Hydrologist, USGS Virginia and West Virginia Water Science Center.
Areas of interest: Surface water hydrology, fluvial geomorphology, environmental and economic analytics, forest management, forecasting, scenario analysis. Evaluating management decisions, trends, time-series, economic and financial questions, supply-chain dynamics, logistics, impulse-response problems.
Special skills: System dynamics modeling, developing project specific analytical tools, custom design of sampling experiments, characterizing statistical variation and relations, determining probable outcomes, testing data for trends, evaluating large and small datasets, reconditioning data.
Methods applied: Discrete and dynamic modeling and simulation. Evaluation of processes, decision interactions, and outcomes that include identifying system structure and simulating endogenous feedback. Interpreting, and characterizing large datasets using innovative statistical methods.
Fields of endeavor: Forest land-use and carbon metrics, surface water flows, hydrology, fluvial geomorphology, processes that include humans and ecosystems.
Areas of special knowledge: forest hydrology, fluvial geomorphology, watershed analysis, forest ecosystem dynamics, open channel flow, suspended and bed sediments, particle shear stress, critical shear velocities, stream classification and evaluation, production-distribution and control systems, management decision-making, biogeochemical cycling and feedback in natural systems.
See ORC-ID page for examples illustrating the educational potential of interactive simulation tools.
-
Darcy's Law
-
Urban Runoff
-
Sediment Motion
Education and Certifications
Duke University School of the Environment, MF, Forestry
Warren Wilson College, BA, Environmental Science
Science and Products
Tracking Status and Trends in Seven Key Indicators of River and Stream Condition in the Chesapeake Bay Watershed
Freshwater Flow into Chesapeake Bay
Chesapeake Bay Estimated Streamflow: METHODS
Modeling summer month hydrological drought probabilities in the United States using antecedent flow conditions
USGS-VDOT Bridge Scour Pilot Study
Estimating Drought Streamflow Probabilities for Virginia Streams
Estimating Peak Streamflow Per Square Mile in Virginia’s Urban Basins
Peak-Flow Characteristics of Virginia Streams
Virginia Bridge Scour Pilot Study Streamflow Data
Terms, Statistics, and Performance Measures for Maximum Likelihood Logistic Regression Models Estimating Hydrological Drought Probabilities in the Northeastern United States (2019)
Terms, Statistics, and Performance Measures for Maximum Likelihood Logistic Regression Models Estimating Hydrological Drought Probabilities in the Delaware River Basin (2020)
Terms, Statistics, and Performance Measures for Maximum Likelihood Logistic Regression Models Estimating Hydrological Drought Probabilities in the United States
Tracking status and trends in seven key indicators of stream health in the Chesapeake Bay watershed
Virginia Bridge Scour Pilot Study—Hydrological Tools
Forecasting drought probabilities for streams in the northeastern United States
Linking altered flow regimes to biological condition: An example using benthic macroinvertebrates in small streams of the Chesapeake Bay watershed
Drought forecasting for streams and groundwaters in northeastern United States
U.S. Geological Survey - Virginia Department of Transportation: Bridge scour pilot study
Variability of hydrological droughts in the conterminous United States, 1951 through 2014
Characteristics of peak streamflows and extent of inundation in areas of West Virginia and southwestern Virginia affected by flooding, June 2016
Modeling summer month hydrological drought probabilities in the United States using antecedent flow conditions
Variability of runoff-based drought conditions in the conterminous United States
Methods for estimating drought streamflow probabilities for Virginia streams
Methods and equations for estimating peak streamflow per square mile in Virginia’s urban basins
Interactive Map: Northeast Region Drought Streamflow Probabilities
This application allows the display and query of drought probability. Maximum likelihood logistic regression is used to estimate drought probabilities for selected Northeast region streams.
Interactive Map: Estimating Drought Streamflow Probabilities for Virginia Streams
Maximum likelihood logistic regression is used to estimate drought probabilities for selected Virginia rivers and streams 5 to 11 months in advance. Hydrologic drought streamflow probabilities for summer months are provided as functions of streamflows during the previous winter months. This application allows the display and query of these drought streamflow probabilities for Virginia streams.
Science and Products
- Science
Tracking Status and Trends in Seven Key Indicators of River and Stream Condition in the Chesapeake Bay Watershed
Identifying and tracking the status of, and trends in, stream health within the Chesapeake Bay watershed is essential to understanding the past, present, and future trajectory of the watershed’s resources and ecological condition. A team of USGS ecosystem scientists is meeting this need with an initiative to track the status of, and trends in, key indicators of the health of non-tidal freshwater...Freshwater Flow into Chesapeake Bay
Explore resources here describing estimates of freshwater flow entering Chesapeake Bay. The health of the Chesapeake Bay is greatly affected by freshwater flow from rivers draining its watershed. The amount of freshwater flow (also called streamflow) will: • Change salinity levels in the Bay, which affect oysters, crabs, and finfish. • Influence the amounts of nutrients, sediment, and contaminants...Chesapeake Bay Estimated Streamflow: METHODS
Methods for Estimating Streamflow to Chesapeake Bay The following is a description of how data presented on the website "Chesapeake Bay Estimated Streamflow" are computed. Essentially, the methodology was published more than 51 years ago, and has been adapted for use in modern automated computing systems. Approaches for summarizing data and describing it using statistics follow standard practices...Modeling summer month hydrological drought probabilities in the United States using antecedent flow conditions
Climate change raises concern that risks of hydrological drought may be increasing. We estimate hydrological drought probabilities for rivers and streams in the United States using maximum likelihood logistic regression (MLLR). Streamflow data from winter months are used to estimate the chance of hydrological drought during summer months. Daily streamflow data collected from 9,144 stream gages...USGS-VDOT Bridge Scour Pilot Study
Cost effective and safe highway bridge designs are required to ensure the long-term sustainability of Virginia’s road systems. The water flows that, over time, scour streambed sediments from bridge piers inherently affect bridge safety and design costs. To ensure safety, bridge designs must anticipate streambed scour at bridge piers over the lifespan of a bridge. Until recently Federal Highway...Estimating Drought Streamflow Probabilities for Virginia Streams
Planning for drought conditions in Virginia streams is essential to the sound management of water resources and associated riparian and watershed ecosystems. Reliable estimations of the likelihood that stream flows during drought-prone months will exceed specific low-flow thresholds can provide advance warning of drought conditions, allowing extended lead times for improved drought awareness and...Estimating Peak Streamflow Per Square Mile in Virginia’s Urban Basins
Models are presented that describe Virginia urban area annual peak streamflow per square mile based on basin percent urban area and basin drainage area.Peak-Flow Characteristics of Virginia Streams
Economic growth and the development, management, and protection of Virginia’s natural resources require anticipating peak stream flows and changes in peak stream flows over time. Extensive hydraulic analysis and smart design are needed to limit the environmental impacts of buildings, pavements, highways, and bridges. Effective design and placement of structures built near streams and on flood... - Data
Virginia Bridge Scour Pilot Study Streamflow Data
The objective of the Virginia Bridge Scour Pilot Study is to investigate methods for improving the utility of estimates of hydrologic flow in streams and rivers used when evaluating potential pier scour over the design-life of highway bridges in Virginia. Data measuring daily discharge and instantaneous discharge were required for analysis. The provided daily value and instantaneous value dischargTerms, Statistics, and Performance Measures for Maximum Likelihood Logistic Regression Models Estimating Hydrological Drought Probabilities in the Northeastern United States (2019)
Tables are presented listing parameters used in logistic regression equations describing drought streamflow probabilities in the Northeastern United States. Streamflow daily data, streamflow monthly mean data, maximum likelihood logistic regression (MLLR) equation explanatory parameters, equation goodness of fit parameters, and Receiver Operating Characteristic (ROC) AUC values identifying the utiTerms, Statistics, and Performance Measures for Maximum Likelihood Logistic Regression Models Estimating Hydrological Drought Probabilities in the Delaware River Basin (2020)
Tables are presented listing parameters and fit statistics for 25,453 maximum likelihood logistic regression (MLLR) models describing hydrological drought probabilities at 324 gaged locations on rivers and streams in the Delaware River Basin (DRB). Data from previous months are used to estimate chance of hydrological drought during future summer months. Models containing 1 explanatory variable useTerms, Statistics, and Performance Measures for Maximum Likelihood Logistic Regression Models Estimating Hydrological Drought Probabilities in the United States
A table is presented listing: (1) USGS Gage Station Numbers, (2) Model Identification Tags, (3) Model Term Estimates, (4) Model Term Fit Statistics, and (5) Model Performance Indices for Maximum Likelihood Logistic Regression (MLLR) Models estimating hydrological drought probabilities in the United States. Models were developed using streamflow daily values (DV) readily available from the U.S. Geo - Multimedia
- Publications
Filter Total Items: 15
Tracking status and trends in seven key indicators of stream health in the Chesapeake Bay watershed
“The Bay Connects us, the Bay reflects us” writes Tom Horton in the book “Turning the Tide—Saving the Chesapeake Bay”. The Chesapeake Bay watershed contains the largest estuary in the United States. The watershed stretches north to Cooperstown, New York, south to Lynchburg and Virginia Beach, Virginia, west to Pendleton County, West Virginia, and east to Seaford, Delaware, and Scranton, PennsylvanAuthorsSamuel H. Austin, Matt J. Cashman, John Clune, James E. Colgin, Rosemary M. Fanelli, Kevin P. Krause, Emily H. Majcher, Kelly O. Maloney, Chris A. Mason, Doug L. Moyer, Tammy M. ZimmermanByEcosystems Mission Area, Water Resources Mission Area, Environmental Health Program, Chesapeake Bay Activities, Eastern Ecological Science Center, Maryland-Delaware-D.C. Water Science Center, Pennsylvania Water Science Center, South Atlantic Water Science Center (SAWSC), Virginia and West Virginia Water Science CenterVirginia Bridge Scour Pilot Study—Hydrological Tools
Hydrologic and geophysical components interact to produce streambed scour. This study investigates methods for improving the utility of estimates of hydrologic flow in streams and rivers used when evaluating potential pier scour over the design-life of highway bridges in Virginia. Recent studies of streambed composition identify potential bridge design cost savings when attributes of cohesive soilAuthorsSamuel H. AustinForecasting drought probabilities for streams in the northeastern United States
Maximum likelihood logistic regression (MLLR) models for the northeastern United States forecast drought probability estimates for water flowing in rivers and streams using methods previously identified and developed. Streamflow data from winter months are used to estimate chances of hydrological drought during summer months. Daily streamflow data collected from 1,143 streamgages from April 1, 187AuthorsSamuel H. AustinLinking altered flow regimes to biological condition: An example using benthic macroinvertebrates in small streams of the Chesapeake Bay watershed
Regionally scaled assessments of hydrologic alteration for small streams and its effects on freshwater taxa are often inhibited by a low number of stream gages. To overcome this limitation, we paired modeled estimates of hydrologic alteration to a benthic macroinvertebrate index of biotic integrity data for 4522 stream reaches across the Chesapeake Bay watershed. Using separate random-forest modelAuthorsKelly O. Maloney, Daren Carlisle, Claire Buchanan, Jennifer L. Rapp, Samuel H. Austin, Matt J. Cashman, John A. YoungDrought forecasting for streams and groundwaters in northeastern United States
BackgroundWhen rainfall is lower than normal over an extended period, streamflows decline, groundwater levels fall, and hydrological drought can occur. Droughts can reduce the water available for societal needs, such as public and private drinking-water supplies, farming, and industry, and for ecological health, such as maintenance of water quality and natural ecosystems. Recent droughts in the noAuthorsSamuel H. Austin, Robert W. DudleyU.S. Geological Survey - Virginia Department of Transportation: Bridge scour pilot study
BackgroundCost effective and safe highway bridge designs are required to ensure the long-term sustainability of Virginia’s road systems. The streamflows that, over time, scour streambed sediments from bridge piers inherently affect bridge safety and design costs. To ensure safety, bridge design must anticipate streambed scour at bridge piers over the lifespan of a bridge. Until recently Federal HiAuthorsSamuel H. AustinVariability of hydrological droughts in the conterminous United States, 1951 through 2014
Spatial and temporal variability in the frequency, duration, and severity of hydrological droughts across the conterminous United States (CONUS) was examined using monthly mean streamflow measured at 872 sites from 1951 through 2014. Hydrological drought is identified as starting when streamflow falls below the 20th percentile streamflow value for 3 consecutive months and ending when streamflow reAuthorsSamuel H. Austin, David M. Wolock, David L. NelmsCharacteristics of peak streamflows and extent of inundation in areas of West Virginia and southwestern Virginia affected by flooding, June 2016
Heavy rainfall occurred across central and southern WestVirginia in June 2016 as a result of repeated rounds of torrentialthunderstorms. The storms caused major flooding and flashflooding in central and southern West Virginia with Kanawha,Fayette, Nicholas, and Greenbrier Counties among the hardesthit. Over the duration of the storms, from 8 to 9.37 inches ofrain was reported in areas in GreenbrieAuthorsSamuel H. Austin, Kara M. Watson, R. Russell Lotspeich, Stephen J. Cauller, Jeremy S. White, Shaun WickleinModeling summer month hydrological drought probabilities in the United States using antecedent flow conditions
Climate change raises concern that risks of hydrological drought may be increasing. We estimate hydrological drought probabilities for rivers and streams in the United States (U.S.) using maximum likelihood logistic regression (MLLR). Streamflow data from winter months are used to estimate the chance of hydrological drought during summer months. Daily streamflow data collected from 9,144 stream gaAuthorsSamuel H. Austin, David L. NelmsVariability of runoff-based drought conditions in the conterminous United States
In this study, a monthly water-balance model is used to simulate monthly runoff for 2109 hydrologic units (HUs) in the conterminous United States (CONUS) for water-years 1901 through 2014. The monthly runoff time series for each HU were smoothed with a 3-month moving average, and then the 3-month moving-average runoff values were converted to percentiles. For each HU, a drought was considered to oAuthorsGregory J. McCabe, David M. Wolock, Samuel H. AustinMethods for estimating drought streamflow probabilities for Virginia streams
Maximum likelihood logistic regression model equations used to estimate drought flow probabilities for Virginia streams are presented for 259 hydrologic basins in Virginia. Winter streamflows were used to estimate the likelihood of streamflows during the subsequent drought-prone summer months. The maximum likelihood logistic regression models identify probable streamflows from 5 to 8 months in advAuthorsSamuel H. AustinMethods and equations for estimating peak streamflow per square mile in Virginia’s urban basins
Models are presented that describe Virginia urban area annual peak streamflow per square mile based on basin percent urban area and basin drainage area. Equations are provided to estimate Virginia urban peak flow per square mile of basin drainage area in each of the following annual exceedance probability categories: 0.995, 0.99, 0.95, 0.9, 0.8, 0.67, 0.5, 0.43, 0.2, 0.1, 0.04, 0.02, 0.01, 0.005,AuthorsSamuel H. Austin - Web Tools
Interactive Map: Northeast Region Drought Streamflow Probabilities
This application allows the display and query of drought probability. Maximum likelihood logistic regression is used to estimate drought probabilities for selected Northeast region streams.
Interactive Map: Estimating Drought Streamflow Probabilities for Virginia Streams
Maximum likelihood logistic regression is used to estimate drought probabilities for selected Virginia rivers and streams 5 to 11 months in advance. Hydrologic drought streamflow probabilities for summer months are provided as functions of streamflows during the previous winter months. This application allows the display and query of these drought streamflow probabilities for Virginia streams.