USGS Professional Pages
Research HydrologistContact Info
I am a research hydrologist. The focus of my research is the description and understanding of long-term variability and change in surface-water quality and streamflow. I develop and apply new statistical tools to help characterize these changes to gain the best possible understanding of the nature of the change and its implications from a policy perspective (for example with respect to water quality improvement, ecosystem restoration, flood hazard mitigation, water supply planning, or provision of in-stream flow). I served as Chief Hydrologist of the USGS from 1994-2008 and at that time returned to a career in hydrologic research. I am the lead developer of a software package called EGRET (Exploration and Graphics for RivEr Trends) which is now an approved USGS model (written in R - an open source computer language). The statistical method (Weighted Regressions on Time, Discharge, and Season - WRTDS) has been used in a number of studies of water quality trends in the US (Chesapeake Bay Watershed, Mississipi River Basin, Lake Champlain Basin, and elsewhere) to describe and better understand changing concentrations and fluxes of nutrients in river systems. I have also been working on the description of long-term trends in streamflow as related to changes in land use and climate.
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PublicationsHirsch, R. M., and De Cicco, Laura, 2014, User Guide to Exploration and Graphic for RivEr Trends (EGRET) and dataRetrieval: R Packages for Hydrologic Data, USGS Techniques and Methods 4-A10, 95p. [Link]
Green, C. T., B. A. Bekins, S. J. Kalkhoff, R. M. Hirsch, L. Liao, and K. K. Barnes, 2014, Decadal surface water quality trends under variable climate, land use, and hydrogeochemical setting in Iowa, USA, Water Resour. Res., 50, 2425–2443, [Link]
Murphy, J. C., Hirsch, R. M., and Sprague, L. A.: 2014, Antecedent flow conditions and nitrate concentrations in the Mississippi River basin, Hydrol. Earth Syst. Sci., 18, 967-979 [Link]
Hirsch, R. M., (2014) Large Biases in Regression-Based Constituent Flux Estimates: Causes and Diagnostic Tools, Journal of the American Water Resources Association. [Link]
Corsi, S.R., De Cicco, L.A., Lutz, M.A., and Hirsch, R.M., 2014, River chloride trends in snow-affected urban watersheds: increasing concentrations outpace urban growth rate and are common among all seasons. Science of the Total Environment, 508, 1 March 2015, 448-497. [Link]
Murphy, J.C., Hirsch, R.M., and Sprague, L.A., 2013, Nitrate in the Mississippi River and its tributaries, 1980–2010—An update: U.S. Geological Survey Scientific Investigations Report 2013–5169, 31 p [Link]
Peterson, T.C., Heim, R.R., Hirsch, R., Kaiser, D.P., Brooks, H., Diffenbaught N.S., Dole, R.M., Giovannettone, J.P., Guirguis, K., Karl, T.R., Katz, R.W., Kunkel, K., Lettenmaier, D., McCabe, G.J., Paciorek, C.J., Ryberg, K.R., Schubert, S., Silva, V.B.S., Stewart, B.C., Vecchia, A.V., Villarini, G., Vose, R.S., Walsh, J., Wehner, M., Wolock, D., Wolter, K., Woodhouse, C.A., and Wuebbles, D., 2013, Monitoring and Understanding Changes in Heat Waves, Cold Waves, Floods and Droughts in the United States: State of Knowledge. Bulletin American Meteorology Society, June 2013, p 821-834 [Link]
Hirsch, R.M., 2012, The Science, Information, and Engineering Needed to Manage Water Availability and Quality in 2050, in "Toward a Sustainable Water Future: Visions for 2050" pp 217-226, editors Grayman, Loucks, and Saito, American Society of Civil Engineers, Reston, VA, 398 pp.
Hirsch, R.M. and Ryberg, K.R., 2012, Has the magnitude of floods across the USA changed with global CO2 levels?, Hydrological Sciences Journal, Vol 57, Issue 1. [Link]
Medalie, L., Hirsch, R.M., and Archfield, S.A., 2012, Use of flow-normalization to evaluate nutrient concentration and flux changes in Lake Champlain tributaries, 1990-2009, Journal of Great Lakes Research, 38, Supplement 1, p. 58-67. [Link]
Rice, K.C. and Hirsch, R.M., 2012, Spatial and Temporal Trends in Runoff at Long-Term Streamgages within and near the Chesapeake Bay Watershed, U.S. Geological Survey, Scientific Investigations Report, 2012-5151, 55 p. [Link]
Hirsch, R.M., 2012, Flux of Nitrogen, Phosphorus, and Suspended Sediment from the Susquehanna River Basin to the Chesapeake Bay during Tropical Storm Lee, September 2011, as an Indicator of the Effects of Reservoir Sedimentation on Water Quality, U.S. Geological Survey, Scientific Investigations Report 2012-5185, 17 p. [Link]
Moyer, D.L., Hirsch, R.M., and Hyer, K.E., 2012, Comparison of two regression-based approaches for determining nutrient and sediment fluxes and trends in the Chesapeake Bay watershed: U.S. Geological Survey Scientific Investigations Report 2012-5244, 118 p. [Link]
Sprague, Lori A.; Hirsch, Robert M.; Aulenbach, Brent T., 2011. Nitrate in the Mississippi River and its tributaries, 1980 to 2008: Are we making progress?. ACS Publications , 8 p. [Link]
Hirsch, R.M., 2011, A Perspective on Nonstationarity and Water Management, Journal of the American Water Resources Association, 47, 436-446. [Download File]
Lins, Harry F.; Hirsch, Robert M.; Kiang, Julie, 2010. Water-the Nation's Fundamental Climate Issue A White Paper on the U.S. Geological Survey Role and Capabilities. U.S. Geological Survey Circular 1347, iv, 9 p. [Link]
Hirsch, R.M, Moyer, D.L., and Archfield, S.A., 2010, Weighted Regressions on Time, Discharge, and Season (WRTDS), with an Application to Chesapeake Bay River Inputs, Journal of the American Water Resources Association p. 857-880. [Link]
Milly, P.C.D., Betancourt, J, Falkenmark, M., Hirsch, R.M., Kundzewicz, Z.W., Lettenmaier, D.P., and Stouffer, R.J., 2008, Stationarity is Dead: Whither Water Management?: Science, vol. 319, p. 573-574. [Download File]
Helsel, Dennis R.; Hirsch, Robert M., 2002. Statistical Methods in Water Resources. Techniques of Water-Resource Investigation 04-A3, 523 p. [Link]
Hirsch, R.M., Alexander, R.B., and Smith, R.A., 1991, Selection of methods for the detection and estimation of trends in water quality: Water Resources Research, v. 27, no. 5, p. 803-813. [Download File]
Hirsch, Robert M.; Alley, William M.; Wilber, William G. , 1988. Concepts for a National Water-Quality Assessment Program. U.S. G.P.O., Circular 1021, vii, 42 p. :ill., maps ;28 cm.
Hirsch, R.M., and Slack, J.R., 1984, A nonparametric trend test for seasonal data with serial dependence: Water Resources Research, v. 20, no. 6, p. 727-732. [Download File]
Hirsch, R.M., Slack, J.R., and Smith, RA., 1982. Techniques of trend analysis for monthly water-quality data: Water Resources Research, v. 18, no. 1, p. 107-121. [Download File]
Hirsch, Robert M.; Slack, James Richard; Smith, Richard A., 1981. Techniques of trend analysis for monthly water-quality data. U.S. Geological Survey, Open-File Report 81-488, 33 p. :ill. ;28 cm.
Hydrologic Variability and Trends
Using long-term data records, this project is focused on two problems of importance to water resources managers. First, long-term streamflow records are being used to a) identify broad regional to national trends in floods and low-flows and relate them to possible causes (climate change, water management changes, land-cover changes, and ground-water level change) and b) determine whether there are patterns that relate to watershed size or climate characteristics. It is often stated in the popular press and in official publications on global climate change that we can expect increased variability, including larger and/or more frequent floods, and deeper and longer droughts, as a result of greenhouse warming. This research will use the long-term historical records of streamflow at USGS streamgages to explore the empirical evidence for such statements. The second area of research is related to long-term changes in nutrient concentration and transport in major rivers. Although water resources managers have been attempting to control nutrients in our Nation's waters through efforts such as point source pollution control, non-point source best-management-practices, and air quality controls to limit atmospheric deposition, the question on how effective these efforts are remains unclear. The scientific complexities of this problem include consideration of: time lags between control measures and expected results, the potential that different control measures will have a different type of impact at low versus high flows or during some seasons and not others, and the potential for hysteresis in relationships between concentration and flow. The answer to this seemingly simple question is difficult to determine because surface-water quality is so highly dependent on the natural interannual variability of flow conditions.
This software is in beta test as of August 2013. It is written in the open-source R language and is designed for the analysis of long term trends in streamflow and long term trends in water quality. The home page for the software and various publications and presentations is located at: https://github.com/USGS-R/EGRET/wiki
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