Analysis of the influence of groundwater on land subsidence in Beijing based on the geographical weighted regression (GWR) model

Sci Total Environ. 2020 Oct 10:738:139405. doi: 10.1016/j.scitotenv.2020.139405. Epub 2020 May 19.

Abstract

A global geological phenomenon caused by natural or human activities is described as land subsidence. Groundwater extraction plays a significant part in causing land subsidence. Due to economic development, urban expansion, and rapid population expansion, the unscientific exploitation of groundwater in Beijing has been accelerated, which makes it the region with the fastest land subsidence rate in China. To study the spatial heterogeneity of land subsidence caused by groundwater aquifers level changes, the monitoring results of land subsidence in 2003-2010 years were analyzed by using PS-InSAR, based on ENVISAT ASAR in Beijing plain area. The maximum value of accumulated land subsidence in the study area is 707 mm, and in this study area multiple subsidence center areas have been formed. A GWR model based on a regular grid has been established by exploring the effects of unconfined aquifer (UA), first confined aquifer (FCA), second confined aquifer (SCA), third confined aquifer (TCA) on land subsidence and their spatial non-stationarity. The change of subsidence in all subsidence areas is positively related to the change of SCA water level. Except the fact that the main control factors of Liyuan and Songzhuang are the change of UA layer, the change of SCA is the main control factor of land subsidence in most subsidence areas. Though the contribution rate of SCA to land subsidence is the highest, the contribution rate of TCA has been increasing. It is predicted that the impact on land subsidence will increase year by year. The results of this will not only help to understand the spatial impact patterns of aquifers on land subsidence zones, but also to formulate optimal groundwater regulation and recharge policies. There is a scarcity of the consideration of the compressible layer in the study and it will become more comprehensive if further datasets are obtained.

Keywords: Aquifer; Land subsidence; Relevance; Spatial nonstationarity.