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Surface Deformation Analysis of the Houston Area Using Time Series Interferometry and Emerging Hot Spot Analysis

Authors :
Shuhab D. Khan
Otto C. A. Gadea
Alyssa Tello Alvarado
Osman A. Tirmizi
Source :
Remote Sensing, Vol 14, Iss 15, p 3831 (2022)
Publication Year :
2022
Publisher :
MDPI AG, 2022.

Abstract

Cities in the northern Gulf of Mexico, such as Houston, have experienced one of the fastest rates of subsidence, with groundwater/hydrocarbon withdrawal being considered the primary cause. This work reports substantial ground subsidence in a few parts of Greater Houston and adjoining areas not reported before. Observation of surface deformation using interferometric synthetic aperture radar (InSAR) data obtained from Sentinel-1A shows total subsidence of up to 9 cm in some areas from 2016 to 2020. Most of the area within the Houston city limits shows no substantial subsidence, but growing suburbs around the city, such as Katy in the west, Spring and The Woodlands in the north and northwest, and Fresno in the south, show subsidence. In this study, we performed emerging hot spot analysis on InSAR displacement products to identify areas undergoing significant subsidence. To investigate the contributions of groundwater to subsidence, we apply optimized hot spot analysis to groundwater level data collected over the past 31 years from over 71,000 water wells and look at the correlation with fault surface deformation patterns. To evaluate the contribution of oil/gas pumping, we applied optimized hot spot analysis to known locations of oil and gas wells. The high rate of water pumping in the suburbs is the main driver of subsidence, but oil/gas withdrawal plays an important role in areas such as Mont Belvieu. Displacement time series shows that the Clodine, Hockley, and Woodgate faults are active, whereas the Long Point Fault shows no motion, although it was once very active.

Details

Language :
English
ISSN :
14153831 and 20724292
Volume :
14
Issue :
15
Database :
Directory of Open Access Journals
Journal :
Remote Sensing
Publication Type :
Academic Journal
Accession number :
edsdoj.971448b39df47fa9d7af1337a15dde1
Document Type :
article
Full Text :
https://doi.org/10.3390/rs14153831