Monitoring and Management of Land Subsidence Induced by Over-exploitation of Groundwater
Most plains in Iran are subject to land subsidence due to over-exploitation of groundwater mainly for agricultural purposes. Synthetic Aperture Radar (SAR) interferometry has shown its ability to provide precise measurements of the ground surface displacement at high spatial and temporal resolution. In SAR interferometry, the processed interferograms are combined together via interferogram stacking or time series analysis. Stacking is a temporal averaging of the interferograms which results in mean displacement velocity. However, time series analysis of a significant number of interferograms enables us to study the short-term as well as ling-term behavior of the subsidence. In this research, three different case studies were accomplished for subsidence monitoring. The subsidence in the Varamin plain was studied using 13 ENVISAR ASAR images spanning between 2003/08/03 and 2005/11/20. The maximum subsidence rate extracted from Small Baseline Subset (SBAS) time series was estimated as 0.4 m/year. The second case study was to monitor the subsidence in the Neyshabour plain. In this area, the interferogram stacking using 9 ENVISAT ASAR images spanning between 2004/01/10 and 2005/06/18 was applied. The maximum subsidence rate was estimated as 0.16 m/year. Groundwater level measurements made at piezometric wells were applied to compare to the interferometry results. The piezometric wells mostly show the increase in water level depth caused by over-exploitation of groundwater. The groundwater information jointly with stratigraphic profiles highly correlate with subsidence in the area. In the last case study, the Persistent Scatterer Interferometry (PSI) which is a proper method of time series analysis in areas with high decorrelation effects, was used in the Shahriar plain. A hybrid method of conventional and PSI was proposed in order to address the problem of monitoring the high-rate deformation. There are 22 ENVISAT ASAR images available in the study area spanning between 2003 and 2008. The maximum subsidence rate was estimated as 0.25 m/year. The time series analysis results were then compared to the groundwater level information at piezometric wells. Due to the low correlation between water level decline and subsidence rate at some piezometric wells, it can be concluded that other geology and hydrogeological factors play important role in controlling the subsidence occurrence. To show this, two data mining methods including Multi-Layer Perceptron (MLP) neural network as well as Support Vector Regression (SVR) were applied to model the subsidence in Shahriar plain using 6 different geology and hydrogeology factors as input and the subsidence rate extracted from interferometry as output of the model. These models can be further applied to estimate the subsidence rate in pixels in which the interferometry technique cannot measure the deformation due to some reasons including insufficient correlation.
KeywordsSubsidence Interferometry Persistent scatterer Groundwater information Data mining
We are grateful to European Space Agency (ESA) for providing ENVISAT ASAR data. We also would like to acknowledge the Geological Survey of Iran and Water Management Organization for providing the hydrogeological information.
- Arabi S, Montazerian AR, Maleki E, Talebi A (2005) Study of land subsidence in south-west of Tehran. J Surv 69:14–24Google Scholar
- Dehghani M, Valadan Zoej MJ, Hooper A, Hanssen RF, Entezam I, Saatchi S (2013) Hybrid conventional and Persistent Scatterer SAR interferometry for land subsidence monitoring in the Tehran Basin. Iran ISPRS J Photogramm Remote Sens 79:157–170. https://doi.org/10.1016/j.isprsjprs.2013.02.012CrossRefGoogle Scholar
- Galloway DL, Hudnut KW, Ingebritsen SE, Phillips SP, Peltzer G, Rogez F, Rosen PA (1998) Detection of aquifer system compaction and land subsidence using interferometric synthetic aperture radar, Antelope valley, Mojave Desert, California. Water Resour Res 34:2573–2585. https://doi.org/10.1029/98WR01285CrossRefGoogle Scholar
- Galloway DL, Jones DR, Ingebritsen SE (1999) Land subsidence in the United States. US Geological Survey Circular 1182:175Google Scholar
- Hooper A (2010) A statistical-cost approach to unwrapping the phase of InSAR time series. Fringe 2009 Workshop. http://home.utad.pt/~jjsousa/PARTILHA/Fringes2009/papers/p1_26hoop.pdf
- Lanari R, Lundgren P, Manzo M and Casu F (2004) Satellite radar interferometry time series analysis of surface deformation for Los Angeles, California, Geophys Res Lett 31. https://doi.org/10.1029/2004gl021294
- Li Z, Bethel J (2008) Image coregistration in SAR interferometry. www.isprs.org/proceedings/XXXVII/congress/1_pdf/72.pdf
- Schmidt DA, Burgmann R (2003) Time-dependent land uplift and subsidence in the Santa Clara valley, California, from a large interferometric synthetic aperture radar data set. J geophys Res. https://doi.org/10.1029/2002jb002267
- Shemshaki A, Blourchi MJ, Ansari F (2005) Earth subsidence review at Tehran plain-Shahriar first report. http://gsi.ir/General/Lang_en/Page_27/GroupId_01-01/TypeId_All/Start_20/Action_ListView/WebsiteId_13/3.html. Accessed Aug 2005