Perfluorinated alkyl acids in water, sediment and wildlife from Sydney Harbour and surroundings

Perfluorinated alkyl compounds (PFCs) including perfluorooctane sulphonate (PFOS) and perfluorooctanoate (PFOA) were measured in environmental samples collected from around Homebush Bay, an urban/industrial area in the upper reaches of Sydney Harbour and Parramatta River estuary. Water, surface sediment, Sea Mullet (Mugil cephalus), Sydney Rock Oyster (Saccostrea commercialis) and eggs of two bird species; White Ibis (Threskiornis molucca), and Silver Gull (Larus novaehollandiae) were analysed. In most samples PFOS was the dominant PFC. Geometric mean PFOS concentrations were 33 ng/g ww (wet weight) in gull eggs, 34 ng/g ww in ibis eggs, and 1.8 ng/g ww and 66 ng/g ww in Sea Mullet muscle and liver, respectively. In sediment the PFOS geometric mean was 1.5 ng/g, in water average PFOS and PFOA concentrations ranged from 7.5 to 21 ng/L and 4.2 to 6.4 ng/L, respectively. In oysters perfluorododecanoic acid was most abundant, with a geometric mean of 2.5 ng/g ww.     

Impact of hypoxia on the structure and function of benthic epifauna in Tolo Harbour, Hong Kong

In Tolo Harbour, Hong Kong, where hypoxia occurs periodically, a large amount of benthic epifauna was found to be absent in the summer but become abundant again in the winter. This observation may indicate that some species are sensitive in detecting low dissolved oxygen (DO) levels and are able to escape from the harbour to more oxygenated, open waters when conditions deteriorate and return when DO levels are improved. Analysis of biological traits of these animals showed that 58% of the categories showed significant differences between the community structure in summer and winter. The significant biological traits of the few species, which remained in the harbour under the summer's hypoxic conditions suggested adaptation rather than opportunism to the low DO levels. Our data also showed that trawling can increase DO at the bottom and may benefit the less sensitive species that remained in the habitat during the summer.     

Subsurface hydrology of tile-drained headwater catchments: Compatibility of concepts and hydrochemistry

Concepts and terms used in previous multidisciplinary studies of tile-drained aquitard-dominated catchments (TDADC) are inconsistent and confusing. We provide a well-defined, comprehensive conceptual model of the subsurface hydrology of TDADC by selecting seven mutually compatible and consistent concepts. These concepts are: (1) groundwater as the main source of baseflow in headwater streams, (2) dominance of ‘pre-event’ water in stormflow, (3) importance of both macropores and matrix, (4) changes in flowpaths with rate of stream discharge, (5) dominance of shallow, lateral subsurface flow, (6) interactive nature of subsurface water, (7) transpiration of groundwater. This conceptual model was successfully ‘field-tested’ by examining data collected in a TDADC in a rural area of southern Ontario, Canada. The data consist mainly of chemical and isotopes tracers in water samples (headwater streams, groundwater, precipitation, tile water, soil-surface water), supplemented by water levels and meteorological data.     

Small volume andesite magmas and melt–mush interactions at Ruapehu, New Zealand: evidence from melt inclusions

Historical eruptions from Mt. Ruapehu (New Zealand) have been small (<0.001 km³ of juvenile magma) and have often occurred without significant warning. Developing better modelling tools requires an improved understanding of the magma storage and transport system beneath the volcano. Towards that end, we have analysed the volatile content and major element chemistry of groundmass glass and phenocryst-hosted melt inclusions in erupted samples from 1945 to 1996. We find that during this time period, magma has been stored at depths of ~2–9 km, consistent with inferences from geophysical data. Our data also show that Ruapehu magmas are relatively H₂O-poor (<2 wt%) and CO₂-rich (≤1,000 ppm) compared to typical arc andesites. Surprisingly, we find that melt inclusions are often more evolved than their transporting melt (as inferred from groundmass glass compositions). Furthermore, even eruptions that are separated by less than 2 years exhibit distinct major element chemistry, which suggests that each eruption involved magma with a unique ascent history. From these data, we infer that individual melt batches rise through, and interact with, crystal mush zones formed by antecedent magmas. From this perspective, we envision the magmatic system at Ruapehu as frequently recharged by small magma inputs that, in turn, cool and crystallise to varying degrees. Melts that are able to erupt through this network of crystal mush entrain (to a greater or lesser extent) exotic crystals. In the extreme case (such as the 1996 eruption), the resulting scoria contain melt inclusion-bearing crystals that are exotic to the transporting magma. Finally, we suggest that complex interactions between recharge and antecedent magmas are probably common, but that the small volumes and short time scales of recharge at Ruapehu provide a unique window into these processes.     

Effects of lidar post‐spacing and DEM resolution to mean slope estimation

This paper examines the effect of scale (exhibited by spatial sampling) in modeling mean slope from lidar data using two representations of scale: lidar posting density (i.e. post‐spacing) and DEM resolution (i.e. cell size). The study areas selected include six small (i.e. approximately 3 km²) urban drainage basins in Richland County, SC, USA, which share similar hydrologic characteristics. This research spatially sampled an airborne lidar dataset collected in 2000 at a 2 m nominal posting density to simulate lidar posting density at various post‐spacings, from 2 m through 10 m. DEMs were created from the lidar observations at a corresponding cell size using spatial interpolation. Finally, using these DEMs, a sensitivity analysis between modeled terrain slope and lidar post‐spacing was conducted. Results of the sensitivity analyses showed that the deviation between mean slope and modeled mean slope decreases with finer posting density and DEM resolution. The relationship of mean slope with varying cell sizes and post‐spacing suggests a linear and a logarithmic function, respectively, for all study areas. More importantly, cell size has a greater effect on mean slope than lidar posting density. Implications of these results for lumped hydrologic modeling are then postulated.     

Towards automation of palynology 3: pollen pattern recognition using Gabor transforms and digital moments

The classification of pollen grains using texture information in combination with shape features is presented in this paper. The surface texture of pollen is characterised by using Gabor transforms, the geometric shape is described by using moment invariants, and the pollen grains are classified by an artificial neural network. In an experiment with five types of pollen grains, more than 97% of samples are correctly classified. Copyright © 2004 John Wiley & Sons, Ltd.     

The hazard exposure of the Maltese Islands

International comparisons of disaster risk frequently classify Malta as being one of the least hazard exposed countries. Such rankings may be criticised because: (1) they fail to take into account historic increases in population and its seasonal variation; (2) they are based on inadequately researched and incomplete historical catalogues of damaging events; and (3), for small island states like Malta, they do not take into account the implications of restricted land area, which can be disproportionately impacted by even small hazardous events. In this paper, we draw upon a variety of data to discuss disaster risk in the Maltese Islands. In particular, the notion that Malta is one of the ‘safest places on earth’ is not only misleading, but also potentially dangerous because it engenders a false sense of security amongst the population. We argue that Malta is exposed to a variety of extreme events, which include: the distal effects of major earthquakes originating in southern Italy and Greece, plus their associated tsunamis; major ash producing eruptions of Mount Etna (Sicily) and their putative impacts on air transport; storm waves; coastal/inland landslides; karstic collapse; flooding and drought. In criticising international rankings of the islands’ exposure, we highlight the issues involved in formulating hazard assessments, in particular incomplete catalogues of extreme natural events. With Malta witnessing swelling resident, seasonal (i.e. tourist) plus foreign-born populations and increases in the urban area, further research into hazards is required in order to develop evidence-based policies of disaster risk reduction (DRR).     

An automated algorithm for mapping building impervious areas from airborne LiDAR point-cloud data for flood hydrology

Buildings, as impervious surfaces, are an important component of total impervious surface areas that drive urban stormwater response to intense rainfall events. Most stormwater models that use percent impervious area (PIA) are spatially lumped models and do not require precise locations of building roofs, as in other applications of building maps, but do require accurate estimates of total impervious areas within the geographic units of observation (e.g. city blocks or sub-watershed units). Two-dimensional mapping of buildings from aerial imagery requires laborious efforts from image analysts or elaborate image analysis techniques using high spatial resolution imagery. Moreover, large uncertainties exist where tall, dense vegetation obscures the structures. Analyzing LiDAR point-cloud data, however, can distinguish buildings from vegetation canopy and facilitate the mapping of buildings. This paper presents a new building extraction approach that is based on and optimized for estimating building impervious areas (BIA) for hydrologic purposes and can be used with standard GIS software to identify building roofs under tall, thick canopy. Accuracy assessment methods are presented that can optimize model performance for modeling BIA within the geographic units of observation for hydrologic applications. The Building Extraction from LiDAR Last Returns (BELLR) model, a 2.5D rule-based GIS model, uses a non-spatial, local vertical difference filter (VDF) on LiDAR point-cloud data to automatically identify and map building footprints. The model includes an absolute difference in elevation (AdE) parameter in the VDF that compares the difference between mean and modal elevations of last-returns in each cell.

The BELLR model is calibrated for an extensive inner-city, highly urbanized small watershed in Columbia, South Carolina, USA that is covered by tall, thick vegetation canopy that obscures many buildings. The calibration of BELLR used a set of building locations compiled by photo-analysts, and validation used independent building reference data. The model is applied to two residential neighborhoods, one of which is a residential area within the primary watershed and the other is a younger suburban neighborhood with a less-well developed tree canopy used as a validation site. Performance results indicate that the BELLR model is highly sensitive to concavity in the lasboundary tool of LAStools® and those settings are highly site specific. The model is also sensitive to cell size and the AdE threshold values. However, properly calibrated the BIA for the two residential sites could be estimated within 1% error for optimized experiments.

To examine results in a hydrologic application, the BELLR estimated BIAs were tested using two different types of hydrologic models to compare BELLR results with results using the National Land Cover Database (NLCD) 2011 Percent Developed Imperviousness data. The BELLR BIA values provide more accurate results than the use of the 2011 NLCD PIA data in both models. The VDF developed in this study to map buildings could be applied to LiDAR point-cloud filtering algorithms for feature extraction in machine learning or mapping other planar surfaces in more broad-based land-cover classifications.