Robin L. Glas Liv M. Herdman Salme E. Cook Kristina K. Masterson 20251205 tabular digital data https://doi.org/10.5066/P13ARD2K This data release includes a shapefile of compound flood hazard scores and the associated input data, scripts, and a sample output file necessary for calculating rain-surge return period adjustments for Long Island Sound and its surrounding areas. The raw input data and imputation scripts are included in this data release and are located in the "Imputation and data compilation.zip" folder. These files allow for filling in missing values with neighboring correlated stations, resulting in time series with no missing values for daily precipitation in millimeters, daily coastal nontidal residuals (NTR) in meters, and monthly groundwater levels as depth to water from land surface in feet. The complete daily time series of rainfall and surge NTR values are provided as separate ".csv" files, labeled with their unique station identifiers and the precipitation and coastal station numbers. These ".csv" files serve as input for the script "Return_Period_Adjustments.R" and are accompanied by two additional tables: "Model_selection.csv" for pre-selected models and "Threshold_selection.csv" for pre-selected thresholds. The methods used for model and threshold selection are described in Glas and others (2025). This data release supports an analysis of compound flooding hazard potential (Glas and others, 2025) in coastal New York and Connecticut. Results of the analysis are intended to provide land planners and coastal engineers with insights into building resiliency against coastal flooding. This work was funded through the EPA Long Island Sound Study and Hurricane Ida Supplemental appropriations. 19700101 20211231 ground condition Complete None planned -74.0819 -71.7474 41.7090 40.4955 ISO 19115 Topic Category biota USGS Thesaurus floods hazard preparedness hazards coastal processes multivariate statistical analysis precipitation (atmospheric) groundwater level USGS Metadata Identifier USGS:655cf935d34ee4b6e05cc55a Common geographic areas Long Island Sound Long Island No access constraints. Please see 'Distribution Information' for details. These data are marked with a Creative Common CC0 1.0 Universal License. These data are in the public domain and do not have any use constraints. Users are advised to read the dataset's metadata thoroughly to understand appropriate use and data limitations. Robin Glas mailing and physical

425 Jordan Rd

Troy NY 12180 518-285-5600 rglas@usgs.gov No new data were collected for this project. All values fall within expected ranges. Multivariate statistical analysis was carried out from historical data inside the range of 1970 to 2021 for precipitation, coastal water levels and groundwater levels from stations around coastal Long Island and Long Island Sound. U.S. Geological Survey 2022 application/service https://waterdata.usgs.gov/ Digital and/or Hardcopy 19750101 20211231 ground condition NWIS groundwater levels Public repository National Oceanic and Atmospheric Administration 2022 tabular digital data https://tidesandcurrents.noaa.gov/ Digital and/or Hardcopy 19700101 20211231 ground condition NOAA daily coastal water levels Public repository National Oceanic and Atmospheric Administration 2022 tabular digital data Digital and/or Hardcopy 19700101 20211231 ground condition NOAA daily precipitation Public repository U.S. Geological Survey 2022 tabular digital data https://waterdata.usgs.gov/ Digital and/or Hardcopy 19700101 20211231 ground condition NWIS coastal water level data Public repository Salme E. Cook Liv M. Herdman 2025 tabular digital data https://doi.org/10.5066/P94P4WXX Digital and/or Hardcopy 19700101 20211231 ground condition Coastal nontidal residual (NTR) values Input data to Return_Period_Adjustments.R script. Zeno F Levy Timothy J Stagnitta Robin L Glas 20240711 application/service https://code.usgs.gov U.S. Geological Survey https://doi.org/10.5066/p1vvhwke Digital and/or Hardcopy unknown ground condition ARCHI imputation software Algorithm used to impute missing values. Robert J Welk Kristina K Masterson Janet R Barclay Kalle L Jahn 20250729 Dataset https://www.sciencebase.gov U.S. Geological Survey https://doi.org/10.5066/p9w4qiv5 Digital and/or Hardcopy unknown ground condition Groundwater emergence hazard data Spatial boundary layer to limit extents of compound flood hazard scores Robert J. Welk Ben N. Fisher Liv M. Herdman Kalle L. Jahn Kristina K. Masterson 2025 vector digital data Digital and/or Hardcopy unknown ground condition Pluvial flooding geospatial layer Grid layer used to aggregate and interpolate compound flood hazard scores Robin L. Glas Liv M. Herdman Salme E. Cook Archi Howlader Kristina K. Masterson 2025 publication Digital and/or Hardcopy unknown ground condition Accompanying full interpretive report Interpretive report Laura A DeCicco Robert M Hirsch David Lorenz David Watkins J Michael Johnson 20180913 application/service https://code.usgs.gov U.S. Geological Survey https://doi.org/10.5066/p9x4l3ge Digital and/or Hardcopy unknown ground condition dataRetrieval R package used to pull monthly groundwater values R. Jane T. Wahl F. Peña J. Obeysekera C. Murphy-Barltrop J. Ali P. Maduwantha H. Li V. Malagón Santos 2025 application/service Digital and/or Hardcopy unknown ground condition MultiHazard R package used to compute return period shifts. Coastal water levels were downloaded from the U.S. Geological Survey and National Oceanic and Atmospheric Administration public databases for the years 1970 to 2021. The daily coastal water levels were converted to nontidal residuals (NTR in meters) by methods described in (Glas et al., 2025). Missing values in the NTR and daily precipitation datasets were then extended and infilled using ARCHI imputation software (Levy et al., 2024), which uses regression to iteratively fill missing values using regionally correlated, neighboring stations. The result is a daily time series for each variable for the entire date range with no missing values. All imputation methods and statistics are described in the accompanying report. 20231101 Monthly unconfined groundwater levels in depth to water from land surface (feet) were extracted from the U.S. Geological Survey National Water Information System for the entire study area spanning Long Island and coastal Connecticut and New York. Missing values were imputed using ARCHI imputation software (Levy et al., 2024). Resulting wells were selected and associated with precipitation and coastal stations according to selection methods outlined in the accompanying report. Monthly imputed values are provided in this data release as well as interpolated daily values, aggregated as the daily median depth to water associated with each station triad as described in the accompanying report. 20231101 To create the interpolated_compound_ranking.shp layer, resulting station-based ranks from Return_Period_Adjustments.R was initially assigned to one of eight spatial clusters using k-means clustering, implemented with the scikit-learn Python library. Clustering was based on the following six features: (1) average return period shift conditioned on precipitation (CoP), (2) average return period shift conditioned on surge (CoS), (3) median minimum groundwater depth (in feet), (4) groundwater hazard score, (5) biconditional dependence score, and (6) upper tail dependence score. To ensure spatial contiguity, stations that were grouped into non-contiguous clusters were reassigned to new, spatially coherent clusters. This post-processing resulted in a total of 11 final clusters, each containing between one and four stations. For each cluster, a centroid was calculated and used to generate polygons that partitioned the entire study area. Separate tessellations were created for Connecticut (CT), and for the north and south shores of Long Island. Within each polygon, 900-meter grid cells were assigned the average compound hazard score of the stations in the corresponding cluster. Averaging was then masked and restricted to 900-meter grid cells located within the coastal 100-year flood (0.01 annual exceedance probability) hazard extent for the study area, as defined by Welk et al. (2025a). This grid is the same grid used for rainfall hazard (Welk et al., 2025b), coastal flood hazard (Cook and Herdman, 2025), and groundwater hazard (Welk et al., 2025a) across the same study area as this compound hazard assessment. It is important to note that the spatially continuous hazard map is based on interpolation of results from discrete monitoring stations. These stations are assumed to be representative of broader conditions, but the map does not account for local variability in precipitation, coastal water levels, or groundwater depth at locations where no measurements were available. More details are available in Glas et al. (2025). imputed_GW.csv weighted_RP_adjustments.csv 2025 interpolated_compound_ranking.shp Liv Herdman U.S. Geological Survey Hydrologist mailing and physical

425 Jordan Rd

Troy New York 12180 518-285-5600 The following excerpt was taken from Glas et al. (2025), which describes the process steps associated with final compound hazard ranking scores found in Compound hazard summary table.csv: To characterize groundwater-related hazard, the shallowest groundwater levels (minimum depth to water below land surface) were identified across the associated wells in each cluster, and their median was used to assign a groundwater hazard score. Median shallow depths ≤ 6 ft were assigned a score of 2 (high hazard), depths between 6 ft and 15 ft were scored as 1 (moderate hazard), and depths > 15 ft were scored as 0 (low hazard). The groundwater hazard score was combined with two scores based on the dependence structure between precipitation and surge. First, a triad received 1 point if either conditioned on precipitation (CoP) or conditioned on storm surge (CoS) event datasets exhibited upper tail dependence, as determined by fitting a copula with upper tail dependence. Second, a triad received 1 point if symmetrical dependence was observed, meaning a non-independent copula was selected for both CoP and CoS event types. Scores were summed and scaled to a range of 1 to 5. 2025 Vector G-polygon 1 Universal Transverse Mercator 18 0.9996 -75.0 0.0 500000.0 0.0 coordinate pair 0.6096 0.6096 meters North_American_Datum_1983 GRS 1980 6378137.0 298.257222101 Triad data\TriadXX_YYYYYYYYYYY_ZZZZZZZ.csv Comma Separated Value (CSV) file containing daily precipitation and surge data where XX is the station pair number and Y_Z are the precipitation and coastal station numbers respectively. Producer Defined date Date in the form YYYY-mm-dd Producer Defined Formatted dates ranging from 1/1/1970 to 12/31/2021 RainFall Daily rainfall amounts Producer Defined 0.0 198.1 millimeters Surge Daily nontidal residual levels Producer Defined -2.90128459147651 5.26842917431256 meters Imputation and data compilation\Station_selections.csv Comma Separated Value (CSV) file containing data. Producer Defined rain_stations rain station IDs Producer Defined Values are free text names determined by the data provider. coastal_stations coastal station IDs Producer Defined Values are free text names determined by the data provider. Agency Agency that manages the coastal station (NOAA or USGS) Producer Defined USGS U.S. Geological Survey Producer defined NOAA National Oceanic and Atmospheric Administration Producer defined Imputation and data compilation\selected_wells.csv Comma Separated Value (CSV) file containing preselected well identification numbers. Producer Defined well_ID USGS groundwater observation well identification numbers Producer Defined These are 15-digit USGS well identification numbers. The well numbers are preceded by "X." to keep station numbers numeric if viewed in spreadsheet software. Imputation and data compilation\NTR_Daily.csv Comma Separated Value (CSV) file containing daily nontidal residual values. Producer Defined site_no USGS or NOAA tidal station corresponding to each NTR value. Producer Defined These are NOAA and USGS station identification numbers. date dates formatted as YYYY-mm-dd Producer Defined Date range from 1/1/1970 to 12/31/2021 value Nontidal residual (NTR) Producer Defined -6.05612834408815 6.62017473594956 meters Imputation and data compilation\NOAA_precipitation_data_raw.csv Comma Separated Value (CSV) file containing daily precipitation data. Producer Defined site_no NOAA station number Producer Defined Station identification numbers date dates formatted as mm/dd/YYYY Producer Defined Date range from 1/1/1970 to 12/31/2021 value Daily precipitation total Producer Defined 0.0 343.2 millimeters Imputation and data compilation\Unconfined_longrecord.csv Comma Separated Value (CSV) file containing data. Producer Defined siteno Site number Producer Defined 15-digit USGS observation well identification number proceeded by "X." to prevent scientific notation formatting and loss of information. lat latitude in decimal degrees Producer Defined 40.5787163 41.6913333 long longitude in decimal degrees Producer Defined -73.9912515 -71.70617638 Imputation and data compilation\imputed_GW.csv Comma Separated Value (CSV) file containing data. Producer Defined station Station ID number Producer Defined 15-digit USGS observation well identification number proceeded by "X." to prevent scientific notation formatting and possible information loss. date date formatted as YYYY-mm-dd Producer Defined Date range 1975-01-01 to 2021-12-01 at monthly timesteps value Groundwater level as depth to water below land surface in feet. Producer Defined -4.5 54.37 feet Return_Period_Adjustments\CF_threshold_selections.csv Comma Separated Value (CSV) file containing data. Producer Defined Triad_ID Precipitation-coastal station pair identification number Producer Defined 1 24 Rainthresh Selected threshold for daily precipitation data Producer Defined 0.98 0.99 fractional percentile RainEPY Number of events per year, on average for data conditioned on precipitation Producer Defined 3.12 5.92 TaurCOS Kendall correlation tau for data conditioned on surge Producer Defined 0.09 0.19 TaurCOSpval P-value associated with Kendall tau conditioned on surge Producer Defined 3.6e-06 0.058 Sgthresh Selected threshold for data conditioned on surge Producer Defined 0.97 0.98 SgEPY Number of events per year, on average, for data conditioned on surge Producer Defined 3.81 5.5 TausCOR Kendall correlation tau for data conditioned on precipitation Producer Defined -0.052 0.11 TausCORpval P-value associated with Kendall tau conditioned on precipitation Producer Defined 0.016 0.72 Return_Period_Adjustments\CF_model_selections.csv Comma Separated Value (CSV) file containing data. Producer Defined Triad_ID Precipitation-coastal station pair identification number Producer Defined 1 24 Best_Model_COP Preselected copula model for data conditioned on precipitation Producer Defined Independence Independence copula Producer defined Gaussian Gaussian copula Producer defined Gumbel Gumbel copula Producer defined Survival Clayton Survival Clayton copula Producer defined Frank Frank copula Producer defined Best_Model_COS Preselected copula model for data conditioned on surge Producer Defined Gumbel Gumbel copula Producer defined Survival Clayton Survival Clayton copula Producer defined Frank Frank copula Producer defined Independence Independence copula Producer defined Gaussian Gaussian copula Producer defined weighted_RP_adjustments.csv Comma Separated Value (CSV) file containing processed return period shifts for biconditionally sampled datasets. Producer Defined Unnamed: 0 Triad number, pertaining to preselected Precipitation-coastal station pair identification number Producer Defined Triad01 - Triad24 CoR_inv Inverse-weighted average return period adjustment for data conditioned on precipitation. Producer Defined NA No Data Producer defined 1.37 6.8 Unitless ratio CoS_inv Inverse-weighted average return period adjustment for data conditioned on surge. Producer Defined NA No Data Producer defined 1.47 8.51 Unitless ratio Return_Period_Adjustments\Return_Period_Adjustments.R This is an R script to compute return period adjustments for precipitation - coastal storm surge data pairs under the assumption of dependence. Producer Defined Return_Period_Adjustments\README_Return_Period_Adjustments.txt README file to use in support of Return_Period_Adjustments.R script. Producer Defined Imputation and data compilation\Imputation and data compilation.R R script to compile data from raw version into aggregated and imputed version for analysis. Producer Defined Imputation and data compilation\READ_ME_Imputation_and_data_compilation.txt README file to be used in support of Imputation and data compilation.R script. Producer Defined interpolated compound ranking\interpolated_compound_ranking.shp Shapefile containing attribute information associated with the data set. Producer Defined FID Internal feature number. ESRI Sequential unique whole numbers that are automatically generated. Shape Feature geometry. ESRI Shape type. SCORE Overall compound hazard score. Represents the relative compound hazard based on shallow groundwater, high storm surge and high precipitation co-occurrence. Producer Defined 1.4 5.0 Compound hazard summary table.csv Table for compound flood hazard analysis that collapses multivariate results into a single score. Producer Defined Triad_ID Precipitation- coastal station pair number Producer Defined 1 24 RPshiftCoP Return period shift conditioned on precipitation Producer Defined << empty cell >> No Data Producer defined 1.37 6.86 RPshiftCoS Return period shift conditioned on storm surge Producer Defined << empty cell >> No Data Producer defined 1.47 8.51 MedGW Median depth to water among groundwater wells proximal to precipitation - coastal station midpoints Producer Defined 1.77 24.735 Feet below land surface GW score Relative stratified score for groundwater from the most deep (score of 0), to moderate depth (score of 1) to most shallow (score of 2) Producer Defined 0 2 Biconditional Dependence Score Binary score indicating that dependence was detected when conditioning on both precipitation and storm surge (score of 1) or that dependence was only detected when conditioning either on precipitation or storm surge, or neither (score of 0). Producer Defined 0 1 Tail Dependence Score Binary score indicating precipitation - storm surge copula fits as being asymptotically dependent (score of one) or asymptotically independent (score of zero). Producer Defined 0 1 Component score sum Sum of GW score, Biconditional dependence score, and Tail dependence score. Producer Defined 0 4 Final Hazard Score Component score sum that has been scaled to the range 1 to 5. Producer Defined 1 5 U.S. Geological Survey - ScienceBase mailing address

Denver Federal Center

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Denver CO 80225 1-888-275-8747 sciencebase@usgs.gov Unless otherwise stated, all data, metadata and related materials are considered to satisfy the quality standards relative to the purpose for which the data were collected. Although these data and associated metadata have been reviewed for accuracy and completeness and approved for release by the U.S. Geological Survey (USGS), no warranty expressed or implied is made regarding the display or utility of the data for other purposes, nor on all computer systems, nor shall the act of distribution constitute any such warranty.Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government. Digital Data https://doi.org/10.5066/P13ARD2K None 20251205 Robin L Glas mailing and physical

425 Jordan Rd

Troy NY 12180 5182855600 rglas@usgs.gov FGDC Content Standard for Digital Geospatial Metadata FGDC-STD-001-1998