Land subsidence in coastal Texas: Locations, rates, triggers, and consequences

Land subsidence and sea level rise are well-known ongoing problems that are negatively impacting the entire Texas coast. While ground-based monitoring techniques using Global Positioning System (GPS) provide accurate subsidence rates, they are labor intensive, expensive, time consuming, and spatially limited (e.g., point measurements). In this study, Interferometric Synthetic Aperture Radar (InSAR) techniques were used to map locations and quantify rates of land subsidence in the Texas Costal Bend region during the period from October 2016 to July 2019. InSAR-derived land subsidence rates were validated against GPS-derived rates. Factors controlling the observed land subsidence rates and locations were also investigated. Consequences of increased land subsidence rates in Texas Costal Bend region were examined. Results indicate: (1) land subsidence rates in the Coastal Bend exhibit both spatial and temporal variabilities, (2) some areas experienced a localized subsidence as high as -21 mm/yr and other areas show a land uplift with rate of > 10 mm/yr, (3) InSAR-derived land subsidence rates were consistent with GPS derived deformation rates, (4) Seven regions (e.g., Victoria, George West, Refugio, Falfurrias, Karnes City, McAllen, and Nueces Bay/Corpus Christi) were observed to experience significant land subsidence rates along Texas Costal Bend region during the investigated period, (5) land subsidence in Coastal Texas is attributed mainly to oil and ground water extraction as well as vertical movements along growth faults, and (6) land subsidence increased both flood frequency and severity in Coastal Texas. Our results provide valuable information regarding not only land deformation rates in the Texas Coastal Bend region, but alsothe effectiveness of interferometric techniques in other coastal rural areas around the world that lack significant GPS coverage. Mapping land subsidence rates and locations in coastal Texas significantly improve the current understanding of factors controlling the variability in land deformation in coastal areas by providing a high-resolution spatial and temporal dataset that is currently not available on this detailed scale.