Abstract
The Mekong delta, like many deltas around the world, is subsiding at a relatively high rate, predominately due to natural compaction and groundwater overexploitation. Land subsidence influences many urbanized areas in the delta. Loading, differences in infrastructural foundation depths, land-use history, and subsurface heterogeneity cause a high spatial variability in
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subsidence rates. While overall subsidence of a city increases its exposure to flooding and reduces the ability to drain excess surface water, differential subsidence results in damage to buildings and above-ground and underground infrastructure. However, the exact contribution of different processes driving differential subsidence within cities in the Mekong delta has not been quantified yet. In this study we aim to identify and quantify drivers of processes causing differential subsidence within three major cities in the Vietnamese Mekong delta: Can Tho, Ca Mau and Long Xuyen. Satellite-based PS-InSAR (Persistent Scatterer Interferometric Synthetic Aperture Radar) vertical velocity datasets were used to identify structures that moved at vertical velocities different from their surroundings. The selected buildings were surveyed in the field to measure vertical offsets between their foundation and the surface level of their surroundings. Additionally, building specific information, such as construction year and piling depth, were collected to investigate the effect of piling depth and time since construction on differential vertical subsidence. Analysis of the PS-InSAR-based velocities from the individual buildings revealed that most buildings in this survey showed less vertical movement compared to their surroundings. Most of these buildings have a piled foundation, which seems to give them more stability. The difference in subsidence rate can be up to 30 mm/year, revealing the contribution of shallow compaction processes above the piled foundation level (up to 20 m depth). This way, piling depths can be used to quantify depth-dependent subsidence. Other local factors such as previous land use, loading of structures without a piled foundation and variation in piling depth, i.e., which subsurface layer the structures are founded on, are proposed as important factors determining urban differential subsidence. PS-InSAR data, in combination with field observations and site-specific information (e.g., piling depths, land use, loading), provides an excellent opportunity to study urban differential subsidence and quantify depth-dependent subsidence rates. Knowing the magnitude of differential subsidence in urban areas helps to differentiate between local and delta wide subsidence patterns in InSAR-based velocity data and to further improve estimates of future subsidence.
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