This data release provides topographic (horizontal and vertical) data for 78 sites, surveyed from November 2017 to July 2019 as part of documentation of flooding that occurred in Puerto Rico during and after Hurricane Maria (September to November 2017). Hurricane Maria made landfall the Island of Puerto Rico on September 20, 2017 and was one of the deadliest storms in U.S. history. The U.S. Geological Survey (USGS) personnel conducted topographic surveys at selected stream sites to facilitate hydraulic modeling of peak streamflows (or discharges) – termed indirect measurements – using published standard USGS methods and hydraulic modeling studies to establish new stage-discharge relations for sites at which flooding substantially changed the pre-existing relation. Indirect (post-flood) measurements are used to characterize flood peaks that could not be determined using direct methods (for example current-velocity meters, hydro-acoustic instruments or established stage-streamflow relations) because flood conditions exceeded the capabilities of those methods, streamgage sites could not be accessed during flooding, or safety issues precluded access by USGS personnel during flooding. The standard-step hydraulic method, often referred to as the step-backwater method, is a widely accepted one-dimensional hydraulic model to determine (theoretical) water-surface elevations at a location of interest for specified streamflows.

Estimates of the magnitude of peak-flows were updated for the 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent chance exceedance levels for 91 rural, unregulated streamgaging stations on the main island of Puerto Rico. These stations required 10 or more years of annual peak-flow record, using data to 2017, for inclusion in the study. The magnitude and frequency of floods at selected streamgages in Puerto Rico were estimated using the U.S. Geological Survey PeakFQ program and updated methods outlined in Bulletin 17C (England and others, 2018). Regional regression equations were calculated to estimate flood frequency statistics at ungaged locations using selected basin characteristics as explanatory variables. These variables were determined from digital spatial datasets and geographic information systems using the most recent data available, as referenced in the U.S. Geological Survey web application, StreamStats, and published in Kolb and Ryan (2021). A generalized least squares procedure in the U.S. Geological Survey program, WREG, was used to account for cross-correlation of sites and develop the final regional regression equations using drainage area as the only explanatory variable. Two separate regions were defined for regression equation use in this study to minimize residuals. NOTE: All of the data in the previous version can be found in version 1.1. References Cited: England J.F., Jr., Cohn, T.A., Faber, B.A., Stedinger,J.R., Thomas,W.O.,Jr., Veilleux,A.G., Kiang,J.E., and Mason,R.R., Jr., 2018, Guidelines for determining flood flow frequency —Bulletin 17C: U.S. Geological Survey Techniques and Methods, book 4, chap. B5, 148p., https://doi.org/10.3133/tm4B5. Kolb, K.R., and Ryan, P.J., 2021, Basin Characteristic Rasters for Puerto Rico StreamStats, 2021: U.S. Geological Survey data release, https://doi.org/10.5066/P9HK9SSQ.

This data release contains the associated data described in the related primary publication, “Predicting Flood Damage Probability Across the Conterminous United States” (Collins et al. [2022], see Cross Reference section). Publicly available geospatial datasets and random forest algorithms were used to analyze the spatial distribution and underlying drivers of flood damage probability caused by excessive rainfall and overflowing water bodies across the conterminous United States. Datasets contain input files for predictor and response variables used in the analysis and output files of flood damage probabilities generated from the analysis.

This data release contains the associated data described in the related primary publication, “Predicting Flood Damage Probability Across the Conterminous United States” (Collins et al. [2022], see Cross Reference section). Publicly available geospatial datasets and random forest algorithms were used to analyze the spatial distribution and underlying drivers of flood damage probability caused by excessive rainfall and overflowing water bodies across the conterminous United States. Datasets contain input files for predictor and response variables used in the analysis and output files of flood damage probabilities generated from the analysis.

This data release includes time-series, qualitative descriptions, and laboratory testing data from two monitoring stations installed in Puerto Rico following Hurricane Maria in 2017, which led to tens of thousands of landslides across the island (Bessette-Kirton et al., 2017). The stations were installed to investigate subsurface hydrologic response to rainfall and develop a quantitative link between rainfall and landsliding. The Toro Negro site is located within the state protected Toro Negro rainforest near 18°10’N, 66°34’W and the Utuado site is located outside the city of Utuado near 18°17’N, 66°39’W. The soil found at the Toro Negro site is low-permeability, fine-grained and cohesive, and underlain by saprolite. In contrast, the soil found at Utuado has higher hydraulic conductivity, relatively incohesive, and shallowly underlain by granodioritic bedrock. Instrumentation was installed at each site to measure precipitation, air temperature, barometric pressure, volumetric water content, pore-water pressure, and soil matric potential, at 15-minute intervals. An electronics enclosure, rain gage, and an instrumented soil pit (SP1) comprised each site for continuous monitoring. Volumetric soil water content was measured at 5 depths below the ground surface in each pit, using ruggedized dielectric sensors (range of 0-0.64 volumetric water content in mineral soils). Soil matric potential was measured at each site with two tensiometers (-80 to 100 kilopascals [kPa]) and one dielectric ceramic disc sensor (-6 to -1000 kPa). Pore-water pressure was measured at two depths with vibrating-wire piezometers (0 to 70 kPa). Each pressure sensor has an integrated thermistor and the associated temperature readings are included. In October 2019 an additional soil-pit was established at Toro Negro (SP2) to clarify the signal of two existing volumetric water content sensors with questionable readings. The data released with this report have not undergone any significant alterations since being recorded by the datalogger and are subject to inaccuracies related to equipment failure or loss of calibration. Missing data is represented as “not a number” (NaN). Also, there are time periods where groundwater conditions are outside of the instruments’ measurement range and these clipped data have been left in the record. Additionally, the tensiometer data returns erroneous data once it cavitates, and a Boolean data quality flag (vector “tensiometerFlag”) has been added to show where the data are likely reliable (1) or not reliable (0). The vibrating-wire piezometers are equipped with low air-entry filter tips (50 micron) and allow limited suctional range and these values should be viewed with skepticism. All values recorded by the piezometer are dependent on filter-saturation and, consequently, readings will be invalid during and after long periods of drought, until the tip has become re-saturated. Soil samples were taken from the documented soil pits at the time of installation and their index properties were measured in the Unsaturated Soil Mechanics Laboratory at Colorado School of Mines. The properties measured include particle size distributions (ASTM-152H), Atterberg limits (ASTM D-4318), soil classifications (USCS), specific gravity (ASTM D-854), unsaturated and saturated soil hydraulic properties including hysteretic saturated hydraulic conductivities and unsaturated soil-water retention curves using the TRIM method (Wayllace and Lu, 2012), strength properties including cohesion and the angle of internal friction determined using direct shear tests on saturated samples (ASTM D-3080) that included modifications for measurements at relatively low effective stresses (i.e., 0.2-20 kPa) (Likos et al., 2010). An additional “monitoring.readme.pdf” file is included and contains these details along with naming conventions for the hydrologic monitoring data. Logs of the soil pits at Utuado and Toro Negro are documented in the “PR UTU-ELT Monitoring Site

This data release contains 16 variables from the National Hydrologic Model Infrastructure with the Precipitation-Runoff Modeling System (NHM-PRMS) modeling application forced with Daymet version 4 (LaFontaine and others, 2024) from January 1950 through December 2021 that are summarized to a monthly time step and a twelve-digit hydrologic unit code for the spatial extent of Puerto Rico and the U.S. Virgin Islands. The following fluxes and storages are included: total monthly precipitation, evapotranspiration, lateral flow, surface runoff, interflow, recharge, groundwater flow, and the average monthly snow water equivalent, interflow storage, groundwater storage, total storage, and soil moisture. These data can be found in the “PR_huc12_monthly_nhmprms_daymet_1950_2021.nc” file. Additionally, two supplementary files are also included in this data release. The first file (“PR_weights_hru_to_huc12_nhmprms_daymet.csv”) contains the spatial weights or fraction that is used to “weight” the modeling output in the area-weighting process. The second file (“PR_summed_weights_per_huc12_nhmprms_daymet.csv”) contains the total fractional area within each twelve-digit hydrologic unit code that is covered by the modeling output and is important for filtering results in the data file (where a fractional coverage may be less than one). In the version 2.0 data release update, a new variable was added to the “PR_huc12_monthly_nhmprms_daymet_1950_2021.nc” file and a new file, "PR_huc12_daily_soil_moisture_fraction_nhmprms_paymet_1950_2021.nc" was added that contains daily estimates of the soil moisture fraction at each twelve-digit hydrologic unit code for the spatial extent of Puerto Rico and the U.S. Virgin Islands. See the file, “revision_history_nhmprms_daymet_PR.txt” for a full description of revisions.

Regional regression equations were calculated in Puerto Rico with generalized least squares techniques to estimate flood frequency statistics at ungaged locations using drainage area as the only explanatory variable. The island was divided into 2 regions to minimize residuals. The region division that resulted in lower and more balanced residuals runs primarily north-south near the center of the island, mostly along an 8-digit hydrologic unit code (HUC8) boundary. The division line runs through a HUC8 polygon on the southern end of the island, but care was taken to include entire watersheds and consideration was given where hydrologic and physiographic properties differed. This data release includes geographic information system files that define the polygons for both regions.

The U.S. Geological Survey (USGS), in cooperation with the Puerto Rico Environmental Quality Board, has compiled a series of geospatial datasets for Puerto Rico to be implemented into the USGS StreamStats application (https://streamstats.usgs.gov/ss/). These geospatial datasets, along with basin characteristics datasets for Puerto Rico published as a separate USGS data release (https://doi.org/10.5066/P9HK9SSQ), were used to delineate watersheds and develop the peak-flow and low-flow regression equations used by StreamStats. The geospatial dataset described herein are the stream link rasters at a 10-m resolution. A number is assigned to a reach of stream located between junctions (such as tributary junctions). Stream link raster contains unique values for each stream segment defined by str. Data are partitioned into four TIFF files, one for each of the four 8-digit Hydrologic Unit Code (HUC) areas for Puerto Rico: 21010002, 21010003, 21010004, and 21010005.

The U.S. Geological Survey (USGS), in cooperation with the Puerto Rico Environmental Quality Board, has compiled a series of geospatial datasets for Puerto Rico to be implemented into the USGS StreamStats application (https://streamstats.usgs.gov/ss/). These geospatial datasets, along with basin characteristics datasets for Puerto Rico published as a separate USGS data release (https://doi.org/10.5066/P9HK9SSQ), were used to delineate watersheds and develop the peak-flow and low-flow regression equations used by StreamStats. The geospatial dataset described herein are watershed catchment rasters at a 10-m resolution. The catchment raster assigns a number to each pixel that is unique for each catchment and corresponds to the value of the stream segment that drains that area. Data are partitioned into four TIFF files, one for each of the four 8-digit Hydrologic Unit Code (HUC) areas for Puerto Rico: 21010002, 21010003, 21010004, and 21010005.

The U.S. Geological Survey (USGS), in cooperation with the Puerto Rico Environmental Quality Board, has compiled a series of geospatial datasets for Puerto Rico to be implemented into the USGS StreamStats application (https://streamstats.usgs.gov/ss/). These geospatial datasets, along with basin characteristics datasets for Puerto Rico published as a separate USGS data release (https://doi.org/10.5066/P9HK9SSQ), were used to delineate watersheds and develop the peak-flow and low-flow regression equations used by StreamStats. The geospatial dataset described herein are the rasters of flow accumulation, which is the number of pixels upstream of a given pixel. Data are partitioned into four TIFF files, one for each of the four 8-digit Hydrologic Unit Code (HUC) areas for Puerto Rico: 21010002, 21010003, 21010004, and 21010005.