Potential Detection of Groundwater Resources of Sero Plain: Applications of Shannon’s Entropy and Frequency Ratio (FR) Models

Document Type : Research Paper


1 Ph. D. Candidate, Water Engineering, Department of Civil Engineering, Roudehen Branch, Islamic Azad University, Roudehen, Iran.

2 Assistant Professor, Department of civil Engineering, Roudehen Branch, Islamic Azad University, Roudehen, Iran.

3 Professor of Faculty of Civil Engineering, University of Tabriz, Tabriz, Iran .


Groundwater plays an important role in the sustainable development of human societies. The rapid growth of population, low level effectiveness, and performance of irrigation in agriculture sector have led to increase in demand for water resources in Iran. Therefore, the regional management of water extraction and the optimal usage of available water resources are highly important. Considering the urgent and intense need for groundwater resources, we used Shannon’s entropy and frequency ratio models to identify the groundwater resources of Sero Plain for agricultural and drinking purposes as well as to detect the factors that affect occurrence of groundwater and zoning.


Main Subjects

1-    Arkoprovo, B. , Adarsa, J. and Prakash, S. S. , 2012. Delineation of groundwater potential zones using satellite remote sensing and geographic information system techniques: a case study from Ganjam district, Orissa, India.  Research Journal of Recent Sciences2277, pp. 2502.
2-    Balamurugan, P., Selvaganapathi, R., Vasudevan, S., Nishikanth, C. V., Gnanachandrasamy, G., & Sathiyamoorthy, G. (2017). Evaluation of groundwater quality and water quality index in the Palacode and Pennagaram Taluks, Dharmapuri district, Tamil Nadu, India. Int J Appl Res, 3(6), 285-290.
3-    Chandhary, B. , Kumar, B. , Saroha, K. , Yadar, G. , Singh, M. , Sharma., A. Pandey, M. and Singh, P. , 2001. Integrated ground water resources mapping in Gurgaon district, (Haryana) India using remote sensing and GIS techniques. Retrieved From Using False Color Composites From Indian Remote Sensing Satellite (IRS-1C), pp. 351-356.
4-    Chung, C.J.F. and Fabbri, A.G., 2003. Validation of spatial prediction models for landslide hazard mapping.  Natural Hazards, 30(3), pp. 451-472.
5-    Damavand, A. A. , Rezaei, F. and Panahi, M. , 2012. Potential detection of groundwater resources using remote sensing and geographic information system, Case study: Seleh-Bon basin.In 2nd Congress of Earth Sciences, Ashtian, pp. 1-9 (In Persian).
6-    Ganapuram, S. , Kumar, G. V. , Krishna, I. M. , Kahya, E. and Demirel, M. C. , 2009. Mapping of groundwater potential zones in the Musi basin using remote sensing data and GIS.  Advances in Engineering Software, 40(7), pp. 506-518.
7-    Hosseini, F. and Tabatabei, S. H. , 2014. Potential detection of new groundwater resources using calculation Pattern and fuzzy logic. In 5th Conferenece on Management of Water Resources of Iran, Iranian Water Resources Association, Shahid Behehsti University.
8-    Khosravi, K. , Pham, B. T. , Chapi, K. , Shirzadi, A. , Shahabi, H. , Revhaug, I. , Prakash, I. and Bui, D. T. , 2018. A comparative assessment of decision trees algorithms for flash flood susceptibility modeling at Haraz watershed, northern Iran.  Science of The Total Environment627, pp. 744-755. (In Persian).
9-    Lee, S. and Pradhan, B. , 2007. Landslide hazard mapping at Selangor, Malaysia using frequency ratio and logistic regression models.  Landslides, 4(1), pp. 33-41.
10- Manap, M. A. , Nampak, H. , Pradhan, B. , Lee, S. , Sulaiman, W. N. A. and Ramli, M. F. , 2014. Application of probabilistic-based frequency ratio model in groundwater potential mapping using remote sensing data and GIS.  Arabian Journal of Geosciences, 7(2), pp. 711-724.
11- Massey ,A. Nancy, A. 1988. The dimensions of residential segregation. Social Forces, Vol. 67, No. 2, pp. 281-315
12- Moghaddam, D. D. , Rezaei, M. , Pourghasemi, H. R. , Pourtaghie, Z. S. and Pradhan, B. , 2015. Groundwater spring potential mapping using bivariate statistical model and GIS in the Taleghan watershed, Iran.  Arabian Journal of Geosciences, 8(2), pp. 913-929.
13- Mohammady, M. , Pourghasemi, H. R. and Pradhan, B. , 2012. Landslide susceptibility mapping at Golestan Province, Iran: a comparison between frequency ratio, Dempster–Shafer, and weights-of-evidence models.  Journal of Asian Earth Sciences, 61, pp. 221-236.
14- Nampak, H. , Pradhan, B. and Manap, M. A. , 2014. Application of GIS based data driven evidential belief function model to predict groundwater potential zonation.  Journal of Hydrology, 513, pp. 283-300.
15- Oh, H. J. , Kim, Y. S. , Choi, J. K. , Park, E. and Lee, S. , 2011. GIS mapping of regional probabilistic groundwater potential in the area of Pohang City, Korea.  Journal of Hydrology, 399(3-4), pp. 158-172.
16- Park, I. , Kim, Y. and Lee, S. , 2014. Groundwater productivity potential mapping using evidential belief function.  Groundwater, 52(S1), pp. 201-207.
17- Pourghasemi, H. R. and Beheshtirad, M. , 2015. Assessment of a data-driven evidential belief function model and GIS for groundwater potential mapping in the Koohrang Watershed, Iran.  Geocarto International, 30(6), pp. 662-685.
18- Pourghasemi, H. R. , Pradhan, B. , Gokceoglu, C. , Mohammadi, M. and Moradi, H. R. , 2013. Application of weights-of-evidence and certainty factor models and their comparison in landslide susceptibility mapping at Haraz watershed, Iran.  Arabian Journal of Geosciences, 6(7), pp. 2351-2365.
19- Pradhan, B. , 2009. Groundwater potential zonation for basaltic watersheds using satellite remote sensing data and GIS techniques.  Open Geosciences, 1(1), pp. 120-129.
20- Pradhan, B., Leeb, L., Manfred, F., Buchroithnera., 2010. A GIS-based back-propagation neural network model and its cross-applicationand validation for landslide susceptibility analyses, Computers, Environment and Urban Systems, 34(3), pp. 216-235
21- Prasanth, S. S. , Magesh, N. S. , Jitheshlal, K. V. , Chandrasekar, N. and Gangadhar, K. , 2012. Evaluation of groundwater quality and its suitability for drinking and agricultural use in the coastal stretch of Alappuzha District, Kerala, India.  Applied Water Science, 2(3), pp. 165-175.
22- Purguyumi, H. , Mahmudi, F. Y. and Ghasemi, A. , 2012. Application of remote sensing and geographic information system for groundwater exploration. In 7th National Conference on Watershed Science and Engineering, Isfahan, Iran, pp. 1-8 (In Persian).
23- Shankar, M. R. and Mohan, G. , 2006. Assessment of the groundwater potential and quality in Bhatsa and Kalu river basins of Thane district, western Deccan Volcanic Province of India.  Environmental Geology, 49(7), pp. 990-998.
24- Singh, A. K., & Prakash, S. R. 2002. An integrated approach of remote sensing, geophysics and GIS to evaluation of groundwater potentiality of Ojhala sub-watershed, Mirjapur district, UP, India. In Asian conference on GIS, GPS, aerial photography and remote sensing, Bangkok-Thailand.
25- Theil, H., 1972. Statistical decomposition analysis. Amsterdam: NorthHolland Publishing Company.
26- Yang, A.L., Huang, G.H.,  & Qin, X.S., 2010, An Integrated Simulation-Assessment Approach for Evaluating Health Risks of Groundwater Contamination Under Multiple Uncertainties, Water Resources Management, vol 24, pp. 3349–3369.
Volume 43, Issue 2
July 2020
Pages 123-137
  • Receive Date: 21 June 2018
  • Revise Date: 30 October 2018
  • Accept Date: 02 November 2018
  • First Publish Date: 21 June 2020