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Scenario development for water resource planning and management: A review

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  • Dong, Congli
  • Schoups, Gerrit
  • van de Giesen, Nick

Abstract

This paper reviews current research on scenario development in water resource management. We provide an overview of existing techniques, highlight any limitations, and discuss future research directions to improve scenario development practices for water resource planning. In water management, scenarios are used to account for uncertainties associated with climatic, socio-economic, and management conditions that affect the performance of water resource systems. These uncertainties affect future water supply, water demand and management strategy. Several water-related scenarios with qualitative and quantitative techniques are reviewed against a general scenario development procedure. Although the reviewed literature demonstrates that scenario development is an effective tool to deal with uncertain future water systems, two limitations of applied quantitative techniques were identified: (i) the need for extending discrete scenarios to continuous scenarios to more completely cover future conditions, and (ii) the need for introducing probabilistic scenarios to explicitly quantify uncertainties. These issues can be addressed using existing techniques from information theory and statistics, pointing the way forward for scenario development practices in water resource planning and management.

Suggested Citation

  • Dong, Congli & Schoups, Gerrit & van de Giesen, Nick, 2013. "Scenario development for water resource planning and management: A review," Technological Forecasting and Social Change, Elsevier, vol. 80(4), pages 749-761.
    • Handle: RePEc:eee:tefoso:v:80:y:2013:i:4:p:749-761
    DOI: 10.1016/j.techfore.2012.09.015
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    Cited by:

    1. Hu, Zhineng & Chen, Yazhen & Yao, Liming & Wei, Changting & Li, Chaozhi, 2016. "Optimal allocation of regional water resources: From a perspective of equity–efficiency tradeoff," Resources, Conservation & Recycling, Elsevier, vol. 109(C), pages 102-113.
    2. Cheng, M.N. & Wong, Jane W.K. & Cheung, C.F. & Leung, K.H., 2016. "A scenario-based roadmapping method for strategic planning and forecasting: A case study in a testing, inspection and certification company," Technological Forecasting and Social Change, Elsevier, vol. 111(C), pages 44-62.
    3. Marasco, Addolorata & Romano, Alessandro, 2018. "Inter-port interactions in the Le Havre-Hamburg range: A scenario analysis using a nonautonomous Lotka Volterra model," Journal of Transport Geography, Elsevier, vol. 69(C), pages 207-220.
    4. Addolorata Marasco & Alessandro Romano, 2018. "Deterministic modeling in scenario forecasting: estimating the effects of two public policies on intergenerational conflict," Quality & Quantity: International Journal of Methodology, Springer, vol. 52(5), pages 2345-2371, September.
    5. Jahel, Camille & Bourgeois, Robin & Bourgoin, Jérémy & Daré, William's & De Lattre-Gasquet, Marie & Delay, Etienne & Dumas, Patrice & Le Page, Christophe & Piraux, Marc & Prudhomme, Rémi, 2023. "The future of social-ecological systems at the crossroads of quantitative and qualitative methods," Technological Forecasting and Social Change, Elsevier, vol. 193(C).
    6. Andrea K. Gerlak & Katharine L. Jacobs & Amy L. McCoy & Season Martin & Mariana Rivera-Torres & Anna M. Murveit & Amanda J. Leinberger & Timothy Thomure, 2021. "Scenario Planning: Embracing the Potential for Extreme Events in the Colorado River Basin," Climatic Change, Springer, vol. 165(1), pages 1-21, March.
    7. Moreira, Fabrícia de Souza & Lopes, Mariana Padilha Campos & de Freitas, Marcos Aurélio Vasconcelos & Antunes, Adelaide Maria de Souza, 2021. "Future scenarios for the development of the desalination industry in contexts of water scarcity: A Brazilian case study," Technological Forecasting and Social Change, Elsevier, vol. 167(C).
    8. Pauline Macharia & Nzula Kitaka & Paul Yillia & Norbert Kreuzinger, 2021. "Assessing Future Water Demand and Associated Energy Input with Plausible Scenarios for Water Service Providers (WSPs) in Sub-Saharan Africa," Energies, MDPI, vol. 14(8), pages 1-22, April.
    9. Feng, Le & Chen, Bin & Hayat, Tasawar & Alsaedi, Ahmed & Ahmad, Bashir, 2017. "Dynamic forecasting of agricultural water footprint based on Markov Chain-a case study of the Heihe River Basin," Ecological Modelling, Elsevier, vol. 353(C), pages 150-157.
    10. Mathijs Vliet & Kasper Kok, 2015. "Combining backcasting and exploratory scenarios to develop robust water strategies in face of uncertain futures," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 20(1), pages 43-74, January.
    11. Marasco, A. & Picucci, A. & Romano, A., 2016. "Market share dynamics using Lotka–Volterra models," Technological Forecasting and Social Change, Elsevier, vol. 105(C), pages 49-62.
    12. Katharina Proswitz & Mamkwe Claudia Edward & Mariele Evers & Felister Mombo & Alexander Mpwaga & Kristian Näschen & Jennifer Sesabo & Britta Höllermann, 2021. "Complex Socio-Ecological Systems: Translating Narratives into Future Land Use and Land Cover Scenarios in the Kilombero Catchment, Tanzania," Sustainability, MDPI, vol. 13(12), pages 1-27, June.
    13. Goran Dominioni & Addolorata Marasco & Alessandro Romano, 2018. "A mathematical approach to study and forecast racial groups interactions: deterministic modeling and scenario method," Quality & Quantity: International Journal of Methodology, Springer, vol. 52(4), pages 1929-1956, July.
    14. Huanhuan Qin & Chunmiao Zheng & Xin He & Jens Christian Refsgaard, 2019. "Analysis of Water Management Scenarios Using Coupled Hydrological and System Dynamics Modeling," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(14), pages 4849-4863, November.

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