Identification of buried sinkholes using refraction tomography at Ft. Campbell Army Airfield,Kentucky

Karst aquifers are highly susceptible to contamination, with numerous points of entry for contaminants through recharge features such as sinkholes, swallow holes and solutionally enlarged fractures. These recharge features may be filled or obscured at the surface, requiring the use of geophysical or remote sensing techniques for their identification. This study uses seismic refraction data collected at the Ft. Campbell Army Airfield (CAAF), Kentucky, USA, to test the hypothesis that refraction tomography is a useful tool for imaging bedrock depressions beneath thick overburden (greater than 20 m of unconsolidated sediment). Southeast of the main taxiway of CAAF seismic velocity tomograms imaged a bedrock low, possibly a closed depression, at a depth of 25 m that had been earlier identified through delay-time analysis of the same refraction data. Tomography suggests the bedrock low is about 250-m wide by 10-m deep at its widest point. High rates of contaminant vapor extraction over the western extension of this feature suggest a high concentration of contaminants above, and within, this filled bedrock low, the base of which may contain solutionally enlarged fractures (i.e. karst conduits) that could funnel these contaminants to the upper or lower bedrock aquifers. This study thus demonstrates the viability of seismic refraction tomography as a tool for identification of filled sinkholes and bedrock depressions in karst areas.     

A novel approach to leveraging social media for rapid flood mapping: a case study of the 2015 South Carolina floods

Rapid flood mapping is critical for local authorities and emergency responders to identify areas in need of immediate attention. However, traditional data collection practices such as remote sensing and field surveying often fail to offer timely information during or right after a flooding event. Social media such as Twitter have emerged as a new data source for disaster management and flood mapping. Using the 2015 South Carolina floods as the study case, this paper introduces a novel approach to mapping the flood in near real time by leveraging Twitter data in geospatial processes. Specifically, in this study, we first analyzed the spatiotemporal patterns of flood-related tweets using quantitative methods to better understand how Twitter activity is related to flood phenomena. Then, a kernel-based flood mapping model was developed to map the flooding possibility for the study area based on the water height points derived from tweets and stream gauges. The identified patterns of Twitter activity were used to assign the weights of flood model parameters. The feasibility and accuracy of the model was evaluated by comparing the model output with official inundation maps. Results show that the proposed approach could provide a consistent and comparable estimation of the flood situation in near real time, which is essential for improving the situational awareness during a flooding event to support decision-making.     

Comparison of spectral and spatial methods for a Moho recovery from gravity and vertical gravity-gradient data

In global studies investigating the Earth’s lithospheric structure, the spectral expressions for the gravimetric forward and inverse modeling of the global gravitational and crustal structure models are preferably used, because of their numerical efficiency. In regional studies, the applied numerical schemes typically utilize the expressions in spatial form. Since the gravity-gradient observations have a more localized support than the gravity measurements, the gravity-gradient data (such as products from the Gravity field and steady-state Ocean Circulation Explorer - GOCE - gravity-gradiometry satellite mission) could preferably be used in regional studies, because of reducing significantly the spatial data-coverage required for a regional inversion or interpretation. In this study, we investigate this aspect in context of a regional Moho recovery. In particular, we compare the numerical performance of solving the Vening Meinesz-Moritz’s (VMM) inverse problem of isostasy in spectral and spatial domains from the gravity and (vertical) gravity-gradient data. We demonstrate that the VMM spectral solutions from the gravity and gravity-gradient data are (almost) the same, while the VMM spatial solutions differ from the corresponding spectral solutions, especially when using the gravity-gradient data. The validation of the VMM solutions, however, reveals that the VMM spatial solution from the gravity-gradient data has a slightly better agreement with seismic models. A more detailed numerical analysis shows that the VMM spatial solution formulated for the gravity gradient is very sensitive to horizontal spatial variations of the vertical gravity gradient, especially in vicinity of the computation point. Consequently, this solution provides better results in regions with a relatively well-known crustal structure, while suppressing errors caused by crustal model uncertainties from distant zones. Based on these findings we argue that the gravity-gradient data are more suitable than the gravity data for a regional Moho recovery.     

Reconstruction of paleocoastlines for the northwestern South China Sea since the Last Glacial Maximum

The range of relative sea level rise in the northwestern South China Sea since the Last Glacial Maximum was over 100 m. As a result, lowland regions including the Northeast Vietnam coast, Beibu Gulf, and South China coast experienced an evolution from land to sea. Based on the principle of reconstructing paleogeography and using recent digital elevation model, relative sea level curves, and sediment accumulation data, this paper presents a series of paleogeographic scenarios back to 20 cal. ka BP for the northwestern South China Sea. The scenarios demonstrate the entire process of coastline changes for the area of interest. During the late glacial period from 20 to 15 cal. ka BP, coastline slowly retreated, causing a land loss of only 1×10⁴ km², and thus the land-sea distribution remained nearly unchanged. Later in 15–10 cal. ka BP coastline rapidly retreated and area of land loss was up to 24×10⁴km², causing lowlands around Northeast Vietnam and South China soon to be underwater. Coastline retreat continued quite rapidly during the early Holocene. From 10 to 6 cal. ka BP land area had decreased by 9×10⁴km², and during that process the Qiongzhou Strait completely opened up. Since the mid Holocene, main controls on coastline change are from vertical crustal movements and sedimentation. Transgression was surpassed by regression, resulting in a land accretion of about 10×10⁴km². Supported by Key Laboratory of Marginal Sea Geology, Chinese Academy of Sciences (Grant No. MSGL0711), the Guangdong Natural Science Foundation (Grant No. 04001309) and Open Fund of the Key Laboratory of Marine Geology and Environment, Chinese Academy of Sciences (Grant No. MGE2007KG04)     

Assessment of shallow landslides from Hurricane Mitch in central America using a physically based model

Shallow landslides induced by heavy rainfall events represent one of the most disastrous hazards in mountainous regions because of their high frequency and rapid mobility. Recent advancements in the availability and accessibility of remote sensing data, including topography, land cover and precipitation products, allow landslide hazard assessment to be considered at larger spatial scales. A theoretical framework for a landslide forecasting system was prototyped in this study using several remotely sensed and surface parameters. The applied physical model SLope-Infiltration-Distributed Equilibrium (SLIDE) takes into account some simplified hypotheses on water infiltration and defines a direct relation between factor of safety and the rainfall depth on an infinite slope. This prototype model is applied to a case study in Honduras during Hurricane Mitch in 1998. Two study areas were selected where a high density of shallow landslides occurred, covering approximately 1,200 km². The results were quantitatively evaluated using landslide inventory data compiled by the United States Geological Survey (USGS) following Hurricane Mitch’s landfall. The agreement between the SLIDE modeling results and landslide observations demonstrates good predictive skill and suggests that this framework could serve as a potential tool for the future early landslide warning systems. Results show that within the two study areas, the values of rates of successful estimation of slope failure locations reached as high as 78 and 75%, while the error indices were 35 and 49%. Despite positive model performance, the SLIDE model is limited by several assumptions including using general parameter calibration rather than in situ tests and neglecting geologic information. Advantages and limitations of this physically based model are discussed with respect to future applications of landslide assessment and prediction over large scales.     

A coupling of mixed and continuous Galerkin finite element methods for poroelasticity I: the continuous in time case

In this paper, we formulate a finite element procedure for approximating the coupled fluid and mechanics in Biot’s consolidation model of poroelasticity. Here, we approximate the pressure by a mixed finite element method and the displacements by a Galerkin method. Theoretical convergence error estimates are derived in a continuous in-time setting for a strictly positive constrained specific storage coefficient. Of particular interest is the case when the lowest-order Raviart–Thomas approximating space or cell-centered finite differences are used in the mixed formulation, and continuous piecewise linear approximations are used for displacements. This approach appears to be the one most frequently applied to existing reservoir engineering simulators.     

粉喷桩单桩承载力与龄期的关系研究

以100余根粉喷桩单桩载荷试验和水泥土强度试验资料为基础，运用桩与土变形的弹塑性计算模型和复合地基理论，分析了同一场区不同龄期单桩承载力的关系，探讨了桩侧极限摩阻力与桩土发生塑性变形大小的关系，得了14d与28d龄期单桩承载力二者的经验公式，该公式经试验验证具有实用价值，为缩短粉喷桩的试桩周期提供了一种简单的计算方法。     

Stabilization of Expansive Clays Using Granulated Blast Furnace Slag (GBFS) and GBFS-Cement

Expansive clays undergo swelling when subjected to water. This can cause damage, especially to light weight structures, water conveyance canals, lined reservoirs, highways, and airport runways unless appropriate measures are taken. In this study, granulated blast furnace slag (GBFS) and GBFS-cement (GBFSC) were utilized to overcome or to limit the expansion of an artificially prepared expansive soil sample (sample A). GBFS and GBFSC were added to sample A in proportions of 5–25% by weight. The effects of these stabilizers on grain size distribution, Atterberg limits, swelling percentage and rate of swell of soil samples were determined. GBFS and GBFSC were shown to successfully decreasing the total amount of swell while increasing the rate of swell.     

Temporal variability in summertime bottom hypoxia in shallow areas of Mobile Bay,Alabama

This paper addresses temporal variability in bottom hypoxia in broad shallow areas of Mobile Bay, Alabama. Time-series data collected in the summer of 2004 from one station (mean depth of 4 m) exhibit bottom dissolved oxygen (DO) variations associated with various time scales of hours to days. Despite a large velocity shear, stratification was strong enough to suppress vertical mixing most of the time. Bottom DO was closely related to the vertical salinity gradient (ΔS). Hypoxia seldom occurred when ΔS (over 2.5 m) was <2 psu and occurred almost all the time when ΔS was >8 psu in the absence of extreme events like hurricanes. Oxygen balance between vertical mixing and total oxygen demand was considered for bottom water from which oxygen demand and diffusive oxygen flux were estimated. The estimated decay rates at 20°C ranging between 0.175–0.322 d⁻¹ and the corresponding oxygen consumption as large as 7.4 g O₂ m⁻² d⁻¹ fall at the upper limit of previously reported ranges. The diffusive oxygen flux and the corresponding vertical diffusivity estimated for well mixed conditions range between 8.6–9.5 g O₂ m⁻² d⁻¹ and 2.6–2.9 m² d⁻¹, respectively. Mobile Bay hypoxia is likely to be associated with a large oxygen demand, supported by both water column and sediment oxygen demands, so that oxygen supply from surface water during destratification events would be quickly exhausted to return to hypoxic conditions within a few hours to days after destratification events are terminated.     

Probabilistic seismic hazard assessment for South-Eastern France

The accurate evaluation and appropriate treatment of uncertainties is of primary importance in modern probabilistic seismic hazard assessment (PSHA). One of the objectives of the SIGMA project was to establish a framework to improve knowledge and data on two target regions characterized by low-to-moderate seismic activity. In this paper, for South-Eastern France, we present the final PSHA performed within the SIGMA project. A new earthquake catalogue for France covering instrumental and historical periods was used for the calculation of the magnitude-frequency distributions. The hazard model incorporates area sources, smoothed seismicity and a 3D faults model. A set of recently developed ground motion prediction equations (GMPEs) from global and regional data, evaluated as adequately representing the ground motion characteristics in the region, was used to calculate the hazard. The magnitude-frequency distributions, maximum magnitude, faults slip rate and style-of-faulting are considered as additional source of epistemic uncertainties. The hazard results for generic rock condition (Vs30 = 800 m/s) are displayed for 20 sites in terms of uniform hazard spectra at two return periods (475 years and 10,000 years). The contributions of the epistemic uncertainties in the ground motion characterizations and in the seismic source characterization to the total hazard uncertainties are analyzed. Finally, we compare the results with existing models developed at national scale in the framework of the first generation of models supporting the Eurocode 8 enforcement, (MEDD 2002 and AFPS06) and at the European scale (within the SHARE project), highlighting significant discrepancies at short return periods.