Skip to main content
Log in

Spatial–temporal assessment and redesign of groundwater quality monitoring network: a case study

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

Abstract

Assessment of groundwater quality monitoring networks requires methods to determine the potential efficiency and cost-effectiveness of the current monitoring programs. To this end, the concept of entropy has been considered as a promising method in previous studies since it quantitatively measures the information produced by a network. In this study, the measure of transinformation in the discrete entropy theory and the transinformation–distance (TD) curves, which are used frequently by other researchers, are used to quantify the efficiency of a monitoring network. This paper introduces a new approach to decrease dispersion in results by performing cluster analysis that uses fuzzy equivalence relations. As a result, the sampling (temporal) frequency determination method also recommends the future sampling frequencies for each location based on certain criteria such as direction, magnitude, correlation with neighboring stations, and uncertainty of the concentration trend derived from representative historical concentration data. The proposed methodology is applied to groundwater resources in the Tehran–Karadj aquifer, Tehran, Iran.

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

  • Abrishamchi, A., Owlia, R. R., Tajrishi, M., & Abrishamchi, A. (2008). Optimal design of groundwater quality monitoring using entropy theory. In: Proceedings of the conference on water scarcity, climate change and groundwater management responses, California, U.S.A., 1–5 December 2008.

  • Bueso, M. C., Angulo, J. M., Cruz-Sanjulian, J., & Carcia-Arostegui, J. L. (1999). Optimal spatial sampling design in a multivariate framework. Mathematical Geology, 31(5), 507–525.

    Article  Google Scholar 

  • Dhar, A., & Datta, B. (2007). Multiobjective design of dynamic monitoring for detection of groundwater pollution. Journal of Water Resources Management, 133(4), 329–338.

    Article  Google Scholar 

  • Granato, G. E., & Smith, K. P. (1999). Robowell: An automated process for monitoring ground water quality using established sampling protocols. Ground Water Monitoring and Remediation, 19(4), 81–89.

    Article  CAS  Google Scholar 

  • Harmancioglu, N. B., Fistikoglu, O., Ozkul, S. D., Singh, V. P., & Alpaslan, N. (1999). Water quality monitoring network design (290 pp.). Boston, MA: Kluwer.

    Google Scholar 

  • Husain, T. (1989). Hydrologic uncertainty measure and network design. Water Resources Bulletin, 25(3), 527–534.

    Google Scholar 

  • Jager, H. I., Sale, M. J., & Schmayer, R. L. (1990). Cokriging to assess regional stream quality in the Southern Blue Ridge Province. Water Resources Research, 26(7), 1401–1412.

    Article  CAS  Google Scholar 

  • Karamouz, M., Khajehzadeh Nokhandan, A., Kerachian, R., & Maksimovic, C. (2008). Design of on-line river water quality monitoring systems using the entropy theory: A case study. Environmental Monitoring and Assessment, 155(1–4), 63–81.

    Google Scholar 

  • Khan, F. I., & Husain, T. (2004). An overview and analysis of site remediation technologies. Journal of Environmental Management, 71, 95–122.

    Article  Google Scholar 

  • Koorehpazan Dezfuli, A. (2005). Fuzzy set theory and its application in the modeling of water engineering problems (pp. 32–73). Tehran, Iran: Jahad Daneshgahi Publication (in Persian).

    Google Scholar 

  • Ling, M., Rifai, H. S., Newell, C. J., Aziz, J. J., & Gonzales, J. R. (2003). Groundwater monitoring plans at small scale sites—An innovative spatial and temporal methodology. Journal of Environmental Monitoring and Assessment, 5, 126–134.

    CAS  Google Scholar 

  • Loaiciga, H. A., Charbeneau, R. J., Everett, L. G., Fogg, G. E., Hobbs, B. F., & Rouhani, S. (1992). Review of ground-water quality monitoring network design. Journal of Hydraulic Engineering, 118(1), 11–37.

    Article  Google Scholar 

  • Mahar, P. S., & Datta, B. (1997). Optimal monitoring and groundwater pollution source identification. Journal of Water Resources Planning and Management, 123(4), 199–207.

    Article  Google Scholar 

  • Masoumi, F., & Kerachian, R. (2007). Optimal groundwater monitoring network design using entropy theory. In: Proceedings of conference on water management, Malaysia, 14–16 May 2007.

  • Masoumi, F., & Kerachian, R. (2008). Optimal redesign of groundwater quality monitoring networks: A case study. Environmental Monitoring and Assessment, 161(1), 247–257.

    Article  Google Scholar 

  • Mogheir, Y. (2003). Assessment and redesign of groundwater quality monitoring networks using the entropy theory—Gaza Strip case study. Ph.D. thesis, Coimbra University, Portugal.

  • Mogheir, Y., Lima, J. L. M. P., & Singh, V. P. (2003). Spatial structure assessment of groundwater quality variables based on the entropy theory. Hydrology and Earth System Sciences, 7(5), 707–721.

    Article  CAS  Google Scholar 

  • Mogheir, Y., Lima, J. L. M. P., & Singh, V. P. (2004). Characterizing the spatial variability of groundwater quality using the entropy theory: I. Case study from Gaza Strip. Hydrological Processes, 18, 2165–2179.

    Article  Google Scholar 

  • Mogheir, Y., & Singh, V. P. (2002). Application of information theory to groundwater quality monitoring networks. Water Resources Management, 16(1), 37–49.

    Article  Google Scholar 

  • Motulsky, H. J., & Christopoulos, A. (2008). Fitting models to biological data using linear and nonlinear regression. A practical guide to curve fitting. San Diego, CA: GraphPad Software Inc. http://www.graphpad.com.

    Google Scholar 

  • Owlia, R. R., Hoseini, F., & Abrishamch, A. (2009). New approach for design of groundwater quality monitoring network using entropy theory. In: Proceedings of 7th international conference on water resources conservation and risk reduction under climatic instability, Limassol, Cyprus, 25–27 June 2009.

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

    Article  Google Scholar 

  • Prakash, M. R., & Singh, V. S. (2000). Network design for groundwater monitoring—A case study. Journal of Environmental Geology, 39(6), 628–632.

    Article  CAS  Google Scholar 

  • Reed, P. M. (1997). Cost effectiveness long term groundwater monitoring design using a genetic algorithm and global mass interpolation. M.Sc. thesis, University of Illinois at Urbana-Champaign, U.S.A.

  • Reed, P. M., & Minsker, B. S. (2004). Striking the balance: Long term monitoring design for conflicting objectives. Journal of Water Resources Planning and Management, 130(2), 140–149.

    Article  Google Scholar 

  • Ren, X., & Minsker, B. (2005). Which groundwater remediation objective is better: A realistic one or a simple one? Journal of Water Resources Planning and Management, 131(5), 351–361.

    Article  Google Scholar 

  • Sanders, T. G., Ward, R. C., Loftis, J. C., Steele, T. D., Adrian, D. D., & Yevjevich, V. (1983). Design of networks for monitoring water quality (Vol. 14, pp. 569–576). Littleton, CO: Water Resources Publications.

    Google Scholar 

  • Sarlak, N., & Sorman, A. U. (2006). Evaluation and selection of stream flow network stations using entropy methods. Turkish Journal of Engineering and Environmental Sciences, 30, 91–100.

    Google Scholar 

  • Shannon, C. E. (1948). A mathematical theory of communication. Bell System Technical Journal, 27, 379–423.

    Google Scholar 

  • Singh, V. P. (1997). The use of entropy in hydrology and water resources. Hydrological Processes, 11, 587–626.

    Article  Google Scholar 

  • Singh, V. P. (1998). Entropy-based parameter estimation in hydrology. Boston, MA: Kluwer Academic Publishers.

    Google Scholar 

  • Strobel, R. O., & Robillard, P. D. (2007). Network design for water quality monitoring of surface freshwater: A review. Journal of Environmental Management. doi:10.1016/j.jenvman.

    Google Scholar 

  • Tuckfield, R. C. (1993). Estimation an appropriate sampling frequency for monitoring groundwater well contamination. DOE Contract No. DE-AC09-89SR18035, International Nuclear Materials Management Annual Meeting, Westinghouse Savannah River Company, Savannah River Site, Naples.

  • U.S. EPA (1999). Use of monitored natural attenuation at superfund, rcra corrective action, and underground storage tank site. Directive 9200.4-17P, Final Draft, U.S. Environmental Protection Agency, Office of Solid Waste and Emergency Response, p. 23.

  • Ward, R. C., & Loftis, J. C. (1986). Establishing statistical design criteria for water quality monitoring systems: Review and synthesis. Water Resources Bulletin, 22(5), 759–767.

    Google Scholar 

  • Yang, Y., & Burn, D. (1994). An entropy approach to data collection network design. Journal of Hydrology, 157, 307–324.

    Article  Google Scholar 

  • Zhou, Y. (1995). Sampling frequency for monitoring the actual state of groundwater systems. Journal of Hydrology, 180(1–4), 301–318.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Rashid Reza Owlia.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Owlia, R.R., Abrishamchi, A. & Tajrishy, M. Spatial–temporal assessment and redesign of groundwater quality monitoring network: a case study. Environ Monit Assess 172, 263–273 (2011). https://doi.org/10.1007/s10661-010-1332-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10661-010-1332-8

Keywords

Navigation