Document Type: Original Article

Authors

1 M.Sc graduated in watershed management, organization of Natural Resources and Watershed Management, Karoon Watershed Management Office (KWMO). Shahrekord, Iran

2 Assistant Professor of Watershed Management, Faculty of Agriculture and Natural Resources, University of Hormozgan, Iran

Abstract

Artificial recharge can be an effective method to raise the groundwater table and to resolve the groundwater crisis in Sefid dasht plain. The most important step to successful accomplishment of artificial recharge is locating suitable areas for artificial recharge. Hence this research carried out with purpose of determining suitable areas for artificial recharge in Sefid dasht plain. Slope, surface infiltration, alluvial thickness, alluvial quality and land use parameters were analyzed, classified and map of every parameter prepared using GIS. To overlay the affective parameters in artificial recharge was Fuzzy c-mean models. Results showed that 16.2 percent of Sefid dasht plain is suitable for artificial recharge based on Fuzzy c- mean model. Using land use layer this value decreased to 4.5 percent. So land use in is a limitative parameter in study area.

Keywords

 Ahani, H., Kherad, M., Kousari, MR., Rezaeian-Zadeh, M., Karampour, M. A., Ejraee, F., Kamali, S., 2012. An investigation of trends in precipitation volume for the last three decades in different regions of Fars province, Iran.
 Theoretical and Applied Climatology. 10.1007/s00704-011-0572-z.
 Alesheikh, A. A., Soltani, M. J., Nouri, N., Khalilzadeh, M., (2008). Land assessment for artificial recharge site selection using geospatial information system, Int, J. Environ. Sci. Tech., 5 (4), 455-462.
 ASCE Standard . (2001). Environmental and water resources institute, American Society of Civil Engineers. Standard guidelines for artificial recharge of groundwater, ASCE standards, EWRI/ASCE 34–01 , 106.
 Balachandar, D., Alaguraja, P., Sundaraj, P., Rutharvelmurthy, K., Kumaraswamy, K., (2010). Application of Remote Sensing and GIS for Artificial Recharge Zone in Sivaganga
 Barcae E, Passarella G. 2008. Spatial evaluation of the risk of groundwater quality degradation: Acomparison between disjunctive kriging and geostatistical simulation , Journal of Environmental Monitoring and Assessment.133: 261-273.
 Berndes, G., (2008). Water Demand for Global Bioenergy Production: Trends, Risks and Opportunities. Wissenschaftlicher Beirat Der Bundesregierung Globale Umweltveränderungen (WBGU).
 Fetouani S, Sbaa M, Vanclooster M, Bendra, B. 2008. Assessing groundwater quality in the irrigated plain of Triffa (Nnorth-east Morocco). Journal of Agricultural Water Management 95: 133-142.
 Ghayoumian J, Ghermezcheshme B, Feiznia S, Noroozi A. A. 2005. Integrating GIS and DSS for identification of suitable areas for artificial recharge, case study Meimeh Basin, Isfahan, Iran. Environ. Geo., 47(4), 493-500.
 Ghayoumian. J., Mohseni Saravi, M., Feiznia, S., Nouri, B., Malekian, A., (2007). Application of GIS techniques to determine areas most suitable for artificial groundwater recharge in a coastal aquifer in southern Iran. Journal of Asian Earth Science 30, 364-347.
 Hofkes, E. H., Visscher, J. T., (1986). Artificial Groundwater Recharge for Water Supply of Medium- Size Communities in Developing Countries. International Refrence Center for Community Water Supply and Sanitation the Hague, the Netherlands.
 Huang, J., & Zhang, J. (2011). Fuzzy C-Means Clustering Algorithm with Spatial Constraints for Distributed WSN Data Stream. International Journal of Advancements in Computing Technology , III, 165-175.
 Islam, Z., Metternicht, G. (2005). The Performance of Fuzzy Operators on
 Jasrotia, A. S., Kumar, R., Saraf, A. K., (2007). Delination of Groundwater Recharge Sites Using Integrated Remote Sensing and GIS in Jammu District, India, International Journal of Remote Sensing, Vol. 28, No. 22, 20, 5019-5036
 Kheirkhah Zarkesh, M. M., Meijerink, A. M. J., Goodarzi, M.,(2008). Decision support system (DSS) for site selection floodwater spreading schemes using remote sensing (RS) and geographical information systems (GIS), DESERT 12, 149-164.
 Mehrvarz, K., Kalantari, A., (2007). Investigation of Quaternary Deposits Suitable for Floodwater Spreading. International Congress on River Basin management.
 Moradi, M, Vagharfard, H., Khorani, A., Mahmoodinejad, V. (2011). Interpolation methods in evaluation of groundwater salinity zonation using Cross-Validation Technique case study: lowland Shahrekord, Iranian Remote Sensing & GIS Journal, 3 (1): 34-44.
 Nirmala, R., Shankara, M., Nagaraju, D., (2011). Artificial groundwater recharge studies in Sathyamangalam and Melur villages of Kulathur taluk, Pudukottai district, Chennai, using GIS techniques. International Journal of Environmental Sciences. Volume 1, No 7, ISSN 0976-4402.
 Nouri, B., Ghayoumian, J., Mohseni Saravi, M., Darvish SEfat, A., Feiznia, S., (2005). Identification of Suitable Sites for Groundwater Artificial Recharge by Basins Method Using GIS. Iranian Journal. Natural Resources, Volume 57, No 3. 635- 647
 Ravi Shankar, M. N. R., Mohan, G., (2005). A GIS based hydrogeomorphic approach for identification of site-specific artificial-recharge
 Rosegrant, M. W., Cai, X., Cline, S. A., (2002). Global Water Outlook to 2025, Averting an Impending Crisis. International Water Management Institute (IWMI).
 Saraf A. C. 1998. Integrated remote sensing and GIS for groundwater exploration and identification of artificial recharge sites. International Journal of Remote Sensing, 19(10): 2595–2616.
 Sayana, V. B. M., Arunbabu, E., Mahesh Kumar, L., Ravichandran, S., and Karunakaran, K., (2010), Groundwater responses to artificial recharge of rainwater in Chennai, India: a case study in an educational institution campus, Indian Jurnal of Science and Tecnology, Vol.3, ISSN:0974-6846.
 Wu K. Y. 2002. Alternating c-means clustering algorithms. Pattern Recognition 35: 2267- 2287.
 Yu J, Cheng Q, Huang H. 2004. Analysis of the weighting exponent in the FCM. IEEE Trans. Systems Man Cybernet. 634–639.