Hydro Geochemical Investigation of Groundwater in Miandoab Plain

Subject Areas : Business Administration and Entrepreneurship

Parisa Pashakhah ¹ (Ph.D. Candidate, Department of Water Science and Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran.)
Hossein Babazadeh ² (Professor, Department of Water Science and Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran)
Shahram Shahmohammadi-Kalalagh ³ (Associate Professor, Department of Water Science and Engineering, Tabriz Branch, Islamic Azad University, Tabriz, Iran)
Mahdi Sarai Tabrizi ⁴ (Assistant Professor, Department of Water Science and Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran)

Received: 2021-12-06 Accepted : 2022-03-11 Published : 2023-07-23

Keywords: Interpolation, Groundwater quality, Langelier Index, Schoeller Method, Wilcox Method,

Abstract :

Abstract
Introduction: Knowing the spatial and temporal changes in groundwater quality is one of the important issues for optimal management of groundwater resources. In this study, the hydro geochemical properties of groundwater resources in Miandoab plain (West Azerbaijan province of Iran) were investigated.
Methods: For this purpose, the data of 51 study wells during the time period (from 2014 to 2018) were used. The qualitative parameters such as the amount of Mg²⁺, Ca²⁺, Na⁺, K⁺, HCO₃^-, SO₄^2-, Cl^-, CO₃^2- and the indexes such as TH (Total Hardness), TDS (Total Dissolved Solids), EC (Electrical Conductivity), SAR (Sodium Absorption Ratio) and pH were evaluated based on drinking, agriculture and industry water quality standards. Aquifer qualitative zoning maps were extracted by entering the descriptive layers obtained from the qualitative analysis in ArcGIS software and selecting the best interpolation method based on the validation technique.
Results: The groundwater hydro chemical analysis based on the drinking water standards of the Energy Ministry indicated that the groundwater of the plain is in a relatively acceptable condition. This was also obtained from groundwater analysis by the Schoeller method. It was found that the largest areas of this plain had saline groundwater, in terms of agriculture. Industrially, sedimentation in the plain was more pronounced than corrosion.
Conclusion: Results showed that the aquifer quality declined from 2014 to 2017 and improved in 2018. Zoning maps showed that Miandoab aquifer has better quality and condition in the feeding areas in terms of drinking, agriculture and industry. In other words, according to the geography of the plain, the aquifer feeding areas were less vulnerable than the areas located in the evacuation areas.

References:

1            Tiwari K, Goyal R, Sarkar A. GIS-based spatial distribution of groundwater quality and regional suitability evaluation for drinking water. Environ. Proc. 2017; 4: 645–662.

2             Machiwal D, Madan K.J, Bimal C.M. GIS-based assessment and characterization of groundwater quality in a hard rock hilly terrain of Western India. Environmental monitoring and assessment. 2011; 174(1-4):645-63.

3            Emami S, Choopan Y, Parsa J. Modelling the groundwater level of the Miandoab Plain using artificial neural network method and election and genetic algorithms. Iranian Journal Echohydrology. 2018; 5(4): 1175-1189 [In Persian].

4            Jeihouni M, Toomanian A, Shahabi M, Alavipanah S.K. Groundwater quality assessment for drinking purposes using GIS modelling (case study: City of Tabriz). Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. 2014; 40, 163-168.

5            Sarhadi M, Nahtani M, Riki M. Assessment Groundwater quality of Zahedan plain for drinking, agricultural and industrial use during drought and normal periods. Proceedings of the first National Conference on Water Quality and Sustainable Development, Arak. 2015.

6            Annapoorna H, Janardhana M.R. Assessment of Groundwater Quality for Drinking Purpose in Rural Areas Surrounding a Defunct Copper Mine. Aquatic Procedia. 2015; (4): 685–692.

7            Khosravi H, Karimi K, Nakhaee Nejadfard S, Mesbahzadeh T. Investigation of Spatial Structure of Groundwater Quality Using Geostatistical Approach in Mehran plain, Iran. Pollution. 2016; 2(1): 57-65.

8            Khan R, Jhariya D. Groundwater quality assessment for drinking purpose in Raipur City, Chhattisgarh using water quality index and geographic information system. J. Geol. Soc. India. 2017; 90: 69–76.

9            Jafari KH, Baghal-Asghari F, Hoseinzadeh E, Heidari Z, Radfard M, Najafi-Saleh H, et al. Groundwater quality assessment for drinking and agriculture purposes in Abhar city, Iran. Data Brief. 2018; 9: 1033–1039.

10            Ghamarnia H, Roshandel F. Assessment of groundwater quality in Chardoley palin located in Kurdistan Province. Water engineering. 2019; 12(41); 145-160 [In Persian].

11            Feizi Z, Keshtkara A.R, Afzali A. Using geostatistical and deterministic modelling to identify spatialvariability of groundwater quality. International Desert Research Center. 2019; 24(1):143-151.

12            ElKashouty M. (2019). Groundwater quality distribution by geostatistical investigation (GIS), Nile Delta, Northern Egypt. Journal of Environmental Chemistry and Ecotoxicology. 2019; 11(1): 1-21.

13            Asadi E, Isazadeh M, Samadianfard S, Ramli M.F, Mosavi A, Nabipour N, et al. Groundwater Quality Assessment for Sustainable Drinking and Irrigation: sustainability. MDPI; 2019.

14            Fallahati A, Soleimani H, Alimohammadi M, Dehghanifard E, Askari M, Eslami F, et al. Impacts of drought phenomenon on the chemical quality of groundwater resources in the central part of Iran-application of GIS technique. Environmental Monitoring and Assessment. 2020; 192(1):64.

15            Jonubi R, Rezaverdinejad V, Behmanesh J, Abbaspour K. Investigation of quantitative changes in the groundwater table of the Miandoab Plain affected by surface and groundwater resources management using the MODFLOW-NWT mathematical model. Iranian Journal of Soil and Water Research. 2018; 49(2): 467-481 [In Persian].

16            Noroozi-Qushbulaq H, Asghari-Moghaddam A, Hateftabar S. Evaluation of Groundwater vulnerability of the Miandoab Plain to nitrate using the genetic algorithm. Ecology. 2019; 45(2): 301-315 [In Persian].

17            Dehghanipour A.H, Zahabiyoun B, Schoups G, Babazadeh H. A WEAP-MODFLOW surface water-groundwater model for the irrigated Miyandoab plain, Urmia lake basin, Iran: multi-objective calibration and quantification of historical drought impacts. Agric Water Manag. 2019; 223:105704.

18            Dehghanipour A.H, Schoups G, Zahabiyoun B, Babazadeh H. Meeting agricultural and environmental water demand in endorheic irrigated river basins: a simulation-optimization approach applied to the Urmia Lake basin in Iran. Agric Water Manag. 2020; 241:106353.

19            Pashakhah P, Babazadeh H, Shahmohammadi-Kalalagh SH, Sarai-Tabrizi M. Salinity‑based spatial evaluation of groundwater quality for agricultural use. International Journal of Environmental Science and Technology. 2022.

20            Update studies of water resources balance Study areas of Urmia Lake catchment area. Iran Water Resources Management Company. Water Consulting Engineers and Sustainable Development. 2015.

21            Emberger L. Sur le quotient pluviothermique. C.R. Sciences. 1952; 234: 2508-2511.

22            Ghasemi-Ziarani A, faryadi Sh, Shaykh-Kazemi Sh. The pollution of the Karaj dam basin by using GIS software. The first environmental engineering conference. Tehran University, Faculty of Engineering. 2006.

23            Rafi Sharifabad J, Zehtabian Gh.R. Tracking temporal and spatial changes in underground water quality for potable and agricultural purpose (Case study: Yazd, Ardakan Plain). Desert management. 2017; 5(9): 107-119 [In Persian].

24            Delgado C, Pacheco J, Cabrera A, Batllori C.E, Orellana R, Bautista F. Quality of groundwater for irrigation in tropical karst environment: The case of Yucatan, Mexico. Agricultural Water Management. 2010; 97(10): 1423-1433.

25            Hernandez-Stefanoni J.L, Ponce-Hernandez R. Mapping the spatial variability of plant diversity in a tropical forest: comparison of spatial interpolation methods. Environ. Monit. Assess. 2006; 117, 307–334.

26            Bagheri R, Mohammadi S. Comparing different interpolation methods to investigate the spatial changes in the water-table of Kerman Plain. The 1^st National Conference on Groundwater. Behbahan, Iran. 2009. (In Persian).

27            Gharbia A.S, Gharbia S.S, Abushbak T, Wafi H, Aish A, Zelenakova M, et al. Groundwater Quality Evaluation Using GIS Based Geostatistical Algorithms. Journal of Geoscience and Environment Protection. 2016; 4: 89-103.

28            Schoeller H. La classification geochimique des eaux. LASH Publication no. 64, Gen. Assembly of Berkeley. 1964; 4: 16-24.

29            Wilcox L.V. Classification and Use of Irrigation Waters. US DA, Circular 969, Washington; 1955.

30            Ghobadinia M, Rahimi H, Sohrabi T. Evaluation of potential calcium carbonate precioitation in agricultural tile drains. Iranian Journal of irrigation and drainage. 2009; 3(1): 1-12 [In Persian].