Control and Prevent Land Subsidence Caused by Foundation Pit Dewatering in a Coastal Lowland Mega City: Indicator Definition, Numerical Simulation and Regression Analysis

Coastal mega cities are often commercial centers because of convenient traffic. Safe elevation above sea level is vital for their sustainable development. Global climate change and sea level rising increase flood risk especially in the lowland subsidence area. Shanghai of China was selected as research background. Although groundwater exploitation had been strictly restrained to control land subsidence and reserve safe elevation, lowering groundwater level during underground excavation cannot be avoided. Foundation pit dewatering (FPD) was intensively performed in underground exploitation during urbanization and city renewal. The FPD settlement accelerated land subsidence. Controlling FPD subsidence was urgent. Normally, the maximum horizontal influence radius of foundation pit excavation was less than three times excavation depth (H), and the 3H settlement was only caused by the FPD. The 3H maximum settlement was defined as the evaluating indicator of FPD land subsidence, and the corresponding 3H drawdown was defined as the control indicator of land subsidence. The FPD conceptual models were established on the basis of estimation and investigation of foundation pit information, including pit area, pit shape, pit depth, and curtain depth. Numerical models were established and a total of 5650 FPD numerical simulations were performed to investigate the land subsidence and FPD drawdown. Multi-factor regression analysis was conducted to obtain relations between land subsidence and FPD drawdown. Regression models were established between the 3H drawdown and the shape, area, depth, and curtain depth of foundation pit on the basis of the numerical simulations. A typical example introduced to verify the regression models. The regression models were used to manage the FPD land subsidence by controlling the 3H FPD drawdown. The results can provide reference for the land subsidence control in a coastal lowland city.

Integration of Numerical Models and InSAR Techniques to Assess Land Subsidence Due to Excessive Groundwater Abstraction in the Coastal and Lowland Regions of Semarang City

This study was carried out to assess land subsidence due to excessive groundwater abstraction in the northern region of Semarang City by integrating the application of both numerical models and geodetic measurements, particularly those based on the synthetic aperture radar interferometry (InSAR) technique. Since 1695, alluvial deposits caused by sedimentations have accumulated in the northern part of Semarang City, in turn resulting in changes in the coastline and land use up to the present. Commencing in 1900, excessive groundwater withdrawal from deep wells in the northern section of Semarang City has exacerbated natural compaction and aggravated the problem of land subsidence. In the current study, a groundwater model equivalent to the hydrogeological system in this area was developed using MODFLOW to simulate the hydromechanical coupling of groundwater flow and land subsidence. The numerical computation was performed starting with the steady-state flow model from the period of 1970 to 1990, followed by the model of transient flow and land subsidence from the period of 1990 to 2010. Our models were calibrated with deformation data from field measurements collected from various sources (e.g., leveling, GPS, and InSAR) for simulation of land subsidence, as well as with the hydraulic heads from observation wells for simulation of groundwater flow. Comparison of the results of our numerical calculations with recorded observations led to low RMSEs, yet high R2 values, mathematically indicating that the simulation outcomes are in good agreement with monitoring data. The findings in the present study also revealed that land subsidence arising from groundwater pumping poses a serious threat to the northern part of Semarang City. Two groundwater management measures are proposed and the future development of land subsidence is accordingly projected until 2050. Our study shows quantitatively that the greatest land subsidence occurs in Genuk District, with a magnitude of 36.8 mm/year. However, if the suggested groundwater management can be implemented, the rate and affected area of land subsidence can be reduced by up to 59% and 76%, respectively.

Spatially Varying Relationships between Land Subsidence and Urbanization: A Case Study in Wuhan, China

Land subsidence has become an increasing global concern over the past few decades due to natural and anthropogenic factors. However, although several studies have examined factors affecting land subsidence in recent years, few have focused on the spatial heterogeneity of relationships between land subsidence and urbanization. In this paper, we adopted the small baseline subset-synthetic aperture radar interferometry (SBAS-InSAR) method using Sentinel-1 radar satellite images to map land subsidence from 2015 to 2018 and characterized its spatial pattern in Wuhan. The bivariate Moran’s I index was used to test and visualize the spatial correlations between land subsidence and urbanization. A geographically weighted regression (GWR) model was employed to explore the strengths and directions of impacts of urbanization on land subsidence. Our findings showed that land subsidence was obvious and unevenly distributed in the study area, the annual deformation rate varied from −42.85 mm/year to +29.98 mm/year, and its average value was −1.0 mm/year. A clear spatial pattern for land subsidence in Wuhan was mapped, and several apparent subsidence funnels were primarily located in central urban areas. All urbanization indicators were found to be significantly spatially correlated with land subsidence at different scales. In addition, the GWR model results showed that all urbanization indicators were significantly associated with land subsidence across the whole study area in Wuhan. The results of bivariate Moran’s I and GWR results confirmed that the relationships between land subsidence and urbanization spatially varied in Wuhan at multiple spatial scales. Although scale dependence existed in both the bivariate Moran’s I and GWR models for land subsidence and urbanization indicators, a “best” spatial scale could not be confirmed because the disturbance of factors varied over different sampling scales. The results can advance the understanding of the relationships between land subsidence and urbanization, and they will provide guidance for subsidence control and sustainable urban planning.