نشریه مهندسی عمران امیرکبیر

نشریه مهندسی عمران امیرکبیر

ارزیابی روش‌های زمین‌آماری در بررسی کیفیت آب‌های زیرزمینی دشت مشگین شهر با استفاده از شاخص‌WQI

نوع مقاله : مقاله پژوهشی

نویسنده
گروه علوم و مهندسی آب، دانشکده کشاورزی و منابع طبیعی، دانشگاه محقق اردبیلی، اردبیل، ایران
چکیده
در این تحقیق کیفیت آب زیرزمینی دشت مشگین بر اساس شاخص WQI و استفاده از روش های زمین آماری، مورد بررسی قرار گرفت. همان‌طور که نتایج و آماره‌های ارزیابی به روش کوکریجینگ نشان داد، واریوگرام‌ متغیر تصادفی شاخصWQI و متغیر کمکی هدایت الکتریکی از مدل نمایی با اثر قطعه‌ای به ترتیب برابر (0/02) و (0/05) بود. همچنین، سقف واریوگرام برای متغیر WQI برابر (0/77) و برای متغیر کمکی هدایت الکتریکی برابر (0/8)، به دست آمد که نشان دهنده نقش موثر مؤلفة ساختاردار واریوگرام نسبت به مؤلفة بی‌ساختار آن است و استحکام ساختار فضایی منطقه برای هر دو متغیر تصادفی شاخصWQI و هدایت الکتریکی را بیان میکند. نتایج نشان داد، روش‌های مبتنی بر زمین آمار و کوکریجینگ ساده، با مقدار ضریب تبیین 0/85 و مجذور میانگین مربعات خطا برابر 3/27برآورد دقیقی از متغیر تصادفی شاخص WQI دارد. بطور کلی می‌توان گفت ارزیابی به روش کوکریجینگ نشان داد، شاخص WQI در سطح منطقه عموما در سطح صفر تا صد متغیر بوده و از نظر کیفی در محدوده "عالی" و " خوب" می باشد و بیش از 96 درصد منطقه مورد مطالعه از کیفیت مناسبی برای مصارف شرب برخوردار است. نتایج این تحقیق نشان داد که برآوردهای زمین آماری در تعیین شاخصWQI در سطح مناطق، مخصوصا در مناطقی که در آ‌‌‌ن‌ها، برداشت آب برای مصارف آشامیدنی انجام می‌شود به دلیل دقت بالای این روش، از اهمیت بالایی برخوردار است.
کلیدواژه‌ها
موضوعات

عنوان مقاله English

Assessment of Geostatistical Methods in Groundwater Quality Evaluation of Mashginshahr Plain Using WQI Index

نویسنده English

Yaser Hoseini
Department of Water Science and Engineering, Faculty of Agriculture and Natural Resources, University of Mohaghegh Ardabili, Ardabil, Iran
چکیده English

In this study, the groundwater quality of the Meshgin Plain was investigated based on the WQI index and using geostatistical methods. As the results and evaluation statistics of the cokriging method showed, the variogram of the random variable WQI index from the exponential model had a nugget effect (0.02) for the WQI index and (0.05) for the auxiliary variable electrical conductivity. the sill of the variogram for the WQI variable was (0.7) and for the auxiliary variable electrical conductivity was (0.77), which indicates that the role of the structured component of the variogram is greater than the role of its unstructured component, and this indicates the strength of the spatial structure of the region for both the random variables WQI index and electrical conductivity at the regional level. The results showed that geostatistical methods and simple cokriging model, with a coefficient of determination of 0.85 and a root mean square error of 3.27, has an accurate estimate of the WQI random variable. In general, it can be said that the evaluation using the kriging method shows that the WQI index at the regional level is generally at the level of 0-100 and is in the "Excelent" and "Good" quality range, and more than 96 percent of the studied area has good quality for drinking purposes. The results of this study showed that geostatistical estimates are of great importance in determining the WQI index at the regional level,

کلیدواژه‌ها English

Groundwater Quality
Geostatistics
WQI Index
GIS
Plain
[1]    M. Pashaei Far, R. Dehghanzadeh, M.E. Ramazani, O. Rafieian, A. Najayi, Assessment of hydrogeochemical processes and groundwater quality using WQI, graphical methods, and multivariate statistical analyses: Case study of Shabestar plain, Journal of Water Resources Engineering, 16(56) (2023) 15–30 (in Persian).
[2]    M. Mirshkari, M. Tabatabai, R.H. Mohammadi, Assessment of spatial and temporal groundwater quality variations in Seydan-Farouq plain for agricultural, industrial, and drinking purposes, National Conference on Water and Wastewater Engineering, Kerman, Iran (2012) (in Persian).
[3]    M. Hassanalipour, A. Esmailiouri, E. Ahmadi, Y. Imani, M. Raeuf, M.R. Abazar, Assessment of urban development impacts on quantity and quality of surface and groundwater in Ardabil plain, Environmental Science Studies, 7(3) (2022) 5374–5385 (in Persian).
[4]    Turkish Statistical Institute (TUIK), Agricultural Statistics Summary, 2018.
[5]    F. Karimi, S. Sultana, A. Shirzadi Babakan, D. Royall, Land suitability evaluation for organic agriculture of wheat using GIS and multi-criteria analysis, Applied Geography, 4(3) (2018) 326–342. 
[6]    Y. Hoseini, M. Kamrani, Using a fuzzy logic decision system to optimize the land suitability evaluation for a sprinkler irrigation method, Outlook on Agriculture, 47(4) (2018) 298–307.
[7]    H.F. Obidavi, Z. Fatemeh, Spatial distribution of water quality index based on WHO standards using GIS: Case study of Firoozabad groundwater, Human and Environment Journal (2021) (in Persian).
[8]    S. Hashmati, H. Beigi Harchgani, Spatial patterns and zoning of groundwater quality indices of Shahr-e-Kord for designing drip irrigation systems, Proceedings of the 5th Environmental Engineering Conference, Tehran, Iran (2012) (in Persian).
[9]    M. Nakhaei, M. Vadiati, Application of fuzzy inference model for assessing qanat water quality for drinking and agricultural uses (Tehran province), Journal of Advanced Applied Geology, 6 (2013) (in Persian).
[10]  B. Imani, J. Jafarzadeh, Groundwater quality assessment for drinking purposes in rural areas using geostatistical analysis and GIS: Case study of Ardabil County, Quarterly Journal of Geographical Information Science, 32(127) (2023) 151–170 (in Persian).
[11]     A. Malkian, M. Mirdashtvan, Groundwater quality assessment for agricultural use using geostatistical analyses: Case study of Hashtgerd plain, Alborz province, Journal of Rangeland and Watershed Management, 68(4) (2015) 809–820 (in Persian).
[12] T. Shirvani, I. Shirvani Sarouyi, M.H. Bouchani, F. Aref, Groundwater quality assessment of Sahra-ye-Bagh plain for agricultural and industrial uses, Ecohydrology, 2(4) (2015) 345–356 (in Persian).
[13]  F. Eslami, R. Shokouhi, S. Mazloumi, M. Darvish Motavali, M. Salari, Assessment of Water Quality Index (WQI) of groundwater resources in Kerman province in 2015, Journal of Occupational Health and Environment, 1(3) (2017) 45–48 (in Persian).
[14]  L. Hamidian, S.H. Meraji, E. Fijani, S. Batalblooi, Assessment of groundwater quality in Bushehr province using water quality index, Journal of Hydrogeology, 2(1) (2017) 31–44 (in Persian).
[15]    R. Bahrami Nasab, H. Pir Kharati, A. Abbasfam, Z. Sheikhi, D. Bazargan, Groundwater quality assessment of Rashkan plain for agricultural use, Proceedings of the First Conference on Fundamental Research in Agricultural and Environmental Sciences, Shahid Beheshti University, Tehran, Iran (2019) (in Persian).
[16]  M. Qareh Mahmoudloo, A. Zare, Groundwater quality assessment of Seydan-Farouq plain for agricultural purposes, Proceedings of the 2nd National Conference on Agricultural Science, Natural Resources, and Environment of Iran, Tehran, Iran (2018) (in Persian)
[17]  H. Banzhad, H. Mohebzadeh, Groundwater quality assessment of Razan-Qahavand plain for agricultural use using GIS, Quarterly Journal of Geographical Space Studies, 12(38) (2011) 9 (in Persian).
[18]   A.A. Hosseini Pak, Geostatistics, University of Tehran Press, Tehran, Iran (1998) (in Persian).
[19]    Y. Hoseini, Optimization of saturated hydraulic conductivity estimation using kriging in drainage networks, Applied Water Science, 13 (2023) 94. https://doi.org/10.1007/s13201-023-01897-3.
[20]   F. Dardour, et al., A novel approach for groundwater quality assessment using WQI, Journal of Hydrology, 598 (2021) 126465.
[21]     World Health Organization (WHO), Guidelines for Drinking-water Quality, 4th Edition, Incorporating the 1st Addendum, Geneva, Switzerland (2017).
[22]  N. Adimalla, H. Qian, Groundwater quality evaluation using water quality index (WQI) and GIS techniques in semi-arid regions, Environmental Science and Pollution Research, 28 (2021) 100–115.
[23]  M. Castellini, A.M. Stellacci, M. Tomaiuolo, E. Barca, Spatial variability of soil physical and hydraulic properties in a durum wheat field: An assessment by the BEST-Procedure, Water, 11 (2019) 1434.
[24]    W.A. Agyare, S.J. Park, P.L.G. Vlek, Artificial neural network estimation of saturated hydraulic conductivity, Vadose Zone Journal, 6(2) (2007) 423–431.
[25]   M.H. Razi, W. Wilopo, D.P.E. Putra, Hydrogeochemical evolution and water–rock interaction processes in the multilayer volcanic aquifer of Yogyakarta-Sleman Groundwater Basin, Indonesia, Environmental Earth Sciences, 83 (2024) 164. https://doi.org/10.1007/s12665-024-11477-6.
[26]  R.S. Chauhan, S. Singh, M. Kumar, A comprehensive water quality index based on analytic hierarchy process for groundwater quality assessment, Ecological Indicators, 145 (2022) 109582. https://doi.org/10.1016/j.ecolind.2022.109582.
[27]  K.K. Yadav, N. Gupta, V. Kumar, J.K. Singh, Integrated WQI–GIS approach for groundwater quality assessment in arid and semi-arid regions, Sustainable Water Resources Management, 9 (2023) 67.
[28]   H. Zheng, S. Hou, J. Liu, Y. Xiong, Y. Wang, Advanced machine learning approaches for groundwater quality assessment using water quality indices, Journal of Hydrology, 629 (2024) 130402. https://doi.org/10.1016/j.jhydrol.2024.130402.
[29]    F.A. Ababakr, K.O. Ahmed, A. Amini, H. Gökçekuş, Spatio-temporal variations of groundwater quality index using geostatistical methods and GIS, Applied Water Science, 13 (2023) 206. https://doi.org/10.1007/s13201-023-02010-4.
[30]  V.B. Patil, V.R. Saraf, Review of groundwater mapping and water quality assessment using GIS and Water Quality Index (WQI), International Journal of Intelligent Systems and Applications in Engineering, 12(21s) (2024) 4612.
[31]  H.M. Shuaibu, S.M. Abdullahi, A.A. Yusuf, M.B. Bello, Hydrogeochemical processes controlling groundwater quality and sustainability in arid environments, Water, 16(4) (2024) 601. https://doi.org/10.3390/w16040601.
[32] L. Seraiche, R. Benzaid, M. Khelifi, Groundwater vulnerability assessment in semi-arid regions using GIS-based multi-criteria and geostatistical approaches, arXiv preprint (2026). https://arxiv.org/abs/2602.00023.