On the choice of calibration periods and objective functions: a practical guide to model parameter identification

• Autorzy: Romanowicz R. , Osuch M. , Grabowiecka M.

Identyfikatory

DOI

10.2478/s11600-013-0157-6

• Języki publikacji: EN

Abstrakty

EN

Despite the development of new measuring techniques, monitoring systems and advances in computer technology, rainfall-flow modelling is still a challenge. The reasons are multiple and fairly well known. They include the distributed, heterogeneous nature of the environmental variables affecting flow from the catchment. These are precipitation, evapotranspiration and in some seasons and catchments in Poland, snow melt also. This paper presents a review of work done on the calibration and validation of rainfall-runoff modelling, with a focus on the conceptual HBV model. We give a synthesis of the problems and propose a practical guide to the calibration and validation of rainfall-runoff models.

Słowa kluczowe

EN

rainfall-runoff model; HBV; calibration; objective function; Wieprz catchment

• Wydawca: Instytut Geofizyki PAN ; Springer
• Czasopismo: Acta Geophysica
• Rocznik: 2013
• Tom: Vol. 61, no. 6
• Strony: 1477--1503
• Opis fizyczny: Bibliogr. 54 poz.

Twórcy

autor

Romanowicz R.

• Institute of Geophysics, Polish Academy of Sciences, Warszawa, Poland

autor

Osuch M.

• Institute of Geophysics, Polish Academy of Sciences, Warszawa, Poland

autor

Grabowiecka M.

• Institute of Geophysics, Polish Academy of Sciences, Warszawa, Poland

Bibliografia

• 1. Abbott, M.B., J.C. Bathurst, J.A. Cunge, P.E. O’Connell, and J. Rasmussen (1986a), An introduction to the European Hydrological System - Systeme Hydrologique Europeen, “SHE”. 1: History and philosophy of a physicallybased, distributed modelling system, J. Hydrol. 87,1-2, 45-59, DOI: 10.1016/0022-1694(86)90114-9.
• 2. Abbott, M.B., J.C. Bathurst, J.A. Cunge, P.E. O’Connell, and J. Rasmussen (1986b), An introduction to the European Hydrological System - Systeme Hydrologique Europeen, “SHE”. 2: Structure of a physically-based, distributed modelling system, J. Hydrol. 87,1-2, 61-77, DOI: 10.1016/0022-1694(86)90115-0.
• 3. Abebe, N.A., F.L. Ogden, and N.R. Pradhan (2010), Sensitivity and uncertainty analysis of the conceptual HBV rainfall-runoff model: Implications for parameter estimation, J. Hydrol. 389,3-4, 301-310, DOI: 10.1016/j.jhydrol.2010.06.007.
• 4. Akhtar, M., N. Ahmad, and M.J. Booij (2009), Use of regional climate model simulations as input for hydrological models for the Hindukush-Karakorum-Himalaya region, Hydrol. Earth Syst. Sci. 13,7, 1075-1089, DOI: 10.5194/hess-13-1075-2009.
• 5. Andréasson, J., S. Bergström, B. Carlsson, L.P. Graham, and G. Lindström (2004), Hydrological change - climate change impact simulations for Sweden, Ambio 33,4, 228-234, DOI: 10.1579/0044-7447-33.4.228.
• 6. Arnold, J.G., R. Srinivasan, R.S. Muttiah, and J.R. Williams (1998), Large area hydrologic modeling and assessment. Part I: Model development, J. Am. Water Resour. Assoc. 34,1, 73-89, DOI: 10.1111/j.1752-1688.1998.tb05961.x.
• 7. Aronica, G., B. Hankin, and K. Beven (1998), Uncertainty and equifinality in calibrating distributed roughness coefficients in a flood propagation model with limited data, Adv. Water Resour. 22,4, 349-365, DOI: 10.1016/S0309-1708(98)00017-7.
• 8. Bergström, S. (1976), Development and application of a conceptual runoff model for Scandinavian catchments, RH07, Swedish Meteorological and Hydrological Institute, Norrköping, Sweden.
• 9. Bergström, S., B. Carlsson, M. Gardelin, G. Lindström, A. Pettersson, and M. Rummukainen (2001), Climate change impacts on runoff in Sweden - assessments by global climate models, dynamical downscaling and hydrological modelling, Clim. Res. 16,2, 101-112, DOI: 10.3354/cr016101.
• 10. Beven, K. (2006), A manifesto for the equifinality thesis, J. Hydrol. 320,1-2, 18-36, DOI: 10.1016/j.jhydrol.2005.07.007.
• 11. Beven, K., and A. Binley (1992), The future of distributed models: Model calibration and uncertainty prediction, Hydrol. Process. 6,3, 279-298, DOI: 10.1002/hyp.3360060305.
• 12. Blasone, R.S., J.A. Vrugt, H. Madsen, D. Rosbjerg, B.A. Robinson, and G.A. Zyvoloski (2008), Generalized likelihood uncertainty estimation(GLUE) using adaptive Markov Chain Monte Carlo sampling, Adv. Water Resour. 31,4, 630-648, DOI: 10.1016/j.advwatres.2007.12.003
• 13. Booij, M.J., and M.S. Krol (2010), Balance between calibration objectives in a conceptual hydrological model, Hydrol. Sci. J. 55,6, 1017-1032, DOI: 10.1080/02626667.2010.505892.
• 14. Box, G.E.P., and G.C. Tiao (1992), Bayesian Inference in Statistical Analysis, John Wiley and Sons Inc., New York.
• 15. Boyle, D. (2000), Multicriteria calibration of hydrological models, Ph.D. Thesis, University of Arizona, Tucson.
• 16. Boyle, D.P., H.V. Gupta, S. Sorooshian, V. Koren, Z. Zhang, and M. Smith (2001), Toward improved streamflow forecasts: value of semidistributed modeling, Water Resour. Res. 37,11, 2749-2759, DOI: 10.1029/2000WR000207.
• 17. Bruen, M., and J. Yang (2006), Combined hydraulic and black-box models for flood forecasting in urban drainage systems, J. Hydrol. Eng. 11,6, 589-596, DOI: 10.1061/(ASCE)1084-0699(2006)11:6(589).
• 18. Das, S., A. Abraham, U.K. Chakraborty, and A. Konar (2009), Differential evolution using a neighbourhood-based mutation operator, IEEE Trans. Evolut. Comput. 13,3, 526-553, DOI: 10.1109/TEVC.2008.2009457.
• 19. Deckers, D.L.E.H., M.J. Booij, T.H.M. Rientjes, and M.S. Krol (2010), Catchment variability and parameter estimation in multi-objective regionalisation of a rainfall-runoff model, Water Resour. Manag. 24,14, 3961-3985, DOI: 10.1007/s11269-010-9642-8.
• 20. Doherty, J. (2004), PEST: Model-independent parameter estimation. User’s manual. 5th ed., Watermark Numerical Computing, Brisbane, Australia.
• 21. Efstratiadis, A., and D. Koutsoyiannis (2010), One decade of multi-objective calibration approaches in hydrological modelling: a review, Hydrolog. Sci. J. 55,1, 58-78, DOI: 10.1080/02626660903526292.
• 22. Fenicia, F., D.P. Solomatine, H.H.G. Savenije, and P. Matgen (2007), Soft combination of local models in a multi-objective framework, Hydrol. Earth Syst. Sci. 11,6, 1797-1809, DOI: 10.5194/hess-11-1797-2007.
• 23. Gassman, P.W., M.R. Reyes, C.H. Green, and J.G. Arnold (2007), The soil and water assessment tool: historical development, applications, and future research directions, Trans. Am. Soc. Agricult. Biol. Eng. 50,4, 1211-1250.
• 24. Graham, L.P., J. Andréasson, and B. Carlsson (2007), Assessing climate change impacts on hydrology from an ensemble of regional climate models, model scales and linking methods - a case study on the Lule River basin, Climatic Change 81,1, Suppl., 293-307, DOI: 10.1007/s10584-006-9215-2.
• 25. Gupta, H.V., S. Sorooshian, and P.O. Yapo (1998), Toward improved calibration of hydrologic models: Multiple and noncommensurable measures of information, Water Resour. Res. 34,4, 751-763, DOI: 10.1029/97WR03495.
• 26. Gupta, H.V., H. Kling, K.K. Yilmaz, and G.F. Martinez (2009), Decomposition of the mean squared error and NSE performance criteria: Implications for improving hydrological modelling, J. Hydrol. 377,1-2, 80-91, DOI: 10.1016/j.jhydrol.2009.08.003.
• 27. Hastie, T.J., and R.J. Tibshirani (1990), Generalised Additive Models, Chapman and Hall, New York, 335 pp.
• 28. Kavetski, D., F. Fenicia, and M.P. Clark (2011), Impact of temporal data resolution on parameter inference and model identification in conceptual hydrological modeling: insights from an experimental catchment, Water Resour. Res. 47,5, W05501, DOI: 10.1029/2010WR009525.
• 29. Lawrence, D., and I. Haddeland (2011), Uncertainty in hydrological modelling of climate change impacts in four Norwegian catchments, Hydrol. Res. 42,6, 457-471, DOI: 10.2166/nh.2011.010.
• 30. Legates, D.R., and G.J. McCabe Jr. (1999), Evaluating the use of “goodness-of-fit” measures in hydrologic and hydroclimatic model validation, Water Resour. Res. 35,1, 233-241, DOI: 10.1029/1998WR900018.
• 31. Lidén, R., and J. Harlin (2000), Analysis of conceptual rainfall-runoff modeling performance in different climates, J. Hydrol. 238,3-4, 231-247, DOI: 10.1016/S0022-1694(00)00330-9.
• 32. Lindström, G. (1997), A simple automatic calibration routine for the HBV model, Nord. Hydrol. 28,3, 153-168, DOI: 10.2166/nh.1997.009.
• 33. Lindström, G., B. Johansson, M. Persson, M. Gardelin, and S. Bergström (1997), Development and test of the distributed HBV-96 hydrological model, J Hydrol. 201,1-4, 272-288, DOI: 10.1016/S0022-1694(97)00041-3.
• 34. Luks, B., M. Osuch, and R.J. Romanowicz (2011), The relationship between snowpack dynamics and NAO/AO indices in SW Spitsbergen, Phys. Chem. Earth 36,13, 646-654, DOI: 10.1016/j.pce.2011.06.004.
• 35. Nash, J.E., and J.V. Sutcliffe (1970), River flow forecasting through conceptual models. Part I - A discussion of principles, J. Hydrol. 10,3, 282-290, DOI: 10.1016/0022-1694(70)90255-6.
• 36. Piotrowski, A.P., and J.J. Napiórkowski (2012), Product-Units neural networks for catchment runoff forecasting, Adv. Water Resour. 49, 97-113, DOI: 10.1016/j.advwatres.2012.05.016.
• 37. Press, W.H., S.A. Teukolsky, W.T. Vetterling, and B.P. Flannery (2002), Numerical Recipes in C++, Cambridge University Press, Cambridge.
• 38. Pushpalatha, R., C. Perrin, N. Le Moine, and V. Andréassian (2012), A review of efficiency criteria suitable for evaluating low-flow simulations, J. Hydrol. 420-421, 171-182, DOI: 10.1016/j.jhydrol.2011.11.055.
• 39. Ratto, M., P.C. Young, R. Romanowicz, F. Pappenberger, A. Saltelli, and A. Pagano (2007), Uncertainty, sensitivity analysis and the role of data based mechanistic modeling in hydrology, Hydrol. Earth Syst. Sci. 11,4, 1249-1266, DOI: 10.5194/hess-11-1249-2007.
• 40. Rientjes, T.H.M., A.T. Haile, E. Kebede, C.M.M. Mannaerts, E. Habib, and T.S. Steenhuis (2011), Changes in land cover, rainfall and stream flow in Upper Gilgel Abbay catchment, Blue Nile basin - Ethiopia, Hydrol. Earth Syst. Sci. 15,6, 1979-1989, DOI: 10.5194/hess-15-1979-2011.
• 41. Romanowicz, R.J., and K.J. Beven (2006), Comments on generalised likelihood uncertainty estimation, Reliab. Eng. Syst. Safe. 91,10-11, 1315-1321, DOI: 10.1016/j.ress.2005.11.030.
• 42. Romanowicz, R.J., and R. Macdonald (2005), Modelling uncertainty and variability in environmental systems, Acta Geophys. Pol. 53,4, 401-417.
• 43. Romanowicz, R.J., K.J. Beven, and J. Tawn (1996), Bayesian calibration of flood inundation models. In: M.G. Anderson, D.E. Walling, and P.D. Bates (eds.), Floodplain Processes, John Wiley and Sons Inc., Chichester, 333-360.
• 44. Romanowicz, R.J., A. Kiczko, and J.J. Napiórkowski (2010), Stochastic transfer function model applied to combined reservoir management and flow routing, Hydrol. Sci. J. 55,1, 27-40, DOI: 10.1080/02626660903526029.
• 45. Romanowicz, R.J., A. Kulasová, J. Ředinová, and S. Blazková (2012), Influence of afforestation on water regime in Jizera catchments, Czech Republic, Acta Geophys. 60,4, 1120-1142, DOI: 10.2478/s11600-012-0046-4.
• 46. Smith, P., K.J. Beven, and J.A. Tawn (2008), Informal likelihood measures in model assessment: Theoretic development and investigation, Adv. Water Resour. 31,8, 1087-1100, DOI: 10.1016/j.advwatres.2008.04.012.
• 47. Sorooshian, S., and J.A. Dracup (1980), Stochastic parameter estimation procedures for hydrologie rainfall-runoff models: Correlated and heteroscedastic error cases, Water Resour. Res. 16,2, 430-442, DOI: 10.1029/ WR016i002p00430.
• 48. Sorooshian, S., and V.K. Gupta (1983), Automatic calibration of conceptual rainfall-runoff models: The question of parameter observability and uniqueness, Water Resour. Res. 19,1, 260-268, DOI: 10.1029/WR019i001p00260.
• 49. Tarantola, A. (1987), Inverse Problems Theory. Methods for Data Fitting and Model Parameter Estimation, Elsevier, Amsterdam.
• 50. Van den Tillaart, S.P.M., M.J. Booij, and M.S. Krol (2013), Impact of uncertainties in discharge determination on the parameter estimation and performance of a hydrological model, Hydrol. Res. 44,3, 454-466, DOI: 10.2166/nh.2012.147.
• 51. 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.
• 52. Wagener, T., N. McIntyre, M.J. Lees, H.S. Wheater, and H.V. Gupta (2003), Towards reduced uncertainty in conceptual rainfall-runoff modelling: dynamic identifiability analysis, Hydrol. Process. 17,2, 455-476, DOI: 10.1002/hyp.1135.
• 53. Wilby, R.L. (2005), Uncertainty in water resource model parameters used for climate change impact assessment, Hydrol. Process. 19,16, 3201-3219, DOI: 10.1002/hyp.5819.
• 54. Young, P. (2003), Top-down and data-based mechanistic modelling of rainfall-flow dynamics at the catchment scale, Hydrol. Process. 17,11, 2195-2217, DOI: 10.1002/hyp.1328.