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Volume 40, Issue 3 (2025)                   GeoRes 2025, 40(3): 221-230 | Back to browse issues page
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Soltani-Samet M, Soltani H, Galoie M. Land Subsidence Due to Groundwater Depletion in Qazvin Plain-Buein Zahra Using Interferometric Synthetic Aperture Radar Method. GeoRes 2025; 40 (3) :221-230
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1- Department of Civil Engineering, Buein Zahra Technical University, Buein Zahra, Iran
2- Department of Civil Engineering, Faculty of Technical and Engineering, Imam Khomeini International University, Qazvin, Iran
* Corresponding Author Address: Department of Civil Engineering, Faculty of Technical and Engineering, Imam Khomeini International University, Norouzian Boulevard, Qazvin, Iran. Postal Code: 3414896818 (galavi@eng.ikiu.ac.ir)
Abstract   (411 Views)
Aims: Land subsidence is a destructive natural hazard that can occur either suddenly or gradually and can lead to severe economic and human losses.
Methodology: In this applied study which is conducted in 2025, the Qazvin plain (Buein Zahra region) was selected to estimate the subsidence rate. The Interferometric Synthetic Aperture Radar method and data series from 2019 to 2025 were used to estimate this phenomenon. To do this, the interpolation maps of groundwater depletion, active faults, and land use data of the area were extracted and analyzed.
Findings: The analysis of the satellite images showed that the average annual drawdown in the study area was 200 mm and that the groundwater depletion rate, which is being observed by the water company of Qazvin, was strongly decreasing during 2019-2025. The subsidence variations were related to groundwater depletion and land use, as the northern part of the region was predominantly used for agriculture, and intensive agricultural activities have led to overexploitation of the aquifers, so that the subsidence rate was higher, while it was quite low in the southern part, which is used for residential purposes.
Conclusion: The northern, western, and central parts of the study area were affected by a high subsidence rate. In addition, groundwater abstraction between 2019 and 2025 was much higher than that of the central part. The correspondence between the groundwater depletion and the estimated subsidence rate indicated the impact of groundwater overexploitation on the occurrence of subsidence in recent years.
 
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References
1. Angornai S, Memarian H, Shariat Panahi M, Bolourchi MJ (2016). Dynamic modeling of land subsidence in Tehran plain. Scientific Quarterly Journal of GeoScience. 25(97):211-220. [Persian] [Link]
2. Azarakhsh Z, Azadbakht M, Matkan A (2022). Estimation, modeling, and prediction of land subsidence using Sentinel-1 time series in Tehran-Shahriar plain: A machine learning-based investigation. Remote Sensing Applications: Society and Environment. 25:100691. [Link] [DOI:10.1016/j.rsase.2021.100691]
3. Babaee S, Mousavi Z, Masoumi Z, Hojati Malekshah A, Roostaei M, Aflaki M (2020). Land subsidence from interferometric SAR and groundwater patterns in the Qazvin plain, Iran. International Journal of Remote Sensing. 41(12):4780-4798. [Link] [DOI:10.1080/01431161.2020.1724345]
4. Buzzanga B, Bekaert DP, Hamlington BD, Sangha SS (2020). Toward sustained monitoring of subsidence at the coast using InSAR and GPS: An application in Hampton Roads, Virginia. Geophysical Research Letters. 47(18):e2020GL090013. [Link] [DOI:10.1029/2020GL090013]
5. Costantini M (2002). A novel phase unwrapping method based on network programming. IEEE Transactions on Geoscience and Remote Sensing. 36(3):813-821. [Link] [DOI:10.1109/36.673674]
6. Dai K, Liu G, Li Z, Li T, Yu B, Wang X, et al (2015). Extracting vertical displacement rates in Shanghai (China) with multi-platform SAR images. Remote Sensing. 7(8):9542-9562. [Link] [DOI:10.3390/rs70809542]
7. Farshbaf A, Mousavi MN, Shahnazi S (2024). Vulnerability assessment of power transmission towers affected by land subsidence via interferometric synthetic aperture radar technique and finite element method analysis: A case study of Zanjan and Qazvin provinces. Environment, Development and Sustainability. 26(4):10845-10864. [Link] [DOI:10.1007/s10668-023-03127-x]
8. Faso B, Verde C, Rica C, Salvador E, Islands M, Guinea PN, et al (2020). Midterm comprehensive review of the implementation of the international decade for action, "water for sustainable development", 2018-2028. New York: United Nations. [Link]
9. Galloway DL, Burbey TJ (2011). Regional land subsidence accompanying groundwater extraction. Hydrogeology Journal. 19(8):1459-1486. [Link] [DOI:10.1007/s10040-011-0775-5]
10. Galoie M, Motamedi A (2022). Modeling infiltration management in a watershed using SWAT software and investigating the impact of groundwater levels: Qazvin province. Report of Shared Project between Vice presidency of Iran and Science Ministry of China. [Link]
11. Gholamian F, Mousavi Z (2016). Assessment of decreasing rate of groundwater and earth surface subsidence by using GRACE satellite and InSAR data (Qazvin plain). Proceedings of the 17th Iranian Geophysical conference; 2016 May 10-12; Tehran, Iran. Tehran: Shahid Beheshti press. [persian] [Link]
12. Haghshenas Haghighi M, Motagh M (2024). Uncovering the impacts of depleting aquifers: A remote sensing analysis of land subsidence in Iran. Science Advances. 10(19). [Link] [DOI:10.1126/sciadv.adk3039]
13. Hanssen RF (2001). Radar interferometry: Data interpretation and error analysis. Dordrecht: Springer. [Link] [DOI:10.1007/0-306-47633-9]
14. Hosseini-Moghari SM, Araghinejad S, Tourian MJ, Ebrahimi K, Döll P (2020). Quantifying the impacts of human water use and climate variations on recent drying of Lake Urmia basin: The value of different sets of spaceborne and in situ data for calibrating a global hydrological model. Hydrology and Earth System Sciences. 24(4):1939-1956. [Link] [DOI:10.5194/hess-24-1939-2020]
15. ILNA News Agency (2022). Reports in "subsidence in Qazvin plain" [Internet]. Tehran: Iranian Labour News Agency [cited 2021 July 24th]. Available from: https://www.ilna.ir/. [Persian] [Link]
16. Iran Ministry of Energy (2022). Report on the status of forbidden and free plains of Iran. Water Resources Management Company, Tehran. [Link]
17. Janbaz Fotamy M, Kholghi M, Abdeh Kolahchi A, Roostaei M (2020). Land subsidence assessment due to groundwater exploration by using differential radar interferometry technique, case study: Qazvin province. Iran-Water Resources Research. 16(3):133-147. [Persian] [Link]
18. Janbaz Fotamy M, Kholghi M, Abdeh Kolahchi A, Roostaei M (2023). The performance of the evidence weighting in GIS for determining the effective factors on the land subsidence in Qazvin Plain. Iran-Water Resources Research. 19(3):118-135. [Persian] [Link]
19. Kaplan G, Fine L, Lukyanov V, Manivasagam VS, Tanny J, Rozenstein O (2021). Normalizing the local incidence angle in sentinel-1 imagery to improve leaf area index, vegetation height, and crop coefficient estimations. Land. 10(7):680. [Link] [DOI:10.3390/land10070680]
20. Moghaddam N, Kholghi M (2025). Analysis of groundwater table decline and salinity intensification in the Qazvin Plain: Implications from a water resources governance perspective. Iranian Journal of Irrigation & Drainage. 19(3):469-487. [Persian] [Link]
21. Motagh M, Walter TR, Sharifi MA, Fielding E, Schenk A, Anderssohn J, et al (2008). Land subsidence in Iran caused by widespread water reservoir overexploitation. Geophysical Research Letters. 35(16). [Link] [DOI:10.1029/2008GL033814]
22. Nouri Qeydari R (2014). Study of land subsidence and its prediction in the Qazvin Plain [dissertation]. Damghan: University of Science & Basic Research Damghan. [Persian] [Link]
23. Pourghasemi HR, Mohseni Saravi M (2018). Land-subsidence spatial modeling using generalized additive model data mining technique. Watershed Management Research. 30(4):20-34. [Persian] [Link]
24. Rosen PA, Gurrola E, Sacco GF, Zebker H (2012). The InSAR scientific computing environment. Proceedings of the 9th European Conference on Synthetic Aperture Radar. Nuremberg: VDE. p. 730-733. [Link]
25. Shadfar S, Nasiri E, Chitgar S, Ahmadi A (2016). Hazard zonation of land subsidence using analytical hierarchy process (AHP) case study (city of Buin Zahra). Geographical Journal of Territory. 12(48):101-116. [Persian] [Link]
26. Tatar M, Jackson J, Hatzfeld D, Bergman E (2007). The 2004 May 28 Baladeh earthquake (M w 6.2) in the Alborz, Iran: Overthrusting the South Caspian Basin margin, partitioning of oblique convergence and the seismic hazard of Tehran. Geophysical Journal International. 170(1):249-261. [Link] [DOI:10.1111/j.1365-246X.2007.03386.x]
27. Xu Y, Wu Z, Zhang H, Liu J, Jing Z (2023). Land subsidence monitoring and building risk assessment using InSAR and machine learning in a Loess Plateau City-A case study of Lanzhou, China. Remote Sensing. 15(11):2851. [Link] [DOI:10.3390/rs15112851]
28. Yuan M, Li M, Liu H, Lv P, Li B, Zheng W (2021). Subsidence monitoring base on SBAS-InSAR and slope stability analysis method for damage analysis in mountainous mining subsidence regions. Remote Sensing. 13(16):3107. [Link] [DOI:10.3390/rs13163107]