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Analyzing vertical crustal deformation induced by hydrological loadings in the US using integrated Hadoop/GIS framework

Ramanayaka Mudiyanselage, Asanga

Abstract Details

2018, Master of Science (MS), Bowling Green State University, Geology.
Vertical crustal deformation for the contiguous US was assessed using continuous GPS stations for a total of 54 months. The study analyzed the correlation of vertical crustal deformation and hydrological loadings. Precipitation data were used as a measure of surface hydrological loadings. The relationship of GPS and precipitation data was studied by deriving Pearson correlation coefficients (r) for four different levels of watersheds (HUCs). To process the data for the temporal analysis, this study presents a prototype Hadoop/GIS framework which supports integrating distinct types of data. GPS data and precipitation data were analyzed by Hadoop and Hive which runs on the configured multi-node cluster. The spatial analysis used GIS tools to produce correlation maps. GRACE data which measure the terrestrial water storage were used to validate results. The generated correlation coefficients suggest that in the Northwestern US, the GPS deformation is negatively correlated with precipitation data. For instance, many watersheds in Washington and Oregon states produced high negative correlations (r) (between -0.55 and -0.75) which indicates the driving factor for vertical crustal deformation in the North-Western US is hydrological loadings which may have resulted from elastic loading processes. At the same time, GPS-GRACE correlation coefficients show a reasonable agreement with GPS-precipitation correlations for the North-Western US (r = - 0.67, r = - 0.69). However, the observed correlation coefficients for some of the watersheds in the Central Valley of California, Pennsylvania, and Maryland states had moderate positive values (r = 0.52, r = 0.42) which may have resulted from other factors such as climatic conditions, geological and geophysical effects.
Peter Gorsevski, Ph.D. (Advisor)
Yuning Fu, Ph.D. (Committee Member)
Jeffrey Snyder, Ph.D. (Committee Member)
66 p.

Recommended Citations

Citations

  • Ramanayaka Mudiyanselage, A. (2018). Analyzing vertical crustal deformation induced by hydrological loadings in the US using integrated Hadoop/GIS framework [Master's thesis, Bowling Green State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1525431761678148

    APA Style (7th edition)

  • Ramanayaka Mudiyanselage, Asanga. Analyzing vertical crustal deformation induced by hydrological loadings in the US using integrated Hadoop/GIS framework. 2018. Bowling Green State University, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1525431761678148.

    MLA Style (8th edition)

  • Ramanayaka Mudiyanselage, Asanga. "Analyzing vertical crustal deformation induced by hydrological loadings in the US using integrated Hadoop/GIS framework." Master's thesis, Bowling Green State University, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1525431761678148

    Chicago Manual of Style (17th edition)