Abstract
The extent of the subsidence and the consequents damage to most of the residential and populated areas of Iran have made this phenomenon one of the most important natural hazards after the earthquake. Accordingly, in this research to assess the land subsidence risk, a GIS fuzzy logic spatial modeling was applied. In this regard, four stages were performed. In stage 1, 14 factors affecting subsidence including aquifer thickness, bedrock depth, Debi zonation of pumping wells, transmissivity, specific yield, Groundwater drawdown in 20 year, soil type, slope, altitude based on DEM, erosion, annual rainfall, distance of fault, lithological units, and land use, were prepared based on the literature review. In stage 2, the parameters were standardized with the fuzzy membership functions. Moreover, in stage 3, for aggregation parameters, several fuzzy overlay operation models were used. Finally, to verification of the models, the statistical benchmarks based on observed land subsidence were used. Accordingly, the “GAMMA 0.8” fuzzy overlay model with the most abundance of rank 1, and the “SUM” fuzzy overlay model with the most abundance of rank 16 among the other models are introduced as the most consistent and the worst consistent models with observed land subsidence data, respectively.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Aalipour Erdi, M., Malekmohammadi, B., & Jafari, H. R. (2017). Risk zoning of land subsidence due to groundwater level declining using fuzzy analytical hierarchy process. Iranian Journal of Watershed Management Science & Engineering, 11(38), 25–34.
Abdollahi, S., Pourghasemi, H. R., Ghanbarian, G. A., & Safaeian, R. (2018). Prioritization of effective factors in the occurrence of land subsidence and its susceptibility mapping using an SVM model and their different kernel functions. Bulletin of Engineering Geology and the Environment. https://doi.org/10.1007/s10064-018-1403-6.
Alimohammadi, A. (2009). Provision and preparation of provincial planning plan, Studies of natural and environmental resources, Analysis of the status of geology, mineral resources and soil. Retrieved from Deputy of Planning, Tehran Governorate, Iran.
Araya-Muñoz, D., Metzger, M. J., Stuart, N., Wilson, A. M. W., & Carvajal, D. (2007). A spatial fuzzy logic approach to urban multi-hazard impact assessment in Concepción, Chile. Science of the Total Environment, 576, 508–519. https://doi.org/10.1016/j.scitotenv.2016.10.077.
Arca, D., Kutoğlu, H. Ş., & Becek, K. (2018). Landslide susceptibility mapping in an area of underground mining using the multicriteria decision analysis method. Environmental Monitoring and Assessment, 190(725), 1–14. https://doi.org/10.1007/s10661-018-7085-5.
Atarzadeh, A. A., Tavana, B., & Abrazi, B. (2014). Quantitative and contamination studies of Varamin aquifer (groundwater studies). Tehran: Yekom Consulting Engineering.
Ayalew, L., Yamagishi, H., Marui, H., & Kanno, T. (2005). Landslides in Sado Island of Japan: Part II. GIS-based susceptibility mapping with comparisons of results from two methods and verifications. Engineering Geology, 81(4), 432–445. https://doi.org/10.1016/j.enggeo.2005.08.004.
Behyari, M., Alizadeh, A., & Mahmoodi, S. (2017). Evaluation of the effect active structures on land subsidence risk using multi-criteria decision models. Journal of Advanced Applied Geology, 7(24), 49–56. https://doi.org/10.22055/aag.2017.13229.
Berberian, M., & King, G. C. P. (1981). Towards a paleogeography and tectonic evolution of Iran. Canadian Journal of Earth Sciences, 18(2), 210–265. https://doi.org/10.1139/e81-019.
Bonham-Carter, G. F. (2014). Geographic information systems for geoscientists: Modelling with GIS. Elsevier Science. Retrieved July 6, 2019, from https://books.google.com/books?id=FkKeBQAAQBAJ.
Buhe, A., Tsuchiya, K., Kaneko, M., Ohtaishi, N., & Halik, M. (2007). Land cover of oases and forest in XinJiang, China retrieved from ASTER data. Advances in Space Research, 39(1), 39–45. https://doi.org/10.1016/j.asr.2006.02.056.
Burbey, T. J. (2002). The influence of faults in basin-fill deposits on land subsidence, Las Vegas Valley, Nevada, USA. Hydrogeology Journal, 10(5), 525–538. https://doi.org/10.1007/s10040-002-0215-7.
Calderhead, A. I., Therrien, R., Rivera, A., Martel, R., & Garfias, J. (2011). Simulating pumping-induced regional land subsidence with the use of InSAR and field data in the Toluca Valley, Mexico. Advances in Water Resources, 34(1), 83–97. https://doi.org/10.1016/j.advwatres.2010.09.017.
Chanapathi, T., Thatikonda, S., Pandey, V. P., & Shrestha, S. (2019). Fuzzy-based approach for evaluating groundwater sustainability of Asian cities. Sustainable Cities and Society, 44, 321–331. https://doi.org/10.1016/j.scs.2018.09.027.
Chavez, P. S., Berlin, G. L., & Sowers, L. B. (1982). Statistical method for selecting landsat MSS. Journal of Applied Photographic Engineering, 8(1), 23–30.
Chen, B., Gong, H., Lei, K., Li, J., Zhou, C., Gao, M., et al. (2019). Land subsidence lagging quantification in the main exploration aquifer layers in Beijing plain, China. International Journal of Applied Earth Observation and Geoinformation, 75, 54–67. https://doi.org/10.1016/j.jag.2018.09.003.
Chen, B., Gong, H., Li, X., Lei, K., Zhu, L., Gao, M., et al. (2016). Characterization and causes of land subsidence in Beijing, China. International Journal of Remote Sensing, 38(3), 808–826. https://doi.org/10.1080/01431161.2016.1259674.
Chen, Y., Shu, L., & Burbey, T. J. (2013). Composite subsidence vulnerability assessment based on an index model and index decomposition method. Human and Ecological Risk Assessment: An International Journal, 19(3), 674–698. https://doi.org/10.1080/10807039.2012.691405.
Choi, J. K., Kim, K. D., Lee, S., & Won, J. S. (2010). Application of a fuzzy operator to susceptibility estimations of coal mine subsidence in Taebaek City, Korea. Environmental Earth Sciences, 59(5), 1009–1022. https://doi.org/10.1007/s12665-009-0093-6.
Dai, F. C., & Lee, C. F. (2001). Terrain-based mapping of landslide susceptibility using a geographical information system: A case study. Canadian Geotechnical Journal, 38(5), 911–923. https://doi.org/10.1139/t01-021.
De Wiest, R. J. M. (1966). On the storage coefficient and the equations of groundwater flow. Journal of Geophysical Research (1896–1977), 71(4), 1117–1122. https://doi.org/10.1029/JZ071i004p01117.
Flores, B. E. (1986). A pragmatic view of accuracy measurement in forecasting. Omega, 14(2), 93–98. https://doi.org/10.1016/0305-0483(86)90013-7.
Galloway, D. L., & Burbey, T. J. (2011). Review: Regional land subsidence accompanying groundwater extraction. Hydrogeology Journal, 19(8), 1459–1486. https://doi.org/10.1007/s10040-011-0775-5.
Gu, T. & Wang, G. (2010). Application of fuzzy neural networks for predicting seismic subsidence coefficient of loess subgrade. In Paper Presented at the 2010 Sixth International Conference on Natural Computation. https://doi.org/10.1109/ICNC.2010.5583718.
Hoaglin, D. C. (2003). John W. Tukey and data analysis. Statistical Science, 18(3), 311–318.
Hu, L., Dai, K., Xing, C., Li, Z., Tomás, R., Clark, B., et al. (2019). Land subsidence in Beijing and its relationship with geological faults revealed by Sentinel-1 InSAR observations. International Journal of Applied Earth Observation and Geoinformation, 82, 101886. https://doi.org/10.1016/j.jag.2019.05.019.
Hu, R. L., Yue, Z. Q., Wang, L. C., & Wang, S. J. (2004). Review on current status and challenging issues of land subsidence in China. Engineering Geology, 76(1), 65–77. https://doi.org/10.1016/j.enggeo.2004.06.006.
IIEES. (2010). An analysis of source parameters of earthquakes in Tehran region. International Institute of Earthquake Engineering and Seismology. Retrieved July 6, 2019, from http://www.iiees.ac.ir/en/?s=varamin.
ITC. (2001). ILWIS 3.0, Academic user’s guide. Retrieved July 6, 2019, from http://www.itc.nl/ilwis/documentation/version3.asp.
Karsli, F., Atasoy, M., Yalcin, A., Reis, S., Demir, O., & Gokceoglu, C. (2009). Effects of land-use changes on landslides in a landslide-prone area (Ardesen, Rize, NE Turkey). Environmental Monitoring and Assessment, 156, 241. https://doi.org/10.1007/s10661-008-0481-5.
Kienast-Brown, S., & Boettinger, J. L. (2010). Applying the optimum index factor to multiple data types in soil survey. In J. L. Boettinger, D. W. Howell, A. C. Moore, A. E. Hartemink, & S. Kienast-Brown (Eds.), Digital soil mapping: Bridging research, environmental application, and operation (pp. 385–398). Dordrecht: Springer. https://doi.org/10.1007/978-90-481-8863-5_30.
Kim, K., Lee, S., & Oh, H. (2009). Prediction of ground subsidence in Samcheok City, Korea using artificial neural networks and GIS. Environmental Geology, 58(1), 61–70. https://doi.org/10.1007/s00254-008-1492-9.
Lashkaripour, G., Rostami Barani, H., Kohandel, A., & Torshizi, H. (2006). Decline in groundwater levels and land subsidence in the Kashmir plain. In Paper presented at the international conference on earth sciences, Tehran, Iran. Retrieved July 6, 2019, from https://www.researchgate.net/publication/294688542_Decline_in_groundwater_levels_and_land_subsidence_in_the_Kashmar_plain.
Lehmann, E. L., & Casella, G. (1998). Theory of point estimation (2nd ed.). New York: Springer.
Lewis, S. M., Fitts, G., Kelly, M., & Dale, L. (2014). A fuzzy logic-based spatial suitability model for drought-tolerant switchgrass in the United States. Computers and Electronics in Agriculture, 103, 39–47. https://doi.org/10.1016/j.compag.2014.02.006.
Lixin, Y., Fang, Z., He, X., Shijie, C., Wei, W., & Qiang, Y. (2011). Land subsidence in Tianjin, China. Journal of Environmental Earth Sciences, 62(6), 1151–1161. https://doi.org/10.1007/s12665-010-0604-5.
Lohman, S. (1961). Compression of elastic artesian aquifers. US Geol. Surv. Prof. Pap., 424-B, pp. 47–49. Retrieved July 6, 2019, from http://scholar.google.com/scholar_lookup?hl=en&volume=424&publication_year=1961&pages=47-49&journal=U.S.+Geol.+Surv.+Prof.+Pap.&author=S.+W.+Lohman&title=Compression+of+elastic+artesian+aquifers.
Mahmoudpour, M., Khamehchiyan, M., Nikudel, M., & Gassemi, M. (2013). Characterization of regional land subsidence induced by groundwater withdrawals in Tehran, Iran. Geopersia, 3(2), 49–62. https://doi.org/10.22059/jgeope.2013.36014.
Minderhoud, P. S. J., Coumou, L., Erban, L. E., Middelkoop, H., Stouthamer, E., & Addink, E. A. (2018). The relation between land use and subsidence in the Vietnamese Mekong delta. Science of the Total Environment, 634, 715–726. https://doi.org/10.1016/j.scitotenv.2018.03.372.
Mohebbi Tafreshi, A., Mohebbi Tafreshi, G., & Bijeh Keshavarzi, M. H. (2018). Qualitative zoning of groundwater to assessment suitable drinking water using fuzzy logic spatial modelling via GIS. Water and Environment Journal, 32(4), 607–620. https://doi.org/10.1111/wej.12358.
Mokhtari, H., & Espahbod, M. (2009). The investigation of hydrodynamic parameters potentiality of the Varamin plan regarding the variation of salinity gradient. Journal of the Earth, 4(2), 27–47.
Mortazavi Chamchali, M., & Ghazifard, A. (2019). The use of fuzzy logic spatial modeling via GIS for landfill site selection (case study: Rudbar-Iran). Environmental Earth Sciences, 78, 305. https://doi.org/10.1007/s12665-019-8296-y.
Motagh, M., Djamour, Y., Walter, T. R., Wetzel, H.-U., Zschau, J., & Arabi, S. (2007). Land subsidence in Mashhad Valley, northeast Iran: Results from InSAR, levelling and GPS. Geophysical Journal International, 168(2), 518–526. https://doi.org/10.1111/j.1365-246X.2006.03246.x.
Mousavi, S. M., Shamsai, A., Naggar, M. H. E., & Khamehchian, M. (2001). A GPS-based monitoring program of land subsidence due to groundwater withdrawal in Iran. Canadian Journal of Civil Engineering, 28(3), 452–464. https://doi.org/10.1139/l01-013.
Nakhaei, M., Mohebbi Tafresh, A., & Mohebbi Tafreshi, G. (2019). Modeling and predicting changes of TDS concentration in Varamin aquifer using GMS software. Journal of Advanced Applied Geology. https://doi.org/10.22055/aag.2019.27539.1903. (in press).
Nameghi, H., Hosseini, S. M., & Sharifi, M. B. (2013). An analytical procedure for estimating land subsidence parameters using field data and InSAR images in Neyshabur plain. Scientific Quarterly Journal of Iranian Association of Engineering Geology, 6(1&2), 33–50.
Nejatijahromi, Z., Nassery, H. R., Hosono, T., Nakhaei, M., Alijani, F., & Okumura, A. (2019). Groundwater nitrate contamination in an area using urban wastewaters for agricultural irrigation under arid climate condition, southeast of Tehran, Iran. Agricultural Water Management, 221, 397–414. https://doi.org/10.1016/j.agwat.2019.04.015.
NGOI. (2008). Topography map (1:50000). National Geographic Organization of Iran. Retrieved July 6, 2019, from http://www.ngo-org.ir/.
Oh, H. J., & Lee, S. (2010). Assessment of ground subsidence using GIS and the weights-of-evidence model. Engineering Geology, 115(1), 36–48. https://doi.org/10.1016/j.enggeo.2010.06.015.
Oh, H. J., Syifa, M., Lee, C. W., & Lee, S. (2019). Land subsidence susceptibility mapping using Bayesian, functional, and meta-ensemble machine learning models. Applied Sciences, 9(6), 1–17. https://doi.org/10.3390/app9061248.
Pacheco, J., Arzate, J., Rojas, E., Arroyo, M., Yutsis, V., & Ochoa, G. (2006). Delimitation of ground failure zones due to land subsidence using gravity data and finite element modeling in the Querétaro valley, México. Engineering Geology, 84(3), 143–160. https://doi.org/10.1016/j.enggeo.2005.12.003.
Park, I., Choi, J., Jin Lee, M., & Lee, S. (2012). Application of an adaptive neuro-fuzzy inference system to ground subsidence hazard mapping. Computers & Geosciences, 48, 228–238. https://doi.org/10.1016/j.cageo.2012.01.005.
Patel, N., & Kaushal, B. (2011). Classification of features selected through optimum index factor (OIF) for improving classification accuracy. Journal of Forest Research, 22(1), 99–105. https://doi.org/10.1007/s11676-011-0133-4.
Phien-wej, N., Giao, P. H., & Nutalaya, P. (2006). Land subsidence in Bangkok, Thailand. Engineering Geology, 82(4), 187–201. https://doi.org/10.1016/j.enggeo.2005.10.004.
Poland, J. F. (1984). Guidebook to studies of land subsidence due to groundwater withdrawal. United Nations Educational, Scientific and Cultural Organization, Paris, Studies and Reports in Hydrology 40:305. Retrieved July 6, 2019, from https://unesdoc.unesco.org/in/rest/annotationSVC/DownloadWatermarkedAttachment/attach_import_4d651c8f-42bd-478e-8f0e-318b0ef13ec2?_=065167engo.pdf.
Pradhan, B., Abokharima, M. H., Jebur, M. N., & Shafapour Tehrany, M. (2014). Land subsidence susceptibility mapping at Kinta Valley (Malaysia) using the evidential belief function model in GIS. Natural Hazards, 73(2), 1019–1042. https://doi.org/10.1007/s11069-014-1128-1.
Putra, D. P. E., Setianto, A., Keokhampui, K., & Fukuoka, H. (2011). Land subsidence risk asseessment in Karst region, case study: Rongkop, Gunung Kidul, Yogyakarta-Indonesia In Mitteilungen zur Ingenieurgeologie und Hydrogeologie-Festschrift zum 60. Geburtstag von Univ.Prof. Dr. Rafig Azzam. (pp. 39–50). RWTH Aachen University, German. Retrieved July 6, 2019, from https://repository.ugm.ac.id/id/eprint/134971.
Rafie, M., & Namin, F. S. (2015). Prediction of subsidence risk by FMEA using artificial neural network and fuzzy inference system. International Journal of Mining Science and Technology, 25(4), 655–663. https://doi.org/10.1016/j.ijmst.2015.05.021.
Raines, G. L., Sawatzky, D. L., & Bonham-Carter, G. F. (2010). New fuzzy logic tools in ArcGIS 10. ArcGIS 10.1. Retrieved July 6, 2019, from http://www.esri.com/news/arcuser/0410/files/fuzzylogic.pdf.
Rajabi, A. M., & Ghorbani, E. (2016). Land subsidence due to groundwater withdrawal in Arak plain, Markazi province, Iran. Arabian Journal of Geosciences, 9(738), 1–7. https://doi.org/10.1007/s12517-016-2753-7.
Ranjbar, A., & Ehteshami, M. (2019). Development of an uncertainty based model to predict land subsidence caused by groundwater extraction (case study: Tehran Basin). Geotechnical and Geological Engineering, 37(4), 3205–3219. https://doi.org/10.1007/s10706-019-00837-w.
Rezaee, P. (2016). Forecast locations at risk of subsidence plain Kermanshah. The Journal of Spatial Planning, 20(1), 235–251.
Sadeghi, A., Fonodi, M., Davari, M., Nourozi, M., Zakili, F., & Keihani, A. (Cartographer). (2006). One hundred thousandth geology map of Varamin, geological survey and mineral exploration of Iran. (in Persian). Retrieved July 6, 2019, from https://gsi.ir/fa/map/207/-%D9%88%D8%B1%D8%A7%D9%85%DB%8C%D9%86.
SCI. (2019). Population of the country in terms of gender in urban and rural areas. Statistical Center of Iran. Retrieved July 6, 2019, from https://www.amar.org.ir/english.
SCWMRI. (2010). Erosion, land use and soil maps (1:250000). Soil Conservation and Watershed Management Research Institute. Retrieved July 6, 2019, from https://www.environmental-expert.com/companies/soil-conservation-and-watershed-management-research-institute-scwmri-24937.
Sentinel-1. (2015). Retrieved July 6, 2019, from https://sentinel.esa.int/web/sentinel/missions/sentinel-1.
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). Territory, 12(48), 101–116.
Shemshaki, A., Boulourchi, M. J., & Entezam Soltani, I. (2006). The study of land subsidence in Tehran plain and its casual factors. In Paper presented at the 24th earth sciences meeting, Geological survey and mineral explorations of Iran. Retrieved July 6, 2019, from https://www.civilica.com/Paper-GSI24-GSI24_071.html.
Suh, J., Choi, Y. E., Park, H.-D., Yoon, S.-H., & Go, W.-R. (2013). Subsidence hazard assessment at the Samcheok Coalfield, South Korea: A case study using GIS. Environmental and Engineering Geoscience, 19(1), 69–83.
Taheri, Z., Barzghari, G., & Dideban, K. (2018). A framework to estimation of potential subsidence of the aquifer using algorithm genetic. Iran Water Resources Research, 14(2), 182–194.
Terzaghi, K. (1925). Principles of soil mechanics, IV—settlement and consolidation of clay. In Engineering news-record (vol. 95, pp. 874–878). Retrieved July 6, 2019, from http://scholar.google.com/scholar_lookup?hl=en&volume=95&publication_year=1925&pages=874-878&journal=Eng.+News+Rec.&issue=3&author=K.+Terzaghi&title=Principles+of+soil+mechanics%2C+IV%2C+Settlement+and+consolidation+of+clay.
Tien Bui, D., Shahabi, H., Shirzadi, A., Chapi, K., Pradhan, B., Chen, W., et al. (2018). Land subsidence susceptibility mapping in South Korea using machine learning algorithms. Sensors (Basel, Switzerland), 18(8), 1–20. https://doi.org/10.3390/s18082464.
TRWA. (2018). Report of groundwater resources studies in Varamin area. Tehran Regional Water Authority. (in Persian).
UNESCO. (2018). Proposal for the establishment of the land subsidence international initative (LaSII). United Nations Educational, Scientific and Cultural Organization, Paris. Retrieved July 6, 2019, from https://www.google.com/url?sa = t&rct = j&q = &esrc = s&source = web&cd = 2&cad = rja&uact = 8&ved = 2ahUKEwit4vSPqs3jAhUisaQKHe_NA-kQFjABegQIAhAC&url = https%3A%2F%2Fen.unesco.org%2Fsites%2Fdefault%2Ffiles%2Fic-xiii_ref_5_land_subsidence.pdf&usg = AOvVaw0_RGemY4ifoJiBQDz7dBnN.
USGS. (2019a). Land subsidence in California. Cause and effect. United State Geological Survey. Retrieved July 6, 2019, from https://www.usgs.gov/centers/ca-water-ls/science/cause-and-effect.
USGS. (2019b). Land subsidence. United State Geological Survey. Retrieved July 6, 2019, from https://www.usgs.gov/special-topic/water-science-school/science/land-subsidence?qt-science_center_objects=0#qt-science_center_objects.
Wang, H. W., Lin, C. W., Yang, C. Y., Ding, C. F., Hwung, H. H., & Hsiao, S. C. (2018). Assessment of land subsidence and climate change impacts on inundation hazard in Southwestern Taiwan. Irrigation and Drainage, 67(S1), 26–37. https://doi.org/10.1002/ird.2206.
Wang, G., Qin, L., Li, G., & Chen, L. (2009). Landfill site selection using spatial information technologies and AHP: A case study in Beijing, China. Journal of Environmental Management, 90(8), 2414–2421. https://doi.org/10.1016/j.jenvman.2008.12.008.
WRI. (2014). Prediction of subsidence due to groundwater resource utilization using combined modeling and interferometric technique in radar satellite imagery. Water Research Institute. Retrieved July 6, 2019, from Iran Ministry of Energy. http://wrr-wri.ir/wp-content/uploads/2017/12/Qom.pdf.
Yu, H. M., Wu, Y. X., Shen, J. S., & Zhou, A. N. (2018). Assessment of social-economic risk of Chinese dual land use system using fuzzy AHP. Sustainability, 10(7), 2541. https://doi.org/10.3390/su10072451.
Zadeh, L. A. (1965). Fuzzy sets. Information and Control, 8(353), 338–353. https://doi.org/10.1016/S0019-9958(65)90241-X.
Acknowledgements
The authors are thankful to Dr. Shemshaki and Dr. Morsali in Geological Survey and Mineral Exploration of Iran (GSI) and Dr. Heydarian and Dr. Mokhtari in Regional Water Company of Tehran (RWCT) for providing the necessary data to carry out this work.
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
The authors declare that they have no conflict interest.
Ethical standards
It is confirmed that this manuscript is an original work of the authors and has not been published or under review in another refereed journal, and is not published anywhere.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Mohebbi Tafreshi, G., Nakhaei, M. & Lak, R. Land subsidence risk assessment using GIS fuzzy logic spatial modeling in Varamin aquifer, Iran. GeoJournal 86, 1203–1223 (2021). https://doi.org/10.1007/s10708-019-10129-8
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10708-019-10129-8