Combination of Fuzzy and Boolean logic and MCDM Methods for Investigating Suitable Areas for Artificial Groundwater Recharge (Case Study: Chenaran Watershed in Razavi Khorasan Province)

نوع مقاله : مقاله پژوهشی

نویسندگان

1 MSc. Graduated of Watershed Management, Islamic Azad University Maybod Branch

2 Dept. of watershed management, Maybod Branch, Islamic Azad University, maybod, Iran

3 Dept. of watershed management, Maybod Branch, Islamic Azad University, Maybod, Iran

چکیده

More than two-thirds of Iran have been located in arid and semi-arid regions. Overuse of groundwater water resources has decreased the groundwater level in these areas. Artificial recharge plays a pivotal role in the sustainable management of groundwater resources. Investigating suitable areas for optimal use of water floods is one of the most important factors in recharging underground water tables in dry lands where the agricultural and rangelands are vulnerable. Hence, this study proposes a methodology to delineate artificial recharge zones and identify favorable artificial recharge sites using integrated Fuzzy logic, Boolean logic and multi-criteria decision-making (MCDM) methods for augmenting groundwater resources in Chenaran Watershed facing water shortage problems. The thematic layers considered in this study are infiltration rate, slope, geology, geomorphology, land cover, distance to river, distance to road and distance to Qanats and wells, which were prepared using satellite imagery and conventional data. Then, by applying the limiting layer as a combination of four criteria of lithology, land use, slope and geomorphology, the final map of recharge suitable areas was prepared and prioritized from highly suitable to unsuitable. The final obtained map divided the study area into five zones according to their suitability for artificial groundwater recharge. The results were then examined against the existing water spreading site to estimate their accuracy. The artificial recharge suitable zone of the final map was found to be in agreement with the map of water spreading project performed by the Ministry of Agriculture Djehad (accuracy was more than 78%). The results of this study could be used to formulate an efficient groundwater management plan for the study area and other similar areas.

کلیدواژه‌ها


عنوان مقاله [English]

Combination of Fuzzy and Boolean logic and MCDM Methods for Investigating Suitable Areas for Artificial Groundwater Recharge (Case Study: Chenaran Watershed in Razavi Khorasan Province)

نویسندگان [English]

  • Meisam Gavahi 1
  • Mohammad Hassanzadeh Nafooti 2
  • Ali Akbar Jamali 3
1 MSc. Graduated of Watershed Management, Islamic Azad University Maybod Branch
2 Dept. of watershed management, Maybod Branch, Islamic Azad University, maybod, Iran
3 Dept. of watershed management, Maybod Branch, Islamic Azad University, Maybod, Iran
چکیده [English]

More than two-thirds of Iran have been located in arid and semi-arid regions. Overuse of groundwater water resources has decreased the groundwater level in these areas. Artificial recharge plays a pivotal role in the sustainable management of groundwater resources. Investigating suitable areas for optimal use of water floods is one of the most important factors in recharging underground water tables in dry lands where the agricultural and rangelands are vulnerable. Hence, this study proposes a methodology to delineate artificial recharge zones and identify favorable artificial recharge sites using integrated Fuzzy logic, Boolean logic and multi-criteria decision-making (MCDM) methods for augmenting groundwater resources in Chenaran Watershed facing water shortage problems. The thematic layers considered in this study are infiltration rate, slope, geology, geomorphology, land cover, distance to river, distance to road and distance to Qanats and wells, which were prepared using satellite imagery and conventional data. Then, by applying the limiting layer as a combination of four criteria of lithology, land use, slope and geomorphology, the final map of recharge suitable areas was prepared and prioritized from highly suitable to unsuitable. The final obtained map divided the study area into five zones according to their suitability for artificial groundwater recharge. The results were then examined against the existing water spreading site to estimate their accuracy. The artificial recharge suitable zone of the final map was found to be in agreement with the map of water spreading project performed by the Ministry of Agriculture Djehad (accuracy was more than 78%). The results of this study could be used to formulate an efficient groundwater management plan for the study area and other similar areas.

کلیدواژه‌ها [English]

  • Fuzzy & Boolean logic
  • Artificial Groundwater Recharge
  • MCDM
  • Chenaran watershed
Al-Adamat, R. 2012., The Use of GIS and Google Earth for Preliminary Site Selection of Groundwater Recharge in the Azraq Oasis Area—Jordan. J. Water Resour. Prot. 4: 395–399.
Alesheikh, AA. And  H. Helali., 2002. Web GIS Developmant Strategy. GIM International, Nov. 2008, 16(ll): 12-25.
Alesheikh, AA. Soltani, M, Nouri J., 2008. Land Assessment for Flood Spreading Site Selection Using Geospatial Information System, International Journal of Environmental Science Technology. 5: 455-462.
Asano T., 1985. Artificial Groundwater Recharging. Butterworth, Boston, p 767.
Babcock HM, Cusing EM., 1942. Recharge to groundwater from floods in a typical desert wash, Pinal County, Arizona. Trans Am Geophysics Union 1:49.
Beeby-Thompson A., 1950. Recharging London’s water basin. Timer Review Industry, pp 20–25.
Bonham Carter, G.F., 1996. Geographic information systems for geosciences modeling with GIS. Oxford: Pergamon, Love Printing Service Ltd, 398.
Bouwer, H., 2002. Artificial recharge of groundwater: hydrogeology and engineering. Hydrogeology Journal 10:121-142. Brown, F. M., 2003. Boolean reasoning: The logic of Boolean equations. Dover Publications:  2nd Ed., 304.
Buchen S., 1955. Artificial replenishment of aquifers. J Inst Water Eng 9:111–163.
Chabok Boldaji, M., Hassanzadeh Nofoti, M., Ebrahimi Khosfi, Z., 2010, Suitable Areas Selection Using AHP (Case study watershed Ashgabat Tabas), Journal of Science and Engineering watershed, 4(13): 33-40.
Chowdhury, A., M. K. Jaha and V. M. Chowdary. 2010. Delineation of groundwater recharge zones and identification of artificial recharge sites in West Medinipur district, West Bengal, using RS & GIS and MCDM techniques. J. Environ. Earth Sci. 59: 1209-1222.
Das, D., 2003. Integrated Remote Sensing and Geographical Information System Based Approach Towards Groundwater Development Through Artificial Recharge in Hard-Rock Terrain. District, Tamilnadu, India. International Journal of Geomatics and Geosciences. 1(1):0976-4380.
Eden, S., Gelt, J., Megdal, S., Shipman, T., Smart, A., Escobedo, M., 2007. Artificial Recharge: A Multi-Purpose water Management Tool. Arroyo.Water Resources Research center.
Escalante, E.F.; Gil, R.C.; San Miguel Fraile, M.Á.; Serrano, F.S., 2014. Economic Assessment of Opportunities forManaged Aquifer Recharge Techniques in Spain Using an Advanced Geographic Information System (GIS).Water 2014, 6, 2021–2040.
Faraji H. AH. Nasiri. M. Hamze. S.Talebi. Y. Rafiei., 2011.  Identification of suitable areas for artificial groundwater recharge using integrated ANP and pair wise comparison methods in GIS environment, (case study: Garbaygan Plain of Fasa). Geography and Environmental Planning Journal 22th Year. 44(4): 41-46.
Faraji H. A.,  Hassanpour S. Azizi A. Malakian A. Alavipanah S.K. 2013. Floodwater Spreading Site Selection by FAHP and GCA and Comparison of Model Performance (Case Study: Garabaygan Catchment, Fasa Plain, Shiraz).Jour of Natural Geographical Researches. 54(2): 55-76.
Faucette, B.; King, W.; Germishuizen, P., 2003. Compost based erosion and sediment control demonstrations. Bio Cycle, 44(10): 32-40.
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.
Hassanzadeh Nafooti, M., jamali, A., Fallah A.A., 2016. Site Selection Underground Dams Using Spatial Multi-Criteria Evaluation (SMCE) (Case Study: the Adori Area in Bam city). Jour of Iran-Watershed Management Science & Engineering. 10(32): 69-76.
Hostetler, S., 2007. Water Banking; Science for Decision Makers. Science for Decision Makers; Australian Government, Bureau of Rural Sciences: Canberra, Australia.
Jasrotia, A, S., Majhi, A., Singh, S., 2009. Water balance approach for rainwater harvesting using remote sensing and gis techniques, Jammu Himalaya, India. Water ResourManag.doi:10.1007/s11269-009-9422-5.
Jha, M. K., Chowdhury, A., Chowdary, V. M., Peiffer, S., 2007. Groundwater management and development by integrated remote sensing and geographic information systems: prospects and constraints. Water Resources Management. 21(2): 426-467.
Kheirkhah Zarkesh, M. 2005. DSS for floodwater site selection in Iran, PhD. Thesis, Wageningen University. 273.
Kowsar, A. 1995. Introduction to floods mitigation and optimum utilization. Book, Pb. no. 1374-150. Ranges and Forests Research institute, Ministry of Jahad-e-Sazandegi, 524 pp.
Malczewski, J., 1999. GIS and Multicriteria Decision Analysis; John Wiley & Sons: New York, NY, USA.
Malczewski, J.; Rinner, C., 2015. Multicriteria Decision Analysis in Geographic Information Science; Springer: New York, NY, USA.
Malekian A., Alipour H, Kheirkhahzarkesh M, Gharachelo S., 2014. Application of Decision Making systems in flood water spreadin site selection. J. Water and Soil Sci. (Sci. & Technol. Agric. & Natural Resources.18(69): 165-177. 
Mardani, A. Jusoh A. Nor K. Khalifah Z., 2015. Multiple Criteria Decision Making Techniques and Their Application- A review of The Literature From 2000- 2014. Economic Research. 28(1): 516-571.
Murugiah M, Venkatraman P., 2013. Role of Remote Sensing and GIS in artificial recharge of the ground water aquifer in Ottapidaram taluk, Tuticorin district, South India International Journal of Geomatics and Geosciences. 3(3): 0976 – 4380.
Nezam asghari, 2011. Identifying suitable flood spreading area for artificial recharge in Andimeshk. Jour of geographical land. 8(32): 90- 112.
Patil, S.G, Mohite N.M., 2014. Identification of groundwater recharge potential zones for a watershed using remote sensing and GIS. International Journal of Geomatics and Geosciences. 4(3): 485-498. 
Pedrero, F.; Albuquerque, A.; Marecos do Monte, H.; Cavaleiro, V.; Alarcón, J.J. 2012. Application of GIS-based multi-criteria analysis for site selection of aquifer recharge with reclaimed water. Resour. Conserv. Recycl. 56: 105–116.
Rafee, N.; Karbassi, A. R.; Nouri, J.; Safari, E.; Mehrdadi, M., (2008). Strategic management of municipal debris aftermath of an earthquacke. Int. J. Environ. Res., 2 (2): 205-204.
Rahman, M.A.; Rusteberg, B.; Gogu, R.C.; Lobo Ferreira, J.P.; Sauter, M., 2012. A new spatial multi-criteria decision support tool for site selection for implementation of managed aquifer recharge. J. Environ. Manag, 99: 61–75.
Russo, T.A.; Fisher, A.T.; Lockwood, B.S. 2015. Assessment of Managed Aquifer Recharge Site Suitability Using a GIS and Modeling. Groundwater. 53: 389–400.
Saaty, TL., 1980. The analytic Hierarchy Process: planning, priority setting, resource allocation. McGraw-Hill, New York, p 287.
Seckler, D., Amarasinghe U., Molden D., de Silva R. and Barker R., 1998. World water demand and supply, 1990 to 2025: scenarios and issues. Research Report 19. International Water Management Institute, Colombo, Sri Lanka.
Singh, A.; Panda, S.N.; Kumar, K.S.; Sharma, C.S., 2013. Artificial groundwater recharge zones mapping using remote sensing and GIS: A case study in Indian Punjab. Environ. Manag. 52: 61–71.
Sukumar, S.; Sankar, K., 2010. Delineation of potential zones for artificial recharge using GIS in Theni district, Tamilnadu, India. Int. J. Geomat. Geosci. 2010, 1, 639.
Todd DK., 1959. Annotated bibliography on artificial recharge of groundwater through 1954. USGS Water Supply Paper 1477, pp 115.
Yazdani moghadam, Y., 2012. Performance of multiple decision making method in floodwater spreading site selectin case study: Kashan Plain. IranianRemote Sensing&GIS. 4(3): 65-80.
Zadeh, L., 1965. Fuzzy sets. Inform. Control, 8 (3), 338-353.
Zahedi, E. Jahanbakhshi F, Talebi A., 2016. Investigating Suitable Areas for Flood Spreading Using Fuzzy Logic and Analytic Network Process (ANP) (Case Study: Mashhad Plain). J. Water and Soil Sci. (Sci. & Technol. Agric. & Natural Resources.), 20 (77): 185-196.