Groundwater quality mapping based on the Wilcox Classification method for agricultural purposes: Qazvin Plain aquifer case

Year 2025, Volume: 9 Issue: 1, 116 - 128, 20.01.2025

Mohammad Taghi Sattari , Yasaman Kamrani , Sahar Javidan , Nasrin Fathollahzadeh Attar , Halit Apaydın

https://doi.org/10.31127/tuje.1523574

Abstract

Water quality is an essential component in managing surface and groundwater resources and for various uses; it is considered a necessary principle in planning. This study aims to map the groundwater quality of the Qazvin Plain aquifer in Iran for agricultural use based on the Wilcox classification method. For this purpose, the parameters of electrical conductivity (EC) and sodium adsorption ratio (SAR) of wells in the years 2015-2018 have been used. For interpolation, the inverse distance weighting (IDW) method with optimal power and Kriging geostatistical techniques were used based on spherical, exponential, and Gaussian semicircle algorithms. Electrical conductivity and SAR maps were drawn in the GIS platform after selecting the best interpolation method due to minor errors. The Wilcox method was used to classify the water quality of the studied wells. In most cases, the IDW method with optimal power was selected as the superior interpolation method. During the study, the results obtained from the water quality maps showed that the level attributed to the "high salinity" water class increased from 25.98 to 36.44, and the level attributed to the "slightly salty" water class decreased from 12.54 to 3.14. Finally, the results showed that the quality of underground water for agricultural purpose in the Qazvin Plain aquifer became more unfavourable during the studied period

Keywords

Irrigation water quality, Optimal Power, Kriging, Semi-variograms, Quality classification

References

• Chung, S. Y., Kim, G. B., & Senapathi, V. (2023). Drought and Groundwater Development. Water, 15(10), 1908.
• Li, P., Tian, R., Xue, C., & Wu, J. (2017). Progress, opportunities, and key fields for groundwater quality research under the impacts of human activities in China with a special focus on western China. Environmental Science and Pollution Research, 24, 13224-13234.
• Mascarelli, A. (2012). Demand for water outstrips supply. Nature, 8.
• Glazer, A. N., & Likens, G. E. (2012). The water table: The shifting foundation of life on land. Ambio, 41, 657-669.
• Aeschbach-Hertig, W., & Gleeson, T. (2012). Regional strategies for the accelerating global problem of groundwater depletion. Nature Geoscience, 5(12), 853-861.
• Chakrabarti, S., & Barua, G. (2020). Analysis of three-dimensional ponded drainage of a multi-layered soil underlain by an impervious barrier. Sādhanā, 45, 1-40.
• Breida, M., Younssi, S. A., Ouammou, M., Bouhria, M., & Hafsi, M. (2019). Pollution of Water Sources from Agricultural and Industrial Effluents: Special Attention to NO3−, Cr (VI), and Cu (II). Water Chemistry, 39.
• Almasri, M. N., Kaluarachchi, J. J., Aral, M. M., & Taylor, S. W. (2011). Groundwater quality: fate and transport of contaminants. Groundwater Management Technical Committee of the Groundwater Council of EWRI Environmental and Water Resources Institute (EWRI) of the American Society of Civil Engineers, 36.
• Macek, T., Pavlikova, D., & Mackova, M. (2004). Phytoremediation of metals and inorganic pollutants. In Applied bioremediation and phytoremediation. Berlin, Heidelberg: Springer Berlin Heidelberg (pp. 135-157).
• Brindha, K., & Schneider, M. (2019). Impact of urbanization on groundwater quality. GIS and geostatistical techniques for groundwater science, 2019, 179-196.
• Khelfi, A. (2019). Sources of Groundwater Pollution. In Advanced Treatment Techniques for Industrial Wastewater. IGI Global (pp. 177-210).
• Sharma, M. K., & Choubey, V. K. (2010). Groundwater Pollution: An Overview. IUP Journal of Chemistry, 3(4).
• Kurwadkar, S. (2014). Emerging trends in groundwater pollution and quality. Water Environment Research, 86(10), 1677-1691.
• Moridi, A. (2017). State of water resources in Iran. Int. J. Hydrol, 1, 111-114.
• Golian, M., Saffarzadeh, A., Katibeh, H., Mahdad, M., Saadat, H., Khazaei, M., ... & Dashti Barmaki, M. (2021). Consequences of groundwater overexploitation on land subsidence in Fars Province of Iran and its mitigation management programme. Water and Environment Journal, 35(3), 975-985.
• Turhan, A., Aşık, B. B., & Kuşçu, H. (2020). The influence of irrigation water salinity and humic acid on nutrient contents of onion (Allium cepa L.). Journal of Agricultural Sciences, 26(2), 147-153.
• Bozdağ, A. (2022). Investigation of over-exploited groundwater in Çumra Plain (Konya-Turkey) with environmental isotopes. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi, 28(3), 483-492.
• Goodarzi, M.R.; Niknam, A.R.R.; Barzkar, A.; Niazkar, M.; Zare Mehrjerdi, Y.; Abedi, M.J.; Heydari Pour, M. (2023). Water Quality Index Estimations Using Machine Learning Algorithms: A Case Study of Yazd-Ardakan Plain, Iran. Water, 15, 1876. https://doi.org/10.3390/w15101876.
• Falbo, D. L., Queen, L. P., & Blinn, C. R. (1991). Introduction to data analysis using Geographic Information Systems.
• Gołaszewski, J., Załuski, D., Żuk-Gołaszewska, K., & Grzela, K. (2013). Geostatistical methods as auxiliary tools in field plot experimentation. In Precision agriculture'13. Wageningen Academic (pp. 499-506).
• Rahmani, A. R., Samadi, M. T., & Heydari, M. (2008). Water Quality Assessment of Hamadan-Bahar Plain Rivers Using Wilcox Diagram for Irrigation.
• Ghafoori, V., Malekpour, N., & Mardani, A. (2012). Evaluation of geostatistical methods for mapping groundwater quality in Fars province. Journal of Water and Soil Resources Conservation, 1(2), 81-94.
• Sadeghi, S. H., Ghasemieh, H., Damaneh, M., & Mosavi, S. H. (2016). Irrigation and municipal water quality zoning by GIS. Irrigation and Water Engineering, 6(4), 128-137.
• Schuler CA. (1987). Impacts of agricultural drainwater and contaminants on wetlands at Kesterson Reservoir, California.
• Alavi, N., Zaree, E., Hassani, M., Babaei, A. A., Goudarzi, G., Yari, A. R., & Mohammadi, M. J. (2016). Water quality assessment and zoning analysis of Dez eastern aquifer by Schuler and Wilcox diagrams and GIS. Desalination and Water Treatment, 57(50), 23686-23697.
• Hassen, I., Hamzaoui-Azaza, F., & Bouhlila, R. (2016). Application of multivariate statistical analysis and hydrochemical and isotopic investigations for evaluation of groundwater quality and its suitability for drinking and agriculture purposes: case of Oum Ali-Thelepte aquifer, central Tunisia. Environmental monitoring and assessment, 188, 1-20.
• Awais, M., Arshad, M., Shah, S. H. H., & Anwar-ul-Haq, M. (2017). Evaluating groundwater quality for irrigated agriculture: spatio-temporal investigations using GIS and geostatistics in Punjab, Pakistan. Arabian Journal of Geosciences, 10, 1-15.
• Sattari, M. T., Mirabbasi, R., Sushab, R. S., & Abraham, J. (2018). Prediction of groundwater level in Ardebil plain using support vector regression and M5 tree model. Groundwater, 56(4), 636-646.
• Ahmadi, A., Hezarjaribi, A., Ghorbani, K., & Hesam, M. (2018). Locating Susceptible Regions Implementation of New Irrigation Systems (Localized irrigation, Sprinkler irrigation, Low pressure irrigation) by using Analytical Hierarchy Process (AHP) in GIS (Case Study: North Khorasan Province, Esfarayen). Journal of Water and Soil Conservation, 25(5), 69-87.
• El-Zeiny, A. M., & Elbeih, S. F. (2019). GIS-based evaluation of groundwater quality and suitability in Dakhla Oases, Egypt. Earth Systems and Environment, 3(3), 507-523.
• Aravinthasamy, P., Karunanidhi, D., Subramani, T., & Roy, P. D. (2021). Demarcation of groundwater quality domains using GIS for best agricultural practices in the drought-prone Shanmuganadhi River basin of South India. Environmental Science and Pollution Research, 28, 18423-18435.
• Jeon, C., Raza, M., Lee, J. Y., Kim, H., Kim, C. S., Kim, B., ... & Lee, S. W. (2020). Countrywide groundwater quality trend and suitability for use in key sectors of Korea. Water, 12(4), 1193.
• Aryafar, A., Khosravi, V., & Karami, S. (2020). Groundwater quality assessment of Birjand plain aquifer using kriging estimation and sequential Gaussian simulation methods. Environmental Earth Sciences, 79, 1-21. [34]
• Masmoudi, T., Benakcha, M., Abdennour, M. A., Bouzekri, A., Amrane, A., & Alcala, F. J. (2024). Groundwater quality evaluation for drinking and agricultural purposes. A case study in semi-arid region (Zab El-gharbi SE-Algeria). Desalination and Water Treatment, 100476.
• Kumar, J., Biswas, B., & Verghese, S. (2021). Assessment of groundwater quality for drinking and irrigation purpose using geospatial and statistical techniques in a semi-arid region of Rajasthan, India. Journal of the Geological Society of India, 97(4), 416-427.
• Said, A. A., Yurtal, R., Cetin, M., & Gölpınar, M. S. (2021). Evaluation of some groundwater quality parameters using geostatistics in the urban coastal aquifer of Bosaso plain, Somalia. Journal of Agricultural Sciences, 27(1), 88-97.
• Sattari, M. T., Feizi, H., Colak, M. S., Ozturk, A., Ozturk, F., & Apaydin, H. (2021). Surface water quality classification using data mining approaches: Irrigation along the Aladag River. Irrigation and Drainage, 70(5), 1227-1246.
• Safari, M., Ahmadfazeli, A., Ghanbari, A., Mokhtari, Z., & Soleimani, Z. (2021). Assessment of the HablehRood river water quality for drinking and irrigation purposes in Garmsar, Iran. Environmental Earth Sciences, 80, 1-11.
• Sener, S., Varol, S., & Sener, E. (2021). Evaluation of sustainable groundwater utilization using index methods (WQI and IWQI), multivariate analysis, and GIS: The case of Aksehir District (Konya/Turkey). Environmental Science and Pollution Research, 28(35), 47991-48010.
• Makki, Z. F., Zuhaira, A. A., Al-Jubouri, S. M., Al-Hamd, R. K. S., & Cunningham, L. S. (2021). GIS-based assessment of groundwater quality for drinking and irrigation purposes in central Iraq. Environmental monitoring and assessment, 193(2), 107.
• Ganjei, S., Shiri, N., & Shiri, J. (2020). Spatial modeling of groundwater quality parameters for agricultural consumptions in Azarshahr plain using geostatistical methods. Water and Soil Science, 30(4), 105-117.
• Mahmodizadeh, S. & Esmaeily, A. (2021). 'Geostatistical Modelling of Spatial Changes in Groundwater Quality Using GIS and Wilcox Model (Case Study: Central and Kenark Districts, Chabahar)', Environment and Water Engineering, 7(1), pp. 103-118. doi: 10.22034/jewe.2020.255847.1460.
• Ak, M., & Top, İ. (2022). İkincil arıtılmış kentsel atıksulardaki azot ve fosforun toprak-akifer arıtma sistemi kullanılarak giderilmesinde toprak tiplerinin etkisi. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi, 28(6), 929-936.
• Ali, A., & Shakoor, A. (2022). Delineation and Evaluation of Groundwater Quality by using GIS mapping system and Statistical Approaches in Southern Punjab, Pakistan. NUST Journal of Engineering Sciences, 15(1), 1-11.
• Othman, M. M. (2023). Modeling of daily groundwater level using deep learning neural networks. Turkish Journal of Engineering, 7(4), 331-337. https://doi.org/10.31127/tuje.1169908
• Megahed, H.A.; GabAllah, H.M.; Ramadan, R.H.; AbdelRahman, M.A.E.; D’Antonio, P.; Scopa, A. & Darwish, M.H. (2023). Groundwater Quality Assessment Using Multi-Criteria GIS Modeling in Drylands: A Case Study at El-Farafra Oasis, Egyptian Western Desert. Water 2023, 15, 1376. https://doi.org/10.3390/w15071376
• Raheja, H., Goel, A., & Pal, M. (2023). Groundwater quality appraisal using IWQI and PCA for irrigation uses. ISH Journal of Hydraulic Engineering, 29(sup1), 264-273.
• Mogaraju, J. K. (2023). Application of machine learning algorithms in the investigation of groundwater quality parameters over YSR district, India. Turkish Journal of Engineering, 7(1), 64-72. https://doi.org/10.31127/tuje.1032314
• Mousavi, S. R., Sarmadian, F., Dehghani, S., Sadikhani, M. R., & Taati, A. (2017). Evaluating inverse distance weighting and kriging methods in estimation of some physical and chemical properties of soil in Qazvin Plain. Eurasian Journal of Soil Science, 6(4), 327-336.
• Wilcox, L. (1955). Classification and use of irrigation waters (No. 969). US Department of Agriculture.
• dos Santos, E. H., Griebeler, N. P., & de Oliveira, L. F. (2011). Spatial and temporal behavior of pluvial precipitation in the João Leite watershed, GO. Engenharia Agrícola, 31, 78-89.
• Mostafavi, R., & Gholami, S. (2013). Temporal and spatial distribution analysis of precipitation using geostatistical method (a case study of Babolrud Basin). Natural ecosystems of Iran, 4(1), 101-113. https://www.sid.ir/en/journal/ViewPaper.aspx?id=398123
• Meng, J. (2021). Raster data projection transformation based-on Kriging interpolation approximate grid algorithm. Alexandria Engineering Journal, 60(2), 2013-2019.
• Watson, D. F. (1985). A refinement of inverse distance weighted interpolation. Geo-processing, 2, 315-327.
• Dale, M. R., & Fortin, M. J. (2014). Spatial analysis: a guide for ecologists. Cambridge University Press.
• Çubukçu, E. A., Demir, V., & Sevimli, M. F. (2022). Digital elevation modeling using artificial neural networks, deterministic and geostatistical interpolation methods. Turkish Journal of Engineering, 6(3), 199-205. https://doi.org/10.31127/tuje.889570.
• Alaboz, P., & Dengiz, O. (2023). The Least Limiting Water Range to Estimate Soil Water Content Using Random Forest Integrated with GIS and Geostatistical Approaches. Journal of Agricultural Sciences, 29(4), 933-946. https://doi.org/10.15832/ankutbd.1137917
• Philip, G. M., & Watson, D. F. (1982). A precise method for determining contoured surfaces. The APPEA Journal, 22(1), 205-212.
• Skok, G. (2006). Analytical and practical examples of estimating the average nearest-neighbor distance in a rain gauge network. Meteorologische Zeitschrift (Berlin), 15.
• Othman, M. M. (2023). Modeling of daily groundwater level using deep learning neural networks. Turkish Journal of Engineering, 7(4), 331-337. https://doi.org/10.31127/tuje.1169908
• Falowo, O., & Daramola, A. S. (2023). Geo-Appraisal of groundwater resource for sustainable exploitation and management in Ibulesoro, Southwestern Nigeria. Turkish Journal of Engineering, 7(3), 236-258. https://doi.org/10.31127/tuje.1107329
• Hajderi , A. & Bozo, L. (2024). Health risks from air pollution from vehicles in the city of Tirana. Engineering Applications, 3(1), 68–77.
• Kocalar, A. C. (2023). Sinkholes caused by agricultural excess water using and administrative traces of the process. Advanced Engineering Science, 3, 15–20.