The karst contagion model: Synopsis and environmental implications

The contagion model of karst terrane evolution focuses on the environmental implications for a large karst depression population on the Pennyroyal Plain (southern Kentucky) and the adjacent Western Highland Rim (Tennessee) immediately south of the Mammoth Cave Plateau. In karst terranes where the contagion model applies, there is a well-defined infrastructure comprised of hydrologic, structural geologic and geomorphic interacting elements that result in clustered depressions underlain by a radial conduit system. Clusters tend to be randomly distributed and typically contain a parent depression surrounded by numerous daughters.Groundwater flow is assumed to be turbulent and confined largely to conduits that are 3-dimensionally configured between clusters in a dendritic to trellis network. Parent depressions serve as conduit nodes for collecting groundwater migrating from beneath daughter depressions.Flow velocities in the 3-dimensional cluster-cell conduits exceed those in granular media by several orders of magnitude making pathogen and chemical contaminant migration rapid. Groundwater quality assessment in karst conduit hydrogeologic settings is difficult because monitoring wells are inappropriate. Monitoring wells may have a low probability of intercepting a major conduit and therefore the sampling regime must take into consideration the pulse discharge of pollutants in karst conduits. Representative water quality data must come from springs located near the local base level.     

A coupling of mixed and discontinuous Galerkin finite-element methods for poroelasticity

In this paper, we formulate a finite-element procedure for approximating the coupled fluid and mechanics in Biot’s consolidation model of poroelasticity. We approximate the flow variables by a mixed finite-element space and the displacement by a family of discontinuous Galerkin methods. Theoretical convergence error estimates are derived and, in particular, are shown to be independent of the constrained specific storage coefficient, c _o . This suggests that our proposed algorithm is a potentially effective way to combat locking, or the nonphysical pressure oscillations, which sometimes arise in numerical algorithms for poroelasticity.     

An agent-based model for risk-based flood incident management

Effective flood incident management (FIM) requires successful operation of complex, interacting human and technological systems. A dynamic agent-based model of FIM processes has been developed to provide new insights which can be used for policy analysis and other practical applications. The model integrates remotely sensed information on topography, buildings and road networks with empirical survey data to fit characteristics of specific communities. The multiagent simulation has been coupled with a hydrodynamic model to estimate the vulnerability of individuals to flooding under different storm surge conditions, defence breach scenarios, flood warning times and evacuation strategies. A case study in the coastal town of Towyn in the United Kingdom has demonstrated the capacity of the model to analyse the risks of flooding to people, support flood emergency planning and appraise the benefits of flood incident management measures.     

A time-distribution study of doline collapse: Framework for prediction

A temporal analysis of doline collapse on the Western Highland Rim (Tennessee) indicated one approach to estimating the probability of collapse in areas where the geologic and hydrologic criteria associated with collapse have been identified. The distribution of collapse was examined for trend, autocorrelation, and goodness of fit. The distribution of doline collapse during one 12-month period conformed to a Poisson distribution with a mean occurrence rate of λ=0.346 collapses per week and with the interoccurrence times being exponentially distributed (0.01 level). Although the proposed model is spatially and temporally restricted, it may provide an initial framework for estimating the probability of doline collapse in other karst terrains of similar geologic and hydrologic settings.     

Influence of geocell reinforcement on uplift response of belled piles

Piles are frequently used to transfer the heavy compressive loads to strong soil layers located in the depth of bed. In addition, such piles may be subjected to combination of repeated compressive and tensile loads due to earthquake, wind, etc. This paper describes a series of laboratory model tests, at unit gravity, performed on belled pile, embedded in unreinforced and geocell-reinforced beds. The tests were performed to evaluate the beneficial effect of geocell in decreasing the downward and upward displacements and performance improvement of the uplift response of belled pile under repeated compressive and tensile loads. Pile displacements due to fifty load repetitions were recorded. The influence of the height of geocell above the bell of pile, an additional geocell layer at the base of belled pile, and the number of load cycles on pile displacements were investigated. The test results show that the geocell reinforcement reduces the magnitude of the final upward displacement. It also acts as a displacement retardant, and changes the behaviour of belled pile from unstable response condition due to excessive upward pile displacement in unreinforced bed to approximately steady response condition. Therefore, the geocell reinforcement permits higher tensile loads or increased cycling. The efficiency of reinforcement in reducing the maximum upward displacement of the pile (i.e. pull-out resistance) was increased by increasing the height of geocell above the bell of the pile. Furthermore, the comparison showed that a specific improvement in upward and downward displacement and the stability against uplift can be achieved using an additional geocell layer at the base. The geocell reinforcement may reduce the required length of pile shaft, consequently reducing required excavation, backfill, and pile’s material. Simple dimensional analysis showed the need for an increased stiffness of the geosynthetic components in order to match prototype-scale performance similitude.     

Ebb-tidal fronts in Charleston Harbor,South Carolina: Physical and biological characteristics

Surface accumulations of foam and flotsam as well as sharp salinity, density, turbidity gradients and regions of acoustic scatter were characteristic of ebb-tidal fronts in Charleston Harbor, South Carolina. Surface convergence velocities at these fronts averaged 0.06 m s^?1 into the front at an angle of 30° to 60° with respect to the frontal axis, indicating along-front transport during the ebb. These fronts are tidally-induced, forming on the late flood and ebb along the interfaces of water masses. Horizontal and vertical measurements of density revealed that the upper harbor fronts form along the margin of a freshwater lens produced by riverine input. The hypothesis that these frontal zones have higher densities of phytoplankton and zooplankton than adjacent water masses was tested using chlorophylla measurements and net collections. The fronts did not demonstrate any significant accumulations of phytoplankton or zooplankton during the ebb tide. The results of this study suggest that the physical characteristics of ebb-tidal estuarine fronts in Charleston Harbor are periodic in nature and may indirectly affect plankton transport in this coastal plain estuary.     

Assessing spatial and attribute errors in large national datasets for population distribution models: a case study of Philadelphia county schools

Geospatial technologies and digital data have developed and disseminated rapidly in conjunction with increasing computing efficiency and Internet availability. The ability to store and transmit large datasets has encouraged the development of national infrastructure datasets in geospatial formats. National datasets are used by numerous agencies for analysis and modeling purposes because these datasets are standardized and considered to be of acceptable accuracy for national scale applications. At Oak Ridge National Laboratory a population model has been developed that incorporates national schools data as one of the model inputs. This paper evaluates spatial and attribute inaccuracies present within two national school datasets, Tele Atlas North America and National Center of Education Statistics (NCES). Schools are an important component of the population model, because they are spatially dense clusters of vulnerable populations. It is therefore essential to validate the quality of school input data. Schools were also chosen since a validated schools dataset was produced in geospatial format for Philadelphia County; thereby enabling a comparison between a local dataset and the national datasets. Analyses found the national datasets are not standardized and incomplete, containing 76 to 90 percent of existing schools. The temporal accuracy of updating annual enrollment values resulted in 89 percent inaccuracy for 2003. Spatial rectification was required for 87 percent of NCES points, of which 58 percent of the errors were attributed to the geocoding process. Lastly, it was found that by combining the two national datasets, the resultant dataset provided a more useful and accurate solution.     

Modeling doline populations with logistic growth functions

Initiation and evolution of a large karst depression population consisting of parent and daughter dolines were spatially and temporally modeled using logistic growth functions. Logistic growth models are well suited for analyzing doline population initiation and evolution because they reflect the density‐dependent growth mechanisms present in the evolution of karst depressions. Seven assumptions based upon previous studies were refined into mathematical statements and tested using more than 2000 dolines from a subpopulation of both parent and daughter karst depressions on the Western Highland Rim and Pennyroyal Plain of Tennessee and Kentucky. Logistic growth models quantify the initiation and evolution of doline populations and interface well with recent models describing the evolution of three‐dimensional conduit systems. Logistic growth models should apply to modeling other doline populations in karst terranes with hydraulically efficient, three‐dimensional conduit systems. Copyright © 2006 John Wiley & Sons, Ltd.     

Discontinuous Galerkin methods for modeling Hurricane storm surge

Storm surge due to hurricanes and tropical storms can result in significant loss of life, property damage, and long-term damage to coastal ecosystems and landscapes. Computer modeling of storm surge can be used for two primary purposes: forecasting of surge as storms approach land for emergency planning and evacuation of coastal populations, and hindcasting of storms for determining risk, development of mitigation strategies, coastal restoration and sustainability.Storm surge is modeled using the shallow water equations, coupled with wind forcing and in some events, models of wave energy. In this paper, we will describe a depth-averaged (2D) model of circulation in spherical coordinates. Tides, riverine forcing, atmospheric pressure, bottom friction, the Coriolis effect and wind stress are all important for characterizing the inundation due to surge. The problem is inherently multi-scale, both in space and time. To model these problems accurately requires significant investments in acquiring high-fidelity input (bathymetry, bottom friction characteristics, land cover data, river flow rates, levees, raised roads and railways, etc.), accurate discretization of the computational domain using unstructured finite element meshes, and numerical methods capable of capturing highly advective flows, wetting and drying, and multi-scale features of the solution.The discontinuous Galerkin (DG) method appears to allow for many of the features necessary to accurately capture storm surge physics. The DG method was developed for modeling shocks and advection-dominated flows on unstructured finite element meshes. It easily allows for adaptivity in both mesh (h) and polynomial order (p) for capturing multi-scale spatial events. Mass conservative wetting and drying algorithms can be formulated within the DG method.In this paper, we will describe the application of the DG method to hurricane storm surge. We discuss the general formulation, and new features which have been added to the model to better capture surge in complex coastal environments. These features include modifications to the method to handle spherical coordinates and maintain still flows, improvements in the stability post-processing (i.e. slope-limiting), and the modeling of internal barriers for capturing overtopping of levees and other structures. We will focus on applications of the model to recent events in the Gulf of Mexico, including Hurricane Ike.