen as responsible. By providing a visual image of the foreseen consequences of flooding, flood hazard maps can enhance people's knowledge about flood risk, making them more capable of an adequate response. Current literature, however, questions the maps' awareness raising capacity, arguing that their content and design are rarely adjusted to laypeople's needs. This paper wants to complement this perspective with a focus on risk communication by studying how these tools are disseminated and marketed to the public in the first place. Judging from communication theory, simply making hazard maps publicly available is unlikely to lead to attitudinal or behavioral effects, since this typically requires two-way communication and material or symbolic incentives. Consequently, it is relevant to investigate whether and how local risk managers, who are well positioned to interact with the local population, make use of flood hazard maps for risk communication purposes. A qualitative case study of this issue in the German state of Baden-Württemberg suggests that many municipalities lack a clear strategy for using this new information tool for hazard and risk communication. Four barriers in this regard are identified: perceived disinterest/sufficient awareness on behalf of the population at risk; unwillingness to cause worry or distress; lack of skills and resources; and insufficient support. These barriers are important to address - in research as well as in practice - since it is only if flood hazard maps are used to enhance local knowledge resources that they can be expected to contribute to social capacity building.

  19. Sept 2013 NFHL Flood Hazard Boundaries

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The National Flood Hazard Layer (NFHL) data incorporates all Digital Flood Insurance Rate Map(DFIRM) databases published by FEMA, and any Letters Of Map Revision...

  20. Flood inundation modeling and hazard mapping under uncertainty in the Sungai Johor basin, Malaysia

    NARCIS (Netherlands)

    Md. Ali, A.

    2018-01-01

    Flooding can have devastating impacts on people’s livelihood, economy and the environment. An important instrument in flood management is floodplain maps, which assist land planners and local authorities in identifying flood-prone areas, and provide useful information for rescue and relief agencies

  1. The use of remote sensing imagery for environmental land use and flood hazard mapping

    Science.gov (United States)

    Mouat, D. A.; Miller, D. A.; Foster, K. E.

    1976-01-01

    Flood hazard maps have been constructed for Graham, Yuma, and Yavapai Counties in Arizona using remote sensing techniques. Watershed maps of priority areas were selected on the basis of their interest to the county planning staff and represented areas of imminent or ongoing development and those known to be subject to inundation by storm runoff. Landsat color infrared imagery at scales of 1:1,000,000, 1:500,000, and 1:250,000 was used together with high-altitude aerial photography at scales of 1:120,000 and 1:60,000 to determine drainage patterns and erosional features, soil type, and the extent and type of ground cover. The satellite imagery was used in the form of 70 mm chips for enhancement in a color additive viewer and in all available enlargement modes. Field checking served as the main backup to the interpretations. Areas with high susceptibility to flooding were determined with a high level of confidence from the remotely sensed imagery.

  2. Automating Flood Hazard Mapping Methods for Near Real-time Storm Surge Inundation and Vulnerability Assessment

    Science.gov (United States)

    Weigel, A. M.; Griffin, R.; Gallagher, D.

    2015-12-01

    Storm surge has enough destructive power to damage buildings and infrastructure, erode beaches, and threaten human life across large geographic areas, hence posing the greatest threat of all the hurricane hazards. The United States Gulf of Mexico has proven vulnerable to hurricanes as it has been hit by some of the most destructive hurricanes on record. With projected rises in sea level and increases in hurricane activity, there is a need to better understand the associated risks for disaster mitigation, preparedness, and response. GIS has become a critical tool in enhancing disaster planning, risk assessment, and emergency response by communicating spatial information through a multi-layer approach. However, there is a need for a near real-time method of identifying areas with a high risk of being impacted by storm surge. Research was conducted alongside Baron, a private industry weather enterprise, to facilitate automated modeling and visualization of storm surge inundation and vulnerability on a near real-time basis. This research successfully automated current flood hazard mapping techniques using a GIS framework written in a Python programming environment, and displayed resulting data through an Application Program Interface (API). Data used for this methodology included high resolution topography, NOAA Probabilistic Surge model outputs parsed from Rich Site Summary (RSS) feeds, and the NOAA Census tract level Social Vulnerability Index (SoVI). The development process required extensive data processing and management to provide high resolution visualizations of potential flooding and population vulnerability in a timely manner. The accuracy of the developed methodology was assessed using Hurricane Isaac as a case study, which through a USGS and NOAA partnership, contained ample data for statistical analysis. This research successfully created a fully automated, near real-time method for mapping high resolution storm surge inundation and vulnerability for the

  3. Spatiotemporal hazard mapping of a flood event "migration" in a transboundary river basin as an operational tool in flood risk management

    Science.gov (United States)

    Perrou, Theodora; Papastergios, Asterios; Parcharidis, Issaak; Chini, Marco

    2017-10-01

    Flood disaster is one of the heaviest disasters in the world. It is necessary to monitor and evaluate the flood disaster in order to mitigate the consequences. As floods do not recognize borders, transboundary flood risk management is imperative in shared river basins. Disaster management is highly dependent on early information and requires data from the whole river basin. Based on the hypothesis that the flood events over the same area with same magnitude have almost identical evolution, it is crucial to develop a repository database of historical flood events. This tool, in the case of extended transboundary river basins, could constitute an operational warning system for the downstream area. The utility of SAR images for flood mapping, was demonstrated by previous studies but the SAR systems in orbit were not characterized by high operational capacity. Copernicus system will fill this gap in operational service for risk management, especially during emergency phase. The operational capabilities have been significantly improved by newly available satellite constellation, such as the Sentinel-1A AB mission, which is able to provide systematic acquisitions with a very high temporal resolution in a wide swath coverage. The present study deals with the monitoring of a transboundary flood event in Evros basin. The objective of the study is to create the "migration story" of the flooded areas on the basis of the evolution in time for the event occurred from October 2014 till May 2015. Flood hazard maps will be created, using SAR-based semi-automatic algorithms and then through the synthesis of the related maps in a GIS-system, a spatiotemporal thematic map of the event will be produced. The thematic map combined with TanDEM-X DEM, 12m/pixel spatial resolution, will define the non- affected areas which is a very useful information for the emergency planning and emergency response phases. The Sentinels meet the main requirements to be an effective and suitable

  4. Flood hazard assessment in areas prone to flash flooding

    Science.gov (United States)

    Kvočka, Davor; Falconer, Roger A.; Bray, Michaela

    2016-04-01

    Contemporary climate projections suggest that there will be an increase in the occurrence of high-intensity rainfall events in the future. These precipitation extremes are usually the main cause for the emergence of extreme flooding, such as flash flooding. Flash floods are among the most unpredictable, violent and fatal natural hazards in the world. Furthermore, it is expected that flash flooding will occur even more frequently in the future due to more frequent development of extreme weather events, which will greatly increase the danger to people caused by flash flooding. This being the case, there will be a need for high resolution flood hazard maps in areas susceptible to flash flooding. This study investigates what type of flood hazard assessment methods should be used for assessing the flood hazard to people caused by flash flooding. Two different types of flood hazard assessment methods were tested: (i) a widely used method based on an empirical analysis, and (ii) a new, physically based and experimentally calibrated method. Two flash flood events were considered herein, namely: the 2004 Boscastle flash flood and the 2007 Železniki flash flood. The results obtained in this study suggest that in the areas susceptible to extreme flooding, the flood hazard assessment should be conducted using methods based on a mechanics-based analysis. In comparison to standard flood hazard assessment methods, these physically based methods: (i) take into account all of the physical forces, which act on a human body in floodwater, (ii) successfully adapt to abrupt changes in the flow regime, which often occur for flash flood events, and (iii) rapidly assess a flood hazard index in a relatively short period of time.

  5. The development of flood map in Malaysia

    Science.gov (United States)

    Zakaria, Siti Fairus; Zin, Rosli Mohamad; Mohamad, Ismail; Balubaid, Saeed; Mydin, Shaik Hussein; MDR, E. M. Roodienyanto

    2017-11-01

    In Malaysia, flash floods are common occurrences throughout the year in flood prone areas. In terms of flood extent, flash floods affect smaller areas but because of its tendency to occur in densely urbanized areas, the value of damaged property is high and disruption to traffic flow and businesses are substantial. However, in river floods especially the river floods of Kelantan and Pahang, the flood extent is widespread and can extend over 1,000 square kilometers. Although the value of property and density of affected population is lower, the damage inflicted by these floods can also be high because the area affected is large. In order to combat these floods, various flood mitigation measures have been carried out. Structural flood mitigation alone can only provide protection levels from 10 to 100 years Average Recurrence Intervals (ARI). One of the economically effective non-structural approaches in flood mitigation and flood management is using a geospatial technology which involves flood forecasting and warning services to the flood prone areas. This approach which involves the use of Geographical Information Flood Forecasting system also includes the generation of a series of flood maps. There are three types of flood maps namely Flood Hazard Map, Flood Risk Map and Flood Evacuation Map. Flood Hazard Map is used to determine areas susceptible to flooding when discharge from a stream exceeds the bank-full stage. Early warnings of incoming flood events will enable the flood victims to prepare themselves before flooding occurs. Properties and life's can be saved by keeping their movable properties above the flood levels and if necessary, an early evacuation from the area. With respect to flood fighting, an early warning with reference through a series of flood maps including flood hazard map, flood risk map and flood evacuation map of the approaching flood should be able to alert the organization in charge of the flood fighting actions and the authority to

  6. FEMA DFIRM Flood Hazard Areas

    Data.gov (United States)

    Minnesota Department of Natural Resources — FEMA flood hazard delineations are used by the Federal Emergency Management Agency (FEMA) to designate the Special Flood Hazard Area (SFHA) and for insurance rating...

  7. Disseminating near-real-time hazards information and flood maps in the Philippines through Web-GIS.

    Science.gov (United States)

    A Lagmay, Alfredo Mahar Francisco; Racoma, Bernard Alan; Aracan, Ken Adrian; Alconis-Ayco, Jenalyn; Saddi, Ivan Lester

    2017-09-01

    The Philippines being a locus of tropical cyclones, tsunamis, earthquakes and volcanic eruptions, is a hotbed of disasters. These natural hazards inflict loss of lives and costly damage to property. Situated in a region where climate and geophysical tempest is common, the Philippines will inevitably suffer from calamities similar to those experienced recently. With continued development and population growth in hazard prone areas, it is expected that damage to infrastructure and human losses would persist and even rise unless appropriate measures are immediately implemented by government. In 2012, the Philippines launched a responsive program for disaster prevention and mitigation called the Nationwide Operational Assessment of Hazards (Project NOAH), specifically for government warning agencies to be able to provide a 6hr lead-time warning to vulnerable communities against impending floods and to use advanced technology to enhance current geo-hazard vulnerability maps. To disseminate such critical information to as wide an audience as possible, a Web-GIS using mashups of freely available source codes and application program interface (APIs) was developed and can be found in the URLs http://noah.dost.gov.ph and http://noah.up.edu.ph/. This Web-GIS tool is now heavily used by local government units in the Philippines in their disaster prevention and mitigation efforts and can be replicated in countries that have a proactive approach to address the impacts of natural hazards but lack sufficient funds. Copyright © 2017. Published by Elsevier B.V.

  8. A Decadal Historical Satellite Data and Rainfall Trend Analysis (2001–2016 for Flood Hazard Mapping in Sri Lanka

    Directory of Open Access Journals (Sweden)

    Niranga Alahacoon

    2018-03-01

    Full Text Available Critical information on a flood-affected area is needed in a short time frame to initiate rapid response operations and develop long-term flood management strategies. This study combined rainfall trend analysis using Asian Precipitation—Highly Resolved Observational Data Integration towards Evaluation of Water Resources (APHRODITE gridded rainfall data with flood maps derived from Synthetic Aperture Radar (SAR and multispectral satellite to arrive at holistic spatio-temporal patterns of floods in Sri Lanka. Advanced Land Observing Satellite Phased Array type L-band Synthetic Aperture Radar (ALOS PALSAR data were used to map flood extents for emergency relief operations while eight-day Moderate Resolution Imaging Spectroradiometer (MODIS surface reflectance data for the time period from 2001 to 2016 were used to map long term flood-affected areas. The inundation maps produced for rapid response were published within three hours upon the availability of satellite imagery in web platforms, with the aim of supporting a wide range of stakeholders in emergency response and flood relief operations. The aggregated time series of flood extents mapped using MODIS data were used to develop a flood occurrence map (2001–2016 for Sri Lanka. Flood hotpots identified using both optical and synthetic aperture average of 325 km2 for the years 2006–2015 and exceptional flooding in 2016 with inundation extent of approximately 1400 km2. The time series rainfall data explains increasing trend in the extreme rainfall indices with similar observation derived from satellite imagery. The results demonstrate the feasibility of using multi-sensor flood mapping approaches, which will aid Disaster Management Center (DMC and other multi-lateral agencies involved in managing rapid response operations and preparing mitigation measures.

  9. Flood Hazard Mapping : Uncertainty and its Value in the Decision-making Process

    NARCIS (Netherlands)

    Mukolwe, M.M.

    2016-01-01

    Computers are increasingly used in the simulation of natural phenomena such as floods. However, these simulations are based on numerical approximations of equations formalizing our conceptual understanding of flood flows. Thus, model results are intrinsically subject to uncertainty and the use of

  10. Flood Hazard Mapping: Uncertainty and its Value in the Decision-making Process

    NARCIS (Netherlands)

    Mukolwe, M.M.

    2016-01-01

    Computers are increasingly used in the simulation of natural phenomena such as floods. However, these simulations are based on numerical approximations of equations formalizing our conceptual understanding of flood flows. Thus, model results are intrinsically subject to uncertainty and the use of

  11. Flood Hazard Areas - High Risk

    Data.gov (United States)

    Department of Homeland Security — The S_Fld_Haz_Ar table contains information about the flood hazards within the study area. A spatial file with locational information also corresponds with this data...

  12. Geomorphological method in the elaboration of hazard maps for flash-floods in the municipality of Jucuarán (El Salvador)

    Science.gov (United States)

    Fernández-Lavado, C.; Furdada, G.; Marqués, M. A.

    2007-07-01

    This work deals with the elaboration of flood hazard maps. These maps reflect the areas prone to floods based on the effects of Hurricane Mitch in the Municipality of Jucuarán of El Salvador. Stream channels located in the coastal range in the SE of El Salvador flow into the Pacific Ocean and generate alluvial fans. Communities often inhabit these fans can be affected by floods. The geomorphology of these stream basins is associated with small areas, steep slopes, well developed regolite and extensive deforestation. These features play a key role in the generation of flash-floods. This zone lacks comprehensive rainfall data and gauging stations. The most detailed topographic maps are on a scale of 1:25 000. Given that the scale was not sufficiently detailed, we used aerial photographs enlarged to the scale of 1:8000. The effects of Hurricane Mitch mapped on these photographs were regarded as the reference event. Flood maps have a dual purpose (1) community emergency plans, (2) regional land use planning carried out by local authorities. The geomorphological method is based on mapping the geomorphological evidence (alluvial fans, preferential stream channels, erosion and sedimentation, man-made terraces). Following the interpretation of the photographs this information was validated on the field and complemented by eyewitness reports such as the height of water and flow typology. In addition, community workshops were organized to obtain information about the evolution and the impact of the phenomena. The superimposition of this information enables us to obtain a comprehensive geomorphological map. Another aim of the study was the calculation of the peak discharge using the Manning and the paleohydraulic methods and estimates based on geomorphologic criterion. The results were compared with those obtained using the rational method. Significant differences in the order of magnitude of the calculated discharges were noted. The rational method underestimated the

  13. Geomorphological method in the elaboration of hazard maps for flash-floods in the municipality of Jucuarán (El Salvador

    Directory of Open Access Journals (Sweden)

    C. Fernández-Lavado

    2007-07-01

    Full Text Available This work deals with the elaboration of flood hazard maps. These maps reflect the areas prone to floods based on the effects of Hurricane Mitch in the Municipality of Jucuarán of El Salvador. Stream channels located in the coastal range in the SE of El Salvador flow into the Pacific Ocean and generate alluvial fans. Communities often inhabit these fans can be affected by floods. The geomorphology of these stream basins is associated with small areas, steep slopes, well developed regolite and extensive deforestation. These features play a key role in the generation of flash-floods. This zone lacks comprehensive rainfall data and gauging stations. The most detailed topographic maps are on a scale of 1:25 000. Given that the scale was not sufficiently detailed, we used aerial photographs enlarged to the scale of 1:8000. The effects of Hurricane Mitch mapped on these photographs were regarded as the reference event. Flood maps have a dual purpose (1 community emergency plans, (2 regional land use planning carried out by local authorities. The geomorphological method is based on mapping the geomorphological evidence (alluvial fans, preferential stream channels, erosion and sedimentation, man-made terraces. Following the interpretation of the photographs this information was validated on the field and complemented by eyewitness reports such as the height of water and flow typology. In addition, community workshops were organized to obtain information about the evolution and the impact of the phenomena. The superimposition of this information enables us to obtain a comprehensive geomorphological map. Another aim of the study was the calculation of the peak discharge using the Manning and the paleohydraulic methods and estimates based on geomorphologic criterion. The results were compared with those obtained using the rational method. Significant differences in the order of magnitude of the calculated discharges were noted. The rational method

  14. Coastal Flood Hazard Composite Layer for the Coastal Flood Exposure Mapper

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This is a map service for the Coastal Flood Hazard Composite dataset. This dataset was created by combining hazard zones from the following datasets: FEMA V zones,...

  15. Flood frequency analysis and generation of flood hazard indicator maps in a semi-arid environment, case of Ourika watershed (western High Atlas, Morocco)

    Science.gov (United States)

    El Alaoui El Fels, Abdelhafid; Alaa, Noureddine; Bachnou, Ali; Rachidi, Said

    2018-05-01

    The development of the statistical models and flood risk modeling approaches have seen remarkable improvements in their productivities. Their application in arid and semi-arid regions, particularly in developing countries, can be extremely useful for better assessment and planning of flood risk in order to reduce the catastrophic impacts of this phenomenon. This study focuses on the Setti Fadma region (Ourika basin, Morocco) which is potentially threatened by floods and is subject to climatic and anthropogenic forcing. The study is based on two main axes: (i) the extreme flow frequency analysis, using 12 probability laws adjusted by Maximum Likelihood method and (ii) the generation of the flood risk indicator maps are based on the solution proposed by the Nays2DFlood solver of the Hydrodynamic model of two-dimensional Saint-Venant equations. The study is used as a spatial high-resolution digital model (Lidar) in order to get the nearest hydrological simulation of the reality. The results showed that the GEV is the most appropriate law of the extreme flows estimation for different return periods. Taking into consideration the mapping of 100-year flood area, the study revealed that the fluvial overflows extent towards the banks of Ourika and consequently, affects some living areas, cultivated fields and the roads that connects the valley to the city of Marrakech. The aim of this study is to propose new technics of the flood risk management allowing a better planning of the flooded areas.

  16. A framework of integrated hydrological and hydrodynamic models using synthetic rainfall for flash flood hazard mapping of ungauged catchments in tropical zones

    Directory of Open Access Journals (Sweden)

    W. Lohpaisankrit

    2016-05-01

    Full Text Available Flash flood hazard maps provide a scientific support to mitigate flash flood risk. The present study develops a practical framework with the help of integrated hydrological and hydrodynamic modelling in order to estimate the potential flash floods. We selected a small pilot catchment which has already suffered from flash floods in the past. This catchment is located in the Nan River basin, northern Thailand. Reliable meteorological and hydrometric data are missing in the catchment. Consequently, the entire upper basin of the main river was modelled with the help of the hydrological modelling system PANTA RHEI. In this basin, three monitoring stations are located along the main river. PANTA RHEI was calibrated and validated with the extreme flood events in June 2011 and July 2008, respectively. The results show a good agreement with the observed discharge data. In order to create potential flash flood scenarios, synthetic rainfall series were derived from temporal rainfall patterns based on the radar-rainfall observation and different rainfall depths from regional rainfall frequency analysis. The temporal rainfall patterns were characterized by catchment-averaged rainfall series selected from 13 rainstorms in 2008 and 2011 within the region. For regional rainfall frequency analysis, the well-known L-moments approach and related criteria were used to examine extremely climatic homogeneity of the region. According to the L-moments approach, Generalized Pareto distribution was recognized as the regional frequency distribution. The synthetic rainfall series were fed into the PANTA RHEI model. The simulated results from PANTA RHEI were provided to a 2-D hydrodynamic model (MEADFLOW, and various simulations were performed. Results from the integrated modelling framework are used in the ongoing study to regionalize and map the spatial distribution of flash flood hazards with four levels of flood severities. As an overall outcome, the presented framework

  17. Swiss Re Global Flood Hazard Zones: Know your flood risk

    Science.gov (United States)

    Vinukollu, R. K.; Castaldi, A.; Mehlhorn, J.

    2012-12-01

    Floods, among all natural disasters, have a great damage potential. On a global basis, there is strong evidence of increase in the number of people affected and economic losses due to floods. For example, global insured flood losses have increased by 12% every year since 1970 and this is expected to further increase with growing exposure in the high risk areas close to rivers and coastlines. Recently, the insurance industry has been surprised by the large extent of losses, because most countries lack reliable hazard information. One example has been the 2011 Thailand floods where millions of people were affected and the total economic losses were 30 billion USD. In order to assess the flood risk across different regions and countries, the flood team at Swiss Re based on a Geomorphologic Regression approach, developed in house and patented, produced global maps of flood zones. Input data for the study was obtained from NASA's Shuttle Radar Topographic Mission (SRTM) elevation data, Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global Digital Elevation Model (GDEM) and HydroSHEDS. The underlying assumptions of the approach are that naturally flowing rivers shape their channel and flood plain according to basin inherent forces and characteristics and that the flood water extent strongly depends on the shape of the flood plain. On the basis of the catchment characteristics, the model finally calculates the probability of a location to be flooded or not for a defined return period, which in the current study was set to 100 years. The data is produced at a 90-m resolution for latitudes 60S to 60N. This global product is now used in the insurance industry to inspect, inform and/or insure the flood risk across the world.

  18. Spatial variability and potential impacts of climate change on flood and debris flow hazard zone mapping and implications for risk management

    Directory of Open Access Journals (Sweden)

    H. Staffler

    2008-06-01

    Full Text Available The main goals of this study were to identify the alpine torrent catchments that are sensitive to climatic changes and to assess the robustness of the methods for the elaboration of flood and debris flow hazard zone maps to specific effects of climate changes. In this study, a procedure for the identification and localization of torrent catchments in which the climate scenarios will modify the hazard situation was developed. In two case studies, the impacts of a potential increase of precipitation intensities to the delimited hazard zones were studied.

    The identification and localization of the torrent and river catchments, where unfavourable changes in the hazard situation occur, could eliminate speculative and unnecessary measures against the impacts of climate changes like a general enlargement of hazard zones or a general over dimensioning of protection structures for the whole territory. The results showed a high spatial variability of the sensitivity of catchments to climate changes. In sensitive catchments, the sediment management in alpine torrents will meet future challenges due to a higher rate for sediment removal from retention basins. The case studies showed a remarkable increase of the areas affected by floods and debris flow when considering possible future precipitation intensities in hazard mapping. But, the calculated increase in extent of future hazard zones lay within the uncertainty of the methods used today for the delimitation of the hazard zones. Thus, the consideration of the uncertainties laying in the methods for the elaboration of hazard zone maps in the torrent and river catchments sensitive to climate changes would provide a useful instrument for the consideration of potential future climate conditions. The study demonstrated that weak points in protection structures in future will become more important in risk management activities.

  19. Reserve Special Flood Hazard Areas (SFHA)

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — This vector dataset depicts the 1% annual flood boundary (otherwise known as special flood hazard area or 100 year flood boundary) for its specified area. The data...

  20. Elephant Butte Special Flood Hazard Areas (SFHA)

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — This vector dataset depicts the 1% annual flood boundary (otherwise known as special flood hazard area or 100 year flood boundary) for its specified area. The data...

  1. Flood hazards for nuclear power plants

    International Nuclear Information System (INIS)

    Yen, B.C.

    1988-01-01

    Flooding hazards for nuclear power plants may be caused by various external geophysical events. In this paper the hydrologic hazards from flash floods, river floods and heavy rain at the plant site are considered. Depending on the mode of analysis, two types of hazard evaluation are identified: 1) design hazard which is the probability of flooding over an expected service period, and 2) operational hazard which deals with real-time forecasting of the probability of flooding of an incoming event. Hazard evaluation techniques using flood frequency analysis can only be used for type 1) design hazard. Evaluation techniques using rainfall-runoff simulation or multi-station correlation can be used for both types of hazard prediction. (orig.)

  2. Flood maps in Europe - methods, availability and use

    Science.gov (United States)

    de Moel, H.; van Alphen, J.; Aerts, J. C. J. H.

    2009-03-01

    To support the transition from traditional flood defence strategies to a flood risk management approach at the basin scale in Europe, the EU has adopted a new Directive (2007/60/EC) at the end of 2007. One of the major tasks which member states must carry out in order to comply with this Directive is to map flood hazards and risks in their territory, which will form the basis of future flood risk management plans. This paper gives an overview of existing flood mapping practices in 29 countries in Europe and shows what maps are already available and how such maps are used. Roughly half of the countries considered have maps covering as good as their entire territory, and another third have maps covering significant parts of their territory. Only five countries have very limited or no flood maps available yet. Of the different flood maps distinguished, it appears that flood extent maps are the most commonly produced floods maps (in 23 countries), but flood depth maps are also regularly created (in seven countries). Very few countries have developed flood risk maps that include information on the consequences of flooding. The available flood maps are mostly developed by governmental organizations and primarily used for emergency planning, spatial planning, and awareness raising. In spatial planning, flood zones delimited on flood maps mainly serve as guidelines and are not binding. Even in the few countries (e.g. France, Poland) where there is a legal basis to regulate floodplain developments using flood zones, practical problems are often faced which reduce the mitigating effect of such binding legislation. Flood maps, also mainly extent maps, are also created by the insurance industry in Europe and used to determine insurability, differentiate premiums, or to assess long-term financial solvency. Finally, flood maps are also produced by international river commissions. With respect to the EU Flood Directive, many countries already have a good starting point to map

  3. Flood maps in Europe – methods, availability and use

    Directory of Open Access Journals (Sweden)

    J. C. J. H. Aerts

    2009-03-01

    Full Text Available To support the transition from traditional flood defence strategies to a flood risk management approach at the basin scale in Europe, the EU has adopted a new Directive (2007/60/EC at the end of 2007. One of the major tasks which member states must carry out in order to comply with this Directive is to map flood hazards and risks in their territory, which will form the basis of future flood risk management plans. This paper gives an overview of existing flood mapping practices in 29 countries in Europe and shows what maps are already available and how such maps are used. Roughly half of the countries considered have maps covering as good as their entire territory, and another third have maps covering significant parts of their territory. Only five countries have very limited or no flood maps available yet. Of the different flood maps distinguished, it appears that flood extent maps are the most commonly produced floods maps (in 23 countries, but flood depth maps are also regularly created (in seven countries. Very few countries have developed flood risk maps that include information on the consequences of flooding. The available flood maps are mostly developed by governmental organizations and primarily used for emergency planning, spatial planning, and awareness raising. In spatial planning, flood zones delimited on flood maps mainly serve as guidelines and are not binding. Even in the few countries (e.g. France, Poland where there is a legal basis to regulate floodplain developments using flood zones, practical problems are often faced which reduce the mitigating effect of such binding legislation. Flood maps, also mainly extent maps, are also created by the insurance industry in Europe and used to determine insurability, differentiate premiums, or to assess long-term financial solvency. Finally, flood maps are also produced by international river commissions. With respect to the EU Flood Directive, many countries already have a good starting

  4. Interconnected ponds operation for flood hazard distribution

    Science.gov (United States)

    Putra, S. S.; Ridwan, B. W.

    2016-05-01

    The climatic anomaly, which comes with extreme rainfall, will increase the flood hazard in an area within a short period of time. The river capacity in discharging the flood is not continuous along the river stretch and sensitive to the flood peak. This paper contains the alternatives on how to locate the flood retention pond that are physically feasible to reduce the flood peak. The flood ponds were designed based on flood curve number criteria (TR-55, USDA) with the aim of rapid flood peak capturing and gradual flood retuning back to the river. As a case study, the hydrologic condition of upper Ciliwung river basin with several presumed flood pond locations was conceptually designed. A fundamental tank model that reproducing the operation of interconnected ponds was elaborated to achieve the designed flood discharge that will flows to the downstream area. The flood hazard distribution status, as the model performance criteria, will be computed within Ciliwung river reach in Manggarai Sluice Gate spot. The predicted hazard reduction with the operation of the interconnected retention area result had been bench marked with the normal flow condition.

  5. Development of Probabilistic Flood Inundation Mapping For Flooding Induced by Dam Failure

    Science.gov (United States)

    Tsai, C.; Yeh, J. J. J.

    2017-12-01

    A primary function of flood inundation mapping is to forecast flood hazards and assess potential losses. However, uncertainties limit the reliability of inundation hazard assessments. Major sources of uncertainty should be taken into consideration by an optimal flood management strategy. This study focuses on the 20km reach downstream of the Shihmen Reservoir in Taiwan. A dam failure induced flood herein provides the upstream boundary conditions of flood routing. The two major sources of uncertainty that are considered in the hydraulic model and the flood inundation mapping herein are uncertainties in the dam break model and uncertainty of the roughness coefficient. The perturbance moment method is applied to a dam break model and the hydro system model to develop probabilistic flood inundation mapping. Various numbers of uncertain variables can be considered in these models and the variability of outputs can be quantified. The probabilistic flood inundation mapping for dam break induced floods can be developed with consideration of the variability of output using a commonly used HEC-RAS model. Different probabilistic flood inundation mappings are discussed and compared. Probabilistic flood inundation mappings are hoped to provide new physical insights in support of the evaluation of concerning reservoir flooded areas.

  6. Introduction: Hazard mapping

    Science.gov (United States)

    Baum, Rex L.; Miyagi, Toyohiko; Lee, Saro; Trofymchuk, Oleksandr M

    2014-01-01

    Twenty papers were accepted into the session on landslide hazard mapping for oral presentation. The papers presented susceptibility and hazard analysis based on approaches ranging from field-based assessments to statistically based models to assessments that combined hydromechanical and probabilistic components. Many of the studies have taken advantage of increasing availability of remotely sensed data and nearly all relied on Geographic Information Systems to organize and analyze spatial data. The studies used a range of methods for assessing performance and validating hazard and susceptibility models. A few of the studies presented in this session also included some element of landslide risk assessment. This collection of papers clearly demonstrates that a wide range of approaches can lead to useful assessments of landslide susceptibility and hazard.

  7. Mapping flood and flooding potential indices: a methodological approach to identifying areas susceptible to flood and flooding risk. Case study: the Prahova catchment (Romania)

    Science.gov (United States)

    Zaharia, Liliana; Costache, Romulus; Prăvălie, Remus; Ioana-Toroimac, Gabriela

    2017-04-01

    Given that floods continue to cause yearly significant worldwide human and material damages, flood risk mitigation is a key issue and a permanent challenge in developing policies and strategies at various spatial scales. Therefore, a basic phase is elaborating hazard and flood risk maps, documents which are an essential support for flood risk management. The aim of this paper is to develop an approach that allows for the identification of flash-flood and flood-prone susceptible areas based on computing and mapping of two indices: FFPI (Flash-Flood Potential Index) and FPI (Flooding Potential Index). These indices are obtained by integrating in a GIS environment several geographical variables which control runoff (in the case of the FFPI) and favour flooding (in the case of the FPI). The methodology was applied in the upper (mountainous) and middle (hilly) catchment of the Prahova River, a densely populated and socioeconomically well-developed area which has been affected repeatedly by water-related hazards over the past decades. The resulting maps showing the spatialization of the FFPI and FPI allow for the identification of areas with high susceptibility to flashfloods and flooding. This approach can provide useful mapped information, especially for areas (generally large) where there are no flood/hazard risk maps. Moreover, the FFPI and FPI maps can constitute a preliminary step for flood risk and vulnerability assessment.

  8. Flood Hazard Management: British and International Perspectives

    Science.gov (United States)

    James, L. Douglas

    This proceedings of an international workshop at the Flood Hazard Research Centre (Queensway, Enfield, Middlesex, U.K.) begins by noting how past British research on flood problems concentrated on refining techniques to implement established policy. In contrast, research covered in North American and Australian publications involved normative issues on policy alternatives and administrative implementation. The workshop's participants included 16 widely recognized scientists, whose origins were about equally divided between Britain and overseas; from this group the workshop's organizers expertly drew ideas for refining British urban riverine flood hazard management and for cultivating links among researchers everywhere. Such intellectual exchange should be of keen interest to flood hazard program managers around the world, to students of comparative institutional performance, to those who make policy on protecting people from hazards, and to hydrologists and other geophysicists who must communicate descriptive information for bureaucratic, political, and public decision- making.

  9. Flood Hazards - A National Threat

    Science.gov (United States)

    ,

    2006-01-01

    In the late summer of 2005, the remarkable flooding brought by Hurricane Katrina, which caused more than $200 billion in losses, constituted the costliest natural disaster in U.S. history. However, even in typical years, flooding causes billions of dollars in damage and threatens lives and property in every State. Natural processes, such as hurricanes, weather systems, and snowmelt, can cause floods. Failure of levees and dams and inadequate drainage in urban areas can also result in flooding. On average, floods kill about 140 people each year and cause $6 billion in property damage. Although loss of life to floods during the past half-century has declined, mostly because of improved warning systems, economic losses have continued to rise due to increased urbanization and coastal development.

  10. 78 FR 52955 - Changes in Flood Hazard Determinations

    Science.gov (United States)

    2013-08-27

    ... community that the Deputy Associate Administrator for Mitigation reconsider the changes. The flood hazard...; Internal Agency Docket No. FEMA-B-1349] Changes in Flood Hazard Determinations AGENCY: Federal Emergency... modification of Base Flood Elevations (BFEs), base flood depths, Special Flood Hazard Area (SFHA) boundaries or...

  11. A high-resolution global flood hazard model

    Science.gov (United States)

    Sampson, Christopher C.; Smith, Andrew M.; Bates, Paul B.; Neal, Jeffrey C.; Alfieri, Lorenzo; Freer, Jim E.

    2015-09-01

    Floods are a natural hazard that affect communities worldwide, but to date the vast majority of flood hazard research and mapping has been undertaken by wealthy developed nations. As populations and economies have grown across the developing world, so too has demand from governments, businesses, and NGOs for modeled flood hazard data in these data-scarce regions. We identify six key challenges faced when developing a flood hazard model that can be applied globally and present a framework methodology that leverages recent cross-disciplinary advances to tackle each challenge. The model produces return period flood hazard maps at ˜90 m resolution for the whole terrestrial land surface between 56°S and 60°N, and results are validated against high-resolution government flood hazard data sets from the UK and Canada. The global model is shown to capture between two thirds and three quarters of the area determined to be at risk in the benchmark data without generating excessive false positive predictions. When aggregated to ˜1 km, mean absolute error in flooded fraction falls to ˜5%. The full complexity global model contains an automatically parameterized subgrid channel network, and comparison to both a simplified 2-D only variant and an independently developed pan-European model shows the explicit inclusion of channels to be a critical contributor to improved model performance. While careful processing of existing global terrain data sets enables reasonable model performance in urban areas, adoption of forthcoming next-generation global terrain data sets will offer the best prospect for a step-change improvement in model performance.

  12. Flood hazard zoning in Yasooj region, Iran, using GIS and multi-criteria decision analysis

    Directory of Open Access Journals (Sweden)

    Omid Rahmati

    2016-05-01

    Full Text Available Flood is considered to be the most common natural disaster worldwide during the last decades. Flood hazard potential mapping is required for management and mitigation of flood. The present research was aimed to assess the efficiency of analytical hierarchical process (AHP to identify potential flood hazard zones by comparing with the results of a hydraulic model. Initially, four parameters via distance to river, land use, elevation and land slope were used in some part of the Yasooj River, Iran. In order to determine the weight of each effective factor, questionnaires of comparison ratings on the Saaty's scale were prepared and distributed to eight experts. The normalized weights of criteria/parameters were determined based on Saaty's nine-point scale and its importance in specifying flood hazard potential zones using the AHP and eigenvector methods. The set of criteria were integrated by weighted linear combination method using ArcGIS 10.2 software to generate flood hazard prediction map. The inundation simulation (extent and depth of flood was conducted using hydrodynamic program HEC-RAS for 50- and 100-year interval floods. The validation of the flood hazard prediction map was conducted based on flood extent and depth maps. The results showed that the AHP technique is promising of making accurate and reliable prediction for flood extent. Therefore, the AHP and geographic information system (GIS techniques are suggested for assessment of the flood hazard potential, specifically in no-data regions.

  13. Coastal Flooding Hazards due to storm surges and subsidence

    DEFF Research Database (Denmark)

    Sørensen, Carlo; Knudsen, Per; Andersen, Ole B.

    Flooding hazard and risk mapping are major topics in low-lying coastal areas before even considering the adverse effects of sea level rise (SLR) due to climate change. While permanent inundation may be a prevalent issue, more often floods related to extreme events (storm surges) have the largest...... damage potential.Challenges are amplified in some areas due to subsidence from natural and/or anthropogenic causes. Subsidence of even a few mm/y may over time greatly impair the safety against flooding of coastal communities and must be accounted for in order to accomplish the economically most viable...

  14. Probabilistic Flood Maps to support decision-making: Mapping the Value of Information

    Science.gov (United States)

    Alfonso, L.; Mukolwe, M. M.; Di Baldassarre, G.

    2016-02-01

    Floods are one of the most frequent and disruptive natural hazards that affect man. Annually, significant flood damage is documented worldwide. Flood mapping is a common preimpact flood hazard mitigation measure, for which advanced methods and tools (such as flood inundation models) are used to estimate potential flood extent maps that are used in spatial planning. However, these tools are affected, largely to an unknown degree, by both epistemic and aleatory uncertainty. Over the past few years, advances in uncertainty analysis with respect to flood inundation modeling show that it is appropriate to adopt Probabilistic Flood Maps (PFM) to account for uncertainty. However, the following question arises; how can probabilistic flood hazard information be incorporated into spatial planning? Thus, a consistent framework to incorporate PFMs into the decision-making is required. In this paper, a novel methodology based on Decision-Making under Uncertainty theories, in particular Value of Information (VOI) is proposed. Specifically, the methodology entails the use of a PFM to generate a VOI map, which highlights floodplain locations where additional information is valuable with respect to available floodplain management actions and their potential consequences. The methodology is illustrated with a simplified example and also applied to a real case study in the South of France, where a VOI map is analyzed on the basis of historical land use change decisions over a period of 26 years. Results show that uncertain flood hazard information encapsulated in PFMs can aid decision-making in floodplain planning.

  15. Modeling Compound Flood Hazards in Coastal Embayments

    Science.gov (United States)

    Moftakhari, H.; Schubert, J. E.; AghaKouchak, A.; Luke, A.; Matthew, R.; Sanders, B. F.

    2017-12-01

    Coastal cities around the world are built on lowland topography adjacent to coastal embayments and river estuaries, where multiple factors threaten increasing flood hazards (e.g. sea level rise and river flooding). Quantitative risk assessment is required for administration of flood insurance programs and the design of cost-effective flood risk reduction measures. This demands a characterization of extreme water levels such as 100 and 500 year return period events. Furthermore, hydrodynamic flood models are routinely used to characterize localized flood level intensities (i.e., local depth and velocity) based on boundary forcing sampled from extreme value distributions. For example, extreme flood discharges in the U.S. are estimated from measured flood peaks using the Log-Pearson Type III distribution. However, configuring hydrodynamic models for coastal embayments is challenging because of compound extreme flood events: events caused by a combination of extreme sea levels, extreme river discharges, and possibly other factors such as extreme waves and precipitation causing pluvial flooding in urban developments. Here, we present an approach for flood risk assessment that coordinates multivariate extreme analysis with hydrodynamic modeling of coastal embayments. First, we evaluate the significance of correlation structure between terrestrial freshwater inflow and oceanic variables; second, this correlation structure is described using copula functions in unit joint probability domain; and third, we choose a series of compound design scenarios for hydrodynamic modeling based on their occurrence likelihood. The design scenarios include the most likely compound event (with the highest joint probability density), preferred marginal scenario and reproduced time series of ensembles based on Monte Carlo sampling of bivariate hazard domain. The comparison between resulting extreme water dynamics under the compound hazard scenarios explained above provides an insight to the

  16. 77 FR 59675 - Compliance With Information Request, Flooding Hazard Reevaluation

    Science.gov (United States)

    2012-09-28

    ... NUCLEAR REGULATORY COMMISSION [NRC-2012-0222] Compliance With Information Request, Flooding Hazard... was needed in the areas of seismic and flooding design, and emergency preparedness. In addition to... licensees reevaluate flooding hazards at nuclear power plant sites using updated flooding hazard information...

  17. Seismic hazard maps for Haiti

    Science.gov (United States)

    Frankel, Arthur; Harmsen, Stephen; Mueller, Charles; Calais, Eric; Haase, Jennifer

    2011-01-01

    We have produced probabilistic seismic hazard maps of Haiti for peak ground acceleration and response spectral accelerations that include the hazard from the major crustal faults, subduction zones, and background earthquakes. The hazard from the Enriquillo-Plantain Garden, Septentrional, and Matheux-Neiba fault zones was estimated using fault slip rates determined from GPS measurements. The hazard from the subduction zones along the northern and southeastern coasts of Hispaniola was calculated from slip rates derived from GPS data and the overall plate motion. Hazard maps were made for a firm-rock site condition and for a grid of shallow shear-wave velocities estimated from topographic slope. The maps show substantial hazard throughout Haiti, with the highest hazard in Haiti along the Enriquillo-Plantain Garden and Septentrional fault zones. The Matheux-Neiba Fault exhibits high hazard in the maps for 2% probability of exceedance in 50 years, although its slip rate is poorly constrained.

  18. Technical note Flood map development by coupling satellite maps ...

    African Journals Online (AJOL)

    Flood maps are important for local authorities in designing mitigation plans to minimise damage and loss due to flooding. In recent years, flood events in the Sarawak River Basin, Malaysia have caused damage to property, loss of life and disruption of productive activities. Currently, the available flood map for Sarawak River ...

  19. Truth or Consequences Special Flood Hazard Areas (SFHA)

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — This vector dataset depicts the 1% annual flood boundary (otherwise known as special flood hazard area or 100 year flood boundary) for its specified area. The data...

  20. Hazard Map for Autonomous Navigation

    DEFF Research Database (Denmark)

    Riis, Troels

    This dissertation describes the work performed in the area of using image analysis in the process of landing a spacecraft autonomously and safely on the surface of the Moon. This is suggested to be done using a Hazard Map. The correspondence problem between several Hazard Maps are investigated...

  1. Differences in flood hazard projections in Europe – their causes and consequences for decision making

    Science.gov (United States)

    Kundzewicz, Z. W.; Krysanova, V.; Dankers, R.; Hirabayashi, Y.; Kanae, S.; Hattermann, F. F.; Huang, S.; Milly, Paul C.D.; Stoffel, M.; Driessen, P.P.J.; Matczak, P.; Quevauviller, P.; Schellnhuber, H.-J.

    2017-01-01

    This paper interprets differences in flood hazard projections over Europe and identifies likely sources of discrepancy. Further, it discusses potential implications of these differences for flood risk reduction and adaptation to climate change. The discrepancy in flood hazard projections raises caution, especially among decision makers in charge of water resources management, flood risk reduction, and climate change adaptation at regional to local scales. Because it is naïve to expect availability of trustworthy quantitative projections of future flood hazard, in order to reduce flood risk one should focus attention on mapping of current and future risks and vulnerability hotspots and improve the situation there. Although an intercomparison of flood hazard projections is done in this paper and differences are identified and interpreted, it does not seems possible to recommend which large-scale studies may be considered most credible in particular areas of Europe.

  2. Hazards related to external flooding

    International Nuclear Information System (INIS)

    1984-04-01

    RFS or Regles Fondamentales de Surete (Basic Safety Rules) applicable to certain types of nuclear facilities lay down requirements with which compliance, for the type of facilities and within the scope of application covered by the RFS, is considered to be equivalent to compliance with technical French regulatory practice. The object of the RFS is to take advantage of standardization in the field of safety, while allowing for technical progress in that field. They are designed to enable the operating utility and contractors to know the rules pertaining to various subjects which are considered to be acceptable by the Service Central de Surete des Installations Nucleaires, or the SCSIN (Central Department for the Safety of Nuclear Facilities). These RFS should make safety analysis easier and lead to better understanding between experts and individuals concerned with the problems of nuclear safety. The SCSIN reserves the right to modify, when considered necessary, any RFS and specify, if need be, the terms under which a modification is deemed retroactive. This RFS is intended to give state-of-the-art definitions of: - an acceptable method to determine water levels to be used in flood design of a facility - facility design principles required to meet the principles above

  3. 78 FR 24439 - Compliance With Information Request, Flooding Hazard Reevaluation

    Science.gov (United States)

    2013-04-25

    ... NUCLEAR REGULATORY COMMISSION [NRC-2013-0073] Compliance With Information Request, Flooding Hazard... Estimating Flooding Hazards due to Dam Failure.'' This draft JLD-ISG provides guidance acceptable to the NRC staff for reevaluating flooding hazards due to dam failure for the purpose of responding to enclosure 2...

  4. Flood Insurance Rate Map, Scott County, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  5. DIGITAL FLOOD INSURANCE RATE MAP DATABASE,

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk Information And supporting data used to develop the risk data. The primary risk;...

  6. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, , USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk Information And supporting data used to develop the risk data. The primary risk;...

  7. Flood susceptibility mapping using novel ensembles of adaptive neuro fuzzy inference system and metaheuristic algorithms

    NARCIS (Netherlands)

    Razavi Termeh, Seyed Vahid; Kornejady, Aiding; Pourghasemi, Hamid Reza; Keesstra, Saskia

    2018-01-01

    Flood is one of the most destructive natural disasters which cause great financial and life losses per year. Therefore, producing susceptibility maps for flood management are necessary in order to reduce its harmful effects. The aim of the present study is to map flood hazard over the Jahrom

  8. Smoky River coal flood risk mapping study

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2004-06-01

    The Canada-Alberta Flood Damage Reduction Program (FDRP) is designed to reduce flood damage by identifying areas susceptible to flooding and by encouraging application of suitable land use planning, zoning, and flood preparedness and proofing. The purpose of this study is to define flood risk and floodway limits along the Smoky River near the former Smoky River Coal (SRC) plant. Alberta Energy has been responsible for the site since the mine and plant closed in 2000. The study describes flooding history, available data, features of the river and valley, calculation of flood levels, and floodway determination, and includes flood risk maps. The HEC-RAS program is used for the calculations. The flood risk area was calculated using the 1:100 year return period flood as the hydrological event. 7 refs., 11 figs., 7 tabs., 3 apps.

  9. Statistical analysis of the uncertainty related to flood hazard appraisal

    Science.gov (United States)

    Notaro, Vincenza; Freni, Gabriele

    2015-12-01

    The estimation of flood hazard frequency statistics for an urban catchment is of great interest in practice. It provides the evaluation of potential flood risk and related damage and supports decision making for flood risk management. Flood risk is usually defined as function of the probability, that a system deficiency can cause flooding (hazard), and the expected damage, due to the flooding magnitude (damage), taking into account both the exposure and the vulnerability of the goods at risk. The expected flood damage can be evaluated by an a priori estimation of potential damage caused by flooding or by interpolating real damage data. With regard to flood hazard appraisal several procedures propose to identify some hazard indicator (HI) such as flood depth or the combination of flood depth and velocity and to assess the flood hazard corresponding to the analyzed area comparing the HI variables with user-defined threshold values or curves (penalty curves or matrixes). However, flooding data are usually unavailable or piecemeal allowing for carrying out a reliable flood hazard analysis, therefore hazard analysis is often performed by means of mathematical simulations aimed at evaluating water levels and flow velocities over catchment surface. As results a great part of the uncertainties intrinsic to flood risk appraisal can be related to the hazard evaluation due to the uncertainty inherent to modeling results and to the subjectivity of the user defined hazard thresholds applied to link flood depth to a hazard level. In the present work, a statistical methodology was proposed for evaluating and reducing the uncertainties connected with hazard level estimation. The methodology has been applied to a real urban watershed as case study.

  10. 77 FR 65417 - Compliance With Information Request, Flooding Hazard Reevaluation

    Science.gov (United States)

    2012-10-26

    ... NUCLEAR REGULATORY COMMISSION [NRC-2012-0261] Compliance With Information Request, Flooding Hazard... flooding hazard reanalysis in response to enclosure 2 of a March 12, 2012, information request. DATES... evaluation of whether further regulatory action was needed in the areas of seismic and flooding design, and...

  11. The influence of the net rainfall mixed Curve Number – Green Ampt procedure in flood hazard mapping: a case study in Central Italy

    Directory of Open Access Journals (Sweden)

    Andrea Petroselli

    2013-09-01

    Full Text Available A net rainfall estimation procedure, referred to as Curve-Number For Green-Ampt (CN4GA, combining the Soil Conservation Service - Curve Number (SCS-CN method and the Green and Ampt (GA infiltration equation was recently developed, aiming to distribute at subdaily time resolution the information provided by the SCS-CN method. The initial abstraction and the total volume of rainfall provided by the SCS-CN method are used to identify the ponding time and to quantify the hydraulic conductivity parameter of the GA equation, whereas the GA infiltration model distributes the total volume of the rainfall excess provided by the SCS-CN method. In this study we evaluate the proposed procedure with reference to a real case comparing the flood mapping obtained applying the event-based approach for two different net rainfall scenarios: the proposed CN4GA and the common SCS-CN. Results underline that the net rainfall estimation step can affect the final flood mapping result.

  12. Flood Hazard Recurrence Frequencies for the Savannah River Site

    International Nuclear Information System (INIS)

    Chen, K.F.

    2001-01-01

    Department of Energy (DOE) regulations outline the requirements for Natural Phenomena Hazard (NPH) mitigation for new and existing DOE facilities. The NPH considered in this report is flooding. The facility-specific probabilistic flood hazard curve defines, as a function of water elevation, the annual probability of occurrence or the return period in years. The facility-specific probabilistic flood hazard curves provide basis to avoid unnecessary facility upgrades, to establish appropriate design criteria for new facilities, and to develop emergency preparedness plans to mitigate the consequences of floods. A method based on precipitation, basin runoff and open channel hydraulics was developed to determine probabilistic flood hazard curves for the Savannah River Site. The calculated flood hazard curves show that the probabilities of flooding existing SRS major facilities are significantly less than 1.E-05 per year

  13. Estimating floodwater depths from flood inundation maps and topography

    Science.gov (United States)

    Cohen, Sagy; Brakenridge, G. Robert; Kettner, Albert; Bates, Bradford; Nelson, Jonathan M.; McDonald, Richard R.; Huang, Yu-Fen; Munasinghe, Dinuke; Zhang, Jiaqi

    2018-01-01

    Information on flood inundation extent is important for understanding societal exposure, water storage volumes, flood wave attenuation, future flood hazard, and other variables. A number of organizations now provide flood inundation maps based on satellite remote sensing. These data products can efficiently and accurately provide the areal extent of a flood event, but do not provide floodwater depth, an important attribute for first responders and damage assessment. Here we present a new methodology and a GIS-based tool, the Floodwater Depth Estimation Tool (FwDET), for estimating floodwater depth based solely on an inundation map and a digital elevation model (DEM). We compare the FwDET results against water depth maps derived from hydraulic simulation of two flood events, a large-scale event for which we use medium resolution input layer (10 m) and a small-scale event for which we use a high-resolution (LiDAR; 1 m) input. Further testing is performed for two inundation maps with a number of challenging features that include a narrow valley, a large reservoir, and an urban setting. The results show FwDET can accurately calculate floodwater depth for diverse flooding scenarios but also leads to considerable bias in locations where the inundation extent does not align well with the DEM. In these locations, manual adjustment or higher spatial resolution input is required.

  14. FEMA Hazard Mitigation Assistance Flood Mitigation Assistance (FMA) Data

    Data.gov (United States)

    Department of Homeland Security — This dataset contains closed and obligated projects funded under the following Hazard Mitigation Assistance (HMA) grant programs: Flood Mitigation Assistance (FMA)....

  15. FEMA Hazard Mitigation Assistance Repetitive Flood Claims (RFC) Data

    Data.gov (United States)

    Department of Homeland Security — This dataset contains closed and obligated projects funded under the following Hazard Mitigation Assistance (HMA) grant programs: Repetitive Flood Claims (RFC). The...

  16. Flood Hazard Assessment for the Savannah River Site

    International Nuclear Information System (INIS)

    Chen, K.F.

    1999-01-01

    'A method was developed to determine the probabilistic flood elevation curves for certain Savannah River Site (SRS) facilities. This paper presents the method used to determine the probabilistic flood elevation curve for F-Area due to runoff from the Upper Three Runs basin. Department of Energy (DOE) Order 420.1, Facility Safety, outlines the requirements for Natural Phenomena Hazard (NPH) mitigation for new and existing DOE facilities. The NPH considered in this paper is flooding. The facility-specific probabilistic flood hazard curve defines as a function of water elevation the annual probability of occurrence or the return period in years. Based on facility-specific probabilistic flood hazard curves and the nature of facility operations (e.g., involving hazardous or radioactive materials), facility managers can design permanent or temporary devices to prevent the propagation of flood on site, and develop emergency preparedness plans to mitigate the consequences of floods.'

  17. Global Rapid Flood Mapping System with Spaceborne SAR Data

    Science.gov (United States)

    Yun, S. H.; Owen, S. E.; Hua, H.; Agram, P. S.; Fattahi, H.; Liang, C.; Manipon, G.; Fielding, E. J.; Rosen, P. A.; Webb, F.; Simons, M.

    2017-12-01

    As part of the Advanced Rapid Imaging and Analysis (ARIA) project for Natural Hazards, at NASA's Jet Propulsion Laboratory and California Institute of Technology, we have developed an automated system that produces derived products for flood extent map generation using spaceborne SAR data. The system takes user's input of area of interest polygons and time window for SAR data search (pre- and post-event). Then the system automatically searches and downloads SAR data, processes them to produce coregistered SAR image pairs, and generates log amplitude ratio images from each pair. Currently the system is automated to support SAR data from the European Space Agency's Sentinel-1A/B satellites. We have used the system to produce flood extent maps from Sentinel-1 SAR data for the May 2017 Sri Lanka floods, which killed more than 200 people and displaced about 600,000 people. Our flood extent maps were delivered to the Red Cross to support response efforts. Earlier we also responded to the historic August 2016 Louisiana floods in the United States, which claimed 13 people's lives and caused over $10 billion property damage. For this event, we made synchronized observations from space, air, and ground in close collaboration with USGS and NOAA. The USGS field crews acquired ground observation data, and NOAA acquired high-resolution airborne optical imagery within the time window of +/-2 hours of the SAR data acquisition by JAXA's ALOS-2 satellite. The USGS coordinates of flood water boundaries were used to calibrate our flood extent map derived from the ALOS-2 SAR data, and the map was delivered to FEMA for estimating the number of households affected. Based on the lessons learned from this response effort, we customized the ARIA system automation for rapid flood mapping and developed a mobile friendly web app that can easily be used in the field for data collection. Rapid automatic generation of SAR-based global flood maps calibrated with independent observations from

  18. Increasing resilience through participative flood risk map design

    Science.gov (United States)

    Fuchs, Sven; Spira, Yvonne; Stickler, Therese

    2013-04-01

    In recent years, an increasing number of flood hazards has shown to the European Commission and the Member States of the European Union the importance of flood risk management strategies in order to reduce losses and to protect the environment and the citizens. Exposure to floods as well as flood vulnerability might increase across Europe due to the ongoing economic development in many EU countries. Thus even without taking climate change into account an increase of flood disasters in Europe might be foreseeable. These circumstances have produced a reaction in the European Commission, and a Directive on the Assessment and Management of Flood Risks was issued as one of the three components of the European Action Programme on Flood Risk Management. Floods have the potential to jeopardise economic development, above all due to an increase of human activities in floodplains and the reduction of natural water retention by land use activities. As a result, an increase in the likelihood and adverse impacts of flood events is expected. Therefore, concentrated action is needed at the European level to avoid severe impacts on human life and property. In order to have an effective tool available for gathering information, as well as a valuable basis for priority setting and further technical, financial and political decisions regarding flood risk mitigation and management, it is necessary to provide for the establishment of flood risk maps which show the potential adverse consequences associated with different flood scenarios. So far, hazard and risk maps are compiled in terms of a top-down linear approach: planning authorities take the responsibility to create and implement these maps on different national and local scales, and the general public will only be informed about the outcomes (EU Floods Directive, Article 10). For the flood risk management plans, however, an "active involvement of interested parties" is required, which means at least some kind of multilateral

  19. Rapid Flood Map Generation from Spaceborne SAR Observations

    Science.gov (United States)

    Yun, S. H.; Liang, C.; Manipon, G.; Jung, J.; Gurrola, E. M.; Owen, S. E.; Hua, H.; Agram, P. S.; Webb, F.; Sacco, G. F.; Rosen, P. A.; Simons, M.

    2016-12-01

    The Advanced Rapid Imaging and Analysis (ARIA) team has responded to the January 2016 US Midwest Floods along the Mississippi River. Daily teleconferences with FEMA, NOAA, NGA, and USGS, provided information on precipitation and flood crest migration, based on which we coordinated with the Japanese Aerospace Exploration Agency (JAXA) through NASA headquarters for JAXA's ALOS-2 timely tasking over two paths. We produced flood extent maps using ALOS-2 SM3 mode Level 1.5 data that were provided through the International Charter and stored at the US Geological Survey's Hazards Data Distribution System (HDDS) archive. On January 6, the first four frames (70 km x 240 km) were acquired, which included the City of Memphis. We registered post-event SAR images to pre-event images, applied radiometric calibration, took a logarithm of the ratio of the two images. Two thresholds were applied to represent flooded areas that became open water (colored in blue) and flooded areas with tall vegetation (colored in red). The second path was acquired on January 11 further down along the Mississippi River. Seven frames (70 km x 420 km) were acquired and flood maps were created in the similar fashion. The maps were delivered to the FEMA as well as posted on ARIA's public website. The FEMA stated that SAR provides inspection priority for optical imagery and ground response. The ALOS-2 data and the products have been a very important source of information during this response as the flood crest has moved down stream. The SAR data continue to be an important resource during times when optical observations are often not useful. In close collaboration with FEMA and USGS, we also work on other flood events including June 2016 China Floods using European Space Agency's (ESA's) Sentienl-1 data, to produce flood extent maps and identify algorithmic needs and ARIA system's requirements to automate and rapidly produce and deliver flood maps for future events. With the addition of Sentinel-1B

  20. INFLUENCE OF DEM IN WATERSHED MANAGEMENT AS FLOOD ZONATION MAPPING

    Directory of Open Access Journals (Sweden)

    M. Alrajhi

    2016-06-01

    Full Text Available Despite of valuable efforts from working groups and research organizations towards flood hazard reduction through its program, still minimal diminution from these hazards has been realized. This is mainly due to the fact that with rapid increase in population and urbanization coupled with climate change, flood hazards are becoming increasingly catastrophic. Therefore there is a need to understand and access flood hazards and develop means to deal with it through proper preparations, and preventive measures. To achieve this aim, Geographical Information System (GIS, geospatial and hydrological models were used as tools to tackle with influence of flash floods in the Kingdom of Saudi Arabia due to existence of large valleys (Wadis which is a matter of great concern. In this research paper, Digital Elevation Models (DEMs of different resolution (30m, 20m,10m and 5m have been used, which have proven to be valuable tool for the topographic parameterization of hydrological models which are the basis for any flood modelling process. The DEM was used as input for performing spatial analysis and obtaining derivative products and delineate watershed characteristics of the study area using ArcGIS desktop and its Arc Hydro extension tools to check comparability of different elevation models for flood Zonation mapping. The derived drainage patterns have been overlaid over aerial imagery of study area, to check influence of greater amount of precipitation which can turn into massive destructions. The flow accumulation maps derived provide zones of highest accumulation and possible flow directions. This approach provide simplified means of predicting extent of inundation during flood events for emergency action especially for large areas because of large coverage area of the remotely sensed data.

  1. Flood Hazard Assessment for the Savannah River Site

    International Nuclear Information System (INIS)

    Chen, K.F.

    2000-01-01

    A method was developed to determine the probabilistic flood elevation curves for certain Savannah River Site (SRS) facilities. This paper presents the method used to determine the probabilistic flood elevation curve for F-Area due to runoff from the Upper Three Runs basin. Department of Energy (DOE) Order 420.1, Facility Safety, outlines the requirements for Natural Phenomena Hazard (NPH) mitigation for new and existing DOE facilities. The NPH considered in this paper is flooding. The facility-specific probabilistic flood hazard curve defines as a function of water elevation the annual probability of occurrence or the return period in years. Based on facility-specific probabilistic flood hazard curves and the nature of facility operations (e.g., involving hazardous or radioactive materials), facility managers can design permanent or temporary devices to prevent the propagation of flood on site, and develop emergency preparedness plans to mitigate the consequences of floods. A method was developed to determine the probabilistic flood hazard curves for SRS facilities. The flood hazard curves for the SRS F-Area due to flooding in the Upper Three Runs basin are presented in this paper

  2. Flood mapping with multitemporal MODIS data

    Science.gov (United States)

    Son, Nguyen-Thanh; Chen, Chi-Farn; Chen, Cheng-Ru

    2014-05-01

    Flood is one of the most devastating and frequent disasters resulting in loss of human life and serve damage to infrastructure and agricultural production. Flood is phenomenal in the Mekong River Delta (MRD), Vietnam. It annually lasts from July to November. Information on spatiotemporal flood dynamics is thus important for planners to devise successful strategies for flood monitoring and mitigation of its negative effects. The main objective of this study is to develop an approach for weekly mapping flood dynamics with the Moderate Resolution Imaging Spectroradiometer data in MRD using the water fraction model (WFM). The data processed for 2009 comprises three main steps: (1) data pre-processing to construct smooth time series of the difference in the values (DVLE) between land surface water index (LSWI) and enhanced vegetation index (EVI) using the empirical mode decomposition (EMD), (2) flood derivation using WFM, and (3) accuracy assessment. The mapping results were compared with the ground reference data, which were constructed from Envisat Advanced Synthetic Aperture Radar (ASAR) data. As several error sources, including mixed-pixel problems and low-resolution bias between the mapping results and ground reference data, could lower the level of classification accuracy, the comparisons indicated satisfactory results with the overall accuracy of 80.5% and Kappa coefficient of 0.61, respectively. These results were reaffirmed by a close correlation between the MODIS-derived flood area and that of the ground reference map at the provincial level, with the correlation coefficients (R2) of 0.93. Considering the importance of remote sensing for monitoring floods and mitigating the damage caused by floods to crops and infrastructure, this study eventually leads to the realization of the value of using time-series MODIS DVLE data for weekly flood monitoring in MRD with the aid of EMD and WFM. Such an approach that could provide quantitative information on

  3. Identification and delineation of areas flood hazard using high accuracy of DEM data

    Science.gov (United States)

    Riadi, B.; Barus, B.; Widiatmaka; Yanuar, M. J. P.; Pramudya, B.

    2018-05-01

    Flood incidents that often occur in Karawang regency need to be mitigated. These expectations exist on technologies that can predict, anticipate and reduce disaster risks. Flood modeling techniques using Digital Elevation Model (DEM) data can be applied in mitigation activities. High accuracy DEM data used in modeling, will result in better flooding flood models. The result of high accuracy DEM data processing will yield information about surface morphology which can be used to identify indication of flood hazard area. The purpose of this study was to identify and describe flood hazard areas by identifying wetland areas using DEM data and Landsat-8 images. TerraSAR-X high-resolution data is used to detect wetlands from landscapes, while land cover is identified by Landsat image data. The Topography Wetness Index (TWI) method is used to detect and identify wetland areas with basic DEM data, while for land cover analysis using Tasseled Cap Transformation (TCT) method. The result of TWI modeling yields information about potential land of flood. Overlay TWI map with land cover map that produces information that in Karawang regency the most vulnerable areas occur flooding in rice fields. The spatial accuracy of the flood hazard area in this study was 87%.

  4. Combined fluvial and pluvial urban flood hazard analysis: method development and application to Can Tho City, Mekong Delta, Vietnam

    Science.gov (United States)

    Apel, H.; Trepat, O. M.; Hung, N. N.; Chinh, D. T.; Merz, B.; Dung, N. V.

    2015-08-01

    Many urban areas experience both fluvial and pluvial floods, because locations next to rivers are preferred settlement areas, and the predominantly sealed urban surface prevents infiltration and facilitates surface inundation. The latter problem is enhanced in cities with insufficient or non-existent sewer systems. While there are a number of approaches to analyse either fluvial or pluvial flood hazard, studies of combined fluvial and pluvial flood hazard are hardly available. Thus this study aims at the analysis of fluvial and pluvial flood hazard individually, but also at developing a method for the analysis of combined pluvial and fluvial flood hazard. This combined fluvial-pluvial flood hazard analysis is performed taking Can Tho city, the largest city in the Vietnamese part of the Mekong Delta, as example. In this tropical environment the annual monsoon triggered floods of the Mekong River can coincide with heavy local convective precipitation events causing both fluvial and pluvial flooding at the same time. Fluvial flood hazard was estimated with a copula based bivariate extreme value statistic for the gauge Kratie at the upper boundary of the Mekong Delta and a large-scale hydrodynamic model of the Mekong Delta. This provided the boundaries for 2-dimensional hydrodynamic inundation simulation for Can Tho city. Pluvial hazard was estimated by a peak-over-threshold frequency estimation based on local rain gauge data, and a stochastic rain storm generator. Inundation was simulated by a 2-dimensional hydrodynamic model implemented on a Graphical Processor Unit (GPU) for time-efficient flood propagation modelling. All hazards - fluvial, pluvial and combined - were accompanied by an uncertainty estimation considering the natural variability of the flood events. This resulted in probabilistic flood hazard maps showing the maximum inundation depths for a selected set of probabilities of occurrence, with maps showing the expectation (median) and the uncertainty by

  5. Integrating Entropy-Based Naïve Bayes and GIS for Spatial Evaluation of Flood Hazard.

    Science.gov (United States)

    Liu, Rui; Chen, Yun; Wu, Jianping; Gao, Lei; Barrett, Damian; Xu, Tingbao; Li, Xiaojuan; Li, Linyi; Huang, Chang; Yu, Jia

    2017-04-01

    Regional flood risk caused by intensive rainfall under extreme climate conditions has increasingly attracted global attention. Mapping and evaluation of flood hazard are vital parts in flood risk assessment. This study develops an integrated framework for estimating spatial likelihood of flood hazard by coupling weighted naïve Bayes (WNB), geographic information system, and remote sensing. The north part of Fitzroy River Basin in Queensland, Australia, was selected as a case study site. The environmental indices, including extreme rainfall, evapotranspiration, net-water index, soil water retention, elevation, slope, drainage proximity, and density, were generated from spatial data representing climate, soil, vegetation, hydrology, and topography. These indices were weighted using the statistics-based entropy method. The weighted indices were input into the WNB-based model to delineate a regional flood risk map that indicates the likelihood of flood occurrence. The resultant map was validated by the maximum inundation extent extracted from moderate resolution imaging spectroradiometer (MODIS) imagery. The evaluation results, including mapping and evaluation of the distribution of flood hazard, are helpful in guiding flood inundation disaster responses for the region. The novel approach presented consists of weighted grid data, image-based sampling and validation, cell-by-cell probability inferring and spatial mapping. It is superior to an existing spatial naive Bayes (NB) method for regional flood hazard assessment. It can also be extended to other likelihood-related environmental hazard studies. © 2016 Society for Risk Analysis.

  6. Probabilistic Flood Mapping using Volunteered Geographical Information

    Science.gov (United States)

    Rivera, S. J.; Girons Lopez, M.; Seibert, J.; Minsker, B. S.

    2016-12-01

    Flood extent maps are widely used by decision makers and first responders to provide critical information that prevents economic impacts and the loss of human lives. These maps are usually obtained from sensory data and/or hydrologic models, which often have limited coverage in space and time. Recent developments in social media and communication technology have created a wealth of near-real-time, user-generated content during flood events in many urban areas, such as flooded locations, pictures of flooding extent and height, etc. These data could improve decision-making and response operations as events unfold. However, the integration of these data sources has been limited due to the need for methods that can extract and translate the data into useful information for decision-making. This study presents an approach that uses volunteer geographic information (VGI) and non-traditional data sources (i.e., Twitter, Flicker, YouTube, and 911 and 311 calls) to generate/update the flood extent maps in areas where no models and/or gauge data are operational. The approach combines Web-crawling and computer vision techniques to gather information about the location, extent, and water height of the flood from unstructured textual data, images, and videos. These estimates are then used to provide an updated flood extent map for areas surrounding the geo-coordinate of the VGI through the application of a Hydro Growing Region Algorithm (HGRA). HGRA combines hydrologic and image segmentation concepts to estimate a probabilistic flooding extent along the corresponding creeks. Results obtained for a case study in Austin, TX (i.e., 2015 Memorial Day flood) were comparable to those obtained by a calibrated hydrologic model and had good spatial correlation with flooding extents estimated by the Federal Emergency Management Agency (FEMA).

  7. Evaluation of various modelling approaches in flood routing simulation and flood area mapping

    Science.gov (United States)

    Papaioannou, George; Loukas, Athanasios; Vasiliades, Lampros; Aronica, Giuseppe

    2016-04-01

    An essential process of flood hazard analysis and mapping is the floodplain modelling. The selection of the modelling approach, especially, in complex riverine topographies such as urban and suburban areas, and ungauged watersheds may affect the accuracy of the outcomes in terms of flood depths and flood inundation area. In this study, a sensitivity analysis implemented using several hydraulic-hydrodynamic modelling approaches (1D, 2D, 1D/2D) and the effect of modelling approach on flood modelling and flood mapping was investigated. The digital terrain model (DTMs) used in this study was generated from Terrestrial Laser Scanning (TLS) point cloud data. The modelling approaches included 1-dimensional hydraulic-hydrodynamic models (1D), 2-dimensional hydraulic-hydrodynamic models (2D) and the coupled 1D/2D. The 1D hydraulic-hydrodynamic models used were: HECRAS, MIKE11, LISFLOOD, XPSTORM. The 2D hydraulic-hydrodynamic models used were: MIKE21, MIKE21FM, HECRAS (2D), XPSTORM, LISFLOOD and FLO2d. The coupled 1D/2D models employed were: HECRAS(1D/2D), MIKE11/MIKE21(MIKE FLOOD platform), MIKE11/MIKE21 FM(MIKE FLOOD platform), XPSTORM(1D/2D). The validation process of flood extent achieved with the use of 2x2 contingency tables between simulated and observed flooded area for an extreme historical flash flood event. The skill score Critical Success Index was used in the validation process. The modelling approaches have also been evaluated for simulation time and requested computing power. The methodology has been implemented in a suburban ungauged watershed of Xerias river at Volos-Greece. The results of the analysis indicate the necessity of sensitivity analysis application with the use of different hydraulic-hydrodynamic modelling approaches especially for areas with complex terrain.

  8. Flood hazard assessment for the Savannah River Site

    International Nuclear Information System (INIS)

    Chen, K.F.

    2000-01-01

    A method was developed to determine the probabilistic flood elevation curves for certain Savannah River Site (SRS) facilities. This paper presents the method used to determine the probabilistic flood elevation curve for F-Area due to runoff from the Upper Three Runs basin. Department of Energy (DOE) Order 420.1, Facility Safety, outlines the requirements for Natural Phenomena Hazard (NPH) mitigation for new and existing DOE facilities. The NPH considered in this paper is flooding. The facility-specific probabilistic flood hazard curve defines as a function of water elevation the annual probability of occurrence or the return period in years. Based on facility-specific probabilistic flood hazard curves and the nature of facility operations (e.g., involving hazardous or radioactive materials), facility managers can design permanent or temporary devices to prevent the propagation of flood on site, and develop emergency preparedness plans to mitigate the consequences of floods. The flood hazard curves for the SRS F-Area due to flooding in the Upper Three Runs basin are presented in this paper

  9. Flood risk assessment and mapping for the Lebanese watersheds

    Science.gov (United States)

    Abdallah, Chadi; Hdeib, Rouya

    2016-04-01

    Of all natural disasters, floods affect the greatest number of people worldwide and have the greatest potential to cause damage. Nowadays, with the emerging global warming phenomenon, this number is expected to increase. The Eastern Mediterranean area, including Lebanon (10452 Km2, 4.5 M habitant), has witnessed in the past few decades an increase frequency of flooding events. This study profoundly assess the flood risk over Lebanon covering all the 17 major watersheds and a number of small sub-catchments. It evaluate the physical direct tangible damages caused by floods. The risk assessment and evaluation process was carried out over three stages; i) Evaluating Assets at Risk, where the areas and assets vulnerable to flooding are identified, ii) Vulnerability Assessment, where the causes of vulnerability are assessed and the value of the assets are provided, iii) Risk Assessment, where damage functions are established and the consequent damages of flooding are estimated. A detailed Land CoverUse map was prepared at a scale of 1/ 1 000 using 0.4 m resolution satellite images within the flood hazard zones. The detailed field verification enabled to allocate and characterize all elements at risk, identify hotspots, interview local witnesses, and to correlate and calibrate previous flood damages with the utilized models. All filed gathered information was collected through Mobile Application and transformed to be standardized and classified under GIS environment. Consequently; the general damage evaluation and risk maps at different flood recurrence periods (10, 50, 100 years) were established. Major results showed that floods in a winter season (December, January, and February) of 10 year recurrence and of water retention ranging from 1 to 3 days can cause total damages (losses) that reach 1.14 M for crop lands and 2.30 M for green houses. Whereas, it may cause 0.2 M to losses in fruit trees for a flood retention ranging from 3 to 5 days. These numbers differs

  10. Accumulation risk assessment for the flooding hazard

    Science.gov (United States)

    Roth, Giorgio; Ghizzoni, Tatiana; Rudari, Roberto

    2010-05-01

    One of the main consequences of the demographic and economic development and of markets and trades globalization is represented by risks cumulus. In most cases, the cumulus of risks intuitively arises from the geographic concentration of a number of vulnerable elements in a single place. For natural events, risks cumulus can be associated, in addition to intensity, also to event's extension. In this case, the magnitude can be such that large areas, that may include many regions or even large portions of different countries, are stroked by single, catastrophic, events. Among natural risks, the impact of the flooding hazard cannot be understated. To cope with, a variety of mitigation actions can be put in place: from the improvement of monitoring and alert systems to the development of hydraulic structures, throughout land use restrictions, civil protection, financial and insurance plans. All of those viable options present social and economic impacts, either positive or negative, whose proper estimate should rely on the assumption of appropriate - present and future - flood risk scenarios. It is therefore necessary to identify proper statistical methodologies, able to describe the multivariate aspects of the involved physical processes and their spatial dependence. In hydrology and meteorology, but also in finance and insurance practice, it has early been recognized that classical statistical theory distributions (e.g., the normal and gamma families) are of restricted use for modeling multivariate spatial data. Recent research efforts have been therefore directed towards developing statistical models capable of describing the forms of asymmetry manifest in data sets. This, in particular, for the quite frequent case of phenomena whose empirical outcome behaves in a non-normal fashion, but still maintains some broad similarity with the multivariate normal distribution. Fruitful approaches were recognized in the use of flexible models, which include the normal

  11. Improving flood risk mapping in Italy: the FloodRisk open-source software

    Science.gov (United States)

    Albano, Raffaele; Mancusi, Leonardo; Craciun, Iulia; Sole, Aurelia; Ozunu, Alexandru

    2017-04-01

    management process, enhancing their awareness. This FOSS approach can promotes transparency and accountability through a process of "guided discovery". Moreover, the immediacy with which information is presented by the qualitative flood risk map, can facilitate and speed up the process of knowledge acquisition. An application of FloodRisk model is showed on a pilot case in "Serio" Valley, (North Italy), and its strengths and limits, in terms of additional efforts required in its application compared with EDQ procedure, have been highlighted focusing on the utility of the results provided for the development of FRMPs. Although they still present limits which prevent the FloodRisk application without critically consider the peculiarities of the investigated area in terms of available knowledge on hazard, exposure and vulnerability, the proposed approach surely produces an increase in available knowledge of flood risk and its drivers. This further information cannot be neglected for defining risk mitigation objectives and strategies. Hence, considering the ongoing efforts in the improvement of data availability and quality, FloodRisk could be a suitable tool for the next revision of flood risk maps due by December 2019, supporting effectively Italian and EU practitioners in the delineation of FRMPs (and for flood risk management in general).

  12. Monitoring and Mapping the Hurricane Harvey Flooding in Houston, Texas.

    Science.gov (United States)

    Balaji Bhaskar, M. S.

    2017-12-01

    Monitoring and Mapping the Hurricane Harvey Flooding in Houston, Texas.Urban flooding is a hazard that causes major destruction and loss of life. High intense precipitation events have increased significantly in Houston, Texas in recent years resulting in frequent river and bayou flooding. Many of the historical storm events such as Allison, Rita and Ike have caused several billion dollars in losses for the Houston-Galveston Region. A category 4 Hurricane Harvey made landfall on South Texas resulting in heavy precipitation from Aug 25 to 29 of 2017. About 1 trillion gallons of water fell across Harris County over a 4-day period. This amount of water covers Harris County's 1,800 square miles with an average of 33 inches of water. The long rain event resulted in an average 40inch rainfall across the area in several rain gauges and the maximum rainfall of 49.6 inches was recorded near Clear Creek. The objectives of our study are to 1) Process the Geographic Information System (GIS) and satellite data from the pre and post Hurricane Harvey event in Houston, Texas and 2) Analyze the satellite imagery to map the nature and pattern of the flooding in Houston-Galveston Region. The GIS data of the study area was downloaded and processed from the various publicly available resources such as Houston Galveston Area Council (HGAC), Texas Commission of Environmental Quality (TCEQ) and Texas Natural Resource Information Systems (TNRIS). The satellite data collected soon after the Harvey flooding event were downloaded and processed using the ERDAS image processing software. The flood plain areas surrounding the Brazos River, Buffalo Bayou and the Addicks Barker reservoirs showed severe inundation. The different watershed areas affected by the catastrophic flooding in the wake of Hurricane Harvey were mapped and compared with the pre flooding event.

  13. A framework for the case-specific assessment of Green Infrastructure in mitigating urban flood hazards

    Science.gov (United States)

    Schubert, Jochen E.; Burns, Matthew J.; Fletcher, Tim D.; Sanders, Brett F.

    2017-10-01

    This research outlines a framework for the case-specific assessment of Green Infrastructure (GI) performance in mitigating flood hazard in small urban catchments. The urban hydrologic modeling tool (MUSIC) is coupled with a fine resolution 2D hydrodynamic model (BreZo) to test to what extent retrofitting an urban watershed with GI, rainwater tanks and infiltration trenches in particular, can propagate flood management benefits downstream and support intuitive flood hazard maps useful for communicating and planning with communities. The hydrologic and hydraulic models are calibrated based on current catchment conditions, then modified to represent alternative GI scenarios including a complete lack of GI versus a full implementation of GI. Flow in the hydrologic/hydraulic models is forced using a range of synthetic rainfall events with annual exceedance probabilities (AEPs) between 1-63% and durations from 10 min to 24 h. Flood hazard benefits mapped by the framework include maximum flood depths and extents, flow intensity (m2/s), flood duration, and critical storm duration leading to maximum flood conditions. Application of the system to the Little Stringybark Creek (LSC) catchment shows that across the range of AEPs tested and for storm durations equal or less than 3 h, presently implemented GI reduces downstream flooded area on average by 29%, while a full implementation of GI would reduce downstream flooded area on average by 91%. A full implementation of GI could also lower maximum flow intensities by 83% on average, reducing the drowning hazard posed by urban streams and improving the potential for access by emergency responders. For storm durations longer than 3 h, a full implementation of GI lacks the capacity to retain the resulting rainfall depths and only reduces flooded area by 8% and flow intensity by 5.5%.

  14. Airborne geophysical radon hazard mapping

    International Nuclear Information System (INIS)

    Walker, P.

    1993-01-01

    Shales containing uranium pose a radon health hazard even when covered by several meters of overburden. Such an alum shale in southern Norway has been mapped with a joint helicopter borne electromagnetic (HEM) and radiometric survey. Results are compared with ground spectrometer, radon emanometer and radon gas measurements in dwellings, and a model to predict radon gas concentrations from the airborne data is developed. Since the shale is conductive, combining the HEM data with the radiometric channel allows the shale to be mapped with greater reliability than if the radiometric channel were used alone. Radiometrically more active areas which do not pose a radon gas hazard can thus be separated from the shales which do. The ground follow-up work consisted of spectrometer and radon emanometer measurements over a uranium anomaly coinciding with a conductor. The correlation between the airborne uranium channel, the ground uranium channel and emanometry is extremely good, indicating that airborne geophysics can, in this case, be used to predict areas having a high radon potential. Contingency tables comparing both radon exhalation and concentration in dwellings with the airborne uranium data show a strong relationship exists between exhalation and the airborne data and while a relationship between concentration and the airborne data is present, but weaker

  15. THE USAGE OF TECHNOLOGIES IN TERRESTRIAL MEASUREMENTS FOR HAZARD MAPS

    Directory of Open Access Journals (Sweden)

    VELE Dan

    2015-06-01

    Full Text Available In the context of natural phenomena (earthquakes, floods, landslides etc. bring economical and social prejudices year by year, watching on them and taking decisions becomes mandatory for reducing the material and human lives loss. Making hazard maps represents a tool used on wide global scale but also particularly in our country. This paper work has the purpose to reveal the interests of certain authors related to the usage of the new technologies of terrestrial measurements (GPS technologies, photogrammetry, cartography and of remote sensing in order to make these hazard maps.

  16. Differences in flood hazard projections in Europe – their causes and consequences for decision making

    NARCIS (Netherlands)

    Kundzewicz, Zbigniew W.; Krysanova, V.; Dankers, R.; Hirabayashi, Y.; Kanae, S.; Hattermann, F. F.; Huang, S.; Milly, P. C. D.; Stoffel, M.H.; Driessen, P. P. J.; Matczak, Piotr; Quevauviller, P.; Schellnhuber, H. J.

    2017-01-01

    This paper interprets differences in flood hazard projections over Europe and identifies likely sources of discrepancy. Further, it discusses potential implications of these differences for flood risk reduction and adaptation to climate change. The discrepancy in flood hazard projections raises

  17. Mapping Infected Area after a Flash-Flooding Storm Using Multi Criteria Analysis and Spectral Indices

    Science.gov (United States)

    Al-Akad, S.; Akensous, Y.; Hakdaoui, M.

    2017-11-01

    This research article is summarize the applications of remote sensing and GIS to study the urban floods risk in Al Mukalla. Satellite acquisition of a flood event on October 2015 in Al Mukalla (Yemen) by using flood risk mapping techniques illustrate the potential risk present in this city. Satellite images (The Landsat and DEM images data were atmospherically corrected, radiometric corrected, and geometric and topographic distortions rectified.) are used for flood risk mapping to afford a hazard (vulnerability) map. This map is provided by applying image-processing techniques and using geographic information system (GIS) environment also the application of NDVI, NDWI index, and a method to estimate the flood-hazard areas. Four factors were considered in order to estimate the spatial distribution of the hazardous areas: flow accumulation, slope, land use, geology and elevation. The multi-criteria analysis, allowing to deal with vulnerability to flooding, as well as mapping areas at the risk of flooding of the city Al Mukalla. The main object of this research is to provide a simple and rapid method to reduce and manage the risks caused by flood in Yemen by take as example the city of Al Mukalla.

  18. Combined fluvial and pluvial urban flood hazard analysis: concept development and application to Can Tho city, Mekong Delta, Vietnam

    Science.gov (United States)

    Apel, Heiko; Martínez Trepat, Oriol; Nghia Hung, Nguyen; Thi Chinh, Do; Merz, Bruno; Viet Dung, Nguyen

    2016-04-01

    coincidence into account. All hazards - fluvial, pluvial and combined - were accompanied by an uncertainty estimation taking into account the natural variability of the flood events. This resulted in probabilistic flood hazard maps showing the maximum inundation depths for a selected set of probabilities of occurrence, with maps showing the expectation (median) and the uncertainty by percentile maps. The results are critically discussed and their usage in flood risk management are outlined.

  19. Revision to flood hazard evaluation for the Savannah River Site

    Energy Technology Data Exchange (ETDEWEB)

    Buckley, R. [Savannah River Site (SRS), Aiken, SC (United States). Savannah River National Lab. (SRNL); Werth, D. [Savannah River Site (SRS), Aiken, SC (United States). Savannah River National Lab. (SRNL)

    2014-08-25

    Requirements for the Natural Phenomena Hazard (NPH) mitigation for new and existing Department of Energy (DOE) facilities are outlined in DOE Order 420.1. This report examines the hazards posed by potential flooding and represents an update to two previous reports. The facility-specific probabilistic flood hazard curve is defined as the water elevation for each annual probability of precipitation occurrence (or inversely, the return period in years). New design hyetographs for both 6-hr and 24-hr precipitation distributions were used in conjunction with hydrological models of various basins within the Savannah River Site (SRS). For numerous locations of interest, peak flow discharge and flood water elevation were determined. In all cases, the probability of flooding of these facilities for a 100,000 year precipitation event is negligible.

  20. Adige river in Trento flooding map, 1892: private or public risk transfer?

    Science.gov (United States)

    Ranzi, Roberto

    2016-04-01

    For the determination of the flood risk hydrologist and hydraulic engineers focuse their attention mainly to the estimation of physical factors determining the flood hazard, while economists and experts of social sciences deal mainly with the estimation of vulnerability and exposure. The fact that flood zoning involves both hydrological and socio-economic aspects, however, was clear already in the XIX century when the impact of floods on inundated areas started to appear in flood maps, for instance in the UK and in Italy. A pioneering 'flood risk' map for the Adige river in Trento, Italy, was already published in 1892, taking into account in detail both hazard intensity in terms of velocity and depth, frequency of occurrence, vulnerability and economic costs for flood protection with river embankments. This map is likely to be the reinterpreted certainly as a pioneering, and possibly as the first flood risk map for an Italian river and worldwide. Risk levels were divided in three categories and seven sub-categories, depending on flood water depth, velocity, frequency and damage costs. It is interesting to notice the fact that at that time the map was used to share the cost of levees' reparation and enhancement after the severe September 1882 flood as a function of the estimated level of protection of the respective areas against the flood risk. The sharing of costs between public bodies, the railway company and private owners was debated for about 20 years and at the end the public sustained the major costs. This shows how already at that time the economic assessment of structural flood protections was based on objective and rational cost-benefit criteria, that hydraulic risk mapping was perceived by the society as fundamental for the design of flood protection systems and that a balanced cost sharing between public and private was an accepted approach although some protests arose at that time.

  1. Flood hazard assessment using 1D and 2D approaches

    Science.gov (United States)

    Petaccia, Gabriella; Costabile, Pierfranco; Macchione, Francesco; Natale, Luigi

    2013-04-01

    The EU flood risk Directive (Directive 2007/60/EC) prescribes risk assessment and mapping to develop flood risk management plans. Flood hazard mapping may be carried out with mathematical models able to determine flood-prone areas once realistic conditions (in terms of discharge or water levels) are imposed at the boundaries of the case study. The deterministic models are mainly based on shallow water equations expressed in their 1D or 2D formulation. The 1D approach is widely used, especially in technical studies, due to its relative simplicity, its computational efficiency and also because it requires topographical data not as expensive as the ones needed by 2D models. Even if in a great number of practical situations, such as modeling in-channel flows and not too wide floodplains, the 1D approach may provide results close to the prediction of a more sophisticated 2D model, it must be pointed out that the correct use of a 1D model in practical situations is more complex than it may seem. The main issues to be correctly modeled in a 1D approach are the definition of hydraulic structures such as bridges and buildings interacting with the flow and the treatment of the tributaries. Clearly all these aspects have to be taken into account also in the 2D modeling, but with fewer difficulties. The purpose of this paper is to show how the above cited issues can be described using a 1D or 2D unsteady flow modeling. In particular the Authors will show the devices that have to be implemented in 1D modeling to get reliable predictions of water levels and discharges comparable to the ones obtained using a 2D model. Attention will be focused on an actual river (Crati river) located in the South of Italy. This case study is quite complicated since it deals with the simulation of channeled flows, overbank flows, interactions with buildings, bridges and tributaries. Accurate techniques, intentionally developed by the Authors to take into account all these peculiarities in 1D and 2

  2. Utilising social media contents for flood inundation mapping

    Science.gov (United States)

    Schröter, Kai; Dransch, Doris; Fohringer, Joachim; Kreibich, Heidi

    2016-04-01

    Data about the hazard and its consequences are scarce and not readily available during and shortly after a disaster. An information source which should be explored in a more efficient way is eyewitness accounts via social media. This research presents a methodology that leverages social media content to support rapid inundation mapping, including inundation extent and water depth in the case of floods. It uses quantitative data that are estimated from photos extracted from social media posts and their integration with established data. Due to the rapid availability of these posts compared to traditional data sources such as remote sensing data, areas affected by a flood, for example, can be determined quickly. Key challenges are to filter the large number of posts to a manageable amount of potentially useful inundation-related information, and to interpret and integrate the posts into mapping procedures in a timely manner. We present a methodology and a tool ("PostDistiller") to filter geo-located posts from social media services which include links to photos and to further explore this spatial distributed contextualized in situ information for inundation mapping. The June 2013 flood in Dresden is used as an application case study in which we evaluate the utilization of this approach and compare the resulting spatial flood patterns and inundation depths to 'traditional' data sources and mapping approaches like water level observations and remote sensing flood masks. The outcomes of the application case are encouraging. Strengths of the proposed procedure are that information for the estimation of inundation depth is rapidly available, particularly in urban areas where it is of high interest and of great value because alternative information sources like remote sensing data analysis do not perform very well. The uncertainty of derived inundation depth data and the uncontrollable availability of the information sources are major threats to the utility of the approach.

  3. Determining the Financial Impact of Flood Hazards in Ungaged Basins

    Science.gov (United States)

    Cotterman, K. A.; Gutenson, J. L.; Pradhan, N. R.; Byrd, A.

    2017-12-01

    Many portions of the Earth lack adequate authoritative or in situ data that is of great value in determining natural hazard vulnerability from both anthropogenic and physical perspective. Such locations include the majority of developing nations, which do not possess adequate warning systems and protective infrastructure. The lack of warning and protection from natural hazards make these nations vulnerable to the destructive power of events such as floods. The goal of this research is to demonstrate an initial workflow with which to characterize flood financial hazards with global datasets and crowd-sourced, non-authoritative data in ungagged river basins. This workflow includes the hydrologic and hydraulic response of the watershed to precipitation, characterized by the physics-based modeling application Gridded Surface-Subsurface Hydrologic Analysis (GSSHA) model. In addition, data infrastructure and resources are available to approximate the human impact of flooding. Open source, volunteer geographic information (VGI) data can provide global coverage of elements at risk of flooding. Additional valuation mechanisms can then translate flood exposure into percentage and financial damage to each building. The combinations of these tools allow the authors to remotely assess flood hazards with minimal computational, temporal, and financial overhead. This combination of deterministic and stochastic modeling provides the means to quickly characterize watershed flood vulnerability and will allow emergency responders and planners to better understand the implications of flooding, both spatially and financially. In either a planning, real-time, or forecasting scenario, the system will assist the user in understanding basin flood vulnerability and increasing community resiliency and preparedness.

  4. Flood Hazards: Communicating Hydrology and Complexity to the Public

    Science.gov (United States)

    Holmes, R. R.; Blanchard, S. F.; Mason, R. R.

    2010-12-01

    Floods have a major impact on society and the environment. Since 1952, approximately 1,233 of 1,931 (64%) Federal disaster declarations were due directly to flooding, with an additional 297 due to hurricanes which had associated flooding. Although the overall average annual number of deaths due to flooding has decreased in the United States, the average annual flood damage is rising. According to the Munich Reinsurance Company in their publication “Schadenspiegel 3/2005”, during 1990s the world experienced as much as $500 billion in economic losses due to floods, highlighting the serious need for continued emphasis on flood-loss prevention measures. Flood-loss prevention has two major elements: mitigation (including structural flood-control measures and land-use planning and regulation) and risk awareness. Of the two, increasing risk awareness likely offers the most potential for protecting lives over the near-term and long-term sustainability in the coming years. Flood-risk awareness and risk-aware behavior is dependent on communication, involving both prescriptive and educational measures. Prescriptive measures (for example, flood warnings and stormwater ordinances) are and have been effective, but there is room for improvement. New communications technologies, particularly social media utilizing mobile, smart phones and text devices, for example, could play a significant role in increasing public awareness of long-term risk and near-term flood conditions. The U.S. Geological Survey (USGS), for example, the Federal agency that monitors the Nation’s rivers, recently released a new service that can better connect the to the public to information about flood hazards. The new service, WaterAlert (URL: http://water.usgs.gov/wateralert/), allows users to set flood notification thresholds of their own choosing for any USGS real-time streamgage. The system then sends emails or text messages to subscribers whenever the threshold conditions are met, as often as the

  5. Damaging Rainfall and Flooding. The Other Sahel Hazards

    Energy Technology Data Exchange (ETDEWEB)

    Tarhule, A. [Department of Geography, University of Oklahoma, 100 East Boyd Street, Norman, OK, 73079 (United States)

    2005-10-01

    Damaging rainfall and rain-induced flooding occur from time to time in the drought-prone Sahel savannah zone of Niger in West Africa but official records of these events and their socioeconomic impacts do not exist. This paper utilized newspaper accounts between 1970 and 2000 to survey and illustrate the range of these flood hazards in the Sahel. During the study interval, 53 newspaper articles reported 79 damaging rainfall and flood events in 47 different communities in the Sahel of Niger. Collectively, these events destroyed 5,580 houses and rendered 27,289 people homeless. Cash losses and damage to infrastructure in only three events exceeded $4 million. Sahel residents attribute these floods to five major causes including both natural and anthropogenic, but they view the flood problem as driven primarily by land use patterns. Despite such awareness, traditional coping strategies appear inadequate for dealing with the problems in part because of significant climatic variability. Analysis of several rainfall measures indicates that the cumulative rainfall in the days prior to a heavy rain event is an important factor influencing whether or not heavy rainfall results in flooding. Thus, despite some limitations, newspaper accounts of historical flooding are largely consistent with measured climatic variables. The study demonstrates that concerted effort is needed to improve the status of knowledge concerning flood impacts and indeed other natural and human hazards in the Sahel.

  6. Prompt Proxy Mapping of Flood Damaged Rice Fields Using MODIS-Derived Indices

    Directory of Open Access Journals (Sweden)

    Youngjoo Kwak

    2015-11-01

    Full Text Available Flood mapping, particularly hazard and risk mapping, is an imperative process and a fundamental part of emergency response and risk management. This paper aims to produce a flood risk proxy map of damaged rice fields over the whole of Bangladesh, where monsoon river floods are dominant and frequent, affecting over 80% of the total population. This proxy risk map was developed to meet the request of the government on a national level. This study represents a rapid, straightforward methodology for estimating rice-crop damage in flood areas of Bangladesh during the large flood from July to September 2007, despite the lack of primary data. We improved a water detection algorithm to achieve a better discrimination capacity to discern flood areas by using a modified land surface water index (MLSWI. Then, rice fields were estimated utilizing a hybrid rice field map from land-cover classification and MODIS-derived indices, such as the normalized difference vegetation index (NDVI and enhanced vegetation index (EVI. The results showed that the developed method is capable of providing instant, comprehensive, nationwide mapping of flood risks, such as rice field damage. The detected flood areas and damaged rice fields during the 2007 flood were verified by comparing them with the Advanced Land Observing Satellite (ALOS AVNIR-2 images (a 10 m spatial resolution and in situ field survey data with moderate agreement (K = 0.57.

  7. Has land subsidence changed the flood hazard potential? A case example from the Kujukuri Plain, Chiba Prefecture, Japan

    Directory of Open Access Journals (Sweden)

    H. L. Chen

    2015-11-01

    Full Text Available Coastal areas are subject to flood hazards because of their topographic features, social development and related human activities. The Kujukuri Plain, Chiba Prefecture, Japan, is located nearby the Tokyo metropolitan area and it faces to the Pacific Ocean. In the Kujukuri Plain, widespread occurrence of land subsidence has been caused by exploitation of groundwater, extraction of natural gas dissolved in brine, and natural consolidation of the Holocene and landfill deposits. The locations of land subsidence include areas near the coast, and it may increase the flood hazard potential. Hence, it is very important to evaluate flood hazard potential by taking into account the temporal change of land elevation caused by land subsidence, and to prepare hazard maps for protecting the surface environment and for developing an appropriate land-use plan. In this study, flood hazard assessments at three different times, i.e., 1970, 2004, and 2013 are implemented by using a flood hazard model based on Multicriteria Decision Analysis with Geographical Information System techniques. The model incorporates six factors: elevation, depression area, river system, ratio of impermeable area, detention ponds, and precipitation. Main data sources used are 10 m resolution topography data, airborne laser scanning data, leveling data, Landsat-TM data, two 1:30 000 scale river watershed maps, and precipitation data from observation stations around the study area and Radar data. The hazard assessment maps for each time are obtained by using an algorithm that combines factors with weighted linear combinations. The assignment of the weight/rank values and their analysis are realized by the application of the Analytic Hierarchy Process method. This study is a preliminary work to investigate flood hazards on the Kujukuri Plain. A flood model will be developed to simulate more detailed change of the flood hazard influenced by land subsidence.

  8. Flood Hazard and Risk Analysis in Urban Area

    Science.gov (United States)

    Huang, Chen-Jia; Hsu, Ming-hsi; Teng, Wei-Hsien; Lin, Tsung-Hsien

    2017-04-01

    Typhoons always induce heavy rainfall during summer and autumn seasons in Taiwan. Extreme weather in recent years often causes severe flooding which result in serious losses of life and property. With the rapid industrial and commercial development, people care about not only the quality of life, but also the safety of life and property. So the impact of life and property due to disaster is the most serious problem concerned by the residents. For the mitigation of the disaster impact, the flood hazard and risk analysis play an important role for the disaster prevention and mitigation. In this study, the vulnerability of Kaohsiung city was evaluated by statistics of social development factor. The hazard factors of Kaohsiung city was calculated by simulated flood depth of six different return periods and four typhoon events which result in serious flooding in Kaohsiung city. The flood risk can be obtained by means of the flood hazard and social vulnerability. The analysis results provide authority to strengthen disaster preparedness and to set up more resources in high risk areas.

  9. Flood hazards in an urbanizing watershed in Riyadh, Saudi Arabia

    Directory of Open Access Journals (Sweden)

    Hatim O. Sharif

    2016-03-01

    Full Text Available Riyadh, the capital of the Kingdom of Saudi Arabia, has experienced unusual levels of urbanization in the past few decades, making it one of the fastest growing cities in the world. This paper examines flood hazards in the rapidly urbanizing catchment of Al-Aysen in Riyadh. Remote sensing and geographic information system techniques were employed to obtain and prepare input data for hydrologic and hydraulic models, with the former based on the very popular curve number approach. Due to the limited nature of the rainfall data, observations from two rain gauges in the vicinity of the catchment were used to estimate design storms. The hydrologic model was run in a semi-distributed mode by dividing the catchment into many sub-catchments. The impact of urbanization on run-off volume and peak discharge resulting from different storms was investigated, with various urbanization scenarios simulated. Flood hazard zones and affected streets were also identified through hydrologic/hydraulic model simulation. The mismatch between administrative and catchment boundaries can create problems in flood risk management for similar cities since hydrologic processes and flood hazards are based on the hydrologic connectivity. Since flooding events impact the road network and create driving hazards, governmental decision-makers must take the necessary precautions to protect drivers in these situations.

  10. The necessity of flood risk maps on Timis River

    International Nuclear Information System (INIS)

    Aldescu, Geogr Catalin

    2008-01-01

    The paper aims to clarify the necessity of risk reduction in flood prone areas along the Timis River. Different methods to reduce risk in flood prone areas are analyzed as well. According to the EU Flood Directive it is mandatory for the European countries to develop flood maps and flood risk maps. The maps help to assess the vulnerable zones in the floodable (i.e. flood prone) areas. Many European countries have produced maps which identify areas prone to flooding events for specific known return periods. In Romania the flood risk maps have not been yet produced, but the process has been started to be implemented at the national and regional level, therefore the first results will be soon available. Banat Hydrographical Area was affected by severe floods on Timis River in 2000, 2005 and 2006. The 2005 flood was the most devastating one with large economic losses. As a result of these catastrophes the need for generating flood risk maps along the Timis. River was clearly stated. The water management experts can use these maps in order to identify the 'hot spots' in Timis catchment, give the people a better understanding of flood risk issues and help reducing flood risk more efficient in the identified vulnerable areas.

  11. Open Source Web-Based Solutions for Disseminating and Analyzing Flood Hazard Information at the Community Level

    Science.gov (United States)

    Santillan, M. M.-M.; Santillan, J. R.; Morales, E. M. O.

    2017-09-01

    We discuss in this paper the development, including the features and functionalities, of an open source web-based flood hazard information dissemination and analytical system called "Flood EViDEns". Flood EViDEns is short for "Flood Event Visualization and Damage Estimations", an application that was developed by the Caraga State University to address the needs of local disaster managers in the Caraga Region in Mindanao, Philippines in accessing timely and relevant flood hazard information before, during and after the occurrence of flood disasters at the community (i.e., barangay and household) level. The web application made use of various free/open source web mapping and visualization technologies (GeoServer, GeoDjango, OpenLayers, Bootstrap), various geospatial datasets including LiDAR-derived elevation and information products, hydro-meteorological data, and flood simulation models to visualize various scenarios of flooding and its associated damages to infrastructures. The Flood EViDEns application facilitates the release and utilization of this flood-related information through a user-friendly front end interface consisting of web map and tables. A public version of the application can be accessed at http://121.97.192.11:8082/. The application is currently expanded to cover additional sites in Mindanao, Philippines through the "Geo-informatics for the Systematic Assessment of Flood Effects and Risks for a Resilient Mindanao" or the "Geo-SAFER Mindanao" Program.

  12. 78 FR 36217 - Proposed Flood Hazard Determinations

    Science.gov (United States)

    2013-06-17

    ... sciences established to review conflicting scientific and technical data and provide recommendations for... Shop Road, Wetumpka, AL 36092. Lowndes County, Alabama, and Incorporated Areas Maps Available for...

  13. Landslide and flood hazard assessment in urban areas of Levoča region (Eastern Slovakia)

    Science.gov (United States)

    Magulova, Barbora; Caporali, Enrica; Bednarik, Martin

    2010-05-01

    The case study presents the use of statistical methods and analysis tools, for hazard assessment of "urbanization units", implemented in a Geographic Information Systems (GIS) environment. As a case study, the Levoča region (Slovakia) is selected. The region, with a total area of about 351 km2, is widely affected by landslides and floods. The problem, for small urbanization areas, is nowadays particularly significant from the socio-economic point of view. It is considered, presently, also an increasing problem, mainly because of climate change and more frequent extreme rainfall events. The geo-hazards are evaluated using a multivariate analysis. The landslide hazard assessment is based on the comparison and subsequent statistical elaboration of territorial dependence among different input factors influencing the instability of the slopes. Particularly, five factors influencing slope stability are evaluated, i.e. lithology, slope aspect, slope angle, hypsographic level and present land use. As a result a new landslide susceptibility map is compiled and different zones of stable, dormant and non-stable areas are defined. For flood hazard map a detailed digital elevation model is created. A compose index of flood hazard is derived from topography, land cover and pedology related data. To estimate flood discharge, time series of stream flow and precipitation measurements are used. The assessment results are prognostic maps of landslide hazard and flood hazard, which presents the optimal base for urbanization planning.

  14. Toward economic flood loss characterization via hazard simulation

    Science.gov (United States)

    Czajkowski, Jeffrey; Cunha, Luciana K.; Michel-Kerjan, Erwann; Smith, James A.

    2016-08-01

    Among all natural disasters, floods have historically been the primary cause of human and economic losses around the world. Improving flood risk management requires a multi-scale characterization of the hazard and associated losses—the flood loss footprint. But this is typically not available in a precise and timely manner, yet. To overcome this challenge, we propose a novel and multidisciplinary approach which relies on a computationally efficient hydrological model that simulates streamflow for scales ranging from small creeks to large rivers. We adopt a normalized index, the flood peak ratio (FPR), to characterize flood magnitude across multiple spatial scales. The simulated FPR is then shown to be a key statistical driver for associated economic flood losses represented by the number of insurance claims. Importantly, because it is based on a simulation procedure that utilizes generally readily available physically-based data, our flood simulation approach has the potential to be broadly utilized, even for ungauged and poorly gauged basins, thus providing the necessary information for public and private sector actors to effectively reduce flood losses and save lives.

  15. 78 FR 48701 - Proposed Flood Hazard Determinations

    Science.gov (United States)

    2013-08-09

    ... DEPARTMENT OF HOMELAND SECURITY Federal Emergency Management Agency [Docket ID FEMA-2013-0002... inspection at both the online location and the respective Community Map Repository address listed in the... online through the FEMA Map Service Center at www.msc.fema.gov for comparison. You may submit comments...

  16. 77 FR 18839 - Proposed Flood Hazard Determinations

    Science.gov (United States)

    2012-03-28

    ... DEPARTMENT OF HOMELAND SECURITY Federal Emergency Management Agency [Docket ID FEMA-2012-0003... community are available for inspection at both the online location and the respective Community Map... each community are accessible online through the FEMA Map Service Center at www.msc.fema.gov for...

  17. 78 FR 57646 - Proposed Flood Hazard Determinations

    Science.gov (United States)

    2013-09-19

    ... DEPARTMENT OF HOMELAND SECURITY Federal Emergency Management Agency [Docket ID FEMA-2013-0002... community are available for inspection at both the online location and the respective Community Map... each community are accessible online through the FEMA Map Service Center at www.msc.fema.gov for...

  18. 77 FR 44651 - Proposed Flood Hazard Determinations

    Science.gov (United States)

    2012-07-30

    ... DEPARTMENT OF HOMELAND SECURITY Federal Emergency Management Agency [Docket ID FEMA-2012-0003... available for inspection at both the online location and the respective Community Map Repository address... are accessible online through the FEMA Map Service Center at www.msc.fema.gov for comparison. You may...

  19. 78 FR 43908 - Proposed Flood Hazard Determinations

    Science.gov (United States)

    2013-07-22

    ... DEPARTMENT OF HOMELAND SECURITY Federal Emergency Management Agency [Docket ID FEMA-2013-0002... inspection at both the online location and the respective Community Map Repository address listed in the... online through the FEMA Map Service Center at www.msc.fema.gov for comparison. You may submit comments...

  20. 78 FR 5824 - Proposed Flood Hazard Determinations

    Science.gov (United States)

    2013-01-28

    ... DEPARTMENT OF HOMELAND SECURITY Federal Emergency Management Agency [Docket ID FEMA-2013-0002... available for inspection at both the online location and the respective Community Map Repository address... are accessible online through the FEMA Map Service Center at www.msc.fema.gov for comparison. You may...

  1. 78 FR 36220 - Proposed Flood Hazard Determinations

    Science.gov (United States)

    2013-06-17

    ... DEPARTMENT OF HOMELAND SECURITY Federal Emergency Management Agency [Docket ID FEMA-2013-0002... are available for inspection at both the online location and the respective Community Map Repository... community are accessible online through the FEMA Map Service Center at www.msc.fema.gov for comparison. You...

  2. 78 FR 20339 - Proposed Flood Hazard Determinations

    Science.gov (United States)

    2013-04-04

    ... DEPARTMENT OF HOMELAND SECURITY Federal Emergency Management Agency [Docket ID FEMA-2013-0002... are available for inspection at both the online location and the respective Community Map Repository... community are accessible online through the FEMA Map Service Center at www.msc.fema.gov for comparison. You...

  3. 78 FR 48888 - Proposed Flood Hazard Determinations

    Science.gov (United States)

    2013-08-12

    ... DEPARTMENT OF HOMELAND SECURITY Federal Emergency Management Agency [Docket ID FEMA-2013-0002... available for inspection at both the online location and the respective Community Map Repository address... are accessible online through the FEMA Map Service Center at www.msc.fema.gov for comparison. You may...

  4. 77 FR 18842 - Proposed Flood Hazard Determinations

    Science.gov (United States)

    2012-03-28

    ... DEPARTMENT OF HOMELAND SECURITY Federal Emergency Management Agency [Docket ID FEMA-2012-0003... are available for inspection at both the online location and the respective Community Map Repository... community are accessible online through the FEMA Map Service Center at www.msc.fema.gov for comparison. You...

  5. 77 FR 46104 - Proposed Flood Hazard Determinations

    Science.gov (United States)

    2012-08-02

    ... DEPARTMENT OF HOMELAND SECURITY Federal Emergency Management Agency [Internal Agency Docket No... inspection at both the online location and the respective Community Map Repository address listed in the... online through the FEMA Map Service Center at www.msc.fema.gov for comparison. You may submit comments...

  6. 78 FR 43907 - Proposed Flood Hazard Determinations

    Science.gov (United States)

    2013-07-22

    ... DEPARTMENT OF HOMELAND SECURITY Federal Emergency Management Agency [Docket ID FEMA-2013-0002... inspection at both the online location and the respective Community Map Repository address listed in the... online through the FEMA Map Service Center at www.msc.fema.gov for comparison. You may submit comments...

  7. 78 FR 21143 - Proposed Flood Hazard Determinations

    Science.gov (United States)

    2013-04-09

    ... DEPARTMENT OF HOMELAND SECURITY Federal Emergency Management Agency [Docket ID FEMA-2013-0002... are available for inspection at both the online location and the respective Community Map Repository... community are accessible online through the FEMA Map Service Center at www.msc.fema.gov for comparison. You...

  8. 77 FR 74859 - Proposed Flood Hazard Determinations

    Science.gov (United States)

    2012-12-18

    ... DEPARTMENT OF HOMELAND SECURITY Federal Emergency Management Agency [Docket ID FEMA-2012-0003... inspection at both the online location and the respective Community Map Repository address listed in the... online through the FEMA Map Service Center at www.msc.fema.gov for comparison. You may submit comments...

  9. 77 FR 50709 - Proposed Flood Hazard Determinations

    Science.gov (United States)

    2012-08-22

    ... DEPARTMENT OF HOMELAND SECURITY Federal Emergency Management Agency [Docket ID FEMA-2012-0003... inspection at both the online location and the respective Community Map Repository address listed in the... online through the FEMA Map Service Center at www.msc.fema.gov for comparison. You may submit comments...

  10. 77 FR 56669 - Proposed Flood Hazard Determinations

    Science.gov (United States)

    2012-09-13

    ... DEPARTMENT OF HOMELAND SECURITY Federal Emergency Management Agency [Docket ID FEMA-2012-0003... inspection at both the online location and the respective Community Map Repository address listed in the... online through the FEMA Map Service Center at www.msc.fema.gov for comparison. You may submit comments...

  11. 78 FR 43909 - Proposed Flood Hazard Determinations

    Science.gov (United States)

    2013-07-22

    ... DEPARTMENT OF HOMELAND SECURITY Federal Emergency Management Agency [Docket ID FEMA-2013-0002... community are available for inspection at both the online location and the respective Community Map... each community are accessible online through the FEMA Map Service Center at www.msc.fema.gov for...

  12. 78 FR 43906 - Proposed Flood Hazard Determinations

    Science.gov (United States)

    2013-07-22

    ... DEPARTMENT OF HOMELAND SECURITY Federal Emergency Management Agency [Docket ID FEMA-2013-0002... inspection at both the online location and the respective Community Map Repository address listed in the... online through the FEMA Map Service Center at www.msc.fema.gov for comparison. You may submit comments...

  13. 78 FR 49278 - Proposed Flood Hazard Determinations

    Science.gov (United States)

    2013-08-13

    ... DEPARTMENT OF HOMELAND SECURITY Federal Emergency Management Agency [Docket ID FEMA-2013-0002... available for inspection at both the online location and the respective Community Map Repository address... are accessible online through the FEMA Map Service Center at www.msc.fema.gov for comparison. You may...

  14. 77 FR 67016 - Proposed Flood Hazard Determinations

    Science.gov (United States)

    2012-11-08

    ... DEPARTMENT OF HOMELAND SECURITY Federal Emergency Management Agency [Docket ID FEMA-2012-0003... inspection at both the online location and the respective Community Map Repository address listed in the... online through the FEMA Map Service Center at www.msc.fema.gov for comparison. You may submit comments...

  15. 78 FR 32679 - Proposed Flood Hazard Determinations

    Science.gov (United States)

    2013-05-31

    ... DEPARTMENT OF HOMELAND SECURITY Federal Emergency Management Agency [Docket ID FEMA-2013-0002... community are available for inspection at both the online location and the respective Community Map... each community are accessible online through the FEMA Map Service Center at www.msc.fema.gov for...

  16. 77 FR 58562 - Proposed Flood Hazard Determinations

    Science.gov (United States)

    2012-09-21

    ... DEPARTMENT OF HOMELAND SECURITY Federal Emergency Management Agency [Docket ID FEMA-2012-0003... inspection at both the online location and the respective Community Map Repository address listed in the... online through the FEMA Map Service Center at www.msc.fema.gov for comparison. You may submit comments...

  17. 77 FR 58560 - Proposed Flood Hazard Determinations

    Science.gov (United States)

    2012-09-21

    ... Channing Street, South Wing, Delaware, OH 43015. Mason County, West Virginia, and Incorporated Areas Maps... Henderson Town Hall, 1 Railroad Street, Henderson, WV 25106. Town of Leon Town Hall, 136 Main Street, Leon... Courthouse, 200 6th Street, Point Pleasant, WV 25550. Wood County, West Virginia, and Incorporated Areas Maps...

  18. Sources of uncertainty in flood inundation maps

    Science.gov (United States)

    Bales, J.D.; Wagner, C.R.

    2009-01-01

    Flood inundation maps typically have been used to depict inundated areas for floods having specific exceedance levels. The uncertainty associated with the inundation boundaries is seldom quantified, in part, because all of the sources of uncertainty are not recognized and because data available to quantify uncertainty seldom are available. Sources of uncertainty discussed in this paper include hydrologic data used for hydraulic model development and validation, topographic data, and the hydraulic model. The assumption of steady flow, which typically is made to produce inundation maps, has less of an effect on predicted inundation at lower flows than for higher flows because more time typically is required to inundate areas at high flows than at low flows. Difficulties with establishing reasonable cross sections that do not intersect and that represent water-surface slopes in tributaries contribute additional uncertainties in the hydraulic modelling. As a result, uncertainty in the flood inundation polygons simulated with a one-dimensional model increases with distance from the main channel.

  19. DRAFT DIGITAL FLOOD INSURANCE RATE MAP DATABASE, CHEROKEE COUNTY, SC

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  20. Digital Flood Insurance Rate Map Database, Buchanan County, Iowa, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  1. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, FLEMING COUNTY, KY

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  2. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Charles COUNTY, MD, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  3. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, BUTLER COUNTY, NE

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  4. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, SACRAMENTO COUNTY, CALIFORNIA, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  5. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, CITY OF SACRAMENTO, CALIFORNIA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  6. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, HONOLULU COUNTY, HI, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  7. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, KAUAI COUNTY, HAWAII, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  8. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, SARPY COUNTY, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  9. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, LUCAS COUNTY, OHIO

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  10. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, NASSAU COUNTY, NEW YORK

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  11. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, HARDIN COUNTY, TX

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  12. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, SULLIVAN COUNTY, NEW YORK

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  13. Digital Flood Insurance Rate Map Database, PRINCE GEORGE, VA, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  14. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, SHELBY COUNTY, OHIO, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  15. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, WAGONER COUNTY, OKLAHOMA, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  16. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, SUFFOLK COUNTY, MASSACHUSETTS

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  17. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, FAIRFIELD COUNTY, CONNECTICUT

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  18. DIGITAL FLOOD INSURANCE RATE MAP DATABASE ROCKLAND COUNTY, NY, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  19. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, OTTAWA COUNTY, OHIO, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  20. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, SAUNDERS COUNTY, NEBRASKA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  1. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, RED WILLOW COUNTY, NEBRASKA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  2. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, CHEROKEE COUNTY, KANSAS

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  3. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, POLK COUNTY, NEBRASKA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  4. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, HARLAN COUNTY, NEBRASKA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  5. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, RENO COUNTY, KANSAS

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  6. DIGITAL FLOOD INSURANCE RATE MAP DATABASE FOR HOWARD COUNTY, NEBRASKA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  7. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, FURNAS COUNTY, NEBRASKA

    Data.gov (United States)

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  8. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, LANCASTER COUNTY, NE, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  9. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, ALLAMAKEE COUNTY, IOWA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  10. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, CASS COUNTY, NEBRASKA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  11. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, MCPHERSON COUNTY, KANSAS

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  12. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, DAWES COUNTY, NEBRASKA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  13. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, VALLEY COUNTY, NEBRASKA

    Data.gov (United States)

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  14. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, ELLSWORTH COUNTY, KANSAS

    Data.gov (United States)

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  15. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, SHERMAN COUNTY, NEBRASKA

    Data.gov (United States)

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  16. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, HARVEY COUNTY, KANSAS

    Data.gov (United States)

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  17. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, PLATTE COUNTY, NEBRASKA

    Data.gov (United States)

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  18. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, COLFAX COUNTY, NEBRASKA

    Data.gov (United States)

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  19. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, THURSTON COUNTY, NEBRASKA

    Data.gov (United States)

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  20. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, TAMA COUNTY, IOWA

    Data.gov (United States)

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  1. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, WEBSTER COUNTY, NEBRASKA

    Data.gov (United States)

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  2. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Eddy County, NM

    Data.gov (United States)

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  3. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, RAY COUNTY, MISSOURI, USA

    Data.gov (United States)

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  4. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, JEFFERSON COUNTY, IDAHO, USA

    Data.gov (United States)

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  5. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, LAWRENCE COUNTY, OHIO, USA

    Data.gov (United States)

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  6. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, GRANT COUNTY, WISCONSIN, USA

    Data.gov (United States)

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  7. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, SEBASTIAN COUNTY, AR

    Data.gov (United States)

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  8. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, SEBASTIAN COUNTY, ARKANSAS

    Data.gov (United States)

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  9. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, FERGUS COUNTY, MONTANA, USA

    Data.gov (United States)

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  10. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, BONNER COUNTY, IDAHO

    Data.gov (United States)

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  11. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, SAN JOAQUIN COUNTY, CALIFORNIA

    Data.gov (United States)

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  12. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, LORAIN COUNTY, OHIO USA

    Data.gov (United States)

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  13. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, ROBERTSON COUNTY, KY

    Data.gov (United States)

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  14. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, COSHOCTON COUNTY, OHIO, USA

    Data.gov (United States)

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  15. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, NEWTON COUNTY, MISSOURI, USA

    Data.gov (United States)

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  16. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, CHEROKEE COUNTY, TX

    Data.gov (United States)

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  17. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, HAMILTON COUNTY, OHIO, USA

    Data.gov (United States)

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  18. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, GRANT COUNTY, KY

    Data.gov (United States)

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  19. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, ESSEX COUNTY, MA

    Data.gov (United States)

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  20. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, CARROLL COUNTY, GEORGIA, USA

    Data.gov (United States)

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  1. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, DOUGLAS COUNTY, ILLINOIS USA

    Data.gov (United States)

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  2. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Douglas County, Oregon, USA

    Data.gov (United States)

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  3. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, LINCOLN COUNTY, ARKANSAS, USA

    Data.gov (United States)

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  4. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, POWELL COUNTY, KY

    Data.gov (United States)

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  5. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, COLFAX COUNTY, New Mexico

    Data.gov (United States)

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  6. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Winston COUNTY, AL

    Data.gov (United States)

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  7. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, CONVERSE COUNTY, WYOMING, USA.

    Data.gov (United States)

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  8. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Dougherty County, GA

    Data.gov (United States)

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  9. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, POLK COUNTY, TX

    Data.gov (United States)

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  10. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, HUNTERDON CO., NJ

    Data.gov (United States)

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  11. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, SEDGWICK COUNTY, KANSAS, USA

    Data.gov (United States)

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  12. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, FINNEY COUNTY, USA

    Data.gov (United States)

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  13. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, CULLMAN COUNTY, AL

    Data.gov (United States)

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  14. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, JOHNSON COUNTY, GEORGIA, USA

    Data.gov (United States)

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  15. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Northumberland County, VA, USA

    Data.gov (United States)

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  16. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, CADDO PARISH, LOUISIANA, USA

    Data.gov (United States)

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  17. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, ETOWAH COUNTY, AL

    Data.gov (United States)

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  18. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, FORT BEND COUNTY, TEXAS

    Data.gov (United States)

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  19. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, LACLEDE COUNTY, MISSOURI, USA

    Data.gov (United States)

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  20. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, CLINTON COUNTY, MISSOURI, USA

    Data.gov (United States)

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  1. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, MCDONALD COUNTY, USA

    Data.gov (United States)

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  2. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, MERCER COUNTY, KY

    Data.gov (United States)

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  3. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, AUGUSTA COUNTY, VA, USA

    Data.gov (United States)

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  4. Digital Flood Insurance Rate Map Database, Crawford County, PA

    Data.gov (United States)

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  5. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, WARREN COUNTY, OH, USA

    Data.gov (United States)

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  6. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, BATH COUNTY, KY

    Data.gov (United States)

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  7. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Spartanburg County, South Carolina

    Data.gov (United States)

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  8. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Douglas COUNTY, Nevada

    Data.gov (United States)

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  9. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Rio Grande County, Colorado

    Data.gov (United States)

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  10. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Elbert County, Colorado

    Data.gov (United States)

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  11. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, JASPER COUNTY, TX

    Data.gov (United States)

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  12. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Roosevelt COUNTY, New Mexico

    Data.gov (United States)

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  13. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Linn County, Oregon, USA

    Data.gov (United States)

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  14. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, TEHAMA COUNTY, CALIFORNIA, USA

    Data.gov (United States)

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  15. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Wythe County, VA, USA

    Data.gov (United States)

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  16. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, SULLIVAN COUNTY, PA, USA

    Data.gov (United States)

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  17. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Cleburne COUNTY, AL

    Data.gov (United States)

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  18. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, KITSAP COUNTY, WASHINGTON, USA

    Data.gov (United States)

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  19. DIGITAL FLOOD INSURANCE RATE MAP DATABASE,CAMDEN COUNTY, GEORGIA

    Data.gov (United States)

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  20. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, MENDOCINO COUNTY, CALIFORNIA

    Data.gov (United States)

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  1. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, APPLING COUNTY, GEORGIA, USA

    Data.gov (United States)

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  2. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Wilcox COUNTY, AL

    Data.gov (United States)

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  3. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, WASHINGTON COUNTY, USA

    Data.gov (United States)

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  4. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, BALLARD COUNTY, KY

    Data.gov (United States)

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  5. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, HARRISON COUNTY, KY

    Data.gov (United States)

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  6. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, PASCO COUNTY, FLORIDA, USA

    Data.gov (United States)

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  7. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, GILMER COUNTY, GEORGIA, USA

    Data.gov (United States)

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  8. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, MIAMI - DADE COUNTY, FLORIDA

    Data.gov (United States)

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  9. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, WALKER COUNTY, TX

    Data.gov (United States)

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  10. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, WALKER COUNTY, AL

    Data.gov (United States)

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  11. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, WALKER COUNTY, GEORGIA, USA

    Data.gov (United States)

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  12. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, BENTON COUNTY, MINNESOTA, USA

    Data.gov (United States)

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  13. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, DAVIESS COUNTY, KY

    Data.gov (United States)

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  14. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, MONROE COUNTY, GEORGIA, USA

    Data.gov (United States)

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  15. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, HENRY COUNTY, GEORGIA, USA

    Data.gov (United States)

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  16. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, MARLBORO COUNTY, SC

    Data.gov (United States)

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  17. FINAL DIGITAL FLOOD INSURANCE RATE MAP DATABASE, GREENWOOD COUNTY, SC

    Data.gov (United States)

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  18. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, RICE COUNTY, MINNESOTA, USA

    Data.gov (United States)

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  19. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, CHRISTIAN COUNTY, KY

    Data.gov (United States)

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  20. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, CHRISTIAN COUNTY, ILLINOIS USA

    Data.gov (United States)

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  1. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, SHELBY COUNTY, IA, USA

    Data.gov (United States)

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  2. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, POTTAWATTAMIE COUNTY, IOWA, USA

    Data.gov (United States)

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  3. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, MITCHELL COUNTY, IOWA, USA

    Data.gov (United States)

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  4. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, WARREN COUNTY, USA

    Data.gov (United States)

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  5. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, CLAYTON COUNTY, IOWA, USA

    Data.gov (United States)

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  6. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, HOWARD COUNTY, IOWA, USA

    Data.gov (United States)

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  7. DIGITAL FLOOD INSURANCE RATE MAP DATABAES, LA PAZ COUNTY, AZ

    Data.gov (United States)

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  8. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, SEWARD COUNTY, USA

    Data.gov (United States)

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  9. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, SCOTT COUNTY, KY

    Data.gov (United States)

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  10. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, NEWTON COUNTY, GEORGIA

    Data.gov (United States)

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  11. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, NEWTON COUNTY, GEORGIA, USA

    Data.gov (United States)

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  12. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, MIDDLESEX, VA, USA

    Data.gov (United States)

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  13. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, KARNES COUNTY, TEXAS, USA

    Data.gov (United States)

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  14. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, VOLUSIA COUNTY, FL, USA

    Data.gov (United States)

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  15. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Marshall COUNTY, AL

    Data.gov (United States)

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  16. DRAFT DIGITAL FLOOD INSURANCE RATE MAP DATABASE, HEMPSTEAD COUNTY, AR

    Data.gov (United States)

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  17. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, TOM GREEN COUNTY, TEXAS

    Data.gov (United States)

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  18. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Berks County, Pennsylvania, USA

    Data.gov (United States)

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  19. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, STONE COUNTY, MISSOURI, USA

    Data.gov (United States)

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  20. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, VAL VERDE COUNTY, TEXAS

    Data.gov (United States)

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  1. Digital Flood Insurance Rate Map Database, Richmond County, Virginia, USA

    Data.gov (United States)

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  2. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, WASATCH COUNTY, UTAH, USA

    Data.gov (United States)

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  3. Digital Flood Insurance Rate Map Database, Westmoreland County, Virginia, USA

    Data.gov (United States)

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  4. Flood Insurance Rate Map Database, Kent County, Delaware, USA

    Data.gov (United States)

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  5. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, SHELBY COUNTY, KENTUCKY, USA

    Data.gov (United States)

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  6. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, MCCRACKEN COUNTY, KY

    Data.gov (United States)

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  7. DIGITAL FLOOD INSURANCE RATE MAP DATABASE,GRAVES COUNTY, KY

    Data.gov (United States)

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  8. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, LYON COUNTY, KY

    Data.gov (United States)

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  9. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, WOLFE COUNTY, KY

    Data.gov (United States)

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  10. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, WEBSTER COUNTY, KY

    Data.gov (United States)

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  11. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, HAWAII COUNTY, HAWAII, USA

    Data.gov (United States)

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  12. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, MCINTOSH COUNTY, GEORGIA, USA

    Data.gov (United States)

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  13. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, HART COUNTY, KY

    Data.gov (United States)

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  14. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, OSCEOLA COUNTY, FL

    Data.gov (United States)

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  15. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, ELLIOTT COUNTY, KY

    Data.gov (United States)

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  16. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, GAGE COUNTY, NEBRASKA

    Data.gov (United States)

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  17. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, CLARK COUNTY, USA

    Data.gov (United States)

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  18. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, ALLEN COUNTY, INDIANA, USA

    Data.gov (United States)

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  19. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, ANGELINA COUNTY, TX

    Data.gov (United States)

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  20. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, DOUGLAS COUNTY, NEBRASKA, USA

    Data.gov (United States)

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  1. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, NEWPORT COUNTY, RHODE ISLAND

    Data.gov (United States)

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  2. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, ATASCOSA COUNTY, TEXAS

    Data.gov (United States)

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  3. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, DOUGLAS COUNTY, USA

    Data.gov (United States)

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  4. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, POLK COUNTY, USA

    Data.gov (United States)

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  5. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, MARION COUNTY, KY

    Data.gov (United States)

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  6. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, LEBANON COUNTY, PENNSYLVANIA

    Data.gov (United States)

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  7. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, CRAWFORD COUNTY, AR ,USA

    Data.gov (United States)

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  8. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, SOLANO COUNTY, CALIFORNIA, USA

    Data.gov (United States)

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  9. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Mitchell County, GA

    Data.gov (United States)

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  10. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, TAYLOR COUNTY, FL, USA

    Data.gov (United States)

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  11. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, GRIMES COUNTY, TX

    Data.gov (United States)

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  12. Digital Flood Insurance Rate Map Database, Allegheny County, Pennsylvania, USA

    Data.gov (United States)

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  13. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, ST. LOUIS, USA

    Data.gov (United States)

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  14. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, DELAWARE COUNTY, OK, USA

    Data.gov (United States)

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  15. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, UNION COUNTY, FLORIDA, USA

    Data.gov (United States)

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  16. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, LEE COUNTY, FLORIDA

    Data.gov (United States)

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  17. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, HAMILTON COUNTY, FLORIDA, USA

    Data.gov (United States)

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  18. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, WAYNE COUNTY, USA

    Data.gov (United States)

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  19. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Jefferson COUNTY, AL

    Data.gov (United States)

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  20. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, WALTON COUNTY, FL, USA

    Data.gov (United States)

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  1. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Kenton COUNTY, Kentucky

    Data.gov (United States)

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  2. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, RUSSELL COUNTY, KY

    Data.gov (United States)

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  3. DRAFT DIGITAL FLOOD INSURANCE RATE MAP DATABASE, LANCASTER COUNTY, SC

    Data.gov (United States)

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  4. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, CHAMBERS COUNTY, TEXAS

    Data.gov (United States)

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  5. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, CHATHAM COUNTY, GEORGIA, USA

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  6. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, HILLSBOROUGH COUNTY, FLORIDA

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  7. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, WALLER COUNTY, TX

    Data.gov (United States)

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  8. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, CARBON COUNTY, UTAH

    Data.gov (United States)

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  9. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Liberty County, TX

    Data.gov (United States)

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  10. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, SAN JACINTO COUNTY, TX

    Data.gov (United States)

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  11. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, New London County, CT

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  12. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Westmoreland County, PA, USA

    Data.gov (United States)

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  13. Digital Flood Insurance Rate Map Database, Sussex County, Delaware, USA

    Data.gov (United States)

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  14. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, TYLER COUNTY, TX

    Data.gov (United States)

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  15. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Stafford County , VIRGINIA

    Data.gov (United States)

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  16. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, SUMNER COUNTY, USA

    Data.gov (United States)

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  17. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, GREENVILLE COUNTY, SOUTH CAROLINA

    Data.gov (United States)

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  18. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, DICKENSON COUNTY, VA, USA

    Data.gov (United States)

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  19. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, HOUSTON COUNTY, TX

    Data.gov (United States)

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  20. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, DESOTO COUNTY, FL, USA

    Data.gov (United States)

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  1. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, FANNIN COUNTY, GEORGIA, USA

    Data.gov (United States)

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  2. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, ST. FRANCOIS COUNTY, USA

    Data.gov (United States)

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  3. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, LAFAYETTE COUNTY, MISSOURI, USA

    Data.gov (United States)

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  4. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, RANDALL COUNTY, TX, USA

    Data.gov (United States)

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  5. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, PEMBINA COUNTY, USA

    Data.gov (United States)

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  6. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, MCLEAN COUNTY, KY

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  7. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, RUSK COUNTY, TX

    Data.gov (United States)

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  8. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Nelson County, VA, USA

    Data.gov (United States)

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  9. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, CHEROKEE COUNTY, GEORGIA, USA

    Data.gov (United States)

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  10. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, NELSON COUNTY, KY

    Data.gov (United States)

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  11. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, MIDDLESEX COUNTY, MASSACHUSETTS

    Data.gov (United States)

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  12. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, ESCAMBIA COUNTY, AL

    Data.gov (United States)

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  13. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Baldwin COUNTY, AL

    Data.gov (United States)

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  14. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, BARTOW COUNTY, GEORGIA, USA

    Data.gov (United States)

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  15. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, ALPENA COUNTY, MI

    Data.gov (United States)

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  16. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, CALDWELL PARISH, LOUISIANA, USA

    Data.gov (United States)

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  17. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, SHIAWASSEE COUNTY, MICHIGAN, USA

    Data.gov (United States)

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  18. Digital Flood Insurance Rate Map for Vermillion County, IN

    Data.gov (United States)

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  19. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, EL DORADO COUNTY, CALIFORNIA

    Data.gov (United States)

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  20. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, GADSDEN COUNTY, FL, USA

    Data.gov (United States)

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  1. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, MARION COUNTY, FLORIDA

    Data.gov (United States)

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  2. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, SHELBY COUNTY, AL

    Data.gov (United States)

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  3. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Harris COUNTY, TX

    Data.gov (United States)

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  4. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, PIKE COUNTY, AL

    Data.gov (United States)

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  5. Digital Flood Insurance Rate Map Database, Bradford County, Pennsylvania, USA

    Data.gov (United States)

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  6. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, JOHNSON COUNTY, KY

    Data.gov (United States)

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  7. Digital Flood Insurance Rate Map Database, Charles County, Maryland, USA

    Data.gov (United States)

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  8. Digital Flood Insurance Rate Map Database, Essex County, Virginia, USA

    Data.gov (United States)

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  9. Digital Flood Insurance Rate Map Database, Calvert County, Maryland, USA

    Data.gov (United States)

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  10. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, COBB COUNTY, GA, USA

    Data.gov (United States)

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  11. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, MATHEWS COUNTY, VIRGINIA

    Data.gov (United States)

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  12. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, HOLMES COUNTY, OHIO

    Data.gov (United States)

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  13. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, HOLMES COUNTY, USA

    Data.gov (United States)

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  14. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, KOOTENAI COUNTY, USA

    Data.gov (United States)

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  15. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Accomack County, VIRGINIA

    Data.gov (United States)

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  16. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, CLARKE COUNTY, GEORGIA, USA

    Data.gov (United States)

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  17. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, LYCOMING COUNTY, PENNSYLVANIA

    Data.gov (United States)

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  18. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, WHATCOM COUNTY, WASHINGTON

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  19. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, HARRISON COUNTY, TEXAS

    Data.gov (United States)

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  20. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, DELTA COUNTY, COLORADO, USA

    Data.gov (United States)

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  1. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, GULF COUNTY, FLORIDA, USA

    Data.gov (United States)

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  2. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Delaware County, Pennsylvania, USA

    Data.gov (United States)

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  3. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, HALL COUNTY, NE, USA

    Data.gov (United States)

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  4. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, NORFOLK COUNTY, MASSACHUSETTS

    Data.gov (United States)

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  5. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, COWLEY COUNTY, USA

    Data.gov (United States)

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  6. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, TALBOT, MARYLAND, USA

    Data.gov (United States)

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  7. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, NANTUCKET COUNTY, MASSACHUSETTS

    Data.gov (United States)

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  8. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, PATRICK COUNTY, VA, USA

    Data.gov (United States)

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  9. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, RANDOLPH COUNTY, WV, USA

    Data.gov (United States)

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  10. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, GRAYSON COUNTY, VA, USA

    Data.gov (United States)

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  11. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, CHESTERFIELD, VA, USA

    Data.gov (United States)

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  12. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, SURRY COUNTY, VA, USA

    Data.gov (United States)

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  13. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, WORCESTER COUNTY, MASSACHUSETTS

    Data.gov (United States)

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  14. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Buckingham County, VA, USA

    Data.gov (United States)

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  15. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, GARRETT COUNTY, Maryland, USA

    Data.gov (United States)

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  16. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, OTTAWA COUNTY, USA

    Data.gov (United States)

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  17. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, RALEIGH COUNTY, WV, USA

    Data.gov (United States)

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  18. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Essex County, VA, USA

    Data.gov (United States)

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  19. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, GRAND COUNTY, USA

    Data.gov (United States)

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  20. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Caroline COUNTY, Maryland, USA

    Data.gov (United States)

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  1. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, TUCKER COUNTY, WV, USA

    Data.gov (United States)

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  2. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Sussex County, VA, USA

    Data.gov (United States)

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  3. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, WESTMORELAND COUNTY, VA, USA

    Data.gov (United States)

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  4. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, FLUVANNA COUNTY, VA, USA

    Data.gov (United States)

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  5. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Richmond County, VA, USA

    Data.gov (United States)

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  6. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Pulaski County, VA, USA

    Data.gov (United States)

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  7. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Scott County, VA, USA

    Data.gov (United States)

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  8. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, DILLON COUNTY, USA

    Data.gov (United States)

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  9. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Upshur County, WV, USA

    Data.gov (United States)

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  10. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, ALLEN COUNTY, USA

    Data.gov (United States)

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  11. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, LINN COUNTY, IA, USA

    Data.gov (United States)

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  12. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, CAROLINE COUNTY, VA, USA

    Data.gov (United States)

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  13. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, BANDERA COUNTY, TEXAS

    Data.gov (United States)

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  14. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Washington COUNTY, NE

    Data.gov (United States)

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  15. Digital Flood Insurance Rate Map Database, Mercer County, PA

    Data.gov (United States)

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  16. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, ST JOSEPH COUNTY, MI

    Data.gov (United States)

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  17. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, SHERBURNE COUNTY, MINNESOTA, USA

    Data.gov (United States)

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  18. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, DUKES COUNTY, MA

    Data.gov (United States)

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  19. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Terrell County, GA

    Data.gov (United States)

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  20. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, GLOUCESTER, VA, USA

    Data.gov (United States)

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  1. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, WORCESTER COUNTY, MA

    Data.gov (United States)

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  2. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, SONOMA COUNTY, CALIFORNIA

    Data.gov (United States)

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  3. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, MONMOUTH COUNTY, NEW JERSEY

    Data.gov (United States)

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  4. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, YORK COUNTY, PA, USA

    Data.gov (United States)

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  5. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, BENTON COUNTY, ARKANSAS

    Data.gov (United States)

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  6. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, GORDON COUNTY, GEORGIA

    Data.gov (United States)

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  7. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, SUSSEX COUNTY, NEW JERSEY

    Data.gov (United States)

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  8. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, MARIN COUNTY, CALIFORNIA

    Data.gov (United States)

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  9. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, CLEARFIELD COUNTY, PA, USA

    Data.gov (United States)

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  10. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, COOPER COUNTY, MISSOURI, USA

    Data.gov (United States)

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  11. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, CAMERON COUNTY, PA, USA

    Data.gov (United States)

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  12. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, BOYLE COUNTY, KY

    Data.gov (United States)

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  13. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, WARREN COUNTY, NEW JERSEY

    Data.gov (United States)

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  14. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, FAYETTE COUNTY, GEORGIA, USA

    Data.gov (United States)

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  15. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, SUFFOLK COUNTY, NEW YORK

    Data.gov (United States)

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  16. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Bell COUNTY, Kentucky

    Data.gov (United States)

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  17. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, BATH COUNTY, VIRGINIA

    Data.gov (United States)

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  18. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, INDIAN RIVER COUNTY, FL

    Data.gov (United States)

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  19. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, SIMPSON COUNTY, KY

    Data.gov (United States)

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  20. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Cherokee COUNTY, AL

    Data.gov (United States)

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  1. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, JACKSON COUNTY, AL

    Data.gov (United States)

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  2. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Lancaster County, VA, USA

    Data.gov (United States)

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  3. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, BEDFORD COUNTY, VA, USA

    Data.gov (United States)

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  4. DRAFT DIGITAL FLOOD INSURANCE RATE MAP DATABASE, HONOLULU COUNTY, HI

    Data.gov (United States)

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  5. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, MAYES COUNTY, OK

    Data.gov (United States)

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  6. DRAFT DIGITAL FLOOD INSURANCE RATE MAP DATABASE, NEWBERRY COUNTY, SC

    Data.gov (United States)

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  7. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, GREENE COUNTY, GEORGIA, USA

    Data.gov (United States)

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  8. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, FRANKLIN COUNTY, VA, USA

    Data.gov (United States)

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  9. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, HIGHLAND COUNTY, VIRGINIA

    Data.gov (United States)

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  10. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, SUMTER COUNTY, AL

    Data.gov (United States)

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  11. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, GRADY COUNTY, OKLAHOMA

    Data.gov (United States)

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  12. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, SHASTA COUNTY, CALIFORNIA

    Data.gov (United States)

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  13. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, HOWELL COUNTY, MISSOURI, USA

    Data.gov (United States)

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  14. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, SISKIYOU COUNTY, CALIFORNIA, USA

    Data.gov (United States)

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  15. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, YOLO COUNTY, CALIFORNIA

    Data.gov (United States)

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  16. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, PLUMAS COUNTY, CALIFORNIA, USA

    Data.gov (United States)

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  17. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, ORANGE COUNTY, CALIFORNIA, USA

    Data.gov (United States)

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  18. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, RIVERSIDE COUNTY, CALIFORNIA, USA

    Data.gov (United States)

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  19. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Tuolumne County, USA

    Data.gov (United States)

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  20. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, PIMA COUNTY, ARIZONA, USA

    Data.gov (United States)

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  1. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, COCHISE COUNTY, ARIZONA, USA

    Data.gov (United States)

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  2. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, MADERA COUNTY, CALIFORNIA

    Data.gov (United States)

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  3. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, TEHAMA COUNTY, CALIFORNIA

    Data.gov (United States)

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  4. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, YUMA COUNTY, ARIZONA, USA

    Data.gov (United States)

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  5. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, SACRAMENTO COUNTY, CALIFORNIA

    Data.gov (United States)

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  6. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, BUTTE COUNTY, CALIFORNIA, USA

    Data.gov (United States)

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  7. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, CLATSOP COUNTY, OR, USA

    Data.gov (United States)

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  8. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, HENRY COUNTY, VA, USA

    Data.gov (United States)

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  9. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, RALLS COUNTY, USA

    Data.gov (United States)

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  10. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, MARION COUNTY, USA

    Data.gov (United States)

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  11. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, HOUSTON COUNTY, Georgia

    Data.gov (United States)

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  12. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, MIDLAND COUNTY, MICHIGAN, USA

    Data.gov (United States)

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  13. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, HOPKINS COUNTY, KY

    Data.gov (United States)

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  14. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, EATON COUNTY, MICHIGAN, USA

    Data.gov (United States)

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  15. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Oswego COUNTY, New York

    Data.gov (United States)

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  16. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Butts County, GA

    Data.gov (United States)

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  17. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, BULLOCH COUNTY, GEORGIA, USA

    Data.gov (United States)

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  18. DIGITAL FLOOD INSURACE RATE MAP DATABASE, LEON COUNTY, FL, USA

    Data.gov (United States)

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  19. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, JONES COUNTY, GEORGIA, USA

    Data.gov (United States)

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  20. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, LUNA COUNTY, New Mexico

    Data.gov (United States)

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