Thomas Over, is a Research Hydrologist, with the Central Midwest Water Science Center, located in Urbana, Illinois.
Tom has worked for the USGS, Central Midwest Water Science Center (formerly the Illinois Water Science Center) since 2001 (originally part-time, full-time beginning 2012). He works in areas of prediction of peak and continuous streamflow in ungaged basins by statistical regionalization, hydrologic and hydraulic modeling (HSPF, SWMM, HEC-RAS, HEC-HMS, PEST), disaggregation and scaling of precipitation and streamflow, streamflow measurement uncertainty, hydrometeorological data analysis (evaluation of gage and radar-based precipitation observations and forecasts, development of homogeneous weather databases), and effects of urbanization on streamflow.
Prior to his full-time appointment with the USGS he was an assistant research professor at Eastern Illinois University (EIU) in the Geology/Geography Department, a visiting assistant professor at University of Illinois at Urbana-Champaign in the Civil and Environmental Engineering Department, and an assistant professor at Texas A&M University in the Civil Engineering Department, where he taught courses in water resources engineering, engineering hydrology, and stochastic hydrology. His research at EIU was in the area of controls of soil moisture and soil hydrophobicity on wind erosion. His Ph.D. is from University of Colorado - Boulder, Geophysics Program - Hydrology Option, where his dissertation was on multifractal space-time scaling properties of precipitation fields. While at CU-Boulder, he worked with Brent Troutman in the USGS (Water) National Research Program on the effects of river basin structure on streamflow. Prior to Ph.D. studies, he worked as a consulting civil engineer.
Professional Experience
2020 to Present, Research Hydrologist, Central Midwest Science Center
2012 to 2020, Hydrologist, Illinois, Illinois-Iowa, Central Midwest Water Science Centers
2001 to 2012, Hydrologist (part-time), Illinois Water Science Center
2000 to 2012, Assistant Research Professor (part-time), Department of Geology / Geography, Eastern Illinois University
2000 to 2001, Visiting Assistant Professor, Department of Civil and Environmental Engineering, University of Illinois at Urbana-Champaign
1996 to 2000, Assistant Professor, Department of Civil Engineering, Texas A&M University
1988 to 1995, Research Assistant, University of Colorado, Boulder
1984 to 1988, Consulting Civil Engineer, Nolte and Associates, San Jose, Calif.
Education and Certifications
Ph.D., Geophysics Program/Hydrology - University of Colorado-Boulder, 1995
M.S., CIvil and Environmental Engineering - Stanford University, 1984
S.B., Civil and Environmental Engineering - Massachusetts Institute of Technology, 1983
Science and Products
Models, Inputs, and Outputs for Estimating the Uncertainty of Discharge Simulations for the Lake Michigan Diversion Using the Hydrological Simulation Program - FORTRAN Model
Daily streamflow performance benchmark defined by D-score (v0.1) for the National Hydrologic Model application of the Precipitation-Runoff Modeling System (v1 byObs Muskingum) at benchmark streamflow locations
Streamflow benchmark locations for hydrologic model evaluation within the conterminous United States (cobalt gages)
Modeled and observed streamflow statistics at managed basins in the conterminous U.S. from October 1, 1983 through September 30, 2016.
Statistical daily streamflow estimates at GAGES-II non-reference streamgages in the conterminous United States, Water Years 1981-2017
Modeled and observed streamflow statistics at reference basins in the conterminous United States from October 1, 1983, through September 30, 2016
Cross-validation results for five statistical methods of daily streamflow estimation at 1,385 reference streamgages in the conterminous United States, Water Years 1981-2017
Statistical daily streamflow estimates at HUC12 outlets in the conterminous United States, Water Years 1981-2017
Meteorological Database, Argonne National Laboratory, Illinois, January 1, 1948 - September 30, 2017
Streamflow, flow-duration curves, basin characteristics, and regression models of flow-duration curves for selected streamgages in the conterminous United States
Bias correction of Simulated Historical Daily Streamflow at Ungauged Locations Using Independently Estimated Flow-Duration Curves: Data Release
Meteorological Database, Argonne National Laboratory, Illinois, January 1, 1948 - September 30, 2016
The consequences of neglecting reservoir storage in national-scale hydrologic models: An appraisal of key streamflow statistics
Improvements to estimate ADCP uncertainty sources for discharge measurements
Effect of uncertainty of discharge data on uncertainty of discharge simulation for the Lake Michigan Diversion, northeastern Illinois and northwestern Indiana
Uncertainty analysis of index-velocity meters and discharge computations at the Chicago Sanitary and Ship Canal near Lemont, Illinois, water years 2006–16
Mean squared error, deconstructed
Assessment of peak flow scaling and Its effect on flood quantile estimation in the United Kingdom
Bias correction of simulated historical daily streamflow at ungauged locations by using independently estimated flow duration curves
Refinement of a regression-based method for prediction of flow-duration curves of daily streamflow in the conterminous United States
Comparison of NEXRAD multisensor precipitation estimates to rain gage observations in and near DuPage County, Illinois, 2002–12
Adjusting annual maximum peak discharges at selected stations in northeastern Illinois for changes in land-use conditions
Estimation of peak discharge quantiles for selected annual exceedance probabilities in northeastern Illinois
Accelerating advances in continental domain hydrologic modeling
Non-USGS Publications**
**Disclaimer: The views expressed in Non-USGS publications are those of the author and do not represent the views of the USGS, Department of the Interior, or the U.S. Government.
Science and Products
- Data
Filter Total Items: 14
Models, Inputs, and Outputs for Estimating the Uncertainty of Discharge Simulations for the Lake Michigan Diversion Using the Hydrological Simulation Program - FORTRAN Model
This data release contains the models and their inputs and outputs needed to reproduce the findings for the publication by Soong and Over (2022), "Effect of Uncertainty of Discharge Data on Uncertainty of Discharge Simulation for the Lake Michigan Diversion, Northeastern Illinois and Northwestern Indiana." These data were developed in cooperation with the U.S. Army Corps of Engineers, Chicago DistDaily streamflow performance benchmark defined by D-score (v0.1) for the National Hydrologic Model application of the Precipitation-Runoff Modeling System (v1 byObs Muskingum) at benchmark streamflow locations
This data release contains the D-score (version 0.1) daily streamflow performance benchmark results for the National Hydrologic Model Infrastructure application of the Precipitation-Runoff Modeling System (NHM) version 1 "byObs" calibration with Muskingum routing computed at streamflow benchmark locations (version 1) as defined by Foks and others (2022). Model error was determined by evaluating prStreamflow benchmark locations for hydrologic model evaluation within the conterminous United States (cobalt gages)
A list of stream gages within the conterminous United States that will serve as the initial list of sites (version 1.0) used for streamflow benchmarking of hydrologic models. Sites within this list were chosen based on their presence in the GAGES-II dataset, their availability of modeled streamflow data from the most recent version of the National Hydrologic Model application of Precipitation-RunoModeled and observed streamflow statistics at managed basins in the conterminous U.S. from October 1, 1983 through September 30, 2016.
This data release contains values of 29 streamflow statistics computed from modeled and observed daily streamflows from October 1, 1983, through September 30, 2016 at 1,257 streamgages in the 19 study regions defined by Falcone (2011) covering the conterminous United States. The streamflow statistics were computed at GAGES-II non-reference streamgages (Falcone, 2011), determined to be affected byStatistical daily streamflow estimates at GAGES-II non-reference streamgages in the conterminous United States, Water Years 1981-2017
This data release contains daily time series estimates of natural streamflow at 5,439 GAGES-II non-reference streamgages in 19 study regions across the conterminous United States from October 1, 1980 through September 30, 2017, using five statistical techniques: nearest-neighbor drainage area ratio (NNDAR), map-correlation drainage area ratio (MCDAR), nearest-neighbor nonlinear spatial interpolatiModeled and observed streamflow statistics at reference basins in the conterminous United States from October 1, 1983, through September 30, 2016
This data release contains 29 streamflow statistics computed from modeled and observed daily streamflows from October 1, 1983, through September 30, 2016 at 1,114 streamgages in 19 study regions covering the conterminous United States. The streamflow statistics were computed at selected GAGES-II reference streamgages (Falcone, 2011) from daily streamflow observations (Russell and others, 2020), frCross-validation results for five statistical methods of daily streamflow estimation at 1,385 reference streamgages in the conterminous United States, Water Years 1981-2017
This data release contains daily time series estimates of natural streamflow for 1,385 streamgages in 19 study regions in the conterminous U.S. from October 1, 1980, through September 30, 2017. These estimates are provided for gages from mostly undisturbed watersheds as defined by Falcone (2011), using five statistical techniques: nearest-neighbor drainage area ratio (NNDAR), map-correlation drainStatistical daily streamflow estimates at HUC12 outlets in the conterminous United States, Water Years 1981-2017
This data release contains daily time series estimates of natural streamflow at the outlets of more than 80,000 12-digit hydrologic units in 19 study regions across the conterminous U.S. from October 1, 1980 through September 30, 2017, using three statistical techniques: Nearest-Neighbor Drainage Area Ratio (NNDAR), Map-Correlation Drainage Area Ratio (MCDAR), and Ordinary Kriging of the logarithmMeteorological Database, Argonne National Laboratory, Illinois, January 1, 1948 - September 30, 2017
This data release is the update of the U.S. Geological Survey - ScienceBase data release by Bera and Over (2017), with the processed data through September 30, 2017. The primary data for each year is downloaded from the Argonne National Laboratory (ANL) (Argonne National Laboratory, 2017) and is processed following the guidelines documented in Over and others (2010). Daily potential evapotranspiraStreamflow, flow-duration curves, basin characteristics, and regression models of flow-duration curves for selected streamgages in the conterminous United States
This data release contains the input used and the output files interpreted in the publication 'Refinement of a Regression-Based Method for Prediction of Flow-Duration Curves of Daily Streamflow in the Conterminous United States'. This data release contains daily streamflow data for 1,378 streamgages in 19 study regions in the conterminous U.S. from October 1, 1980 through September 30, 2013 from mBias correction of Simulated Historical Daily Streamflow at Ungauged Locations Using Independently Estimated Flow-Duration Curves: Data Release
This dataset contains the observed and simulated streamflow used to produce the results of the journal article entitled Bias correction of Retrospective Simulation of Daily Streamflow at Ungauged Locations Using Independently Estimated Flow-Duration Curves . Observed streamflow, retrieved from the U.S. Geological Surveys National Water Information System (https://waterdata.usgs.gov/nwis) in SpringMeteorological Database, Argonne National Laboratory, Illinois, January 1, 1948 - September 30, 2016
This data release is the update of the U.S. Geological Survey - ScienceBase data release by Bera and Over (2016), with the processed data through September 30, 2016. The primary data for each year is downloaded from the Argonne National Laboratory (ANL) (http://gonzalo.er.anl.gov/ANLMET/numeric/) and is processed following the guidelines documented in Over and others (2010) and Bera (2014). Daily - Publications
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The consequences of neglecting reservoir storage in national-scale hydrologic models: An appraisal of key streamflow statistics
A better understanding of modeled streamflow errors related to basin reservoir storage is needed for large regions, which normally have many ungaged basins with reservoirs. We quantified the difference between modeled and observed streamflows for one process-based and three statistical-transfer hydrologic models, none of which explicitly accounted for reservoir storage. Streamflow statistics repreAuthorsGlenn A. Hodgkins, Thomas M. Over, Robert W. Dudley, Amy M. Russell, Jacob H. LaFontaineImprovements to estimate ADCP uncertainty sources for discharge measurements
The use of moving boat ADCPs (Acoustic Doppler Current Profilers) for discharge measurements requires identification of the sources and magnitude of uncertainty to ensure accurate measurements. Recently, a tool known as QUant was developed to estimate the contribution to the uncertainty estimates for each transect of moving-boat ADCP discharge measurements, by varying different sampling configuratAuthorsJosé M. Díaz Lozada, Carlos M. García, Kevin Oberg, Thomas M. Over, Federico Flores NietoEffect of uncertainty of discharge data on uncertainty of discharge simulation for the Lake Michigan Diversion, northeastern Illinois and northwestern Indiana
Simulation models of watershed hydrology (also referred to as “rainfall-runoff models”) are calibrated to the best available streamflow data, which are typically published discharge time series at the outlet of the watershed. Even after calibration, the model generally cannot replicate the published discharges because of simplifications of the physical system embedded in the model structure and unAuthorsDavid T. Soong, Thomas M. OverUncertainty analysis of index-velocity meters and discharge computations at the Chicago Sanitary and Ship Canal near Lemont, Illinois, water years 2006–16
Monitoring discharge in the Chicago Sanitary and Ship Canal is critical for the accounting done by the U.S. Army Corps of Engineers of the diversion of water from Lake Michigan to the Mississippi River Basin by the State of Illinois. The primary streamgage used for this discharge monitoring, the Chicago Sanitary and Ship Canal near Lemont, Illinois (U.S. Geological Survey station 05536890), is opeAuthorsThomas M. Over, Marian Muste, James J. Duncker, Heng-Wei Tsai, P. Ryan Jackson, Kevin K. Johnson, Frank L. Engel, Crystal D. PraterMean squared error, deconstructed
As science becomes increasingly cross-disciplinary and scientific models become increasingly cross-coupled, standardized practices of model evaluation are more important than ever. For normally distributed data, mean squared error (MSE) is ideal as an objective measure of model performance, but it gives little insight into what aspects of model performance are “good” or “bad.” This apparent weakneAuthorsTimothy O. Hodson, Thomas M. Over, Sydney FoksAssessment of peak flow scaling and Its effect on flood quantile estimation in the United Kingdom
Regional flood frequency analysis (RFFA) methods are essential tools to assess flood hazard and plan interventions for its mitigation. They are used to estimate flood quantiles when the at‐site record of streamflow data is not available or limited. One commonly used RFFA method is the index flood method (IFM), which assumes that peak floods satisfy the simple scaling hypothesis.In this work we preAuthorsGiuseppe Formetta, Thomas M. Over, Elizabeth StewartBias correction of simulated historical daily streamflow at ungauged locations by using independently estimated flow duration curves
In many simulations of historical daily streamflow distributional bias arising from the distributional properties of residuals has been noted. This bias often presents itself as an underestimation of high streamflow and an overestimation of low streamflow. Here, 1168 streamgages across the conterminous USA, having at least 14 complete water years of daily data between 1 October 1980 and 30 SeptembAuthorsWilliam H. Farmer, Thomas M. Over, Julie E. KiangRefinement of a regression-based method for prediction of flow-duration curves of daily streamflow in the conterminous United States
Regional regression is a common tool used to estimate daily flow-duration curves (FDCs) at ungaged locations. In this report, several refinements to a particular implementation of the regional regression method for estimating FDCs are evaluated by consideration of different methodological options through a leave-one-out cross-validation procedure in the 19 major river basins of the conterminous UnAuthorsThomas M. Over, William H. Farmer, Amy M. RussellComparison of NEXRAD multisensor precipitation estimates to rain gage observations in and near DuPage County, Illinois, 2002–12
In this report, precipitation data from 2002 to 2012 from the hourly gridded Next-Generation Radar (NEXRAD)-based Multisensor Precipitation Estimate (MPE) precipitation product are compared to precipitation data from two rain gage networks—an automated tipping bucket network of 25 rain gages operated by the U.S. Geological Survey (USGS) and 51 rain gages from the volunteer-operated Community CollaAuthorsRyan R. Spies, Thomas M. Over, Terry OrtelAdjusting annual maximum peak discharges at selected stations in northeastern Illinois for changes in land-use conditions
The effects of urbanization on annual maximum peak discharges in northeastern Illinois and nearby areas from 1945 to 2009 were analyzed with a two-step longitudinal-quantile linear regression approach. The peak discharges were then adjusted to 2010 land-use conditions. The explanatory variables used were daily precipitation at the time of the peak discharge event and a housing density-based measurAuthorsThomas M. Over, Riki J. Saito, David T. SoongEstimation of peak discharge quantiles for selected annual exceedance probabilities in northeastern Illinois
This report provides two sets of equations for estimating peak discharge quantiles at annual exceedance probabilities (AEPs) of 0.50, 0.20, 0.10, 0.04, 0.02, 0.01, 0.005, and 0.002 (recurrence intervals of 2, 5, 10, 25, 50, 100, 200, and 500 years, respectively) for watersheds in Illinois based on annual maximum peak discharge data from 117 watersheds in and near northeastern Illinois. One set ofAuthorsThomas M. Over, Riki J. Saito, Andrea G. Veilleux, Padraic S. O'Shea, Jennifer B. Sharpe, David T. Soong, Audrey L. IshiiAccelerating advances in continental domain hydrologic modeling
In the past, hydrologic modeling of surface water resources has mainly focused on simulating the hydrologic cycle at local to regional catchment modeling domains. There now exists a level of maturity among the catchment, global water security, and land surface modeling communities such that these communities are converging toward continental domain hydrologic models. This commentary, written fromAuthorsStacey A. Archfield, Martyn Clark, Berit Arheimer, Lauren E. Hay, Hilary McMillan, Julie E. Kiang, Jan Seibert, Kirsti Hakala, Andrew R. Bock, Thorsten Wagener, William H. Farmer, Vazken Andreassian, Sabine Attinger, Alberto Viglione, Rodney Knight, Steven L. Markstrom, Thomas M. OverNon-USGS Publications**
Over, T.M., Soong, D.T., and Su, T.Y., “Evaluation of HSPF snow modeling parameters using NWS Coop and SNODAS snow data”, Proceedings, EWRI Watershed Management 2010, Madison, WI, August 2010Hirpa, F., M. Gebremichael., and T.M. Over, “River flow fluctuation analysis: Effect of watershed area”, Water Resources Research, 46, W12529, doi:10.1029/2009WR009000, 2010.Gebremichael, M., Rigon, R., Bertoldi, R., and T. M. Over, “On the scaling characteristics of observed and simulated spatial soil moisture fields”, Nonlin. Processes Geophys., 16, 141–150, 2009Ravi, S. P. D’Odorico, T.M. Zobeck, and T.M. Over, “The effect of fire-induced soil hydrophobicity on wind erosion in a semiarid grassland: Experimental observations and theoretical framework”,Geomorphology, 105: 80-86, 2009.Gebremichael, M., W.F. Krajewski, T.M. Over, Y.N. Takayabu, P. Arkin, and M. Katayama, “Scaling of tropical rainfall as observed by TRMM Precipitation Radar”, Atmospheric Research, 88 (3-4): 337-354, 2008.Alfieri, L., P. Claps, P. D’Odorico, F. Laio, and T.M. Over, “An analysis of the soil moisture feedback on convective and stratiform precipitation”, J. Hydrometeorol. 9(2): 280-291, 2008.Ravi, S., P. D’Odorico, T.M. Zobeck, T.M. Over, and S.L. Collins, “Feedbacks between fires and wind erosion in heterogeneous arid lands”, J. Geophys Res., 112, G04007, doi:10.1029/2007JG000474, 2007.
Over, T.M., E.A. Murphy, T.W. Ortel, and A.L. Ishii, “Comparisons between NEXRAD radar and tipping bucket gage rainfall data: A case study for DuPage County, Illinois”, Proceedings, ASCE-EWRI World Environmental and Water Resources Congress, Tampa, Florida, May 2007.Ravi, S. P. D'Odorico, B.E. Herbert, T. M. Zobeck, and T.M. Over, “Enhancement of wind erosion by fire-induced water repellency”, Water Resour. Res., 42, W11422, doi:10.1029/2006WR004895, 2006.
Gebremichael, M., T.M. Over, and W.F. Krajewski, “Comparison of the scaling characteristics of rainfall derived from space-based and ground-based radar observations”, J. Hydrometeorology, 7: 1277-1294, 2006.Ravi, S., T. M. Zobeck, T. M. Over, G. S. Okin, and P. D'Odorico, “On the effect of moisture bonding forces in air-dry soils on threshold friction velocity of wind erosion”, Sedimentology, 53: 597-609, 2006.Rigon, R. G. Bertoldi, and T. M. Over, “GEOtop: A distributed hydrological model with coupled water and energy budgets”, J. Hydrometeorology, 7: 371-388, 2006.Bertoldi, G., R. Rigon, and T. M. Over, “Impact of watershed geomorphic characteristics on the energy and water budgets”, J. Hydrometeorology, 7: 389-404, 2006.Lee, S.-W., A. G. Klein, and T. M. Over, “A comparison of MODIS and NOHRSC snowcover products for simulating streamflow using the Snowmelt Runoff Model”, Hydrol. Proc., 19: 2951-2972, 2005.Wang, H., C.-M.Wang, J.-H. Wang, D.-Y. Qin, Z.-H. Zhou, and T.M. Over, “Theory and practice of runoff space-time distribution”, Sci. China Ser. E-Eng. Mater. Sci., 47(Suppl S.): 90-105, 2004.Kuzuha, Y., T. M. Over, K. Tomosugi, and T. Kishii, “Analysis of multifractal properties of temporal and spatial precipitation data in Japan”, J. Hydrosci. Hydraul. Eng., 22(2): 59-78, 2004.Ravi, S., P. D’Odorico, T. M. Over, and T. M. Zobeck, “Effect of soil moisture on threshold velocity for wind erosion”, Geophys. Res. Let., 31(9): 1-4, 2004.Lee, S.-W., A. G. Klein, and T. M. Over, “Effects of El Nino / Southern Oscillation on temperature, precipitation, snow water equivalent and resulting streamflow in the Upper Rio Grande River Basin”,Hydrol. Proc., 18(6): 1053-1071, 2004.D’Odorico, P., J.-C. Yoo, and T. M. Over, “On the Assessment of ENSO-induced Patterns of Rainfall Erosivity in the Southwestern United States,” J. Climate, 14(21): 4230-4242, 2001.Over, T. M., and V. K. Gupta, “A Space-Time Theory of Mesoscale Rainfall Using Random Cascades,” J. Geophys. Res., 101(D21): 26,319-26,331, 1996.Gupta, V.K., S. L. Castro, and T. M. Over, “On Scaling Exponents of Spatial Peak Flows from Spatial Rainfall and River Network Geometry”, J. Hydrology, 187(1/2), 81-104, 1996.Over, T.M., Modeling Space-Time Rainfall at the Mesoscale using Random Cascades, Ph.D. dissertation, University of Colorado-Boulder, 1995, 238 p. [Link]Over, T.M., and V. K. Gupta, “Statistical Analysis of Mesoscale Rainfall: Dependence of a Random Cascade Generator on the Large-Scale Forcing,” J. Applied Meteorol., 33(12):1526-1542, 1994.Karlinger, M.R., T. M. Over and B.M. Troutman, “Relating Thin and Fat-Fractal Scaling of River-Network Models,” Fractals, 2(4):557-565, 1994.**Disclaimer: The views expressed in Non-USGS publications are those of the author and do not represent the views of the USGS, Department of the Interior, or the U.S. Government.