Multiobjective calibration with Pareto preference ordering: An application to rainfall-runoff model calibration

Water Resources Research

Volumn 41, Issue 3, 2005, Pages 1-14

  Soon, Thiam Khu ^a   Madsen, Henrik ^b  

^a UNIVERSITY OF EXETER   (United Kingdom)

^b DHI   (Denmark)

Author keywords

[No Author keywords available]

Indexed keywords

CALIBRATION; CATCHMENTS; GENETIC ALGORITHMS; MATHEMATICAL MODELS; OPTIMIZATION; PARETO PRINCIPLE; RAIN; WATER RESOURCES;

COMPUTATIONAL POWER; HYDROLOGIC MODELS; OPTIMIZATION TECHNIQUES; PARETO PREFERENCE;

HYDROLOGY;

CALIBRATION; HYDROLOGICAL MODELING; MULTIOBJECTIVE PROGRAMMING; RAINFALL-RUNOFF MODELING;

EID: 17844379254     PISSN: 00431397     EISSN: None     Source Type: Journal    
DOI: 10.1029/2004WR003041     Document Type: Article

References (32)

1. ASCE Task Committee (1993), Definition of criteria of evaluation of watershed models, J. Irrig. Drain. Eng., 119(3), 429-442.
2. Baffaut, C., and J. W. Delleur (1988), Expert system for calibrating SWMM, J. Water Resour. Plann. Manage., 115(3), 278-298.
3. Boyle, D. P., H. V. Gupta, and S. Sorooshian (2000), Toward improved calibration of hydrologic models: Combining the strengths of manual and automatic methods, Water Resour. Res., 35(12), 3663-3674.
4. Cheng, C. T., C. P. Ou, and K. W. Chau (2002), Combining a fuzzy optimal model with a genetic algorithm to solve multi-objective rainfall-runoff model calibration, J. Hydrol., 268( 1-4), 72-86.
5. Cooper, V. A., V. T. V. Nguyen, and J. A. Nicell (1997), Evaluation of global optimization methods for conceptual rainfall-runoff model calibration, Water Sci. Technol., 36(5), 53-60.
6. Das, I. (1999), A preference ordering among various Pareto optimal alternatives, Struct. Opt., 18(1), 30-35.
7. Deb, K., S. Agrawal, A. Pratap, and T. Meyarivan (2000), A fast elitist non-dominated sorting genetic algorithm for multi-objective optimization: NSGA-II, in Proceedings of the Parallel Problem Solving Form Nature VI Conference, Lect. Notes in Comput. Sci., vol. 1917, edited by M. Schoenauer et al., pp. 849-858, Springer, New York.
8. Duan, Q. Y., S. Sorooshian, and V. Gupta (1992), Effective and efficient global optimization for conceptual rainfall-runoff models, Water Resour. Res., 28(4), 1015-1031.
9. Franchini, M., G. Galeati, and S. Berra (1998), Global optimization techniques for the calibration of conceptual rainfall-runoff models, Hydrol. Sci. J., 43(3), 443-458.
10. Goldberg, D. E. (1989), Genetic Algorithms in Search, Optimisation and Machine Learning, Addison-Wesley, Boston, Mass.
11. Gupta, V. K., and S. Sorooshian (1985), The automatic calibration of conceptual catchment models using derivative-based optimization algorithms, Water Resour. Res., 21(4), 473-485.
12. Gupta, H. V., S. Sorooshian, and P. O. Yapo (1998), Toward improved calibration of hydrological models: Multiple and noncommensurable measures of information, Water Resour. Res., 34(4), 751-763.
13. Gupta, H., S. Sorooshian, and P. O. Yapo (1999), Status of automatic calibration for hydrological models: Comparison with multilevel expert calibration, J. Hydrol. Eng., 4(2), 135-143.
14. Havnø, K., M. N. Madsen, and J. Dørge (1995), MIKE 11 - A generalized river modeling package, in Computer Models of Watershed Hydrology, edited by V. P. Singh, pp. 733-782, Water Resour. Publ., Highlands Ranch, Colo.
15. Holland, J. H. (1975), Adaptation in Natural and Artificial Systems, Univ. of Mich. Press, Ann Arbor.
16. Ibbitt, R. P., and T. O'Donnell (1971), Fitting methods for conceptual catchment models, J. Hydraul. Div. Am. Soc. Civ. Eng., 7(9), 1331-1342.
17. Johnston, P. R., and D. H. Pilgrim (1976), Parameter optimization for watershed models, Water Resour. Res., 12(3), 477-486.
18. Khu, S. T., and M. J. Werner (2003), Reduction of Monte-Carlo runs for uncertainty estimation in hydrological modelling, Hydrol. Earth Syst. Sci., 7(5), 680-692.
19. Klemes, V. (1986), Operational testing of hydrological simulation models, Hydrol. Sci. J., 31(1), 13-24.
20. Liong, S. Y., S. T. Khu, and W. T. Chan (2001), Derivation of Pareto front with genetic algorithm and neural network, J. Hydrol. Eng., 6(1), 52-61.
21. Madsen, H. (2000), Automatic calibration of a conceptual rainfall-runoff model using multiple objectives, J. Hydrol., 235, 276-288.
22. Madsen, H. (2003), Parameter estimation in distributed hydrological catchment modelling using automatic calibration with multiple objectives, Adv. Water Resour., 26(2), 205-216.
23. Madsen, H., and S. T. Khu (2002), Parameter estimation in hydrological modelling using multi-objective optimization, in Proceedings of the 5th International Conference on Hydroinformatics, edited by R. A. Falconer et al., pp. 1160-1165, Int. Water Assoc., London.
24. Madsen, H., G. Wilson, and H. C. Ammentorp (2002), Comparison of different automated strategies for calibration of rainfall-runoff models, J. Hydrol., 261, 48-59.
25. Nielsen, S. A., and E. Hansen (1973), Numerical simulation of the rainfall runoff process on a daily basis, Nord. Hydrol., 4, 171-190.
26. Refsgaard, J. C., and B. Storm (1996), Construction, calibration and validation of hydrological models, in Distributed Hydrological Modelling, edited by M. B. Abbott and J. C. Refsgaard, pp. 41-54, Springer, New York.
27. Sorooshian, S., Q. Y. Duan, and V. K. Gupta (1993), Automatic calibration of conceptual rainfall-runoff models: Application of global optimization to the Sacramento soil moisture accounting model, Water Resour. Res., 29(4), 1185-1194.
28. Thyer, M., G. Kuczera, and B. C. Bates (1999), Probabilistic optimization for conceptual rainfall-runoff models: A comparison of the shuffled complex evolution and simulated annealing algorithms, Water Resour. Res., 35(3), 767-773.
29. van Griensven, A., and W. Bauwens (2001), Multi-objective calibration in integrated river basin modelling, paper presented at the 26th General Assembly, Eur. Geophys. Soc., Nice, France, 25-30 March.
30. Wang, Q. J. (1991), The genetic algorithm and its application to calibrating conceptual rainfall-runoff models, Water Resour. Res., 27(9), 2467-2471.
31. Yapo, P. O., H. V. Gupta, and S. Sorooshian (1998), Multi-objective global optimization for hydrologic models, J. Hydrol., 204, 83-97.
32. Zitzler, E., K. Deb, and L. Thiele (2000), Comparison of multi-objective evolutionary algorithms: Empirical results, Evol. Comput., 8(2), 173-195.