Coupling a 3D patch model and a rockfall module to assess rockfall protection in mountain forests

Many forests in the Alps are acknowledged for protecting objects, such as (rail) roads, against rockfall. However, there is a lack of knowledge on efficient silvicultural strategies and interventions to maintain these forests at optimal protection level. Therefore, assessment tools are required that quantify the rockfall protection effect of forest stands over time, and thereby provide the ability to evaluate the necessity and effect of management interventions. This paper introduces such a tool that consists of a 3D rockfall module embedded in the patch based forest simulator PICUS. The latter is extended for this study with a new regeneration module. In a series of experiments the new combined simulation tool is evaluated with regard to parameter sensitivity, model intercomparison experiments with recently proposed algorithms from the literature, and the ability to respond realistically to different management regimes in rockfall protection forests. Results confirm the potential of the new tool for realistic simulation of rockfall activity in heterogeneous mountain forests, but point at the urgent need to improve the knowledge base on the interaction of understory and rockfall activity. Further work will focus on model validation against empirical rockfall data, and include reduced tree vitality due to damage from boulder collisions as well as the explicit consideration of downed dead wood.     

Risk assessment and prioritisation of contaminated sites on the catchment scale

Contaminated sites pose a significant threat to groundwater resources worldwide. Due to limited available resources a risk-based prioritisation of the remediation efforts is essential. Existing risk assessment tools are unsuitable for this purpose, because they consider each contaminated site separately and on a local scale, which makes it difficult to compare the impact from different sites. Hence a modelling tool for risk assessment of contaminated sites on the catchment scale has been developed. The CatchRisk screening tool evaluates the risk associated with each site in terms of its ability to contaminate abstracted groundwater in the catchment. The tool considers both the local scale and the catchment scale. At the local scale, a flexible, site specific leaching model that can be adjusted to the actual data availability is used to estimate the mass flux over time from identified sites. At the catchment scale, a transport model that utilises the source flux and a groundwater model covering the catchment is used to estimate the transient impact on the supply well. The CatchRisk model was tested on a groundwater catchment for a waterworks north of Copenhagen, Denmark. Even though data scarcity limited the application of the model, the sites that most likely caused the observed contamination at the waterworks were identified. The method was found to be valuable as a basis for prioritising point sources according to their impact on groundwater quality. The tool can also be used as a framework for testing hypotheses on the origin of contamination in the catchment and for identification of unknown contaminant sources.     

Seasonal Variation of Toxic Benzene Emissions in Petroleum Refinery

Petroleum refineries are largest chemical industries that are responsible for the emission of several pollutants into the atmosphere. Benzene is among the most important air pollutants that are emitted by petroleum refineries, since they are involved in almost every refinery process. Volatile organic compounds (VOCs) are a major group of air pollutants, which play a critical role in atmospheric chemistry. These contribute to toxic oxidants, which are harmful to ecosystem, human health and atmosphere. The variability of pollutants is an important factor in determining human exposure to these chemicals. The ambient air concentrations of benzene were measured in several sites around the Digboi petroleum refinery, near the city of Gowahati in northeast India, during winter and summer 2004. The seasonal and spatial variations of the ambient air concentrations of this benzene were investigated and analyzed. An estimation of the contribution of the refinery to the measured atmospheric levels of benzene was also performed. The ambient air mixing ratios of benzene in a large area outside the refinery was generally low, in ppbv range, much lower than the ambient air quality standards. This article presents the temporal and spatial variation of air pollution in and around petroleum refinery and showed that no health risk due to benzene is present in the areas adjacent to the refinery.     

Estimated Variability of National Atmospheric Deposition Program/Mercury Deposition Network Measurements Using Collocated Samplers

The National Atmospheric Deposition Program/Mercury Deposition Network (MDN) provides long-term, quality-assured records of mercury in wet deposition in the USA and Canada. Interpretation of spatial and temporal trends in the MDN data requires quantification of the variability of the MDN measurements. Variability is quantified for MDN data from collocated samplers at MDN sites in two states, one in Illinois and one in Washington. Median absolute differences in the collocated sampler data for total mercury concentration are approximately 11% of the median mercury concentration for all valid 1999–2004 MDN data. Median absolute differences are between 3.0% and 14% of the median MDN value for collector catch (sample volume) and between 6.0% and 15% of the median MDN value for mercury wet deposition. The overall measurement errors are sufficiently low to resolve between NADP/MDN measurements by ±2 ng·l⁻¹ and ±2 μg·m⁻²·year⁻¹, which are the contour intervals used to display the data on NADP isopleths maps for concentration and deposition, respectively.     

Determination of Impact of Urbanization on Agricultural Land and Wetland Land Use in Balçovas’ Delta by Remote Sensing and GIS Technique

Because of their intense vegetation and the fact that they include areas of coastline, deltas situated in the vicinity of big cities are areas of greet attraction for people who wish to get away from in a crowded city. However, deltas, with their fertile soil and unique flora and fauna, need to be protected. In order for the use of such areas to be planned in a sustainable way by local authorities, there is a need for detailed data about these regions. In this study, the changes in land use of the Balçova Delta, which is to the immediate west of Turkey’s third largest city Izmir, from 1957 up to the present day, were investigated. In the study, using aerial photographs taken in 1957, 1976 and 1995 and an IKONOS satellite image from the year 2005, the natural and cultural characteristics of the region and changes in the coastline were determined spatially. Through this study, which aimed to reveal the characteristics of the areas of land already lost as well as the types of land use in the Balçova delta and to determine geographically the remaining areas in need of protection, local authorities were provided with the required data support. Balçova consists of flat and fertile wetland with mainly citrus-fruit orchards and flower-producing green houses. The marsh and lagoon system situated in the coastal areas of the delta provides a habitat for wild life, in particular birds. In the Balçova Delta, which provides feeding and resting for migratory birds, freshwater sources are of vital importance for fauna and flora. The settlement area, which in 1957 was 182 ha, increased 11-fold up to the year 2005 when it reached 2,141 ha. On the other hand, great losses were determined in farming land, olive groves, forest and in the marsh and lagoon system. This unsystematic and rapid urbanization occurring in the study region is not only causing the loss of important agricultural land and wetland, but also lasting water and soil pollution.     

Coastal Flood Risk Analysis Using Landsat-7 ETM+ Imagery and SRTM DEM: A Case Study of Izmir, Turkey

The Intergovernmental Panel on Climate Change (IPCC) reports an acceleration of the global mean sea-level rise (MSLR) in the twentieth century in response to global climate change. If this acceleration remains constant, then some coastal areas are most likely to be inundated by the year 2100. The ability to identify the differential vulnerability of coastlines to future inundation hazards as result of global climate change is necessary for timely actions to be taken. Yildiz et al. (Journal of Mapping, 17, 1-75, 2003) reported that the local MSLR in the city of Izmir rose at a rate of 6.8 +/- 0.9 mm year(-1) between 1984 and 2002. In this study, the spatial distribution of the coastal inundation hazards of Izmir region was determined using not only land-use and land-cover (LULC) types derived from the maximum likelihood classification of Landsat-7 Enhanced Thematic Mapper Plus (ETM+) multi-spectral image set but also the classification of the digital elevation model (DEM) acquired by the shuttle radar topography mission (SRTM). Coastal areas with elevations of 2 and 5 m above mean sea-level vulnerable to inundation were found to cover 2.1 and 3.7% of the study region (6,107 km(2)), respectively. Our findings revealed that Menemen plain along Gediz river, and the settlements of Karsiyaka, Alacati, Aliaga, Candarli and Selcuk are at high risk in order of decreasing vulnerability to permanent and episodic inundation by 2100 under the high MSLR scenarios of 20 to 50 mm year(-1).     

Mapping Turbidity in the Charles River, Boston Using a High-resolution Satellite

The usability of high-resolution satellite imagery for estimating spatial water quality patterns in urban water bodies is evaluated using turbidity in the lower Charles River, Boston as a case study. Water turbidity was surveyed using a boat-mounted optical sensor (YSI) at 5 m spatial resolution, resulting in about 4,000 data points. The ground data were collected coincidently with a satellite imagery acquisition (IKONOS), which consists of multispectral (R, G, B) reflectance at 1 m resolution. The original correlation between the raw ground and satellite data was poor (R2 = 0.05). Ground data were processed by removing points affected by contamination (e.g., sensor encounters a particle floc), which were identified visually. Also, the ground data were corrected for the memory effect introduced by the sensor's protective casing using an analytical model. Satellite data were processed to remove pixels affected by permanent non-water features (e.g., shoreline). In addition, water pixels within a certain buffer distance from permanent non-water features were removed due to contamination by the adjacency effect. To determine the appropriate buffer distance, a procedure that explicitly considers the distance of pixels to the permanent non-water features was applied. Two automatic methods for removing the effect of temporary non-water features (e.g., boats) were investigated, including (1) creating a water-only mask based on an unsupervised classification and (2) removing (filling) all local maxima in reflectance. After the various processing steps, the correlation between the ground and satellite data was significantly better (R2 = 0.70). The correlation was applied to the satellite image to develop a map of turbidity in the lower Charles River, which reveals large-scale patterns in water clarity. However, the adjacency effect prevented the application of this method to near-shore areas, where high-resolution patterns were expected (e.g., outfall plumes).     

Serial Correlation and Inter-annual Variability in Relation to the Statistical Power of Monitoring Schemes to Detect Trends in Fish Populations

We studied the effects of inter-annual variability and serial correlation on the statistical power of monitoring schemes to detect trends in biomass of bream (Abramis brama) in Lake Veluwemeer (The Netherlands). In order to distinguish between 'true' system variability and sampling variability we simulated the development of the bream population, using estimates for population structure and growth, and compared the resulting inter-annual variabilities and serial correlations with those from field data. In all cases the inter-annual variability in the field data was larger than in simulated data (e.g. for total biomass of all assessed bream sigma = 0.45 in field data, and sigma = 0.03-0.14 in simulated data) indicating that sampling variability decreased statistical power for detecting trends. Moreover, sampling variability obscured the inter-annual dependency (and thus the serial correlation) of biomass, which was expected because in this long-lived population biomass changes are buffered by the many year classes present. We did find the expected serial correlation in our simulation results and concluded that good survey data of long-lived fish populations should show low sampling variability and considerable inter-annual serial correlation. Since serial correlation decreases the power for detecting trends, this means that even when sampling variability would be greatly reduced, the number of sampling years to detect a change of 15%.year(-1) in bream populations (corresponding to a halving or doubling in a six-year period) would in most cases be more than six. This would imply that the six-year reporting periods that are required by the Water Framework Directive of the European Union are too short for the existing fish monitoring schemes.     

Distribution of Polycyclic Aromatic Hydrocarbons (PAHs) and phenolic endocrine disrupting chemicals in South and Southeast Asian mussels

A comprehensive monitoring survey for polycyclic aromatic hydrocarbons (PAHs) and phenolic endocrine disrupting chemicals (EDCs) utilizing mussels as sentinel organisms was conducted in South and Southeast Asia as a part of the Asian Mussel Watch project. Green mussel (Perna viridis) samples collected from a total of 48 locations in India, Indonesia, Singapore, Malaysia, Thailand, Cambodia, Vietnam, and the Philippines during 1994–1999 were analyzed for PAHs, EDCs including nonylphenol (NP), octylphenol (OP) and bisphenol A (BPA), and linear alkylbenzenes (LABs) as molecular markers for sewage. Concentrations of NP ranged from 18 to 643 ng/g-dry tissue. The highest levels of NP in Malaysia, Singapore, the Philippines, and Indonesia were comparable to those observed in Tokyo Bay. Elevated concentrations of EDCs were not observed in Vietnam and Cambodia, probably due to the lower extent of industrialization in these regions. No consistent relationship between concentrations of phenolic EDCs and LABs were found, suggesting that sewage is not a major source of EDCs. Concentrations of PAHs ranged from 11 to 1,133 ng/g-dry, which were categorized as “low to moderate” levels of pollution. The ratio of methylphenanthrenes to phenanthrene (MP/P ratio) was >1.0 in 20 out of 25 locations, indicating extensive input of petrogenic PAHs. This study provides a bench-mark for data on the distribution of anthropogenic contaminants in this region, which is essential in evaluating temporal and spatial variation and effect of future regulatory measures.