| تعداد نشریات | 282 |
| تعداد نشریات سازمان | 80 |
| تعداد شماره‌ها | 3,262 |
| تعداد مقالات | 36,058 |
| تعداد مشاهده مقاله | 55,181,291 |
| تعداد دریافت فایل اصل مقاله | 94,181,800 |
تعیین آسیبپذیری آبخوان روضه چای دشت ارومیه با استفاده از روش ترکیبی شاخصهای DRASTIC، SINTACS و SI | ||
| پژوهش های آبخیزداری | ||
| مقاله 6، دوره 33، شماره 3 - شماره پیاپی 128، مهر 1399، صفحه 70-90 اصل مقاله (1.37 M) | ||
| نوع مقاله: پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22092/wmej.2020.127818.1261 | ||
| نویسندگان | ||
| رامین موسی زاده1؛ اسفندیار عباس نوین پور* 2؛ فریبا صادقی اقدم3 | ||
| 1دانش‌آموخته کارشناسی ارشد هیدروژئولوژی گروه زمین‌شناسی، دانشکده علوم، دانشگاه ارومیه، ارومیه، ایران | ||
| 2استادیار، گروه زمین‌شناسی، دانشکده‌ی علوم، دانشگاه ارومیه، ارومیه، ایران | ||
| 3دانشجوی دکتری هیدروژئولوژی، گروه علوم زمین، دانشکده علوم طبیعی، دانشگاه تبریز، ایران | ||
| چکیده | ||
| دشت روضه‌چای در حاشیهی غربی دریاچهی ارومیه بهدلیل کمی عمق سطح ایست‌آبی، رونق کشاورزی، به‌کاربردن کودهای شیمیایی و آفت‌کشها با احتمال آلودگی آبخوان مواجه است. ارزیابی آسیبپذیری می‌تواند نقشی حیاتی در حفاظت و بهرهبرداری از آبخوان بازی کند. داده‌ها و اطلاعات متعدد ازجمله نقشههای ارتفاع رقومی و کاربری زمین، آمار چاههای بهرهبرداری و اکتشافی، و غلظت نیترات نمونه‌های تجزیه‌شده در خرداد 1395 به‌کار برده شد. توزیع فراسنج‌های عمق سطح ایست‌آبی، تغذیهی خالص، هدایت آبی، پستی‌وبلندی، کاربری زمین، محیط نااشباع، آبخوان و خاک با کاربرد درونیابی کریجینگ با نرمافزار آرک‌جی‌آی‌اس انجام شد. لایههای رستری با اعمال رتبهبندی و وزندهی با توابع هم‌پوشان تلفیق و توزیع آسیبپذیری روشهای دراستیک، سینتکس و اس‌آی تعیین شد. با کاربرد روش ترکیبی وزندار، نقشهی نهایی منطقه‌های آسیب‌پذیر تهیه شد. برای ارزیابی عمل‌کرد هر یک از سه روش، ضریب همبستگی بین اندازه‌ی نیترات و شاخصهای آسیبپذیری به‌ترتیب با اندازه‌ی 0/43، 0/37 و 0/30 و شاخص همبستگی 28، 27 و 25 محاسبه شد. نتیجه‌ها نشان داد که اندازه‌ی ضریب همبستگی روش ترکیبی (60/0) و شاخص همبستگی (35) بیش‌تر از روشهای منفرد آسیبپذیری بود. شاخص ترکیبی داده‌شده در این مقاله می‌تواند هم‌زمان آسیبپذیری ذاتی و اندازه‌ی خطر واقعی و به‌هنگام آسیبپذیری را باهم یکی کند و آسیبپذیری جامع را نشان دهد. براساس نتیجه‌ی کاربرد این روش حدود 30% از مساحت دشت روضه‌چای در محدوده‌های با خطر آسیبپذیری کم، 45% با آسیبپذیری متوسط و 25% با آسیبپذیری زیاد است. | ||
| کلیدواژه‌ها | ||
| اس آی؛ دراستیک؛ دشت روضه‌ی‌چای؛ روش ترکیبی؛ سینتکس؛ شاخص های آسیبپذیری | ||
| عنوان مقاله [English] | ||
| Determining Vulnerability of the Rozeh Chay Aquifer in the Urmia Plain, Using the Combination Method of DRASTIC, SINSTAC and SI Indexes | ||
| نویسندگان [English] | ||
| Ramin Mosazade1؛ Esfendiar Abbas Novinpour2؛ Fariba Sadeghi Aghdam3 | ||
| 1M.Sc. Graduated Student in Hydrogeology, Department of Geology, Faculty of Science, Urmia University, Urmia, Iran | ||
| 2Assistant Professor, Department of Geology, Faculty of Science, Urmia University, Urmia, Iran | ||
| 3Ph.D student in Hydrogeology, Department of Earth Sciences, Faculty of Natural Sciences, University of Tabriz, Iran | ||
| چکیده [English] | ||
| The Rozeh Chay Plain is located on the western margin of the Urmia Lake. The shallow groundwater table, agricultural activities, and particularly the use of fertilizers and pesticides may lead to the groundwater contamination. Therefore, assessing the vulnerability can play a vital role in protecting and benefiting from this aquifer. Various data, including: DEM, land use, operation and observation wells and nitrate concentration of water samples analyses in May 2016 were used. Using the ArcGIS, the raster layers of groundwater depth, net recharge, hydraulic conductivity, topography, land use, unsaturated zones, aquifer and soil media were determined using the kriging interpolation method. These layers were integrated by ranking and weighting with the overlapping functions and the layers of DRASTIC, SINTACS and SI methods were determined. The final map of the vulnerable areas was prepared using a weighted combination method. In order to evaluate the performance of each DRASTIC, SINTACS and SI method, the correlation coefficients (r) were calculated between the nitrate values and vulnerability indices were: 0.43, 0.37 and 0.30, respectively, and the correlation indices (CI) were 28, 27 and 25 respectively. The results showed that combination methods had higher values of the r (0.60) and CI (35) than the individual methods. The combined index presented in this study can combine both the intrinsic vulnerability and the actual and timely vulnerability risk, and in fact shows the comprehensive vulnerability. Based on the combined method, about 30, 45, and 25 percent of the area of the Rozeh Chay Plain are located in the low, medium and high vulnerability range, respectively. | ||
| کلیدواژه‌ها [English] | ||
| DRASTIC, combined method, Rozeh chay plain, SI, SINSTAC, vulnerability indexes | ||
| مراجع | ||
|
Aboulouafa M, Taouil H, lbn Ahmed S, Tairi A, Arouya K, Hsaissoune M. 2017. Sintacs and Drastic models for groundwater vulnerability assessment and mapping using a GIS and remote sensing techniques: A Case study on Berrechid Plain. IOSR Journal of Engineering. 7(5): 23–30. Akhavan S, Mousavi SF, Abedi-Koupai J, Abbaspour K. 2011. Conditioning Drastic model to simulate nitrate pollution case study: Hamadan–Bahar plain. Environ Earth Sci. 63(6): 1155–1167. Al-Adamat RAN, Foster IDL, Baban SMJ. 2003. Groundwater vulnerability and risk mapping for the Basaltic aquifer of the Azraq basin of Jordan using GIS, remote sensing and DRASTIC. Applied Geography. 23(4): 303–324. Aller L, Bennet T, Leher JH, Petty RJ, Hackett G. 1987. Drastic: A standardized system for evaluating ground water pollution potential using geo hydrogeology settings. 622 p. Almasri MN. 2008. Assessment of intrinsic vulnerability to contamination for Gaza Coastal aquifer. Palestine Journal of Environ. Management. 88(4): 577–593. Al-Zabet T. 2002. Evaluation of aquifer vulnerability to contamination potential using the Drastic method. Journal of Environmental Geology. 43(1–2): 203–208. Anane M, Abidi B, Lachaal F, Limam A, Jellali S. 2015. GIS-based Drastic, pesticide Drastic and the usceptibility Index (SI): Comparative study for evaluation of pollution potential in the Nabeul-Hammamet shallow aquifer, Tunisia. Journal of Hydrogeology. 21(3): 715–731. ASTM. 2002. Annual book of ASTM standards. Section 11, Water and environmental technology. American Society for Testing and Materials. 11.01. 1020 pp. Aydi W, Saidi S, Chalbaoui M, Chaibi S, Ben Dhia H. 2013. Evaluation of the groundwater vulnerability to pollution using an intrinsic and a specific method in a GIS environment: Application to the Plain of Sidi Bouzid (Central Tunisia). Arabian Journal for Science and Engineering. 38(7): 1815–1831. Babiker IS, Mohamed AA, Tetsuya H. 2015. A GIS–based Drastic model assessing aquifer vulnerability in Kakamigahara Height Gifu Prefecture. Science of the Total Environment Journal. 345(1): 127–140. Civita M. 1994. Le carte della vulnerabilita` degli aquifer all’inquinamento Teoria and practica (Aquifer vulnerability maps to pollution) (In Italian). Pitagora Ed, Bologna. Civita M, De Maio M. 1997. SINTACS. Un sistema parametrico per la valutazione e la cartografia della vulnerabilita‘ degli acquiferi all’inquinamento. Metodologia and Automatizzazione. Pitagora Editrice, Bologna. (In Italian). 60: 191. Dixon B. 2005. Groundwater vulnerability mapping: A GIS and fuzzy rule based integrated tool. Applied Geography. 25(4): 327–347. Entezari M, Amiri F, Tabatabaie T. 2018. A GIS, DRASTIC techniques for assessing groundwater vulnerability in Torghabeh –Shandiz watershed of Khorasan county. 9(3-32): 19–32. (In Persian). Ersoy AF, Gültekin F. 2013. Drastic-based methodology for assessing groundwater vulnerability in the Gümüşhacıköy and Merzifon basin (Amasya, Turkey). Earth Sci. Res. SJ. 17(1): 33–40. Evans BM, Myers WL. 1990. A GIS-based approach to evaluating regional groundwater pollution potential with Drastic. Journal of Soil and Water Conservation. 45(2): 242–245. Gharekhani M, Nadiri AA, Asghari Moghaddam A, Sadeghi Aghdam F. 2015. Optimization of Drastic Model by support vector machine and artificial neural network for evaluating of intrinsic vulnerability of Ardabil Plain Aquifer. Ecology hydrology. 2(3): 311–324. (In Persian). Ghosh A, Kumar Tiwari A, Das S. 2015. A GIS based Drastic model for assessing groundwater vulnerability of Katri Watershed, Dhanbad, India. Modeling earth systems and environment. pp: 1–15. Javanshir G, Nadiri AA, Sadeghfam S, Abbas Novinpour E. 2016. Introducing a new method to aquifer vulnerability assessment of Moghan plain based on combination of DRASTIC, SINTACS and SI methods. Journal of Ecohydrology. 3(4):491–503. (In Persian). Khodaei K, Shahsavari HA, Etebari B. 2005. Valuation vulnerability aquifer Join basin by DRASTIC and GODS method. Journal of Iranian Geology. 2(4):73–87. (In Persian). Khosravi Kh, habibnejad M, Solaimani K, Babaei KH. 2012. Assessment of groundwater vulnerability using a-GIS based DRASTIC Model (Case study: Dehgolan Plain, Kurdistan Province). Journal of Watershed Management Research. 3(5):42–62. (In Persian). Kozłowski M, Sojka M. 2019. Applying a modified DRASTIC model to assess groundwater vulnerability to pollution: Pol. J. Environ. Stud. 28(3): 1223–1231. Lathamani R, Janardhana MR, Mahalingam B, Sureshad S. 2015. Evaluation of aquifer vulnerability using Drastic Model and GIS: A case study Of Mysore City, Karnataka, India. Aquatic Procedia. 4: 1031–1038. Margat J. 1968. Vulnerabilite des nappes d’eau souterraine a la pollution: bases de la cartographie [Vulnerability of groundwater to pollution: database mapping]. BRGM Publication. BRGM, Orleans, France. 68-SGL 198. Maria R. 2018. Comparative studies of groundwater vulnerability assessment. Global Colloquium on GeoSciences and Engineering. IOP Conference Series: Earth and Environmental Science. 18(1): 012018. 118 012018. Mirzaei S. 2009. Valuation vulnerability and preparation of contamination risk maps of Shahrekord aquifer by using GIS and DRASTIC and SINTACS models. Master Thesis. University of Shahrekord. (In Persian). Nadiri AA, Gharekhani M, Khatibi R, Sadeghfam S, Asghari Moghaddam A. 2017a. Groundwater vulnerability indices conditioned by Supervised Intelligence Committee Machine (SICM). Sci. Total Environ. 574: 691–706. Nadiri AA, Sedghi Z, Khatibi R, Gharekhani M. 2017b. Mapping vulnerability of multiple aquifers using multiple models and fuzzy logic to objectively derive model structures. Science of the Total Environment. 593–594: 75–90. Nadiri AA, Gharekhani M, Khatibi R. 2018. Mapping aquifer vulnerability indices using artificial intelligence-running multiple frameworks (AIMF) with supervised and unsupervised learning. Water Resour. Manage. 32(9): 3023–3040. Niknam R, Mohammadi K, Majd VJ. 2007. Groundwater Vulnerability Evaluation of Tehran-Karaj Aquifer Using DRASTIC Method and Fuzzy Logic. Iran-Water Resources Research. 3(2): 39–47. (In Persian). Oroji B. 2018. Groundwater vulnerability assessment using GIS-based DRASTIC and GOD in the Asadabad plain. Journal of Materials and Environmental Sciences. 9(6): 1809–1816. Panagopoulos G, Antonakos A, Lambrakis N. 2006. Optimization of DRASTIC model for groundwater vulnerability assessment, by the use of simple statistical methods and GIS. Journal of Hydrogeology. 14(6): 894–911. Rahman A. 2008. A GIS based DRASTIC model for assessing groundwater vulnerability in shallow aquifer in Aligarh India. Applied Geography. 28(1): 32–53. Regional Water Company of West Azarbaijan. 2012a. Semi-detailed studies of groundwater plain covered by West Azarbaijan water organization, Groundwater Studies in Urmia Plain. (In Persian). Regional Water Company of West Azarbaijan. 2012b. Water resource inventory updating studies, Study Areas of Lake Urmia Basin, Leading to the Years 2011–2012, Vol. 5: Appendix 10. (In Persian). Rezaei F, Safavi HR, Ahmadi A. 2013. Groundwater vulnerability assessment using fuzzy logic: a case study in the Zayandehrood aquifers, Iran. Environmental management. 51(1): 267–277. Sadatipoor E, Noori N, Baghvand A, Javadi Pirbazari S, Kardan Moghaddam H. 2016. Application of DRASTIC Model for groundwater vulnerability assessment of the Ghaen Aquifer. Journal of Environmental Sciences Studies. 1(2): 63–71. (In Persian). Sadeghi Aghdam F, NadiriAA, Asgharai Moghaddam A, Abbas Novinpour E. 2019. Assessing the suitability and quality zoning of groundwater resources of Naqadeh plain for drinking, agriculture, and industrial purposes. RS and GIS for Natural Resources. 9(4): 17–36. (In Persian). Scanlon BR, Healy RW, Cook PG. 2002. Choosing appropriate techniques for quantifying groundwater recharge. Hydrogeology Journal. 10(1): 18–39. Secunda S, Collin ML, Melloul AJ. 1998. Groundwater vulnerability assessment using a composite model combining DRASTIC with extensive agricultural land use in Israel's Sharon region. Journal of Environmental Management. 54(1): 39–57. Sharadqah S. 2017. Contamination risk evaluation of groundwater in the canton of portoviejo-ecuador, using Susceptibility Index and two intrinsic vulnerability models. American Journal of Environmental Sciences. 13(1): 65–76. Shekhar Sh, Chandra A. Pandey. 2014. Delineation of groundwater potential zone in hard rock terrain of India using Remote Sensing, Geographical Information System (GIS) and Analytic Hierarchy Process (AHP) techniques. Geocarto International. 30(4): 402-421. Stigter TY, Ribeiro L, Carvalho Dill AMM. 2006. Evaluation of anintrinsic and a specific vulnerability assessment method in comparison with groundwater salinisation and nitrate contamination levels in two agricultural regions in the south of Portugal. Journal of Hydrogeology. 14(1): 79–99. Tidoune, PBD Ndao, S Ba A, Dlaw EHB. 2017. Assessment of groundwater vulnerability by Susceptibility Index (SI) method in the Niayes Area, Senegal. Journal of Scientific and Engineering Research. 4(11): 247–257. Urmia Novin water drilling company. 2006. Exploration and exploitation geological log, Urmia water affairs department. (In Persian). Vrba J, Zaporozec A. 1994. Guidebook on mapping groundwater vulnerability. International Contributions to Hydrogeology, 16. FRG, Heise Publication, Hannover. 131p. | ||
|
آمار تعداد مشاهده مقاله: 785 تعداد دریافت فایل اصل مقاله: 934 |
||