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Data Files for USGS Response to Hurricane Maria Flooding in Puerto Rico and Characterization of Peak Streamflows Observed September 20-22, 2017
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.
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Data Files for USGS Response to Hurricane Maria Flooding in Puerto Rico and Characterization of Peak Streamflows Observed September 20-22, 2017
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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.
Data Files for the Development of Regression Equations for the Estimation of the Magnitude and Frequency of Floods at Rural, Unregulated Gaged and Ungaged Streams in Puerto Rico through Water Year 2017 (ver. 1.1, September 2021)
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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.
Data Files for the Development of Regression Equations for the Estimation of the Magnitude and Frequency of Floods at Rural, Unregulated Gaged and Ungaged Streams in Puerto Rico through Water Year 2017 (ver. 1.1, September 2021)
공공데이터포털
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.
Infiltration data collected post-Hurricane Maria across landslide source area materials, Puerto Rico, USA
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This Data Release includes information to support the characterization of surface/near-surface infiltration rates of selected landslide source area materials following Hurricane Maria across Puerto Rico, USA. The dataset includes comma-delimited measurements of field-saturated hydraulic conductivity (Kfs) collected over two field campaigns (Fall 2018 and Spring 2019) as well as laboratory-derived measurements of soil/saprolite texture. The Kfs experiments were conducted within (or in the vicinity of) landslide source areas across the three primary geologic terranes on the island (Bawiec, 1998), including intrusive, volcaniclastic, and submarine basalt/chert lithologies. Depending on site conditions and the hydrologic conditions of interest, a Soil Moisture Inc. Guelph Permeameter (Soil Moisture, Inc. 2012), Decagon DualHead Infiltrometer (Decagon Devices, Inc. 2016), Decagon Mini-Disk Infiltrometer (Decagon Devices, Inc. 2018), or bottomless bucket approach (Nimmo et al. 2009) was used. Timing, location, and material information are provided for each Kfs measurement. All Kfs measurements (see Kfs-PR.csv) include a field-based texture estimate, and select measurements include quantitative texture estimates based on a Beckman Coulter particle size analyzer (Gee & Or 2002). Dianne Brien, Lindsay Davis, and William Schulz provided invaluable field assistance during this infiltration measurement campaign. Ben Mirus and Eric Jones provided constructive reviews for an earlier version of this Data Release. The following citations relate to this Data Release: Bawiec, W.J. (1998). Geology, Geochemistry, Geophysics, Mineral Occurrences and Mineral Resource Assessment for the Commonwealth of Puerto Rico (Open-File Report 98-38). Reston, VA: U.S. Geological Survey. https://doi.org/10.3133/ofr9838 Beckman Coulter, Inc. (2011). LS 13 32 Laser Diffraction Particle Size Analyzer Operator’s Manual. Brea, CA: Beckman Coulter, Inc. Available at: https://www.beckmancoulter.com/wsrportal/techdocs?docname=B05577AB.pdf Decagon Devices, Inc.; now Meter Environment Group, Inc. (2016). DualHead Infiltrometer Operator’s Manual. Pullman, WA: Decagon Devices, Inc. Available at: http://manuals.decagon.com/Retired%20and%20Discontinued/Manuals/14968_DHInfiltr ometer_Web.pdf Decagon Devices, Inc.; now Meter Environment Group, Inc. (2018). Mini Disk Infiltrometer Operator’s Manual. Pullman, WA: Decagon Devices, Inc. Available at: http://library.metergroup.com/Manuals/10564_Mini%20Disk%20Infiltrometer_Web.pdf Gee G.W., & Or D. (2002). Particle size analysis. In: Dane, J.H., & Topp, G.C. (Eds), Methods of Soil Analysis, Part 4-Physical Methods, Soil Science Society of America Book Series, Volume 5 (pp. 255-293). Madison, WA: Soil Science Society of America. Nimmo, J.R., Schmidt, K.M., Perkins, K.S., & Stock, J.D. (2009). Rapid measurement of field- saturated hydraulic conductivity for areal characterization. Vadose Zone Journal, 8(1), 142-149. https://doi.org/10.2136/vzj2007.0159 Soil Moisture, Inc. (2012). 2800K1 Guelph Permeameter Operating Instructions. Santa Barbara, CA: Soil Moisture, Inc. Available at: https://www.soilmoisture.com
Infiltration data collected post-Hurricane Maria across landslide source area materials, Puerto Rico, USA
공공데이터포털
This Data Release includes information to support the characterization of surface/near-surface infiltration rates of selected landslide source area materials following Hurricane Maria across Puerto Rico, USA. The dataset includes comma-delimited measurements of field-saturated hydraulic conductivity (Kfs) collected over two field campaigns (Fall 2018 and Spring 2019) as well as laboratory-derived measurements of soil/saprolite texture. The Kfs experiments were conducted within (or in the vicinity of) landslide source areas across the three primary geologic terranes on the island (Bawiec, 1998), including intrusive, volcaniclastic, and submarine basalt/chert lithologies. Depending on site conditions and the hydrologic conditions of interest, a Soil Moisture Inc. Guelph Permeameter (Soil Moisture, Inc. 2012), Decagon DualHead Infiltrometer (Decagon Devices, Inc. 2016), Decagon Mini-Disk Infiltrometer (Decagon Devices, Inc. 2018), or bottomless bucket approach (Nimmo et al. 2009) was used. Timing, location, and material information are provided for each Kfs measurement. All Kfs measurements (see Kfs-PR.csv) include a field-based texture estimate, and select measurements include quantitative texture estimates based on a Beckman Coulter particle size analyzer (Gee & Or 2002). Dianne Brien, Lindsay Davis, and William Schulz provided invaluable field assistance during this infiltration measurement campaign. Ben Mirus and Eric Jones provided constructive reviews for an earlier version of this Data Release. The following citations relate to this Data Release: Bawiec, W.J. (1998). Geology, Geochemistry, Geophysics, Mineral Occurrences and Mineral Resource Assessment for the Commonwealth of Puerto Rico (Open-File Report 98-38). Reston, VA: U.S. Geological Survey. https://doi.org/10.3133/ofr9838 Beckman Coulter, Inc. (2011). LS 13 32 Laser Diffraction Particle Size Analyzer Operator’s Manual. Brea, CA: Beckman Coulter, Inc. Available at: https://www.beckmancoulter.com/wsrportal/techdocs?docname=B05577AB.pdf Decagon Devices, Inc.; now Meter Environment Group, Inc. (2016). DualHead Infiltrometer Operator’s Manual. Pullman, WA: Decagon Devices, Inc. Available at: http://manuals.decagon.com/Retired%20and%20Discontinued/Manuals/14968_DHInfiltr ometer_Web.pdf Decagon Devices, Inc.; now Meter Environment Group, Inc. (2018). Mini Disk Infiltrometer Operator’s Manual. Pullman, WA: Decagon Devices, Inc. Available at: http://library.metergroup.com/Manuals/10564_Mini%20Disk%20Infiltrometer_Web.pdf Gee G.W., & Or D. (2002). Particle size analysis. In: Dane, J.H., & Topp, G.C. (Eds), Methods of Soil Analysis, Part 4-Physical Methods, Soil Science Society of America Book Series, Volume 5 (pp. 255-293). Madison, WA: Soil Science Society of America. Nimmo, J.R., Schmidt, K.M., Perkins, K.S., & Stock, J.D. (2009). Rapid measurement of field- saturated hydraulic conductivity for areal characterization. Vadose Zone Journal, 8(1), 142-149. https://doi.org/10.2136/vzj2007.0159 Soil Moisture, Inc. (2012). 2800K1 Guelph Permeameter Operating Instructions. Santa Barbara, CA: Soil Moisture, Inc. Available at: https://www.soilmoisture.com
At-site Flood Frequency PeakFQ Estimates in Puerto Rico Through Water Year 2017
공공데이터포털
The magnitude and frequency of floods at 91 rural, unregulated streamgages in Puerto Rico were updated using annual peak-flows through 2017. The USGS program PeakFQ version 7.3 (U.S. Geological Survey, 2019) was used to estimate the parameters of the Log-Pearson Type III distribution using updated methods outlined in Bulletin 17C (England and others, 2018) and regional skew of 0.28 and a mean-squared error of 0.20. This data release includes (1) a spreadsheet file showing streamgage information, perception thresholds, and intervals used in PeakFQ; (2) raw input files (.txt) and spec file (.psf) loaded into PeakFQ; and (3) output files (.PRT) from PeakFQ showing the magnitude and frequency peak-flow estimates, as well as paramters of the Log-Pearson Type III distribution and Kendall's tau trend test. References Cited: U.S. Geological Survey, 2019, PeakFQ version 7.3, accessed December 17, 2019, at https://water.usgs.gov/software/PeakFQ/. 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.
At-site Flood Frequency PeakFQ Estimates in Puerto Rico Through Water Year 2017
공공데이터포털
The magnitude and frequency of floods at 91 rural, unregulated streamgages in Puerto Rico were updated using annual peak-flows through 2017. The USGS program PeakFQ version 7.3 (U.S. Geological Survey, 2019) was used to estimate the parameters of the Log-Pearson Type III distribution using updated methods outlined in Bulletin 17C (England and others, 2018) and regional skew of 0.28 and a mean-squared error of 0.20. This data release includes (1) a spreadsheet file showing streamgage information, perception thresholds, and intervals used in PeakFQ; (2) raw input files (.txt) and spec file (.psf) loaded into PeakFQ; and (3) output files (.PRT) from PeakFQ showing the magnitude and frequency peak-flow estimates, as well as paramters of the Log-Pearson Type III distribution and Kendall's tau trend test. References Cited: U.S. Geological Survey, 2019, PeakFQ version 7.3, accessed December 17, 2019, at https://water.usgs.gov/software/PeakFQ/. 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.
Hillslope hydrologic monitoring data following Hurricane Maria in 2017, Puerto Rico, July 2018 to June 2020
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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
Hillslope hydrologic monitoring data following Hurricane Maria in 2017, Puerto Rico, July 2018 to June 2020
공공데이터포털
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
Data release: Flood and Storm Tracker (FaST) data
공공데이터포털
This product summarizes data used in the analysis portion of our Flood and Storm Tracker (FaST) manuscript (see larger work citation). The dataset titled HUCsppMatrices2012-2022.csv has each Hydraulic Unit Code (HUC) with an introduced taxon in each storm and the HUC it connected to by flood waters (lateral or longitudinal). The dataset titled ConnectionPoints_2012-2022.csv has each lateral (not longitudinal or downstream) connection point for each storm event. The dataset titled LongitudinalConnectionPoints_2012-2022.csv has each longitudinal or downstream connection point for each storm event.