Investigation of the Relationship between Land Surface Changes due to Subsidence and Groundwater using Sentinel-1 Satellite Images and Statistical Models (Case study: Varamin plain)

Abstract

One of the most important issues that has been considered by many researchers in recent years is the study of the phenomenon of land subsidence. The purpose of studying subsidence is to examine the risks and consequences that can result from it over many years. In their research, most researchers considered the occurrence of earthquakes and excessive abstraction of groundwater aquifers due to the drilling of a large number of illegal wells as the most important causes of subsidence. The aim of this study was to obtain a statistical relationship between groundwater level changes and the rate of vertical movement of the earth's surface using linear regression and grade 3 models and using InSAR radar interferometry technique in Varamin plain between 2014 and 2019. Most of the surface of Varamin plain is covered by agricultural lands and therefore it can be said that the uncontrolled abstraction of groundwater is considered as the main cause of vertical movements of the earth. In order to analyze the subsidence that occurred in this plain, Snap software was used and by applying the desired filters to eliminate the noise in the initial images, surface displacement maps were obtained in Varamin plain. The images used for the surface of the earth from 2014 to 2019 were obtained by Sentinel-1 satellite SAR sensor as ascending, and finally, by comparing the obtained statistical models from the fluctuation of the aquifer and the ground, it was found that the linear regression model has a better predictive power than the 3rd degree regression model.

Keywords

• land subsidence
• ground water level
• insar
• snap
• sentinel-1