Abstract
Uncertainty analysis is an essential step in river modelling. Knowledge of the uncertainty is crucial for a meaningful interpretation of the model results. In this chapter we describe the whole process of an uncertainty analysis in four steps: identification, prioritization, quantification and propagation. In each step the rationale behind choosing a method is described and illustrated with an example of the design water level computation of the Dutch river Waal with a 2D hydrodynamic model. The sources of uncertainty related to the case study are identified and their (relative) importance is determined using expert opinions combined with a novel uncertainty identification method. Subsequently, the sources with the largest effect on the design water levels are individually quantified and propagated using Monte Carlo analysis to yield the quantified uncertainty in the design water levels. The uncertainty analysis provided information about the reliability of the model results and about further actions to possibly reduce the uncertainty and their benefits in terms of increased accuracy.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Bates PD, Horritt MS, Aronica G, Beven KJ (2004) Bayesian updating of flood inundation likelihoods conditioned on flood extent data. Hydrol Process 18(17):3347–3370. doi:10.1002/hyp.1499
Beven K, Binley A (1992) The future of distributed models: model calibration and uncertainty prediction. Hydrol Process 6:279–298. doi:10.1002/hyp.3360060305
Brugnach M (2005) Process level sensitivity analysis for complex ecological models. Ecol Model 187(2–3):99–120. doi:10.1016/j.ecolmodel.2005.01.044
Dewulf A, Craps M, Bouwen R, Taillieu T, Pahl-Wostl C (2005) Integrated management of natural resources: dealing with ambiguous issues, multiple actors and diverging frames. Water Sci Technol 52 (6):115˝U–124
Delta Programme (2015) Working on the delta. The decisions to keep the Netherlands safe and liveable. Ministry of Infrastructure and the Environment and Ministry of Economic Affairs.www.deltacommissaris.nl. Accessed 18 May 2015
Engelund F (1977) Hydraulic resistance for flow over dunes. Progress report of the Institute for Hydrodynamic and Hydraulic Engineering 44, Technical University Denmark
European Parliament (2007) Directive 2007/60/EC of the European Parliament and of the Council of 23 October 2007 on the assessment and management of flood risks. Official Journal of the European Union, L 288/27
Gan Y, Duan Q, Gong W, Tong C, Sun Y, Chu W, Ye A, Miao C, Di Z (2014) A comprehensive evaluation of various sensitivity analysis methods: a case study with a hydrological model. Environ Model Softw 51:269–285. doi:10.1016/j.envsoft.2013.09.031
Hall JW, Tarantola S, Bates PD, Horritt MS (2005) Distributed sensitivity analysis of flood Inundation model calibration. J Hydraul Eng131 (2):117–126. doi: 10.1061/(ASCE)0733-9429(2005)131:2(117)
Hall JW, Boyce SA, Wang Y, Dawson RJ, Tarantola S, Saltelli A (2009) Sensitivity analysis for hydraulic models. J Hydraul Eng 135(11):959–969. doi:10.1061/(ASCE)HY.1943-7900.0000098
Haque MI, Mahmood K (1983) Analytical determination of form friction factor. J Hydraul Eng 109(4):590–610
Helton JC, Davis FJ (2003) Latin hypercube sampling and the propagation of uncertainty in analyses of complex systems. Reliab Eng Syst Saf 81(1):23–69. doi:10.1016/S0951-8320(03)00058-9
Jakeman AJ, Letcher RA, Norton JP (2006) Ten iterative steps in development and evaluation of environmental models. Environ Model Softw 21(5):602–614. doi:10.1016/j.envsoft.2006.01.004
Julien PY, Klaassen GJ, Ten Brinke WBM, Wilbers AWE (2002) Case study: bed resistance of Rhine river during 1998 flood. J Hydraul Eng 128(12):1042–1050. doi: 10.1061/(ASCE)0733-9429(2002)128:12(1042)
Krayer von Krauss MP, Casman EA, Small MJ (2004) Elicitation of expert judgments of uncertainty in the risk assessment of herbicide-tolerant oilseed crops. Risk Anal 24(6):1515–1527. doi:10.1111/j.0272-4332.2004.00546.x
Leskens J, Brugnach M, Hoekstra AY, Schuurmans W (2014) Why are decisions in flood disaster management so poorly supported by information from flood models? Environ Model Softw 53:53–61. doi:10.1016/j.envsoft.2013.11.003
Loucks DP, Van Beek E (2005) Water resources systems planning and management, an introduction to methods, models and applications. Unesco Publishing, Paris and WL | Delft Hydraulics, the Netherlands. ISBN 92-3-103998-9
Morgan MG, Henrion M (1990) Uncertainty: a guide to dealing with uncertainty in quantitative risk and policy analysis. Cambridge University Press, Cambridge. ISBN 0-521-36542-2
Pappenberger F, Beven KJ (2006) Ignorance is bliss: or seven reasons not to use uncertainty analysis. Water Resour Res 42:W05302. doi:10.1029/2005WR004820
Parrish MA, Moradkhani H, DeChant CM (2012) Toward reduction of model uncertainty: integration of Bayesian model averaging and data assimilation. Water Resour Res 48(3):W03519. doi:10.1029/2011WR011116
Refsgaard JC, Van der Keur P, Nilsson B, Müller-Wohlfeil D, Brown J (2006) Uncertainties in river basin data at various support scales—example from Odense pilot river basin. Hydrol Earth Syst Sci Discuss 3(4):1943–1985. doi:10.5194/hessd-3-1943-2006
Refsgaard JC, Van der Sluijs JP, Lajer Hojberg A, Vanrolleghem PA (2007) Uncertainty in the environmental modelling process: a framework and guidance. Environ Model Softw 22(11):1543–1556. doi:10.1016/j.envsoft.2007.02.004
Rijkswaterstaat (2007) Hydraulische randvoorwaarden primaire waterkeringen, voor de derde toetsronde 2006–2011 (HR 2006). Ministry of Transportation, Public Works and Water Management (in Dutch)
Saltelli A, Funtowicz S (2014) When all models are wrong. Issues Sci Technol winter 2014:79–85
Saltelli A, Tarantola S, Campologno F, Ratto M (2004) Sensitivity analysis in practice, a guide to assessing scientific models. Wiley, London. ISBN 0-470-87093-1
Saltelli A, Ratto M, Andres T, Campolongo F, Cariboni J, Gatelli D, Saisana M, Tarantola S (2008) Global sensitivity analysis, the primer. Wiley, West Sussex. ISBN 978-0-470-05997-5
Silva W, Klijn F, Dijkman J (2001) Room for the Rhine branches in the Netherlands: what the research has taught us. RIZA report 2001.031, Ministry of Public Works, Transportation and Water Management and WL|Delft Hydraulics, the Netherlands
Straatsma MW, Huthoff F (2011) Uncertainty in 2D hydrodynamic models from errors in roughness parameterization based aerial images. J Phys Chem Earth 36(7–8):324–334. doi:10.1016/j.pce.2011.02.009
Todini E (2008) A model conditional process to assess predictive uncertainty in flood forecasting. Int J River Basin Manage 6(2):123–137
Van den Brink NGM, Beyer D, Scholten MJM, van Velzen EH (2006) Onderbouwing hydraulische randvoorwaarden 2001 voor de Rijn en zijn takken. RIZA report 2002.015, RIZA, Lelystad, the Netherlands. ISBN 90-3695-322-7 (in Dutch)
Van den Hoek RE, Brugnach M, Mulder JPM, Hoekstra AY (2013) Analysing the cascades of uncertainty in flood defence projects: how ‘‘not knowing enough’’ is related to ‘‘knowing differently’’. Glob Environ Change. doi:10.1016/j.gloenv-cha.2013.11.008
Van der Klis H (2003) Uncertainty analysis applied to numerical models of bed morphology. Ph.D. thesis, Delft University of Technology, Delft, the Netherlands
Van der Sluijs JP, Craye M, Funtowicz S, Kloprogge P, Ravetz J, Risbey J (2005a) Combining quantitative and qualitative measures of uncertainty in model-based environmental assessment: the NUSAP system. Risk Anal 25(2):481–492. doi:10.1111/j.1539-6924.2005.00604.x
Van der Sluijs JP, Risbey JS, Ravetz J (2005b) Uncertainty assessment of VOC emissions from paint in the Netherlands using the NUSAP system. Environ Monit Assess 105(1–3):229–259. doi:10.1007/s10661-005-3697-7
Van Gelder PHAJM, Mai CV (2008) Distribution functions of extreme sea waves and river discharges. J Hydraul Res 46(Special Issue 2):280–291
Van Loon E, Refsgaard JC (eds) (2005) Guidelines for assessing data uncertainty in river basin management studies. Geological survey of Denmark and Greenland, Copenhagen, pp 182. Available on http://www.harmonirib.com
Van Rijn LC (1984) Sediment transport, part III: bed forms and alluvial roughness. J Hydraul Eng 110(12):1733–1754. doi: 10.1061/(ASCE)0733-9429(1984)110:12(1733)
Van Stokkom HTC, Smits AJM, Leuven, RSEW (2005) Flood defence in the Netherlands: a new era a new approach. Water International 30(1):76-87. doi:10.1080/02508060508691839
Vanoni VA, Hwang LS (1967) Relation between bed forms and friction in streams. J Hydraul Div 93(HY3):121–144
Walker WE, Harremoës P, Rotmans J, van der Sluijs JP, van Asselt MBA, Janssen P, Krayer von Kraus MP (2003) Defining uncertainty, a conceptual basis for uncertainty management in model–based decision support. Integr Assess 4(1):5–17
Warmink JJ (2011) Unravelling uncertainties. The effect of hydraulic roughness on design water levels in river models. Ph.D. thesis, University of Twente, pp 185
Warmink JJ, Booij MJ, Van der Klis H, Hulscher SJMH (2007) Uncertainty of water level predictions due to differences in the calibration discharge. In: Proceedings of the international conference on adaptive and integrated water management, CAIWA2007. Basel, Switserland, p 18
Warmink JJ, Janssen JAEB, Booij MJ, Krol M (2010) Identification and classification of uncertainties in the application of environmental models. Environ Model Softw 25(12):1518–1527. doi:10.1016/j.envsoft.2010.04.011
Warmink JJ, Booij MJ, Van der Klis H, Hulscher SJMH (2013a) Quantification of uncertainty in design water levels due to uncertain bed form roughness in the Dutch river Waal. Hydrol Process 27:1646–1663. doi:10.1002/hyp.9319
Warmink JJ, Straatsma MW, Huthoff F, Booij MJ, Hulscher SJMH (2013b) Uncertainty of design water levels due to combined bed form and vegetation roughness in the Dutch River Waal. J Flood Risk Manage 6:302–318
Warmink JJ, Van der Klis H, Booij MJ, Hulscher SJMH (2011) Identification and quantification of uncertainties in a hydrodynamic river model using expert opinions. Water Resour Manage 25(2):601–622. doi:10.1007/s11269-010-9716-7
Wilbers AWE, Ten Brinke WBM (2003) The response of subaqueous dunes to floods in sand and gravel bed reaches of the Dutch Rhine. Sedimentology 50(6):1013–1034. doi:10.1046/j.1365-3091.2003.00585.x
Wright S, Parker G (2004) Flow resistance and suspended load in sand-bed rivers: simplified stratification model. J Hydraul Eng 130(8):796–805. doi:10.1061/(ASCE)0733-9429(2004)130:8(796)
Zhou H, Gomez-Hernandez JJ, Li L (2014) Inverse methods in hydrogeology: evolution and recent trends. Adv Water Resour 63:22–37. doi:10.1016/j.advwatres.2013.10.014
Acknowledgments
This research was supported by the Technology Foundation STW, applied science division of the Netherlands Organisation for Scientific Research (NWO), and the technology program of the Ministry of Economic Affairs. We thank the Dutch Centre for Water Management for providing the WAQUA model to do the analysis. Furthermore, we thank all the co-authors: Freek Huthoff, Hanneke Van der Klis, Menno Straatsma and Suzanne Hulscher for their assistance during the research. The research in Sect. 11.6 was also supported by the Flood Control 2015 program (www.floodcontrol2015.com).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this chapter
Cite this chapter
Warmink, J.J., Booij, M.J. (2015). Uncertainty Analysis in River Modelling. In: Rowiński, P., Radecki-Pawlik, A. (eds) Rivers – Physical, Fluvial and Environmental Processes. GeoPlanet: Earth and Planetary Sciences. Springer, Cham. https://doi.org/10.1007/978-3-319-17719-9_11
Download citation
DOI: https://doi.org/10.1007/978-3-319-17719-9_11
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-17718-2
Online ISBN: 978-3-319-17719-9
eBook Packages: Earth and Environmental ScienceEarth and Environmental Science (R0)