The U.S. Geological Survey (USGS), in cooperation with the State of Hawaiʻi Department of Transportation, estimated flood magnitudes for the 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities (AEP) for unregulated streamgages in Kauaʻi, Oʻahu, Molokaʻi, Maui, and Hawaiʻi, State of Hawaiʻi, using data through water year 2020. Regression equations which can be used to estimate flood magnitude and associated frequency at ungaged streams were developed. The methods and results of the study are published in a separate report (https://doi.org/10.3133/sir20235014). This data release includes peak-flow, specification, output, and export files from version 7.3 of USGS PeakFQ software (Veilleux and others, 2014; Flynn and others, 2006) for 238 streamgages operated by the USGS in the State of Hawaiʻi and a summary of data from the output and export files. Within PeakFQ software, the Expected Moments Algorithm (EMA) was used to conduct frequency analysis to estimate stream discharges corresponding to the 0.5, 0.2, 0.1, 0.04, 0.02, 0.01, 0.005, and 0.002 AEPs (otherwise known as the 2-, 5-, 10-, 25-, 50-, 100-, 200-, and 500-year floods, respectively). Results of the frequency analysis were used to develop a regional flood skew with Bayesian weighted least squares/Bayesian generalized least squares (B-WLS/B-GLS) regression and were used in generalized least-squares (GLS) regression to generate equations that predict stream discharges corresponding to selected AEPs at ungaged locations on streams in the State of Hawaiʻi (Mitchell and others, 2023).

The U.S. Geological Survey (USGS), in cooperation with the State of Hawaiʻi Department of Transportation, estimated flood magnitudes for the 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities (AEP) for unregulated streamgages in Kauaʻi, Oʻahu, Molokaʻi, Maui, and Hawaiʻi, State of Hawaiʻi, using data through water year 2020. Regression equations which can be used to estimate flood magnitude and associated frequency at ungaged streams were developed.The methods and results of the study are published in a separate report (https://doi.org/10.3133/sir20235014). This data release includes two geographic information system (GIS) shapefiles, one of polygons representing the extents of the drainage basins of 238 selected streamgages operated by the USGS in the State of Hawaiʻi, and the other of polygons representing the extents of flood-regression regions in the State of Hawaiʻi. The 238 selected streamgages were used to develop a regional flood skew with Bayesian weighted least squares/Bayesian generalized least squares (B-WLS/B-GLS) regression and were used in generalized least-squares (GLS) regression to generate equations that predict stream discharges corresponding to selected AEPs at ungaged locations on streams in the State of Hawaiʻi (Mitchell and others, 2023). Also included is a comma-separated values (.csv) text file containing the physical, land-cover, and climatic characteristics of the basin polygons corresponding to each of the 238 selected streamgages. The data supporting the basin delineations and basin characteristics were previously published as separate data releases: https://doi.org/10.5066/P9N61WJ7, and https://doi.org/10.5066/P9TOQANM.

The U.S. Geological Survey (USGS), in cooperation with the State of Hawaiʻi Department of Transportation, estimated flood magnitudes for the 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities (AEP) for unregulated streamgages in Kauaʻi, Oʻahu, Molokaʻi, Maui, and Hawaiʻi, State of Hawaiʻi, using data through water year 2020. Regression equations which can be used to estimate flood magnitude and associated frequency at ungaged streams were developed.The methods and results of the study are published in a separate report (https://doi.org/10.3133/sir20235014). This data release includes two geographic information system (GIS) shapefiles, one of polygons representing the extents of the drainage basins of 238 selected streamgages operated by the USGS in the State of Hawaiʻi, and the other of polygons representing the extents of flood-regression regions in the State of Hawaiʻi. The 238 selected streamgages were used to develop a regional flood skew with Bayesian weighted least squares/Bayesian generalized least squares (B-WLS/B-GLS) regression and were used in generalized least-squares (GLS) regression to generate equations that predict stream discharges corresponding to selected AEPs at ungaged locations on streams in the State of Hawaiʻi (Mitchell and others, 2023). Also included is a comma-separated values (.csv) text file containing the physical, land-cover, and climatic characteristics of the basin polygons corresponding to each of the 238 selected streamgages. The data supporting the basin delineations and basin characteristics were previously published as separate data releases: https://doi.org/10.5066/P9N61WJ7, and https://doi.org/10.5066/P9TOQANM.

The U.S. Geological Survey (USGS), in cooperation with the State of Hawaiʻi Department of Transportation, estimated flood magnitudes for the 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities (AEP) for unregulated streamgages in Kauaʻi, Oʻahu, Molokaʻi, Maui, and Hawaiʻi, State of Hawaiʻi, using data through water year 2020. Regression equations which can be used to estimate flood magnitude and associated frequency at ungaged streams were developed. The methods and results of the study are published in a separate report (https://doi.org/10.3133/sir20235014). This data release contains data supporting the larger work: (1) PeakFQ inputs and selected outputs for 238 selected streamgages in Hawaiʻi; (2) inputs and outputs for the USGS weighted-multiple-linear regression (WREG) program used to develop the regional regression equations; (3) geospatial data supporting the report, including basin delineations, basin characteristics, and regional regression boundaries; and (4) selected appendices from the larger work. These data can be used to reproduce the results in the larger work: Magnitude and Frequency of Floods on Kauaʻi, Oʻahu, Molokaʻi, Maui, and Hawaiʻi, State of Hawaiʻi, Based on Data through Water Year 2020.

The U.S. Geological Survey (USGS), in cooperation with the State of Hawaiʻi Department of Transportation, estimated flood magnitudes for the 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities (AEP) for unregulated streamgages in Kauaʻi, Oʻahu, Molokaʻi, Maui, and Hawaiʻi, State of Hawaiʻi, using data through water year 2020. Regression equations which can be used to estimate flood magnitude and associated frequency at ungaged streams were developed. The methods and results of the study are published in a separate report (https://doi.org/10.3133/sir20235014). This data release contains the tabular data that are listed as appendices (appendices A, B, and D) in the larger work: Magnitude and Frequency of Floods on Kauaʻi, Oʻahu, Molokaʻi, Maui, and Hawaiʻi, State of Hawaiʻi, Based on Data through Water Year 2020.

The U.S. Geological Survey (USGS), in cooperation with the State of Hawaiʻi Department of Transportation, estimated flood magnitudes for the 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities (AEP) for unregulated streamgages in Kauaʻi, Oʻahu, Molokaʻi, Maui, and Hawaiʻi, State of Hawaiʻi, using data through water year 2020. Regression equations which can be used to estimate flood magnitude and associated frequency at ungaged streams were developed. The methods and results of the study are published in a separate report (https://doi.org/10.3133/sir20235014). This data release contains (1) a folder with the PeakFQ output files for each streamgage, ".PRT" and ".EXP" files, for use in the USGS weighted-multiple-linear regression (WREG) program; (2) a tab-delimited text file that contains the basin characteristics for use in the USGS WREG program; and (3) a folder with the output from the USGS WREG program, with results separated into folders for each regression region and selected AEP. These data can be used to reproduce the regression results in the larger work: Magnitude and Frequency of Floods on Kauaʻi, Oʻahu, Molokaʻi, Maui, and Hawaiʻi, State of Hawaiʻi, Based on Data through Water Year 2020.

The U.S. Geological Survey (USGS), in cooperation with the State of Hawaiʻi Department of Transportation, estimated flood magnitudes for the 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities (AEP) for unregulated streamgages in Kauaʻi, Oʻahu, Molokaʻi, Maui, and Hawaiʻi, State of Hawaiʻi, using data through water year 2020. Regression equations which can be used to estimate flood magnitude and associated frequency at ungaged streams were developed. The methods and results of the study are published in a separate report (https://doi.org/10.3133/sir20235014). This data release contains (1) a folder with the PeakFQ output files for each streamgage, ".PRT" and ".EXP" files, for use in the USGS weighted-multiple-linear regression (WREG) program; (2) a tab-delimited text file that contains the basin characteristics for use in the USGS WREG program; and (3) a folder with the output from the USGS WREG program, with results separated into folders for each regression region and selected AEP. These data can be used to reproduce the regression results in the larger work: Magnitude and Frequency of Floods on Kauaʻi, Oʻahu, Molokaʻi, Maui, and Hawaiʻi, State of Hawaiʻi, Based on Data through Water Year 2020.

This data release consists of a comma-delimited ascii file with attributes for 21 U.S. Geological Survey streamgage sites in Hawai‘i and Southeast Alaska selected to enable assessment of how floods might change in a future climate. Floods in Hawai‘i and Southeast Alaska have led to loss of human life; damage to agricultural crops, cultural and biological resources, infrastructure, and property; threats to public health; and conditions that are highly disruptive to residents and visitors. Floods are generated by atmospheric and terrestrial processes that may be enhanced or depressed in response to climate change. Understanding the mechanisms that generate floods can be useful for assessing how floods may change in future climates and developing adaptive-management strategies to cope with future floods. Key to improved understanding of floods in Hawai‘i and Southeast Alaska is identifying sites that are affected by known flood-generating mechanisms and that can be used to potentially assess the effects of these mechanisms on the magnitude and frequency of floods, both historically and in a future climate. Stakeholders representing scientific, public-safety, cultural, and ecologic perspectives from government, academic, and private institutions provided input for developing and refining site-selection criteria and selecting sites. The site-selection criteria were: (1) the site contributes to representing the primary flood-generating mechanisms in the study area, (2) the site's available annual peak-streamflow record contains a minimum of 10 years of record during the 1980-2020 period, with a preference for longer records, (3) streamflow at the site during 1980-2020 was not substantively affected by regulation, urban areas, and basin land-use change, which could confound interpretation of the relation between floods and flood-generating mechanisms, (4) concurrent water years of annual peak-streamflow and daily mean streamflow records are available, which enables assessment of antecedent flood conditions, and (5) the site is preferably currently (2022) active, which indicates current relevance of the site’s data that could continue to be relevant in the future. The 21 selected sites are representative of classes of spatial climatic variations for Hawai‘i and seasonal and other flow regimes for Southeast Alaska. For Hawai‘i, selected sites consist of at least one site each from the drier (leeward) and wetter (windward) side of each of the five largest islands (Kaua‘i, O‘ahu, Moloka‘i, Maui, and Hawai‘i). For Southeast Alaska, selected sites consist of at least one site each from five seasonal streamflow regimes variously controlled by rain, snowmelt, and high-elevation melt (Curran and Biles, 2021), and one site each from flow regimes controlled by large basins and glacial lake outburst floods.

This data release consists of a comma-delimited ascii file with attributes for 21 U.S. Geological Survey streamgage sites in Hawai‘i and Southeast Alaska selected to enable assessment of how floods might change in a future climate. Floods in Hawai‘i and Southeast Alaska have led to loss of human life; damage to agricultural crops, cultural and biological resources, infrastructure, and property; threats to public health; and conditions that are highly disruptive to residents and visitors. Floods are generated by atmospheric and terrestrial processes that may be enhanced or depressed in response to climate change. Understanding the mechanisms that generate floods can be useful for assessing how floods may change in future climates and developing adaptive-management strategies to cope with future floods. Key to improved understanding of floods in Hawai‘i and Southeast Alaska is identifying sites that are affected by known flood-generating mechanisms and that can be used to potentially assess the effects of these mechanisms on the magnitude and frequency of floods, both historically and in a future climate. Stakeholders representing scientific, public-safety, cultural, and ecologic perspectives from government, academic, and private institutions provided input for developing and refining site-selection criteria and selecting sites. The site-selection criteria were: (1) the site contributes to representing the primary flood-generating mechanisms in the study area, (2) the site's available annual peak-streamflow record contains a minimum of 10 years of record during the 1980-2020 period, with a preference for longer records, (3) streamflow at the site during 1980-2020 was not substantively affected by regulation, urban areas, and basin land-use change, which could confound interpretation of the relation between floods and flood-generating mechanisms, (4) concurrent water years of annual peak-streamflow and daily mean streamflow records are available, which enables assessment of antecedent flood conditions, and (5) the site is preferably currently (2022) active, which indicates current relevance of the site’s data that could continue to be relevant in the future. The 21 selected sites are representative of classes of spatial climatic variations for Hawai‘i and seasonal and other flow regimes for Southeast Alaska. For Hawai‘i, selected sites consist of at least one site each from the drier (leeward) and wetter (windward) side of each of the five largest islands (Kaua‘i, O‘ahu, Moloka‘i, Maui, and Hawai‘i). For Southeast Alaska, selected sites consist of at least one site each from five seasonal streamflow regimes variously controlled by rain, snowmelt, and high-elevation melt (Curran and Biles, 2021), and one site each from flow regimes controlled by large basins and glacial lake outburst floods.

This data release contains inputs for and outputs from hydrologic simulations for the Hawai‘i (HI) domain using the Precipitation Runoff Modeling System (PRMS) version 5.2.1.1 and the USGS National Hydrologic Model infrastructure (NHM, Regan and others, 2018). This child item holds GIS layers and methodology to make mean-monthly calibration targets (baselines) for the HI domain, as was used in the "byHRU" calibration. Global Circulation Model (GCM) data from National Aeronautics and Space Administration (NASA) were processed into 10 mean-monthly global datasets (Koczot and others, 2025) and stored in NetCDF format ( .nc file extension; https://www.unidata.ucar.edu/software/netcdf/ ). Using these datasets, mean-monthly values were computed for each hydrologic response unit (HRU) in the HI domain (Bock and others, 2024). Resulting data are used as calibration targets for the HI NHM-PRMS model application. DATA TYPE DESIGNATION: Data layers are labeled according to type, as shown below: ID Data Type 1. AET Actual evapotranspiration 2. GW Groundwater (really baseflow) component of total runoff. 3. PET Potential evapotranspiration 4. SCA Snow-cover area (fraction of cell area) from NASA FLDAS. 5. SM Soil moisture 6. SR Solar radiation 7. SRO Surface runoff 8. SSR Subsurface runoff. 9. SWE Snow-water equivalent 10. SWI Soil-water infiltration CONTENTS OF THIS CHILD PAGE: 1. HI_HRU_baseline_targets.zip = Folder containing the 10 mean-monthly calibration target shapefiles files used in the by-HRU calibration step for each of the data types defined above.