No abstract

Many areas worldwide are known to experience land subsidence due to groundwater extraction. It is traditionally assumed that subsidence extent and rates are controlled by groundwater extraction locations and volumes. Here, we reevaluate this assumption in the Mexico City metropolitan area by combining stratigraphic, hydrologic, geodetic, and demographic datasets. Integration of 115 years of leveling with 24 years of Interferometric Synthetic Aperture Radar (InSAR) and 14 years of GPS data reveals that subsidence rates have been mostly constant in Mexico City since at least 1950 and reach 50 cm/year. Analysis of InSAR and GPS data shows that no significant elastic deformation exists, demonstrating that the subsidence is almost fully irreversible. In Mexico City, no direct relationships exist between groundwater level fluctuations and subsidence rates or between pumping rates and subsidence rates. In contrast, a strong positive linear relationship is isolated between subsidence rates and the thickness of the upper aquitard. Through the integration of these long‐term datasets, we forecast that it will take ∼150 years to reach total compaction of the upper aquitard, which may lead to additional subsidence up to 30 m. With the potentiometric surface now deeper than most of the aquitard, clay's porewater rich in salts, chemical constituents, and pollutants is now flowing downward into the productive aquifer, hence decreasing water quality. Finally, our work shows that the consequences of land subsidence greatly influence the socioeconomic landscape in the Mexico City metropolitan area.

Land subsidence is a phenomenon present in several cities in central Mexico, and results from a combination of groundwater resources' overexploitation and the local stratigraphic nature. Furthermore, subsidence occurs inhomogeneously in space, producing differential vertical displacements, which affect both the natural media, as well as human-built structures. Subsidence associated structural-vulnerability assessments usually rely on direct field measurements to determine parameters such as angular distortion. However, the large areas in which land subsidence occurs (city-scale) in Mexico City hinders a direct quantification of differential displacements for all buildings and structures present in it. A Sentinel-1 based subsidence analysis shows that the highest velocities are located on the eastern sector of the city. This velocity map was used as the basis for a population density weighted land subsidence correlation analysis. Our Land Subsidence Risk assessment indicates that 15.43 % of the population of Mexico City live in intermediate, high and very-high risk zones which corresponds to 1 358 873 inhabitants. Therefore, a significant percentage of Mexico City's population is vulnerable to suffering damage in their housing structures due to land subsidence. Furthermore, the lower income inhabitants share a proportionally greater economic cost due to land subsidence and associated shallow faulting. The structural vulnerability analysis of the civil structures in the city was performed using angular distortion maps derived from the subsidence velocity gradient between October 2014-October 2017 period. These maps indicate that within this time window, ∼ 12 % of the total urbanized area in Mexico City had already exceeded a 0.002 radian angular distortion threshold; above which damage in civil structures is more likely to occur. In fact, more than 1 million people have already suffered damages in their houses due to the differential ground subsidence and the resulting structural angular distortion. With these results, we can evaluate correspondence between angular distortion map and critical infrastructure of the city, as a result, we found that between 0 % and 12.84 % of these buildings have undergone over 0.002 radian angular distortion.Published by Copernicus Publications on behalf of the International Association of Hydrological Sciences. 584 E. Fernández-Torres et al.: Land Subsidence risk maps and InSAR based angular distortion