These data are damage and loss estimates obtained from various Hazus outputs covering all census tracts in 17 counties in and around the San Francisco Bay region in California, for the HayWired earthquake scenario and sixteen M5 or greater aftershocks occurring in the region during the two years following the HayWired mainshock. The HayWired earthquake scenario is a magnitude 7.0 earthquake hypothesized to occur on the Hayward Fault on April 18, 2018, with an epicenter in the city of Oakland, CA. The estimates contained in this dataset are a subset of the many results products generated by FEMA's Hazus-MH 2.1 application, and reflect potential damage due to the HayWired earthquake scenario mainshock and its aftershocks. The data included in this data release were obtained directly from Hazus or by using Hazus outputs to create derivative results. Products include: Hazus building inventory replacement value estimates, Hazus building contents value estimates, estimates of injuries and fatalities (mainshock and three aftershocks), estimates of displaced households and population requiring short-term shelter (mainshock and three aftershocks), value of building damage estimates (mainshock and sum of mainshock and 16 M5 or greater aftershocks), damage ratio estimates (mainshock and sum of mainshock and 16 M5 or greater aftershocks), estimates of damaged square footage by damage state (mainshock), and direct economic losses (mainshock and 16 M5 or greater aftershocks). For additional information on each dataset, please refer to the metadata accompanying the specific dataset of interest. These tab-delimited .TXT datasets were developed and intended for use in standalone spreadsheet or database applications (such as Microsoft Excel or Access). Please note that some data included in this data release are not optimized for use in GIS applications (such as ESRI's ArcGIS software suite) as-is--census tracts are repeated (the data are not "one-to-one"), so not all information belonging to a tract would necessarily be associated with a single record. Separate preparation is needed in a standalone spreadsheet or database application like Microsoft Excel or Microsoft Access before using these data in a GIS. These data support the following publication: Seligson, H.A., Wein, A.M., and Jones, J.L., 2018, HayWired scenario--Hazus analyses of the mainshock and aftershocks, chap. J of Detweiler, S.T., and Wein, A.M., eds., The HayWired earthquake scenario--Earthquake implications: U.S. Geological Survey Scientific Investigations Report 2017-5013-I-Q, 41 p., https://doi.org/10.3133/sir20175013.

The Location Facility feature class is one of 20 essential (critical) facility feature classes developed for and maintained by the Des Moines Area Regional GIS for the purpose of performing hazard risk assessments and loss estimation using GIS. The data is also appropriately used in preparing hazard mitigation plans, emergency response plans, and general maps. The data is not compatible for direct use in HAZUS-MH (www.fema.gov/hazus) but may be extracted and converted for use in HAZUS-MH using the Comprehensive Data Management System (CDMS) tools. Used in HAZUS-MH, the data provides a basis for estimating the damage to and resulting loss of functionality of essential facilities in a given flood, hurricane, and/or earthquake scenario. Thereby, the HAZUS-MH user can model the economic and physical impacts of a flood, hurricane, and/or earthquake scenario.

Tropical storms, hurricanes, and tsunamis create waves that flood low-lying coastal areas. The National Flood Insurance Program (NFIP) produces flood insurance rate maps (FIRMs) that depict flood risk zones referred to as Special Flood Hazard Areas (SFHA) based modeling 1%-annual-chance flood event also referred to as a 100-year flood. The purpose of the FIRM is twofold: (1) to provide the basis for application of regulatory standards and (2) to provide the basis for insurance rating.

SFHAs identify areas at risk from infrequent but severe storm-induced wave events and riverine flood events that are based upon historical record. By law (44 Code of Federal Regulations [CFR] 60.3), FEMA can only map flood risk that will be utilized for land use regulation or insurance rating based on historical data, therefore, future conditions with sea level rise and other impacts of climate change are not considered in FIRMs. It is important to note that FEMA can produce Flood Insurance Rate Maps that include future condition floodplains, but these would be considered “awareness” zones and not to be used for regulatory of insurance rating purposes.

The State of Hawai‘i 2018 Hazard Mitigation Plan incorporated the results of modeling and an assessment of vulnerability to coastal flooding from storm-induced wave events with sea level rise (Tetra Tech Inc., 2018). The 1% annual-chance-coastal flood zone with sea level rise (1%CFZ) was modeled to estimate coastal flood extents and wave heights for wave-generating events with sea level rise. Modeling was conducted by Sobis Inc. under State of Hawaiʻi Department of Land and Natural Resources Contract No: 64064. The 1%CFZ with 3.2 feet of sea level rise was utilized to assess vulnerability to coastal event-based flooding in mid to - late century.

The 1%CFZ with sea level rise would greatly expand the impacts from a 100-year flood event meaning that more coastal land area will be exposed to damaging waves. For example, over 120 critical infrastructure facilities in the City and County of Honolulu, including water, waste, and wastewater systems and communication and energy facilities would be impacted in the 1%CFZ with 3.2 feet of sea level rise (Tetra Tech Inc., 2018). This is double the number of facilities in the SFHA which includes the impacts of riverine flooding.

A simplified version of the Wave Height Analysis for Flood Insurance Studies (WHAFIS) extension (FEMA, 2019b) included in Hazus-MH, was used to create the 1% annual chance coastal floodplain. Hazus is a nationally applicable standardized methodology that contains models for estimating potential losses from earthquakes, floods, tsunamis, and hurricanes (FEMA, 2019a).

The current 1%-annual-chance stillwater elevations were collected using the most current flood insurance studies (FIS) for each island conducted by FEMA (FEMA, 2004, 2010, 2014, 2015). The FIS calculates the 1%-annual-chance stillwater elevation, wave setup, and wave run-up (called maximum wave crest) at regularly-spaced transects around the islands based on historical data. Modeling for the 1%CFZ used the NOAA 3-meter digital elevation model (DEM) which incorporates LiDAR data sets collected between 2003 and 2007 from NOAA, FEMA, the State of Hawaiʻi Emergency Management Agency, and the USACE (NOAA National Centers for Environmental Information, 2017).

Before Hazus was run for future conditions, it was run for the current conditions and compared to the FEMA regulatory floodplain to determine model accuracy. This also helped determine the stillwater elevation for the large gaps between some transects in the FIS. Hazus was run at 0.5-foot stillwater level intervals and the results were compared to the existing Flood Insurance Rate Map (FIRM). The interval of 0.5-feet was chosen as a small enough step to result in a near approximation of the FIRM while not being too impractically narrow to require the testing of dozens of input elevations. The elevation which matched up

Splitgraph serves as an HTTP API that lets you run SQL queries directly on this data to power Web applications. For example:

See the Splitgraph documentation for more information.

The values in this dataset include the percent of damaged buildings, displaced people, and people that would require shelter for the 0.1% and 0.2% annual exceedance probability (AEP) coastal flood along the northern Gulf of Mexico coast (Mississippi, Alabama, and the Florida panhandle). The data includes values for sea level rise scenarios of low (l, 0.2 m), intermediate-low (il, 0.5 m), intermediate-high (ih, 1.2 m), and high (2.0 m). The datasets were produced by the FEMA HAZUS (FEMA, 2013) software using storm surge flooding results from Bilskie et al. (2019).

Bilskie, M. V., S. C. Hagen, and J. L. Irish (2019), Development of Return Period Stillwater Floodplains for the Northern Gulf of Mexico under the Coastal Dynamics of Sea Level Rise, J. Waterway, Port, Coastal, Ocean Eng., 145(2), 04018043. doi:10.1061/(ASCE)WW.1943-5460.0000468.

Federal Emergency Management Agency (FEMA) (2013), Hazus-MH Flood Model User Manual,https://www.fema.gov/media-library-data/20130726-1820-25045-8814/hzmh2_1_fl_um.pdf.

The Police Station Facility feature class is one of 20 essential (critical) facility feature classes developed for and maintained by the Des Moines Area Regional GIS for the purpose of performing hazard risk assessments and loss estimation using GIS. The data is also appropriately used in preparing hazard mitigation plans, emergency response plans, and general maps. The data is not compatible for direct use in HAZUS-MH (www.fema.gov/hazus) but may be extracted and converted for use in HAZUS-MH using the Comprehensive Data Management System (CDMS) tools. Used in HAZUS-MH, the data provides a basis for estimating the damage to and resulting loss of functionality of essential facilities in a given flood, hurricane, and/or earthquake scenario. Thereby, the HAZUS-MH user can model the economic and physical impacts of a flood, hurricane, and/or earthquake scenario.

This dataset was developed to communicate the socio-economic consequences of flooding within the 1% and 0.2% Annual Exceedance Probability Floodplain (AEP) under 4 sea-level rise (SLR) scenarios. Assessment methods primarily used HAZUS-MH software, a GIS-based modeling tool developed by the Federal Emergency Management Agency, to estimate the physical, economic, and social impacts of natural disasters. The dataset includes point files describing impacts to essential facilities and wastewater treatment facilities, line files highlighting road exposure to storm surge, and polygon files summarizing displayed people, shelter needs, and the economic impacts of storm surge flooding on buildings, vehicles, roads, bridges, and crops. The SLR scenarios include 0.2 m, 0.5 m, 1.2 m, and 2.0 m for the year 2100.

[Metadata] Tropical storms, hurricanes, and tsunamis create waves that flood low-lying coastal areas. The National Flood Insurance Program (NFIP) produces flood insurance rate maps (FIRMs) that depict flood risk zones referred to as Special Flood Hazard Areas (SFHA) based modeling 1%-annual-chance flood event also referred to as a 100-year flood. The purpose of the FIRM is twofold: (1) to provide the basis for application of regulatory standards and (2) to provide the basis for insurance rating.SFHAs identify areas at risk from infrequent but severe storm-induced wave events and riverine flood events that are based upon historical record. By law (44 Code of Federal Regulations [CFR] 60.3), FEMA can only map flood risk that will be utilized for land use regulation or insurance rating based on historical data, therefore, future conditions with sea level rise and other impacts of climate change are not considered in FIRMs. It is important to note that FEMA can produce Flood Insurance Rate Maps that include future condition floodplains, but these would be considered “awareness” zones and not to be used for regulatory of insurance rating purposes.The State of Hawai‘i 2018 Hazard Mitigation Plan incorporated the results of modeling and an assessment of vulnerability to coastal flooding from storm-induced wave events with sea level rise (Tetra Tech Inc., 2018). The 1% annual-chance-coastal flood zone with sea level rise (1%CFZ) was modeled to estimate coastal flood extents and wave heights for wave-generating events with sea level rise. Modeling was conducted by Sobis Inc. under State of Hawaiʻi Department of Land and Natural Resources Contract No: 64064. The 1%CFZ with 3.2 feet of sea level rise was utilized to assess vulnerability to coastal event-based flooding in mid to - late century.The 1%CFZ with sea level rise would greatly expand the impacts from a 100-year flood event meaning that more coastal land area will be exposed to damaging waves. For example, over 120 critical infrastructure facilities in the City and County of Honolulu, including water, waste, and wastewater systems and communication and energy facilities would be impacted in the 1%CFZ with 3.2 feet of sea level rise (Tetra Tech Inc., 2018). This is double the number of facilities in the SFHA which includes the impacts of riverine flooding.A simplified version of the Wave Height Analysis for Flood Insurance Studies (WHAFIS) extension (FEMA, 2019b) included in Hazus-MH, was used to create the 1% annual chance coastal floodplain. Hazus is a nationally applicable standardized methodology that contains models for estimating potential losses from earthquakes, floods, tsunamis, and hurricanes (FEMA, 2019a). The current 1%-annual-chance stillwater elevations were collected using the most current flood insurance studies (FIS) for each island conducted by FEMA (FEMA, 2004, 2010, 2014, 2015). The FIS calculates the 1%-annual-chance stillwater elevation, wave setup, and wave run-up (called maximum wave crest) at regularly-spaced transects around the islands based on historical data. Modeling for the 1%CFZ used the NOAA 3-meter digital elevation model (DEM) which incorporates LiDAR data sets collected between 2003 and 2007 from NOAA, FEMA, the State of Hawaiʻi Emergency Management Agency, and the USACE (NOAA National Centers for Environmental Information, 2017).Before Hazus was run for future conditions, it was run for the current conditions and compared to the FEMA regulatory floodplain to determine model accuracy. This also helped determine the stillwater elevation for the large gaps between some transects in the FIS. Hazus was run at 0.5-foot stillwater level intervals and the results were compared to the existing Flood Insurance Rate Map (FIRM). The interval of 0.5-feet was chosen as a small enough step to result in a near approximation of the FIRM while not being too impractically narrow to require the testing of dozens of input elevations. The elevation which matched up best was used as the current base flood elevation.Key steps in modeling the projected 1%CFZ with sea level rise include: (1) generating a contiguous (no gaps along the shoreline) and present-day 1%-annual-chance stillwater elevation based on the most recent FIS, (2) elevating the present-day 1%-annual-chance stillwater elevation by adding projected sea level rise heights, and (3) modeling the projected 1%-annual-chance coastal flood with sea level rise in HAZUS using the 1%-annual-chance wave setup and run-up from the FIS. The 1%CFZ extent and depth was generated using the HAZUS 3.2 coastal flood risk assessment model, 3-meter DEM, the FIS for each island, and the IPCC AR5 upper sea level projection for RCP 8.5 scenario for 0.6 feet, 1.0 feet, 2.0 feet, and 3.2 feet of sea level rise above MHHW (IPCC, 2014). The HAZUS output includes the estimated spatial extent of coastal flooding as well as an estimated flood depth map grid for the four sea level rise projections.Using the current floodplain generated with Hazus, the projected 1%-annual-chance stillwater elevation was generated using the four sea level rise projections. This stillwater elevation with sea level rise was used as a basis for modeling. The projected 1%-annual coastal flood with sea level rise was modeled in Hazus using the current 1%-annual-chance wave setup and run-up from the FIS and the projected 1%-annual-chance stillwater elevation with sea level rise. Statewide GIS Program staff extracted individual island layers for ease of downloading. A statewide layer is also available as a REST service, and is available for download from the Statewide GIS geoportal at https://geoportal.hawaii.gov/, or at the Program's legacy download site at https://planning.hawaii.gov/gis/download-gis-data-expanded/#009. For additional information, please refer to summary metadata at https://files.hawaii.gov/dbedt/op/gis/data/coastal_flood_zones_summary.pdf or contact Hawaii Statewide GIS Program, Office of Planning and Sustainable Development, State of Hawaii; PO Box 2359, Honolulu, Hi. 96804; (808) 587-2846; email: gis@hawaii.gov.

[Metadata] Tropical storms, hurricanes, and tsunamis create waves that flood low-lying coastal areas. The National Flood Insurance Program (NFIP) produces flood insurance rate maps (FIRMs) that depict flood risk zones referred to as Special Flood Hazard Areas (SFHA) based modeling 1%-annual-chance flood event also referred to as a 100-year flood. The purpose of the FIRM is twofold: (1) to provide the basis for application of regulatory standards and (2) to provide the basis for insurance rating.SFHAs identify areas at risk from infrequent but severe storm-induced wave events and riverine flood events that are based upon historical record. By law (44 Code of Federal Regulations [CFR] 60.3), FEMA can only map flood risk that will be utilized for land use regulation or insurance rating based on historical data, therefore, future conditions with sea level rise and other impacts of climate change are not considered in FIRMs. It is important to note that FEMA can produce Flood Insurance Rate Maps that include future condition floodplains, but these would be considered “awareness” zones and not to be used for regulatory of insurance rating purposes.The State of Hawai‘i 2018 Hazard Mitigation Plan incorporated the results of modeling and an assessment of vulnerability to coastal flooding from storm-induced wave events with sea level rise (Tetra Tech Inc., 2018). The 1% annual-chance-coastal flood zone with sea level rise (1%CFZ) was modeled to estimate coastal flood extents and wave heights for wave-generating events with sea level rise. Modeling was conducted by Sobis Inc. under State of Hawaiʻi Department of Land and Natural Resources Contract No: 64064. The 1%CFZ with 3.2 feet of sea level rise was utilized to assess vulnerability to coastal event-based flooding in mid to - late century.The 1%CFZ with sea level rise would greatly expand the impacts from a 100-year flood event meaning that more coastal land area will be exposed to damaging waves. For example, over 120 critical infrastructure facilities in the City and County of Honolulu, including water, waste, and wastewater systems and communication and energy facilities would be impacted in the 1%CFZ with 3.2 feet of sea level rise (Tetra Tech Inc., 2018). This is double the number of facilities in the SFHA which includes the impacts of riverine flooding.A simplified version of the Wave Height Analysis for Flood Insurance Studies (WHAFIS) extension (FEMA, 2019b) included in Hazus-MH, was used to create the 1% annual chance coastal floodplain. Hazus is a nationally applicable standardized methodology that contains models for estimating potential losses from earthquakes, floods, tsunamis, and hurricanes (FEMA, 2019a). The current 1%-annual-chance stillwater elevations were collected using the most current flood insurance studies (FIS) for each island conducted by FEMA (FEMA, 2004, 2010, 2014, 2015). The FIS calculates the 1%-annual-chance stillwater elevation, wave setup, and wave run-up (called maximum wave crest) at regularly-spaced transects around the islands based on historical data. Modeling for the 1%CFZ used the NOAA 3-meter digital elevation model (DEM) which incorporates LiDAR data sets collected between 2003 and 2007 from NOAA, FEMA, the State of Hawaiʻi Emergency Management Agency, and the USACE (NOAA National Centers for Environmental Information, 2017).Before Hazus was run for future conditions, it was run for the current conditions and compared to the FEMA regulatory floodplain to determine model accuracy. This also helped determine the stillwater elevation for the large gaps between some transects in the FIS. Hazus was run at 0.5-foot stillwater level intervals and the results were compared to the existing Flood Insurance Rate Map (FIRM). The interval of 0.5-feet was chosen as a small enough step to result in a near approximation of the FIRM while not being too impractically narrow to require the testing of dozens of input elevations. The elevation which matched up best was used as the current base flood elevation.Key steps in modeling the projected 1%CFZ with sea level rise include: (1) generating a contiguous (no gaps along the shoreline) and present-day 1%-annual-chance stillwater elevation based on the most recent FIS, (2) elevating the present-day 1%-annual-chance stillwater elevation by adding projected sea level rise heights, and (3) modeling the projected 1%-annual-chance coastal flood with sea level rise in HAZUS using the 1%-annual-chance wave setup and run-up from the FIS. The 1%CFZ extent and depth was generated using the HAZUS 3.2 coastal flood risk assessment model, 3-meter DEM, the FIS for each island, and the IPCC AR5 upper sea level projection for RCP 8.5 scenario for 0.6 feet, 1.0 feet, 2.0 feet, and 3.2 feet of sea level rise above MHHW (IPCC, 2014). The HAZUS output includes the estimated spatial extent of coastal flooding as well as an estimated flood depth map grid for the four sea level rise projections.Using the current floodplain generated with Hazus, the projected 1%-annual-chance stillwater elevation was generated using the four sea level rise projections. This stillwater elevation with sea level rise was used as a basis for modeling. The projected 1%-annual coastal flood with sea level rise was modeled in Hazus using the current 1%-annual-chance wave setup and run-up from the FIS and the projected 1%-annual-chance stillwater elevation with sea level rise. For additional information, please refer to summary metadata at https://files.hawaii.gov/dbedt/op/gis/data/coastal_flood_zones_summary.pdf or contact Hawaii Statewide GIS Program, Office of Planning and Sustainable Development, State of Hawaii; PO Box 2359, Honolulu, Hi. 96804; (808) 587-2846; email: gis@hawaii.gov.

[Metadata] Tropical storms, hurricanes, and tsunamis create waves that flood low-lying coastal areas. The National Flood Insurance Program (NFIP) produces flood insurance rate maps (FIRMs) that depict flood risk zones referred to as Special Flood Hazard Areas (SFHA) based modeling 1%-annual-chance flood event also referred to as a 100-year flood. The purpose of the FIRM is twofold: (1) to provide the basis for application of regulatory standards and (2) to provide the basis for insurance rating.SFHAs identify areas at risk from infrequent but severe storm-induced wave events and riverine flood events that are based upon historical record. By law (44 Code of Federal Regulations [CFR] 60.3), FEMA can only map flood risk that will be utilized for land use regulation or insurance rating based on historical data, therefore, future conditions with sea level rise and other impacts of climate change are not considered in FIRMs. It is important to note that FEMA can produce Flood Insurance Rate Maps that include future condition floodplains, but these would be considered “awareness” zones and not to be used for regulatory of insurance rating purposes.The State of Hawai‘i 2018 Hazard Mitigation Plan incorporated the results of modeling and an assessment of vulnerability to coastal flooding from storm-induced wave events with sea level rise (Tetra Tech Inc., 2018). The 1% annual-chance-coastal flood zone with sea level rise (1%CFZ) was modeled to estimate coastal flood extents and wave heights for wave-generating events with sea level rise. Modeling was conducted by Sobis Inc. under State of Hawaiʻi Department of Land and Natural Resources Contract No: 64064. The 1%CFZ with 3.2 feet of sea level rise was utilized to assess vulnerability to coastal event-based flooding in mid to - late century.The 1%CFZ with sea level rise would greatly expand the impacts from a 100-year flood event meaning that more coastal land area will be exposed to damaging waves. For example, over 120 critical infrastructure facilities in the City and County of Honolulu, including water, waste, and wastewater systems and communication and energy facilities would be impacted in the 1%CFZ with 3.2 feet of sea level rise (Tetra Tech Inc., 2018). This is double the number of facilities in the SFHA which includes the impacts of riverine flooding.A simplified version of the Wave Height Analysis for Flood Insurance Studies (WHAFIS) extension (FEMA, 2019b) included in Hazus-MH, was used to create the 1% annual chance coastal floodplain. Hazus is a nationally applicable standardized methodology that contains models for estimating potential losses from earthquakes, floods, tsunamis, and hurricanes (FEMA, 2019a). The current 1%-annual-chance stillwater elevations were collected using the most current flood insurance studies (FIS) for each island conducted by FEMA (FEMA, 2004, 2010, 2014, 2015). The FIS calculates the 1%-annual-chance stillwater elevation, wave setup, and wave run-up (called maximum wave crest) at regularly-spaced transects around the islands based on historical data. Modeling for the 1%CFZ used the NOAA 3-meter digital elevation model (DEM) which incorporates LiDAR data sets collected between 2003 and 2007 from NOAA, FEMA, the State of Hawaiʻi Emergency Management Agency, and the USACE (NOAA National Centers for Environmental Information, 2017).Before Hazus was run for future conditions, it was run for the current conditions and compared to the FEMA regulatory floodplain to determine model accuracy. This also helped determine the stillwater elevation for the large gaps between some transects in the FIS. Hazus was run at 0.5-foot stillwater level intervals and the results were compared to the existing Flood Insurance Rate Map (FIRM). The interval of 0.5-feet was chosen as a small enough step to result in a near approximation of the FIRM while not being too impractically narrow to require the testing of dozens of input elevations. The elevation which matched up best was used as the current base flood elevation.Key steps in modeling the projected 1%CFZ with sea level rise include: (1) generating a contiguous (no gaps along the shoreline) and present-day 1%-annual-chance stillwater elevation based on the most recent FIS, (2) elevating the present-day 1%-annual-chance stillwater elevation by adding projected sea level rise heights, and (3) modeling the projected 1%-annual-chance coastal flood with sea level rise in HAZUS using the 1%-annual-chance wave setup and run-up from the FIS. The 1%CFZ extent and depth was generated using the HAZUS 3.2 coastal flood risk assessment model, 3-meter DEM, the FIS for each island, and the IPCC AR5 upper sea level projection for RCP 8.5 scenario for 0.6 feet, 1.0 feet, 2.0 feet, and 3.2 feet of sea level rise above MHHW (IPCC, 2014). The HAZUS output includes the estimated spatial extent of coastal flooding as well as an estimated flood depth map grid for the four sea level rise projections.Using the current floodplain generated with Hazus, the projected 1%-annual-chance stillwater elevation was generated using the four sea level rise projections. This stillwater elevation with sea level rise was used as a basis for modeling. The projected 1%-annual coastal flood with sea level rise was modeled in Hazus using the current 1%-annual-chance wave setup and run-up from the FIS and the projected 1%-annual-chance stillwater elevation with sea level rise. Statewide GIS Program staff extracted individual island layers for ease of downloading. A statewide layer is also available as a REST service, and is available for download from the Statewide GIS geoportal at https://geoportal.hawaii.gov/, or at the Program's legacy download site at https://planning.hawaii.gov/gis/download-gis-data-expanded/#009. For additional information, please refer to summary metadata at https://files.hawaii.gov/dbedt/op/gis/data/coastal_flood_zones_summary.pdf or contact Hawaii Statewide GIS Program, Office of Planning and Sustainable Development, State of Hawaii; PO Box 2359, Honolulu, Hi. 96804; (808) 587-2846; email: gis@hawaii.gov.

[Metadata] Tropical storms, hurricanes, and tsunamis create waves that flood low-lying coastal areas. The National Flood Insurance Program (NFIP) produces flood insurance rate maps (FIRMs) that depict flood risk zones referred to as Special Flood Hazard Areas (SFHA) based modeling 1%-annual-chance flood event also referred to as a 100-year flood. The purpose of the FIRM is twofold: (1) to provide the basis for application of regulatory standards and (2) to provide the basis for insurance rating.SFHAs identify areas at risk from infrequent but severe storm-induced wave events and riverine flood events that are based upon historical record. By law (44 Code of Federal Regulations [CFR] 60.3), FEMA can only map flood risk that will be utilized for land use regulation or insurance rating based on historical data, therefore, future conditions with sea level rise and other impacts of climate change are not considered in FIRMs. It is important to note that FEMA can produce Flood Insurance Rate Maps that include future condition floodplains, but these would be considered “awareness” zones and not to be used for regulatory of insurance rating purposes.The State of Hawai‘i 2018 Hazard Mitigation Plan incorporated the results of modeling and an assessment of vulnerability to coastal flooding from storm-induced wave events with sea level rise (Tetra Tech Inc., 2018). The 1% annual-chance-coastal flood zone with sea level rise (1%CFZ) was modeled to estimate coastal flood extents and wave heights for wave-generating events with sea level rise. Modeling was conducted by Sobis Inc. under State of Hawaiʻi Department of Land and Natural Resources Contract No: 64064. The 1%CFZ with 3.2 feet of sea level rise was utilized to assess vulnerability to coastal event-based flooding in mid to - late century.The 1%CFZ with sea level rise would greatly expand the impacts from a 100-year flood event meaning that more coastal land area will be exposed to damaging waves. For example, over 120 critical infrastructure facilities in the City and County of Honolulu, including water, waste, and wastewater systems and communication and energy facilities would be impacted in the 1%CFZ with 3.2 feet of sea level rise (Tetra Tech Inc., 2018). This is double the number of facilities in the SFHA which includes the impacts of riverine flooding.A simplified version of the Wave Height Analysis for Flood Insurance Studies (WHAFIS) extension (FEMA, 2019b) included in Hazus-MH, was used to create the 1% annual chance coastal floodplain. Hazus is a nationally applicable standardized methodology that contains models for estimating potential losses from earthquakes, floods, tsunamis, and hurricanes (FEMA, 2019a). The current 1%-annual-chance stillwater elevations were collected using the most current flood insurance studies (FIS) for each island conducted by FEMA (FEMA, 2004, 2010, 2014, 2015). The FIS calculates the 1%-annual-chance stillwater elevation, wave setup, and wave run-up (called maximum wave crest) at regularly-spaced transects around the islands based on historical data. Modeling for the 1%CFZ used the NOAA 3-meter digital elevation model (DEM) which incorporates LiDAR data sets collected between 2003 and 2007 from NOAA, FEMA, the State of Hawaiʻi Emergency Management Agency, and the USACE (NOAA National Centers for Environmental Information, 2017).Before Hazus was run for future conditions, it was run for the current conditions and compared to the FEMA regulatory floodplain to determine model accuracy. This also helped determine the stillwater elevation for the large gaps between some transects in the FIS. Hazus was run at 0.5-foot stillwater level intervals and the results were compared to the existing Flood Insurance Rate Map (FIRM). The interval of 0.5-feet was chosen as a small enough step to result in a near approximation of the FIRM while not being too impractically narrow to require the testing of dozens of input elevations. The elevation which matched up best was used as the current base flood elevation.Key steps in modeling the projected 1%CFZ with sea level rise include: (1) generating a contiguous (no gaps along the shoreline) and present-day 1%-annual-chance stillwater elevation based on the most recent FIS, (2) elevating the present-day 1%-annual-chance stillwater elevation by adding projected sea level rise heights, and (3) modeling the projected 1%-annual-chance coastal flood with sea level rise in HAZUS using the 1%-annual-chance wave setup and run-up from the FIS. The 1%CFZ extent and depth was generated using the HAZUS 3.2 coastal flood risk assessment model, 3-meter DEM, the FIS for each island, and the IPCC AR5 upper sea level projection for RCP 8.5 scenario for 0.6 feet, 1.0 feet, 2.0 feet, and 3.2 feet of sea level rise above MHHW (IPCC, 2014). The HAZUS output includes the estimated spatial extent of coastal flooding as well as an estimated flood depth map grid for the four sea level rise projections.Using the current floodplain generated with Hazus, the projected 1%-annual-chance stillwater elevation was generated using the four sea level rise projections. This stillwater elevation with sea level rise was used as a basis for modeling. The projected 1%-annual coastal flood with sea level rise was modeled in Hazus using the current 1%-annual-chance wave setup and run-up from the FIS and the projected 1%-annual-chance stillwater elevation with sea level rise. Statewide GIS Program staff extracted individual island layers for ease of downloading. A statewide layer is also available as a REST service, and is available for download from the Statewide GIS geoportal at https://geoportal.hawaii.gov/, or at the Program's legacy download site at https://planning.hawaii.gov/gis/download-gis-data-expanded/#009. For additional information, please refer to summary metadata at https://files.hawaii.gov/dbedt/op/gis/data/coastal_flood_zones_summary.pdf or contact Hawaii Statewide GIS Program, Office of Planning and Sustainable Development, State of Hawaii; PO Box 2359, Honolulu, Hi. 96804; (808) 587-2846; email: gis@hawaii.gov.

General Abstract/Purpose (70 words): Data were collected to assist in cost-benefit analysis of flood mitigation actions that could be taken by the U.S. and Canada to prevent structural damage and associated costs and losses in future flood conditions, including conditions worse than the historical record flooding in spring of 2011. Data were commissioned to revise or fill gaps in estimates from structural damage modeling software commonly used for depth-damage economic assessments of flood impacts. The Summary text that immediately follows this introductory sentence offers overview information, but also includes context and detail that is not present in the Word document ("Principal Indicator Combo SET - REVIEW FINAL v2.docx") that constitutes the main body of this data release, supported by Excel files (that are copied without formatting in csv files for each Excel tab). Lake Champlain is a relatively large lake bordered by New York on the western side and Vermont on the eastern side, whose uppermost region spans the U.S.-Canadian border. The 436 mi^2 (1,130 km^2) lake sits within a 9,277 mi^2 (23,900 km^2) basin, and Champlain’s only drainage point is north into Canada via the Richelieu River into the province of Quebec. About 75% of the Lake Champlain shoreline of New York is within Adirondack State Park, covering all or part of Clinton, Essex, and Washington counties. Of Vermont’s 14 counties, Franklin, Chittenden, and Addison Counties border Lake Champlain, while Grand Isle is surrounded by Champlain and at its northern edge the Canadian border. Development and anthropogenic modifications, especially over the last 50 years, have converted wetlands, changed the timing and flows of water, and increased impervious surface area including new residences in floodplains on both sides of the border. Occasionally there is damaging flooding, with significant economic damages in New York, Vermont, and Quebec. With flood stage at 99.57’ (30.35m) and major flooding from 101.07’ (30.81m) over sea level, a 101.4’ (30.91m) flood in 1993 broke the previous recorded high flood in 1869. Following the third heaviest recorded snow, almost no seasonal snowmelt, then heavy rains, the spring of 2011 brought record flooding more than one foot over the 1993 record to 102.77’ (31.32m), expanding the lake’s area by 66 mi^2 (106.2 km^2, or about 5.8%). From reaching flood stage to peak and then returning to a lake level below flood stage took around six weeks. Wind-to-wave-driven erosion was up to 5 feet (1.5m) above static lake elevation in some areas. The record flood height (102.77’) is often reported as 103.07’ or 103.27’ in Burlington, owing to different vertical and horizontal datums and digital elevation models (DEMs), and some wave action. In a 1976 flood the U.S. side incurred more than 50% of the economic damages, but in 2011, Quebec experienced some 80% of structural and economic damages estimated at $82 million. Tropical Storm Irene hit the area in August of 2011 and did far more damage on the American side, for example spurring $29 million in home and business repair loans for damage across 12 of Vermont’s 14 counties. Co-reporting across the two events for 2011 confounded some data, making it impossible to separately identify spring flooding numbers. Following the Boundary Waters Treaty between the U.S. and Canada in 1909, from 1912 the International Joint Commission (IJC) handles boundary water issues between the two countries. The IJC Lake Champlain Richelieu River (LCRR) Study Project is a bi-national (U.S., Canada) multi-agency effort to assess flood risk and flood mitigation options as they affect potential structural damages and wider non-structural damages that include secondary economic, community, and psychological effects. Key economic parts of the report to the IJC LCRR Study Board are calculated using a new tool developed for the study project, an Integrated Socio-Economic-Environmental (ISEE) model, with forecasting for damages up to 105.57’ flood (105.9’, or 106’ [32.3m] for short, by alternative datum and DEMs, as apply in some of the modeling and estimations herein). There is also a Collaborative Decision Support Tool (CDST) that also processes non-structural economic damages, costs, or losses as inputs. CDST is a pared-down version of ISEE that applies historical estimates but does not project outcomes for higher floods in the future. Outputs from this data release are inputs to the ISEE or the CDST for calculations of the benefit-to-cost ratios projected to follow different structural interventions. For example adding a weir in the Richelieu River yielded a greater-than-one benefit-to-cost ratio in late-stage modeling, whereas a dam on either side, or an entirely new canal on the Canadian side, were never entertained as cost feasible or even appropriate. USGS economists were contracted to supply economic “principal indicators” for potential U.S.-side depth-damage effects from lake-rise flooding. The scope of this analysis is limited by several factors associated with the objectives of the IJC LCRR Study Board. Damages from tributary flooding were defined out of a project focused on joint-management options for mitigating flood effects, as tributary flows would be managed only by the U.S. Uncommonly low Lake Champlain levels were also ultimately considered as a stakeholder concern (the weir option also addressed this concern). It is standard to model economic damages to structures and related economic costs due to flooding using the FEMA-designed Hazus®-MH (Multi-Hazard) Flood Model of structural damages (https://res1wwwd-o-tfemad-o-tgov.vcapture.xyz/flood-maps/products-tools/hazus; the Hazus-MH Technical Manual, 2011, 569pp, which explains definitions and parameterization of the tool rather than use of the tool itself, is a frequently referred source here). “Hazus” (tool) modeling is used in the LCRR Study Board research to estimate structural damages at different flood depths, and the primary work presented in this data release estimates depth-damage values for “Principal Indicators” (PIs) that were defined to supplement or alternatively estimate results from applying Hazus, where gaps exist or where straight Hazus values may be questionable in the LCRR context. A number of Principal Indicators were estimated on the Canadian and U.S. sides, where no PIs include any estimates for repair of structural damage, as those calculations are done separately using the Hazus tool (or the ISEE model application with Hazus outputs as inputs). In the final list, the USGS team produced estimates for six PIs: temporary lodging costs, residential debris clean-up and disposal, damage to roads and bridges, damage to water treatment facilities, income loss from industrial or commercial properties, and separately and specifically recreation sector income loss. So associated with residential damage, the costs of securing emergency and longer-term lodging when a household is displaced by lake-rise flooding are estimated, and the costs of cleaning up and removing and disposing of debris from residential property damage are estimated. In the public sector, costs of clean up and repair of damages to roads and bridges from lake-rise flooding are calculated, as are damages and potential revenue losses from flood mitigation measures and service reductions where public or private water utilities are inundated by lake-rise flooding. In the commercial sector, revenue losses from being closed for business due to flooding are calculated outside of the recreation sector, and then also for the recreation sector as lakeside campgrounds, marinas, and ferry services (where the last is also used for local commercial traffic). All of these PIs are characterized by being little-discussed in the literature. To derive information necessary to bound economic estimates for each of the 6 PIs, consultation with subject-matter experts in New York and Vermont (or at agencies covering these areas) was employed more often than anything in peer-reviewed literature specifically applied. Depth-damage functions that result are not formal mathematical functions, and across the six PIs calculations and results tend to be in increments of one foot or more. Results thus suggest magnitudes of costs that comply with reasonable scenario assumptions for a small but fairly consistent set of flood depths from 99.57’ to 105.57’, where the latter value is almost three feet (1m) above the historic maximum flood. Nothing reported in these estimates is empirically deterministic, or capable of including probabilistic error margins. Simplifying assumptions serve first to actually simplify the calculations and legibility of estimated results, and second to avoid the impression that specifically calibrated empirical estimations are being conducted. This effort offers plausible, logical, reliable, and reproducible magnitudes for estimates, using a method that can be easily modified if better information becomes available for future estimations. Certain worksheets and specific results are withheld to avoid the outright identification of specific businesses (or homes). Facts in this abstract generally attribute to: International Lake Champlain-Richelieu River Study Board, 2019. The Causes and Impacts of Past Floods in the Lake Champlain-Richelieu River Basin – Historical Information on Flooding, A Report to the International Joint Commission, 108pp (https://res1ijcd-o-torg.vcapture.xyz/en/lcrr). Some supplemental factual support is from: Lake Champlain Basin Program, 2013. Flood Resilience in the Lake Champlain Basin and Upper Richelieu River, 93 pp (https://res1ijcd-o-torg.vcapture.xyz/en/lcrr).

These data are an expanded geospatial representation of liquefaction probability for the HayWired earthquake scenario, a magnitude 7.0 earthquake occurring on the Hayward Fault on April 18, 2018, with an epicenter in the city of Oakland, CA. These data supplement the liquefaction probability analysis completed by Jones and others (2017) for the earthquake hazards volume of the HayWired earthquake scenario, which was the product of an analysis that created a detailed liquefaction probability map covering the northern Santa Clara County and western Alameda County areas. This expanded liquefaction probability dataset makes use of FEMA's Hazus-MH 2.1 loss-estimation software and liquefaction susceptibility data by Knudsen and others (2000) to provide liquefaction probabilities for areas in the San Francisco Bay region outside the extent modeled by Jones and others (2017). This vector .SHP dataset was developed and intended for use in GIS applications such as ESRI's ArcGIS software suite. These data support the following publication: Jones, J.L., Wein, A.M., Schweikert, A.E., and Ballanti, L.R., 2019, Lifeline infrastructure and collocation exposure to the HayWired earthquake scenario--A summary of hazards and potential service disruptions, chap. T of Detweiler, S.T., and Wein, A.M., eds., The HayWired earthquake scenario--Societal consequences: U.S. Geological Survey Scientific Investigations Report 2017-5013, https://doi.org/10.3133/sir20175013.

This dashboard was created to support the Northeast Florida Focus Area Action Strategy and visualizes tributary ranking based on the spatial distribution and aggregate of 11 input datasets:SACS Social Vulnerability Index (CDC SVI)SACS Tier 1 Infrastructure Index (HIFLD)SACS Tier 2 Economic Risk Assessment - Existing Conditions (FEMA HAZUS-MH)SACS Tier 2 Economic Risk Assessment - Future Conditions (FEMA HAZUS-MH)2010 Census Population Density (US Census Bureau)1% AEP Flood Event (FEMA NFHL)10% AEP Flood Event (ERDC - NOAA SLR)1% AEP Flood Event Plus 3 ft. of SLR (NOAA SLR)10% AEP Flood Event Plus 3 ft. of SLR (NOAA SLR)FWS Critical Habitat Area (USFWS)NFWF Resiliency Hubs (NFWF)Waterbody ID's were the boundary for the analysis, all datasets were ranked for each input, percentages of area were used to control for variations in waterbody ID size, and then the final ranking was the sum of all input rankings. The lower the ranking, the higher the exposure.

This map was developed to communicate the socio-economic consequences of flooding within the 1% and 0.2% Annual Exceedance Probability Floodplain (AEP) under 4 sea-level rise (SLR) scenarios. The complete Economic Impacts of Sea-Level Rise data viewer can be found here (https://experience.arcgis.com/experience/0aa2ee3b86304fffb6b97f6dd6ffa42b). Assessment methods primarily used HAZUS-MH software, a GIS-based modeling tool developed by the Federal Emergency Management Agency, to estimate the physical, economic, and social impacts of natural disasters. The data here are a subset of the entire dataset (linked below) which includes impacts to essential facilities and wastewater treatment facilities, road exposure to storm surge, and displaced people, shelter needs, and the economic impacts of storm surge flooding on buildings, vehicles, roads, bridges, and crops. The SLR scenarios include 0.7ft (0.2 m), 1.6 ft (0.5 m), 3.9 ft (1.2 m), and 6.6 ft (2.0 m) for the year 2100. The data highlighted here are associated with the N2E2 project. They are intended for geographic representation and analysis of potential socioeconomic losses due to storm surge flooding under present-day and future sea-level rise scenarios. These data map community features, facilities, and zones that will likely be impacted. Data is intended to inform state, regional, and local governments planning flood loss mitigation and emergency preparedness

This map was developed to communicate the socio-economic consequences of flooding within the 1% and 0.2% Annual Exceedance Probability Floodplain (AEP) under 4 sea-level rise (SLR) scenarios. Assessment methods primarily used HAZUS-MH software, a GIS-based modeling tool developed by the Federal Emergency Management Agency, to estimate the physical, economic, and social impacts of natural disasters. The data here are a subset of the entire dataset (linked below) which includes impacts to essential facilities and wastewater treatment facilities, road exposure to storm surge, and displaced people, shelter needs, and the economic impacts of storm surge flooding on buildings, vehicles, roads, bridges, and crops. The SLR scenarios include 0.7ft (0.2 m), 1.6 ft (0.5 m), 3.9 ft (1.2 m), and 6.6 ft (2.0 m) for the year 2100. The data highlighted here are associated with the N2E2 project. They are intended for geographic representation and analysis of potential socioeconomic losses due to storm surge flooding under present-day and future sea-level rise scenarios. These data map community features, facilities, and zones that will likely be impacted. Data is intended to inform state, regional, and local governments planning flood loss mitigation and emergency preparedness

This layer was developed to communicate the socio-economic consequences of flooding within the 1% and 0.2% Annual Exceedance Probability Floodplain (AEP) under 4 sea-level rise (SLR) scenarios. The complete Economic Impacts of Sea-Level Rise data viewer can be found here (https://experience.arcgis.com/experience/0aa2ee3b86304fffb6b97f6dd6ffa42b). Assessment methods primarily used HAZUS-MH software, a GIS-based modeling tool developed by the Federal Emergency Management Agency, to estimate the physical, economic, and social impacts of natural disasters. The data here are a subset of the entire dataset (linked below) which includes impacts to essential facilities and wastewater treatment facilities, road exposure to storm surge, and displaced people, shelter needs, and the economic impacts of storm surge flooding on buildings, vehicles, roads, bridges, and crops. The SLR scenarios include 0.7ft (0.2 m), 1.6 ft (0.5 m), 3.9 ft (1.2 m), and 6.6 ft (2.0 m) for the year 2100. The data highlighted here are associated with the N2E2 project. They are intended for geographic representation and analysis of potential socioeconomic losses due to storm surge flooding under present-day and future sea-level rise scenarios. These data map community features, facilities, and zones that will likely be impacted. Data is intended to inform state, regional, and local governments planning flood loss mitigation and emergency preparedness

This layer was developed to communicate the socio-economic consequences of flooding within the 1% and 0.2% Annual Exceedance Probability Floodplain (AEP) under 4 sea-level rise (SLR) scenarios. The complete Economic Impacts of Sea-Level Rise data viewer can be found here (https://experience.arcgis.com/experience/0aa2ee3b86304fffb6b97f6dd6ffa42b). Assessment methods primarily used HAZUS-MH software, a GIS-based modeling tool developed by the Federal Emergency Management Agency, to estimate the physical, economic, and social impacts of natural disasters. The data here are a subset of the entire dataset (linked below) which includes impacts to essential facilities and wastewater treatment facilities, road exposure to storm surge, and displaced people, shelter needs, and the economic impacts of storm surge flooding on buildings, vehicles, roads, bridges, and crops. The SLR scenarios include 0.7ft (0.2 m), 1.6 ft (0.5 m), 3.9 ft (1.2 m), and 6.6 ft (2.0 m) for the year 2100. The data highlighted here are associated with the N2E2 project. They are intended for geographic representation and analysis of potential socioeconomic losses due to storm surge flooding under present-day and future sea-level rise scenarios. These data map community features, facilities, and zones that will likely be impacted. Data is intended to inform state, regional, and local governments planning flood loss mitigation and emergency preparedness

These data layers were developed to communicate the socio-economic consequences of flooding within the 1% and 0.2% Annual Exceedance Probability Floodplain (AEP) under 4 sea-level rise (SLR) scenarios. The complete Economic Impacts of Sea-Level Rise data viewer can be found here (https://experience.arcgis.com/experience/0aa2ee3b86304fffb6b97f6dd6ffa42b). Assessment methods primarily used HAZUS-MH software, a GIS-based modeling tool developed by the Federal Emergency Management Agency, to estimate the physical, economic, and social impacts of natural disasters. The data here are a subset of the entire dataset (linked below) which includes impacts to essential facilities and wastewater treatment facilities, road exposure to storm surge, and displaced people, shelter needs, and the economic impacts of storm surge flooding on buildings, vehicles, roads, bridges, and crops. The SLR scenarios include 0.7ft (0.2 m), 1.6 ft (0.5 m), 3.9 ft (1.2 m), and 6.6 ft (2.0 m) for the year 2100. The data highlighted here are associated with the N2E2 project. They are intended for geographic representation and analysis of potential socioeconomic losses due to storm surge flooding under present-day and future sea-level rise scenarios. These data map community features, facilities, and zones that will likely be impacted. Data is intended to inform state, regional, and local governments planning flood loss mitigation and emergency preparedness

This data was extracted from Hazus-MH essential facilities data set.