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تحلیل روند تغییرات کیفیت آب زیرزمینی با شاخص کیفی آب زیرزمینی (منطقه مورد مطالعه: آبخوان قزوین)

نوع مقاله : مقاله پژوهشی

نویسندگان

1 گروه علمی مدیریت ساخت و آب، واحد علوم و تحقیقات، دانشگاه آزاد اسلامی، تهران، ایران.

2 مؤسسه تحقیقات آب، وزارت نیرو، تهران، ایران.

3 دانشکده تحصیلات تکمیلی محیط زیست، دانشگاه تهران، تهران، ایران

10.22077/jaaq.2025.9864.1120

چکیده

شاخص کیفیت آب زیرزمینی (GWQI) برای ارزیابی کیفیت آب‌های زیرزمینی و مناسب بودن آن برای اهداف مختلف استفاده می‌‌شود. این شاخص توسط یکپارچه سازی داده‌ها و تولید یک عدد که بیانگر کلی کیفیت آب است بکار می‌رود. در این تحقیق تغییرات کیفیت آب زیرزمینی در آبخوان قزوین در یک دوره 15 ساله منتهی به سال 1400 با استفاده از GWQI مورد بررسی قرار گرفت. برای این منظور طیف وسیعی از پارامترهای شیمیایی آب شامل Na ,K، Mg، Ca، SO4، Cl، HCO3، pH، TDS، EC و TH استفاده شدند. نتایج نشان می‌دهد که حداقل مقدار GWQI از 6/18 تا 2/24 و مقدار حداکثری آن از 1/118 تا 2/205 متغیر بود. در میان پارامترهای کیفی EC و K به ترتیب بیشترین و کمترین تاثیر را در مقدار GWQI داشتند. نتایج آزمون روند من کندال نیز نشان دهنده عدم وجود یک روند معنادار در شاخص GWQI بود. همچنین آنالیز مکانی نتایج نشان داد که محدوده مینیمم GWQI در قسمت شمال و شمال غرب آبخوان و محدوده ماکزیمم آن در غرب آبخوان قرار داشتند. ذکر این نکته ضروریست که محدوده جغرافیایی مربوط به مینیمم GWQI بسیار گسترده تر از محدوده ماکزیمم آن بود که نشان دهنده کیفیت مناسب آب زیرزمینی در اکثر نواحی بود.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

Trend Analysis of Groundwater Quality Changes Using Groundwater Quality Index (Study Area: Ghazvin Aquifer)

نویسندگان [English]

  • Mohammad Mofidi 1
  • Farhad Hooshyaripor 1
  • Hamid Kardan moghaddam 2
  • Roohollah Noori 3

1 Department of Civil Engineering, SRC, Islamic Azad University, Tehran, Iran.

2 Water Research Institute, Ministry of Energy, Tehran, Iran.

3 Graduate Faculty of Environment, University of Tehran, Tehran, Iran

چکیده [English]

The Groundwater Quality Index (GWQI) is used to assess the quality of groundwater and its suitability for various purposes. This index is employed by integrating data and generating a single number that reflects the overall quality of the water. In this study, changes in groundwater quality in the Qazvin aquifer were examined using GWQI over a 15-year period ending in 2021. In this regard, we used a wide range of water chemistry parameters, including Na, K, Mg, Ca, SO4, Cl, HCO3, pH, TDS, EC, and TH. The results showed that the minimum GWQI value ranged from 6.18 to 2.24, while the maximum value ranged from 1.118 to 2.205. Among the water chemistry parameters, EC and K had the highest and lowest impact on the GWQI value, respectively. The results of the Mann-Kendall trend test also indicated no significant trend in the GWQI index. Spatial analysis of the results revealed that the minimum values of GWQI were located in the northern and northwestern parts of the aquifer, while the maximum values were found in the western part of the aquifer. It is essential to note that the geographic area corresponding to the minimum GWQI values were much broader than that of the maximum values, indicating suitable groundwater quality in most regions.

کلیدواژه‌ها [English]

  • Groundwater
  • Qazvin aquifer
  • Water Quality
  • Trend analysis
  • GWQI
مراجع
Adepelumi, A., Ako, B.D., Ajayi, T.R., Afolabi, O. & Omotoso, E.J. (2007). Delineation of saltwater intrusion into the freshwater aquifer of Lekki Peninsula, Lagos, Nigeria, Environ. Geol., 56(5), 927–933. https://doi.org/10.1007 / s00254-008-1194-3.
Alijani, B., Mahmoudi, P. & Chogan, A. (2012). A Study of Annual and Seasonal Precipitation Trends in Iran Using a Nonparametric Method (Sen’s Slope Estimator), Journal of Climate Research. 3(9), 106-105. SID. https://sid.ir/paper/401943/en. (In Persian)
Barani, N. & Karami, A. (2019). Annual trend analysis of climate parameters of temperature and precipitation in decuple agroecology regions of Iran, Environmental Sciences 17(4), 75-90. https://doi.org/10.29252/envs.17.4.75. (In Persian)
Dashti, M., Rezaie, M. & Saberi Nasr, A. (2013). Evaluation of groundwater quality index in the Lenjanat Aquifer using geographic information system, Journal of Geology Engineering. 8(2), 2121-2138. http://jeg.khu.ac.ir/article-1-416-en.html. (In Persian)
El-Zeiny, A.M. & Elbeih, S.F. (2019). GIS-based evaluation of groundwater quality and suitability in Dakhla Oases, Egypt, Earth Syst. Environ., 3, 507-523. https://doi.org/10.1007/s41748-019-00112-1.
Eslami, F., Shokoohi, R., Mazloomi, S., Darvish Motevalli, S, & Salari, M. (2016). Evaluation of Water Quality Index of Groundwater Supplies in Kerman Province, Journal of Occupational and Environmental Health. 3(1), 48-58. https://hsenk.ir/?p=8178. (In Persian)
Faryabi, M. & Shojaheidari, R. (2019). Assessment of Groundwater Quality of Jiroft plain for drinking water using Groundwater Quality Index. Human and environment, 1(60), 183-197. https://sid.ir/paper/1043293/en. (In Persian)
Fazelifard, M. (2022). Assessment of aquifer vulnerability using meta-heuristic methods and GWQI index (case study: Varamin Aquifer, Tehran, Iran), MSc. dissertation. Water Resources Engineering, University of Tehran, Iran. (In Persian)
Gong, G., Mattevada, S., & O’Bryant, S.E. (2014). Comparison of the accuracy of kriging and IDW interpolations in estimating groundwater arsenic concentrations in Texas, Environ. Res., 130, 59-69. https://doi.org/10.1016/j.envres.2013.12.005
 
 
 
Gong, G., Mattevada, S., & O’Bryant, S.E. (2014). Comparison of the accuracy of kriging and IDW interpolations in estimating groundwater arsenic concentrations in Texas, Environ. Res., 130, 59-69. https://doi.org/10.1016/j.envres.2013.12.005
Hoseini, S.Z., Shahidi, A. & Hanafi, H. (2024). Investigating Spatial and Temporal Changes of Quantitative Parameters of Underground Water Resources Using Inverse Distance Weighting Interpolation Method (Case Study: Mashhad Plain), Journal of Aquifer and Qanat, 4(2), 103-114. https://doi.org/10.22077/jaaq.2024.7330.1064. (In Persian)
Kaheh, M., Kardan Moghaddam, H., Ramezani, M. & Javadi, S. (2022), Evaluation of groundwater quality of aquifer based on agricultural consumption (Case study: Sari aquifer), Journal of Aquifer and Qanat, 3(2), 89-97. https://doi.org/10.22077/jaaq.2019.1736.1009. (In Persian)
Kardan Moghaddam, H. & Akbarzadeh, A. (2025). Evaluating climatic periods in predicting subsidence rates using numerical modeling (Case study: Najafabad aquifer), Eco Hydrology Journal, 11(4), 511-526. https://doi.org/10.22059/ije.2025.386827.1855. (In Persian)
Khouni, I., Louhichi, G. & Ghrabi, A. (2021). Use of GIS-based Inverse Distance Weighted interpolation to assess surface water quality: Case of Wadi El Bey, Tunisia, Environmental Technology & Innovation, 24, 101892. https://doi.org/10.1016/j.eti.2021.101892.
Jodhani, K.H., Gupta, N., Dadia, S., Patel, H., Patel, D., Jamjareegulgarn, P., Singh, S K & Rathnayake, R. (2025). Sustainable groundwater management through water quality index and geochemical insights in Valsad, India, Sci Rep., 15 (1), 8769. https://doi.org/10.1038/s41598-025-92053-1.
Mehrabinejad, A., Kalantari, N., Alijani, F., Mousavi, S.F., & Mohammadi, H. (2025). Nitrate Pollution of the Izeh Urban Aquifer: Health Risks and Local Management, Journal of Aquifer and Qanat, 5(2), 203-220. https://doi.org/10.22077/jaaq.2025.9299.1111. (In Persian)
Mirzaei, R. & Sakizadeh, M. (2016). Comparison of interpolation methods for the estimation of groundwater contamination in Andimeshk-Shush Plain, Southwest of Iran, Environ. Sci. Pollut. Res., 23(3), 2758-2769. https://doi.org/10.1007/s11356-015-5507-2. (In Persian) `
Mirzavand, M., Sadatinejad, S.J. & Kardan Moghaddam, H. (2025). Assessment of Groundwater Quality Affected by Saltwater Intrusion and Theoretical Mixing Ratio Calculation of Saline and Fresh Groundwater, Journal of Aquifer and Qanat, 5(2), 63-78. https://doi.org/10.22077/jaaq.2025.9007.1102. (In Persian)
Modou M., EL Hammoudani Y., Dimane F., Haboubi K., Achouki I., EL Boudammoussi M., Faiz H. et Touzani A. (2024). Application of the water quality index (IQEs) to assess the quality of groundwater in the Ghiss-Nekkour aquifer, Al-Hoceima, Northern Morocco. BIO Web of Conferences 109, 01018 (2024).
Mohammadi, B. (2010). Trend Analysis of annual rainfall over Iran. Journal of Geography and Environmental Planning. .22(3), 95-106. https://doi.org/20.1001.1.20085362.1390.22.3.6.1. (In Persian)
Moradzadeh, M. & Pourhosein, H. (2024). Assessment of Sudden Drought and Flood Occurrence (Case Study of the Karun River Basin). Environmental Sciences Studies. 9(4), 9379-9389. https://doi.org/10.22034/jess.2024.433131.2201. (In Persian)
Noori, R., Hooshyaripor, F., Javadi, S., Dodangeh, M., Tian, F., et al. (2020). PODMT3DMS-Tool: Proper orthogonal decomposition linked to the MT3DMS model for nitrate simulation in aquifers, Hydrogeology Journal 28 (3), 1125-1142. https://doi.org/10.1007/s10040-020-02114-0.
Ostovari, Y., Beigi-Harchegani, H. & Davooudian, A. (2014). Assessment of Groundwater Quality Index (GWQI) and its Geostatistical Analysis in Lordegan Plain Aquifer. J. Env. Sci. Tech., 19(2), 227-238. https://www.magiran.com/p1804345. (In Persian)
Panhalakr, S.S. & Jarag, A.P. (2016). Assessment of spatial interpolation techniques for river bathymetry generation of Panchganga River basin using geoinformatic techniques, Asian J. Geoinform., 15(3), 9-15.
Paul, R., Brindha, K., Gowrisankar, G., Tan, M.L. & Singh, M.K. (2019). Identification of hydrogeochemical processes controlling groundwater quality in Tripura, Northeast India using evaluation indices, GIS, and multivariate statistical methods, Environ. Earth Sci., 78(15), 470. https://doi.org/10.1007/s12665-019-8479-6.
Pouramini, T., Fotouhi Firoozabad, F., & Barkhordari, J. (2024). Performance Investigation of Flood Spreading System on the Groundwater Quality, Environ. Water Eng., 10(2), 212-226. https://doi.org/10.22034/ewe.2023.409401.1883
Qiao, P., Lei, M., Yang, S., Yang, J., Guo, G. & Zhou, X. (2018). Comparing ordinary kriging and inverse distance weighting for soil as pollution in Beijing, Environ. Sci. Pollut. Res., 25, 15597-15608. https://doi.org/10.1007/s11356-018-1552-y.
Salarijazi, M., Ahmadianfar, I. & Yaseen, Z.M. (2024). Prediction enhancement for surface water sodium adsorption ratio using limited inputs: Implementation of hybridized stacked ensemble model with feature selection algorithm, Physics and Chemistry of the Earth, Parts A/B/C, 134, 103561. https://doi.org/10.1016/j.pce.2024.103561.
Sarvi Sadrabad, H. & Zare-Chahouki, A. (2022). Study of the Efficiency of Groundwater Quality Index to Evaluate the Long-term Effects of Inter-Basin Water Transfer Using Non-Parametric Methods and GIS (Case Study: Yazd-Ardakan Aquifer). Journal of Water and Soil. 35(6), 791-804. https://doi.org/10.22067/jsw.2021.71571.1073. (In Persian)
Shuaibou, A., Kalin, R.M., Phoenix, V., Banda, L.C. & Lawal, I.M. (2024). Hydrogeochemistry and Water Quality Index for Groundwater Sustainability in the Komadugu-Yobe Basin, Sahel Region, Water, 16(4), 601. https://doi.org/10.3390/w16040601.
Shanmugam, P. & Ambujam, N.K. (2012). A Hydrochemical and Geological Investigation on the Mambakkam Mini Watershed, Kancheepuram District, Tamil Nadu. J. Environmental Monitoring and Assessment May, 184(5), 3293-306. https://doi.org/10.1007/s10661-011-2189-1.
Soleimani, S., Mahmoodi Gharaie, M.H., Ghasemzadeh, F. & Sayareh, A. (2013). Investigation on Water Resources Quality by Application of GQI Index and GIS in the West of Kooh-Sorkh. Earth science, 23(89), 175-182. https://doi.org/10.22071/gsj.2013.53601. (In Persian)
Turgay, P. & Ercan, K. (2005). Trend Analysis in Turkish Precipitation Data. Hydrological processes, 29(9), 2011-2026. https://doi.org/10.1002/hyp.5993.
WHO (World Health Organization) (2017). Guidelines for drinking-water quality: small water supplies, fourth edition incorporating the first and second addenda, https://www.who.int/publications/i/item/9789240045064
Zhou, X., Leng, Y., Salarijazi, M., Ahmadianfar, I. & Farooque, A.A. (2024). Development of forecasting of monthly SAR time series in river systems: A multivariate data decomposition-based hybrid approach, Process Safety and Environmental Protection, 188, 1355-1375. https://doi.org/10.1016/j.psep.2024.06.050
آبخوان و قنات
دوره 6، شماره 1 - شماره پیاپی 10
شهریور 1404
صفحه 107-130
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