干旱区生态环境知识资源中心(Arid): Machine-Learning Characterization of Tectonic, Hydrological and Anthropogenic Sources of Active Ground Deformation in California

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DOI	10.1029/2021JB022373
	Machine-Learning Characterization of Tectonic, Hydrological and Anthropogenic Sources of Active Ground Deformation in California
	Hu, Xie; Burgmann, Roland; Xu, Xiaohua; Fielding, Eric; Liu, Zhen
通讯作者	Hu, X (corresponding author), Univ Calif Berkeley, Berkeley Seismol Lab, Berkeley, CA 94720 USA. ; Hu, X (corresponding author), Univ Calif Berkeley, Dept Earth & Planetary Sci, Berkeley, CA 94720 USA. ; Hu, X (corresponding author), Univ Houston, Dept Civil & Environm Engn, Houston, TX 77204 USA. ; Hu, X (corresponding author), Peking Univ, Coll Urban & Environm Sci, Beijing, Peoples R China.
来源期刊	JOURNAL OF GEOPHYSICAL RESEARCH-SOLID EARTH
ISSN	2169-9313
EISSN	2169-9356
出版年	2021
卷号	126 期号:11
英文摘要	Tectonic, hydrological and industrial processes coexist in the dynamic natural environments. However, our knowledge of ground deformation associated with tectonic, hydrological and anthropogenic processes and their interactions remains limited. California represents a natural laboratory that hosts the San Andreas fault system, Central Valley and other aquifer systems, and extensive human extraction of natural resources. The attendant multi-scale ground deformation that has been mapped using Copernicus Sentinel-1 Synthetic Aperture Radar (SAR)-satellite constellation from four ascending and five descending tracks during 2015-2019. We consider the secular horizontal surface velocities and strain rates, constrained from GNSS measurements and tectonic models, as proxies for tectonic processes, and seasonal displacement amplitudes from interferometric SAR (InSAR) time series as proxies for hydrological processes. We synergize 23 types of multidisciplinary datasets, including ground deformation, sedimentary basins, precipitation, soil moisture, topography, and hydrocarbon production fields, using a machine learning algorithm-random forest, and we succeed in predicting 86%-95% of the representative data sets. High strain rates along the SAF system mainly occur in areas with a low-to-moderate vegetation fraction (similar to 0.3), suggesting a correlation of rough/high-relief coastal range morphology and topography with the active faulting, seasonal and orographic rainfall, and vegetation growth. Linear discontinuities in the long-term, seasonal amplitude and phase of the surface displacement fields coincide with some fault strands, the boundary zone between the sediment-fill Central Valley and bedrock-dominated Sierra Nevada, and the margins of the inelastically deforming aquifer in the San Joaquin Valley, suggesting groundwater flow interruptions, contrasting elastic properties, and heterogeneous hydrological units.
英文关键词	machine learning random forest InSAR ground deformation tectonics hydrology
类型	Article
语种	英语
收录类别	SCI-E
WOS记录号	WOS:000723102600003
WOS关键词	FRANCISCO BAY AREA ; SAN-ANDREAS FAULT ; AQUIFER-SYSTEM ; LAND SUBSIDENCE ; MOJAVE DESERT ; LOS-ANGELES ; SLIP RATES ; INSAR ; GPS ; EARTHQUAKES
WOS类目	Geochemistry & Geophysics
WOS研究方向	Geochemistry & Geophysics
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/373704
作者单位	[Hu, Xie; Burgmann, Roland] Univ Calif Berkeley, Berkeley Seismol Lab, Berkeley, CA 94720 USA; [Hu, Xie; Burgmann, Roland] Univ Calif Berkeley, Dept Earth & Planetary Sci, Berkeley, CA 94720 USA; [Hu, Xie] Univ Houston, Dept Civil & Environm Engn, Houston, TX 77204 USA; [Hu, Xie] Peking Univ, Coll Urban & Environm Sci, Beijing, Peoples R China; [Xu, Xiaohua] Univ Texas Austin, Inst Geophys, Austin, TX USA; [Fielding, Eric; Liu, Zhen] CALTECH, Jet Prop Lab, Pasadena, CA USA
推荐引用方式 GB/T 7714	Hu, Xie,Burgmann, Roland,Xu, Xiaohua,et al. Machine-Learning Characterization of Tectonic, Hydrological and Anthropogenic Sources of Active Ground Deformation in California[J],2021,126(11).
APA	Hu, Xie,Burgmann, Roland,Xu, Xiaohua,Fielding, Eric,&Liu, Zhen.(2021).Machine-Learning Characterization of Tectonic, Hydrological and Anthropogenic Sources of Active Ground Deformation in California.JOURNAL OF GEOPHYSICAL RESEARCH-SOLID EARTH,126(11).
MLA	Hu, Xie,et al."Machine-Learning Characterization of Tectonic, Hydrological and Anthropogenic Sources of Active Ground Deformation in California".JOURNAL OF GEOPHYSICAL RESEARCH-SOLID EARTH 126.11(2021).