ارزیابی آسیب‏ پذیری آبخوان ساحلی قره‌سو-گرگان‌رود با استفاده از روش GALDIT و SINTACS و بهینه‏ سازی آن با ابزار SPSA و GIS

نوع مقاله: پژوهشی

نویسندگان

1 دانشجوی کارشناسی ارشد گروه سنجش از دور و سیستم اطلاعات جغرافیایی، دانشکدۀ منابع طبیعی و محیط‏زیست، دانشگاه آزاد اسلامی، واحد علوم تحقیقات تهران

2 استادیار گروه سنجش از دور و سیستم اطلاعات جغرافیایی، دانشکدۀ منابع طبیعی و محیط‏زیست، دانشگاه آزاد اسلامی، واحد علوم تحقیقات تهران

3 استادیار گروه مهندسی آبیاری و زهکشی، پردیس ابوریحان، دانشگاه تهران

چکیده

آب‏های زیرزمینی مهم‏ترین منبع تأمین آب در بسیاری از نواحی ساحلی جهان هستند. با توجه به برداشت بی‏رویه از آبخوان‏ها و هجوم آب شور، باید در آبخوان‏های ساحلی مدیریت صحیح اعمال شود. در این مطالعه، آسیب‏پذیری آبخوان ساحلی قره‏سو-گرگان‌رود برای شناسایی نواحی آسیب‏پذیر با استفاده از روش SINTACS و GALDIT بررسی ‏شده است. نقشه‏های آسیب‏پذیری این دو مدل در محیط نرم‌افزار GIS تولید، طبقه‏بندی و تلفیق شدند. به‏منظور دست‌یابی به مدل بهینه، ضریب همبستگی بین شاخص‏های آسیب‏پذیری و غلظت TDS محاسبه شد. نتایج به‌دست‌آمده نشان داد مدل GALDIT ضریب همبستگی بیشتری نسبت به مدل SINTACS برای تهیۀ نقشۀ آسیب‏پذیری در منطقۀ مطالعه‌شده دارد. علاوه بر این، برای اصلاح مدل GALDIT از روش تحلیل حساسیت تک‏پارامتری استفاده شد. نتایج به‌دست‌آمده از این تحلیل نشان داد مؤثرترین پارامترها در ارزیابی آسیب‏پذیری آبخوان منطقۀ مد نظر، هدایت هیدرولیکی و ارتفاع سطح آب زیرزمینی بالاتر از سطح دریا هستند.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Vulnerability assessment of Gharesou-Gorganroud coastal aquifer using GALDIT and SINTACS and optimization by SPSA and GIS

نویسندگان [English]

  • Mozhgan Bordbar 1
  • Aminreza Neshat 2
  • Saman Javadi 3
1 Department of GIS/RS, Faculty of Environment and Energy, Science and Research Branch, Islamic Azad University,Tehran,Iran
2 Department of GIS/RS, Faculty of Environment and Energy, Science and Research Branch, Islamic Azad University,Tehran,Iran
3 Assistant Professor Department of Irrigation and Drainage Engineering,Abouryhan; Tehran
چکیده [English]

Groundwater is the most important source of water in coastal areas. Recently, due to overexploitation of the aquifer and seawater intrusion, a correct management in coastal aquifers must be applied. In this study, GALDIT and SINTACS models are used with geographic information system (GIS), in order to identify Gharesou-Gorganroud vulnerability areas. To generate, classify, weight and overlay vulnerability maps according to these two models, GIS environment is used. Geographic information system (GIS) is a useful tool to identify and assess vulnerability areas. The Pearson correlation coefficients is used to achieve an optimal model. To compare correlation results of GALDIT model and SINTACS model, GALDIT model has a higher correlation with TDS concentrations. In addition, Single parameter sensitivity analysis used to modify the GALDIT model to observe effect of each parameter on the GALDIT result model. In the study area, the result illustrated that the effective parameters in aquifer vulnerability assessment were hydraulic conductivity, depth of groundwater level, distance from the shore, type of aquifer, thickness of aquifer and impact status of existing saltwater intrusion, respectively.

کلیدواژه‌ها [English]

  • vulnerability
  • GIS
  • GALDIT
  • SINTACS
  • Coastal aquifer
[1]. Javadi S, Hashemy SM, Mohammadi K, Howard KWF, Neshat A. Classification of aquifer vulnerability using K-means cluster analysis. Journal of Hydrology. 2017;549:27–37.
[2]. Majandang J, Sarapirome S. Groundwater vulnerability assessment and sensitivity analysis in Nong Rua, Khon Kaen, Thailand, using a GIS-based SINTACS model. Environmental earth sciences. 2013;68(7):2025–39.
[3]. Neshat A, Pradhan B, Pirasteh S, Shafri HZM. Estimating groundwater vulnerability to pollution using a modified DRASTIC model in the Kerman agricultural area. Iran. Environmental Earth Sciences.Doi. 2014;10.
[4]. Neshat A, Pradhan B. An integrated DRASTIC model using frequency ratio and two new hybrid methods for groundwater vulnerability assessment. Nat Hazards. 2015;76(1):543–63.
[5]. Werner AD. A review of seawater intrusion and its management in Australia. Hydrogeology Journal. 2010;18(1):281–5.
[6]. Vrba J, Zaporozec A. Guidebook on mapping groundwater vulnerability. Heise; 1994.
[7]. Samey AA, Gang C. A GIS based DRASTIC Model for the assessment of groundwater vulnerability to pollution in West Mitidja: Blida City, Algeria. J Appl Sci. 2008;3(7):500–7.
[8]. Neshat A, Pradhan B. Evaluation of groundwater vulnerability to pollution using DRASTIC framework and GIS. Arabian Journal of Geosciences. 2017;1;10(22):501.
 
[9]. Ribeiro L, Pindo JC, Dominguez-Granda L. Assessment of groundwater vulnerability in the Daule aquifer, Ecuador, using the susceptibility index method. Science of The Total Environment. 2017;574:1674–83.
[10].            Javadi S, Kavehkar N, Mousavizadeh MH, Mohammadi K. Modification of DRASTIC model to map groundwater vulnerability to pollution using nitrate measurements in agricultural areas. Journal of Agricultural Science and Technology. 2010;13:239–49.
[11].            Neshat A, Pradhan B, Shafri HZM. An integrated GIS based statistical model to compute groundwater vulnerability index for decision maker in agricultural area. Journal of the Indian Society of Remote Sensing. 2014;42(4):777–88.
[12].            Huan H, Wang J, Teng Y. Assessment and validation of groundwater vulnerability to nitrate based on a modified DRASTIC model: a case study in Jilin City of northeast China. Science of the Total Environment. 2012;440:14–23.
[13].            Bouderbala A, Remini B, Hamoudi AS, Pulido-Bosch A. Assessment of groundwater vulnerability and quality in coastal aquifers: a case study (Tipaza, North Algeria). Arabian Journal of Geosciences. 2016;9(3):181.
[14].            Gontara M, Allouche N, Jmal I, Bouri S. Sensitivity analysis for the GALDIT method based on the assessment of vulnerability to pollution in the northern Sfax coastal aquifer, Tunisia. Arab J Geosci. 2016;9(5):416.
[15].            Gorgij AD, Moghaddam AA. Vulnerability Assessment of saltwater intrusion using simplified GAPDIT method: a case study of Azarshahr Plain Aquifer, East Azerbaijan, Iran. Arabian Journal of Geosciences. 2016;9(2):106.
[16].            Allouche N, Brahim FB, Gontara M, Khanfir H, Bouri S. Validation of two applied methods of groundwater vulnerability mapping: application to the coastal aquifer system of Southern Sfax (Tunisia). Journal of Water Supply: Research and Technology-Aqua. 2015;64(6):719–37.
[17].            Kura NU, Ramli MF, Ibrahim S, Sulaiman WNA, Aris AZ, Tanko AI, et al. Assessment of groundwater vulnerability to anthropogenic pollution and seawater intrusion in a small tropical island using index-based methods. Environmental Science and Pollution Research. 2015;22(2):1512–33.
[18].            Saidi S, Bouri S, Dhia HB. Groundwater management based on GIS techniques, chemical indicators and vulnerability to seawater intrusion modelling: application to the Mahdia–Ksour Essaf aquifer, Tunisia. Environmental earth sciences. 2013;70(4):1551–68.
[19].            Civita MV. Le carte della vulnerabilita ‘degli aquiferi all’inquinamento (Aquifer pollution vulnerability maps). Teor Pract Pitagora Bologna Ital. 1993.
[20].            Al Kuisi M, El-Naqa A, Hammouri N. Vulnerability mapping of shallow groundwater aquifer using SINTACS model in the Jordan Valley area, Jordan. Environ Geol. 2006;50(5):651–67.
[21].            Civita M, De Maio M, Berberi F. Sintacs: un sistema parametrico per la valutazione e la cartografia della vulnerabilità degli acquiferi all’inquinamento: metodologia e automatizzazione. Pitagora Editrice; 1997.
[22].            Chachadi AG, Lobo-Ferreira JP. Sea water intrusion vulnerability mapping of aquifers using GALDIT method. Coastin—A Coast Policy Res Newsl. 2001;4:7–9.
[23].            Chachadi AG. Seawater intrusion mapping using modified GALDIT indicator model—case study in Goa. Jalvigyan Sameeksha. 2005;20:29–45.
[24].            Balakrishnan P, Saleem A, Mallikarjun ND. Groundwater quality mapping using geographic information system (GIS): A case study of Gulbarga City, Karnataka, India. African Journal of Environmental Science and Technology. 2011;5(12):1069–84.
[25].            Hasiniaina F, Zhou J, Guoyi L. Regional assessment of groundwater vulnerability in Tamtsag basin, Mongolia using drastic model. J Am Sci. 2010;6(11):65–78.
[26].            Babiker IS, Mohamed MA, Hiyama T, Kato K. A GIS-based DRASTIC model for assessing aquifer vulnerability in Kakamigahara Heights, Gifu Prefecture, central Japan. Science of the Total Environment. 2005;345(1):127–40.
[27].            Civita M, De Maio M. Assessing and mapping groundwater vulnerability to contamination: the Italian combined approach. Geofísica Int. 2004;43(4):513–32.
[28].            Linsley Jr RK, Kohler MA, Paulhus JL. Hydrology for engineers. 1975.
[29].            Aller L, Lehr JH, Petty R, Bennett T. DRASTIC: a standardized system to evaluate groundwater pollution potential using hydrogeologic settings. National Water Well Association, Worthington, Ohio, United States of America. 1987.
[30].            Bear J, Verruijt A. Modeling Groundwater Flow and Pollution. D. D. Reidel Publication Company, Dodreich, Holland. 1987.
[31].            Badon-Ghyben W. Nota in verband met de voorgenomen putboring nabil Amsterdam. Tijdschr K Inst Ing Hague. 1889;27:1888–9.
[32].            Herzberg A. Die wasserversorgung einiger Nordseebader. J Gasbeleucht Wasserversorg. 1901;44:842–4.