Measurement of the spatial distribution of fluvial bedload transport velocity in both sand and gravel

Maps are presented of the spatial distribution of two‐dimensional bedload transport velocity vectors. Bedload velocity data were collected using the bottom tracking feature of an acoustic Doppler current pro?ler (aDcp) in both a gravel‐bed reach and a sand‐bed reach of Fraser River, British Columbia. Block‐averaged bedload velocity vectors, and bedload velocity vectors interpolated onto a uniform grid, revealed coherent patterns in the bedload velocity distribution. Concurrent Helley‐Smith bedload sampling in the sand‐bed reach corroborated the trends observed in the bedload velocity map. Contemporaneous 2D vector maps of near‐bed water velocity (velocity in bins centered between 25 cm and 50 cm from the bottom) and depth‐averaged water velocity were also generated from the aDcp data. Using a vector correlation coef?cient, which is independent of the choice of coordinate system, the bedload velocity distribution was signi?cantly correlated to the near‐bed and depth‐averaged water velocity distributions. The bedload velocity distribution also compared favorably with variations in depth and estimates of the spatial distribution of shear stress. Published in 2004 by John Wiley & Sons, Ltd.     

Black Holes and Loose Connections in a Global Urban Network

This paper introduces the concept of black holes and loose connections in a global urban hierarchy. Black holes are defined as large cities, with a population of over 3 million, that are not classified as world cities. The paper draws upon a classification that uses advanced producer services as an indicator of world city status. Large, nonworld cities are identified, and provisional ideas about explaining their position are outlined. Connectivity and population data are used in a simple regression analysis to identify loose connections: cities whose connectivity is less than that predicted by their population.     

Developing a conceptual model of marine farming in New Zealand

Survey and Geographic Information System (GIS) data analysis describes the relative influence of biophysical and human variables on site choices made by marine farmers in New Zealand. Community conflicts have grown in importance in determining farm location and different government planning strategies leave distinct signature patterns. Recent legislation empowers local governments to choose among three strategies for future regional aquaculture development. This paper suggests each strategy could result in different spatial outcomes. Simulation modelling of the type described here can provide a better understanding of farmer responses to management approaches and the range of futures that could result from planning choices made today.     

Numerical simulation of the circulation within the Perth Submarine Canyon,Western Australia

Surface and sub-surface currents along the ocean boundary of Western Australia were simulated using Regional Ocean Modelling System (ROMS) to examine the circulation within the Perth Canyon. Two major current systems influenced the circulation within the canyon: (1) The Leeuwin current interacted weakly with the canyon as the majority of the canyon was below the depth of the Leeuwin current and (2) Leeuwin undercurrent interacted strongly with the canyon, forming eddies within the canyon at depths of 400–800 m. The results indicated that within the canyon, the current patterns changed continuously although there were some repeated patterns. Recurrent eddies produced regions where upwelling or downwelling dominated during the model runs. Deep upwelling was stronger within the canyon than elsewhere on the shelf, but vertical transport in the upper ocean was strong everywhere when wind forcing was applied. Upwelling alone appeared to be insufficient to transport nutrients to the euphotic zone because the canyon rims were deep. Increased upwelling, combined with entrapment within eddies and strong upwelling-favourable winds, which could assist mixing, may account for the high productivity attributed to the canyon. The Leeuwin current is otherwise a strong barrier to the upwelling of nutrients.     

Gravel‐bed rivers: from particles to patterns

The papers in this special issue reflect several of the major themes and topics from the 7^th International Workshop on Gravel‐Bed Rivers. The papers focus primarily on aspects of bed material transport in gravel‐bed rivers and larger scale morpho‐dynamics. Research in gravel‐bed rivers is increasingly integrating processes over a wide range of temporal and spatial scales by combining field observation, lab experimentation, numerical modeling and theory testing in a range of river types, aided by new technological developments in particle tracking, computational modeling and high resolution spatial data. This is leading to greater understanding of the processes leading to distinctive morpho‐dynamics of river types and a more reliable basis for river management. Copyright © 2012 John Wiley & Sons, Ltd.     

A Probabilistic Expert System Approach for Sea Mine Burial Prediction

Knowledge of the extent of burial of bottom sitting sea mines is critical to mine detection due to the significantly degraded capabilities of mine-hunting systems when the mines are buried. To provide an enhanced capability for predicting mine burial in support of U.S. Navy mine countermeasure (MCM) operations, an expert system approach to predicting sea mine burial has been developed. This expert system serves as a means to synthesize previous and current research on sea mine burial due to impact upon deployment and subsequently due to scour, the two dominant burial mechanisms in littoral waters. Prediction systems for impact and scour burial have been implemented as simple Bayesian networks whose probabilistic basis provides means of accounting for the inherent uncertainties associated with mine deployment methods, simplified physics-based burial models, and environmental variability. Examples of burial predictions and comparisons to results from field experiments are illustrated. In addition, a proposed risk metric is developed and applied to provide a geospatial mapping of mine burial probability.     

Neural network modeling applications in active slope stability problems

A back propagation artificial neural network approach is applied to three common challenges in engineering geology: (1) characterization of subsurface geometry/position of the slip (or failure surface) of active landslides, (2) assessment of slope displacements based on ground water elevation and climate, and (3) assessment of groundwater elevations based on climate data. Series of neural network models are trained, validated, and applied to a landslide study along Lake Michigan and cases from the literature. The subsurface characterization results are also compared to a limit equilibrium circular failure surface search with specific adopted boundary conditions. It is determined that the neural network models predict slip surfaces better than the limit equilibrium slip surface search using the most conservative criteria. Displacements and groundwater elevations are also predicted fairly well, in real time. The models’ ability to predict displacements and groundwater elevations provides a foundational framework for building future warning systems with additional inputs.     

The tourism disaster vulnerability framework: an application to tourism in small island destinations

Islands are known to be vulnerable to natural hazards, resulting in substantial risks for their tourism industries. To facilitate the systematic analysis of the underlying vulnerability drivers, a tourism disaster vulnerability framework was developed. The conceptual model then guided qualitative empirical research in three regions: the Caribbean, the South Pacific, and the Indian Ocean. The results from 73 interviews highlight common, as well as idiosyncratic, factors that shape the islands’ hazardscapes and vulnerabilities. Key vulnerabilities included social, economic, political, and environmental dimensions. Probably, the most critical vulnerability driver is the lack of private sector investment in disaster risk reduction. This is interrelated with deficient planning processes, on-going demand for coastal products, lack of political will, and poor environmental conditions. Notwithstanding many barriers, some businesses and organisations engage proactively in addressing disaster risk. The paper’s empirical evidence supports the validity of the framework, and suggestions for further research are made.