Volume 18, Issue 3 (8-2026)
jorar 2026, 18(3): 173-180 |
Back to browse issues page
Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
Khabazi M, Abdi S, Bay N, Oveisi N. Assessment of Land Surface Displacement Along the Hamadan–Sanandaj Railway Corridor and Its Relationship with Groundwater Level Changes. , jorar. 2026; 18 (3) :173-180
URL: http://jorar.ir/article-1-1092-en.html
URL: http://jorar.ir/article-1-1092-en.html
Associate Professor, Department of Physical Geography, Faculty of Humanities, Tarbiat Modarres University, Tehran, Iran.
Abstract: (6 Views)
INTRODUCTION: Land subsidence is a geomorphological process that can have environmental, social, and economic consequences. In Iran, this phenomenon is associated with factors such as unsustainable groundwater extraction, climate variability, and increasing water demand. This study aimed to assess land surface displacement along the Hamadan–Sanandaj railway corridor, focusing on the Dehgolan–Qorveh and Hamadan–Bahar sections, and to examine its relationship with groundwater level changes.
METHODS: An integrated approach based on literature review and field studies was adopted. Sentinel-1 time-series images were processed using Interferometric Synthetic Aperture Radar (InSAR), and the resulting displacement estimates were compared with groundwater level data recorded by regional piezometers.
FINDINGS: Analysis of Sentinel-1 radar imagery showed that the maximum negative displacement along the satellite Line of Sight (LOS) during the periods 2019–2020, 2020–2021, and 2021–2022 was 0.17, 1.10, and 1.50 cm, respectively. Higher displacement values were mainly concentrated in the Dehgolan–Qorveh area. Piezometric data were used to assess the relationship between groundwater level changes and land surface displacement.
CONCLUSION: Given the nature of radar measurements, the reported values represent displacement along the satellite LOS and should not be interpreted as direct measurements of vertical land subsidence without separating the displacement components. Continued land surface deformation may have implications for the stability of railway and road infrastructure. Therefore, continuous monitoring and integrated management of groundwater resources are essential.
METHODS: An integrated approach based on literature review and field studies was adopted. Sentinel-1 time-series images were processed using Interferometric Synthetic Aperture Radar (InSAR), and the resulting displacement estimates were compared with groundwater level data recorded by regional piezometers.
FINDINGS: Analysis of Sentinel-1 radar imagery showed that the maximum negative displacement along the satellite Line of Sight (LOS) during the periods 2019–2020, 2020–2021, and 2021–2022 was 0.17, 1.10, and 1.50 cm, respectively. Higher displacement values were mainly concentrated in the Dehgolan–Qorveh area. Piezometric data were used to assess the relationship between groundwater level changes and land surface displacement.
CONCLUSION: Given the nature of radar measurements, the reported values represent displacement along the satellite LOS and should not be interpreted as direct measurements of vertical land subsidence without separating the displacement components. Continued land surface deformation may have implications for the stability of railway and road infrastructure. Therefore, continuous monitoring and integrated management of groundwater resources are essential.
Keywords: Land subsidence, Land surface displacement, Interferometric Synthetic aperture radar, Hamadan–Sanandaj railway, Groundwater.
Article Type: Research article |
Subject:
Environmental disasters
References
1. Galloway DL, Jones DR, Ingebritsen SE. Land subsidence in the United States. Reston (VA): U.S. Geological Survey; 1999. (Circular; 1182). viii, 177 p. [DOI:10.3133/cir1182]
2. Shemshaki A, Bolourchi MJ, Entezam Soltani I. [Land subsidence in Tehran plain and factors contributing to its formation (Persian)]. In: Proceedings of the 24th Geosciences Conference; 2005; Tehran, Iran.
3. Sharifi Kia MR. [Determining the magnitude and extent of land subsidence using radar interferometry (D-InSAR) in the Noogh-Bahreman Plain (Persian)]. Journal of Spatial Planning. 2012;16(3):55-77.
4. Ravanfar SM. [Assessment of land subsidence using a raster model in a GIS (Persian)]. [Master's thesis]. Marvdasht: Islamic Azad University, Marvdasht Branch, Faculty of Engineering; 2015.
5. Sheikhi M, Shamsipour A, Feizi V, Davoudvandi T. [Vulnerability of informal settlements to natural hazards: a case study of Chahestaniha neighborhood in Bandar Abbas (Persian)]. Journal of Spatial Planning. 2012;16(2):101-120.
6. Afzali AA, Sharifikia M, Shayan S. [Vulnerability assessment of infrastructure and settlements due to land subsidence in Damghan Plain (Persian)]. Iranian Journal of Applied Geomorphology. 2013;1(1):61-73.
7. Angorani S, Memarian H, Shariat Panahi M, Bolourchi MJ. [Dynamic modeling of land subsidence in Tehran Plain (Persian)]. Geosciences. 2015;25(97):211-220.
8. Mirasi S, Rahnama H. [Analysis and evaluation of effective parameters affecting land subsidence (Persian)]. Journal of Modarres Civil Engineering.2016;16(1):45-54.
9. Papi R, Attarchi S, Soleimani M. [Analyzing time series of land subsidence in the west of Tehran province (Shahriar plain) and its relation to groundwater discharge by InSAR technique (Persian)]. Geography and Sustainability of Environment. 2020;10(34):109-128. [DOI:10.22126/ges.2020.4933.2182]
10. Noori R, Maghrebi M, Jessen S, et al. Decline in Iran's groundwater recharge. Nature Communications. 2023; 14:6674. [DOI:10.1038/s41467-023-42411-2]
11. Ganjaeian H, Ghasemi A, Ebrahimi A, Asadpor Z. [Evaluation of subsidence rate of Hamadan-Bahar plain using SBAS time series method (Persian)]. Arid Regions Geographic Studies. 2020;(36):62-73.
12. Ahmadi S, Soudmand Afshar R. [Monitoring of land subsidence in Qorveh and Chahardoli plains of Hamadan and Kurdistan provinces using PS-InSAR technique (Persian)]. Environment and Water Engineering. 2020;6 (3):219-233. [DOI:10.22034/jewe.2020.236939.1375]
13. Ghahroudi Tali M, Khodamoradi F, Ali Nouri K. [Effects of groundwater decline on land subsidence hazards in Dehgolan Plain, Kurdistan Province (Persian)]. Journal of Environmental Hazard Management. 2023;10(1):57-70.
14. Berardino P, Fornaro G, Lanari R, Sansosti E. A new algorithm for surface deformation monitoring based on small baseline differential SAR interferograms. IEEE Trans Geosci Remote Sens. 2002;40(11):2375-2383. [DOI:10.1109/TGRS.2002.803792]
15. Karimi S, Pourkhosravani M, Ramezani A. [Monitoring the land subsidence phenomenon using differential radar interferometry technique (case study: Khanmirza plain, Chaharmahal and Bakhtiari province) (Persian)]. Journal of Physical Geography. 2023;16(59):43-62.
16. Ghorbani Mohammadabadi S, Nejad Hosseini R, Ganjaeian H. [Analysis of the effective factors in the subsidence of the Qahavand plain using radar and satellite images (Persian)]. Geography and Human Relations. 2023;6(20):542-553.
17. Nouri-Sangarab S, Asghari Moghadam A, Jebraili Andrian N. [Assessment of subsidence potential in Ajabshir plain using artificial intelligence models and radar interferometry technique (Persian)]. Geosciences. 2023;33(129):71-84.
18. Helali L, Bagheri R, Momeni A. [Investigation of land subsidence using radar interferometry technique (case study: Semnan plain) (Persian)]. Journal of Hydrogeology. 2024;9(1):86-100.
19. Choubin B, Shirani K, Hosseini FS, Taheri J, Rahmati O. Scrutinization of land subsidence rate using a supportive predictive model: Incorporating radar interferometry and ensemble soft-computing. J Environ Manage. 2023;345:118685. [DOI:10.1016/j.jenvman.2023.118685]
20. Shi M, Chen B, Gong H, Li X, Chen W, Gao M, et al. Monitoring differential subsidence along the Beijing–Tianjin Intercity Railway with multiband SAR data. Int J Environ Res Public Health. 2019;16(22):4453. [DOI:10.3390/ijerph16224453]
21. Chang L, Sakpal NP, Oude Elberink S, Wang H. Railway infrastructure classification and instability identification using Sentinel-1 SAR and laser scanning data. Sensors (Basel). 2020;20(24):7108. [DOI:10.3390/s20247108]
22. Xue YA, Zou YF, Li HY, Zhang WZ. Regional subsidence monitoring and prediction along high-speed railways based on PS-InSAR and LSTM. Sci Rep. 2024;14:24622. [DOI:10.1038/s41598-024-76485-9]
23. Carlvik F, Mirzanamadi R, Torstensson PT, Eriksson LEB, Göransson G, Palmqvist CW. Remote sensing of track degradation using InSAR: A case study of the Iron Ore Line. Transp Res Procedia. 2025;86:313-320. [DOI:10.1016/j.trpro.2025.04.040]
Send email to the article author
| Rights and permissions | |
 |
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |
