Structuring expert input for a knowledge-based approach to watershed condition assessment for the Northwest Forest Plan, USA

Assessments of watershed condition for aquatic and riparian species often have to rely on expert opinion because of the complexity of establishing statistical relationships among the many factors involved. Such expert-based assessments can be difficult to document and apply consistently over time and space. We describe and reflect on the process of developing a computer-based decision support application from expert judgments for assessing aquatic and riparian conditions over the 100,000?km² managed by the US federal government under the Northwest Forest Plan. The decision support system helped structure and document the assessment process and provided consistency and transparency to the evaluation methodology. However, many decisions and trade-offs were required in the expert engagement and model-building processes. Knowledge elicitation in an interactive group had a number of benefits over nominal group or Delphi processes, but efficient knowledge capture required considerable planning and expertise in the subject matter and modeling process. Communicating model results for validation was problematic and only effectively accomplished via in-person workshops. The choice to use different expert groups for each biophysical province provided more opportunities for participation and promoted greater ownership in the assessment, but it also led to increased variation among the resulting model structures. We propose three possible approaches for better managing the consistency of assessment models when multiple expert groups are involved.     

An expert system for assessing safety and security of heterogeneous public water sources

We have implemented a diagnostic system designed to advise on the likely causes of sanitary problems with public water sources. The approach to the problem makes extensive use of rule based expert systems and multi media information (maps, data, text, expert knowledge). The rules were based on actual water survey data, with a weighting scheme designed to highlight causes of health risks approximately in reverse order of importance (where such order may be presumed to exist). Out put is a vailable in one of several languages.     

A knowledge-based approach to regional acidification modelling

Data from over 2000 stations and knowledge from experts on atmospheric transport, soil geochemistry, lake chemistry, wetland processes and acidification modelling were assembled in an expert system. The data were grouped by aggregates of tertiary watersheds based on water chemistry knowledge. A set of expert rules was used to determine which of six existing models was most appropriate for a given set of data. Comparison of computed and observed alkalinity indicated median relative errors from 11.3–17.9%, with regression slopes ranging from 0.91–1.18 and regression coefficients between 0.82 and 0.99. The expert model performance was further confirmed with paleolimnological data and other independent sets of data. The sensitivity of the predicted alkalinity was illustrated by changing some of the rules. Given that the rules were acceptable by experts and produced reasonable agreement with observations, the knowledge-based system seemed a viable approach to the impact assessment of acidic deposition.     

An expert system for water quality modelling

The RAISON-micro (Regional Analysis by Intelligent System ON a micro-computer) expert system is being used to predict the effects of mine effluents on receiving waters in Ontario. The potential of this system to assist regulatory agencies and mining industries to define more acceptable effluent limits was shown in an initial study. This system has been further developed so that the expert system helps the model user choose the most appropriate model for a particular application from a hierarchy of models. The system currently contains seven models which range from steady state to time dependent models, for both conservative and nonconservative substances in rivers and lakes. The menu driven expert system prompts the model user for information such as the nature of the receiving water system, the type of effluent being considered, and the range of background data available for use as input to the models. The system can also be used to determine the nature of the environmental conditions at the site which are not available in the textual information database, such as the components of river flow. Applications of the water quality expert system are presented for representative mine sites in the Timmins area of Ontario.     

污染源自动监测数据异常诊断系统研究

简述了污染源自动监测数据异常诊断系统的概念以及异常数据的来源,以及系统的工作原理和基本功能结构。提出了系统模拟专家分析过程的信息处理工作方式,以期实现污染源自动监测数据质量自动诊断与故障识别。     

Land cover classification with an expert system approach using Landsat ETM imagery: a case study of Trabzon

The main objective of this study is to generate a knowledge base which is composed of user-defined variables and included raster imagery, vector coverage, spatial models, external programs, and simple scalars and to develop an expert classification using Landsat 7 (ETM+) imagery for land cover classification in a part of Trabzon city. Expert systems allow for the integration of remote-sensed data with other sources of geo-referenced information such as land use data, spatial texture, and digital elevation model to obtain greater classification accuracy. Logical decision rules are used with the various datasets to assign class values for each pixel. Expert system is very suitable for the work of image interpretation as a powerful means of information integration. Landsat ETM data acquired in the year 2000 were initially classified into seven classes for land cover using a maximum likelihood decision rule. An expert system was constructed to perform post-classification sorting of the initial land cover classification using additional spatial datasets such as land use data. The overall accuracy of expert classification was 95.80%. Individual class accuracy ranged from 75% to 100% for each class.     

A statistics-based system for treatment plant operation

This paper describes work toward development of a convenient computer system to improve everyday operation and control of the wastewater treatment process. The goal is to help the operator detect the problems in the process and to select appropriate control actions. The system comprises subsystems for a data base management, data analysis including several statistical methods, and an expert advisory system. The statistical methods investigated include construction of external reference distributions, computation of moving averages, graphical methods, discriminant functions for early detection of upsets, and several kinds of control charts. The latter two methods are still under development and are not built into the system. Reference distributions are used to help define the fuzzy terms such as high and low for the conditions of the variables involved in the expert system control rules. The system is written in dBase-III and Lotus-123 and has a user-friendly interface for the communication between the user and the system.     

Development of an Expert System for the Remediation of Petroleum-Contaminated Sites

Groundwater and soil contamination caused by light nonaqueous phase liquids (LNAPLs) spills and leakage in petroleum industry is currently one of the major environmental concerns in North America. Numerous site remediation technologies, generally classified as ex situ and in situ remediation techniques, have been developed and implemented to clean up the contaminated sites in the last two decades. One of the problems associated with ex situ remediation is the cost of operation. In recent years, in situ techniques have acquired popularity. However, the selection process of the desired techniques needs a large amount of knowledge. Insufficient expertise in the process may result in unnecessary inflation of expenses. In this study, petroleum waste management experts and Artificial Intelligence (AI) researchers worked together to develop an expert system (ES) for the management of petroleum contaminated sites. Various AI techniques were used to construct a useful tool for site remediation decision-making. This paper presents the knowledge engineering processes of knowledge acquisition, conceptual design, and system implementation in the project. The expert system was applied to a real-world case study and the results show that the expert system can generate desired remediation alternatives to assist decision-makers. The application case study constitutes partial validation of the prototype expert system.     

遥感技术在察布查尔县土壤侵蚀调查中的应用

依据陆地卫星TM遥感影像资料,在ERDAS软件下,通过室内判读与野外调查相结合的方法,解译出土地利用类型图、植被覆盖度图、坡度图。在建立知识库的基础上,利用土壤侵蚀专家分类系统,快速获得察布查尔县土壤侵蚀分类分级状况,为今后该区域的水土保持工作提供参考和依据。     

Monitoring the effects of forestry on streams: Variable selection and the development of an expert system

An expert system, PASSSFA, has been developed to help select the most appropriate variables for monitoring the effects of extensive land use activities, particularly forestry, on streams. PASSSFA was initially developed for headwater streams in the northwestern U.S. and Alaska, but the consistency of the underlying principles make it much more broadly applicable. The selection process is based on the designated beneficial uses of concern, the type of management activity, accessibility during high flows, frequency of sampling, and the costs for equipment, data collection, and sample analysis. A total of thirty potential monitoring variables are considered, and these were selected because of their sensitivity to land management activities and their effects on key designated uses. Problems in developing PASSSFA and the use of expert systems are discussed.     

A prototype expert system for fishway design

The design of structures for fish passage in rivers and streams provides an opportunity to apply expert system concepts to a design problem. Fishways contribute to the sustainable development of water resources projects by providing a path that allows fish migrations to be maintained. A prototype expert system (FDES) has been developed to recommend the most suitable fishway type for given design conditions. A recommendation is provided on the basis of fishway hydraulics, fish passage performance, and cost requirements. Fishway design demands expertise in various scientific disciplines such as hydrology, hydraulics, and fish biology. Expert system technology may be used to reduce design time requirements and to serve as a teaching aid to inexperienced engineers by organizing and accessing the cumulative knowledge of the most experienced designers. The rule-based expert system development tool, VP-Expert, supplies the backward chaining control structure for accessing the knowledge within the prototype.     

Expres: An expert system for assessing the fate of pesticides in the subsurface

The expert system described here is designed to aid regulatory personnel in their assessment of the potential for pesticides to contaminate the soil and groundwater environment. The expert system, known as EXPRES (EXpert system for Pesticide Regulatory Evaluation Simulations), consists of existing numerical models which are used to simulate the transport and transformation of pesticides in the unsaturated zone, coupled with a knowledge-based system that guides the user through the choice of all the necessary information for characterizing the physical, meteorological, hydrogeological, pedological and agricultural settings of typical agricultural regions across Canada, as required by the pesticide model. The expert system is designed to be used as a management tool to aid in policy decisions. Thus, its purpose is to provide an assessment of the potential hazards and to identify if further study is warranted.     

The Value of Better Information on Technology R&D Programs in Response to Climate Change

Expert elicitations are a promising method for determining how R&D investments are likely to have an impact on technological advance in climate change energy technologies. But, expert elicitations are time consuming and resource intensive. Thus, we investigate the value of the information gained in expert elicitations. More specifically, given baseline elicitations from one study, we estimate the expected value of better information (EVBI) from revisiting and improving these assessments. We find that the EVBI is very large in comparison with the cost of performing expert elicitations. We also find that EVBI is higher on technologies with larger budgets and with net values that are not too high or too low.     

Assessment of anthropogenic threats to Chilean Mediterranean freshwater ecosystems: Literature review and expert opinions

Anthropogenic threats and their impacts on aquatic ecosystems have traditionally been evaluated only through literature reviews. Within the last decade, however, expert opinions have become an increasingly popular alternative for gaining complementary information to literature reviews. This study employed a standardized method for collecting bibliographic data combined with synthesize expert opinions to establish a current knowledge baseline on threats to Mediterranean freshwater ecosystems in Chile.We revised 79 scientific articles that included a variety of taxonomic groups containing fish (n = 32); macroinvertebrates (n = 17); amphibians (n = 18); freshwater plants (n = 8); and two taxonomic groups simultaneously (n = 4). From this review, we identified 14 threats, with land-use change, species introductions, and industrial/domestic effluents as salient factors. These findings were in agreement with results from expert opinion surveys (n = 46 researchers). An analysis by taxonomic group indicated freshwater fishes as most threatened by hydropower plants. Aquatic plants were most threatened by mining. Amphibians were most threatened by changes in soil use whereas aquatic macroinvertebrates by industrial/domestic effluents. Remarkably, the magnitude of threats identified in the literature review was of similar order than those catalogued by experts. Moreover, the primary threats identified here align with those reported in other Mediterranean regions of the world. Our combined approach using literature review and expert opinion was useful in determining the consistency of the main threats to each taxonomic group. Our findings can be used as a baseline to further research and in prioritizing management strategies for threatened Mediterranean ecosystems worldwide.     

Uncertain spatial reasoning of environmental risks in GIS using genetic learning algorithms

Modeling the impact of air pollution is one of the most important approaches for managing damages to the ecosystem. This problem can be solved by sensing and modeling uncertain spatial behaviors, defining topological rules, and using inference and learning capabilities in a spatial reasoning system. Reasoning, which is the main component of such complex systems, requires that proper rules be defined through expert judgments in the knowledge-based part. Use of genetic fuzzy capabilities enables the algorithm to learn and be tuned to proper rules in a flexible manner and increases the preciseness and robustness of operations. The main objective of this paper was to design and evaluate a spatial genetic fuzzy system, with the goal of assessing environmental risks of air pollution due to oil well fires during the Persian Gulf War. Dynamic areas were extracted and monitored through images from NOAA, and the data were stored in an efficient spatial database. Initial spatial knowledge was determined by expert consideration of the application characteristics, and the inference engine was performed with genetic learning (GL) algorithms. Finally, GL (0.7 and 0.03), GL (0.7 and 0.08), GL (0.98 and 0.03), GL (0.98 and 0.08), and Cordon learning methods were evaluated with test and training data related to samples extracted from Landsat thematic mapper satellite images. Results of the implementation showed that GL (0.98, 0.03) was more precise than the other methods for learning and tuning rules in the concerned application.     

华北地区滨海湿地生态系统健康评价体系构建研究

以华北地区滨海湿地中的天津宁河七里海湿地为例,以PSR模型作为评价基础框架,运用可持续发展的理论、环境生态学、城市生态学、景观生态学等科学理论,结合社会经济资料收集、地面数据的采集与生态环境现状调查,应用层次分析法(AHP),在咨询专家意见的基础上,利用T L Saaty的标度法,构建了华北地区滨海湿地生态系统健康评价体系。体系由压力子系统、状态子系统、响应子系统构成,共筛选出三大类共计19项综合指标,其中压力指标6项、状态指标9项、响应指标4项。通过实际验证,该评价体系能客观地反映出湿地生态系统健康水平,可为环境管理部门的科学决策以及湿地的可持续发展提供技术支持,可供其他滨海地区湿地评价时参考。     

决策树模型在水环境监测网络中选取代表性样点的应用

地表水体中的硝酸盐污染已经成为全球关注的热点环境问题之一。现今,国内外均建立了相关的监测网络对地表水体的水质实施长期监测,但是却导致大量的监测数据累积,给后续的科学研究工作带来了不便,尤其是在庞大的监测网络中如何选取有代表性样点的研究点则成为急需解决的问题之一。以比利时弗拉芒地区地表水的长期监测物理化学指标为例,利用决策树模型评估地表水样点的硝酸盐污染来源专家分类的有效性,为点位优化提供理论依据。原有监测点位的污染源专家分类和模型输出的可匹配率为80%,优化后监测点位从原有47个点降低到30个点,提高了监测工作效率。     

Theorising EIA effectiveness: A contribution based on the Danish system

Considerable attention has been given to the effectiveness of environmental impact assessment (EIA) since the 1970s. Relatively few research studies, however, have approached EIA as an instrument of environmental governance, and have explored the mechanisms through which EIA influences the behaviour of actors involved in planning processes. Consequently, theory in this area is underspecified. In this paper we contribute to theory-building by analysing the effectiveness of a unique EIA system: the Danish system. In this system the competent authority, instead of the project proponent, undertakes EIA reporting. Additionally, the public, rather than experts, play a central role in quality control and the Danish EIA community is relatively small which influences community dynamics in particular ways. A nation-wide survey and expert interviews were undertaken in order to examine the views of actors involved in EIA on the effectiveness of this anomalous system. The empirical data are compared with similar studies on governance mechanisms in other countries, especially the United Kingdom and the Netherlands, as well as with earlier evaluations of EIA effectiveness in Denmark. The results indicate that the more extensive role attributed to the competent authority may lead to higher EIA effectiveness when this aligns with their interests; the influence of the public is amplified by a powerful complaints system; and, the size of the EIA community appears to have no substantial influence on EIA effectiveness. We discuss how the research findings might enhance our theoretical understanding of the operation and effectiveness of governance mechanisms in EIA.     

中俄跨界水体水质联合监测数据可比性研究

中俄跨界水体水质联合监测已经连续开展了11 a,积累了大量的监测数据。笔者针对双方实际监测数据,选用相关性分析和t检验等统计学方法,分析了中俄双方联合监测数据可比性。研究结果表明:p H、溶解氧、高锰酸盐指数和化学需氧量的相对偏差统计容许限基本满足中国标准建议值;氨氮和铁2个指标高于中国标准建议值;锰的数据差异最大。建议中俄双方针对溶解氧使用便携式溶解氧仪进行原位监测;重点对氨氮、铁和锰开展技术交流,设计相关实验,从样品采集、保存、运输、前处理和实验室分析等各环节查找双方差异。