Advertisement

Application of GIS and Modified DRASTIC Model Based on Entropy Weight and Fuzzy Theory to Ground Water Vulnerability Evaluation

  • Shaofei LiEmail author
  • Guanyou Li
Conference paper
Part of the IFIP Advances in Information and Communication Technology book series (IFIPAICT, volume 509)

Abstract

Groundwater vulnerability assessment coupling with geographic information systems (GIS) should be considered as an important means for groundwater management, especially in agricultural areas. Nowadays, for groundwater vulnerability evaluating, DRASTIC model has been very popular and widely used in the world. However, DRASTIC model has some disadvantage. To overcome the problem, this paper proposed a modified DRASTIC model based on entropy theory and fuzzy theory. Moreover,three additional parameters, were added to the modified DRASTIC model, which were wastewater discharge of unit area, fertilizer usage of unit area, and density of river network. Using ArcGIS10.2 and the modified model, groundwater vulnerability grade (GVG) in Tianjin plain was analyzed and calculated. Groundwater vulnerability map of the plain area in Tianjin was constructed. According to the results, the study area was divided into five level zones: low vulnerability zone, lower vulnerability zone, medium vulnerability zone, higher vulnerability zone and high vulnerability zone, with coverage area of 17.1%, 26.7%, 25.2%, 22% and 9%, respectively. The results are consistent with the actual situation of studied area.

Keywords

Groundwater vulnerability GIS Modified DRASTIC model Entropy weight Fuzzy theory 

Notes

Acknowledgment

This research was funded by the Key project of Tianjin Municipal Natural Science Foundation (Grant No. 15JCZDJC41400), National Water Pollution Control and Treatment Key Specialized Project (Grant No. 2017ZX07106003)

References

  1. Dixon, B.: Prediction of groundwater vulnerability using an integrated GIS-based neuro-fuzzy techniques. J. Hydrol. 4(309), 17–38 (2004)Google Scholar
  2. Dixon, B.: Groundwater vulnerability mapping: a GIS and fuzzy rule based integrated tool. Appl. Geogr. 25(4), 327–347 (2005)CrossRefGoogle Scholar
  3. Foster, S.S.: Fundamental concepts in aquifer vulnerability, pollution risk and protection strategy. In: Van Duijvenbooden, W., Van Waegeningh, H.G. (eds.) TNO Committee on Hydrological Research, The Hague Vulnerability of Soil and Groundwater to Pollutants, Proceedings and Information, vol. 38, pp. 69–86 (1987)Google Scholar
  4. Daly, D., Drew, D.: Irish methodologies for karst aquifer protection. In: Beek, B. (ed.) Hydrogeology and Engineering Geology of Sinkholes and Karst, pp. 267–327. Balkema, Rotterdam (1999)Google Scholar
  5. Van Stemproot, D., Evert, L., Wassenaar, L.: Aquifer vulnerability index: a GIS compatible method for groundwater vulnerability mapping. Can Water Resour. J. 18, 25–37 (1993)CrossRefGoogle Scholar
  6. Aller, L., Bennet, T., Lehr, J.H., Petty, R.J., et al.: DRASTIC: a standardized system for evaluating groundwater pollution potential using hydrogeological settings. US Environmental Protection Agency, Ada. 1987, EPA/600/2–87/035 (1987)Google Scholar
  7. Fritch, T.G., McKnight, C.L., Yelderman, J.C., et al.: An aquifer vulnerability assessment of the Paluxy aquifer, Central Texas, USA, using GIS and a modified DRASTIC approach. Environ. Manag. 25, 337–345 (2000)CrossRefGoogle Scholar
  8. Plymale, C.L., Angle, M.P.: Groundwater pollution potential of Fulton County, Ohio. Ohio Department of Natural Resources Division of Water, Water Resources Section. Groundwater Pollution Potential, Report No 45 (2002)Google Scholar
  9. Shukla, S., Mostaghimi, S., Shanholt, V.O., et al.: A county-level assessment of ground water contamination by pesticides. Groundwater Monit. Remediat. 20(1), 104–119 (2000)CrossRefGoogle Scholar
  10. Naqa, A., Hammouri, N., Kuisi, M.: GIS-based evaluation of groundwater vulnerability in the Russeifa area, Jordan. Revista Mexicana de Ciencias Geologicas 23(3), 277–287 (2006)Google Scholar
  11. Yin, L., Zhang, E., Wang, X., Wenninger, J., et al.: A GIS-based DRASTIC model for assessing groundwater vulnerability in the Ordos Plateau. China. Environ. Earth Sci. 69(1), 171–185 (2012)CrossRefGoogle Scholar
  12. Chenini, I., Mammou, A.B.: Groundwater recharge study in arid region: an approach using GIS techniques and numerical modeling. Comput. Geosci. 36(6), 801–817 (2010)CrossRefGoogle Scholar
  13. Carrera-Hernández, J.J., Gaskin, S.J.: The groundwater modeling tool for GRASS (GMTG): open source ground water flow modeling. Comput. Geosci. 32(3), 339–351 (2006)CrossRefGoogle Scholar
  14. Jha, M.K., Chowdhury, A., Chowdary, V.M., et al.: Groundwater management and development by integrated remote sensing and geographic information systems: prospects and constraints. Water Resour. Manag. 21, 427–467 (2007)CrossRefGoogle Scholar
  15. Halliday, S.L., Wolfe, M.L.: Assessing groundwater pollution potential from nitrogen fertilizer using a GIS. Water Resour. Bull. AWRA 27(2), 237–245 (1991)CrossRefGoogle Scholar
  16. Ho, W.: Integrated analytic hierarchy process and its applications—a literature review. Eur. J. Oper. Res. 186, 211–228 (2008)MathSciNetCrossRefGoogle Scholar
  17. Kahraman, C., Cebeci, U., Ulukan, Z.: Multi-criteria supplier selection using fuzzy AHP. Logis Inf. Manag. 16(6), 382–394 (2003)CrossRefGoogle Scholar
  18. Sener, E., Sener, S.: Evaluation of groundwater vulnerability to pollution using fuzzy analytic hierarchy process method. Environ. Earth Sci. 73, 8405–8424 (2015)CrossRefGoogle Scholar

Copyright information

© IFIP International Federation for Information Processing 2019

Authors and Affiliations

  1. 1.College of Hydraulic EngineeringTianjin Agricultural UniversityTianjinChina

Personalised recommendations