References

HESS

Hydrology and Earth System Sciences

HESS

Hydrol. Earth Syst. Sci.

1607-7938

Copernicus Publications

Göttingen, Germany

10.5194/hess-18-2393-2014

Uncertainty analysis in model parameters regionalization: a case study involving the SWAT model in Mediterranean catchments (Southern France)

Sellami

¹ La Jeunesse

https://orcid.org/0000-0003-2411-5972

² ³ Benabdallah

⁴ Baghdadi

⁵ Vanclooster

https://orcid.org/0000-0003-1358-8723

Earth and Life Institute, Université catholique de Louvain, Croix du Sud 2, Box 2, 1348 Louvain-la-Neuve, Belgium

UMR 7324 CITERES, Université de Tours, 33 allée Ferdinand de Lesseps BP 60449 – 37204 Tours cedex 3, France

LETG-Angers LEESA, UMR 6554 CNRS, Université d'Angers, Faculté des Sciences, 2 Bd Lavoisier, 49045 Angers Cedex 1, France

Centre de Recherches et des Technologies des Eaux, Technopole Borj Cedria, BP 273, Soliman 8020, Tunisia

IRSTEA, UMR TETIS, 500 rue François Breton, 34093 Montpellier CEDEX 5, France

26 06 2014

18 6 2393 2413

2014

This work is licensed under the Creative Commons Attribution 3.0 Unported License. To view a copy of this licence, visit https://creativecommons.org/licenses/by/3.0/

This article is available from https://hess.copernicus.org/articles/18/2393/2014/hess-18-2393-2014.html

The full text article is available as a PDF file from https://hess.copernicus.org/articles/18/2393/2014/hess-18-2393-2014.pdf

In this study a method for propagating the hydrological model uncertainty in discharge predictions of ungauged Mediterranean catchments using a model parameter regionalization approach is presented. The method is developed and tested for the Thau catchment located in Southern France using the SWAT hydrological model. Regionalization of model parameters, based on physical similarity measured between gauged and ungauged catchment attributes, is a popular methodology for discharge prediction in ungauged basins, but it is often confronted with an arbitrary criterion for selecting the "behavioral" model parameter sets (Mps) at the gauged catchment. A more objective method is provided in this paper where the transferrable Mps are selected based on the similarity between the donor and the receptor catchments. In addition, the method allows propagating the modeling uncertainty while transferring the Mps to the ungauged catchments. Results indicate that physically similar catchments located within the same geographic and climatic region may exhibit similar hydrological behavior and can also be affected by similar model prediction uncertainty. Furthermore, the results suggest that model prediction uncertainty at the ungauged catchment increases as the dissimilarity between the donor and the receptor catchments increases. The methodology presented in this paper can be replicated and used in regionalization of any hydrological model parameters for estimating streamflow at ungauged catchment.

European Commission

CLIMB - Climate Induced Changes on the Hydrology of Mediterranean Basins: Reducing Uncertainty and Quantifying Risk through an Integrated Monitoring and Modeling System (244151)

References 1

Abbaspour, K. C., van Genuchten, M. T., Schulin, R., and Schläppi, E.: A sequential uncertainty domain inverse procedure for estimating subsurface flow and transport parameters, Water Resour. Res., 33, 1879–1892, <a href="http://dx.doi.org/10.1029/97wr01230">https://doi.org/10.1029/97wr01230</a>, 1997.

Aquilina, L., Ladouche, B., Doerfliger, N., Seidel, J. L., Bakalowicz, M., Dupuy, C., and Le Strat, P.: Origin, evolution and residence time of saline thermal fluids (Balaruc springs, southern France): implications for fluid transfer across the continental shelf, Chem. Geol., 192, 1–21, <a href="http://dx.doi.org/10.1016/S0009-2541(02)00160-2">https://doi.org/10.1016/S0009-2541(02)00160-2</a>, 2002.

Arabi, M., Govindaraju, R. S., and Hantush, M. M.: A probabilistic approach for analysis of uncertainty in the evaluation of watershed management practices, J. Hydrol., 333, 459–471, <a href="http://dx.doi.org/10.1016/j.jhydrol.2006.09.012">https://doi.org/10.1016/j.jhydrol.2006.09.012</a>, 2007.

Arnold, J. G., Srinivasan, R., Muttiah, R. S., and Williams, J. R.: Large area hydrological modeling and assessment Part I: Model development 1, J. Am. Water. Resour. Ass., 34, 73–89, <a href="http://dx.doi.org/10.1111/j.1752-1688.1998.tb05961.x">https://doi.org/10.1111/j.1752-1688.1998.tb05961.x</a>, 1998.

Baghdadi, N., Cresson, R., El Hajj, M., Ludwig, R., and La Jeunesse, I.: Estimation of soil parameters over bare agriculture areas from C-band polarimetric SAR data using neural networks, Hydrol. Earth Syst. Sci., 16, 1607–1621, <a href="http://dx.doi.org/10.5194/hess-16-1607-2012">https://doi.org/10.5194/hess-16-1607-2012</a>, 2012.

Bàrdossy, A.: Calibration of hydrological model parameters for ungauged catchments, Hydrol. Earth Syst. Sci., 11, 703–710, <a href="http://dx.doi.org/10.5194/hess-11-703-2007">https://doi.org/10.5194/hess-11-703-2007</a>, 2007.

Bastola, S., Ishidaira, H., and Takeuchi, K.: Regionalisation of hydrological model parameters under parameter uncertainty: A case study involving TOPMODEL and basins across the globe, J. Hydrol., 357, 188–206, <a href="http://dx.doi.org/10.1016/j.jhydrol.2008.05.007">https://doi.org/10.1016/j.jhydrol.2008.05.007</a>, 2008.

Beven, K. J.: TOPMODEL: a critique, Hydrol. Process., 11, 1069–1086, 1997.

Beven, K.: On the future of distributed modelling in hydrology, Hydrol. Process., 14, 3183–3184, <a href="http://dx.doi.org/10.1002/1099-1085">https://doi.org/10.1002/1099-1085</a>, 2000.

Beven, K.: A manifesto for the equifinality thesis, J. Hydrol., 320, 18–36, <a href="http://dx.doi.org/10.1016/j.jhydrol.2005.07.007">https://doi.org/10.1016/j.jhydrol.2005.07.007</a>, 2006.

Beven, K. and Binley, A.: The future of distributed models: Model calibration and uncertainty prediction, Hydrol. Process., 6, 279–298, 1992.

Beven, K. and Freer, J.: Equifinality, data assimilation, and uncertainty estimation in mechanistic modelling of complex environmental systems using the GLUE methodology, J. Hydrol., 249, 11–29, 2001.

Blasone, R.-S., Madsen, H., and Rosbjerg, D.: Uncertainty assessment of integrated distributed hydrological models using GLUE with Markov chain Monte Carlo sampling, J. Hydrol., 353, 18–32, <a href="http://dx.doi.org/10.1016/j.jhydrol.2007.12.026">https://doi.org/10.1016/j.jhydrol.2007.12.026</a>, 2008.

Castellarin, A., Galeati, G., Brandimarte, L., Montanari, A., and Brath, A.: Regional flow-duration curves: reliability for ungauged basins, Adv. Water Resour., 27, 953–965, <a href="http://dx.doi.org/10.1016/j.advwatres.2004.08.005">https://doi.org/10.1016/j.advwatres.2004.08.005</a>, 2004.

Chahinian, N., Tournoud, M.-G., Perrin, J.-L., and Picot, B.: Flow and nutrient transport in intermittent rivers: a modelling case-study on the Vène River using SWAT 2005, Hydrol. Sci. J., 56, 268–287, <a href="http://dx.doi.org/10.1080/02626667.2011.559328">https://doi.org/10.1080/02626667.2011.559328</a>, 2011.

Dotto, C. B., Mannina, G., Kleidorfer, M., Vezzaro, L., Henrichs, M., McCarthy, D. T., Freni, G., Rauch, W., and Deletic, A.: Comparison of different uncertainty techniques in urban stormwater quantity and quality modelling, Water Res., 46, 2545–2558, <a href="http://dx.doi.org/10.1016/j.watres.2012.02.009">https://doi.org/10.1016/j.watres.2012.02.009</a>, 2012.

Duan, Q., Sorooshian, S., and Gupta, V.: Effective and efficient global optimization for conceptual rainfall-runoff models, Water Resour. Res., 28, 1015–1031, <a href="http://dx.doi.org/10.1029/91wr02985">https://doi.org/10.1029/91wr02985</a>, 1992.

Eckhardt, K., Fohrer, N., and Frede, H.-G.: Automatic model calibration, Hydrol. Process., 19, 651–658, <a href="http://dx.doi.org/10.1002/hyp.5613">https://doi.org/10.1002/hyp.5613</a>, 2005.

Freer, J., Beven, K., and Ambroise, B.: Bayesian Estimation of Uncertainty in Runoff Prediction and the Value of Data: An Application of the GLUE Approach, Water Resour. Res., 32, 2161–2173, <a href="http://dx.doi.org/10.1029/95WR03723">https://doi.org/10.1029/95WR03723</a>, 1996.

Freni, G. and Mannina, G.: Bayesian approach for uncertainty quantification in water quality modelling: The influence of prior distribution, J. Hydrol., 392, 31–39, <a href="http://dx.doi.org/10.1016/j.jhydrol.2010.07.043">https://doi.org/10.1016/j.jhydrol.2010.07.043</a>, 2010.

Gallart, F., Amaxidis, Y., Botti, P., Can\`E, G., Castillo, V., Chapman, P., Froebrich, J., GarcÍA-Pintado, J., Latron, J., Llorens, P., Porto, A. L., Morais, M., Neves, R., Ninov, P., Perrin, J.-L., Ribarova, I., Skoulikidis, N., and Tournoud, M.-G.: Investigating hydrological regimes and processes in a set of catchments with temporary waters in Mediterranean Europe, Hydrol. Sci. J., 53, 618–628, <a href="http://dx.doi.org/10.1623/hysj.53.3.618">https://doi.org/10.1623/hysj.53.3.618</a>, 2008.

Gassman, P. W., Reyes, M. R., Green, C. H., and Arnold, J. G.: The Soil and Water Assessment Tool: Historical development, applications and future research directions, Trans. ASABE, 50, 1211–1250, 2007.

Gitau, M. W. and Chaubey, I.: Regionalization of SWAT Model Parameters for Use in Ungauged Watersheds, Water, 2, 849–871, 2010.

Gong, Y., Shen, Z., Hong, Q., Liu, R., and Liao, Q.: Parameter uncertainty analysis in watershed total phosphorus modeling using the GLUE methodology, Agr. Ecosys. Environ., 142, 246–255, <a href="http://dx.doi.org/10.1016/j.agee.2011.05.015">https://doi.org/10.1016/j.agee.2011.05.015</a>, 2011.

He, Y., Bàrdossy, A., and Zehe, E.: A review of regionalisation for continuous streamflow simulation, Hydrol. Earth Syst. Sci., 15, 3539–3553, <a href="http://dx.doi.org/10.5194/hess-15-3539-2011">https://doi.org/10.5194/hess-15-3539-2011</a>, 2011.

Heuvelmans, G., Muys, B., and Feyen, J.: Analysis of the spatial variation in the parameters of the SWAT model with application in Flanders, Northern Belgium, Hydrol. Earth Syst. Sci., 8, 931–939, <a href="http://dx.doi.org/10.5194/hess-8-931-2004">https://doi.org/10.5194/hess-8-931-2004</a>, 2004.

Heuvelmans, G., Muys, B., and Feyen, J.: Regionalisation of the parameters of a hydrological model: Comparison of linear regression models with artificial neural nets, J. Hydrol., 319, 245–265, <a href="http://dx.doi.org/10.1016/j.jhydrol.2005.07.030">https://doi.org/10.1016/j.jhydrol.2005.07.030</a>, 2006.

Jin, X., Xu, C.-Y., Zhang, Q., and Singh, V. P.: Parameter and modeling uncertainty simulated by GLUE and a formal Bayesian method for a conceptual hydrological model, J. Hydrol., 383, 147–155, <a href="http://dx.doi.org/10.1016/j.jhydrol.2009.12.028">https://doi.org/10.1016/j.jhydrol.2009.12.028</a>, 2010.

La Jeunesse, I., Deslous-Paoli, J. M., Ximénès, M. C., Cheylan, J. P., Mende, C., Borrero, C., and Scheyer, L.: Changes in point and non-point sources phosphorus loads in the Thau catchment over 25 years (Mediterranean Sea – France), Hydrobiologia., 475–476, 403–411, <a href="http://dx.doi.org/10.1023/a:1020351711877">https://doi.org/10.1023/a:1020351711877</a>, 2002.

Mantovan, P. and Todini, E.: Hydrological forecasting uncertainty assessment: Incoherence of the GLUE methodology, J. Hydrol., 330, 368–381, <a href="http://dx.doi.org/10.1016/j.jhydrol.2006.04.046">https://doi.org/10.1016/j.jhydrol.2006.04.046</a>, 2006.

Masih, I., Uhlenbrook, S., Maskey, S., and Ahmad, M. D.: Regionalization of a conceptual rainfall–runoff model based on similarity of the flow duration curve: A case study from the semi-arid Karkheh basin, Iran, J. Hydrol., 391, 188–201, <a href="http://dx.doi.org/10.1016/j.jhydrol.2010.07.018">https://doi.org/10.1016/j.jhydrol.2010.07.018</a>, 2010.

McIntyre, N., Lee, H., Wheater, H., Young, A., and Wagener, T.: Ensemble predictions of runoff in ungauged catchments, Water Resour. Res., 41, W12434, <a href="http://dx.doi.org/10.1029/2005WR004289">https://doi.org/10.1029/2005WR004289</a>, 2005.

Merz, R. and Blöschl, G.: Regionalisation of catchment model parameters, J. Hydrol., 287, 95–123, <a href="http://dx.doi.org/10.1016/j.jhydrol.2003.09.028">https://doi.org/10.1016/j.jhydrol.2003.09.028</a>, 2004.

Montanari, A.: Large sample behaviors of the generalized likelihood uncertainty estimation (GLUE) in assessing the uncertainty of rainfall-runoff simulations, Water Resour. Res., 41, W08406, <a href="http://dx.doi.org/10.1029/2004WR003826">https://doi.org/10.1029/2004WR003826</a>, 2005.

Moore, R. J.: The probability-distributed principle and runoff production at point and basin scales, Hydrol. Sci. J., 30, 273–297, 1985.

Muleta, M. K. and Nicklow, J. W.: Sensitivity and uncertainty analysis coupled with automatic calibration for a distributed watershed model, J. Hydrol., 306, 127–145, <a href="http://dx.doi.org/10.1016/j.jhydrol.2004.09.005">https://doi.org/10.1016/j.jhydrol.2004.09.005</a>, 2005.

Nathan, R. J. and McMahon, T. A.: Identification of homogeneous regions for the purposes of regionalisation, J. Hydrol., 121, 217–238, 1990.

Neitsh, S. L., Arnold, J. G., Kiniry, J. R., Srinivasan, R., and Williams, J. R.: Soil and Water Assessment Tool input/output file documentation, version 2005, Temple, Texas: Grassland, Soil and Water Research Laboratory, Agricultural Research Service, 2005.

Ouarda, T. B. J. M., Girard, C., Cavadias, G. S., and Bobee, B.: Regional flood frequency estimation with canonical correlation analysis, J. Hydrol., 254, 157–173, 2001.

Oudin, L., Andréassian, V., Perrin, C., Michel, C., and Le Moine, N.: Spatial proximity, physical similarity, regression and ungaged catchments: A comparison of regionalization approaches based on 913 French catchments, Water Resour. Res., 44, W03413, <a href="http://dx.doi.org/10.1029/2007WR006240">https://doi.org/10.1029/2007WR006240</a>, 2008.

Parajka, J., Merz, R., and Blöschl, G.: A comparison of regionalisation methods for catchment model parameters, Hydrol. Earth Syst. Sci., 9, 157–171, 10.5194/hess-9-157-2005, 2005.

Perrin, J.-L. and Tournoud, M.-G.: Hydrological processes controlling flow generation in a small Mediterranean catchment under karstic influence, Hydrol. Sci. J., 54, 1125–1140, <a href="http://dx.doi.org/10.1623/hysj.54.6.1125">https://doi.org/10.1623/hysj.54.6.1125</a>, 2009.

Perrin, C., Michel, C., and Andréassian, V.: Improvement of a parsimonious model for streamflow simulation. J. Hydrol, 279, 275–289, 2003.

Plus, M., La Jeunesse, I., Bouraoui, F., Zaldivar, J., Chapelle, A., and Lazure, P.: Modelling water discharges and nitrogen inputs into a Mediterranean lagoon-Impact on the primary production, Ecol. Model., 193, 69–89, <a href="http://dx.doi.org/10.1016/j.ecolmodel.2005.07.037">https://doi.org/10.1016/j.ecolmodel.2005.07.037</a>, 2006.

Sellami, H., La Jeunesse, I., Benabdallah, S., and Vanclooster, M.: Parameter and rating curve uncertainty propagation analysis of the SWAT model for two small Mediterranean watersheds, Hydrol. Sci. J., 58, 1635–1657, <a href="http://dx.doi.org/10.1080/02626667.2013.837222">https://doi.org/10.1080/02626667.2013.837222</a>, 2013.

Shen, Z. Y., Chen, L., and Chen, T.: Analysis of parameter uncertainty in hydrological modeling using GLUE method: a case study of SWAT model applied to Three Gorges Reservoir Region, China, Hydrol. Earth Syst. Sci 8, 8203–8229, <a href="http://dx.doi.org/10.5194/hess-8-8203-2012">https://doi.org/10.5194/hess-8-8203-2012</a>, 2012.

Shrestha, D. L., Kayastha, N., and Solomatine, D. P.: A novel approach to parameter uncertainty analysis of hydrological models using neural networks, Hydrol. Earth Syst. Sci., 13, 1235–1248, <a href="http://dx.doi.org/10.5194/hess-13-1235-2009">https://doi.org/10.5194/hess-13-1235-2009</a>, 2009.

Shu, C. and Burn, D. H.: Spatial patterns of homogeneous pooling groups for flood frequency analysis, Hydrol. Sci. J., 48, 601–618, <a href="http://dx.doi.org/10.1623/hysj.48.4.601.51417">https://doi.org/10.1623/hysj.48.4.601.51417</a>, 2003.

Sivapalan, M., Takeuchi, K., Franks, S. W., Gupta, V. K., Karambiri, H., Lakshmi, V., Liang, X., McDonnell, J. J., Mendiondo, E. M., O'Connell, P. E., Oki, T., Pomeroy, J. W., Schertzer, D., Uhlenbrook, S., and Zehe, E.: IAHS Decade on Predictions in Ungauged Basins (PUB), 2003–2012: Shaping an exciting future for the hydrological sciences, Hydrol. Sci. J., 48, 857–880, <a href="http://dx.doi.org/10.1623/hysj.48.6.857.51421">https://doi.org/10.1623/hysj.48.6.857.51421</a>, 2003.

Smakhtin, V. U.: Low flow hydrology: a review, J. Hydrol., 240, 147–186, <a href="http://dx.doi.org/10.1016/S0022-1694(00)00340-1">https://doi.org/10.1016/S0022-1694(00)00340-1</a>, 2001.

van Griensven, A., Meixner, T., Grunwald, S., Bishop, T., Diluzio, M., and Srinivasan, R.: A global sensitivity analysis tool for the parameters of multi-variable catchment models, J. Hydrol., 324, 10–23, <a href="http://dx.doi.org/10.1016/j.jhydrol.2005.09.008">https://doi.org/10.1016/j.jhydrol.2005.09.008</a>, 2006.

van Griensven, A., Ndomba, P., Yalew, S., and Kilonzo, F.: Critical review of SWAT applications in the upper Nile basin countries, Hydrol. Earth Syst. Sci., 16, 3371–3381, <a href="http://dx.doi.org/10.5194/hess-16-3371-2012">https://doi.org/10.5194/hess-16-3371-2012</a>, 2012.

Vandewiele, G. L. and Elias, A.: Monthly water balance of ungauged catchments obtained by geographical regionalization, J. Hydrol., 170, 277–291, 1995.

Viola, F., Noto, L. V., Cannarozzo, M., and La Loggia, G.: Daily streamflow prediction with uncertainty in ephemeral catchments using the GLUE methodology, Physics and Chemistry of the Earth, Parts A/B/C, 34, 701–706, <a href="http://dx.doi.org/10.1016/j.pce.2009.06.006">https://doi.org/10.1016/j.pce.2009.06.006</a>, 2009.

Vogel, R. M. and Fennessey, N. M.: Flow-Duration Curves 2. New Interpretation and Con?dence-Intervals, J. Water Resour. Plan. Manage., 120, 485–504, 1994.

Vogel, R. M. and Fennessey, N. M.: Flow Duration Curve II: A review of applications in water resources planning, JAWRA, J. Am. Water Resour. Ass., 31, 1029–1039, <a href="http://dx.doi.org/10.1111/j.1752-1688.1995.tb03419.x">https://doi.org/10.1111/j.1752-1688.1995.tb03419.x</a>, 1995.

Vrugt, J. A., ter Braak, C. J. F., Clark, M. P., Hyman, J. M., and Robinson, B. A.: Treatment of input uncertainty in hydrologic modeling: Doing hydrology backward with Markov chain Monte Carlo simulation, Water Resour. Res., 44, W00B09, <a href="http://dx.doi.org/10.1029/2007wr006720">https://doi.org/10.1029/2007wr006720</a>, 2008.

Wagener, T. and Wheater, H. S.: Parameter estimation and regionalization for continuous rainfall-runoff models including uncertainty, J. Hydrol., 320, 132–154, 2006.

Wagener, T., Wheater, H. S., and Gupta, H. V.: Rainfall-Runoff Modelling in Gauged and Ungauged Catchments, Imperial College Press, London, 300, 2004.

Wagener, T., Sivapalan, M., Troch, P., and Woods, R.: Catchment Classification and Hydrologic Similarity, Geography Compass, 1, 901–931, <a href="http://dx.doi.org/10.1111/j.1749-8198.2007.00039.x">https://doi.org/10.1111/j.1749-8198.2007.00039.x</a>, 2007.

Xiong, L. and O'Connor, K. M.: An empirical method to improve the prediction limits of the GLUE methodology in rainfall-runoff modeling, J. Hydrol., 349, 115–124, 2008.

Yadav, M., Wagener, T., and Gupta, H.: Regionalization of constraints on expected watershed response behavior for improved predictions in ungauged basins, Adv. Water. Resour, 30, 1756–1774, <a href="http://dx.doi.org/10.1016/j.advwatres.2007.01.005">https://doi.org/10.1016/j.advwatres.2007.01.005</a>, 2007.

Yang, J., Reichert, P., Abbaspour, K. C., Xia, J., and Yang, H.: Comparing uncertainty analysis techniques for a SWAT application to the Chaohe Basin in China, J. Hydrol., 358, 1–23, <a href="http://dx.doi.org/10.1016/j.jhydrol.2008.05.012">https://doi.org/10.1016/j.jhydrol.2008.05.012</a>, 2008.

Zhang, X., Srinivasan, R., Zhao, K., and Liew, M. V.: Evaluation of global optimization algorithms for parameter calibration of a computationally intensive hydrologic model, Hydrol. Process., 23, 430–441, <a href="http://dx.doi.org/10.1002/hyp.7152">https://doi.org/10.1002/hyp.7152</a>, 2009.