Water and Irrigation Management

Water and Irrigation Management

Using two inherent and specific vulnerability approaches to identify potentials for the development of groundwater resources

Document Type : Research Paper

Authors
Fateme Riahi 1
Hasan Vagharfard 2
Peyman Daneshkar Araste 3
Hamid Kardan Moghaddam 4
1 Ph.D. of Watershed Engineering, Factually of Agriculture and Natural Resource, Hormozgan University, Bandarabas, Iran.
2 Associate Professor of Watershed , Factually of Agriculture and Natural Resource, Hormozgan University, Hormozgan, Iran.
3 Associate Professor of Water Engineering , Emam Khomeini of Ghazvin International University, Ghazvin, Iran.
4 Assistant Professor, Water Research Institute Tehran, Iran.
10.22059/jwim.2022.326696.900
Abstract
One of the appropriate tools to understand the state of development in groundwater resources is to use the concept of vulnerability of groundwater resources. From a theoretical point of view, the concept of aquifer vulnerability is based on two types of special vulnerability and intrinsic vulnerability, which is defined based on hydrogeological characteristics and aquifer pollution. In this study, to assess the vulnerability of Sarkhoon aquifer in Hormozgan province, the Drastic vulnerability index was used to assess the inherent vulnerability and the GQI quality index was used to assess the specific vulnerability of the aquifer. The results of aquifer vulnerability classification showed that the intrinsic vulnerability index in the southern part of the aquifer has a high vulnerability and most of the aquifer range is in the medium vulnerability class. On the other hand, based on quality parameters in wells in the region, GQI index was measured and analyzed. The weighting of this index showed that the TDS parameter is the most important in groundwater resources. Qualitative zoning at the level of the Sarkhon aquifer indicates a decrease in the index and another expression is an increase in the concentration of solutes in the central parts and the outlet of the aquifer. Finally, by normalizing the two indicators of intrinsic aquifer vulnerability and special vulnerability, the Sarkhon aquifer vulnerability index was evaluated and calculated. Vulnerability index estimation showed that the level of vulnerability has increased in the aquifer outlet and this is also consistent with groundwater flow. In order to evaluate the accuracy of the total vulnerability index, the correlation of this index with nitrate concentration was used, which the results indicate a statistical accuracy of 72%.
Keywords
GQI index
Intrinsic vulnerability
Specific vulnerability
TDS
Subjects
  1. Aller, L. (1985). DRASTIC: a standardized system for evaluating ground water pollution potential using hydrogeologic settings. Robert S. Kerr Environmental Research Laboratory, Office of Research and Development, US Environmental Protection Agency.
  2. Arya, S., Subramani, T., Vennila, G., & Roy, P.D. (2020). Groundwater vulnerability to pollution in the semi-arid Vattamalaikarai River Basin of south India thorough DRASTIC index evaluation. Geochemistry, 80(4),125635.
  3. Babiker, I.S., Mohamed, M.A., & Hiyama, T. (2007). Assessing groundwater quality using GIS. Water Resources Management, 21(4), 699-715.
  4. Bordbar, M., Neshat, A., & Javadi, S. (2019). A new hybrid framework for optimization and modification of groundwater vulnerability in coastal aquifer. Environmental Science and Pollution Research, 26(21), 21808-21827.
  5. Javadi, s., Hashemi, M., & Sokhtezari, M. (2018). Analysis of multiple parameters pollution map based on land use map and using K-mean clustering technique in Qazvin aquifer. Iranian journal of Ecohydrology, 5(1), 293-305. [In Persian].
  6. Javadi, S., & Kardan moghaddam, H. (2019). Utilizing 3-D Simulation of saltwater intrusion in desert aquifer by SEAWAT model. Water and Irrigation Management, 9(1), 129-142. [In Persian].
  7. Javadi, S., Kavehkar, N., Mousavizadeh, M.H., & Mohammadi, K. (2011). Modification of DRASTIC model to map groundwater vulnerability to pollution using nitrate measurements in agricultural areas.
  8. Javadi, S., Hashemy, S.M., Mohammadi, K., Howard, K.W.F., & Neshat, A. (2017). Classification of aquifer vulnerability using K-means cluster analysis. Journal of Hydrology, 549, 27-37.
  9. Javadi, S., Kardan Moghaddam, H., & Neshat, A. (2018). Evaluation and Simulation of Groundwater Flow in Aquifers Enclosed with Desert Saline Areas (Case Study: Isfahan Province-Ardestan Aquifer), Water Harvesting Research, 3(1), 1-14.
  10. Kardan moghaddam, H., Javadi, S., & Rahimzadeh, Z. (2020). Evaluation of Aquifer Vulnerability Assessment Methods for Alluvial and Coastal Aquifers, Case Study in Astaneh-Koochesfahan Aquifer, Guilan, Iran. Journal of water and irrigation management, 10(2), 203-220 [In Persian].
  11. Kardan Moghaddam, H., Jafari, F., & Javadi, S. (2017). Vulnerability evaluation of a coastal aquifer via GALDIT model and comparison with DRASTIC index using quality parameters. Hydrological Sciences Journal, 62(1), 137-146.
  12. Kardan moghaddam, H., & Roozbahani, A. (2016). Evaluation of Bayesian networks model in monthly groundwater level prediction (Case study: Birjand aquifer). Journal of water and irrigation management. 5(2): 139-151[In Persian].
  13. Ministry of Power. (2015). Report of Reduction program and balance groundwater in sarkhoon aquifer. (In Persian)
  14. Moghaddam, H.K., Kivi, Z.R., Bahreinimotlagh, M., & Moghddam, H.K. (2020). Evaluation of the groundwater resources vulnerability index using nitrate concentration prediction approach. Geocarto International (just-accepted), 1-15.
  15. Saadati, H., Malekian, A., & Moghaddamnia, A. (2020). Assessment of Vulnerability Index and Risk Zoning in Ardabil Plain. Water and Irrigation Management, 10(1), 157-171. [In Persian].
  16. Singha, S., Devatha, C.P., Singha, S., & Verma, M.K. (2015). Assessing ground water quality using GIS. International Journal of Engineering Research & Technology, 4(11), 11.
  17. Torkashvand, M., Neshat, A., Javadi, S., & Yousefi, H. (2021). DRASTIC framework improvement using stepwise weight assessment ratio analysis (SWARA) and combination of genetic algorithm and entropy. Environmental Science and Pollution Research, 28(34), 46704-46724.
  18. Wang, B., Teng, Y., Wang, H., Zuo, R., Zhai, Y., Yue, W., & Yang, J. (2020). Entropy weight method coupled with an improved DRASTIC model to evaluate the special vulnerability of groundwater in Songnen Plain, Northeastern China. Hydrology Research, 51(5), 1184-1200.
Water and Irrigation Management
Volume 11, Issue 4
Winter 2022
Pages 739-751