| تعداد نشریات | 286 |
| تعداد نشریات سازمان | 84 |
| تعداد شماره‌ها | 3,020 |
| تعداد مقالات | 33,742 |
| تعداد مشاهده مقاله | 44,987,207 |
| تعداد دریافت فایل اصل مقاله | 47,280,896 |
پهنه بندی آسیب پذیری آبخوان شهرستان البرز استان قزوین به روش دراستیک و سامانۀ اطلاعات جغرافیایی | ||
| تحقیقات مهندسی سازه های آبیاری و زهکشی | ||
| دوره 26، بهار - شماره پیاپی 98، اردیبهشت 1404، صفحه 122-105 اصل مقاله (1.08 M) | ||
| نوع مقاله: مقاله پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22092/idser.2025.369519.1621 | ||
| نویسندگان | ||
| حسین آتشگران1؛ معصومه رستم آبادی* 2؛ سعید کاظمی محسن آبادی3 | ||
| 1دانشجوی کاشناسی ارشد مهندسی آب و سازه های هیدرولیکی، دانشگاه آزاد اسلامی واحد بوئین زهرا، بوئین زهرا، ایران | ||
| 2گروه مهندسی عمران، ,واحد بوئین زهرا، دانشگاه آزاد اسلامی، بوئین زهرا، ایران | ||
| 3گروه مهندسی عمران، واحد بوئین زهرا، دانشگاه آزاد اسلامی، بوئین زهرا، ایران | ||
| چکیده | ||
| منبع ارزشمند آب زیرزمینی که تامین کننده اصلی مصارف کشاورزی، شرب و صنعتی است، تحت تأثیر آلودگی ناشی از آبهای برگشتی آبیاری آغشته به کودهای نیتراتی، فاضلاب شهری و روستایی و پساب‌های صنعتی است. در دشت شهرستان البرز، از قطبهای بزرگ توسعۀ کشاورزی و صنعتی، هر ساله شهرکهای متعدد ساخته میشود و جمعیت انسانی و تقاضای آب در آن رو به افزایش است. سالانه حجم بالایی از آلایندهها از جمله نیترات به دلیل اجرانشدن سامانۀ مناسب دفع پساب‌ها وارد آبخوان این دشت میشود. هدف از این پژوهش، علاوه بر مشخص کردن مناطق مستعد آلوده‌شدن، کمک به تبیین سیاستهای کاربردی برای برنامهریزی و مدیریت محیط زیست منطقه و مدیریت کیفی منابع آب زیرزمینی است. بدین منظور با مراجعه به سازمان‌های متعدد، آمار و دادههای عمق سطح ایستابی، تغذیۀ خالص، ساختار زمین‌شناسی آبخوان، بافت خاک، شیب منطقه، محیط غیراشباع، قابلیت انتقال و همضخامت آبرفت این آبخوان جمعآوری شد. پس از آن با استفاده از روش دراستیک بر مبنای سامانۀ اطلاعات جغرافیایی، نقشه پهنهبندی آسیب‌پذیری آبخوان (امکان نفوذ و انتشار آلایندهها از سطح زمین به آب زیرزمینی) تهیه و با اطلاعات موجود نیترات آب زیرزمینی در محیط GIS مقایسه و صحتسنجی شد. نتایج بررسیها نشان داد دشت شهرستان البرز به دو پهنه قابل طبقه‌بندی است. حدود 31 درصد از مساحت کل منطقه متعلق به کلاس آسیب‌پذیری کم و 69 درصد از مساحت در کلاس آسیب‌پذیری متوسط قرار دارد. قسمت غربی و مرکزی آبخوان دشت شهرستان البرز به دلیل اینکه شیب زمین، در این نواحی بسیارکم و سطح آب زیرزمینی بالا است، پتانسیل آسیب‌پذیری بیشتری دارد. | ||
| کلیدواژه‌ها | ||
| آسیب پذیری؛ دشت شهرستان البرز؛ دراستیک؛ سیستم اطلاعات جغرافیایی | ||
| عنوان مقاله [English] | ||
| Vulnerability zoning of the Alborz County of Qazvin Province aquifer using DRASTIC method and GIS | ||
| نویسندگان [English] | ||
| Hosein Atashgaran1؛ Massumeh Rostamabadi2؛ Saeed Kazemi Mohsenabadi3 | ||
| 1MSc student of water and hydraulic structures engineering, Islamic Azad University, Buin Zahra Branch, Buin Zahra | ||
| 2Department of Civil Engineering, BuZ. C., Islamic Azad University, BuinZahra , Iran. | ||
| 3Department of Civil Engineering, BuZ. C. Islamic Azad University, BuinZahra, Iran | ||
| چکیده [English] | ||
| Introduction Groundwater resources, as the main supplier of agricultural, drinking and industrial uses, are affected by polluting factors such as irrigation return water, urban and rural wastewater, and industrial effluents. Alborz County, one of the important agricultural and industrial regions of Qazvin Province, is at risk of groundwater pollution due to its increasing development and population. Due to the lack of implementation of appropriate wastewater disposal systems, a large volume of pollutants, including nitrate, enter the aquifer of this plain. The aim of this study is to investigate the vulnerability of the Alborz County aquifer using the DRASTIC method and to utilize the Geographic Information System (GIS) to determine areas susceptible to pollution and to provide management solutions to maintain the quality of groundwater resources. Materials and Methods Geographical Location Alborz County is located in the northeast of Qazvin Province with an area of about 428 square kilometers. The county borders Qazvin County to the north, Abyeq County to the east, Abyek and Buin Zahra County to the south, and Qazvin County to the west. This region is heavily affected by environmental pressures due to industrial and agricultural development. DRASTIC Model The DRASTIC method, introduced by the US Environmental Protection Agency, focuses on assessing groundwater vulnerability using seven key parameters: depth of groundwater (D), net recharge (R), aquifer media (A), soil media (S), topography (T), Impact of vadoes zone (I), Hydraulic conductivity of the aquifer (C). A rate value and a weight were determined for each of these parameters based on table (1), and then these data were processed in ARCGIS software to prepare a vulnerability map of the region. Table 1- Drastic parameter weight and rate table for Alborz County C I T S A R D Parameter 3 5 1 2 3 4 5 Weight 1--4 5--6 8--10 4--7 6--8 6--9 1--2 Rate The vulnerability index (DI) was calculated based on the combination of these factors according to equation (1) and levels of vulnerability were identified. Based on the analysis, the vulnerability index of the Alborz County plain varies between 87 and 136. According to the Drastic classification, the study area is divided into two zones of low vulnerability (31 percent) and medium vulnerability (69 percent). The western and central areas of the aquifer have the highest vulnerability potential due to the high groundwater level and low land slope and require more monitoring. To examine the accuracy of the vulnerability zoning map, the nitrate level of groundwater in the area was examined. The results showed that areas with higher vulnerability have higher nitrate concentrations, indicating a direct relationship between the vulnerability index and groundwater quality. The most important polluting factor in this area is the excessive use of chemical fertilizers and the lack of urban wastewater treatment systems. In order to assess the effect of different parameters on the vulnerability index, a sensitivity analysis of layer removal was performed. The results showed that the most important parameters affecting vulnerability are Impact of vadoes zone (I) and net recharge (R). Removing these factors caused significant changes in the vulnerability index, indicating their critical role in the transfer of contaminants to groundwater. Conclusion This research, by providing vulnerability maps, provides an important tool for planning and managing groundwater resources in Alborz County and will assist officials in major environmental and executive decisions. The results showed that Alborz County has areas with a moderate level of vulnerability, and the western and central parts of the aquifer should be considered as critical areas. Accordingly, the following suggestions are made: Management of chemical fertilizer use: Modifying the cropping pattern and monitoring the use of nitrate fertilizers in order to reduce the transfer of contaminants to groundwater. Implementation of urban and rural wastewater treatment projects: To prevent the entry of contaminated wastewater into groundwater resources. Monitoring well drilling in vulnerable areas: Preventing hydraulic communication between contaminated and uncontaminated aquifers. Accurate monitoring of groundwater quality: Implementing continuous monitoring systems to control and manage groundwater pollution. | ||
| کلیدواژه‌ها [English] | ||
| Vulnerability, Alborz Plain, DRASTIC, GIS | ||
| مراجع | ||
|
Aghazadeh, N., Chitsazan, M., Mirzaee, Y. & Ebrahimi, H. (2022). Modifying DRASTIC Model DRAST-VUL to determine groundwater vulnerability in an urban aquifer. Watershed Engineering and Management, 13(4), 690-703. doi: 10.22092/ijwmse.2021.125064.1596. (In Persian). Ahmed, I. & Nazzal., Y. )2015(. Hydrogeological vulnerability and pollution risk apping of the Saq and overlying aquifers using the DRASTIC model and GIS techniques, NW Saudi Arabia. Environment Earth Science.64: 342-356. Aller, L., T. Bennet, J.H. Lehr, R.J. Petty, & G. Hackett. )1987(. DRASTIC: a standardized system for evaluating groundwater pollution potential using hydrogeological settings. EPA/600/2–87/035. US Environmental Protection Agency, Ada, OK, USA. Amirahmadi, A., Abbariki, Z. & Ebrahimi, M. (2022). Evaluation of the vulnerability of Davarzan Aquifer by DRASTIC method using GIS. Journal of Arid Regions Geographic Studies, 2(6), 51-66. (In Persian). Amiri F., Tabatabaie, T., & Entezari M. )2020(. GIS based DRASTIC and modified DRASTIC techniques for assessing groundwater vulnerability to pollution in Torghabeh-Shandiz of Khorasan County, Iran. Arabian Journal of Geosciences, 13(12): 1-16. doi:https://doi.org/10.1007/s12517- 020-05445-0. Babiker, IS., Mohamed, MAA., & Hiyama,T. )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. Bera, A., Mukhopadhyay, BP., Chowdhury, P., Ghosh, A., & Biswas, S. )2021(. Groundwater vulnerability assessment using GIS-based DRASTIC model in Nangasai River Basin, India with special emphasis on agricultural contamination. Ecotoxicology and Environmental Safety, 214: 112085. Bhuvaneswaran, C., & Ganesh, A. )2019(. Spatial assessment of groundwater vulnerability using DRASTIC model with GIS in Uppar odai subwatershed, Nandiyar, Cauvery Basin, Tamil Nadu. Groundwater for Sustainable Development, 9:100270. doi:https://doi.org/10.1016/j.gsd.2019.100270. Chitsazan, M., & Akhtari, Y. (2009). A GIS-based DRASTIC Model for Assessing Aquifer Vulnerability in Kherran Plain, Khuzestan, Iran. Water Resource Management, 23, 1137–1155. doi.org/10.1007/s11269-008-9319-8. Dixon B. (2005). Applicability of neuro-fuzzy techniques in predicting groundwater vulnerability: a GIS-based sensitivity analysis. Journal of Hydrology. 309(1–4):17–38. https://doi.org/10.1016/j.jhydrol.2004.11.010. Fathie, H. A.& Beygi, H. H. (2012). Zoning the vulnerability potential of Shahrekord aquifer using the DRASTIC model and its validation using seasonal changes in nitrate and phosphate pollutant concentrations. Water Resources Engineering, 5(14), 1-16. Doi: 20.1001.1.20086377.1391.5.14.1.6 (In Persian). Ganwer, S., Sinha, M. Multaniya, A., & Ghodichore, N. (2024). Introducing reverse Multi Influencing Factor technique in DRASTIC model for groundwater vulnerability assessment. Groundwater for Sustainable Development, Volume 25, 101106. https://doi.org/10.1016/j.gsd.2024.101106. Hamed Masoud, H., Dara Rebwar, N., & Kirlas Marios, C. (2024). Groundwater vulnerability assessment using a GIS-based DRASTIC method in the Erbil Dumpsite area (Kani Qirzhala), Central Erbil Basin, North Iraq. Journal of Groundwater Science and Engineering, 12(1): 16-33. doi: 10.26599/JGSE.2024.9280003. Jokar Niasar, V. (2002). Investigation and estimation of nitrate transfer from absorbent wells to the groundwater surface in Tehran, Master's thesis, Sharif University of Technology. (In Persian). Krishna, R., Iqbal., J., & Gorai, A.K. (2015). Groundwater vulnerability to pollution mapping of Ranchi district using GIS. Applied Water Science 5, 345–358. https://doi.org/10.1007/s13201-014-0198-2. Lathamani, M.R., Janardhana, B., Mahalingam, S., & Suresha. (2015). Evaluation of Aquifer Vulnerability Using Drastic Model and GIS: A Case Study of Mysore City, Karnataka, India, Aquatic Procedia. 4, Pages 1031-1038, doi.org/10.1016/j.aqpro.2015.02.130. Mardan, H., & Yargholi, B. (2020). Ardabil Alluvial Plain Aquifer Vulnerability Zoning Using a Combination of GIS and DRASTIC Method. Journal of Environmental Science and Technology, 22(6(97)), 391-406. (In Persian). Moradinejad, T., Rezaei, M., & Nakhaei, M. (2023). Vulnerability Assessment of Groundwater Resources in Qazvin Aquifer with DRASTIC, Modified and Fuzzy Methods. Journal of Drought and Climate Change Research, 1(3), 35-56. doi: 10.22077/jdcr.2023.6186.1020. (In Persian). Nakhostin Rouhi, M., Rezaei Moghaddam, M. H., & Rahimpour, T. (2017). Groundwater vulnerability zonation using DRASTIC and SI models in GIS (Case Study: Ajabshir Plain). Journal of Eco hydrology, 4(2), 587-599. doi: 10.22059/ije.2017.61496. (In Persian). Novinpour, E.A., Moghimi, H., & Kaki, M. (2022). Aquifer vulnerability based on classical methods and GIS-based fuzzy optimization method (case study: Chahardoli plain in Kurdistan province, Iran). Arabian Journal of Geoscience 15, 360 (2022). doi.org/10.1007/s12517-022-09549-7. Ozegin, K., Ilugbo, S. & Adebo, B. (2024). Spatial evaluation of groundwater vulnerability using the DRASTIC-L model with the analytic hierarchy process (AHP) and GIS approaches in Edo State, Nigeria. Physics and Chemistry of the Earth, Parts A/B/C, Volume 134 103562, doi.org/10.1016/j.pce.2024.103562. Pourbalighy, M., Rezayan, S., Rafaty, M, & hejazi, R. (2022). Evaluation of groundwater vulnerability of aquifers in aisin plain by drastic and GODS models and GIS. Journal of RS and GIS for natural resources, 12(4 (45), 71-94. (In Persian). Rahman, A. (2008). A GIS based model for assessing groundwater vulnerability in shallow aquifer in Algarh, India. Applied Geography, 28(1):32–53. Rangzan, k., Firouzabadi, P, Mirzaei, & Alijani, f. (2008). Mapping of groundwater vulnerability using drastic and empirical assessment of unsaturated zone in gis, varamin plain. Iranian journal of geology, 2(6), 21-32. (In Persian). Sarcheshmeh, B. & Shahmohammadi-Kalalagh, S. (2017). Evaluation of Salmas Plain Aquifer Vulnerability to Pollution Using DRASTIC Model and GIS. Water and Soil Science, 26(4.2), 55-67. (In Persian). Taheri Tizro, A., Qaleban Tgmedash, M., & Farajy, F. (2021). Vulnerability evaluation of Qazvin Plain Using DRASTIC-AHP Based on Geographic Information System. Journal of Natural Environmental Hazards, 10(29), 145-160. doi: 10.22111/jneh.2020.34024.1659. (In Persian). Vrba J., & Zoporozec A. (1994). Guidebook on mapping groundwater vulnerability. International Contributions to Hydrogeology. Verlag Heinz Heise GmbH and Co, KG. Yazdani, V., & Mansourian, H. (2019). The assessment vulnerability of Qazvin-plain aquifer, sensitivity analysis removing parameters by using GIS. Irrigation and Water Engineering, 10(2), 127-145. doi: 10.22125/iwe.2019.100746. (In Persian). | ||
|
آمار تعداد مشاهده مقاله: 52 تعداد دریافت فایل اصل مقاله: 51 |
||