Skip to main content

Advertisement

Log in

Impact assessment of industrial wastewater discharge in a river basin using interval-valued fuzzy group decision-making and spatial approach

  • Published:
Environment, Development and Sustainability Aims and scope Submit manuscript

Abstract

Sustainable and integrated river basin planning and management is a complex process involving uncertain data at different stages of decision-making process. Moreover, there are multiple decision makers at different institutions with contrasting interests and objectives, and thus, a collaborative decision making is required to resolve the conflicts. Although the formulation or modeling of such problems under fuzzy framework provides a very strong ground to deal with the uncertain and complex judgments, there is scope to model the problem more accurately. The present study develops a novel approach of dealing with uncertainty associated with group decision making in a river basin, by extending fuzzy Delphi process using interval-valued fuzzy sets. A case study of assessing the impact of industrial wastewaters on the Ganges River basin, India, has also been presented to demonstrate the effectiveness of the proposed methodology. A total of 33 industrial units, mainly paper pulp, tanneries and textiles, discharging massive quantities of wastewater in the Ganges River basin have been chosen for the analysis. These industries are rated by the expert decision makers to represent their objective judgments (and/or subjective preferences) on the basis of ten essential sets of criteria such as impact on river, impact on groundwater, critical pollutants level, impact on public health. The ratings are analyzed and aggregated using modified fuzzy decision-making approach, and industries are ranked accordingly. To enhance the decision-making process, the results are also represented spatially under GIS environment. Analysis of results clearly demonstrates the contribution of crucial indicators/criteria in ensuring the sustainable use of water resources with respect to environmental, social and economic dimensions. The results obtained are compared and validated with the recent research works and reports of pollution control boards. The study recommends several policy implementations, primarily revisal in prescribed effluent discharge standards of the industries. The model developed herein can be an efficient and productive tool for complex group decisions in water resources planning by facilitating participation and knowledge sharing among the experts.

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

Access this article

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

  • Afshar, A., Mariño, M. A., & Saadatpour, M. (2011). Fuzzy TOPSIS multi-criteria decision analysis applied to Karun reservoirs system. Water Resource Management, 25(2), 545–563.

    Article  Google Scholar 

  • Asl Rousta, B., & Araghinejad, S. (2015). Development of a multi criteria decision making tool for a water resources decision support system. Water Resource Management, 29(15), 5713–5727.

    Article  Google Scholar 

  • Azarnivand, A., Hashemi-Madani, F. S., & Banihabib, M. E. (2015). Extended fuzzy analytic hierarchy process approach in water and environmental management (case study: Lake Urmia Basin, Iran). Environmental Earth Sciences, 73, 13–26.

    Article  Google Scholar 

  • Boroushaki, S., & Malczewski, J. (2010). Using the fuzzy majority approach for GIS-based multicriteria group decision-making. Computers & Geosciences, 36(3), 302–312.

    Article  Google Scholar 

  • Chaudhary, M., Mishra, S., & Kumar, A. (2017). Estimation of water pollution and probability of health risk due to imbalanced nutrients in River Ganga, India. International Journal of River Basin Management, 15(1), 53–60.

    Article  Google Scholar 

  • Chen, S. M., & Lee, L. W. (2010). A fuzzy multiple attributes group decision-making based on the interval type-2 TOPSIS method. Expert Systems with Applications, 37, 2790–2798.

    Article  Google Scholar 

  • CPCB. (2013). Pollution assessment: River Ganga. New Delhi: Central Pollution Control Board (CPCB).

    Google Scholar 

  • CWC. (2014). Status of trace and toxic metals in Indian rivers. New Delhi: Central Water Commission (CWC).

    Google Scholar 

  • Dalkey, N., & Helmer, O. (1963). An experimental application of the Delphi method to the use of experts. Management Science, 9(3), 458–467.

    Article  Google Scholar 

  • Dixon, B. (2005). Applicability of neuro-fuzzy techniques in predicting ground-water vulnerability: a GIS-based sensitivity analysis. Journal of Hydrology, 309, 17–38.

    Article  Google Scholar 

  • Gorzalczany, M. B. (1987). A method of inference in approximate reasoning based on interval-valued fuzzy sets. Fuzzy Sets and Systems, 21(1), 1–17.

    Article  Google Scholar 

  • Karamouz, M., Zahraie, B., & Kerachian, R. (2009). Development of a master plan for water pollution control using MCDM techniques: A case study. Water International, 28(4), 478–490.

    Article  Google Scholar 

  • Kyem, P. A. K. (2004). On intractable conflicts participatory GIS applications: The search for consensus amidst competing claims and institutional demands. Annals of the Association of American Geographers, 94(1), 37–57.

    Article  Google Scholar 

  • Loucks, D. P. (2000). Achieving a concensus in the restoration of the Everglades: A challenge for shared vision modelers. In Proceedings of 27th annual water resource planning and management conference. ASCE, Reston, VA.

  • Minatour, Y., Bonakdari, H., Zarghami, M., & Ali, B. M. (2015). Water supply management using an extended group fuzzy decision-making method: A case study in North-Eastern Iran. Applied Water Science, 5(3), 291–304.

    Article  Google Scholar 

  • Pasi, G., & Yager, R. R. (2006). Modeling the concept of majority opinion in group decision-making. Information Sciences, 176, 390–414.

    Article  Google Scholar 

  • Paul, D. (2017). Research on heavy metal pollution of river Ganga: A review. Annals of Agrarian Science, 15(2), 278–286.

    Article  Google Scholar 

  • Rather, J. A., & Andrabi, Z. A. B. R. (2012). Fuzzy logic based GIS modeling for identification of ground water potential zones in the Jhagrabaria Watershed of Allahabad District, Uttar Pradesh, India. International Journal of Advances in Remote Sensing and GIS, 1(2), 218–233.

    Google Scholar 

  • Razavi Toosi, S. L., & Samani, J. M. V. (2012). Evaluating water transfer projects using analytic network process (ANP). Water Resource Management, 26(7), 1999–2014.

    Article  Google Scholar 

  • Saaty, T. L. (1980). The analytic hierarchy process. New York: McGraw-Hill.

    Google Scholar 

  • Saaty, T. L. (2001). How to make a decision? In T. L. Saaty & L. G. Vargas (Eds.), Models, methods, concepts and applications of the analytic hierarchy process (pp. 1–25). New Mexico: Springer.

    Chapter  Google Scholar 

  • Singh, A. P. (2008). An integrated fuzzy approach to assess water resources’ potential in a watershed. Journal of Computational Mathematics, 1(1), 7–23.

    Google Scholar 

  • Singh, A. P., & Ghosh, S. K. (2003). Uncertainty analysis in river basin water quality management. In K. Srinivasa Raju, A. K. Sarkar, & M. L. Dash (Eds.), Integrated water resources planning and management (pp. 260–268). New Delhi: Jain Brothers.

    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. Water Resources Management, 21(2), 515–532.

    Article  Google Scholar 

  • Singh, A. P., Srinivas, R., Kumar, S., & Chakrabarti, S. (2015). Water quality assessment of a river basin under fuzzy multi-criteria framework. International Journal of Water, 9(3), 226–247.

    Article  Google Scholar 

  • Sinha, S., Agarwal, N., Pandey, S., & Grover, V. (2016). Impact of tanneries on ground water contamination in Unnao district. Green Chemistry & Technology Letters, 2(2), 110–114.

    Google Scholar 

  • Srinivas, R., Bhakar, P., & Singh, A. P. (2015). Groundwater quality assessment in some selected area of Rajasthan, India using fuzzy multi-criteria decision making tool. Elsevier Aquatic Procedia, 4, 1023–1030.

    Article  Google Scholar 

  • Viessman, W. Jr., & Smerdon, E. T. (1990). Managing water-related conflicts: The engineer’s role. In Proceedings of engineering foundation conference. ASCE, New York.

  • UPJN, UPPCB, & CPCB. (2017). Assessment of pollution of drains carrying sewage/industrial effluent joining River Ganga and its tributaries. A joint report by Uttar Pradesh Jal Nigam (UPJN), Uttar Pradesh Pollution Control Board (UPPCB), Lucknow and Central Pollution Control Board (CPCB) New Delhi, India.

  • UPPCB. (2013). Pollution caused by leather tanning industry to the water bodies/ground water in Unnao District of Uttar Pradesh. Uttar Pradesh Pollution Control Board (UPPCB), Lucknow.

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

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Ajit Pratap Singh.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Srinivas, R., Singh, A.P. Impact assessment of industrial wastewater discharge in a river basin using interval-valued fuzzy group decision-making and spatial approach. Environ Dev Sustain 20, 2373–2397 (2018). https://doi.org/10.1007/s10668-017-9994-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10668-017-9994-9

Keywords

Navigation