Sensitivity and uncertainty analysis of the conceptual HBV rainfall-runoff model: Implications for parameter estimation

Journal of Hydrology

Volumn 389, Issue 3-4, 2010, Pages 301-310

  Abebe, Nibret A ^a   Ogden, Fred L ^a   Pradhan, Nawa R ^a  

^a UNIVERSITY OF WYOMING   (United States)

Author keywords

DYNIA; HBV; Identifiability analysis; Model structure; Sensitivity analysis

Indexed keywords

COLLINS; DYNAMIC BEHAVIORS; FLOW SERIES; HBV MODEL; HYDROCLIMATIC CONDITIONS; HYDROLOGICAL FORECASTING; HYDROLOGICAL MODELS; HYDROLOGICAL PROCESS; IDENTIFIABILITY; IDENTIFIABILITY ANALYSIS; MISSISSIPPI; MONTE CARLO; MULTI OBJECTIVE; OBJECTIVE MEASURE; RAINFALL-RUNOFF MODELS; RIVER CATCHMENT; RUNOFF VOLUMES; SHUFFLED COMPLEX EVOLUTION; STRUCTURE SENSITIVITY; TEMPORAL CHANGE; TIME VARYING; WATER BALANCE;

CATCHMENTS; DYNAMIC ANALYSIS; ERRORS; PARAMETER ESTIMATION; RUNOFF; SENSITIVITY ANALYSIS; STREAM FLOW;

UNCERTAINTY ANALYSIS;

ALGORITHM; CATCHMENT; MONTE CARLO ANALYSIS; PARAMETERIZATION; RAINFALL-RUNOFF MODELING; SENSITIVITY ANALYSIS; STREAMFLOW; UNCERTAINTY ANALYSIS; WATER BUDGET; WATER LEVEL;

LEAF BASIN; MISSISSIPPI; UNITED STATES;

HEPATITIS B VIRUS;

EID: 77955056639     PISSN: 00221694     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jhydrol.2010.06.007     Document Type: Article

References (29)

1. Bergstrom, S., 1976. Development and Application of a Conceptual Runoff Model for Scandinavian Catchments. Report RHO 7, Swedish Meteorological and Hydrological Institute, Norrkoping, Sweden, 134 pp.
2. Von Bertalanffy L. The theory of open systems in physics and biology. Science New Series 1950, 111(2872):23-29.
3. Beven K.J., Binley A. The future of distributed models: model calibration and uncertainty prediction. Hydrol. Process. 1992, 6:279-298.
4. Beven K., Freer J. Equifinality, data assimilation, and uncertainty estimation in mechanistic modelling of complex environmental systems using the GLUE methodology. J. Hydrol. 2001, 249:11-29.
5. Bronstert A., Niehoff D., Bürger G. Effects of climate and land-use change on storm runoff generation: present knowledge nd modelling capabilities. Hydrol. Process. 2002, 16:509-529. 10.1002/hyp. 326.
6. Butts B.M., Payne T.J., Kristensen M., Madsen H. An evaluation of the impact of model structure on hydrological modeling uncertainty for stream flow simulation. J. Hydrol. 2004, 298:242-266.
7. Cullmann J., Wriedt G. Joint application of event-based calibration and dynamic identifiability analysis in rainfall-runoff modeling: implications for model parameterization. J. Hydroinform. 2008, 10(4):301-316. 10.2166/hydro.2008.055.
8. Duan Q., Gupta V.K., Sorooshian S. Effective and efficient global optimization for conceptual rainfall-runoff models. Water Resour. Res. 1992, 28(4):1015-1031.
9. Harlin J., Kung C.S. Parameter uncertainty and simulation of design floods in Sweden. J. Hydrol. 1992, 137:209-230.
10. Huang M., Liang X. On the assessment of the impact of reducing parameters and identification of parameter uncertainties for a hydrologic model with applications to ungauged basins. J. Hydrol. 2006, 320:37-61.
11. Lee B., Moon Y. Analysis and development of conceptual rainfall-runoff model structures for regionalization purposes. KSCE J. Civil Eng. 2007, 11(1):57-64.
12. Madsen H. Automatic calibration of a conceptual rainfall-runoff model using multiple objectives. J. Hydrol. 2000, 235:276-288.
13. McCuen R.H. The role of sensitivity analysis in hydrologic modeling. J. Hydrol. 1973, 18:37-53.
14. Seibert J. Multi-criteria calibration of a conceptual runoff model using a genetic algorithm. Hydrol. Earth Syst. Sci. 2000, 4(2):215-224.
15. Senarath S.U.S., Ogden F.L., Downer C.W., Sharif H.O. On the calibration and verification of two-dimensional, distributed, hortonian, continuous watershed models. Water Resour. Res. 2000, 36:1495-1510.
16. Shulla, J., 1997. Hydrologische Modellierung von Flussgebieten zur Abschätzung der Folgen von Klimaänderungen, Diss., ETH Zürick, CH, 161 pp.
17. Sieber A., Uhlenbrook S. Sensitivity analyses of a distributed catchment model to verify the model structure. J. Hydrol. 2005, 310:216-235.
18. Sorooshian S., Gupta V.K., Fulton J.L. Evaluation of maximum likelihood parameter estimation techniques for conceptual rainfall-runoff models: influence of calibration data variability and length on model credibility. Water Resour. Res. 1983, 19:251-259.
19. Sorooshian S., Duan Q., Gupta V.J. Calibration of rainfall-runoff models: application of global optimization to the sacramento soil moisture accounting model. Water Resour. Res. 1993, 29(4):1185-1194.
20. Spear R.C., Hornberger G.M. Eutrophication in peel inlet, II, identification of critical uncertainties via generalized sensitivity analysis. Water Res. 1980, 14:43-49.
21. Tripp D.R., Niemann J.D. Evaluating the parameter identifiability and structural validity of a probability-distributed model for soil moisture. J. Hydrol. 2008, 353:93-108.
22. Uhlenbrook S., Seibert J., Leibundgut C., Rodhe A. Prediction uncertainty of conceptual rainfall-runoff models caused by problems in identifying model parameters and structure. Hydrol. Sci. - J. Sci. Hydrol. 1999, 44(5).
23. Vrugt J.A., Gupta V.H., Bastidas L.A., Bouten W., Sorooshian S. Effective and efficient algorithm for multi-objective optimization of hydrologic models. Water Resour. Res. 2003, 39(8):1214. 10.1029/2002WR001746.
24. Wagener, T., 2004. Monte-Carlo Analysis Toolbox User Manual. Penn State University.
25. Wagener T., McIntyre N., Lees M.J., Wheater H.S., Gupta H.V. Towards reduced uncertainty in conceptual rainfall-runoff modeling: dynamic identifiability analysis. Hydrol. Process. 2003, 17:455-476.
26. Wriedt G., Rode M. Investigation of parameter uncertainty and identifiability of the hydrological model WaSiM-ETH. Adv. Geosci. 2006, 9:145-150.
27. Yapo P.O., Gupta H.V., Sorooshian S. Automatic calibration of conceptual rainfall-runoff models: sensitivity to calibration data. J. Hydrol. 1996, 181:23-48.
28. Yapo P.O., Gupta V.H., Sorooshian S. Multi-objective global optimization for hydrologic models. J. Hydrol. 1998, 204:83-97.
29. Yapo P.O., Gupta H.V., Sorooshian S. Towards improved calibration of hydrologic models: combining the strengths of manual and automatic calibration methods. Water Resour. Res. 2000, 36(12):3663-3674.