Analysis of Urban Atmosphere Plume Concentration Fluctuations

Concentration variability in the fast-response tracer dataset for continuous, near-surface, point source releases in the urban core from the Joint Urban 2003 field study is analyzed. Concentration variability for conditionally and unconditionally sampled time series is characterized by probability densities, concentration fluctuation intensity, skewness, and kurtosis. Significant day-night differences in plume dispersion are observed. Relative to daytime, nighttime plumes were more likely to have reduced concentration fluctuation intensities, higher normalized surface concentrations, suppressed vertical mixing, and a greater prevalence of Gaussian-like distributions rather than log-normal or mixed mode distributions. This was in spite of the similar stability and turbulence conditions in the urban core for day and night. The potential roles of flow meander and thermal stability in explaining these differences are examined. Probability densities of concentration are found to be a strong function of fluctuation intensity. There are few differences in probability densities between day and night when classified by fluctuation intensity. There are no appreciable differences between conditional and unconditional probability densities and only small differences between conditional and unconditional sampling statistics relative to the larger differences usually observed in more homogeneous settings. Fluctuation intensity, skewness, and kurtosis are higher for the daytime experiments, and closer to the source, but show little difference between conditional and unconditional results over most of their range of values. The log-normal distribution provides a better overall fit to a broader range of the dataset than the exponential or clipped-normal distributions.     

Sheeting Joints: Characterisation,Shear Strength and Engineering

Sheeting joints are extensive fractures that typically develop parallel to natural slopes. Embryonic sheeting joints initially constitute channels for water flow and then become the focus for weathering and sediment infill accompanied by progressive deterioration and dilation. Slabs of rock fail along them periodically because of their adverse orientation and long persistence. They are however rough and wavy and these characteristics contribute highly to their shear strength and improve their stability. This paper reviews several landslide case histories and on the basis of these provides guidelines for characterising sheeting joints and determining their shear strength. Engineering options for stabilising sheeting joints in natural and cut slope configurations are then examined with reference to case examples.     

A GIS tool for infinite slope stability analysis (GIS-TISSA)

Landslides are one of the most common and a destructive natural hazard in mountainous terrain and thus evaluating their potential locations and the conditions under which they may occur is crucial for their hazard assessment.Shallow landslide occurrence in soil and regolith covered slopes are often modeled using the infinite slope model,which characterizes the slope stability in terms of a factor of safety(FS) value.Different approaches have been followed to also assess and propagate uncertainty through such models.Haneberg(2004) introduced the use of the First Order Second Moment(FOSM) method to propagate input uncertainty through the infinite slope model,further developing the model and implementing it in the PISA-m software package(Haneberg,2007).Here we present an ArcPy implementation of PISA-m algorithms,which can be run from ESRI ArcMap in an entirely consistent georeferenced framework,and which we call "GIS Tool for Infinite Slope Stability Analysis"(GIS-TISSA).Users can select between different input options,e.g.,following a similar input style as for PISA-m,i.e., using an ASCII.csv parameters input file,or providing each input parameter as a raster or constant value,through the program graphic user interface.Analysis outputs can include FS mean and standard deviation estimates,the probability of failure(FS <1), and a reliability index(RI) calculation for FS.Following the same seismic analysis approach as in PISA-m, the Newmark acceleration can also be done,for which raster files of the mean,standard deviation,probability of exceedance,and RI are also generated.Verification of the code is done by replicating the results obtained with the PISA-m code for different input options,within a 10-5 relative error.Monte Carlo modeling is also applied to validate GIS-TISSA outputs,showing a good overall correspondence.A case study was performed for Kannur district,Kerala,India,where an extensive landslide databa se for the year 2018 was available.81.19% of the actual landslides fell in zones identified by the model as unstable.GIS-TISSA provides a user-friendly interface,particularly for those users familiar with ESRI ArcMap,that is fully embedded in a GIS framework and which can then be used for further analysis without having to change software platforms and do data conversions.The ArcPy toolbox is provided as a.pyt file as an appendix as well as hosted at the weblink:https://pages.mtu.edu/~toommen/GeoHazard.html.     

Sediment transport analysis as a component of coastal management— a UK example

Detrimental effects of engineering works on the coast and a wish to conserve parts of the coastline have increased realization among coastal managers of the need to examine shoreline problems and proposals for protection in a wider spatial context than the site itself and over a longer time scale than the past few years. This paper outlines the approach taken in one region of the United Kingdom, the central south coast of England, to provide that wider perspective. Authorities responsible for coastal protection and sea defenses formed a coastal group, which, among other activities, commissioned research aimed at providing a greater understanding on which to base shoreline management decisions. A major project undertaken was a sediment transport study in which all existing information relating to coastal sediment processes in the region was collated and analyzed. All inputs, flows, and outputs of sediment were documented. Links between processes were examined for each part of the region. Finally, nine littoral cells of sediment circulation were identified and were suggested as forming a framework for shoreline management. The methods of compilation and analysis are outlined here and are exemplified for one area in the region. The approach is recommended as a cost-effective basis for strategic management of the coast in developed regions.