William H. Asquith
William has about 34 years at the USGS encompassing a wide range of algorithms and statistical and extreme value frequency studies of meteorology, surface water hydrology, and other water resources topics such as data acquisition, hydraulics, hydrologic regionalization, and research mentoring on statistical methods and algorithms.
Recent (2016–2026) research includes copula methods and algorithms; exceptionally low annual exceedance probability (AEP) flood events; regulated flood-frequency approaches; N-day volumetric flood frequency bias correction for all of US and Territories; statistics of USGS discharge measurements; technical advising on probable maximum precipitation in Texas and New Mexico-Colorado; flood- and rainfall-hazards for the Qashqadaryo Region, Uzbekistan, including defining an equal-area grid for Central Asian studies; small watershed hydrometeorological station operation; missing-record estimation; real-time uncertainty forecasting for hydrometeorological stations, and groundwater level informatics and machine-learning applications for prediction of monthly water-level grids for the Mississippi River Valley alluvial aquifer underlying the Mississippi River Alluvial Plain and Chicot aquifer, southwestern Louisiana; long-term trend analyses of daily salinity predictions for 91 monitoring locations in bays and estuaries of the gulf coast with statistical methods including Cubist, Randomforest, and Support Vector Machines; Texas lake-evaporation validation by probabilistic methods (linear moments); and reduction in USGS staffing efforts in groundwater monitoring with minimization of loss of information content from the Louisiana network.
Recent cooperators include Gulf Coast Ecosystem Restoration Council, Environment Agency – Abu Dhabi (2016−18) and Ministry of Ecology, Environmental Protection and Climate Change for the Republic of Uzbekistan (2021−26) via USGS Office of International Programs, Texas Commission on Environmental Quality, Texas Department of Transportation, Texas Water Development Board, U.S. Army Corps of Engineers, U.S. Nuclear Regulatory Commission, and USGS Office of Quality Assurance.
Thrice featured four-city speaker in 2016, 2017, and 2018 in Bolivia for Universidad Catolica Boliviana and U.S. State Department, and USGS Surfacewater Mission co-lead to Uzbekistan (June 2022, April 2024, September 2024).
Education and Certifications
Institution: Texas Tech University (TTU), College of Engineering, Lubbock, 2008–2011
Degree: Ph.D. (Civil Engineering, May 2011)Institution: University of Texas at Austin, Jackson School of Geosciences, Geoscience, 1998–2003
Degree: Ph.D. (Geosciences, May 2003)Institution: University of Texas at Austin, College of Engineering, 1988–1994
Degrees: B.S. (Civil Engineering, Dec. 1992); M.S. (Civil Engineering, May 1994)
Affiliations and Memberships*
Professional Geoscientist no. 1494, State of Texas 2003–present
Science and Products
Filter Total Items: 70
Application of a workflow to determine the feasibility of using simulated streamflow for estimation of streamflow frequency statistics Application of a workflow to determine the feasibility of using simulated streamflow for estimation of streamflow frequency statistics
Streamflow records from hydrologic models are attractive for use in operational hydrology, such as a streamflow frequency analysis. The amount of bias inherent to simulated streamflow from hydrologic models is often unknown, but it is likely present in derivative products. Therefore, a workflow may help determine where streamflow frequency analysis is credibly feasible from simulated...
Authors
Amanda Whaling, Kelly Sanks, William H. Asquith, Kirk D. Rodgers
Use of Doppler velocity radars to monitor and predict debris and flood wave velocities and travel times in post-wildfire basins Use of Doppler velocity radars to monitor and predict debris and flood wave velocities and travel times in post-wildfire basins
The magnitude and timing of extreme events such as debris and floodflows (collectively referred to as floodflows) in post-wildfire basins are difficult to measure and are even more difficult to predict. To address this challenge, a sensor ensemble consisting of noncontact, ground-based (near-field), Doppler velocity (velocity) and pulsed (stage or gage height) radars, rain gages, and a...
Authors
John W, Fulton, Nicholas Graff Hall, Laura A. Hempel, J.J. Gourley, Mark F. Henneberg, Michael S. Kohn, William H. Farmer, William H. Asquith, Daniel Wasielewski, Andrew S. Stecklein, Amanullah Mommandi, Aziz Khan
System-scale airborne electromagnetic surveys in the lower Mississippi River Valley support multidisciplinary applications System-scale airborne electromagnetic surveys in the lower Mississippi River Valley support multidisciplinary applications
The lower Mississippi River Valley spans over 200,000 square kilometres in parts of seven states, encompassing areas of critical groundwater supplies, natural hazards, infrastructure, and low-lying coastal regions. From 2018 - 2022, the U.S. Geological Survey acquired over 82,000 line-kilometres of airborne electromagnetic, radiometric, and magnetic data over this region to provide...
Authors
Burke J. Minsley, Ryan F. Adams, William H. Asquith, Bethany L. Burton, Bennett Eugene Hoogenboom, Stephanie R. James, Courtney D. Killian, Katherine J. Knierim, Wade H. Kress, Maxwell A. Lindaman, Andrew T. Leaf, James R. Rigby, Jonathan P. Traylor
Simulation of monthly mean and monthly base flow of streamflow using random forests for the Mississippi River Alluvial Plain, 1901 to 2018 Simulation of monthly mean and monthly base flow of streamflow using random forests for the Mississippi River Alluvial Plain, 1901 to 2018
Improved simulations of streamflow and base flow for selected sites within and adjacent to the Mississippi River Alluvial Plain area are important for modeling groundwater flow because surface-water flows have a substantial effect on groundwater levels. One method for simulating streamflow and base flow, random forest (RF) models, was developed from the data at gaged sites and, in turn...
Authors
Benjamin J. Dietsch, William H. Asquith, Brian Breaker, Stephen M. Westenbroek, Wade H. Kress
Generalized additive model estimation of no-flow fractions and L-moments to support flow-duration curve quantile estimation using selected probability distributions for bay and estuary restoration in the Gulf States Generalized additive model estimation of no-flow fractions and L-moments to support flow-duration curve quantile estimation using selected probability distributions for bay and estuary restoration in the Gulf States
Censored and uncensored generalized additive models (GAMs) were developed using streamflow data from 941 U.S. Geological Survey streamflow-gaging stations (streamgages) to predict decadal statistics of daily streamflow for streams draining to the Gulf of Mexico. The modeled decadal statistics comprise no-flow fractions and L-moments of logarithms of nonzero streamflow for six decades...
Authors
Elena Crowley-Ornelas, William H. Asquith, Scott C. Worland
Technique to estimate generalized skew coefficients of annual peak streamflow for natural watershed conditions in Texas, Oklahoma, and eastern New Mexico Technique to estimate generalized skew coefficients of annual peak streamflow for natural watershed conditions in Texas, Oklahoma, and eastern New Mexico
Reliable information about the frequency of annual peak streamflow is needed for floodplain management, objective assessment of flood risk, and cost-effective design of dams, levees, other flood-control structures, and roads, bridges, and culverts. Generalized skew coefficients are among the data needed for log-Pearson type III peak-streamflow frequency analyses of annual peak...
Authors
William H. Asquith, Monica Veale Yesildirek, Raven N. Landers, Theodore G Cleveland, Zheng N. Fang, Jiaqi Zhang
Modeling and Projecting the Influence of Climate Change on Texas Surface Waters and their Aquatic Biotic Communities
Water scarcity is a growing concern in Texas, where surface water is derived almost entirely from rainfall. Changes in air temperature and precipitation patterns associated with global climate change are anticipated to regionally affect the quality and quantity of inland surface waters and consequently their suitability as habitat for freshwater life. In addition to directly affecting...
Filter Total Items: 48
Statistical predictions of groundwater levels and related spatial diagnostics for a hydrogeologic framework of the Chicot aquifer system, southwestern Louisiana, 1983–2023, from the mmlCHICOTla statistical research software Statistical predictions of groundwater levels and related spatial diagnostics for a hydrogeologic framework of the Chicot aquifer system, southwestern Louisiana, 1983–2023, from the mmlCHICOTla statistical research software
Results of predicted groundwater levels and related spatial diagnostics, produced by an applied prediction-modeling statistical-research workflow, are provided as multi-banded GeoTIFF rasters for two custom bundles (classifications) of local aquifer codes for many thousands of wells in the hydrogeologically complex Chicot aquifer system, southwestern Louisiana. The modeling workflow was...
Statistical predictions of typical well depths and related spatial diagnostics for two hydrogeologic frameworks through blending cubist and generalized additive statistical models for the Chicot aquifer system, southwestern Louisiana, from the covCHICOTla Statistical predictions of typical well depths and related spatial diagnostics for two hydrogeologic frameworks through blending cubist and generalized additive statistical models for the Chicot aquifer system, southwestern Louisiana, from the covCHICOTla
This data release provides gridded predictions of “typical” well depth for the hydrogeologically complex Chicot aquifer system, southwestern Louisiana. These predictions were made using an applied statistical prediction modeling workflow named welldepmod_make.R (Asquith and Lindaman, 2025) to estimate groundwater well depths for two custom bundles (classifications) of local aquifer codes...
Simulated Snow and Meteorology Variables, Qashqadaryo Region, Uzbekistan, 1950-2023 Simulated Snow and Meteorology Variables, Qashqadaryo Region, Uzbekistan, 1950-2023
This data release contains output from a numerical snow simulation for a 166 kilometer (km) × 160 km model domain in the Qashqadaryo region of Uzbekistan. The simulation encompasses key watersheds within the region and uses SnowModel (Liston and Elder, 2006; Liston and others, 2020; Liston, 2020) to estimate the snow water resources and meteorology across the simulation domain. The...
Datasets used to map the potentiometric surface and depth to water, spring 2022, Mississippi River Valley alluvial aquifer Datasets used to map the potentiometric surface and depth to water, spring 2022, Mississippi River Valley alluvial aquifer
Potentiometric-surface and depth-to-water maps for spring 2022 were created for the Mississippi River Valley alluvial aquifer (MRVA) using most of the available groundwater-altitude data from wells and surface-water-altitude data from streamgages. The potentiometric surface was referenced to the North American Vertical Datum of 1988 (NAVD 88), This data release contains (1) the location...
The Central Asia Equal Area Projection and Model Grid The Central Asia Equal Area Projection and Model Grid
The Central Asia Equal Area Projection and Model Grid (CAEAP-MG) dataset includes raster and vector representations of 1-km cells defining a uniform equal-area grid encompassing the Republics of Kazakhstan, Kyrgyzstan, Tajikistan, Turkmenistan, and Uzbekistan. The grid is extended south into Afghanistan for purposes of encompassing the northward drainages into Central Asia including the...
Monotonic trend computations for streamflow statistics within and near the Mobile Bay and Perdido Bay watersheds, United States, 1950–2022 Monotonic trend computations for streamflow statistics within and near the Mobile Bay and Perdido Bay watersheds, United States, 1950–2022
This data release provides comprehensive results of monotonic trend assessment for long-term U.S. Geological Survey (USGS) streamgages in or proximal to the watersheds of Mobile and Perdido Bays, south-central United States (Tatum and others, 2024). Long-term is defined as streamgages having at least five complete decades of daily streamflow data since January 1, 1950, exclusive to those
Altitude of the potentiometric surface and depth to water in the Mississippi River Valley alluvial aquifer, spring 2022 Altitude of the potentiometric surface and depth to water in the Mississippi River Valley alluvial aquifer, spring 2022
Potentiometric-surface and depth-to-water maps for spring 2022 were created for the Mississippi River Valley alluvial aquifer (MRVA) using groundwater-altitude data from 1,136 wells completed in the MRVA and from the altitude of the top of the water surface in area rivers from 160 streamgages. The potentiometric-surface and depth-to-water maps for 2022 were created to support...
Altitude of the potentiometric surface in the Mississippi River Valley alluvial aquifer, spring 2020 Altitude of the potentiometric surface in the Mississippi River Valley alluvial aquifer, spring 2020
The purpose of this report is to present a potentiometric-surface map for the Mississippi River Valley alluvial aquifer (MRVA). The source data for the map were groundwater-altitude data from wells measured manually or continuously generally in spring 2020 and from the altitude of the top of the water surface measured generally on April 9, 2020, in rivers in the area.
Altitude of the potentiometric surface in the Mississippi River Valley alluvial aquifer, spring 2018 Altitude of the potentiometric surface in the Mississippi River Valley alluvial aquifer, spring 2018
A potentiometric-surface map for spring 2018 was created for the Mississippi River Valley alluvial (MRVA) aquifer using available groundwater-altitude data from 1,126 wells completed in the MRVA aquifer and from the altitude of the top of the water surface in area rivers from 66 streamgages. Personnel from Arkansas Natural Resources Commission, Arkansas Department of Health, Arkansas...
Potentiometric surface of the Mississippi River Valley alluvial aquifer, spring 2016 Potentiometric surface of the Mississippi River Valley alluvial aquifer, spring 2016
A potentiometric surface map for spring 2016 was created for the Mississippi River Valley alluvial (MRVA) aquifer using selected available groundwater-altitude data from wells and surface-water-altitude data from streamgages. Most of the wells were measured annually or one time after installation, but some wells were measured more than one time or continually; streamgages are typically...
Filter Total Items: 22
mmlCHICOTla, Source code for construction and implementation of multiple machine-learning models of water levels in the Chicot aquifer system, southwestern Louisiana mmlCHICOTla, Source code for construction and implementation of multiple machine-learning models of water levels in the Chicot aquifer system, southwestern Louisiana
The mmlCHICOTla repository contains R, Mermaid, and Perl language source code that can be used for construction multiple methods of machine learning (MML) of water levels in the Chicot aquifer system, southwestern Louisiana. The source code is written in R (primary and extensive), Mermaid (workflow diagrams), and Perl (minor utility for simple implementation of parallel processing on...
Research software technical note and source code for creation of statistical models for prediction of typical well depths and related spatial diagnostics for the Chicot aquifer system, southwestern Louisiana Research software technical note and source code for creation of statistical models for prediction of typical well depths and related spatial diagnostics for the Chicot aquifer system, southwestern Louisiana
This "software technical note" (`TECHNOTE.md`) provides extensive details involving the construction of typical well-depth grids from research-grade statistical study of the Chicot aquifer system. The README also within this directory is designed and intended to parallel the documentation of individual covariate construction as part of the primal feature of the **covCHICOTla** software...
covCHICOTla, Source code for construction of covariates bound to monthly groundwater levels for statistical modeling of water levels in the Chicot aquifer system, southwestern Louisiana covCHICOTla, Source code for construction of covariates bound to monthly groundwater levels for statistical modeling of water levels in the Chicot aquifer system, southwestern Louisiana
The covCHICOTla repository contains primarily R and limited Mermaid, Perl, and Python language source code that collectively can be used for the construction of many tables of monthly groundwater levels (response variable) and predictor variables (covariates) intended to be inputs to statistical modeling of water levels in the Chicot aquifer system, southwestern Louisiana. The source...
mmlMRVAgen1, Source Code for Construction of Multiple Machine-Learning Models of Water Levels in the Mississippi River Valley Alluvial Aquifer mmlMRVAgen1, Source Code for Construction of Multiple Machine-Learning Models of Water Levels in the Mississippi River Valley Alluvial Aquifer
The mmlMRVAgen1 repository contains R, LaTeX, Mermaid, and Perl language source code that can be used for construction multiple methods of machine learning (MML) of water levels in the Mississippi River Valley alluvial aquifer (MRVA) within the Mississippi Alluvial Plain (MAP), south-central United States. The source code is written in R (primary and extensive), LaTeX (for structured...
syntheticdv2lff, Scripts for low-flow frequency (LFF) estimation (and bias correction) from daily mean streamflow estimated at level-12 hydrologic unit code (HUC12) pour points in the southeastern United States syntheticdv2lff, Scripts for low-flow frequency (LFF) estimation (and bias correction) from daily mean streamflow estimated at level-12 hydrologic unit code (HUC12) pour points in the southeastern United States
The syntheticdv2lff repository contains R language source code that document the workflow to compute low-streamflow (low-flow) frequency (LFF) statistics from previously estimated streamflow at level-12 hydrologic unit code (HUC12) pour points (watershed outlet locations) in the south-central and southeastern United States for 1950 through 2010 and associated bias correction. LFF...
syntheticdv2lff, Scripts for low-flow frequency (LFF) estimation (and bias correction) from daily mean streamflow estimated at level-12 hydrologic unit code (HUC12) pour points in the southeastern United States syntheticdv2lff, Scripts for low-flow frequency (LFF) estimation (and bias correction) from daily mean streamflow estimated at level-12 hydrologic unit code (HUC12) pour points in the southeastern United States
The syntheticdv2lff repository contains R language source code that document the workflow to compute low-streamflow (low-flow) frequency (LFF) statistics from previously estimated streamflow at level-12 hydrologic unit code (HUC12) pour points (watershed outlet locations) in the south-central and southeastern United States for 1950 through 2010 and associated bias correction. LFF...
Science and Products
Filter Total Items: 70
Application of a workflow to determine the feasibility of using simulated streamflow for estimation of streamflow frequency statistics Application of a workflow to determine the feasibility of using simulated streamflow for estimation of streamflow frequency statistics
Streamflow records from hydrologic models are attractive for use in operational hydrology, such as a streamflow frequency analysis. The amount of bias inherent to simulated streamflow from hydrologic models is often unknown, but it is likely present in derivative products. Therefore, a workflow may help determine where streamflow frequency analysis is credibly feasible from simulated...
Authors
Amanda Whaling, Kelly Sanks, William H. Asquith, Kirk D. Rodgers
Use of Doppler velocity radars to monitor and predict debris and flood wave velocities and travel times in post-wildfire basins Use of Doppler velocity radars to monitor and predict debris and flood wave velocities and travel times in post-wildfire basins
The magnitude and timing of extreme events such as debris and floodflows (collectively referred to as floodflows) in post-wildfire basins are difficult to measure and are even more difficult to predict. To address this challenge, a sensor ensemble consisting of noncontact, ground-based (near-field), Doppler velocity (velocity) and pulsed (stage or gage height) radars, rain gages, and a...
Authors
John W, Fulton, Nicholas Graff Hall, Laura A. Hempel, J.J. Gourley, Mark F. Henneberg, Michael S. Kohn, William H. Farmer, William H. Asquith, Daniel Wasielewski, Andrew S. Stecklein, Amanullah Mommandi, Aziz Khan
System-scale airborne electromagnetic surveys in the lower Mississippi River Valley support multidisciplinary applications System-scale airborne electromagnetic surveys in the lower Mississippi River Valley support multidisciplinary applications
The lower Mississippi River Valley spans over 200,000 square kilometres in parts of seven states, encompassing areas of critical groundwater supplies, natural hazards, infrastructure, and low-lying coastal regions. From 2018 - 2022, the U.S. Geological Survey acquired over 82,000 line-kilometres of airborne electromagnetic, radiometric, and magnetic data over this region to provide...
Authors
Burke J. Minsley, Ryan F. Adams, William H. Asquith, Bethany L. Burton, Bennett Eugene Hoogenboom, Stephanie R. James, Courtney D. Killian, Katherine J. Knierim, Wade H. Kress, Maxwell A. Lindaman, Andrew T. Leaf, James R. Rigby, Jonathan P. Traylor
Simulation of monthly mean and monthly base flow of streamflow using random forests for the Mississippi River Alluvial Plain, 1901 to 2018 Simulation of monthly mean and monthly base flow of streamflow using random forests for the Mississippi River Alluvial Plain, 1901 to 2018
Improved simulations of streamflow and base flow for selected sites within and adjacent to the Mississippi River Alluvial Plain area are important for modeling groundwater flow because surface-water flows have a substantial effect on groundwater levels. One method for simulating streamflow and base flow, random forest (RF) models, was developed from the data at gaged sites and, in turn...
Authors
Benjamin J. Dietsch, William H. Asquith, Brian Breaker, Stephen M. Westenbroek, Wade H. Kress
Generalized additive model estimation of no-flow fractions and L-moments to support flow-duration curve quantile estimation using selected probability distributions for bay and estuary restoration in the Gulf States Generalized additive model estimation of no-flow fractions and L-moments to support flow-duration curve quantile estimation using selected probability distributions for bay and estuary restoration in the Gulf States
Censored and uncensored generalized additive models (GAMs) were developed using streamflow data from 941 U.S. Geological Survey streamflow-gaging stations (streamgages) to predict decadal statistics of daily streamflow for streams draining to the Gulf of Mexico. The modeled decadal statistics comprise no-flow fractions and L-moments of logarithms of nonzero streamflow for six decades...
Authors
Elena Crowley-Ornelas, William H. Asquith, Scott C. Worland
Technique to estimate generalized skew coefficients of annual peak streamflow for natural watershed conditions in Texas, Oklahoma, and eastern New Mexico Technique to estimate generalized skew coefficients of annual peak streamflow for natural watershed conditions in Texas, Oklahoma, and eastern New Mexico
Reliable information about the frequency of annual peak streamflow is needed for floodplain management, objective assessment of flood risk, and cost-effective design of dams, levees, other flood-control structures, and roads, bridges, and culverts. Generalized skew coefficients are among the data needed for log-Pearson type III peak-streamflow frequency analyses of annual peak...
Authors
William H. Asquith, Monica Veale Yesildirek, Raven N. Landers, Theodore G Cleveland, Zheng N. Fang, Jiaqi Zhang
Modeling and Projecting the Influence of Climate Change on Texas Surface Waters and their Aquatic Biotic Communities
Water scarcity is a growing concern in Texas, where surface water is derived almost entirely from rainfall. Changes in air temperature and precipitation patterns associated with global climate change are anticipated to regionally affect the quality and quantity of inland surface waters and consequently their suitability as habitat for freshwater life. In addition to directly affecting...
Filter Total Items: 48
Statistical predictions of groundwater levels and related spatial diagnostics for a hydrogeologic framework of the Chicot aquifer system, southwestern Louisiana, 1983–2023, from the mmlCHICOTla statistical research software Statistical predictions of groundwater levels and related spatial diagnostics for a hydrogeologic framework of the Chicot aquifer system, southwestern Louisiana, 1983–2023, from the mmlCHICOTla statistical research software
Results of predicted groundwater levels and related spatial diagnostics, produced by an applied prediction-modeling statistical-research workflow, are provided as multi-banded GeoTIFF rasters for two custom bundles (classifications) of local aquifer codes for many thousands of wells in the hydrogeologically complex Chicot aquifer system, southwestern Louisiana. The modeling workflow was...
Statistical predictions of typical well depths and related spatial diagnostics for two hydrogeologic frameworks through blending cubist and generalized additive statistical models for the Chicot aquifer system, southwestern Louisiana, from the covCHICOTla Statistical predictions of typical well depths and related spatial diagnostics for two hydrogeologic frameworks through blending cubist and generalized additive statistical models for the Chicot aquifer system, southwestern Louisiana, from the covCHICOTla
This data release provides gridded predictions of “typical” well depth for the hydrogeologically complex Chicot aquifer system, southwestern Louisiana. These predictions were made using an applied statistical prediction modeling workflow named welldepmod_make.R (Asquith and Lindaman, 2025) to estimate groundwater well depths for two custom bundles (classifications) of local aquifer codes...
Simulated Snow and Meteorology Variables, Qashqadaryo Region, Uzbekistan, 1950-2023 Simulated Snow and Meteorology Variables, Qashqadaryo Region, Uzbekistan, 1950-2023
This data release contains output from a numerical snow simulation for a 166 kilometer (km) × 160 km model domain in the Qashqadaryo region of Uzbekistan. The simulation encompasses key watersheds within the region and uses SnowModel (Liston and Elder, 2006; Liston and others, 2020; Liston, 2020) to estimate the snow water resources and meteorology across the simulation domain. The...
Datasets used to map the potentiometric surface and depth to water, spring 2022, Mississippi River Valley alluvial aquifer Datasets used to map the potentiometric surface and depth to water, spring 2022, Mississippi River Valley alluvial aquifer
Potentiometric-surface and depth-to-water maps for spring 2022 were created for the Mississippi River Valley alluvial aquifer (MRVA) using most of the available groundwater-altitude data from wells and surface-water-altitude data from streamgages. The potentiometric surface was referenced to the North American Vertical Datum of 1988 (NAVD 88), This data release contains (1) the location...
The Central Asia Equal Area Projection and Model Grid The Central Asia Equal Area Projection and Model Grid
The Central Asia Equal Area Projection and Model Grid (CAEAP-MG) dataset includes raster and vector representations of 1-km cells defining a uniform equal-area grid encompassing the Republics of Kazakhstan, Kyrgyzstan, Tajikistan, Turkmenistan, and Uzbekistan. The grid is extended south into Afghanistan for purposes of encompassing the northward drainages into Central Asia including the...
Monotonic trend computations for streamflow statistics within and near the Mobile Bay and Perdido Bay watersheds, United States, 1950–2022 Monotonic trend computations for streamflow statistics within and near the Mobile Bay and Perdido Bay watersheds, United States, 1950–2022
This data release provides comprehensive results of monotonic trend assessment for long-term U.S. Geological Survey (USGS) streamgages in or proximal to the watersheds of Mobile and Perdido Bays, south-central United States (Tatum and others, 2024). Long-term is defined as streamgages having at least five complete decades of daily streamflow data since January 1, 1950, exclusive to those
Altitude of the potentiometric surface and depth to water in the Mississippi River Valley alluvial aquifer, spring 2022 Altitude of the potentiometric surface and depth to water in the Mississippi River Valley alluvial aquifer, spring 2022
Potentiometric-surface and depth-to-water maps for spring 2022 were created for the Mississippi River Valley alluvial aquifer (MRVA) using groundwater-altitude data from 1,136 wells completed in the MRVA and from the altitude of the top of the water surface in area rivers from 160 streamgages. The potentiometric-surface and depth-to-water maps for 2022 were created to support...
Altitude of the potentiometric surface in the Mississippi River Valley alluvial aquifer, spring 2020 Altitude of the potentiometric surface in the Mississippi River Valley alluvial aquifer, spring 2020
The purpose of this report is to present a potentiometric-surface map for the Mississippi River Valley alluvial aquifer (MRVA). The source data for the map were groundwater-altitude data from wells measured manually or continuously generally in spring 2020 and from the altitude of the top of the water surface measured generally on April 9, 2020, in rivers in the area.
Altitude of the potentiometric surface in the Mississippi River Valley alluvial aquifer, spring 2018 Altitude of the potentiometric surface in the Mississippi River Valley alluvial aquifer, spring 2018
A potentiometric-surface map for spring 2018 was created for the Mississippi River Valley alluvial (MRVA) aquifer using available groundwater-altitude data from 1,126 wells completed in the MRVA aquifer and from the altitude of the top of the water surface in area rivers from 66 streamgages. Personnel from Arkansas Natural Resources Commission, Arkansas Department of Health, Arkansas...
Potentiometric surface of the Mississippi River Valley alluvial aquifer, spring 2016 Potentiometric surface of the Mississippi River Valley alluvial aquifer, spring 2016
A potentiometric surface map for spring 2016 was created for the Mississippi River Valley alluvial (MRVA) aquifer using selected available groundwater-altitude data from wells and surface-water-altitude data from streamgages. Most of the wells were measured annually or one time after installation, but some wells were measured more than one time or continually; streamgages are typically...
Filter Total Items: 22
mmlCHICOTla, Source code for construction and implementation of multiple machine-learning models of water levels in the Chicot aquifer system, southwestern Louisiana mmlCHICOTla, Source code for construction and implementation of multiple machine-learning models of water levels in the Chicot aquifer system, southwestern Louisiana
The mmlCHICOTla repository contains R, Mermaid, and Perl language source code that can be used for construction multiple methods of machine learning (MML) of water levels in the Chicot aquifer system, southwestern Louisiana. The source code is written in R (primary and extensive), Mermaid (workflow diagrams), and Perl (minor utility for simple implementation of parallel processing on...
Research software technical note and source code for creation of statistical models for prediction of typical well depths and related spatial diagnostics for the Chicot aquifer system, southwestern Louisiana Research software technical note and source code for creation of statistical models for prediction of typical well depths and related spatial diagnostics for the Chicot aquifer system, southwestern Louisiana
This "software technical note" (`TECHNOTE.md`) provides extensive details involving the construction of typical well-depth grids from research-grade statistical study of the Chicot aquifer system. The README also within this directory is designed and intended to parallel the documentation of individual covariate construction as part of the primal feature of the **covCHICOTla** software...
covCHICOTla, Source code for construction of covariates bound to monthly groundwater levels for statistical modeling of water levels in the Chicot aquifer system, southwestern Louisiana covCHICOTla, Source code for construction of covariates bound to monthly groundwater levels for statistical modeling of water levels in the Chicot aquifer system, southwestern Louisiana
The covCHICOTla repository contains primarily R and limited Mermaid, Perl, and Python language source code that collectively can be used for the construction of many tables of monthly groundwater levels (response variable) and predictor variables (covariates) intended to be inputs to statistical modeling of water levels in the Chicot aquifer system, southwestern Louisiana. The source...
mmlMRVAgen1, Source Code for Construction of Multiple Machine-Learning Models of Water Levels in the Mississippi River Valley Alluvial Aquifer mmlMRVAgen1, Source Code for Construction of Multiple Machine-Learning Models of Water Levels in the Mississippi River Valley Alluvial Aquifer
The mmlMRVAgen1 repository contains R, LaTeX, Mermaid, and Perl language source code that can be used for construction multiple methods of machine learning (MML) of water levels in the Mississippi River Valley alluvial aquifer (MRVA) within the Mississippi Alluvial Plain (MAP), south-central United States. The source code is written in R (primary and extensive), LaTeX (for structured...
syntheticdv2lff, Scripts for low-flow frequency (LFF) estimation (and bias correction) from daily mean streamflow estimated at level-12 hydrologic unit code (HUC12) pour points in the southeastern United States syntheticdv2lff, Scripts for low-flow frequency (LFF) estimation (and bias correction) from daily mean streamflow estimated at level-12 hydrologic unit code (HUC12) pour points in the southeastern United States
The syntheticdv2lff repository contains R language source code that document the workflow to compute low-streamflow (low-flow) frequency (LFF) statistics from previously estimated streamflow at level-12 hydrologic unit code (HUC12) pour points (watershed outlet locations) in the south-central and southeastern United States for 1950 through 2010 and associated bias correction. LFF...
syntheticdv2lff, Scripts for low-flow frequency (LFF) estimation (and bias correction) from daily mean streamflow estimated at level-12 hydrologic unit code (HUC12) pour points in the southeastern United States syntheticdv2lff, Scripts for low-flow frequency (LFF) estimation (and bias correction) from daily mean streamflow estimated at level-12 hydrologic unit code (HUC12) pour points in the southeastern United States
The syntheticdv2lff repository contains R language source code that document the workflow to compute low-streamflow (low-flow) frequency (LFF) statistics from previously estimated streamflow at level-12 hydrologic unit code (HUC12) pour points (watershed outlet locations) in the south-central and southeastern United States for 1950 through 2010 and associated bias correction. LFF...
*Disclaimer: Listing outside positions with professional scientific organizations on this Staff Profile are for informational purposes only and do not constitute an endorsement of those professional scientific organizations or their activities by the USGS, Department of the Interior, or U.S. Government