Skip to main content
SpringerLink
Log in

Analytical Support for Integrated Water Resources Management: A New Method for Addressing Spatial and Temporal Variability

  • Published:
Water Resources Management Aims and scope Submit manuscript

Abstract

This paper discusses the development of an analytical support system for implementation of the Integrated Water Resources Management (IWRM) process. The system integrates four analytical tools: (i) geographic information system; (ii) system dynamics simulation; (iii) agent-based model; and (iv) hydrologic simulation. The choice of tools is driven by their ability to (a) respond to the main requirements of the IWRM and (b) explicitly describe system behaviour as function of time and location in space. The system dynamics simulation captures temporal dynamics in an integrated feedback model that includes sectors representing physical and socioeconomic system components. Management policies established in the participatory decision making environment are easily investigated through the simulation of system behaviour. Agent-based model is used to analyze spatial dynamics of complex physical-social-economic-biologic system. The IWRM support system is tested using data from the Upper Thames River Watershed, Ontario, Canada, in collaboration with the Upper Thames River Conservation Authority.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9

Similar content being viewed by others

References

  • Ahmad S (2002) An Intelligent decision support system for flood management: a spatial system dynamics approach. Dissertation, The University of Western Ontario, London, Canada

  • Ahmad S, Simonovic SP (2000a) Analysis of economic and social impacts of flood management policies using system dynamics. Proc. Int. Conf. of the American Institute of Hydrology. Atmospheric, Surface and Subsurface Hydrology and Interactions, Research Triangle Park, N.C.

  • Ahmad S, Simonovic SP (2000b) Dynamic modeling of flood management policies. Proc. 18th Int. Conf. of the System Dynamics Society, Sustainability in the Third Millennium, Bergen, Norway

  • Ahmad S, Simonovic SP (2000c) System dynamics modeling of reservoir operation for flood management. J Comput Civ Eng 14(3):190–198

    Article  Google Scholar 

  • Clavel L, Charron MH, Therond O, Leenhardt D (2012) A modelling solution for developing and evaluating agricultural land-use scenarios in water scarcity contexts. Water Resour Manag 26(9):2625–2641. doi:10.1007/s11269-012-0037-x

    Article  Google Scholar 

  • Coelho AC, Labadie JW, Fontane DG (2012) Multicriteria decision support system for regionalization of integrated water resources management. Water Resour Manag 26(5):1325–1346. doi:10.1007/s11269-011-9961-4

    Article  Google Scholar 

  • Cunderlik J, Simonovic SP (2004) Selection of Calibration and Verification Data for the HEC-HMS Hydrologic Model. Water Resources Research Report no. 047, Facility for Intelligent Decision Support, Department of Civil and Environmental Engineering, The University of Western Ontario, London, Ontario, Canada

  • Cunderlik J, Simonovic SP (2005) Hydrologic extremes in South–Western Ontario under future climate projections. J Hydrolog Sci 50(4):631–654

    Google Scholar 

  • Cunderlik J, Simonovic SP (2007) Inverse flood risk modeling under changing climatic conditions. Hydrolog Sci J 21(5):563–577

    Google Scholar 

  • Ferber J (1999) Multi-agent system: an introduction to distributed artificial intelligence. Addison-Wesley, Harlow

    Google Scholar 

  • Feuillette S, Bousquet F, Le Goulven P (2003) (2003) SINUSE: a multi-agent model to negotiate water demand management on a free access water table. Environ Model Softw 18:413–427

    Article  Google Scholar 

  • Fletcher EJ (1998) The use of system dynamics as a decision support tool for the management of surface water resources. Proc. 1st Int. Conf. on New Information Technologies for Decision Making in Civil Engineering, Montreal, 909–920

  • Forrester JW (1961) Industrial dynamics. Pegasus Communications Inc., Willinston

    Google Scholar 

  • Gunkel A (2005) The application of multi-agent systems for water resources research – possibilities and limits. Master Thesis, Institut für Hydrologie der Albert-Ludwigs-Universität Freiburg, Freiburg

  • Gunkel A, Kulls C (2005) Toward agent-based modelling of stakeholder behaviour – a pilot study of drought vulnerability of decentralized water supply in NE Brazil. International Environmental Modelling and Software Society (iEMSs)

  • Keyes AM, Palmer R (1993) The role of object oriented simulation models in the drought preparedness studies. Proc. Water Management in 90’s: a time for innovation, ASCE, New York

  • Lansing JS, Kremer JN (1993) Emergent properties of Balinese water temples. Am Anthropol 95(1):97–114

    Article  Google Scholar 

  • Mainuddin M, Kirby M, Qureshi ME (2007) Integrated hydrologic–economic modelling for analyzing water acquisition strategies in the Murray River Basin. Agr Water Manag 93:123–135

    Article  Google Scholar 

  • North MJ, Macal CM (2009) Agent-based modeling and systems dynamics model replication. International Journal of Simulation and Process Modelling

  • Ota S (2009) IWRM guidelines at river basin level, UNESCO

  • Prodanovic P, Simonovic SP (2007a) Impacts of changing climatic conditions in the upper Thames river basin. Canadian Water Resour Manag 32(4):265–284

    Article  Google Scholar 

  • Prodanovic P, Simonovic SP (2007a) integrated water resources modelling of the upper Thames river basin. Proceedings of the 18th CSCE Canadian Hydrotechnical Conference, Canadian Society for Civil engineering; 22–24 August, 2007; Winnipeg, Manitoba, Canada

  • Prodanovic P, Simonovic SP (2010) An operational model for integrated water resources management of a watershed. Int J Water Resour Manag 24(6):1161–1194

    Article  Google Scholar 

  • Raymond JK, Loucks DP, Stedinger JR, 10 (2012) Artificial neural network models of watershed nutrient loading. Water Resour Manag 26:2781–2797. doi:10.1007/s11269-012-0045-x

    Article  Google Scholar 

  • Simonovic SP (2009) Managing water resources: methods and tools for a systems approach, UNESCO, Paris and Earthscan James & James, London, pp. 576, ISBN 978-1-84407-554-6

  • Simonovic SP, Li L (2003) Methodology for assessment of climate change impacts on large-scale flood protection system. J Water Resour Plan Manag 129(5):361–371

    Article  Google Scholar 

  • Sterman JD (2000) Business dynamics: systems thinking and modeling for a complex world. McGraw-Hill, New York

    Google Scholar 

  • Upper Thames River Conservation Authority UTRCA (2006) http://www.thamesriver.on.ca/ (accessed 09/2011)

  • USACE (2000) Hydrologic modelling system HEC–HMS, Technical reference manual. United States Army Corps of Engineers, Davis

    Google Scholar 

  • Ward FA, Booker JF, Michelsen AM (2006) Integrated economic, hydrologic, and institutional analysis of policy responses to mitigate drought impacts in Rio Grande Basin. J Water Resour Plann Manag 132(6):488–502

    Article  Google Scholar 

  • Wilensky U (1999) NetLogo. http://ccl.northwestern.edu/netlogo/. Center for Connected Learning and Computer-Based Modeling, Northwestern University, Evanston, IL

  • Wooldridge M (2009) An introduction to MultiAgent systems. Wiley, 2002, ISBN 0-471-49691-X.

  • Ximing C, McKinney DC, Lasdon LS (2002) A framework for sustainability analysis in water resources management and application to the Syr Darya Basin, WRR, 38(6)

Download references

Acknowledgments

Work presented in this paper is supported by the Natural Sciences and Engineering Research Council of Canada through the Discovery Grant provided to the second author. Work presented in this paper is also supported by the Ministry of Education and Science, Republic of Serbia, through grant No. TR37018, provided to the third author.

Author information

Authors and Affiliations

  1. Department of Civil and Environmental Engineering, The University of Western Ontario, London, Canada

    Vladimir V. Nikolic & Slobodan P. Simonovic

  2. Faculty of Civil Engineering and Architecture, University of Nis, Nis, Serbia

    Dragan B. Milicevic

Authors
  1. Vladimir V. Nikolic
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Slobodan P. Simonovic
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Dragan B. Milicevic
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Vladimir V. Nikolic.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Nikolic, V.V., Simonovic, S.P. & Milicevic, D.B. Analytical Support for Integrated Water Resources Management: A New Method for Addressing Spatial and Temporal Variability. Water Resour Manage 27, 401–417 (2013). https://doi.org/10.1007/s11269-012-0193-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11269-012-0193-z

Keywords

Search

Navigation