Dr. Kenneth H. Reckhow, Director

• Background
• Research Interests
• Recent Publications
• Other Work
• Neuse Projects
• Neuse River MODeling& MONitoring
• Neuse Nitrogen TMDL Modeling
• Eutromod
• Personal Interests
• Links to Other Sites
• ENV335 Water Quality Modeling Class
• Director's Forum (short essays on science and policy)
• National Academy of Sciences report on TMDLs

Background

Current Position:

• Director, Water Resources Research Institute of The University of North Carolina
• Professor, Duke University (reckhow@duke.edu) Nicholas School of the Environment and Earth Sciences
• Adjunct Professor, Department of Civil Engineering, North Carolina State University

Education

• S.B. Cornell University, Engineering Physics, 1971
• S.M. Harvard University, Environmental Science and Engineering, 1972
• Ph.D. Harvard University, Environmental Science and Engineering, 1977

Research Interests

For the past several years, my research has focused on surface water quality modeling and decision analysis. I am particularly interested in the treatment of scientific uncertainty, methods for combining information (in particular, Bayesian inference), statistical characterization of multivariate patterns in water quality, and recently, probabilistic modeling approaches. This research has involved a number of Ph.D. students and faculty colleagues at Duke and other universities. In addition, I am interested in the more applied area concerning the development and presentation of mathematical models and statistical methods for use by practicing professional scientists and engineers.

Recent Publications (since 1990)

Borsuk, Mark E., Craig A. Stow, and Kenneth H. Reckhow. 2002. The confounding effects of nitrogen load on eutrophication of the Neuse River estuary, North Carolina. (submitted).(pdf file)

Borsuk, Mark E., Craig A. Stow, and Kenneth H. Reckhow. 2002. Ecological prediction using causal Bayesian networks: A case study of eutrophication management in the Neuse River estuary. Unpublished manuscript. (pdf file)

Adams, Barbara V., and Kenneth H. Reckhow. 2002. An Examination of the Scientific Basis for Mechanisms and Parameters in Water Quality Models. (submitted). (pdf file)

Craig A. Stow, Chris Roessler, Mark E. Borsuk, James D. Bowen, and Kenneth H. Reckhow. 2002. A Comparison of Estuarine Water Quality Models for TMDL development in the Neuse River Estuary. Journal Water Resources Planning and Management. (accepted). (pdf file)

Borsuk, Mark E., Craig A. Stow, and Kenneth H. Reckhow. 2002. An integrated approach to TMDL development for the Neuse River estuary using a Bayesian probability network model (Neu-BERN) . Journal Water Resources Planning and Management. (accepted). (pdf file)

Reckhow, Kenneth H. 2002. Bayesian Approaches in Ecological Analysis and Modeling . In: The Role of Models in Ecosystem Science. Charles D. Canham, Jonathan J. Cole, and William K. Lauenroth, Eds. Princeton University Press. (in press). (pdf file)

Borsuk, Mark E., Craig A. Stow, and Kenneth H. Reckhow. 2002. Integrative environmental prediction using Bayesian networks: A synthesis of models describing estuarine eutrophication. IEMSS Conference proceedings, Lugano, Switzerland. (pdf file)

Borsuk, Mark E., Craig A. Stow, and Kenneth H. Reckhow. 2002. Predicting the frequency of water quality standard violations: A probabilistic approach for TMDL development. Environmental Science and Technology 36:2109-2115. (pdf file) 

Stow, Craig A., Mark E. Borsuk, and Kenneth H. Reckhow. 2001. Nitrogen TMDL Development in the Neuse River Watershed: An Imperative for Adaptive Management. Universities Council on Water Resources' Water Resources Update.(pdf file)

Borsuk, M.E., D. Higdon, C.A. Stow, and K.H.Reckhow. 2001. A Bayesian Hierarchical Model to Predict Benthic Oxygen Demand from Organic Matter Loading in Estuaries and Coastal Zones Ecological Modelling 143:165-181. (pdf file)

Borsuk, M.,  R. Clemen, L. Maguire, and K. Reckhow. 2001. A Multiple-Criteria Bayes Net Model of the Neuse River Estuary. Group Decision and Negotiation 10:355-373. (MSWord file)

Wickham, J.D., K.H. Ritters, R.V. O'Neill, K.H. Reckhow, T.G. Wade, and K. B. Jones. 2000. Land Cover as a Framework for Assessing Risk of Water Pollution. Journal American Water Resources Association. 36:1417-1422. 

Reckhow, K.H., and S.C. Chapra. 1999. Modeling Excessive Nutrient Loading in the Environment. Environmental Pollution. 100:197-207. pdf file

Reckhow, K.H. 1999. Water Quality Prediction and Probability Network Models.  Canadian Journal of Fisheries and Aquatic Sciences. 56:1150-1158. pdf file

Reckhow, K.H. 1999. Lessons from Risk Assessment. Human and Ecological Risk Assessment. 5:245-253. pdf file

Olson, A., R., J. Sedransk, D. Edwards, C.A.Gotway, W. Liggett, S. Rathbun, K. H. Reckhow, and L.J. Young. 1999. Statistical Issues for Monitoring Ecological and Natural Resources in theUnited States. Environmental Monitoring and Assessment. 54:1-45.

Qian, S.S., and K.H. Reckhow. 1998. Modeling Phosphorus Trapping in Wetlands Using Nonparametric Bayesian Regression.  Water Resources Research. 34:1745-1754. postscript manuscript

Dominici, F., G. Parmigiani, R.L. Wolpert,  and K.H. Reckhow. 1997. Combining Information from Related Regressions. Journal of Agricultural, Biological, and Environmental Statistics. 2:313-332. postscript manuscript

Mew, H. E., Jr., M.A. Medina, Jr., R.C. Heath, K.H. Reckhow, and T. L. Jacobs. 1997. Cost-Effective Monitoring Strategies to Estimate Mean Water-Table Depth. Ground Water. 35:1089-1096.

Reckhow, K.H., K.S. Korfmacher, and N.G. Aumen. 1997. Decision Analysis to Guide Lake Okeechobee Research Planning. Lakeand Reservoir Management. 13:49-56.

Reckhow, K.H., and N.G. Aumen. 1997. Uncertainty Analysis and Simulation Modeling for Lake Okeechobee Research Prioritization. Lake and Reservoir Management. 13:44-48.

Steinberg, L.J., K.H. Reckhow, and R.L. Wolpert.1997. Characterization of Parameters in Mechanistic Models: A Case Study of PCB Fate and Transport in Surface Waters. Ecological Modelling. 97:35-46. (postscript manuscript)

Lamon, E.C., K.H. Reckhow, and K.E. Havens. 1996. Using Generalized Additive Models for Prediction of Chlorophyll a in Lake Okeechobee, Florida. Lakes & Reservoirs: Research and Management. 2:37-46.

Hession, W.C., D.E. Storm, C.T. Haan, K.H. Reckhow, and M.D. Smolen. 1996. Risk Analysis of Total Maximum Daily Loads in an Uncertain Environment Using EUTROMOD. Lake and Reservoir Management. 12:331-347.

Reckhow, K.H. 1996. Improved Estimation of Ecological Effects Using an Empirical Bayes Method. Water Resources Bulletin. 32:929-935.

Stow, C., and K.H. Reckhow. 1996. Estimator Bias in a Lake Phosphorus Model with Observation Error. Water Resources Research. 32:165-170. 

Steinberg, L.J., K.H. Reckhow, and R.L. Wolpert. 1996. Bayesian Model for Fate and Transport of PCB in Upper Hudson River. Journal of Environmental Engineering, 122:341-349. 

Qian, S.S., K.H. Reckhow, and M.L. Lavine. 1994. Wetland Modeling Using Nonparametric Bayes Analysis. Proceedings, International Symposium on Water Quality Modeling, Kissimmee, FL. 

Reckhow, K.H. and S.S. Qian. 1994. Modeling Phosphorus Trapping in Wetlands Using Generalized Additive Models. Water Resources Research. 30:3105-3114. 

Reckhow, K.H. 1994. A Decision Analytic Framework for Environmental Analysis and Simulation Modeling. Environmental Toxicologyand Chemistry. 13:1901-1906. 

Reckhow, K.H. 1994. Water Quality Simulation Modeling and Uncertainty Analysis for Risk Assessment and Decision Making. Ecological Modelling. 72:1-20.

Reckhow, K.H. 1994. The Importance of Scientific Information in Decision Making. Environmental Management. 18:161-166. 

Reckhow, K.H., and C. Stow. 1994. Ecological Impacts of Excess Nutrients in the Environment: Issues, Management, and Decision Making. In: Economic Issues Associated with Nutrient ManagementPolicy. P.E. Norris and L.E. Danielson, eds. p. 5-19. SRIEG-10, No. 32. Southern Rural Development Center, Mississippi State University, Mississippi State, MS. 

Reckhow, K.H. 1993. A Random Coefficient Model for Chlorophyll-Nutrient Relationships in Lakes. Ecological Modelling. 70:35-50. 

Wolpert, R.L., L.J. Steinberg, and K.H. Reckhow. 1993. Bayesian Decision Support Using Environmental Transport and Fate Models. In: Case Studies in Bayesian Statistics. C. Gatsonis, R. Kass, J. Hodges, and N.D. Singpurwalla, eds. p. 241-270. Springer-Verlag. New York. 

Reckhow, K.H. 1993. Lake Ecosystem Modelling (p. 315-318); Trophic State Criteria (p. 630-631); and Validation of Simulation Models: Philosophy and Statistical Methods of Confirmation (p. 656-660). all in: Concise Encyclopedia of Environmental Systems. P.C. Young, ed. Pergamon Press. Oxford, UK. 

Reckhow, K.H. 1992. Decision Theory Applied to Product Life Cycle Assessment. In: Proceedings of the Product Life Cycle Assessment Workshop. Society of Environmental Toxicology and Chemistry, Pensacola, FL. 

Reckhow, K.H. 1990. Bayesian Inference in Non-Replicated Ecological Studies. Ecology. 71:2053-2059.

Reckhow, K.H., J.T. Clements, and R.C.Dodd. 1990. Statistical Evaluation of Mechanistic Water Quality Models. Journal of Environmental Engineering. 116:250-268. 

Reckhow, K.H., and C. Stow. 1990. Monitoring Design and Data Analysis for Trend Detection. Lake and Reservoir Management. 6:49-60. 

Technical Guidance Documents

Reckhow, K.H., and W. Warren-Hicks. 1994. Biological Criteria: Technical Guidance for Survey Design and Statistical Evaluationof Biosurvey Data. Draft final report prepared for USEPA, Washington, DC. 63 pp. 

Reckhow, K.H., K. Kepford, and W. Warren-Hicks. 1993. Methods for the Analysis of Lake Water Quality Trends. EPA 841-R-93-003. Washington, DC. 84 pp. (includes software). Available from EPA Publications.

Reckhow, K.H., S.C. Coffey, M.H. Henning, K.Smith, and R. Banting. 1992. EUTROMOD: Technical Guidance and Spreadsheet Models for Nutrient Loading and Lake Eutrophication. North American Lake Management Society. 95 pp. (includes spreadsheet software). The spreadsheet program and the users manual, may be ordered from the North American Lake Management Society, NALMS, at 608-233-2836 or at the NALMS homepage.

Gaugush, R. F., D.C. Blouin, J.P. Geaghan, K.H. Reckhow, and W.G. Warren. 1986. Statistical Methods for Reservoir Water Quality Investigations. Instruction Report E-86-2. US Army Corps of Engineers Waterways Experiment Station. Vicksburg, MS. 216 pp. 

Reckhow, K.H., J.T. Clements and R.C. Dodd. 1986. Statistical Goodness-of-Fit Measures for Waste Load Allocation Models. Project completion report to the U.S. Environmental Protection Agency, Washington, DC. 68 pp. 

Reckhow, K.H. 1981. Lake Data Analysis and Nutrient Budget Modeling. United States Environmental Protection Agency, EPA-600/3-81-011, 97 pp. 

Reckhow, K.H., M. Beaulac, and J. Simpson. 1980. Modeling Phosphorus Loading and Lake Response Under Uncertainty: A Manual and Compilation of Export Coefficients. U.S. Environmental ProtectionAgency, EPA-440/5-80-011, 214 pp. Available from EPA Publications.

Reckhow, K.H. 1979. Quantitative Techniques for the Assessment of Lake Quality. Michigan Dept. of Natural Resources (1978) and U.S. Environmental Protection Agency (1979), EPA - 440/5-79-015, 146 pp. Available from EPA Publications.
 

Unpublished Manuscripts

Water Quality Prediction, Mechanism, and Probability Network Models: This is a postscript file of a recent (December, 1996) manuscript. 

These are postscript files of short discussion papers (November, 1996) on uncertainty and the scientific basis for model specification.

• Reaction Rates and Uncertainty in Water Quality Models
• Issues in Parameter Selection: Phytoplankton Settling Velocity

Uncertainty in Water Quality Modeling and Assessment - This is a postscript file of a manuscript (November, 1996) on uncertainty.
 

EUTROMOD

Eutromod is a spreadsheet-based model that is used for the prediction of nutrient runoff and lake eutrophication for individual lakes in the US. With the model, phosphorus and nitrogen runoff may be predicted using either nutrient loading functions or nutrient export coefficients. The nutrient loading functions are based on the rational formula for dissolved nutrients, and the universal soil loss equation for sediment-attached nutrients. The sediment delivery ratio is addressed with user-defined trapping zones.

Lake eutrophication response is predicted based on a set of regional statistical models. Respose variables include:total phosphorus concentration, total nitrogen concentration, chlorophylla level, Secchi disk depth and in some cases - probability of hypolimnetic anoxia and probability of blue-green algal dominance. The spreadsheet program, and a users manual, may be ordered from the North American Lake Management Society, NALMS, at 608-233-2836 or at the NALMS web site .

Personal Interests

Some Interesting Sites:

• Duke Sports Online
• Carolina Godiva Track Club

Family:

• Ellen
• Sarah
• Michael

Links to Other Sites

School of the Environment, Duke University

Civil and Environmental Engineering, Duke University

Civil Engineering, North Carolina State University
 
 

ENV335 Water Quality Monitoring Class

Fall, 2000

Instructor: Dr. Kenneth H. Reckhow, A317ALSRC,613-8026, reckhow@duke.edu
Office Hours: Wednesday 1:30 - 3:30; Friday 9:30-11:30

Class Schedule and Lecture Topic (Readings)

1. Introduction (Reckhow & Chapra, Chapter 1)

2. Basic modeling concepts (Reckhow 1994b;
   Chapra and Reckhow, Chapter 10)
3. Probability network models (Reckhow 1996) 
4. Stream DO models (Chapra 1997, Lectures19-21)
5. Uncertainty analysis (Reckhow andChapra, Chapter 2)
6. Mechanistic models - QUAL2E (Chapra1997, Lecture 26, 36)
7. Pollutant runoff models (Novotny and Olem, Chapter 9)
8. Lake eutrophication models (Chapra 1997, Lecture 29)
9. Trend analysis (Reckhow, Kepford, and Warren-Hicks 1994)
10. To be determined
11. Statistical modeling 
12. Toxic substances (Chapra 1991)
13. Final issues

Course Objective: To acquaint students with problems and approaches in surface water quality modeling, with particular attention to model choice and applications for management.

Course Requirements: Six problem sets, weekly written literature reviews, readings, and active participation inclass discussion.

Standard Class Format: first half lecture and second half discussion.

Expected Assignment Schedule: Each assignment will have two weeks for completion; the first assignment will be given on the first day of class. Assignment topics and expected sequence are:

1. model selection criteria
2. probability network models
3. stream DO model error analysis
4. pollutant runoff models 
5. water quality trend analysis
6. statistical modeling

Readings: There is no class  textbook; instead, copies of all readings will be distributed in class.

Additional useful websites:

• EPA TMDLs
• ODU list of WQ model sites
• USGS Water Research Abstracts

Literature Reviews: Each week, a paper from the recent professional literature will be assigned for reading and critique. Written reviews (approximately three pages) will be due the following week, and the second half of that class will be devoted to a discussion of the paper and related issues. For each reading, the written review should provide a brief summary, your own comments on the paper, and answers to questions; these will provide the initial basis for class discussion.