Journal of Advances in Environmental Health Research

Journal of Advances in Environmental Health Research

Impacts of Land Surface Characteristics on Groundwater Quality and Quantity: A Case Study of Qazvin Plain, Iran

Document Type : Original Article

Authors
Mohamad Parsi Mehr 1
Eisa Solgi 2
1 Department of Environmental Sciences and Engineering, Faculty of Natural Resources and Environment, Malayer University, Malayer, Hamedan, Iran
2 Professor of Department of Environmental Science, Faculty of Natural Resources and Environment, Malayer University, Malayer, Hamedan, Iran
10.34172/jaehr.1399
Abstract
Background: The Qazvin Plain is one of Iran’s largest and most important agricultural regions. It is situated on the Qazvin aquifer. Understanding the relationship between surface features such as topography, land use, and soil type with the quantitative and qualitative characteristics of the aquifer is crucial for this region.
Methods: In this study, the Soil and Water Assessment Tool (SWAT) model was used to delineate the hydrological response units (HRUs) of the plain. These units were calculated based on common characteristics, including land use, topography, and soil type. Additionally, the MODFLOW model was used to simulate groundwater levels based on the hydraulic conductivity (K) map, well pumping tests, and other parameters. This model served as a quantitative indicator of groundwater resources. Furthermore, the spatial distribution map of electrical conductivity (EC) values was used as a qualitative indicator of groundwater resources. In the Qazvin aquifer, EC is the most important limiting factor for water quality. The relationship between these factors was then analyzed using geographically weighted regression (GWR).
Results: The values of EC with a statistic of R2 = 0.66 and groundwater level with a statistic of R² = 0.79 were controlled by surface characteristics, indicating a strong relationship between these variables and surface features.
Conclusion: This research can highly assist water and environmental resource managers and decision-makers in managing the quantity and quality of water in this region.
Keywords
Groundwater quality
SWAT
MODFLOW
Regression
Pollution

Subjects

  1. Zhong F, Xu X, Li Z, Zeng X, Yi R, Luo W, et al. Relationships between lithology, topography, soil, and vegetation, and their implications for karst vegetation restoration. Catena (Amst). 2022;209(Pt 1):105831. doi: 1016/j.catena.2021.105831.
  2. Zhang W, Jiang F, Ou J. Global pesticide consumption and pollution: with China as a focus. Proc Int Acad Ecol Environ Sci. 2011;1(2):125-44.
  3. O’Geen AT. Soil water dynamics. Nature Education Knowledge. 2013;4(5):9.
  4. Scanlon BR, Healy RW, Cook PG. Choosing appropriate techniques for quantifying groundwater recharge. Hydrogeol J. 2002;10(1):18-39. doi: 1007/s10040-001-0176-2.
  5. Childs EC. The use of soil moisture characteristics in soil studies. Soil Sci. 1940;50(4):239-52.
  6. Rawls WJ, Brakensiek DL, Saxtonn KE. Estimation of soil water properties. Trans ASAE. 1982;25(5):1316-20. doi: 13031/2013.33720.
  7. Foster SS, Chilton PJ. Groundwater: the processes and global significance of aquifer degradation. Philos Trans R Soc Lond B Biol Sci. 2003;358(1440):1957-72. doi: 1098/rstb.2003.1380.
  8. Zarghami Dastjerdi S, Sharifi E, Rahbar R, Saghafian B. Downscaling WGHM-based groundwater storage using random forest method: a regional study over Qazvin plain, Iran. Hydrology. 2022;9(10):179. doi: 3390/hydrology9100179.
  9. Amini H, Ashrafzadeh A, Khaledian M. Enhancing groundwater salinity estimation through integrated GMDH and geostatistical techniques to minimize Kriging interpolation error. Earth Sci Inform. 2024;17(1):283-97. doi: 1007/s12145-023-01157-7.
  10. Sadeghi A, Galalizadeh S, Zehtabian G, Khosravi H. Assessing the change of groundwater quality compared with land-use change and precipitation rate (Zrebar Lake’s Basin). Appl Water Sci. 2021;11(11):170. doi: 1007/s13201-021-01508-z.
  11. Davoodi Memar Otagvar L, Fataei E, Tajiabadi M, Naeimi B. Spatio-temporal assessment of changes in groundwater quality in Qazvin Plain. Journal of Range and Watershed Managment. 2024;77(3):353-69. doi: 22059/jrwm.2024.370962.1744.
  12. Babaee S, Mousavi Z, Masoumi Z, Hojati Malekshah A, Roostaei M, Aflaki M. Land subsidence from interferometric SAR and groundwater patterns in the Qazvin plain, Iran. Int J Remote Sens. 2020;41(12):4780-98. doi: 1080/01431161.2020.1724345.
  13. Noori R, Maghrebi M, Mirchi A, Tang Q, Bhattarai R, Sadegh M, et al. Anthropogenic depletion of Iran’s aquifers. Proc Natl Acad Sci U S A. 2021;118(25):e2024221118. doi: 1073/pnas.2024221118.
  14. Golian M, Saffarzadeh A, Katibeh H, Mahdad M, Saadat H, Khazaei M, et al. Consequences of groundwater overexploitation on land subsidence in Fars province of Iran and its mitigation management programme. Water Environ J. 2021;35(3):975-85. doi: 1111/wej.12688.
  15. Siebert S, Burke J, Faures JM, Frenken K, Hoogeveen J, Döll P, et al. Groundwater use for irrigation–a global inventory. Hydrol Earth Syst Sci. 2010;14(10):1863-80. doi: 5194/hess-14-1863-2010.
  16. Lerner DN, Harris B. The relationship between land use and groundwater resources and quality. Land Use Policy. 2009;26:S265-73. doi: 1016/j.landusepol.2009.09.005.
  17. The United Nations World Water Development Report 3. Water in a changing world. 2009.UNESCO Publishing.
  18. Leaf AT, Fienen MN. Modflow-setup: robust automation of groundwater model construction. Front Earth Sci. 2022;10:903965. doi: 3389/feart.2022.903965.
  19. Arnold JG, Srinivasan R, Muttiah RS, Williams JR. Large area hydrologic modeling and assessment part I: model development. J Am Water Resour Assoc. 1998;34(1):73-89. doi: 1111/j.1752-1688.1998.tb05961.x.
  20. Neitsch SL, Arnold JG, Kiniry JR, Williams JR. Soil and Water Assessment: Tool Theoretical Documentation, Version 2009. College Station: Texas Water Resources Institute; 2011.
  21. Ikhwali MF, Rau MI, Nur S, Ferijal T, Prayogo W, Saputra SF. Application of soil and water assessment tool in Indonesia–a review and challenges. Desalin Water Treat. 2022;277:105-19. doi: 5004/dwt.2022.29018.
  22. Chen X. Statistical Methods for Global Health and Epidemiology: Principles, Methods and Applications. Springer Nature; 2020.
  23. Fischer MM, Nijkamp P. Handbook of Regional Science. Heidelberg: Springer; 2014.
  24. Wheeler DC. Geographically weighted regression. In: Handbook of Regional Science. Berlin: Springer; 2014. p. 1895-921.
  25. Fotheringham AS, Brunsdon C, Charlton M. Geographically weighted regression. In: The SAGE Handbook of Spatial Analysis. SAGE Publications; 2009. p. 243-54.
  26. Yifru BA, Lee S, Lim KJ. Calibration and uncertainty analysis of integrated SWAT-MODFLOW model based on iterative ensemble smoother method for watershed scale river-aquifer interactions assessment. Earth Sci Inform. 2023;16(4):3545-61. doi: 1007/s12145-023-01071-y.
  27. Sisay BM, Nedaw D, Birhanu B, Gigar AG. Application of SWAT and MODFLOW models for characterization of surface–groundwater interaction in the Modjo River catchment, central Ethiopia. Environ Earth Sci. 2023;82(13):341. doi: 1007/s12665-023-10988-y.
  28. Gautam A, Rai SC, Rai SP, Ram K, Sanny. Impact of anthropogenic and geological factors on groundwater hydrochemistry in the unconfined aquifers of Indo-Gangetic plain. Phys Chem Earth Parts A/B/C. 2022;126:103109. doi: 1016/j.pce.2022.103109.
  29. He S, Li P, Wu J, Elumalai V, Adimalla N. Groundwater quality under land use/land cover changes: a temporal study from 2005 to 2015 in Xi’an, Northwest China. Hum Ecol Risk Assess. 2020;26(10):2771-97. doi: 1080/10807039.2019.1684186.
  30. Hoseini SM, Mazandaranizadeh H, Nazari B. Simultaneously management of surface and groundwater resources and increasing farmers’ resilience to water scarcity by predicting the price of agricultural products and using GA (case study of irrigation and drainage network of Qazvin plain). Iran J Soil Water Res. 2021;52(2):563-76. [Persian].
  31. Lei C. Evaluating coupled influences of slope class and land use change on water quality using single and composite indices in an agricultural basin. Catena (Amst). 2025;248:108584. doi: 1016/j.catena.2024.108584.
  32. Mukundan R, Moknatian M, Gelda RK. Investigation and modeling of land use effects on water quality in two NYC water supply streams. J Environ Manage. 2025;373:123993. doi: 1016/j.jenvman.2024.123993.
Journal of Advances in Environmental Health Research
Volume 13, Issue 2
Winter 2025
Pages 135-142