طراحی شبکه پایش آب زیرزمینی با استفاده از تحلیل آسیب پذیری در محدوده شعاع موثر چاه‌های پایش

نوع مقاله : مقاله پژوهشی

نویسندگان

دانشکده مهندسی عمران، آب و محیط زیست، دانشگاه شهید بهشتی، تهران، ایران

چکیده

 
پایش کمی و کیفی آب­های زیرزمینی قسمت جدانشدنی سیستم اطلاعات محیط زیستی است. روش­های مختلفی برای طراحی شبکه پایش آب زیرزمینی وجود دارد. در تحقیق حاضر سعی بر این بود تا روشی نوین جهت طراحی منعطف شبکه پایش تدوین شود. منظور از منعطف این است که نتایج حاصل از این تحقیق به تصمیم گیرنده این امکان را می­دهد تا با در نظر گرفتن سطح بودجه اختصاص یافته به طرح، تعداد محدودی از چاه­های با اولویت بالا را انتخاب کند. همچنین این امکان وجود دارد تا این روش به راحتی برای چاه­های در دست مطالعه یا احداث نیز استفاده گردد. همینطور در این روش طراحی منحصر به پایش فقط یک پارامتر (در تحقیق حاضر غلظت EC) نیست و به سادگی می­توان یک یا چند پارامتر را جایگزین نمود. برای محاسبه آسیب­پذیری آبخوان مدل DRASTIC استفاده شده است که از هفت لایه مربوط به آبخوان شامل عمق آب زیرزمینی، تغذیه خالص، مصالح تشکیل دهنده آبخوان، نوع خاک، توپوگرافی، ماهیت منطقه غیر اشباع و هدایت هیدرولیکی مصالح آبخوان تشکیل شده است. که وزن لایه­های آن با استفاده از الگوریتم تکاملی تفاضلی (DE) به منظور یافتن بیشترین همبستگی بین نقاط آسیب­پذیر و نقاطی که غلظت بالایی از هدایت الکتریکی دارند، بهینه شده­اند. در نتیجه­ی این بهینه­سازی مقدار تغذیه آبخوان (نفوذ واقعی آب به آبخوان) بیشترین همبستگی را دارد که این موضوع با استفاده از مقایسه نقشه­های تغذیه و هدایت الکتریکی صحت‏سنجی می­گردد. سطح حوضه به سلول­هایی با ابعاد 60 متر تقسیم شد. در استراتژی  اول سلول­هایی که حداقل در 60 درصد حالات مقدار آسیب­پذیری آن­ها بیشتر از میانگین است و در استراتژی دوم سلول­هایی که حداقل در 25 درصد حالات مقدار آسیب‏پذیری آن­ها بیشتر از میانگین به علاوه انحراف معیار است، مشخص شده­اند. با کمک مدل WhAEM2000 حریم حمایتی (10 ساله) چاه­های آب شرب موجود محاسبه شد و در نهایت چاه­های پایش به وسیله تعداد سلول­های محصور در حریم هر چاه اولویت­بندی شدند.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Groundwater monitoring network design using vulnerability analysis and well preservation zone

نویسندگان [English]

  • Hossein Yousefi
  • Mona Jamalomidi
  • Ali Moridi
Civil, water and environmental engineering faculty, Shahid Beheshti University, Tehran, Iran.
چکیده [English]

Monitoring the quantity and quality of groundwater is a non-separable part of the environmental information system. There are several ways to design a groundwater monitoring network. In the present study, we attempted to develop a new method for flexible design. Flexible means that the results of this study allow the decision maker to select a limited number of high-priority wells, taking into account the budget level allocated to the project. It is also possible to use this method easily for wells under study or construction. Also, in this design method, monitoring is not limited to just one parameter (in the present study, EC concentration) and one or more parameters can be easily replaced. The DRASTIC model was used to calculate the aquifer vulnerability, which consists of seven layers of aquifer, including groundwater depth, net recharge, aquifer media, soil type, topography, impact of vadose zone, and the hydraulic conductivity of aquifers. The layers were optimized using differential evolutionary algorithm (DE) to find the highest correlation between the vulnerable points and the points with the highest concentration of EC. As a result of this optimization, the amount net recharge (the actual infiltration of water into the aquifer) had the highest correlation, which was confirmed by comparing net recharge and EC maps. With the help of WhAEM2000, 10-year capture zone of existing wells was calculated. The final priority of the wells was calculated by linking of these models.

کلیدواژه‌ها [English]

  • WhAEM2000
  • DRASTIC
  • DE algorithm
  • MODFLOW
Abedi Koupai J, Zamani N, Goodarzi M, and Akhavan S (2018) Studying different methods for wellhead protection area delineation using WhAEM2000 analytic model in drinking wells of Damaneh-Daran. Iran-Water Resources Research 13:39–50 (In Persian)
Afshar A, Marino MA, Ebtehaj M, and Moosavi J (2007) Rule-based fuzzy system for assessing groundwater vulnerability. Journal of Environmental Engineering, American Society of Civil Engineers 133(5):532–540
Akbarzadeh M, Ghahraman B, and Davary K (2016) Optimization of groundwater quality monitoring network in Mashhad city aquifer using spatial-temporal modeling. Iran-Water Resources Research 12:133–144 (In Persian)
Alizadeh Z and Mahjouri N (2017) A spatiotemporal Bayesian maximum entropy-based methodology for dealing with sparse data in revising groundwater quality monitoring networks: The Tehran region experience. Environmental Earth Sciences 76(436):1-15
Alizadeh Z, Yazdi J, and Moridi A (2018) Development of an entropy method for groundwater quality monitoring network design. Environmental Processes 5(4):769–788
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
Aller L, Bennett T, Lehr JH, Petty RJ, and Hackett G (1987) DRASTIC: A standardized system for evaluating ground water pollution potential using hydrogeologic settings. US Environmental Protection Agency
Almasri MN (2008) Assessment of intrinsic vulnerability to contamination for Gaza coastal aquifer, Palestine. Journal of Environmental Management 88(4):577–593
Ayvaz MT and Karahan H (2008) A simulation/optimization model for the identification of unknown groundwater well locations and pumping rates. Journal of Hydrology 357(1–2):76–92
Baalousha H (2006) Vulnerability assessment for the Gaza Strip, Palestine using DRASTIC. Environmental Geology 50(3):405–414
Babiker IS, Mohamed MAA, Hiyama T, and Kato K (2005) A GIS-based DRASTIC model for assessing aquifer vulnerability in Kakamigahara Heights, Gifu Prefecture, central Japan. Science of the Total Environment 345(1–3):127–140
Bashi-Azghadi SN and Kerachian R (2010) Locating monitoring wells in groundwater systems using embedded optimization and simulation models. Science of the Total Environment, Elsevier B.V. 408(10):2189–2198
Bazimenyera JDD and Zhonghua T (2008) A GIS based DRASTIC model for assessing groundwater vulnerability in shallow aquifer in Hangzhou-Jiaxing-Huzhou Plain, China. Research Journal of Applied Sciences 3(8):550–559
Bhat S, Motz LH, Pathak C, and Kuebler L (2015) Geostatistics-based groundwater-level monitoring network design and its application to the Upper Floridan aquifer, USA. Environmental Monitoring and Assessment 187(1):4183
Connell LD and Van den Daele G (2003) A quantitative approach to aquifer vulnerability mapping. Journal of Hydrology 276(1–4):71–88
Desbarats AJ, Logan CE, Hinton MJ, and Sharpe DR (2002) On the kriging of water table elevations using collateral information from a digital elevation model. Journal of Hydrology 255(1–4):25–38
Dixon B (2004) Prediction of ground water vulnerability using an integrated GIS-based Neuro-Fuzzy techniques. Journal of Spatial Hydrology 4(2):1-38
Esquivel JM, Morales GP, and Esteller M V (2015) Groundwater monitoring network design using GIS and multicriteria analysis. Water Resources Management 29(9):3175–3194
Gogu RC and Dassargues A (2000) Current trends and future challenges in groundwater vulnerability assessment using overlay and index methods. Environmental Geology 39(6):549–559
Huan H, Wang J, and Teng Y (2012) 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 440:14–23
Jafari F, Javadi S, Golmohammadi G, Mohammadi K, Khodadadi A, and Mohammadzadeh M (2016) Groundwater risk mapping prediction using mathematical modeling and the Monte Carlo technique. Environmental Earth Sciences 75(6):491
Jafari SM and Nikoo MR (2016) Groundwater risk assessment based on optimization framework using DRASTIC method. Arabian Journal of Geosciences 9(20):742
Javadi S, Kavehkar N, Mohammadi K, Khodadadi A, and Kahawita R (2011) Calibrating DRASTIC using field measurements, sensitivity analysis and statistical methods to assess groundwater vulnerability. Water International, Taylor & Francis 36(6):719–732
Karterakis SM, Karatzas GP, Nikolos IK, and Papadopoulou MP (2007) Application of linear programming and differential evolutionary optimization methodologies for the solution of coastal subsurface water management problems subject to environmental criteria. Journal of Hydrology 342(3–4):270–282
Kazakis N and Voudouris KS (2015) Groundwater vulnerability and pollution risk assessment of porous aquifers to nitrate: Modifying the DRASTIC method using quantitative parameters. Journal of Hydrology, Elsevier B.V. 525:13–25
Maghsudsangatash S, Khashei Siuki A, Pourreza Bilondi M, and Shafiei M (2018) Application of acceptance probability method in assessment of groundwater chlorine quality monitoring network (Case study: Mashhad Aquifer). Iran-Water Resources Research 14:253–256 (In Persian)
Mahar PS and Datta B (2001) Optimal identification of ground-water pollution sources and parameter estimation. Journal of Water Resources Planning and Management, American Society of Civil Engineers 127(1):20–29
Maymandi N, Kerachian R, and Reza M (2018) Optimal spatio-temporal design of water quality monitoring networks for reservoirs: Application of the concept of value of information. Journal of Hydrology, Elsevier B.V. 558:328–340
McDonald MG and Harbaugh AW (1988) A modular three-dimensional finite-difference ground-water flow model. US Geological Survey Reston, VA
McLay CDA, Dragten R, Sparling G, and Selvarajah N (2001) Predicting groundwater nitrate concentrations in a region of mixed agricultural land use: A comparison of three approaches. Environmental Pollution 115(2):191–204
Moustafa M (2019) Assessing perched aquifer vulnerability using modified DRASTIC: A case study of colliery waste in north-east England (UK). Hydrogeology Journal 1–14
Nadiri AA, Sadeghfam S, Gharekhani M, Khatibi R, and Akbari E (2018) Introducing the risk aggregation problem to aquifers exposed to impacts of anthropogenic and geogenic origins on a modular basis using ‘risk cells.’ Journal of Environmental Management, Elsevier Ltd 217:654–667
Naghibi SA, Pourghasemi HR, and Dixon B (2016) GIS-based groundwater potential mapping using boosted regression tree, classification and regression tree, and random forest machine learning models in Iran. Environmental Monitoring and Assessment 188(1):1–27
Neshat A and Pradhan B (2015) Risk assessment of groundwater pollution with a new methodological framework: Application of Dempster–Shafer theory and GIS. Natural Hazards 78(3):1565–1585
Neshat A and Pradhan B (2017) Evaluation of groundwater vulnerability to pollution using DRASTIC framework and GIS. Arabian Journal of Geosciences 10(22)
Neshat A, Pradhan B, and Dadras M (2014) Groundwater vulnerability assessment using an improved DRASTIC method in GIS. Resources, Conservation, and Recycling 86:74–86
Pacheco FAL, Martins LMO, Quininha M, Oliveira AS, and Sanches Fernandes LF (2018) Modification to the DRASTIC framework to assess groundwater contaminant risk in rural mountainous catchments. Journal of Hydrology 566(September):175–191
Pathak DR and Hiratsuka A (2011) An integrated GIS based fuzzy pattern recognition model to compute groundwater vulnerability index for decision making. Journal of Hydro-environment Research 5(1):63–77
Sadeghfam S, Hassanzadeh Y, Nadiri AA, and Zarghami M (2016) Localization of groundwater vulnerability assessment using catastrophe theory. Water Resources Management 30(13):4585–4601
Saidi S, Bouri S, Ben Dhia H, and Anselme B (2011) Assessment of groundwater risk using intrinsic vulnerability and hazard mapping: Application to Souassi aquifer, Tunisian Sahel. Agricultural Water Management, Elsevier B.V. 98(10):1671–1682
Storn R and Price K (1995) DE-a simple and efficient adaptive scheme for global optimization over continuous space. Journal of Global Optimization 25(6):95–102
Sun J, Zhang Q, and Tsang EPK (2005) DE/EDA: A new evolutionary algorithm for global optimization. Information Sciences 169(3–4):249–262
Thirumalaivasan D, Karmegam M, and Venugopal K (2003) AHP-DRASTIC: Software for specific aquifer vulnerability assessment using DRASTIC model and GIS. Environmental Modelling & Software 18(7):645–656
Tilahun K and Merkel BJ (2010) Assessment of groundwater vulnerability to pollution in Dire Dawa, Ethiopia using DRASTIC. Environmental Earth Sciences 59(7):1485–1496
Zamani moghadam MG, Moridi A, and Yazdi J (2019) Determining the groundwater quality protection zone by considering the vulnerability of aquifer. Iran-Water Resources Research 16(1):1-16 (In Persian)