Risk-based modelling of surface water quality: A case study of the Charles River, Massachusetts

Journal of Hydrology

Volumn 274, Issue 1-4, 2003, Pages 225-247

  McIntyre, Neil R ^a   Wagener, Thorsten ^b   Wheater, Howard S ^a   Chapra, Steven C ^c  

^a IMPERIAL COLLEGE LONDON   (United Kingdom)

^b UNIVERSITY OF ARIZONA   (United States)

^c TUFTS UNIVERSITY   (United States)

Author keywords

Eutrophication; Monte Carlo; Risk; Sensitivity analysis; Water quality

Indexed keywords

COMPUTER SIMULATION; DATA REDUCTION; EUTROPHICATION; MONTE CARLO METHODS; OXYGEN; RIVERS; SENSITIVITY ANALYSIS; SURFACE WATERS; WASTEWATER TREATMENT; WATER QUALITY;

RISK-BASED MODELLING;

HYDROLOGY;

EUTROPHICATION; RISK ASSESSMENT; RIVER WATER; SENSITIVITY ANALYSIS; WATER QUALITY;

CHARLES RIVER; MASSACHUSETTS; UNITED STATES;

EID: 0037376313     PISSN: 00221694     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0022-1694(02)00417-1     Document Type: Article

References (37)

1. Ambrose, R.B., Barnwell, T.O., McCutcheon, S.C., William, J.R., 1996. Computer models for water quality analysis. In: Mays, L.W., (Ed.), Water Resources Handbook, McGraw-Hill, New York, pp. 14.1-14.28.
2. Ang, A.H.S., Tang, W.H., 1975. Probability concepts in engineering planning and design. Vol. 1 - basic principles, Wiley, New York.
3. Bastidas, L.A., Gupta, H.V., Sorooshian, S., Shuttleworth, W.J., Yang, Z.L., 1999. Sensitivity analysis of a land surface scheme using multicriteria methods. Journal of Geophysical Research 104 (D16), 19481-19490.
4. Beck, M.B., 1987. Uncertainty in water quality models. Water Resources Research 23 (8), 1393.
5. Beck, M.B., 1997. Applying systems analysis in managing the water environment: towards a new agenda. Water Science and Technology 36 (5), 1-17.
6. Beck, M.B., 1999. Coping with ever larger problems, models, and data bases. Water Science and Technology 39 (4), 1-11.
7. Beven, K.J., Binley, A.M., 1992. The future of distributed models; model calibration and predictive uncertainty. Hydrological Processes 6, 279-298.
8. Bowie, G.L., Williams, B.M., Porcella, D.B., Campbell, C.L., Pagenkopf, J.R., Rupp, G.L., Johnson, K.M., Chen, P.W.H., Gherini, S.A., 1985. Rates, Constants and Kinetics Formulations in Surface Water Quality (2nd Edition). EPA/600/3-85/040.
9. Brown, L.C., Barnwell, T.O., 1987. The enhanced stream water quality models QUAL2E and QUAL2E-UNCAS: documentation and user manual. Report No. EPA/600/3-87/007, US EPA, Athens, Georgia, USA.
10. CDM, 1997. Charles River Pollution Control District/Town of Holliston, Massachusetts: Upper Charles River Wasteload Allocation Study, Camp, Dresser and McKee, Inc., Cambridge, MA, USA.
11. CEC, 2000. Directive 2000/60/EC of the European Parliament and of the Council of 23rd October 2000 establishing a framework for Community action in the field of water policy, Council of the European Community, Brussels.
12. Chapra, S.C., 1997. Surface Water-Quality Modeling, McGraw-Hill, New York.
13. Chatfield, 1995. Model uncertainty, data mining and statistical inference. Journal of the Royal Statistical Society (A) 158 (3), 419-466.
14. CRWA, 2000. Charles River Watershed Association Annual Report 2000. Available from www.crwa.org.
15. Gardner, R.H., O'Neill, R.V., Mankin, J.B., Kumar, D., 1980. Comparative error analysis of six predator prey models. Ecology'6 (2), 323-332.
16. Henderson-Sellers, B., Henderson-Sellers, A., 1993. Factorial techniques for testing environmental model sensitivity. In: Jakeman, A.J., Beck, M.B., McAleer, M.J. (Eds.), Modelling Changes in Environmental Systems, Wiley, New York, pp. 59-76.
17. Hornberger, G.M., Spear, R.C., 1980. Eutrophication in Peel Inlet. 1. Problem-defining behaviour and a mathematical model for the phosphorus scenario. Water Research 14, 29-42.
18. Ivanov, P., Masliev, I., Kularathna, M., De Marchi, C., Somlyódy, L., 1996. DESERT User Manual. International Institute for Applied Systems Analysis, Laxenburg, Austria/Institute for Water and Environmental Problems, Barnaul, Russia.
19. Kuczera, G., 1983. Improved parameter inference in catchment models 1. Evaluating parameter uncertainty. Water Resources Research 19 (5), 1151-1162.
20. MacKay, M.D., Beckman, R.J., Conover, W.J., 1979. A comparison of three methods for selecting values of input variables in the analysis of output from a computer code. Technometrics 21 (2), 239-245.
21. McIntyre, N., Zeng, S., 2002. WaterRAT User Manual (Version 1). A Report to the European Commission. Department of Civil and Environmental Engineering, Imperial College, London, UK.
22. McIntyre, N., Wheater, H.S., Lees, M.J., 2002a. Estimation and propagation of parametric uncertainty in environmental models. Journal of Hydroinformatics 4 (3), 177-198.
23. McIntyre, N., Jackson, B., Wheater, H.S., Chapra, S., 2002b. Role of numerical efficiency in the viability of Monte Carlo simulation of the environment - a case study of river thermodynamics. Journal of Environment Engineering (ASCE) (Acceptef for publication).
24. Meixner, T., Gupta, H.V., Bastidas, L.A., Bales, R.C., 1999. Sensitivity analysis using mass flux and concentration. Hydrological Processes 13, 2233-2244.
25. Reckhow, K.H., 1994. Water quality simulation modeling and uncertainty analysis for risk assessment and decision making. Ecological Modelling 72 (1/2), 1-20.
26. Reichart, P., Omlin, M., 1996. On the usefulness of over-parameterised ecological models. Ecological Modelling 95, 289-299.
27. Spear, R.C., Hornberger, G.M., 1980. Eutrophication in peel inlet-2. Identification of critical uncertainties via generalized sensitivity analysis. Water Research 14 (1), 43-49.
28. Thomann, R.V., Mueller, J.A., 1987. Principles of Surface Water Quality Modeling and Control, Addison-Wesley, Reading, MA.
29. UK Environment Agency, 2001. SIMCAT 7.6: A Guide and Reference for Users. UK Environment Agency, Bristol, UK.
30. Van der Perk, M., 1997. Effect of model structure on the accuracy and uncertainty of results from water quality models. Hydrological Processes 11 (3), 227-239.
31. Van Straten, G., 1998. Models for water quality management: the problem of structural change. Water Science and Technology 37 (3), 103-111.
32. Wagener, T., McIntyre, N., Lees, M.J., Wheater, H.S., Gupta, H.V., 2002. Reducing uncertainty in conceptual rainfall-runoff modelling: dynamic identifiability analysis. Hydrological and Earth System Sciences 5 (1), 13-26.
33. Whitehead, P.G., Hornberger, G.M., 1984. Modelling algal behaviour in the River Thames. Water Research 18 (8), 945-953.
34. Whitehead, P.G., Toms, I.P., 1993. Dynamic modelling of nitrate in reservoirs and lakes. Water Research 27 (8), 1377-1384.
35. Whitehead, P.G., Young, P., 1979. Water quality in river systems: Monte Carlo analysis. Water Resources Research 15 (2), 451-459.
36. Yapo, P.O., Gupta, H.V., Sorooshian, S., 1998. Multi-objective global optimization for hydrological models. Journal of Hydrology 204 (1-4), 83-97.
37. Young, P., Parkinson, S., Lees, M., 1996. Simplicity out of complexity in environmental modelling: Occam's razor revisited. Journal of Applied Statistics 23 (2), 165-210.