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Journals / Turkish Journal of Engineering / 2026 / Volume: 10 Issue: 4

An integrated geospatial approach for spatiotemporal analysis of groundwater level variability and effecting environmental factors

Rabab Abood(University of Tabriz)0009-0009-9249-4805
Bakhtiar Feizizadeh(Humboldt Univerity of Berlin)0000-0002-3367-2925
Khalil Valizadeh Kamran(University of Tabriz)0000-0003-4648-842X
Nadia Aziz(University of Technology, Department of Geomatics)0000-0000-0000-2564
Pages
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Publication Date
2026-10-16
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

The results showed significant spatial variations in the groundwater levels of the study area.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Sustainable water resource management requires an understanding of the spatial and temporal variability of groundwater, particularly in semi-arid areas.
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Key Findings & Data:This study investigates groundwater level variability in Wadi Al-Ubayyid, Iraq, during the period of 2009-2013 using integrated geospatial analysis techniques based on data availability.
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Conclusion & Impact:The results showed significant spatial variations in the groundwater levels of the study area.
🔬Design:Research Article
📍Scope:2009-2013 Verileri
⚙️Variables:Groundwater levels · spatial interpolation · Wadi Al-Ubayyid

Abstract

Sustainable water resource management requires an understanding of the spatial and temporal variability of groundwater, particularly in semi-arid areas. This study investigates groundwater level variability in Wadi Al-Ubayyid, Iraq, during the period of 2009-2013 using integrated geospatial analysis techniques based on data availability. This study aimed to explore the impact of geological and environmental factors on groundwater variability using an integrated GIS spatial analysis and a data-driven approach. Spatial maps of groundwater distribution were produced by analyzing groundwater-level data from the sampling observation wells. Zonal statistics were applied to calculate the mean groundwater levels and analyze groundwater variability. The influence of environmental and hydrogeological factors on groundwater variability was evaluated using Landsat-derived land use/land cover and geological data. The results showed significant spatial variations in the groundwater levels of the study area. The time series analysis revealed an overall increasing trend in groundwater levels, whereas the other wells were relatively stable or experienced minor fluctuations in water levels. The results also show that groundwater variability in the study area is attributed to natural and anthropogenic factors, especially lithological features and land use. Floodplain deposits are important hydrogeological units that play a significant role in groundwater storage and recharge. The results indicate the effectiveness of GIS-based approaches in the evaluation of groundwater and provide a scientific basis for the sustainable management of groundwater resources in semi-arid environments. In summary, the findings of this study underscore the significance of integrated geospatial approaches for the assessment, monitoring, and sustainable management of groundwater resources. The proposed approach can provide useful scientific information to help decision-makers develop effective groundwater management strategies and encourage sustainable water resource use in semi-arid regions.

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Cite This Article

Abood, R., Feizizadeh, B., Kamran, K. V., Aziz, N. (2026). An integrated geospatial approach for spatiotemporal analysis of groundwater level variability and effecting environmental factors. Turkish Journal of Engineering, Volume: 10 Issue: 4. https://ajindex.com/articles/1326357

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References (34)

  1. Reinecke, R., 2022., Groundwater: Global abundance and distribution. Encyclopedia of Inland Waters (2nd ed., Vol. 3, pp. 306–314). Elsevier. https://doi.org/10.1016/B978-0-12-819166-8.00133-X.
  2. Pointet, T., 2022., The United Nations World Water Development Report 2022 on groundwater: A synthesis. La Houille Blanche, 108(1). https://doi.org/10.1080/27678490.2022.2090867.
  3. Ojoawo, A. I., & Adagunodo, T. A., 2023. Groundwater occurrence and flow in varying geological formations. IOP Conference Series: Earth and Environmental Science, 1197(1), 012009. https://doi.org/10.1088/1755-1315/1197/1/012009.
  4. Al-Gburi, M. R. G., Al-Khatony, S. E., Znad, R. K., & Al-Sumaidaie, M. A. H., 2022. Mapping of groundwater potential zone using GIS and remote sensing of Shwan Sub-Basin, Kirkuk, NE Iraq. Iraqi Geological Journal, 55(2B), 62–72. https://doi.org/10.46717/igj.55.2B.6Ms-2022-08-22.
  5. Khudair, M. Y., Kamel, A. H., Sulaiman, S. O., & Al-Ansari, N., 2022. Groundwater quality and sustainability evaluation for irrigation purposes: A case study in an arid region, Iraq. International Journal of Sustainable Development and Planning, 17(2), 413–419. https://doi.org/10.18280/IJSDP.170206.
  6. Mandal, S., Roy, S., Kar, D., Rakshit, A., Sarkar, A., Chakraborty, A., Das, S., Roy Choudhury, M., Bera, M., Tripathi, S., & Dutta, S., 2025. Impact of land use and land cover changes on groundwater storage dynamics. Developments in Environmental Science, 19, 71–107. https://doi.org/10.1016/B978-0-443-33787-1.00003-4.
  7. Mukherjee, A., Jha, M. K., Kim, K.-W., & Pacheco, F. A. L., 2024. Groundwater resources: Challenges and future opportunities. Scientific Reports, 14, 28540. https://doi.org/10.1038/s41598-024-79936-5.
  8. Al-Ansari, N., Abdellatif, M., Zakaria, S., & Knutsson, S.,2022. Water resources in Iraq: Challenges and solutions. Journal of Earth Sciences and Geotechnical Engineering, 12(1), 1–22.
  9. Awadh, S. M., Al-Mimar, H., & Yaseen, Z. M., 2021. Groundwater availability and water demand sustainability over the upper mega aquifers of Arabian Peninsula and west region of Iraq. Environment, Development and Sustainability, 23(1), 1–21.
  10. Feizizadeh, B., Abdollahi, Z., & Shokati, B., 2022. A GIS-based spatiotemporal impact assessment of droughts in the hyper-saline Urmia Lake Basin on the hydro-geochemical quality of nearby aquifers. Remote Sensing, 14(11), 2516. https://doi.org/10.3390/rs14112516.
  11. Boroushaki, S., & Malczewski, J., 2021. An extension of GIS-based MCDM using ANP for complex environmental decisions. Environmental Modelling & Software, 140, 105046.
  12. Al-Bahrani, H. S., Al-Rammahi, A. H., Al-Mamoori, S. K., Al-Maliki, L. A., & Al-Ansari, N., 2022. Groundwater detection and classification using remote sensing and GIS in Najaf, Iraq. Groundwater for Sustainable Development, 19, 100838. https://doi.org/10.1016/j.gsd.2022.100838.
  13. Sharma, M., 2021. Groundwater analytics for measuring quality and quantity. In Urban Water Crisis and Management (pp. 415–430). Springer. https://doi.org/10.1007/978-3-030-71945-6_23.
  14. Sulaiman, S. O., Kamel, A. H., Sayl, K. N., & Alfadhel, M. Y.,2019. Water resources management and sustainability over the Western Desert of Iraq. Environmental Earth Sciences, 78(16), 495. https://doi.org/10.1007/s12665-019-8510-y.
  15. Li, L., 2021. The state of the world's land and water resources for food and agriculture (SOLAW): Systems at breaking point. Food and Agriculture Organization of the United Nations.
  16. Citaristi, I., 2022. United Nations Educational, Scientific and Cultural Organization (UNESCO). In The Europa Directory of International Organizations 2022 (pp. 369–375). Routledge. https://doi.org/10.4324/9781003292548-76.
  17. Hamed, M. H., Dara, R. N., & Kirlas, M. C., 2022. Groundwater vulnerability assessment using a GIS-based DRASTIC method in the Erbil Dumpsite area (Kani Qirzhala), Central Erbil Basin, North Iraq. Journal of Groundwater Science and Engineering, 12(1), 16. https://doi.org/10.26599/JGSE.2024.9280003
  18. Philip, G. M., & Watson, D. F., 1986. Matheronian geostatistics—Quo vadis? Mathematical Geology, 18(1), 93–117. https://doi.org/10.1007/BF00897657.
  19. Hanuwate, S. C., & Shravan Kumar, G., 2026. An integrated approach to analysis groundwater quality using remote sensing and GIS. Retrieved April 24, 2026, from https://ijirse.com/ADMIN/admin/postimages/images/fullpdf/6.pdf.
  20. Bhat, V., Prajwal, M., Shetty, A., Srivastava, A., & Bhosale, R., 2018. Spatiotemporal relationship linking land use/land cover with groundwater level. In Groundwater: Select Proceedings of ICWEES 2016 (pp. 41–54). Springer. https://doi.org/10.1007/978-981-10-5789-2_4
  21. Abooda, R. H., Mahdi, A. H., Khalaf, A. G., & Kadhim, A. A., 2024. Evaluation of land cover changes in Karbala Governorate using remote sensing and GIS techniques. Iraqi National Journal of Earth Science, 24(2), 177–185. https://doi.org/10.33899/EARTH.2023.143323.1144.
  22. Joachim, B., Geoffrey, O., Denis, N., Jimmy, B., Louis, L. R., & Martine, N., 2025. Application of GeoModeller in production of enhanced lithological map for groundwater exploration. Cureus. https://doi.org/10.7759/s44388-025.
  23. Rehman, A., Islam, F., Tariq, A., Ul Islam, I., Brian, J. D., Bibi, T., Ahmad, W., Ali Waseem, L., Karuppannan, S., & Al-Ahmadi, S., 2024. Groundwater potential zone mapping using GIS and remote sensing-based models for sustainable groundwater management. Geocarto International, 39(1). https://doi.org/10.1080/10106049.2024.2306275
  24. Jones, W. R., Rock, L., Wesch, A., Marzusch, E., & Low, M., 2022. Groundwater spatiotemporal data analysis tool: Case studies, new features and future developments. Groundwater Monitoring & Remediation, 42(3), 14–22. https://doi.org/10.1111/GWMR.12522
  25. Longley, P. A., Goodchild, M. F., Maguire, D. J., & Rhind, D. W., 2015. Geographic information science and systems (4th ed.). Wiley.
  26. Adhikary, P. P., & Dash, C. J. (2017). Comparison of deterministic and stochastic methods to predict spatial variation of groundwater depth. Applied Water Science, 7(1), 339–348. https://doi.org/10.1007/S13201-014-0249-8
  27. Susatio, R., Riyanto, I. A., Wilopo, W., & Hendrayana, H., 2025. Comparative evaluation of IDW and spline interpolation methods for analyzing groundwater table depth and elevation. Jurnal Ilmiah Dinamika Rekayasa, 21(2), 98–106. https://doi.org/10.20884/1.JIDR.2025.21.2.47.
  28. Shahmohammadi-Kalalagh, S., & Taran, F., 2021. Evaluation of the classical statistical, deterministic and geostatistical interpolation methods for estimating the groundwater level. International Journal of Energy and Water Resources, 5(1), 33–42. https://doi.org/10.1007/S42108-020-00094-1.
  29. Li, J., & Heap, A. D., 2014. Spatial interpolation methods applied in the environmental sciences: A review. Environmental Modelling & Software, 53, 173–189.
  30. Machiwal, D., Moharana, P. C., Kumar, S., Srivastava, V., & Bhandari, S. L., 2021. Exploring temporal dynamics of spatially distributed groundwater levels by integrating time series modeling with geographic information systems. Geocarto International, 36(12), 1325–1345. https://doi.org/10.1080/10106049.2019.1648561.
  31. Yang, J., Ye, M., Tang, Z., Jiao, T., Song, X., Pei, Y., & Liu, H., 2020. Using cluster analysis for understanding spatial and temporal patterns and controlling factors of groundwater geochemistry in a regional aquifer. Journal of Hydrology, 583, 124594. https://doi.org/10.1016/j.jhydrol.2020.124594.
  32. Shahzad, H., Farid, H. U., Khan, Z. M., Anjum, M. N., Ahmad, I., Chen, X., Sakindar, P., Mubeen, M., Ahmad, M., & Gulakhmadov, A. (2020). An integrated use of GIS, geostatistical and map overlay techniques for spatio-temporal variability analysis of groundwater quality and level in the Punjab Province of Pakistan, South Asia. Water, 12(12), 3555. https://doi.org/10.3390/w12123555.
  33. Wei, H., Chen, H., & Li, F., 2025. Optimization of well layout based on spatial variability of groundwater. Highlights in Science, Engineering and Technology, 127, 66–78. https://doi.org/10.54097/8GBXDH81.
  34. Adeyeye, O. A., Ikpokonte, A. E., & Arabi, A. S., 2018. Geospatial signature of augmented groundwater accessibility around streams. Sustainable Water Resources Management, 4(4), 673–685. https://doi.org/10.1007/S40899-017-0153-0.