This dataset is a merged and unified one from seven individual datasets, making it the longest records ever and wide coverage in the US for flood studies. All individual databases and a unified database are provided to accommodate different user needs. It is anticipated that this database can support a variety of flood-related research, such as a validation resource for hydrologic or hydraulic simulations, climatic studies concerning spatiotemporal patterns of floods given this long-term and U.S.-wide coverage, and flood susceptibility analysis for vulnerable geophysical locations.

Description of filenames:

1. cyberFlood_1104.csv – web-based crowdsourced flood database, developed at the University of Oklahoma (Wan et al., 2014). 203 flood events from 1998 to 2008 are retrieved with the latest version. Data accessed on 11/04/2020.

Data attributes: ID, Year, Month, Day, Duration, fatality, Severity, Cause, Lat, Long, Country Code, Continent Code

2. DFO.xlsx – the Dartmouth Flood Observatory flood database. It is a tabular form of global flood database, collected from news, government agencies, stream gauges, and remote sensing instruments from 1985 to the present. Data accessed on 10/27/2020.

Data attributes: ID, GlodeNumber, Country, OtherCountry, long, lat, Area, Began, Ended, Validation, Dead, Displaced, MainCause, Severity

3. emdat_public_2020_11_01_query_uid-MSWGVQ.xlsx – Emergency Events Database (EM-DAT). This flood report is managed by the Centre for Research on the Epidemiology of Disasters in Belgium, which contains all types of global natural disasters from 1900 to the present. Data accessed on 11/01/2020.

Data attributes: Dis No, Year, Seq, Disaster Group, Disaster Subgroup, Disaster Type, Disaster Subtype, Disaster Subsubtype, Event Nane, Entity Criteria, Country, ISO, Region, Continent, Location, Origin, Associated Disaster, Associated Disaster2, OFDA Response, Appeal, Declaration, Aid Contribution, Disaster Magnitude, Latitude, Longitude, Local Time, River Basin, Start Year, Start Month, Start Day, End Year, End Month, End Day, Total Death, No. Injured, No. Affected, No. Homeless, Total Affected, Reconstruction, Insured Damages, Total Damages, CPI

4. extracted_events_NOAA.csv – The national weather service storm reports. The NOAA NWS team collects weather-related natural hazards from 1950 to the present. Data accessed on 10/27/2020.

Data attributes: BEGIN_YEARMONTH, BEGIN_DAY, BEGIN_TIME, END_YEARMONTH, END_DAY, END_TIME, EPISODE_ID, EVENT_ID, STATE, STATE_FIPS, YEAR, MONTH_NAME, EVENT_TYPE, CZ_TYPE, CZ_FIPS, CZ_NAME, WFO, BEGIN_DATETIME, CZ_TIMEZONE, END_DATE_TIME, INJURIES_DIRECT, INJURIES_INDIRECT, DEATHS_DIRECT, DEATHS_INDIRECT, DAMAGE_PROPERTY, DAMAGE_CROPS, SOURCE, MAGNITUDE, MAGNITUDE_TYPE, FLOOD CAUSE, CATEGORY, TOR_F_SCALE< TOR_LENGTH, TOR_WIDTH, TOR_OTHER_WFO, TOR_OTHER_CZ_STATE, TOR_OTHER_CZ_FIPS, BEGIN_RANGE, BEGIN_AZIMUTH, BEGIN_LOCATION, END_RANGE, END_AZIMUTH, END_LOCATION, BEGIN_LAT, BEGIN_LON, END_LAT, END_LON, EPISODE_NARRATIVE, EVENT_NARRATIVE, DATA_SOURCE

5. FEDB_1118.csv – The University of Connecticut Flood Events Database. Floods retrieved from 6,301 stream gauges in the U.S. after flow separation from 2002 to 2013 (Shen et al., 2017). Data accessed on 11/18/2020.

Data attributes: STCD, StartTimeP, EndTimeP, StartTimeF, EndTimeF, Perc, Peak, RunoffCoef, IBF, Vp, Vb, Vt, Pmean, ETr, ELs, VarTr, VarLs, EQ, Q2, CovTrLs, Category, Geometry

6. GFM_events.csv – Global Flood Monitoring dataset. It is a crowdsourcing flood database derived from Twitter tweets over the globe since 2014. Data accessed on 11/9/2020.

Data attributes: event_id, location_ID, location_ID_url, name, type, country_location_ID, country_ISO3, start, end, time of detection

7. mPing_1030.csv – meteorological Phenomena Identification Near the Ground (mPing). The mPing app is a crowdsourcing, weather-reporting software jointly developed by NOAA National Severe Storms Laboratory (NSSL) and the University of Oklahoma (Elmore et al., 2014). Data accessed on 10/30/2020.

Data attributes: id, obtime, category, description, description_id, lon, lat

8. USFD_v1.0.csv – A merged United States Flood Database from 1900 to the present.

Data attributes: DATE_BEGIN, DATE_END, DURATION, LON, LAT, COUNTRY, STATE, AREA, FATALITY, DAMAGE, SEVERITY, SOURCE, CAUSE, SOURCE_DB, SOURCE_ID, DESCRIPTION, SLOPE, DEM, LULC, DISTANCE_RIVER, CONT_AREA, DEPTH, YEAR.

Details of attributes:

DATE_BEGIN: begin datetime of an event. yyyymmddHHMMSS

DATE_END: end datetime of an event. yyyymmddHHMMSS

DURATION: duration of an event in hours

LON: longitude in degrees

LAT: latitude in degrees

COUNTRY: United States of America

STATE: US state name

AREA: affected areas in km^2

FATALITY: number of fatalities

DAMAGE: economic damages in US dollars

SEVERITY: event severity, (1/1.5/2) according to DFO.

SOURCE: flood information source.

CAUSE: flood cause.

SOURCE_DB: source database from item 1-7.

SOURCE_ID: original ID in the source database.

DESCRIPTION: event description

SLOPE: calculated slope based on SRTM DEM 90m

DEM: Digital Elevation Model

LULC: Land Use Land Cover

DISTANCE_RIVER: distance to major river network in km,

CONT_AREA: contributing area (km^2), from MERIT Hydro

DEPTH: 500-yr flood depth

YEAR: year of the event.

The script to merge all sources and figure plots can be found in https://github.com/chrimerss/USFD.

Global Flood Database Scripts & Data

This repository includes code and supporting data for the Global Flood Database. This include descriptions of the data and code, and how they relate to Tellman et al, Satellite observations indicate increasing proportion of population exposed to floods

The Global Flood Database contains maps of the extent and temporal distribution of 913 flood events occurring between 2000-2018. For more information, see the associated journal article. Flood events were collected from the Dartmouth Flood Observatory and used to collect MODIS imagery. The selected 913 events are those that were successfully mapped (passed quality control as having significant inundation beyond permanent water) using 12,719 scenes from Terra and Aqua MODIS sensors. Each pixel was classified as water or non-water at 250-meter resolution during the full date range of each flood event and subsequent data products were generated including maximum flood extent ("flooded" band) and the duration of inundation in days ("duration" band). Water and non-water classifications during a flood event include permanent water (here resampling the 30-meter JRC Global Surface Water dataset representing permanent water to 250-meter resolution), which can be masked out to isolate flood water using the "jrc_perm_water" band. Extra data quality bands were added representing cloud conditions during the flood event (e.g., "clear_views" representing the number of clear days the flood was observed between its start and end dates and "clear_perc" representing the percentage of clear day observation of the total event duration in days). Each image in the ImageCollection represents the map of an individual flood. The collection can be filtered by date, country, or Dartmouth Flood Observatory original ID.

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 (LOMRs) that have been issued against those databases since their publication date. The DFIRM Database is the digital, geospatial version of the flood hazard information shown on the published paper Flood Insurance Rate Maps(FIRMs). The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The NFHL data are derived from Flood Insurance Studies (FISs), previously published Flood Insurance Rate Maps (FIRMs), flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data where available. The FISs and FIRMs are published by the Federal Emergency Management Agency (FEMA). The specifications for the horizontal control of DFIRM data are consistent with those required for mapping at a scale of 1:12,000. The NFHL data contain layers in the Standard DFIRM datasets except for S_Label_Pt and S_Label_Ld. The NFHL is available as State or US Territory data sets. Each State or Territory data set consists of all DFIRMs and corresponding LOMRs available on the publication date of the data set.

The Historic Flood Map is a GIS layer showing the maximum extent of individual Recorded Flood Outlines from river, the sea and groundwater springs that meet a set criteria. It shows areas of land that have previously been subject to flooding in England. This excludes flooding from surface water, except in areas where it is impossible to determine whether the source is fluvial or surface water but the dominant source is fluvial.

The majority of records began in 1946 when predecessor bodies to the Environment Agency started collecting detailed information about flooding incidents, although we hold limited details about flooding incidents prior to this date.

If an area is not covered by the Historic Flood Map it does not mean that the area has never flooded, only that we do not currently have records of flooding in this area that meet the criteria for inclusion. It is also possible that the pattern of flooding in this area has changed and that this area would now flood or not flood under different circumstances. Outlines that don’t meet this criteria are stored in the Recorded Flood Outlines dataset.

The Historic Flood Map takes into account the presence of defences, structures, and other infrastructure where they existed at the time of flooding. It will include flood extents that may have been affected by overtopping, breaches or blockages.

Flooding is shown to the land and does not necessarily indicate that properties were flooded internally.

This collection is for datasets of flood depths, flood extents, high water marks, streamflow, damages recorded, aerial oblique photos, and related subjects. This includes both forecast and observed data. These were primarily obtained from national agencies such as NOAA (weather related), USGS (surface water related), FEMA (surface water and damage related), and Civil Air Patrol (aerial photos).

Note on November 2023 updates: due to numerous updates among the resources linked below, this collection has been updated to point to the most recent resources.

The Global Flood Hazard Frequency and Distribution is a 2.5 minute grid derived from a global listing of extreme flood events between 1985 and 2003 (poor or missing data in the early/mid 1990s) compiled by Dartmouth Flood Observatory and georeferenced to the nearest degree. The resultant flood frequency grid was then classified into 10 classes of approximately equal number of grid cells. The greater the grid cell value in the final data set, the higher the relative frequency of flood occurrence. This data set is the result of collaboration among the Columbia University Center for Hazards and Risk Research (CHRR) and Columbia University Center for International Earth Science Information Network (CIESIN).

The National Flood Hazard Layer (NFHL) data incorporates all Flood Insurance Rate Map (FIRM) databases published by the Federal Emergency Management Agency (FEMA), and any Letters of Map Revision (LOMRs) that have been issued against those databases since their publication date. It is updated on a monthly basis. The FIRM Database is the digital, geospatial version of the flood hazard information shown on the published paper FIRMs.The FIRM Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The FIRM Database is derived from Flood Insurance Studies (FISs), previously published FIRMs, flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by FEMA.The NFHL is available as State or US Territory data sets. Each State or Territory data set consists of all FIRM Databases and corresponding LOMRs available on the publication date of the data set.The specification for the horizontal control of FIRM Databases is consistent with those required for mapping at a scale of 1:12,000. This file is georeferenced to the Earth's surface using the Geographic Coordinate System (GCS) and North American Datum of 1983.For more information, visit https://msc.fema.gov/portal/home.

Abstract

This dataset and its metadata statement were supplied to the Bioregional Assessment Programme by a third party and are presented here as originally supplied.

Polygon data delineating modelled statistical flood extent with an Average Recurrence Interval (ARI) of 100 years. For historical/actual flood extents, refer to 'Historic_extent' layer. Also known as the 1 in 100 year flood layer, it is used, among other things, in the creation of 'Land Subject to Inundation' areas as used in Planning Scheme Zones. The 1 in 100 year data is not restricted. This data is part of a group of layers depicting a range of statistical ARI extents. Current layers include 5, 10, 20, 30, 50, 100, 200, 500, 1000 year intervals, each in a separate dataset. The layer called EXTENT_PMF represents areas of 'probable maximum flood' and is also part of this group. The data is statistically derived using hydrological models, historic flood extents and heights.

Purpose

Mainly used for municipal planning and risk assessment. The EXTENT_100Y_ARI layer is deemed the most appropriate to use for determining areas at risk of flooding. This layer directly inputs into the Land Subject to Inundation overlay. (LSIO)

Dataset History

Lineage: Primary

Positional Accuracy: Precision: 5m to 100m Initial data, flagged as 'modified = 20000101' varies in accuracy, and should be treated with caution, particularly at scales less than 1:25,000. Data with 'modified' values later than 20000101 are quite accurate and mostly sourced from flood studies. This data is suitable to use at township and parcel level. Reliability field provides clues to the accuracy, where a value of 1 is best and 3 is worst.

Attribute Accuracy: Attributes are verified and should be accurate. Overall reliability of the source material is indicated in RELIABILITY field, where 'HIGH' is good and 'LOW' is poor quality source information.

Logical Consistency: Attributes are consistent with other related layers e.g. flood height contours

Data Source: Flood data dates back to mid 1800s and historically has been predominantly located in DNRE Floodplain Management. Some data is located in Water Authorities.

Completeness: Floodplain Management Unit mapping conventions on definitions of flood mapping height data will be followed.

Additional Metadata: Recommend liaison with Floodplain Management Unit to clarify use of this layer

Refer to mapping reports for each major data capture effort to be kept at DNRE Floodplain Management Unit.

Dataset Citation

Victorian Department of Environment and Primary Industries (2014) Victoria - 1 in 100 Year Flood Extent. Bioregional Assessment Source Dataset. Viewed 05 October 2018, http://data.bioregionalassessments.gov.au/dataset/6e59ed35-3fde-48e3-8135-eb05263ce4aa.

This metadata record is for Approval for Access product AfA256.

Flood Risk Areas identify locations where there is believed to be significant flood risk. The EU Floods Directive refers to Flood Risk Areas as 'Areas of Potentially Significant Flood Risk' (APSFR).

Flood Risk Areas have been defined by the Environment Agency (main rivers and the sea) and Lead Local Flood Authorities (surface water). Other sources of flooding are not covered. This dataset includes Flood Risk Areas defined for both Cycle 1 (December 2011) and Cycle 2 (December 2018).

The criteria used to determine significance are explained in supporting guidance document supplied with this data.

Flood Risk Areas determine where Flood Hazard and Risk Maps and Flood Risk Management Plans must subsequently be produced to meet obligations under the EU Floods Directive.

INFORMATION WARNING

Flood Risk Areas are designed to meet the needs of the European Floods Directive. They are designed for broad planning purposes only and are not appropriate for any other type of flood mapping. Other flood mapping is available which is more appropriate to showing localised flood risk. Attribution statement: © Environment Agency copyright and/or database right 2019. All rights reserved.

Early event detection and response can significantly reduce the societal impact of floods. Currently, early warning systems rely on gauges, radar data, models and informal local sources. However, the scope and reliability of these systems are limited. Recently, the use of social media for detecting disasters has shown promising results, especially for earthquakes. Here, we present a new database for detecting floods in real time on a global scale using Twitter. The method was developed using 125 million tweets, from which we derived over 10.000 flood events in countries or their first administrative subdivisions across 176 countries in 12 languages in just over four years. Using strict parameters, validation shows that approximately 83% of the events were correctly detected. In countries where the first official language is included, our algorithm detected 70% of events in NatCatSERVICE disaster database at admin 1 level. Moreover, a large number of flood events not included in NatCatSERVICE are detected. All results are publicly available on www.globalfloodmonitor.org.

This dataset is an inventory of globally occurred Glacier Lake Outburst Floods (GLOFs). Our database encompasses data from 769 different sources including satellite and aerial images, reports from local authorities, scientific publications, news outlets, workshop proceedings, social media posts, and unpublished work.

Files: glofdatabase_V3.ods: Database spreadsheet (OpenOffice file) containing all reported GLOFs. Parameter_Readme.ods: Readme file describing all database parameters (i.e. columns in glofdatabase_V3.ods) and their units.

Our database is an ongoing project and we offer a web-based, interactive map that grants access to the most recent state of the database (http://glofs.geoecology.uni-potsdam.de). Users can also download all previous versions of the database from this interface.

The National Flood Hazard Layer (NFHL) is a geospatial database that contains current effective flood hazard data. FEMA provides the flood hazard data to support the National Flood Insurance Program. You can use the information to better understand your level of flood risk and type of flooding.The NFHL is made from effective flood maps and Letters of Map Change (LOMC) delivered to communities. NFHL digital data covers over 90 percent of the U.S. population. New and revised data is being added continuously. If you need information for areas not covered by the NFHL data, there may be other FEMA products which provide coverage for those areas.In the NFHL Viewer, you can use the address search or map navigation to locate an area of interest and the NFHL Print Tool to download and print a full Flood Insurance Rate Map (FIRM) or FIRMette (a smaller, printable version of a FIRM) where modernized data exists. Technical GIS users can also utilize a series of dedicated GIS web services that allow the NFHL database to be incorporated into websites and GIS applications. For more information on available services, go to the NFHL GIS Services User Guide.You can also use the address search on the FEMA Flood Map Service Center (MSC) to view the NFHL data or download a FIRMette. Using the “Search All Products” on the MSC, you can download the NFHL data for a County or State in a GIS file format. This data can be used in most GIS applications to perform spatial analyses and for integration into custom maps and reports. To do so, you will need GIS or mapping software that can read data in shapefile format.FEMA also offers a download of a KMZ (keyhole markup file zipped) file, which overlays the data in Google Earth™. For more information on using the data in Google Earth™, please see Using the National Flood Hazard Layer Web Map Service (WMS) in Google Earth™.

This is an update of the digital FIRM information in the state of Idaho. The FIRM is the basis for floodplain management, mitigation, and insurance activities for the National Flood Insurance Program (NFIP). Insurance applications include enforcement of the mandatory purchase requirement of the Flood Disaster Protection Act, which "... requires the purchase of flood insurance by property owners who are being assisted by Federal programs or by Federally supervised, regulated or insured agencies or institutions in the acquisition or improvement of land facilities located or to be located in identified areas having special flood hazards," Section 2 (b) (4) of the Flood Disaster Protection Act of 1973. In addition to the identification of Special Flood Hazard Areas (SFHAs), the risk zones shown on the FIRMs are the basis for the establishment of premium rates for flood coverage offered through the NFIP.This Database presents the flood risk information depicted on the FIRM in a digital format suitable for use in electronic mapping applications. This database has been created by digitizing data from georeferenced paper FIRM maps in the Idaho counties specified by this project. This data should be used as a reference layer, not as an authoritative source.The Flood Insurance Rate Map (FIRM) depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event (A or AE) and the 0.2-percent-annual- chance flood event (X). The FIRM data can be derived from Flood Insurance Studies (FISs) and previously published Flood Insurance Rate Maps (FIRMs). The FISs and FIRMs are published by the Federal Emergency Management Agency (FEMA). This database has been created by digitizing data from georeferenced paper FIRM maps and adding information from FIS where available. All FIRMs were georeferenced at a 1:4000 scale or finer. This data should be used as a reference layer, not as an authoritative source. Section 11 of FEMA's "Flood Insurance Rate Map (FIRM) Database Technical Reference: Preparing Flood Insurance Rate Map Databases (Nov. 2022)" document contains a detailed description of each attribute code and a reference to other relevant information.https://www.fema.gov/flood-maps/guidance-reports/guidelines-standards/technical-references-flood-risk-analysis-and-mappinghttps://www.fema.gov/sites/default/files/documents/fema_firm-database-technical-reference_112022.pdf

Flood risk areas display the extent of known historical flood events as well as areas that have a probability of flooding as determined from historical records. The polygon data includes the description of the flood event, the typical causes of the flood and any associated place name keys. The line data indicates the limits of the flood risk mapping information and the 2008 and 2018 flood data. Flood extents for the 2008 and 2018 Lower Saint John River floods are included.

The Indian Observational Flood Events Database (INDOFLOODS) is a unique flood event database designed to advance flood research and management in India. This database integrates long-term station discharge observations with official flooding thresholds to provide detailed historical flood event information.

Key hydrological data include:

1. start and end date and time of flooding
2. peak flood water level (with corresponding dates)
3. peak discharge (with corresponding dates)
4. flood volume
5. event duration
6. time to peak, and
7. recession time.

In addition to flooding details, the database includes metadata such as upstream catchment area, geographic coordinates, and river and tributary names. It is further enhanced with extensive:

1. geomorphological,
2. climatological,
3. event-scale precipitation,
4. land cover,
5. soil,
6. lithology,
7. and anthropogenic characteristics derived at the catchment scale.

Catchment boundary shapefiles are also provided to facilitate users' extension of the database as per their needs.

Contents of the Database:

1. Variables description
2. Metadata
3. Flood events
4. Catchment characteristics
5. Precipitation variables
6. Catchment boundary shapefiles

Please refer to the Variables description file (variables_description_indofloods.pdf) for a complete list of variables and their descriptions.

For detailed information about this database and its development, please refer to the original research article published in the Bulletin of the American Meteorological Society (BAMS):

Kuntla, S. K., & Saharia, M. (2025). INDOFLOODS: A comprehensive database for flood events in India enhanced with catchment attributes. Bulletin of the American Meteorological Society, 106(2), E333–E343. https://doi.org/10.1175/BAMS-D-24-0008.1

Disclaimer

The INDOFLOODS database on this web portal is openly accessible for academic and research purposes. While every effort has been made to ensure the accuracy of the data, the authors do not assume responsibility for errors, omissions, or misuse. Users must cite the INDOFLOODS database and the associated research article published in the Bulletin of the American Meteorological Society (BAMS) when utilizing this data and acknowledge that all interpretations and conclusions are their own. We also encourage users to cite or acknowledge the original sources of catchment variables per their respective data usage policies.

To Be Cited:

1. Kuntla, S. K., & Saharia, M. (2025). INDOFLOODS: A comprehensive database for flood events in India enhanced with catchment attributes. Bulletin of the American Meteorological Society, 106(2), E333–E343. https://doi.org/10.1175/BAMS-D-24-0008.1
2. Kuntla, S. K., & Saharia, M. (2025). INDOFLOODS: A Comprehensive Database for Flood Events in India Enhanced with Catchment Attributes [Data set]. Zenodo. https://doi.org/10.5281/zenodo.14584654
   
   

Additional Information:

The INDOFLOODS database doesn't contain data for the Ganga and Brahmaputra basins. Interested users may contact the authors to request the complete dataset, subject to a reasonable request.

Contacts:

Dr. Sai Kiran Kuntla: kuntlasaikiran@gmail.com

Dr. Manbendra Saharia: msaharia@iitd.ac.in

This hosted feature layer has been published in RI State Plane Feet NAD 83.Statewide flood hazard areas compiled from county-based Digital Flood Insurance Rate Map (DFIRM) databases for Rhode Island. The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. TheDFIRM Database is derived from Flood Insurance Studies (FISs), previously published Flood Insurance Rate Maps (FIRMs), flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by the Federal Emergency Management Agency (FEMA), and in this case redistributed by the Rhode Island Geographic Information System (RIGIS) at the request of the Rhode Island Emergency Management Agency.This dataset provides the user with information on the flood risk hazard zones throughout the state of Rhode Island. Note: the above summary is a slightly modified version adapted from source metadata records provided by FEMA. To provide the user with information on the statewide flood risk based on information provided by the Federal Emergency Management Agency (FEMA) in the DFIRM databases created specifically for the five counties of Rhode Island (Bristol, Kent, Newport, Providence, and Washington). This dataset provides information on the likelihood that a flood may occur at a given location in the state. The files and information used to create this dataset were originally provided to the Rhode Island Emergency Management Agency (RIEMA) by FEMA.This information was in the form of DFIRM databases for each of the five RI counties. This information was then redistributed by RIGIS at the request of RIEMA. The information provided by this data is only a subset of the information available in the original DFIRM databases located on the RIGIS website. For a specific county's complete DFIRM database, please visit the RIGIS website and download the appropriate DFIRM database. This metadata record is specific to this dataset and only contains information relevant to this dataset as provided by FEMA the original DFIRM metadata records. These can be found and referenced in the /DOCUMENT folder that is downloaded as part of a DFIRM package for a specific Rhode Island county. Another valuable source of documentation is FEMA's "Guidelines and Specifications for Flood Hazard Mapping Partners". It is currently available online at https://www.fema.gov/guidelines-and-standards-flood-risk-analysis-and-mapping. The Guide offers a tremendous amount of information regarding how DFIRM data are created, and detailed information about the individual files that constitute a DFIRM database.

The entire Vermont extent of the National Flood Hazard Layer (NFHL) as acquired 12/15/15 from the FEMA Map Service Center msc.fema.gov upon publication 12/2/2015 and converted to VSP.The FEMA DFIRM NFHL database compiles all available officially-digitized Digital Flood Insurance Rate Maps. This extract from the FEMA Map Service Center includes all of such data in Vermont including counties and a few municipalities. This data includes the most recent map update for Bennington County effective 12/2/2015.DFIRM - Letter of Map Revision (LOMR) DFIRM X-Sections DFIRM Floodways Special Flood Hazard Areas (All Available)

The Flood Map for Planning Service includes several layers of information. This includes the Flood Zones data which shows the extent of land at present day risk of flooding from rivers and the sea, ignoring the benefits of defences, for the following scenarios:

• Flood Zone 1 – Land having a less than 0.1% (1 in 1000) annual probability of flooding. • Flood Zone 2 – Land having between 0.1% - 1% (1 in 100 to 1 in 1000) annual probability of flooding from rivers or between 0.1% - 0.5% (1 in 200 to 1 in 1000) annual probability of flooding from the sea, and accepted recorded flood outlines . • Flood Zone 3 – Areas shown to be at a 1% (1 in 100) or greater annual probability of flooding from rivers or 0.5% (1 in 200) or greater annual probability of flooding from the sea.

Flood Zone 1 is not shown in this dataset, but covers all areas not contained within Flood Zones 2 and 3. Local Planning Authorities (LPAs) use the Flood Zones to determine if they must consult the Environment Agency on planning applications. They are also used to determine if development is incompatible and whether development is subject to the exception test. The Flood Zones are one of several flood risk datasets used to determine the need for planning applications to be supported by a Flood Risk Assessment (FRA) and subject to the sequential test.

The Flood Zones are a composite dataset including national and local modelled data, and information from past floods.

The Flood Zones are designed to only give an indication of flood risk to an area of land and are not suitable for showing whether an individual property is at risk of flooding. This is because we cannot know all the details about each property.

Users of these datasets should always check they are suitable for the intended use

The S_FIRM_Pan table contains information about the FIRM panel area. A spatial file with location information also corresponds with this data table. The spatial entities representing FIRM panels are polygons. The polygon for the FIRM panel corresponds to the panel neatlines. Panel boundaries are generally derived from USGS DOQQ boundaries. As a result, the panels are generally rectangular. In situations where a portion of a panel lies outside the jurisdiction being mapped, the user must refer to the S_Pol_Ar table to determine the portion of the panel area where the FIRM Database shows the effective flood hazard data for the mapped jurisdiction. This information is needed for the FIRM Panel Index and the following tables in the FIS report: Listing of NFIP Jurisdictions, Levees, Incorporated Letters of Map Change, and Coastal Barrier Resources System Information. The spatial entities representing FIRM panels are polygons. The polygon for the FIRM panel corresponds to the panel neatlines. Panel boundaries are generally derived from USGS DOQQ boundaries. As a result, the panels are generally rectangular. FIRM panels must not overlap or have gaps within a study. In situations where a portion of a panel lies outside the jurisdiction being mapped, the user must refer to the S_Pol_Ar table to determine the portion of the panel area where the FIRM Database shows the effective flood hazard data for the mapped jurisdiction. This information is needed for the FIRM Panel Index and the following tables in the FIS report: Listing of NFIP Jurisdictions, Levees, Incorporated Letters of Map Change, and Coastal Barrier Resources System Information.Flood hazard and supporting data are developed using specifications for horizontal control consistent with 1:12,000–scale mapping. If you plan to display maps from the National Flood Hazard Layer with other map data for official purposes, ensure that the other information meets FEMA’s standards for map accuracy. The minimum horizontal positional accuracy for base map hydrographic and transportation features used with the NFHL is the NSSDA radial accuracy of 38 feet. USGS imagery and map services that meet this standard can be found by visiting the Knowledge Sharing Site (KSS) for Base Map Standards (420). Other base map standards can be found at https://riskmapportal.msc.fema.gov/kss/MapChanges/default.aspx. You will need a username and password to access this information.The NFHL data are from FEMA’s Flood Insurance Rate Map (FIRM) databases. New data are added continually. The NFHL also contains map changes to FIRM data made by Letters of Map Revision (LOMRs). The NFHL is stored in North American Datum of 1983, Geodetic Reference System 80 coordinate system, though many of the NFHL GIS web services support the Web Mercator Sphere projection commonly used in web mapping applications.