The moment magnitude () 5.4 Pohang earthquake, the most damaging event in South Korea since instrumental seismic observation began in 1905, occurred beneath the Pohang geothermal power plant in 2017. Geological and geophysical data suggest that the Pohang earthquake was induced by fluid from an enhanced geothermal system (EGS) site, which was injected directly into a near-critically stressed subsurface fault zone. The magnitude of the mainshock makes it the largest known induced earthquake at an EGS site.
We apply the single-station microtremor horizontal-to-vertical spectral ratio (HVSR) method to image the geometry of Pohang Basin, South Korea, which experienced the greatest earthquake damage in Korea during a series of anthropogenic earthquakes between November 2017 and February 2018. We collected and analysed the ambient seismic noise at 124 temporary stations. The resonance frequencies, which vary significantly across the area (0.35–19.86 Hz), were inverted to constrain the depth of the major impedance contrast, which is interpreted to be the sediment–bedrock interface beneath each station. The sedimentary layer thickness is generally thin in the north and thickens to the southern and central parts of the basin, where the depth to bedrock is up to 340 m. We compare the HVSR results with six borehole observations in the area, whose depth to bedrock ranges from 189 to 359 m. The sediment thicknesses obtained via the direct borehole measurements and HVSR method are comparable with each other. The resultant three-dimensional shape of the sedimentary basin provides crucial information for the microzonation of the Pohang area for seismic risk mitigation. It also provides a realistic initial velocity model for three-dimensional tomographic inversions to elucidate the detailed subsurface structure of the region.
BackgroundThe purpose of this study is to examine the spatial and population (e.g., socio-economic) characteristics of low birthweight using two different cluster estimation techniques. We compared the results of Kulldorff's Spatial Scan Statistic with the results of Rushton's Spatial filtering technique across increasing sizes of spatial filters (circle). We were able to demonstrate that varying approaches exist to explore spatial variation in patterns of low birth weight.ResultsSpatial filtering results did not show any particular area that was not statistically significant based on SaTScan. The high rates, which remain as the filter size increases to 0.4, 0.5 to 0.6 miles, respectively, indicate that these differences are less likely due to chance. The maternal characteristics of births within clusters differed considerably between the two methods. Progressively larger Spatial filters removed local spatial variability, which eventually produced an approximate uniform pattern of low birth weight.ConclusionSaTScan and Spatial filtering cluster estimation methods produced noticeably different results from the same individual level birth data. SaTScan clusters are likely to differ from Spatial filtering clusters in terms of population characteristics and geographic area within clusters. Using the two methods in conjunction could provide more detail about the population and spatial features contained with each type of cluster.
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