Skip to main content

Advertisement

Log in

Revising river water quality monitoring networks using discrete entropy theory: the Jajrood River experience

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

Abstract

This paper aims at evaluating and revising the spatial and temporal sampling frequencies of the water quality monitoring system of the Jajrood River in the Northern part of Tehran, Iran. This important river system supplies 23% of domestic water demand of the Tehran metropolitan area with population of more than 10 million people. In the proposed methodology, by developing a model for calculating a discrete version of pair-wise spatial information transfer indices (SITIs) for each pair of potential monitoring stations, the pair-wise SITI matrices for all water quality variables are formed. Also, using a similar model, the discrete temporal information transfer indices (TITIs) using the data of the existing monitoring stations are calculated. Then, the curves of the pair-wise SITI versus distance between monitoring stations and TITI versus time lags for all water quality variables are derived. Then, using a group pair-wise comparison matrix, the relative weights of the water quality variables are calculated. In this paper, a micro-genetic-algorithm-based optimization model with the objective of minimizing a weighted average spatial and temporal ITI is developed and for a pre-defined total number of stations, the best combination of monitoring stations is selected. The results show that the existing monitoring system of the Jajrood River should be partially strengthened and in some cases the sampling frequencies should be increased. Based on the results, the proposed approach can be used as an effective tool for evaluating, revising, or redesigning the existing river water quality monitoring systems.

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.

Similar content being viewed by others

References

  • Harmancioglu, N. B. (1981). Measuring the information content of hydrological processes by the entropy concept, Centennial of Ataturk’s Birth. Journal of the Civil Engineering, Faculty of Ege University, 1, 13–88.

    Google Scholar 

  • Harmancioglu, N. B., & Alpaslan, N. (1992). Water quality monitoring network design: A problem of multi-objective decision making. Water resources bulletin, 28(1), 179–192.

    CAS  Google Scholar 

  • Harmancioglu, N. B., & Baran, T. (1989). Effects of recharge systems on hydrologic information transfer along rivers. Proceedings of the Third Scientific Assembly—New Directions for Surface Water Modelling, IAHS Publications, 181, 223–233.

    Google Scholar 

  • Harmancioglu, N. B., & Yevjevich, V. (1987). Transfer of hydrologic information among river points. Journal of Hydrology, 91, 103–118.

    Article  Google Scholar 

  • Harmancioglu, N. B., Fistikoglu, O., Ozkul, S. D., Singh, V. P., & Alpaslan, N. (1999). Water quality monitoring network design. Boston: Kluwer, 299 pp.

    Google Scholar 

  • Karamouz, M., Kerachian, R., Zahraie, B., & Araghi-Nejhad, S. (2002). Monitoring and evaluation scheme using the multiple-criteria-decision-making technique: Application to irrigation projects. Journal of Irrigation and Drainage Engineering, ASCE, 128(6), 341–350.

    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, IWRA, 28(4), 478–490.

    Article  Google Scholar 

  • Karamouz, M., Zahraie, B., Kerachian, R., Jaafarzadeh, N., & Mahjouri, N. (2007). Developing a master plan for hospital solid waste management: A case study. Waste Management, Elsevier, 27(5), 626–638.

    Google Scholar 

  • Karamouz, M., Nokhandan, A. K., Kerachian, R., & Maksimovic, C. (2009). Design of on-line river water quality monitoring systems using the entropy theory: a case study. Environmental Monitoring and Assessment, Springer, 155(1–4), 63–81. doi:10.1007/s10661-008-0418-z.

    Article  CAS  Google Scholar 

  • Masoumi, F., & Kerachian, R. (2008). Assessment of the groundwater salinity monitoring network of the Tehran region: Application of the discrete entropy theory. Water Science and Technology, IWA, 58(4), 765–771. doi:10.2166/wst.2008.674.

    Article  CAS  Google Scholar 

  • Masoumi, F., & Kerachian, R. (2010). Optimal redesign of groundwater quality monitoring networks: A case study. Environmental Monitoring and Assessment, Springer, 161(1–4), 247–257. doi:10.1007/s10661-008-0742-3.

    Article  Google Scholar 

  • Mogheir, Y., & Singh, V. P. (2002). Application of information theory to groundwater quality monitoring networks. Journal of Water Resources Management, 16, 37–49.

    Article  Google Scholar 

  • Mogheir, Y., de Lima, J. L. M. P., & Singh, V. P. (2004a). Characterizing the spatial variability of groundwater quality using the entropy theory: I. Synthetic data. Journal of Hydrolgical Process, 18, 2165–2179.

    Article  Google Scholar 

  • Mogheir, Y., de Lima, J. L. M. P., & Singh, V. P. (2004b). Characterizing the spatial variability of groundwater quality using the entropy theory: II. Case study from Gaza Strip. Journal of Hydrolgical Process, 18, 2579–2590.

    Article  Google Scholar 

  • Mogheir, Y., de Lima, J. L. M. P., & Singh, V. P. (2005). Assessment of informativeness of groundwater monitoring in developing regions (Gaza Strip Case Study). Journal of Water Resources Management, 19, 737–757.

    Article  Google Scholar 

  • Ozkul, S., Harmancioglu, N. B., & Singh, V. P. (2000). Entropy-based assessment of water quality monitoring networks. Journal of hydrologic engineering, 5(1), 90–100.

    Article  Google Scholar 

  • Saaty, T. L. (1980). The analytical hierarchy process, planning, priority, resource allocation. USA: RWS.

    Google Scholar 

  • Saaty, T. L. (1994). Highlights and critical points in the theory and application of the analytical hierarchy process. European Journal of Operation Research, 74, 426–447.

    Article  Google Scholar 

  • Shannon, C. E., & Weaver, W. (1949). The mathematical theory of communication. Illinois: The University of Illinois Press.

    Google Scholar 

  • Uslu, O., & Tanriover, A. (1979). Measuring the information content of hydrological process. Proceedings of the First National Congress on Hydrology, Istanbul, 437–443.

  • Water and Energy Research Center (1380). Pollution source identification and control in upstream of the Latyan dam. Technical Report, Sharif University of Technology.

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Reza Kerachian.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Mahjouri, N., Kerachian, R. Revising river water quality monitoring networks using discrete entropy theory: the Jajrood River experience. Environ Monit Assess 175, 291–302 (2011). https://doi.org/10.1007/s10661-010-1512-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10661-010-1512-6

Keywords

Navigation