Analysis of the behavior of a rainfall-runoff model using three global sensitivity analysis methods evaluated at different temporal scales

Journal of Hydrology

Volumn 475, Issue , 2012, Pages 97-110

  Massmann, C ^a   Holzmann, H ^a  

^a UNIVERSITY OF NATURAL RESOURCES AND LIFE SCIENCES   (Austria)

Author keywords

Mutual entropy; Parameter interactions; Parameter ranking; Regional sensitivity analysis; Sobol' sensitivity indices

Indexed keywords

CORRELATION ANALYSIS; DATA SETS; DISCHARGE LEVEL; GLOBAL SENSITIVITY ANALYSIS; HIGH SENSITIVITY; INTERFLOW; MODEL RESULTS; MUTUAL ENTROPY; PARAMETER INTERACTIONS; PARAMETER RANGE; PARAMETER RANKING; PARAMETER SENSITIVITIES; PARAMETERS CHARACTERIZING; POSITIVE CORRELATIONS; QUANTITATIVE SENSITIVITY; RAINFALL-RUNOFF MODELS; SENSITIVE PARAMETER; SENSITIVITY METHODS; SOBOL' SENSITIVITY INDEX; SOIL STORAGE; TEMPORAL SCALE;

CATCHMENTS; ENTROPY; GEOLOGIC MODELS; RUNOFF; SENSITIVITY ANALYSIS; SOLVENTS;

PARAMETER ESTIMATION;

CATCHMENT; DATA SET; DISCHARGE; ENTROPY; NUMERICAL MODEL; RAINFALL-RUNOFF MODELING; SENSITIVITY ANALYSIS; TEMPORAL VARIATION;

AUSTRIA;

EID: 84870253525     PISSN: 00221694     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jhydrol.2012.09.026     Document Type: Article

References (48)

1. Atkinson S.E., Woods R.A., Sivapalan M. Climate and landscape controls on water balance model complexity over changing timescales. Water Resour. Res 2002, 38(12):1314. 10.1029/2002WR001487.
2. Auder B., Iooss B. Global sensitivity analysis based on entropy. Safety, Reliability and Risk Analysis: Theory, Methods and Applications 2009, Taylor & Francis Group, London, pp. 2107-2115. S. Martorell, C. Guedes, J. Bernett (Eds.).
3. Beven K. A manifesto for the equifinality thesis. J. Hydrol. 2006, 320:18-36. 10.1016/j.jhydrol.2005.07.007.
4. Beven K. Environmental Modelling: An Uncertain Future? 2009, Taylor and Francis Group, Routledge, 310p.
5. Brutsaert W. Hydrology an Introduction 2005, Cambridge University Press, Cambridge, 605p.
6. Cibin R., Sudheer K.P., Chaubey I. Sensitivity and identifiability of stream flow generation parameters of the SWAT model. Hydrol. Process. 2010, 24:1133-1148. 10.1002/hyp. 7568.
7. Clark M.P., Slater A.G., Rupp D.E., Woods R.A., Vrugt J.A., Gupta H.V., Wagener T., Hay L.E. Framework for Understanding Structural Errors (FUSE): a modular framework to diagnose differences between hydrological models. Water Resour. Res. 2008, 44. W00B02. 10.1029/2007WR006735.
8. Cloke H.L., Pappenberger F., Renaud J.-P. Multi-method global sensitivity analysis (MMGSA) for modelling floodplain hydrological processes. Hydrol. Process. 2008, 22:1660-1674. 10.1002/hyp. 6734.
9. Demaria E.M., Nijssen B., Wagener T. Monte Carlo sensitivity analysis of land surface parameters using the Variable Infiltration Capacity model. J. Geophys. Res. 2007, 112:D11113. 10.1029/2006JD007534.
10. Dunne T. Field studies of hillslope flow processes. Hillslope Hydrology 1978, John Wiley & Sons, Chichester, pp. 227-293. M.J. Kirkby (Ed.).
11. Eder G., Sivapalan M., Nachtnebel H.P. Modelling water balances in an Alpine catchment through exploitation of emergent properties over changing time scales. Hydrol. Process. 2003, 17(11):2125-2149. 10.1002/hyp. 1325.
12. Esterhammer, C., 1995. Das Abflussverhalten in drei kleinen forstlich genutzten Einzugsgebieten im Rosaliengebirge [The runoff behaviour of three small forested watersheds in the 'Rosalia']. PhD Dissertation. University of Natural Resources and Life Sciences, Vienna.
13. Freer J., Beven K., Ambroise B. Bayesian estimation of uncertainty in runoff, prediction and the value of data: an application of the GLUE approach. Water Resour. Res. 1996, 32(7):2161-2173. 10.1029/95WR03723.
14. Frey H.C., Patil S.R. Identification and review of sensitivity analysis methods. Risk Anal. 2002, 22(3):553-578. 10.1111/0272-4332.00039.
15. Grayson R., Blöschl G. Summary of pattern comparison and concluding remarks. Spatial Patterns in Catchment Hydrology: Observations and Modelling 2000, Cambridge University Press, Cambridge, pp. 355-367. R. Grayson, G. Blöschl (Eds.).
16. Hamilton S. Just say NO to equifinality. Hydrol. Process. 2007, 21:1979-1980. 10.1002/hyp. 6800.
17. Holzmann, H., 2003. Intercomparison of field observations and hydrological modeling of hillslope runoff components. In: Proceedings of the 9th Conference of the European Network of Experimental and Representative Basins (ERB), September 2002, Slovakia, IHP-VI Technical Documents in Hydrology N 67, UNESCO, 117-123p.
18. Holzmann H., Nachtnebel H.P. Abflussprognose für mittelgroße Einzugsgebiete - Methodik und Anwendungen [Runoff forecast for medium sized basins - methods and applications]. Oesterr. Wasser Abfallwirtsch. 2002, 54(9-10):142-153.
19. Jakeman, A.J., Ghassemi, F., Dietrich, C.R., 1990. Calibration and reliability of an aquifer system model using generalised sensitivity analysis. In: Proceedings ModelCARE 90: Calibration and Reliability in Groundwater Modelling. IAHS Publication, p. 195.
20. Kirchner J.W. Getting the right answers for the right reasons: linking measurements, analyses, and models to advance the science of hydrology. Water Resour. Res. 2006, 42. W03S04. 10.1029/2005WR004362.
21. Lilburne, L., Gatelli, D., Tarantola, S., 2006. Sensitivity analysis on spatial models: a new approach. In: Caetano, M., Painho, M. (Eds.), Proceedings of the 7th International Symposium on Spatial Accuracy Assessment in Natural Resources and Environmental Sciences, July 2006, Lisboa.
22. Liu H., Chen W., Sudjianto A. Relative entropy based method for probabilistic sensitivity analysis in engineering design. J. Mech. Des. 2006, 128(2):326-336. 10.1115/1.2159025.
23. Massmann, C., Holzmann, H., 2012. Multi-method global sensitivity analyses - results for a rainfall-runoff model. In: Seppelt, R., Voinov, A.A., Lange, S., Bankamp, D. (Eds.), Managing Resources of a Limited Planet, Proceedings of the 2012 International Congress on Environmental Modelling and Software, July 2012, Leipzig, Germany.
24. Matott L.S., Babendreier J.E., Purucker S.T. Evaluating uncertainty in integrated environmental models: a review of concepts and tools. Water Resour. Res. 2009, 45. W06421. 10.1029/2008WR007301.
25. Merz R., Blöschl G. A regional analysis of event runoff coefficients with respect to climate and catchment characteristics in Austria. Water Resour. Res. 2009, 45. W01405. 10.1029/2008WR007163.
26. Mishra S., Deeds N., Ruskauff G. Global sensitivity analysis techniques for probabilistic ground water modeling. Ground Water 2009, 47:727-744. 10.1111/j.1745-6584.2009.00604.x.
27. Mogheir Y., de Lima J.L.M.P., Singh V.P. Characterizing the spatial variability of groundwater quality using the entropy theory: I. Synthetic data. Hydrol. Process. 2004, 18:2165-2179. 10.1002/hyp.1465.
28. O'Loughlin, F., Bruen, M., Wagener, T., in press. Parameter sensitivity of a watershed-scale flood forecasting model as a function of modeling time-step. Hydrol. Res. doi:10.2166/nh.2012.157.
29. Pappenberger F., Beven K.J., Ratto M., Matgen P. Multi-method global sensitivity analysis of flood inundation models. Adv. Water Resour. 2008, 31(1):1-14. 10.1016/j.advwatres.2007.04.009.
30. Petropoulos G., Wooster M.J., Carlson T.N., Kennedy M.C., Scholze M. A global Bayesian sensitivity analysis of the 1d SimSphere soil-vegetation-atmospheric transfer (SVAT) model using Gaussian model emulation. Ecol. Model. 2009, 220(19):2427-2440. 10.1016/j.ecolmodel.2009.06.006.
31. Ratto M., Tarantola S., Saltelli A. Sensitivity analysis in model calibration: GSA-GLUE approach. Comput. Phys. Commun. 2001, 136(3):212-224. 10.1016/S0010-4655(01)00159-X.
32. Ratto M., Young P.C., Romanowicz R., Pappenberger F., Saltelli A., Pagano A. Uncertainty, sensitivity analysis and the role of data based mechanistic modeling in hydrology. Hydrol. Earth Syst. Sci. 2007, 11:1249-1266. 10.5194/hess-11-1249-2007.
33. Reusser D.E., Buytaert W., Zehe E. Temporal dynamics of model parameter sensitivity for computationally expensive models with the Fourier amplitude sensitivity test. Water Resour. Res 2011, 47. W07551. 10.1029/2010WR009947.
34. Saltelli A. Making best use of model evaluations to compute sensitivity indices. Comput. Phys. Commun. 2002, 145(2):280-297. 10.1016/S0010-4655(02)00280-1.
35. Saltelli A., Annoni P. How to avoid a perfunctory sensitivity analysis. Environ. Model. Softw. 2010, 25:1508-1517. 10.1016/j.envsoft.2010.04.012.
36. Saltelli A., Tarantola S., Campolongo F. Sensitivity analysis as an ingredient of modeling. Stat. Sci. 2000, 15(4):377-395. 10.1214/ss/1009213004.
37. Saltelli A., Tarantola S., Campolongo F., Ratto M. Sensitivity Analysis in Practice. A Guide to Assessing Scientific Models 2004, Wiley & Sons, 219p.
38. Savenije H.H.G. Equifinality, a blessing in disguise?. Hydrol. Process. 2001, 15:2835-2838. 10.1002/hyp. 494.
39. Sieber A., Uhlenbrook S. Sensitivity analyses of a distributed catchment model to verify the model structure. J. Hydrol. 2005, 310:216-235. 10.1016/j.jhydrol.2005.01.004.
40. Tang Y., Reed P., Wagener T., van Werkhoven K. Comparing sensitivity analysis methods to advance lumped watershed model identification and evaluation. Hydrol. Earth Syst. Sci. 2007, 11:793-817. 10.5194/hess-11-793-2007.
41. Tang Y., Reed P., van Werkhoven K., Wagener T. Advancing the identification and evaluation of distributed rainfall-runoff models using global sensitivity analysis. Water Resour. Res. 2007, 43. W06415. 10.1029/2006WR005813.
42. Ulrich, E., 1989. Abflussverhalten eines forstlichen Einzugsgebietes in der Rosalia 1983-1988 und Ansätze zu einem hydrologisch-chemischen Input-Output Modell [Runoff characteristic of a forested watershed in the 'Rosalia' and approaches to a hydrologic-chemical input-output model]. PhD Dissertation. University of Natural Resources and Life Sciences, Vienna.
43. van Griensven A., Meixner T., Grunwald S., Bishop T., Diluzio M., Srinivasan R. A global sensitivity analysis tool for the parameters of multi-variable catchment models. J. Hydrol. 2006, 324(1-4):10-23. 10.1016/j.jhydrol.2005.09.008.
44. van Werkhoven K., Wagener T., Reed P., Tang Y. Characterization of watershed model behavior across a hydroclimatic gradient. Water Resour. Res. 2008, 44. W01429. 10.1029/2007WR006271.
45. van Werkhoven K., Wagener T., Reed P., Tang Y. Sensitivity-guided reduction of parametric dimensionality for multi-objective calibration of watershed models. Adv. Water Resour. 2009, 32:1154-1169. 10.1016/j.advwatres.2009.03.002.
46. Wagener T., Kollat J. Numerical and visual evaluation of hydrological and environmental models using the Monte Carlo analysis toolbox. Environ. Model. Softw. 2007, 22(7):1021-1033. 10.1016/j.envsoft.2006.06.017.
47. Wagener T., McIntyre N., Lees M.J., Wheater H.S., Gupta H.V. Towards reduced uncertainty in conceptual rainfall-runoff modelling: dynamic identifiability analysis. Hydrol. Process. 2003, 17(2):455-476. 10.1002/hyp. 1135.
48. Wagener T., van Werkhoven K., Reed P., Tang Y. Multiobjective sensitivity analysis to understand the information content in streamflow observations for distributed watershed modeling. Water Resour. Res. 2009, 45. W02501. 10.1029/2008WR007347.