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International Conference on Informatics in Control, Automation and Robotics

ICINCO 2018: Informatics in Control, Automation and Robotics pp 168–192Cite as

Influence of the Predictive Rainfall/Runoff Model Accuracy on an Optimal Water Resource Management Strategy

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Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 613))

Abstract

This work regards the improvement of water asset management and modelling strategies proposed recently for hydrographical networks in a context of global warming which exacerbates extreme events. Indeed, hydrographical systems, and more specifically those including inland waterways, are large scale systems that involve mass energy transport phenomena consisting in the amount of water in excess induced by extreme rainy events. The water excess has to be dispatched over the complete network in order to anticipate the effects of potential floods and rejected to the sea either by gravity flow heeding the tides or by the utilization of pumps. The latter solution leads to big operation costs and has to be minimized. These goals are fulfilled by means of an integrated model within a flow-based network and a quadratic optimization based on constraints. The recent improvements in the field of predictive rainfall/runoff modelling approaches helps to enhance the operational goals of this water management strategy. A particular example of these approaches are those related to the identification of black-box ARX models in its linear and nonlinear structures. A performance comparison between the recursive least square and the recursive instrumental variable estimation of an ARX model and the estimation of a Linear Parameter Varying ARX-based model is carried out on a river located in the north of France with a prediction horizon of 24 h. Further, the performance of the resource management methodology is tested by means of a realistic case study based on a portion of the real inland waterways located in the north of France.

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References

  1. Alves DCCS, Duviella E, Doniec A (2018) Improvement of water resource allocation planning of inland waterways based on predictive optimization approach. In: Proceedings of the 15th international conference on informatics in control, automation and robotics (ICINCO 2018), pp 305–312

    Google Scholar 

  2. Arkell B, Darch G (2006) Impact of climate change on london’s transport network. Proc ICE - Municipal Eng 159:231–237

    Article  Google Scholar 

  3. Asefa T, Kemblowski M, McKee M, Khalil A (2006) Multi-time scale stream flow predictions: the support vector machines approach. J Hydrol 318(1):7–16

    Article  Google Scholar 

  4. Bastin G, Moens L, Dierick P (2009) Online river flow forecasting with hydromax: successes and challenges after twelve years of experience. In: proceedings of the 15th IFAC symposium on system identification, Saint-Malo, France, 6–8 July 2009

    Google Scholar 

  5. Bates B, Kundzewicz Z, Wu S, Palutikof J (2008) Climate change and water. Technical report, Intergovernmental Panel on Climate Change, Geneva

    Google Scholar 

  6. Boé J, Terray L, Martin E, Habetsi F (2009) Projected changes in components of the hydrological cycle in French river basins during the 21st century. Water Resour Res 45

    Google Scholar 

  7. Bourgin F (2014) Comment quantifier l’incertitude prédictive en modélisation hydrologique?: Travail exploratoire sur un grand échantillon de bassins versants. Ph.D. thesis, thèse de doctorat dirigée par Andréassian, Vazken Hydrologie Paris, AgroParisTech 2014. http://www.theses.fr/2014AGPT0016

  8. Brand C, Tran M, Anable J (2012) The UK transport carbon model: an integrated life cycle approach to explore low carbon futures. Energy Policy 41:107–124

    Article  Google Scholar 

  9. Dakhlaoui H, Ruelland D, Tramblay Y, Bargaoui Z (2017) Evaluating the robustness of conceptual rainfall-runoff models under climate variability in northern Tunisia. J Hydrol 550:201–217. https://doi.org/10.1016/j.jhydrol.2017.04.032. http://www.sciencedirect.com/science/article/pii/S0022169417302512

    Article  Google Scholar 

  10. Ducharne A, Habets F, Pagé C, Sauquet E, Viennot P, Déqué M, Gascoin S, Hachour A, Martin E, Oudin L, Terray L, Thiéry D (2010) Climate change impacts on water resources and hydrological extremes in northern France. In: XVIII conference on computational methods in water resources, Barcelona, Spain, June 2010

    Google Scholar 

  11. Duviella E, Bako L (2012) Predictive black-box modeling approaches for flow forecasting of the Liane river. In: SYSID 2012, Bruxelles, Belgium, 11–13 July 2012

    Article  Google Scholar 

  12. Duviella E, Nouasse H, Doniec A, Chuquet K (2016) Dynamic optimization approaches for resource allocation planning in inland navigation networks. In: ETFA 2016, Berlin, Germany, 6–9 September 2016

    Google Scholar 

  13. Duviella E, Rajaoarisoa L, Blesa J, Chuquet K (2013) Adaptive and predictive control architecture of inland navigation networks in a global change context: application to the cuinchy-fontinettes reach. In: IFAC MIM conference, Saint Petersburg, 19–21 June 2013

    Article  Google Scholar 

  14. Edijatno, Michel C (1989) Un modèle pluie-débit journalier à trois paramètres. La Houille Blanche 2:113–121

    Article  Google Scholar 

  15. Edijatno, Nascimento NDO, Yang X, Makhlouf Z, Michel C (1999) GR3J: a daily watershed model with three free parameters. Hydrol Sci J 44(2):263–277

    Article  Google Scholar 

  16. Elshorbagy A, Corzo G, Srinivasulu S, Solomatine DP (2010) Experimental investigation of the predictive capabilities of data driven modeling techniques in hydrology - part 2: application. Hydrol Earth Syst Sci 14(10):1943–1961

    Article  Google Scholar 

  17. EnviCom (2008) Climate change and navigation - waterborne transport, ports and waterways: a review of climate change drivers, impacts, responses and mitigation. EnviCom - Task Group 3

    Google Scholar 

  18. Ficchi A (2017) An adaptive hydrological model for multiple time-steps: diagnostics and improvements based on fluxes consistency. Theses, Université Pierre et Marie Curie - Paris VI, France, February 2017. https://tel.archives-ouvertes.fr/tel-01619102

  19. Hadid B, Duviella E (2018) Water asset management strategy based on predictive rainfall/runoff model to optimize the evacuation of water to the sea. In: Proceedings of the 15th international conference on informatics in control, automation and robotics (ICINCO 2018), pp 76–85

    Google Scholar 

  20. Hadid B, Duviella E, Lecoeuche S (2018) Improvement of a predictive data-driven model for rainfall-runoff global characterization of a river. In: Proceedings of the 4th international forum on research and technologies for society and industry, Palermo, Italy, September 2018

    Google Scholar 

  21. Horvàth K, Duviella E, Rajaoarisoa L, Chuquet K (2014) Modelling of a navigation reach with unknown inputs: the cuinchy-fontinettes case study. Simhydro, Sofia Antipolis, 11–13 June 2014

    Google Scholar 

  22. Horvàth K, Duviella E, Rajaoarisoa L, Negenborn R, Chuquet K (2015) Improvement of the navigation conditions using a model predictive control - the cuinchy-fontinettes case study. In: International conference on computational logistics, Delft, The Netherlands, 23–25 September 2015

    Google Scholar 

  23. Horvàth K, Petrecsky M, Rajaoarisoa L, Duviella E, Chuquet K (2014) MPC of water level in a navigation canal - the cuinchy-fontinettes case study. In: European control conference, Strasbourg, France, 24–27 June 2014

    Google Scholar 

  24. Horvàth K, Rajaoarisoa L, Duviella E, Blesa J, Petreczky M, Chuquet K (2015) Enhancing inland navigation by model predictive control of water level - the cuinchy-fontinettes case. In: Ocampo-Martinez C, Engenborn R (eds) Transport of water versus transport over water. Springer, Heidelberg Exploring the dynamic interplay between transport and water

    Google Scholar 

  25. http://www.hydro.eaufrance.fr

  26. IWAC (2009) Climate change mitigation and adaptation. Implications for inland waterways in England and wales. Report

    Google Scholar 

  27. Jonkeren O, Rietveld P, van Ommeren J (2007) Climate change and inland waterway transport: welfare effects of low water levels on the river Rhine. J Transp Econ Policy 41:387–412

    Google Scholar 

  28. Kara S, Sihn W, Pascher H, Ott K, Stein S, Schumacher A, Mascolo G (2015) A green and economic future of inland waterway shipping. In: Procedia CIRP - the 22nd CIRP conference on life cycle engineering, vol 29, pp 317–322. https://doi.org/10.1016/j.procir.2015.02.171, http://www.sciencedirect.com/science/article/pii/S2212827115004850

    Article  Google Scholar 

  29. Koetse MJ, Rietveld P (2009) The impact of climate change and weather on transport: an overview of empirical findings. Transp Res Part D Transp Environ 14(3):205–221. https://doi.org/10.1016/j.trd.2008.12.004

    Article  Google Scholar 

  30. Laurain V (2010) Contributions à l’identification de modèeles paramétriques non linéaires. application à la modélisation de bassins versants ruraux. Ph.D. thesis, Université Henri Poincaré, Nancy 1

    Google Scholar 

  31. Ljung L (1999) System identification: theory for the user, 2nd edn. Prentice Hall, Upper Saddle River

    MATH  Google Scholar 

  32. Mallidis I, Dekker R, Vlachos D (2012) The impact of greening on supply chain design and cost: a case for a developing region. J Transp Geogr 22:118–128

    Article  Google Scholar 

  33. Mihic S, Golusin M, Mihajlovic M (1993) Policy and promotion of sustainable inland waterway transport in Europe - Danube river. Renew Sustain Energy Rev 15:1801–1809

    Article  Google Scholar 

  34. Nash JE, Sutcliffe JV (1970) River flow forecasting through conceptual models part I: a discussion of principles. J Hydrol 10(3):282–290

    Article  Google Scholar 

  35. Nouasse H, Doniec A, Lozenguez G, Duviella E, Chiron P, Archimède B, Chuquet K (2016) Constraint satisfaction problem based on flow transport graph to study the resilience of inland navigation networks in a climate change context. In: IFAC conference MIM, Troyes, France, 28–30 June 2016

    Google Scholar 

  36. Nouasse H, Horvàth K, Rajaoarisoa L, Doniec A, Duviella E, Chuquet K (2016) Study of global change impacts on the inland navigation management: application on the nord-pas de calais network. Transport Research Arena, Varsovie, Poland

    Google Scholar 

  37. Nouasse H, Rajaoarisoa L, Doniec A, Chiron P, Duviella E, Archimède B, Chuquet K (2015) Study of drought impact on inland navigation systems based on a flow network model. In: ICAT, Sarajevo, Bosnie Herzegovia

    Google Scholar 

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

    Article  Google Scholar 

  39. Previdi F, Lovera M (2009) Identification of parametrically-varying models for the rainfall-runoff relationship in urban drainage networks. IFAC Proc Vol 42(10):1768–1773. https://doi.org/10.3182/20090706-3-FR-2004.00294 15th IFAC symposium on system identification, http://www.sciencedirect.com/science/article/pii/S147466701638908X

    Article  Google Scholar 

  40. Rajaoarisoa L, Horvàth K, Duviella E, Chuquet K (2014) Large-scale system control based on decentralized design. Application to cuinchy fontinette reach. In: IFAC world congress, Cape Town, South Africa, 24–29 August 2014

    Google Scholar 

  41. Segovia P, Rajaoarisoa L, Nejjari F, Puig V, Duviella E (2017) Decentralized control of inland navigation networks with distributaries: application to navigation canals in the north of France. In: ACC 2017, Seattle, WA, USA, 24–26 May 2017

    Google Scholar 

  42. Siou LKA, Johannet A, Pistre S, Borrell V (2010) Flash floods forecasting in a Karstic basin using neural networks: the case of the Lez basin (south of France). In: Andreo et al (eds) International symposium on Karst – ISKA, Malaga. Advances in research in karst media. Springer

    Google Scholar 

  43. Tòth R, Felici F, Heuberger PSC, den Hof PMJV (2007) Discrete time LPV I/O and state space representations, differences of behavior and pitfalls of interpolation. In: Proceedings of the European control conference, Kos, Greece, pp 5418–5425, July 2007

    Google Scholar 

  44. Tóth R, Laurain V, Gilson M, Garnier H (2011) On the closed loop identification of LPV models using instrumental variables. In: Proceedings of the 18th IFAC world congress, Milano, Italy, vol 44, no 1, pp 7773–7778

    Article  Google Scholar 

  45. Wang S, Kang S, Zhang L, Li F (2007) Modelling hydrological response to different land-use and climate change scenarios in the Zamu river basin of northwest China. Hydrol Process 22:2502–2510

    Article  Google Scholar 

  46. Young PC (1986) Time series methods and recursive estimation in hydrological systems analysis. In: Kraijenhoff DA, Moll JR (eds) River flow modelling and forecasting. D. Reidel, Dordrecht, pp 129–180

    Chapter  Google Scholar 

  47. Young P (2003) Top-down and data-based mechanistic modelling of rainfall-flow dynamics at the catchment scale. Hydrol Process 17:2195–2217

    Article  Google Scholar 

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Authors and Affiliations

  1. Institut Mines Telecom Lille Douai, University of Lille, Lille, France

    Baya Hadid & Eric Duviella

Authors
  1. Baya Hadid
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  2. Eric Duviella
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Correspondence to Baya Hadid .

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Editors and Affiliations

  1. Ford Research and Advanced Engineer, Dearborn, MI, USA

    Oleg Gusikhin

  2. University of Paris-EST Créteil (UPEC), Créteil, France

    Kurosh Madani

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Hadid, B., Duviella, E. (2020). Influence of the Predictive Rainfall/Runoff Model Accuracy on an Optimal Water Resource Management Strategy. In: Gusikhin, O., Madani, K. (eds) Informatics in Control, Automation and Robotics. ICINCO 2018. Lecture Notes in Electrical Engineering, vol 613. Springer, Cham. https://doi.org/10.1007/978-3-030-31993-9_8

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