GEOSTATISTICAL ESTIMATION OF HORIZONTAL HYDRAULIC CONDUCTIVITY FOR THE KIRKWOOD‐COHANSEY AQUIFER1

ABSTRACT: The Kirkwood‐Cohansey aquifer has been identified as a critical source for meeting existing and expected water supply needs for southern New Jersey. Several contaminated sites exist in the region; their impact on the aquifer has to be evaluated using ground water flow and transport models. Ground water modeling depends on availability of measured hydrogeologic data (e.g., hydraulic conductivity, for parameterization of the modeling runs). However, field measurements of such critical data have inadequate spatial density, and their locations are often clustered. The goal of this study was to research, compile, and geocode existing data, then use geostatistics and advanced mapping methods to develop a map of horizontal hydraulic conductivity for the Kirkwood‐Cohansey aquifer. Spatial interpolation of horizontal hydraulic conductivity measurements was performed using the Bayesian Maximum Entropy (BME) Method implemented in the BMELib code library. This involved the integration of actual measurements with soft information on likely ranges of hydraulic conductivity at a given location to obtain estimate maps. The estimation error variance maps provide an insight into the uncertainty associated with the estimates, and indicate areas where more information on hydraulic conductivity is required.     

MODELING DRINKING WATER QUALITY VIOLATIONS WITH BAYESIAN NETWORKS1

ABSTRACT: Compliance violations at community water systems are rare but represent significant human health risks. These risks are mediated by the decision schema of human operators at water treatment facilities. However, causal uncertainty among physical and human factors involved in water quality problems complicates assessment of their probability and severity. This study uses a probabilistic Bayesian network modeling approach to explore the causes of compliance violations in a sample of water treatment systems in Pennsylvania. The model presented here is one of several created by treatment system operators during an expert elicitation process. The expert model alone predicts violations poorly, suggesting that experts make inaccurate quantitative estimates. However, Bayesian networks are capable of combining the subjective expertise of treatment system operators with the objective compliance histories of the facilities they manage, and the expert model accurately predicts violations when trained with historical compliance data. Analysis of the trained network reveals those components of the treatment process, including environmental and system characteristics as well as operator decisions, that play the greatest role in determining the likelihood of major violation types. Among operator decisions, coagulant dosing and filter backwash frequency are the most important determinants of violation likelihood.     

Environmental management systems and sustainable development

The idea of sustainable development was first brought to widespread attention as a global issue; however, it is increasingly being applied at more local levels down to that of individual companies. This raises the potential danger that sustainable development will come to be predominantly identified with the preservation of the organisation involved. A likely outcome is that management decision-making will tip the balance too far in favour of people-centred interests as against environmental interests. An initial step in preventing this is to make any bias in the balance of interests transparent to management. To do this, a model of sustainability is set up in terms that provide a context for the implementation of a quality based environmental management system such as that specified by the International Standard, ISO 14001. In response to inherent uncertainty, a precautionary approach is adopted. The implications of this model for the structuring of critical environmental management system elements are then discussed and a way to generate an indicator of bias proposed. The content of an audit, which would measure the extent to which an organisation has a management system competent to measure and monitor this bias, is also discussed and proposed as another useful indicator.     

DEVELOPMENT AND EVALUATION OF MULTIPLE‐OBJECTIVE DECISION‐MAKING METHODS FOR WATERSHED MANAGEMENT PLANNING1

ABSTRACT: Making decisions for environmental management is a complex task due to the multiplicity and diversity of technological choices. Furthermore, the exploitation of natural resources and the preservation of the natural environment imply objectives that are often in conflict within a sustainable development paradigm. Managers and other decision makers require techniques to assist them in understanding strategic decision making. This paper illustrates the use of a multiple‐objective decision‐making methodology and an integrative geographical information system‐based decision‐making tool developed to help watershed councils prioritize and evaluate restoration activities at the watershed level. Both were developed through a multidisciplinary approach. The decision‐making tool is being applied in two watersheds of Oregon's Willamette River Basin. The results suggest that multiple‐objective methods can provide a valuable tool in analyzing complex watershed management issues.     

What we know,what we don't know,and what we need to know about graduated driver licensing

On November 5-7, 2002, the Symposium on Graduated Driver Licensing in Chatham, MA, brought together 75 researchers and practitioners from the United States, Canada, Australia, and New Zealand to document the current science of graduated driver licensing (GDL) and to outline research needs. Participants reviewed 12 background papers and discussed the papers in depth. The symposium's background papers are published in this issue of the Journal of Safety Research.This paper summarizes and provides a quick reference to information from the symposium papers and participant discussions. It cites the 12 symposium papers, which in turn provide more information and cite original sources. Issues and recommendations not followed by a citation were raised in the symposium discussions.This paper is divided into seven sections. The first six sections summarize information from the symposium papers and discussions. The sections are: (1) The need for graduated driver licensing; (2) Effectiveness of GDL as implemented; (3) The learner's permit phase; (4) The provisional license phase; (5) The roles of teens, parents, and public agencies; and (6) Enacting and implementing GDL. In each of these six sections, research needs are classified as either high priority (important for designing and implementing effective GDL programs) or lower priority (useful but not critical for GDL at this time).The final section summarizes the discussion of research issues and priorities from the symposium's closing session. This section has three topics: general research, issues involving parents, and issues involving graduated licensing legislation and implementation. It presents participants' collective views on both broad priorities and specific issues.In providing a concise summary of presentations and discussions from the symposium, this paper necessarily omits some information and points of discussion. The views and judgments expressed are the authors' best attempt to capture the symposium's consensus, but they do not necessarily represent the views of the authors, their organizations, or any other individual symposium participant. In particular, they are not necessarily endorsed by the symposium's sponsors: General Motors, the National Highway Traffic Safety Administration, the National Safety Council, and Nationwide.     

Self-reported driving under the influence of alcohol and cannabis among Ontario students: Associations with graduated licensing,risk taking,and substance abuse

Objective: This article describes the patterns of self-reported driving under the influence of alcohol (DUIA) and driving under the influence of cannabis (DUIC) among licensed Ontario students in 2009 and examines their associations with graduated licensing, risk taking, and substance use problems for understanding DUIA and DUIC behaviors. Ontario's graduated licensing system requires new drivers to hold a G1 license for a minimum of 8 months and a G2 license for a minimum of 12 months before a full and unrestricted G license can be obtained. Among other restrictions, G1 drivers must maintain a 0 blood alcohol content (BAC), have an experienced driver in the passenger seat, not drive on any high-speed expressways, and not drive between the hours of midnight and 5 a.m. A G2 license is more similar to a G license, with fewer restrictions.

Method: This study analyzed data from the 2009 Ontario Student Drug Use and Health Survey (OSDUHS). The OSDUHS is a biennial population-based survey of students (grades 7 to 12) in Ontario, Canada.

Results: The results showed that 16.3% of licensed students in Ontario reported DUIC and 11.5% reported DUIA during the past year. After controlling for the effect of age, type of license emerged as a robust predictor for both DUIA and DUIC behavior, because students with a G2 and full license were significantly more likely to report DUIA and DUIC than drivers with a G1 license. Multivariate analyses suggested that risk-seeking behaviors were more important for understanding DUIA behavior than for DUIC behavior. Elevated problem indicators for alcohol and for cannabis were associated with DUIA and DUIC, respectively.

Conclusions: Though much attention has been paid to drinking and driving among adolescents, this research shows that more Ontario students now report driving after cannabis use than after drinking alcohol. The results identify important correlates of both behaviors that may be useful for prevention purposes.     

Information systems and needs assessment in natural disasters: An approach for better disaster relief management

The paper addresses the issue of information in disasters relief. It begins by establishing the need for planning and systematic organization in disaster action, in order to produce a long term effect on the vulnerability levels of communities. Information is introduced as a key element in any phase of disaster management. The different informational needs are described by phases; information types and possible sources are briefly described. The organizational network of information collection is presented and the immediate need for research in this field is emphasized.     

Emergency and institutional crisis in Peru during El Nino 1982-1983

From December 1982 through July 1983, Peru was plagued by disastrous consequences of El Nino/Southern Oscillation phenomenon. While the northern part of the country was devastated by torrential rains and floods, central Andean Peru endured landslides and flash floods, the southern Altiplano suffered a severe drought. Hazard preparedness was nonexistent, and official disaster relief uncoordinated and slow in coming. Administrative inefficiency magnified the stress upon the populations under disaster conditions. Provisions of disaster training from specialized international organizations is recommended as a preventive measure and as a policy to improve catastrophe-coping abilities in developing nations.     

Safety rules: procedural freedom or action constraint?

The paper presents a partial classification of safety rules as constraints imposed from outside on the freedom of choice of individuals or companies. The classification is linked to the Reason model of skill-, rule-, and knowledge-based behaviour. The imposition of constraints is related to a number of criteria concerning the context and use of the rules to arrive at proposals for when and where to apply what type of rule. To illustrate the principles discussed an example is given of the rule from the Dutch Working Environment legislation concerning the requirement to use “current state of the art in prevention” in companies. The paper proposes providing procedural rule support to companies on how to meet the rule, in the form of a data bank of practicable solutions to health and safety problems.