Zoning of land subsidence risk in the central plain of Alborz province using radar interferometry technique and ARAS multi-criteria analysis algorithm

Document Type : Research Article

Authors

1 Professor, Department of Natural Geography, Faculty of Social Sciences, University of Mohaghegh Aredebili, , Ardebil, Iran

2 PhD student in geomorphology, Mohaghegh Ardabili University, Ardebil, Iran

3 PhD in Geomorphology, Mohaghegh Ardabili University, Ardebil, Iran

Abstract

One of the dangers that has occurred in many areas in recent years is the dangers of subsidence. The central plain of Alborz province has also faced a sharp drop in groundwater levels in recent years, which has caused this area to be at risk of subsidence. The purpose of this study is in the first stage of subsidence assessment using radar interferometry technique in SNAP software environment, using the A1 Sentinel image capability and also in relation to zoning of susceptible areas with ARAS multi-criteria algorithm in software environment. Edrisi was implemented in the period of 2016 and 2021. The results of the present study showed that the amount of zero to 300 mm of subsidence has been created in the study area, with the highest amount of subsidence in the central part (Mehrshahr, Khorramdasht, Mohammadshahr) and then in the south. The west is concentrated in Mahdasht. According to the results of subsidence risk zoning; Criteria of water level decline, land use, slope and geology, with weight coefficients of 0.151, 0.147, 0.43 and 0.136, respectively, are the most important factors involved in creating the risk of subsidence of the study area and respectively 55. 135 and 192.28 square kilometers of the area have a very high risk. In addition, the results of the correlation coefficient between the map extracted from the radar interferometry with the water level drop of the wells is 0.89 and with the subsidence zoning map is 0.98. Finally, it can be said that the most important factor involved in increasing the amount and potential of subsidence of the central plain of Alborz province is the excessive use of groundwater and falling water levels.

Keywords

References

[1]. Sharifi Kia, Mohammad, Determining the extent and amplitude of land subsidence using radar interference method in Nogh-Bahraman plain, Journal of Spatial Planning and Planning 2012: Volume 16, Number 3, pp. 73-55. [Persian]
[2]. Shafiee, Najmeh, Mokhtari, Leilagli, Amir Ahmadi, Abolghasem, Zandi, Rahman. Investigation of aquifer subsidence in Nurabad plain using radar interferometry method. Quantitative Geomorphological Research 2020:, 8 (4), pp. 93-111. [Persian]
[3]. Shirani Kourosh, Pasandi Mehrdad, Ebrahimi Babak. Investigation of land subsidence in Najafabad plain of Isfahan using radar differential interferometry technique. Journal of Soil and Water Sciences 2021: 25 (1): 127-105. [Persian]
[4]. Montazeriun, Maryam; Aslani, Fereshteh. Landslide risk assessment using GIS in Tehran and Alborz provinces. Crisis Prevention and Management Knowledge Quarterly 2019: Volume 9, Number 1, pp. 13-1. [Persian]
[5]. Abidin H. Z., Andreas H., Gumilar I., and Brinkman J. J., On correlation between urban development, land subsidence and flooding phenomena in Jakarta, Changes in Flood Risk and Perception in Catchments and Cities (HS01 – IUGG2015). Published by Copernicus Publications on behalf of the International Association of Hydrological Sciences 2015.
[6]. Dong, J., Zhang, L., Tang, M., Liao, M., Xu, Q., Gong, J., & Ao, M.. Mapping landslide surface displacements with time series SAR interferometry by combining persistent and distributed scatterers: A case study of Jiaju landslide in Danba, China. Remote Sensing of Environment 2018: 205,180–198.
[7]. Shirani Kourosh, Pasandi Mehrdad, Ebrahimi Babak. Investigation of land subsidence in Najafabad plain of Isfahan using radar differential interferometry technique. Journal of Soil and Water Sciences 2021: 25 (1): 127-105. [Persian]
[8]. Bou kheir, R., Cerdan, O & Abdelah, C. Regional soil erosion risk mapping in Lebanon. Geomorphology 2006: 82, 347-359.
[9]. Aher P, Adinarayana J, Gorantiwar SD Prioritization of watersheds using multi-criteria evaluation through the fuzzy analytical hierarchy process. Agric Eng Int CIGR J 2013 :15(1):11–18.
[10]. Georgiou, D., Mohammed, E.S., Rozakis, S. Multi-criteria decisionmaking on the energy supply configuration of autonomous desalination units. Renew. Energy 2015: 75, 459–467.
 
[11]. Arab Ameri, A., Pourghasemi, H.R., Cerda. A., (2018), Erodibility prioritization of sub-watersheds using morphometric parameters analysis and its mapping: A comparison among TOPSIS, VIKOR, SAW, and CF multi-criteria decision making models, Science of The Total Environment 2015: 613-614.
[12]. Turani, Marjan, Aq Atabay, Maryam, Rustaei, Meh Asa. Study of subsidence in Gorgan city using radar interferometry method. Journal of Spatial Planning 2019: 8 (27), 117-128. [Persian]
[13]. Kooh Banani, Hamid, Yazdani, Mohammad Reza, Hosseini, Seyed Keyvan.. Zoning of land subsidence risk using radar interference (Case study: Kashmar and Khalilabad plains. Desert Management 2019: 7 (13), 76-65. [Persian]
[14]. Ebrahimi, Atrin, Ghasemi, Afshan, Ganjaeian, Hamid. Monitoring the subsidence of Pakdasht urban area using radar interferometry method. Geography and Human Relations 2020: 2 (4), 29-41. [Persian]
[15]. Asghari Saraskanrood, Sayad, Mohammadzadeh Shishegran, Maryam. Estimation of subsidence using radar interferometry technique and groundwater parameters and land use (Case study: Shahriar plain. Quantitative geomorphological research 2021: 10 (1), 54-40. [Persian]
[16]. Bhattarai, R. Alifu, H. Maitiniyazi, A. Kondoh. Detection of Land Subsidence in Kathmandu Valley, Nepal, Using DInSAR Technique, Land 2017: 6(2(, 1-178.
[17]. Minh, D. H. T. Tran., Q, C. Pham, Q.N, Dang, T, Nguyen, D.A, El-Moussaw, A.. "Measuring Ground Subsidence in Ha Noi Through the Radar Interferometry Technique Using TerraSAR-X and Cosmos SkyMed Data," in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 2019: 10,3874-3884.
[18]. Huang, G. Fan, H. Lu, L. Yu, W., The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences 2020: 1-6.
[19]. Ranjgar, Babak, Seyed V. Razavi-Termeh, Fatemeh Foroughnia, Abolghasem Sadeghi-Niaraki, and Daniele Perissin.. "Land Subsidence Susceptibility Mapping Using Persistent Scatterer SAR Interferometry Technique and Optimized Hybrid Machine Learning Algorithms" Remote Sensing 2021. [Persian]
[20]. Qanvati, Ezatullah, Sharifi Kia, Mohammad, Hosseini, Seyed Ibrahim. Explaining the effect and geomorphological process of subsidence phenomenon in changing the land pattern of geomorphological forms Case study of Yazd-Ardakan plain. Quantitative Geomorphological Research 2019: 8 (3), 1-16. [Persian]
[21]. Qara Cheloo, Saeed, Akbari Quchani, Hesam, Glian, Saeed, Ganji, Kamran. Assessment of land subsidence in relation to groundwater with the help of Sentinel-1 and Alus-1 radar satellites (study area: Mashhad plain). Remote Sensing and GIS in Natural Resources 2021: 12 (3), 40-61.
[22]. Abdul Maleki, Ali, Maleki, Amjad, Khazaei, Ali. Monitoring the elevation of the earth and analyzing its geomorphological effects using telemetry data. Remote Sensing and Geographic Information System in Natural Resources 2021: 12 (4), 118-95. [Persian]
[23]. Alizadeh Reza, Izadi Hassan, Arasteh Mojtaba. Ranking of nature-based tourism capacity in mountainous areas, case study: Eastern region of Lorestan province. Planning and arranging space 2021: 25 (1): 117-142. [Persian]
[24]. Anamradnejad, Rahim Bardi, Nikpour, Amer, Hassani, Zohreh. Physical-Spatial Analysis of Urban Areas Based on Intelligent Urban Growth Indicators (Case Study: Babol), Journal of Urban Research and Planning 2019: 9 (34), 19-30. [Persian]
[25]. Hoseini H.. Use fuzzy interface systems to optimize land suitability evaluation for surface and trickle irrigation, Information Processing in Agriculture 2019: 6 (1): 11-19. [Persian]
[26]. Alinezhad A, Khalili J.. New Methods and Applications in Multiple Attribute Decision Making (MADM). International Series in Operations Research & Management Science 2019.[Persian]
[27]. Tuş A, Aytaç Adalı E. The new combination with CRITIC and WASPAS methods for the time and attendance software selection problem, opsearch 2019: 56: 528–538.
[28]. Diani Leila, Portaheri Mehdi, Rokanuddin Eftekhari Abdolreza, Ahmadi Hassan. Ranking of the main structures of organizing the worn-out structures of the villages around the metropolises using the cumulative ratio evaluation method (ARAS) (Case study: around the metropolis of Tehran). Planning and arranging space 2019: 22 (3): 145-181.
[29]. Zavadskas, E.; Turskis, Z. a new additive ratio assessment (ARAS) method in multicriteria decision‐making, Technological and Economic Development of Economy 2010: 16(2) 159-172.
Iranian journal of Ecohydrology
Volume 9, Issue 2
July 2022
Pages 353-371

Files

History

  • Receive Date: 29 November 2021
  • Revise Date: 20 January 2022
  • Accept Date: 01 May 2022
  • First Publish Date: 22 June 2022
  • Publish Date: 22 June 2022

Share

How to cite

Statistics