Sobre la evaluación de predicciones de un modelo de recursos hídricos

  • Raúl Fernando Vázquez Zambrano Grupo de Ciencias de la Tierra y del Ambiente, Dirección de Investigación de la Universidad de Cuenca
Palabras clave: modelación hidrológica-hidráulica, calidad de modelación, estadístico, calibración, evaluación, validación, incertidumbre, simulaciones Monte-Carlo


The analysis of the most commonly used measures of hydrological/hydraulic model performance was herein carried out by means of their statistical examination and illustrative modelling applications. In doing so, the model performance indexes were classified in two groups, according to the type of error (or residual) that those indexes are measuring: (i) statistics measuring the average systematic error (model bias); and (ii) statistics measuring the average combined systematic and random discrepancies among simulations and observations. The reader can in this way easily select a set of unrelated statistics to report on model performance. The manuscript addresses as well the main pitfalls of some of the most popular statistics used in scientific literature and suggests some approaches to overcome such potential pitfalls when addressing model performance.


La descarga de datos todavía no está disponible.


Abbaspour, K.C., M.T. van Genuchten, R. Schulin, E. Schläppi, 1997. A sequential uncertainty domain inverse procedure for estimating subsurface flow and transport parameters. Water Resour. Res., 33(8), 1879-1892.

Abbott, M.B., J.C. Bathurst, P.E. Cunge, P.E., O’Connell, J. Rasmussen, 1986. An introduction to the European Hydrological System Système Hydrologique Européen, ‘SHE’, 1. History and philosophy of a physically based distributed modeling system. J. Hydrol., 87, 45-59.

Beven, K.J., 1993. Prophecy, reality and uncertainty in distributed hydrological modeling. Adv. Water Resourc., 16, 41-51.

Beven, K.J., 1997. TOPMODEL: A critique. Hydrol. Process., 11(9), 1069-1085.

Binley, A.M., K.J. Beven, A. Calver, L.G. Watts, 1991. Changing Responses in Hydrology: Assessing the Uncertainty in Physically Based Model Predictions. Water Resour. Res., 27(6), 1253-1261.

Braud, I., P. Fernandez, F. Bouraoui, 1999. Study of the rainfall-runoff process in the Andes region using a continuous distributed model. J. Hydrol., 216(3-4), 155-171.

Buytaert, W., B. De Bièvre, G. Wyseure, J. Deckers, 2004. The use of the linear reservoir concept to quantify the impact of land use changes on the hydrology of catchments in the Ecuadorian Andes. Hydrol. Earth Syst. Sc., 8, 108-114.

Buytaert, W., V. Iñegues, R. Célleri, B. De Bièvre, 2006. The impact of pine plantations on water yield: a case study from the Ecuadorian Andes. 3rd Int. Symp. on Int. Water Manage., Bochum, Germany.

Feyen, L., R.F. Vazquez, K., Christiaens, O. Sels, J. Feyen, 2000. Application of a distributed physically-based hydrological model to a medium size catchment. Hydrol. Earth Sys. Sci., 4(1), 47-63.

Fleischbein, K., W. Wilcke, C. Valarezo, W. Zech, K. Knoblich, 2006. Water budgets of three small catchments under montane forest in Ecuador: experimental and modeling approach. Hydrol. Process., 20, 2491-2507.

Freeze, R.A., R.L. Harlan, 1969. Blueprint for a physically based digitally simulated hydrologic response model. J. Hydrol., 9, 237-258.

Grayson, R.B., I.D. Moore, T.A. McHanon, 1992. Physically-based hydrological modelling: a terrain-based model for investigative purposes. Water Resour. Res., 28(10), 2639-2658.

Legates, D.R., G.J. McCabe, 1999. Evaluating the use of 'goodness-of-fit' measures in hydrological and hydroclimatic model validation. Water Resour. Res., 35(1), 233-241.

Loague, K., R.E. Green, 1991. Statistical and graphical methods for evaluating solute transport models: overview and applications. J. Contam. Hydrol., 7, 51-73.

Nash, J.E., J.V. Sutcliffe, 1970. River flow forecasting through conceptual models. Part I: A discussion of principles. J. Hydrol., 10(3), 282-290.

Perrin, J.L., C. Bouvier, J.L. Janeau, G. Menez, F. Cruz, 2001. Rainfall/runoff processes in a small peri-urban catchment in the Andes mountains. The Rumihurcu Quebrada, Quito (Ecuador). Hydrol. Process., 15(5), 843-854.

Refsgaard, J.C. 1997. Parameterisation, calibration and validation of distributed hydrological models. J. Hydrol., 198, 69-97.

Refsgaard, J.C., B. Storm, 1995. MIKE SHE. In Singh, V.P. (Ed.). Computer Models of Watershed Hydrology. Water Resources Publications, Colorado, USA, 809-846.

Refsgaard, J.C., B. Storm, 1996. Construction, calibration and validation of hydrological models. In: Abbott, M.B. and Refsgaard , J.C. (Eds.), Distributed Hydrological Modelling, Kluwer Academic, The Netherlands, 41-54.

Salas, J.D., 1993. Analysis and modelling of hydrologic timeseries. In: Maidment, D.R. (Ed.), Handbook of hydrology, McGraw-Hill Inc., USA, 19.1-19.71.

Vázquez, R.F., 2003. Assessment of the performance of physically based distributed codes simulating medium size hydrological systems. Tesis Ph.D. ISBN 90-5682-416-3, K.U.Leuven, Bélgica, 335 págs.

Vázquez, R.F., J. Feyen, 2007. Assessment of the effects of DEM gridding on the predictions of basin runoff using MIKE SHE and a modelling resolution of 600 m. J. Hydrol., 334, 73- 87.

Vázquez, R.F., J. Feyen, 2008. Application of distributed hydrologic models. En: Pilar García-Navarro, P., E. Playán (Eds.): Numerical modelling of Hydrodynamics for Water Resources. Taylor & Francis, Londres, Reino Unido, 153-174.

Vázquez, R.F., P. Willems, J. Feyen, 2008. Improving the predictions of a MIKE SHE catchment-scale application by using multi-criteria approach. Hydrol. Process., 22(13), 2159-2179.

Vázquez, R.F., K. Beven, J. Feyen, 2009. GLUE based assessment on the overall predictions of a MIKE SHE application. Water Resour. Manag., 23(7), 1325-1349.

Vázquez, R.F., L. Feyen, J. Feyen, J.C. Refsgaard, 2002. Effect of grid-size on effective parameters and model performance of the MIKE SHE code applied to a medium sized catchment. Hydrol. Process., 16(2), 355-372.

Resumen visto = 139 veces
PDF descargado = 92 veces
Cómo citar
Vázquez Zambrano, R. (2011). Sobre la evaluación de predicciones de un modelo de recursos hídricos. Maskana, 2(1), 49-58.
Artículos científicos