William H. Asquith
William has more than 28 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, and hydrologic regionalization.
Present (2016–2021) research includes exceptionally low annual exceedance probability (AEP) flood events, regulated flood-frequency, documentable climate-cycle impacts on flood-risk assessment, statistics of USGS discharge measurements, recent technical advisor on probable maximum precipitation in Texas, small watershed hydrometeorological stations, missing record estimation, real-time uncertainty forecasting for hydrometeorological stations, and groundwater level informatics and machine learning applications.
Recent cooperators include Gulf Coast Ecosystem Restoration Council, Environment Agency – Abu Dhabi via USGS Office of International Programs, Texas Commission on Environmental Quality, Texas Department of Transportation, 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.
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
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: 45
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...
Streamflow recession indices computed by automation within and proximal to the Mobile Bay and Perdido Bay watersheds, south-central United States Streamflow recession indices computed by automation within and proximal to the Mobile Bay and Perdido Bay watersheds, south-central United States
This data release presents streamflow recession analyses and supporting statistics for 164 U.S. Geological Survey (USGS) streamgages located in or near the watersheds of Mobile and Perdido Bays in the south-central United States (see Tatum and others, 2024). Streamgages were selected based on a minimum of two complete decades of daily streamflow data since January 1, 1950, with the...
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...
Statistical predictions of groundwater levels and related spatial diagnostics for the Mississippi River Valley alluvial aquifer from the mmlMRVAgen1 statistical machine-learning software Statistical predictions of groundwater levels and related spatial diagnostics for the Mississippi River Valley alluvial aquifer from the mmlMRVAgen1 statistical machine-learning software
A multiple machine-learning model (Asquith and Killian, 2024) implementing Cubist and Random Forest regressions was used to predict monthly mean groundwater levels through time for the available years described in the metadata for the Mississippi River Valley alluvial aquifer (MRVA). The MRVA is the surficial aquifer of the Mississippi Alluvial Plain (MAP), located in the south-central...
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...
Geospatial extent of the study area and additional geospatial buffer for Mobile and Perdido bays contributing watersheds in the southeastern United States Geospatial extent of the study area and additional geospatial buffer for Mobile and Perdido bays contributing watersheds in the southeastern United States
The U.S. Geological Survey (USGS) Lower Mississippi-Gulf Water Science Center (LMGWSC) in collaboration with the U.S. Environmental Protection Agency and funded through the Resources and Ecosystems, Sustainability, Tourist, Opportunities, and Revived Economies of the Gulf Coast States Act (RESTORE Act) are conducting a multiyear multistate study to analyze the alteration and trends of...
Modeled daily salinity derived from multiple machine learning methodologies for 91 salinity monitoring sites in the northern Gulf of Mexico, 1980–2021 Modeled daily salinity derived from multiple machine learning methodologies for 91 salinity monitoring sites in the northern Gulf of Mexico, 1980–2021
This data release consists of statistical predictions of daily salinity time series generated from the makESTUSAL software repository described by Asquith and others (2023b). The statistical methods included multiple methods of machine learning, which produced the daily salinity prediction and attendant credible uncertainties included in the data release. The geographic scope includes...
Modeled daily salinity derived from multiple machine learning methodologies and generalized additive models for three salinity monitoring sites in Mobile Bay, northern Gulf of Mexico, 1980–2021 Modeled daily salinity derived from multiple machine learning methodologies and generalized additive models for three salinity monitoring sites in Mobile Bay, northern Gulf of Mexico, 1980–2021
Results from generalized additive models (GAM), random forest models (RFM), and cubist models (CUB) for three Dauphin Island Sealab (DIS) operated salinity sites in Mobile Bay are reported in this data release. These sites included Meaher Park (DIS:MHPA1), Middle Bay Lighthouse (DIS:MBLA1), and Dauphin Island (DIS:DPIA1). The constructed models predicted a 42-year daily salinity record...
infoGWauxs, Auxiliary methods for infoGW and similar groundwater level data objects and other helpful utilities infoGWauxs, Auxiliary methods for infoGW and similar groundwater level data objects and other helpful utilities
The infoGWauxs package in the R language provides auxiliary methods for data merging, duplicate-record removal, and monthly rollup of groundwater levels in the so-called infoGW or GWmaster data objects. These data structures are particularly well suited for statistical analyses of groundwater levels. This package is part of a greater body of data processors oriented around the infoGW...
Quality assurance of water levels in the Mississippi River Valley alluvial aquifer in Louisiana from the Louisiana Department of Natural Resources' Strategic Online Natural Resources Information System (SONRIS) Quality assurance of water levels in the Mississippi River Valley alluvial aquifer in Louisiana from the Louisiana Department of Natural Resources' Strategic Online Natural Resources Information System (SONRIS)
This data release provides several data files representing groundwater levels reported through driller's reports for the State of Louisiana Department of Natural Resources (Louisiana Department of Natural Resources, 2023) within or near the Mississippi Alluvial Plain (MAP) and (or) associated with the Mississippi River Valley alluvial aquifer (MRVA). First, a retrieval of data from the...
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: 69
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 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 Fulton, Nicholas Hall, Laura Hempel, J.J. Gourley, Mark Henneberg, Michael Kohn, William H. Farmer, William Asquith, Daniel Wasielewski, Andrew Stecklein, Amanullah Mommandi, Aziz Khan
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 Dietsch, William Asquith, Brian K. Breaker, Stephen Westenbroek, Wade 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 Asquith, Scott 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 Asquith, Monica Yesildirek, Raven Landers, Theodore Cleveland, Zheng Fang, Jiaqi Zhang
Regional regression equations for estimation of four hydraulic properties of streams at approximate bankfull conditions for different ecoregions in Texas Regional regression equations for estimation of four hydraulic properties of streams at approximate bankfull conditions for different ecoregions in Texas
The U.S. Geological Survey, in cooperation with the U.S. Army Corps of Engineers, assessed statistical relations between hydraulic properties of streams at approximate bankfull conditions for different ecological regions (ecoregions) in Texas. Data from more than 103,000 records of measured discharge and ancillary hydraulic properties were assembled from summaries of discharge...
Authors
William Asquith, John Gordon, David S. Wallace
Methods to quality assure, plot, summarize, interpolate, and extend groundwater-level information—Examples for the Mississippi River Valley alluvial aquifer Methods to quality assure, plot, summarize, interpolate, and extend groundwater-level information—Examples for the Mississippi River Valley alluvial aquifer
Large-scale computational investigations of groundwater levels are proposed to accelerate science delivery through a workflow spanning database assembly, statistics, and information synthesis and packaging. A water-availability study of the Mississippi River alluvial plain, and particularly the Mississippi River Valley alluvial aquifer (MRVA), is ongoing. Software (visGWDBmrva) has been...
Authors
William Asquith, Ronald Seanor, Virginia McGuire, Wade Kress
The use of support vectors from support vector machines for hydrometeorologic monitoring network analyses The use of support vectors from support vector machines for hydrometeorologic monitoring network analyses
Hydrometeorologic monitoring networks are ubiquitous in contemporary earth-system science. Network stakeholders often inquire about the importance of sites and their locations when discussing funding and monitoring design. Support vector machines (SVMs) can be useful by their assigning each monitoring site as either a support or nonsupport vector. A potentiometric surface was created...
Authors
William Asquith
Copula theory as a generalized framework for flow-duration curve-based streamflow estimates in ungaged and partially gaged catchments Copula theory as a generalized framework for flow-duration curve-based streamflow estimates in ungaged and partially gaged catchments
Flow‐duration curve (FDC) based streamflow estimation methods involve estimating an FDC at an ungaged or partially gaged location and using the time series of nonexceedance probabilities estimated from donor streamgage sites to generate estimates of streamflow. We develop a mathematical framework to illustrate the connection between copulas and prior FDC‐based approaches. The performance...
Authors
Scott Worland, Scott Steinschneider, William H. Farmer, William Asquith, Rodney Knight
Prediction and inference of flow-duration curves using multi-output neural networks Prediction and inference of flow-duration curves using multi-output neural networks
We develop multi-output neural network models (MNNs) to predict flow-duration curves (FDCs) in 9,203 ungaged locations in the Southeastern United States for six decades between 1950-2009. The model architecture contains multiple response variables in the output layer that correspond to individual quantiles along the FDC. During training, predictions are made for each quantile, and a...
Authors
Scott Worland, Scott Steinschneider, William Asquith, Rodney Knight, Michael E. Wieczorek
Characterizing groundwater/surface-water interaction using hydrograph-separation techniques and groundwater-level data throughout the Mississippi Delta, USA Characterizing groundwater/surface-water interaction using hydrograph-separation techniques and groundwater-level data throughout the Mississippi Delta, USA
The Mississippi Delta, located in northwest Mississippi, is an area dense with industrial-level agriculture sustained by groundwater-dependent irrigation supplied by the Mississippi River Valley Alluvial aquifer (alluvial aquifer). The Delta provides agricultural commodities across the United States and around the world. Observed declines in groundwater altitudes and streamflow...
Authors
Courtney Killian, William Asquith, Jeannie Barlow, Gardner C. Bent, Wade Kress, Paul Barlow, Darrel Schmitz
Annual and approximately quarterly series peak streamflow derived from interpretations of indirect measurements for a crest-stage gage network in Texas through water year 2015 Annual and approximately quarterly series peak streamflow derived from interpretations of indirect measurements for a crest-stage gage network in Texas through water year 2015
In 2006, the U.S. Geological Survey (USGS), incooperation with the Texas Department of Transportation,began collecting annual and approximately quarterly seriespeak-streamflow data at streamflow-gaging stations in smalltomedium-sized watersheds in central and western Texasas part of a crest-stage gage (CSG) network, along withselected flood-hydrograph data at a subset of these stations...
Authors
William Asquith, Glenn Harwell, Karl Winters
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...
infoGWauxs, Auxiliary methods for infoGW and similar groundwater level data objects and other helpful utilities infoGWauxs, Auxiliary methods for infoGW and similar groundwater level data objects and other helpful utilities
The infoGWauxs package in the R language provides auxiliary methods for data merging, duplicate-record removal, and monthly rollup of groundwater levels in the so-called infoGW or GWmaster data objects. These data structures are particularly well suited for statistical analyses of groundwater levels. This package is part of a greater body of data processors oriented around the infoGW...
RESTORE/TCEQswqmisESTUSAL, Source code for manipulation of data stemming from the Texas Commission on Environmental Quality Surface Water Quality Monitoring Program with emphasis on salinity change statistics for Texas coastal segments RESTORE/TCEQswqmisESTUSAL, Source code for manipulation of data stemming from the Texas Commission on Environmental Quality Surface Water Quality Monitoring Program with emphasis on salinity change statistics for Texas coastal segments
The RESTORE/TCEQswqmisESTUSAL repository contains R language source code that can be used for digesting data retrieved from the Texas Commission on Environmental Quality Surface Water Quality Monitoring Program through their Surface Water Quality Data Viewer. The workflow described concerns data manipulations, base data filtering, and computations towards documenting long-term salinity...
RESTORE/makESTUSAL, Source code for construction of various statistical models and prediction of daily salinity in coastal regions of the Gulf of Mexico, United States RESTORE/makESTUSAL, Source code for construction of various statistical models and prediction of daily salinity in coastal regions of the Gulf of Mexico, United States
The RESTORE/makESTUSAL software repository contains R language source code that can be used for the construction of various statistical models and output time series of predicted daily salinity coastal regions of the Gulf of Mexico, United States. The source code is expansive, and the repository is organizationally deep following logical organization units. One major subsystem of the...
Simulation and comparison of five estimators of variability in units of standard deviation for small samples drawn from normally distributed data Simulation and comparison of five estimators of variability in units of standard deviation for small samples drawn from normally distributed data
It is convenient to measure or estimate variation in samples or distributions in units of standard deviations. There are alternative methods of estimation of standard deviation aside from the conventional and well-known definition. Estimation of standard deviation for very small samples (as small as two), whereas not always ideal, might be useful in certain practical circumstances. A...
Study of L-kurtosis and several distribution families for prediction of uncertainty distributions, An applied software technical note concerning L-kurtosis use in daily salinity prediction from multiple machine learning methods Study of L-kurtosis and several distribution families for prediction of uncertainty distributions, An applied software technical note concerning L-kurtosis use in daily salinity prediction from multiple machine learning methods
Statistical predictions that are based on multiple machine learning (MML) methods (from including differing training regimes) produce differing predictions. When the predictions are combined to a final estimate, then there are residuals of the predictions spread around the final estimate. It is common to assume normality or near-normality of the residuals (errors), but the assumption of...
RESTORE/covESTUSAL, Source code for construction of covariates bound to daily salinity and specific conductance data for purposes of statistical modeling in coastal regions of the Gulf of Mexico, United States RESTORE/covESTUSAL, Source code for construction of covariates bound to daily salinity and specific conductance data for purposes of statistical modeling in coastal regions of the Gulf of Mexico, United States
The RESTORE/covESTUSAL software repository contains R language source code useful for the construction of input tables of daily salinity and specific conductance (response variables) from multi-agency monitoring stations and potential predictor variables (covariates) intended for reuse in statistical model construction in coastal regions of the Gulf of Mexico, United States. The source...
Science and Products
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: 45
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...
Streamflow recession indices computed by automation within and proximal to the Mobile Bay and Perdido Bay watersheds, south-central United States Streamflow recession indices computed by automation within and proximal to the Mobile Bay and Perdido Bay watersheds, south-central United States
This data release presents streamflow recession analyses and supporting statistics for 164 U.S. Geological Survey (USGS) streamgages located in or near the watersheds of Mobile and Perdido Bays in the south-central United States (see Tatum and others, 2024). Streamgages were selected based on a minimum of two complete decades of daily streamflow data since January 1, 1950, with the...
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...
Statistical predictions of groundwater levels and related spatial diagnostics for the Mississippi River Valley alluvial aquifer from the mmlMRVAgen1 statistical machine-learning software Statistical predictions of groundwater levels and related spatial diagnostics for the Mississippi River Valley alluvial aquifer from the mmlMRVAgen1 statistical machine-learning software
A multiple machine-learning model (Asquith and Killian, 2024) implementing Cubist and Random Forest regressions was used to predict monthly mean groundwater levels through time for the available years described in the metadata for the Mississippi River Valley alluvial aquifer (MRVA). The MRVA is the surficial aquifer of the Mississippi Alluvial Plain (MAP), located in the south-central...
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...
Geospatial extent of the study area and additional geospatial buffer for Mobile and Perdido bays contributing watersheds in the southeastern United States Geospatial extent of the study area and additional geospatial buffer for Mobile and Perdido bays contributing watersheds in the southeastern United States
The U.S. Geological Survey (USGS) Lower Mississippi-Gulf Water Science Center (LMGWSC) in collaboration with the U.S. Environmental Protection Agency and funded through the Resources and Ecosystems, Sustainability, Tourist, Opportunities, and Revived Economies of the Gulf Coast States Act (RESTORE Act) are conducting a multiyear multistate study to analyze the alteration and trends of...
Modeled daily salinity derived from multiple machine learning methodologies for 91 salinity monitoring sites in the northern Gulf of Mexico, 1980–2021 Modeled daily salinity derived from multiple machine learning methodologies for 91 salinity monitoring sites in the northern Gulf of Mexico, 1980–2021
This data release consists of statistical predictions of daily salinity time series generated from the makESTUSAL software repository described by Asquith and others (2023b). The statistical methods included multiple methods of machine learning, which produced the daily salinity prediction and attendant credible uncertainties included in the data release. The geographic scope includes...
Modeled daily salinity derived from multiple machine learning methodologies and generalized additive models for three salinity monitoring sites in Mobile Bay, northern Gulf of Mexico, 1980–2021 Modeled daily salinity derived from multiple machine learning methodologies and generalized additive models for three salinity monitoring sites in Mobile Bay, northern Gulf of Mexico, 1980–2021
Results from generalized additive models (GAM), random forest models (RFM), and cubist models (CUB) for three Dauphin Island Sealab (DIS) operated salinity sites in Mobile Bay are reported in this data release. These sites included Meaher Park (DIS:MHPA1), Middle Bay Lighthouse (DIS:MBLA1), and Dauphin Island (DIS:DPIA1). The constructed models predicted a 42-year daily salinity record...
infoGWauxs, Auxiliary methods for infoGW and similar groundwater level data objects and other helpful utilities infoGWauxs, Auxiliary methods for infoGW and similar groundwater level data objects and other helpful utilities
The infoGWauxs package in the R language provides auxiliary methods for data merging, duplicate-record removal, and monthly rollup of groundwater levels in the so-called infoGW or GWmaster data objects. These data structures are particularly well suited for statistical analyses of groundwater levels. This package is part of a greater body of data processors oriented around the infoGW...
Quality assurance of water levels in the Mississippi River Valley alluvial aquifer in Louisiana from the Louisiana Department of Natural Resources' Strategic Online Natural Resources Information System (SONRIS) Quality assurance of water levels in the Mississippi River Valley alluvial aquifer in Louisiana from the Louisiana Department of Natural Resources' Strategic Online Natural Resources Information System (SONRIS)
This data release provides several data files representing groundwater levels reported through driller's reports for the State of Louisiana Department of Natural Resources (Louisiana Department of Natural Resources, 2023) within or near the Mississippi Alluvial Plain (MAP) and (or) associated with the Mississippi River Valley alluvial aquifer (MRVA). First, a retrieval of data from the...
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: 69
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 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 Fulton, Nicholas Hall, Laura Hempel, J.J. Gourley, Mark Henneberg, Michael Kohn, William H. Farmer, William Asquith, Daniel Wasielewski, Andrew Stecklein, Amanullah Mommandi, Aziz Khan
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 Dietsch, William Asquith, Brian K. Breaker, Stephen Westenbroek, Wade 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 Asquith, Scott 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 Asquith, Monica Yesildirek, Raven Landers, Theodore Cleveland, Zheng Fang, Jiaqi Zhang
Regional regression equations for estimation of four hydraulic properties of streams at approximate bankfull conditions for different ecoregions in Texas Regional regression equations for estimation of four hydraulic properties of streams at approximate bankfull conditions for different ecoregions in Texas
The U.S. Geological Survey, in cooperation with the U.S. Army Corps of Engineers, assessed statistical relations between hydraulic properties of streams at approximate bankfull conditions for different ecological regions (ecoregions) in Texas. Data from more than 103,000 records of measured discharge and ancillary hydraulic properties were assembled from summaries of discharge...
Authors
William Asquith, John Gordon, David S. Wallace
Methods to quality assure, plot, summarize, interpolate, and extend groundwater-level information—Examples for the Mississippi River Valley alluvial aquifer Methods to quality assure, plot, summarize, interpolate, and extend groundwater-level information—Examples for the Mississippi River Valley alluvial aquifer
Large-scale computational investigations of groundwater levels are proposed to accelerate science delivery through a workflow spanning database assembly, statistics, and information synthesis and packaging. A water-availability study of the Mississippi River alluvial plain, and particularly the Mississippi River Valley alluvial aquifer (MRVA), is ongoing. Software (visGWDBmrva) has been...
Authors
William Asquith, Ronald Seanor, Virginia McGuire, Wade Kress
The use of support vectors from support vector machines for hydrometeorologic monitoring network analyses The use of support vectors from support vector machines for hydrometeorologic monitoring network analyses
Hydrometeorologic monitoring networks are ubiquitous in contemporary earth-system science. Network stakeholders often inquire about the importance of sites and their locations when discussing funding and monitoring design. Support vector machines (SVMs) can be useful by their assigning each monitoring site as either a support or nonsupport vector. A potentiometric surface was created...
Authors
William Asquith
Copula theory as a generalized framework for flow-duration curve-based streamflow estimates in ungaged and partially gaged catchments Copula theory as a generalized framework for flow-duration curve-based streamflow estimates in ungaged and partially gaged catchments
Flow‐duration curve (FDC) based streamflow estimation methods involve estimating an FDC at an ungaged or partially gaged location and using the time series of nonexceedance probabilities estimated from donor streamgage sites to generate estimates of streamflow. We develop a mathematical framework to illustrate the connection between copulas and prior FDC‐based approaches. The performance...
Authors
Scott Worland, Scott Steinschneider, William H. Farmer, William Asquith, Rodney Knight
Prediction and inference of flow-duration curves using multi-output neural networks Prediction and inference of flow-duration curves using multi-output neural networks
We develop multi-output neural network models (MNNs) to predict flow-duration curves (FDCs) in 9,203 ungaged locations in the Southeastern United States for six decades between 1950-2009. The model architecture contains multiple response variables in the output layer that correspond to individual quantiles along the FDC. During training, predictions are made for each quantile, and a...
Authors
Scott Worland, Scott Steinschneider, William Asquith, Rodney Knight, Michael E. Wieczorek
Characterizing groundwater/surface-water interaction using hydrograph-separation techniques and groundwater-level data throughout the Mississippi Delta, USA Characterizing groundwater/surface-water interaction using hydrograph-separation techniques and groundwater-level data throughout the Mississippi Delta, USA
The Mississippi Delta, located in northwest Mississippi, is an area dense with industrial-level agriculture sustained by groundwater-dependent irrigation supplied by the Mississippi River Valley Alluvial aquifer (alluvial aquifer). The Delta provides agricultural commodities across the United States and around the world. Observed declines in groundwater altitudes and streamflow...
Authors
Courtney Killian, William Asquith, Jeannie Barlow, Gardner C. Bent, Wade Kress, Paul Barlow, Darrel Schmitz
Annual and approximately quarterly series peak streamflow derived from interpretations of indirect measurements for a crest-stage gage network in Texas through water year 2015 Annual and approximately quarterly series peak streamflow derived from interpretations of indirect measurements for a crest-stage gage network in Texas through water year 2015
In 2006, the U.S. Geological Survey (USGS), incooperation with the Texas Department of Transportation,began collecting annual and approximately quarterly seriespeak-streamflow data at streamflow-gaging stations in smalltomedium-sized watersheds in central and western Texasas part of a crest-stage gage (CSG) network, along withselected flood-hydrograph data at a subset of these stations...
Authors
William Asquith, Glenn Harwell, Karl Winters
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...
infoGWauxs, Auxiliary methods for infoGW and similar groundwater level data objects and other helpful utilities infoGWauxs, Auxiliary methods for infoGW and similar groundwater level data objects and other helpful utilities
The infoGWauxs package in the R language provides auxiliary methods for data merging, duplicate-record removal, and monthly rollup of groundwater levels in the so-called infoGW or GWmaster data objects. These data structures are particularly well suited for statistical analyses of groundwater levels. This package is part of a greater body of data processors oriented around the infoGW...
RESTORE/TCEQswqmisESTUSAL, Source code for manipulation of data stemming from the Texas Commission on Environmental Quality Surface Water Quality Monitoring Program with emphasis on salinity change statistics for Texas coastal segments RESTORE/TCEQswqmisESTUSAL, Source code for manipulation of data stemming from the Texas Commission on Environmental Quality Surface Water Quality Monitoring Program with emphasis on salinity change statistics for Texas coastal segments
The RESTORE/TCEQswqmisESTUSAL repository contains R language source code that can be used for digesting data retrieved from the Texas Commission on Environmental Quality Surface Water Quality Monitoring Program through their Surface Water Quality Data Viewer. The workflow described concerns data manipulations, base data filtering, and computations towards documenting long-term salinity...
RESTORE/makESTUSAL, Source code for construction of various statistical models and prediction of daily salinity in coastal regions of the Gulf of Mexico, United States RESTORE/makESTUSAL, Source code for construction of various statistical models and prediction of daily salinity in coastal regions of the Gulf of Mexico, United States
The RESTORE/makESTUSAL software repository contains R language source code that can be used for the construction of various statistical models and output time series of predicted daily salinity coastal regions of the Gulf of Mexico, United States. The source code is expansive, and the repository is organizationally deep following logical organization units. One major subsystem of the...
Simulation and comparison of five estimators of variability in units of standard deviation for small samples drawn from normally distributed data Simulation and comparison of five estimators of variability in units of standard deviation for small samples drawn from normally distributed data
It is convenient to measure or estimate variation in samples or distributions in units of standard deviations. There are alternative methods of estimation of standard deviation aside from the conventional and well-known definition. Estimation of standard deviation for very small samples (as small as two), whereas not always ideal, might be useful in certain practical circumstances. A...
Study of L-kurtosis and several distribution families for prediction of uncertainty distributions, An applied software technical note concerning L-kurtosis use in daily salinity prediction from multiple machine learning methods Study of L-kurtosis and several distribution families for prediction of uncertainty distributions, An applied software technical note concerning L-kurtosis use in daily salinity prediction from multiple machine learning methods
Statistical predictions that are based on multiple machine learning (MML) methods (from including differing training regimes) produce differing predictions. When the predictions are combined to a final estimate, then there are residuals of the predictions spread around the final estimate. It is common to assume normality or near-normality of the residuals (errors), but the assumption of...
RESTORE/covESTUSAL, Source code for construction of covariates bound to daily salinity and specific conductance data for purposes of statistical modeling in coastal regions of the Gulf of Mexico, United States RESTORE/covESTUSAL, Source code for construction of covariates bound to daily salinity and specific conductance data for purposes of statistical modeling in coastal regions of the Gulf of Mexico, United States
The RESTORE/covESTUSAL software repository contains R language source code useful for the construction of input tables of daily salinity and specific conductance (response variables) from multi-agency monitoring stations and potential predictor variables (covariates) intended for reuse in statistical model construction in coastal regions of the Gulf of Mexico, United States. The source...
*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