Skip to main content
SpringerLink
Log in

Optimal water and waste-load allocations in rivers using a fuzzy transformation technique: a case study

  • Published:
Environmental Monitoring and Assessment Aims and scope Submit manuscript

Abstract

In this paper, a new methodology is developed for integrated allocation of water and waste-loads in river basins utilizing a fuzzy transformation method (FTM). The fuzzy transformation method is used to incorporate the existing uncertainties in model inputs. In the proposed methodology, the FTM, as a simulation model, is utilized in an optimization framework for constructing a fuzzy water and waste-loads allocation model. In addition, economic as well as environmental impacts of water allocation to different water users are considered. For equitable water and waste load allocation, all possible coalition of water users are considered and total benefit of each coalition, which is a fuzzy number, is reallocated to water users who are participating in the coalition. The fuzzy cost savings are reallocated using a fuzzy nucleolus cooperative game and the FTM. As a case study, the Dez River system in south-west of Iran is modeled and analyzed using the methodology developed here. The results show the effectiveness of the methodology in optimal water and waste-loads allocations under uncertainty.

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
Fig. 10
Fig. 11

Similar content being viewed by others

References

  • Aramaki, T., & Matsuo, T. (1998). Evaluation model of policy scenarios for basin-wide water resources and quality management in the tone river, Japan. Water Science and Technology, 38(11), 59–67.

    Article  CAS  Google Scholar 

  • Babel, M. S., Das Gupta, A., & Nayak, D. K. (2005). A model for optimal allocation of water to competing demands. Water Resources Management, 19, 693–712.

    Article  Google Scholar 

  • Burn, D. H., & Lence, B. J. (1992). Comparison of optimization formulations for waste-load allocations. Journal of Environmental Engineering, 118(4), 597–612.

    Article  CAS  Google Scholar 

  • Dezab Consulting Engineers (2001). Restoration of the Karoon-Dez river system, Technical Report.

  • Ghahraman, B., & Sepaskhah, A. R. (1997). Use of water deficit sensitivity index for partial irrigation scheduling of wheat and barley. Irrigation Science, 18, 11–16.

    Article  Google Scholar 

  • Ghosh, S., & Mujumdar, P. P. (2005). A fuzzy waste load allocation model integrating skewness of distributions. In: Proc. National Conference on Advances in Water Engineering for Sustainable Development (NCAWESD-2005), 16–17 May IIT Madras, India, pp 55–61.

  • Ghosh, S., & Mujumdar, P. P. (2006). Risk minimization in water quality control problems of a river system. Advances in Water Resources, 29(3), 458–470.

    Article  CAS  Google Scholar 

  • Ghosh, S., & Mujumdar, P. P. (2010). Fuzzy waste load allocation model: A multiobjective approach. Journal of Hydroinformatics, 12(1), 83–96.

    Article  Google Scholar 

  • Hanss, M. (2002). The transformation method for the simulation and analysis of systems with uncertain parameters. Fuzzy Sets and Systems, 130, 277–289.

    Article  Google Scholar 

  • Javier, P. A., Joaquín, A. A., Miguel, M., & Abel, S. (2010). Water quantity and quality models applied to the Jucar River Basin, Spain. Water Resources Management, 24(1), 2759–2779.

    Article  Google Scholar 

  • Karamouz, M., Zahraie, B., & Kerachian, R. (2003). Development of a master plan for water pollution control using MCDM techniques: A case study. Water International, 28(4), 478–490.

    Article  Google Scholar 

  • Karamouz, M., Tabari, M. M. R., & Kerachian, R. (2007). Application of genetic algorithms and artificial neural networks in conjunctive use of surface and groundwater resources. Water International, 32(1), 163–176.

    Article  Google Scholar 

  • Mahjouri, N., & Ardestani, M. (2010). A game theoretic approach for interbasin water resources allocation considering the water quality issues. Environmental Monitoring and Assessment, 167(1–4), 527–544.

    Article  Google Scholar 

  • Nikoo, M.R., Kerachian, R. & Karimi, A. (2012). A nonlinear interval model for water and waste load allocation in river basins. Water Resources Management, 26(10), 2911–2926.

    Google Scholar 

  • Niksokhan, M. H., Kerachian, R., & Karamouz, M. (2009). A game theoretic approach for trading discharge permits in rivers. Water Science & Technology, 60(3), 793–804.

    Article  Google Scholar 

  • Rehana, S., & Mujumdar, P. P. (2009). An imprecise fuzzy risk approach for water quality management of a river system. Journal of Environmental Management, 90(11), 3653–3664.

    Article  CAS  Google Scholar 

  • Sadegh, M., & Kerachian, R. (2011). Water resources allocation using solution concepts of fuzzy cooperative games: Fuzzy least core and fuzzy weak least core. Water Resources Management, 25(10), 2543–2573.

    Article  Google Scholar 

  • Sadegh, M., Mahjouri, N., & Kerachian, R. (2010). Optimal inter-basin water allocation using crisp and fuzzy Shapley games. Water Resources Management, 24, 2291–2310.

    Article  Google Scholar 

  • Sasikumar, K., & Mujumdar, P. P. (2000). Application of fuzzy probability in water quality management of a river system. International Journal of Systems Science, ASCE, 31(5), 575–592.

    Article  Google Scholar 

  • Singh, A. P., Ghosh, S. K., & Sharma, P. (2007). Water quality management of a stretch of river Yamuna: An interactive fuzzy multi-objective approach. International Journal of Water Resources Management, 21, 515–532.

    Article  Google Scholar 

  • Wang, L., Fang, L., & Hipel, K. W. (2008). Basin-wide cooperative resources allocation. European Journal of Operational Research, 190(3), 798–817.

    Article  Google Scholar 

  • Zadeh, L. A. (1965). Fuzzy sets. Information and Control, 8(3), 338–353.

    Article  Google Scholar 

  • Zhang, W., Wang, Y., Peng, H., Li, Y., Tang, J., & Wu, K. B. (2010). A coupled water quantity–quality model for water allocation analysis. Water Resources Management, 24, 485–511.

    Article  Google Scholar 

Download references

Acknowledgments

The authors would like to acknowledge the financial support of the University of Tehran for this research under grant number 8102060/1/02.

Author information

Authors and Affiliations

  1. School of Civil Engineering, College of Engineering, University of Tehran, Tehran, Iran

    Mohammad Reza Nikoo & Ali Asghar Azadnia

  2. School of Civil Engineering and Center of Excellence for Engineering and Management of Civil Infrastructures, College of Engineering, University of Tehran, Tehran, Iran

    Reza Kerachian

  3. Department of Civil Engineering, Islamic Azad University, East-Tehran Branch, Tehran, Iran

    Akbar Karimi

Authors
  1. Mohammad Reza Nikoo
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Reza Kerachian
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Akbar Karimi
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Ali Asghar Azadnia
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Mohammad Reza Nikoo.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Nikoo, M.R., Kerachian, R., Karimi, A. et al. Optimal water and waste-load allocations in rivers using a fuzzy transformation technique: a case study. Environ Monit Assess 185, 2483–2502 (2013). https://doi.org/10.1007/s10661-012-2726-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10661-012-2726-6

Keywords

Search

Navigation