Decision Support for Road System Analysis and Modification on the Tahoe National Forest

The United States Forest Service is required to analyze road systems on each of the national forests for potential environmental impacts. We have developed a novel and inexpensive way to do this using the Ecosystem Management Decision Support program (EMDS). We used EMDS to integrate a user-developed fuzzy logic knowledge base with a grid-based geographic information system to evaluate the degree of truth for assertions about a roads environmental impact. Using spatial data for natural and human processes in the Tahoc National Forest (TNF, California, USA), we evaluated the assertion the road has a high potential for impacting the environment. We found a high level of agreement between the products of this evaluation and ground observations of a TNF transportation engineer, as well as occurrences of road failures. We used the modeled potential environmental impact to negatively weight roads for a least-cost path network analysis to 1573 points of interest in the forest. The network analysis showed that out of 8233 km of road analyzed in the forest, 3483 km (42%) must be kept in a modified road network to ensure access to these points. We found that the modified network had improved patch characteristics, such as significantly fewer cherry stem roads intruding into patches, an improved area-weighted mean shape index, and larger mean patch sizes, as compared to the original network. This analysis system could be used by any public agency to analyze infrastructure for environmental or other risk and included in other mandated analyses such as risks to watersheds.     

Learning about knowledge management for improving environmental impact assessment in a government agency: the Western Australian experience

How does knowledge management (KM) by a government agency responsible for environmental impact assessment (EIA) potentially contribute to better environmental assessment and management practice? Staff members at government agencies in charge of the EIA process are knowledge workers who perform judgement-oriented tasks highly reliant on individual expertise, but also grounded on the agency’s knowledge accumulated over the years. Part of an agency’s knowledge can be codified and stored in an organizational memory, but is subject to decay or loss if not properly managed. The EIA agency operating in Western Australia was used as a case study. Its KM initiatives were reviewed, knowledge repositories were identified and staff surveyed to gauge the utilisation and effectiveness of such repositories in enabling them to perform EIA tasks.     

BAF处理系统的BP神经网络模型

本文以某污水处理厂曝气生物滤池（Biologlcal aerated filter,BAF）的实际运行数据为基础,采用人工神经网络（Artificial neural network,ANN）方法,建立起BAF处理系统的BP神经网络预测模型。模型运算结果表明,预测值和实测值能较好地吻合,起到了模拟预测的效果,同时能优化运行状态。该模型的建立为BAF处理系统的预测及运行管理供了一条简便实用的途径,具有良好的研究和工程实用价值。     

Initial decision analysis (IDA): a participatory approach for developing resource policies

Initial decision analysis (IDA) is a microcomputer based decision-making technique that is organized so that a rational, step-by-step, procedure can be followed to use existing knowledge to develop resource policies. The IDA process provides a systematic way for participants to define their own problem and to explore jointly alternative solutions. IDA is particularly suited to resolving complex problems involving many groups with conflicting interests. IDA is illustrated with data from the US Forest Service's Draft Environmental Impact Statement for the 1985 to 2030 Resource Planning Act Program for the United States. Four policy options are evaluated: maximization of timber production, of grazing, and of wilderness, and a dominant use policy that concentrates timber management on productive sites. Policies were evaluated using a new mathematical satisficing procedure. Mathematical satisficing of simulated policy consequences showed that, for selected performance standards, current RPA policies are superior to the four alternative policies examined.     

Fuzzy assessment of land suitability for scientific research reserves

Evaluating the characteristics of a set of sites as potential scientific research reserves is an example of land suitability assessment. Suitability in this case is based upon multiple criteria, many of which can be linguistically imprecise and often incompatible. Fuzzy logic is a useful method for characterizing imprecise suitability criteria and for combining criteria into an overall suitability rating. The Ecosystem Management Decision Support software combined a fuzzy logic knowledge base we developed to represent the assessment problem with a GIS database providing site-specific data for the assessment. Assessment of sites as a potential natural reserve for the new University of California campus at Merced demonstrates the benefits of fuzzy suitability assessment. The study was conducted in three stages of successively smaller assessment regions with increasingly fine spatial resolution and specificity of criteria. Several sites were identified that best satisfy the suitability criteria for a reserve to represent vernal pool habitat.