Separately accounting for uncertainties in rainfall and runoff: Calibration of event-based conceptual hydrological models in small urban catchments using Bayesian method

Water Resources Research

Volumn 49, Issue 9, 2013, Pages 5381-5394

  Sun, Siao ^a   Bertrand Krajewski, Jean Luc ^a  

^a UNIVERSITÉ DE LYON   (France)

Author keywords

Bayesian method; calibration; hydrological model; MCMC method; rainfall uncertainty

Indexed keywords

BAYESIAN NETWORKS; CALIBRATION; CATCHMENTS; CLIMATE MODELS; ERRORS; LOW PASS FILTERS; RAIN; RESERVOIRS (WATER); RUNOFF;

BAYESIAN METHODS; HYDROLOGICAL MODEL CALIBRATIONS; HYDROLOGICAL MODELING; LIKELIHOOD FUNCTIONS; MCMC METHOD; MODEL STRUCTURAL UNCERTAINTIES; PREDICTIVE UNCERTAINTY; RAINFALL UNCERTAINTIES;

UNCERTAINTY ANALYSIS;

BAYESIAN ANALYSIS; CALIBRATION; ERROR ANALYSIS; HYDROLOGICAL MODELING; PARAMETERIZATION; RAINFALL; RUNOFF; UNCERTAINTY ANALYSIS; URBAN DRAINAGE;

EID: 84883278427     PISSN: 00431397     EISSN: 19447973     Source Type: Journal    
DOI: 10.1002/wrcr.20444     Document Type: Article

References (40)

1. Balin, D., H. Lee, and, M. Rode, (2010), Is point uncertain rainfall likely to have a great impact on distributed complex hydrological modeling?, Water Resour. Res., 46, W11520, doi: 10.1029/2009WR007848.
2. Bates, B. C., and, E. P. Campell, (2001), A Markov chain Monte Carlo scheme for parameter estimation and inference in conceptual rainfall-runoff modeling, Water Resour. Res., 37 (4), 937-947, doi: 10.1029/2000WR900363. (Pubitemid 32516048)
3. Bertrand-Krajewski, J.-L., and, J.-P. Bardin, (2002), Evaluation of uncertainties in urban hydrology: Application to volumes and pollutant loads in a storage and settling tank, Water Sci. Technol., 45 (4-5), 437-444. (Pubitemid 34256568)
4. Beven, K. J., and, A. M. Binley, (1992), The future of distributed models: Model calibration and uncertainty prediction, Hydrol. Processes, 6, 279-298.
5. Blasone, R. S., J. A. Vrugt, H. Madsen, D. Rosbjerg, B. A. Robinson, G. A. Zyvoloski, (2008), Generalized likelihood uncertainty estimation (GLUE) using adaptive Markov chain Monte Carlo sampling, Adv. Water Resour., 31 (4), 630-648.
6. Ciach, J. G., (2002), Notes and correspondence: Local random errors in tipping-bucket rain gauge measurements, J. Atmos. Ocean Technol., 20, 752-759.
7. Deletic, A., et al. (2012), Assessing uncertainties in urban drainage models, Phys. Chem. Earth, 42-44, 3-10.
8. Dotto, C. B. S., M. Kleidorfer, A. Deletic, W. Rauch, D. T. McCarthy, and, T. D. Fletcher, (2011), Performance and sensitivity analysis of stormwater models using a Bayesian approach and long-term high resolution data, Environ. Modell. Software, 26, 1225-1239.
9. Dotto, C. B. S., G. Mannina, M. Kleidorfer, L. Vezzaro, M. Henrichs, D. T. McCarthy, G. Freni, W. Rauch, and, A. Deletic, (2012), Comparison of different uncertainty techniques in urban stormwater quantity and quality modeling, Water Res., 46 (8), 2545-2558, doi: 10.1016/j.watres.2012.02.009.
10. Gelman, A., and, D. B. Rubin, (1992), Inference from iterative simulation using multiple sequences, Stat. Sci., 7 (4), 457-511.
11. Heistermann, M., and, D. Kneis, (2011), Benchmarking quantitative precipitation estimation by conceptual rainfall-runoff modeling, Water Resour. Res., 47, W06514, doi: 10.1029/2010WR009153.
12. Huard, D., and, A. Mailhot, (2006), A Bayesian perspective on input uncertainty in model calibration: Application to hydrological model "abc," Water Resour. Res., 42, W07416, doi: 10.1029/2005WR004661.
13. Huard, D., and, A. Mailhot, (2008), Calibration of hydrological model GR2M using Bayesian uncertainty analysis, Water Resour. Res., 44, W02424, doi: 10.1029/2007WR005949.
14. Jin, X., C. Y. Xu, Q. Zhang, and, V. P. Singh, (2010), Parameter and modeling uncertainty simulated by GLUE and a formal Bayesian method for a conceptual hydrological model, J. Hydrol., 383 (3-4), 147-155.
15. Kavetski, D. S. W., Franks, and G., Kuczera, (2002), Confronting input uncertainty in environmental modeling, in calibration of watershed models, Water Sci. Appl., 6, 49-68.
16. Kavetski, D., G. Kuczera, and, S. W. Franks, (2006a), Bayesian analysis of input uncertainty in hydrological modeling. 1. Theory, Water Resour. Res., 42, W03407, doi: 10.1029/2005WR004368.
17. Kavetski, D., G. Kuczera, and, S. W. Franks, (2006b), Bayesian analysis of input uncertainty in hydrological modeling. 2. Application, Water Resour. Res., 42, W03408, doi: 10.1029/2005WR004376.
18. Keating, E. H., J. Doherty, J. A. Vrugt, and, A. Kang, (2010), Optimization and uncertainty assessment of strongly nonlinear groundwater odels with high parameter dimensionality, Water Resour. Res., 46, W10517, doi: 10.1029/2009WR008584.
19. Kirchner, J. W., (2009), Catchments as simple dynamical systems: Catchment characterization, rainfall-runoff modeling, and doing hydrology backward, Water Resour. Res., 45, W02429, doi: 10.1029/2008WR006912.
20. Kuczera, G., D. Kavetski, S. Franks, and, M. Thyer, (2006), Towards a Bayesian total error analysis of conceptual rainfall-runoff models: Characterizing model error using storm-dependent parameters, J. Hydrol., 331, 161-177. (Pubitemid 44646456)
21. Kuczera, G., B. Renard, M. Thyer, and, D. Kavetski, (2010), There are no hydrological monsters, just models and observations with large uncertainties!, Hydrol. Sci. J., 55 (6), 980-991.
22. Li, M., D. Yang, J. Chen, and, S. S. Hubbard, (2012), Calibration of a distributed flood forecasting model with input uncertainty using a Bayesian framework, Water Resour. Res., 48, W08510, doi: 10.1029/2010WR010062.
23. Makowski, D. T., D. Wallach, and, M. Tremblay, (2002), Using a Bayesian approach to parameter estimation: Comparison of the GLUE and MCMC methods, Agronomie, 22 (S1), 191-203. (Pubitemid 34468141)
24. McMillan, H., and, M. Clark, (2009), Rainfall runoff model calibration using informal likelihood measures within a Markov chain Monte Carlo sampling scheme, Water Resour. Res., 41, W10422, doi: 10.1029/2008WR007288.
25. Montovan, P., and, E. Todini, (2006), Hydrological forecasting uncertainty assessment: Incoherence of the GLUE methodology, J. Hydrol. 330, 368-381. (Pubitemid 44528546)
26. Muste, M., K. Lee, and, J. L. Bertrand-Krajewski, (2012), Standardized uncertainty analysis for hydrometry: A review of relevant approaches and implementation examples, Hydrolog. Sci. J., 57 (4), 643-667.
27. Refsgaard, J. C., J. P. van der Sluijs, J. Brown, and, P. van der Keur, (2006), A framework for dealing with uncertainty due to model structure error, Adv. Water Resour., 29 (11), 1586-1597. (Pubitemid 44341076)
28. Reichert, P., and, J. Mieleitner, (2009), Analyzing input and structural uncertainty of nonlinear dynamic models with stochastic, time-dependent parameters, Water Resour. Res., 45, W10402, doi: 10.1029/2009WR007814.
29. Renard, B., D. Kavetski, G. Kuczera, M. Thyer, and, S. W. Franks, (2010), Understanding predictive uncertainty in hydrologic modeling: The challenge of identifying input and structural errors, Water Resour. Res., 46, W05521, doi: 10.1029/2009WR008328.
30. Renard, B., D. Kavetski, E. Leblois, M. Thyer, G. Kuzera, S. W. Granks, (2011), Toward a reliable decomposition of predictive uncertainty in hydrological modeling: Characterizing rainfall errors using conditional simulation, Water Resour. Res., 47, W11516, doi: 10.1029/2011WR010643.
31. Salamon, P., and, L. Feyen, (2010), Disentangling uncertainties in distributed hydrological modeling using multiplicative error models and sequential data assimilation, Water Resour. Res., 46, W12501, doi: 10.1029/2009WR009022.
32. Schoups, G., and, A. Vrugt, (2010), A formal likelihood function for parameter and predictive inference of hydrologic models with correlated, heteroscedastic and non-Gaussian errors, Water Resour. Res., 46, W10531, doi: 10.1029/2009WR008933.
33. Schoups, G., J. A. Vrugt, F. Fenicia, and, N. C. van de Giesen, (2010), Corruption of accuracy and efficiency of Markov chain Monte Carlo simulation by inaccurate numerical implementation of conceptual hydrologic models, Water Resour. Res., 46, W10530. doi: 10.1029/2009WR008648.
34. Sikorska, A. E., A. Scheidegger, K. Banasik, and, J. Rieckermann, (2012), Bayesian uncertainty assessment of flood predictions in ungauged urban basins for conceptual rainfall runoff models, Hydrol. Earth Syst. Sci., 16 (4), 1221-1236.
35. Snowling, S. D., and, J. R. Kramer, (2001), Evaluating modelling uncertainty for model selection, Ecol. Model., 138 (1-3), 17-30. (Pubitemid 32497476)
36. Stransky, D., V. Bares, and, P. Fatka, (2007), The effect of rainfall measurement uncertainties on rainfall-runoff processes modeling, Water Sci. Technol., 55 (4), 103-111. (Pubitemid 46487424)
37. Thyer, M., B. Renard, D. Kavetski, G. Kuczera, S. W. Franks, and, S. Srikanthan, (2009), Critical evaluation of parameter consistency and predictive uncertainty in hydrological modeling: A case study using Bayesian total error analysis, Water Resour. Res., 45, W00B14, doi: 10.1029/2008WR006825.
38. Vrugt, J. A., H. V. Gupta, W. Bouten, and, S. Sorooshian, (2003), A shuffled complex evolution metropolis algorithm for optimization and uncertainty assessment of hydrologic model parameters, Water Resour. Res., 39 (8), 1201, doi: 10.1029/2002WR001642.
39. Vrugt, J. A., C. J. K. Ter Braak, M. P. Clark, J. M. Hyman, and, B. A. Robinson, (2008), Treatment of input uncertainty in hydrologic modeling: Doing hydrology backward with Markov chain Monte Carlo simulation, Water Resour. Res., 44, W00B09, doi: 10.1029/2007WR006720.
40. Vrugt, J. A., C. J. F. Ter Braak, C. G. H. Diks, and, B. A. Robinson, (2009), Equifinality of formal (DREAM) and informal (GLUE) Bayesian approaches to hydrologic modeling, Stochastic Environ. Res. Risk Assess., 23, 1059-1060.