Use of environmental sensors and sensor networks to develop water and salinity budgets for seasonal wetland real-time water quality management

Management of river salt loads in a complex and highly regulated river basin such as the San Joaquin River Basin of California presents significant challenges for current Information Technology. Computer-based numerical models are used as a means of simulating hydrologic processes and water quality within the basin and can be useful tools for organizing Basin data in a structured and readily accessible manner. These models can also be used to extend information derived from environmental sensors within existing monitoring networks to areas outside these systems based on similarity factors – since it would be cost prohibitive to collect data for every channel or pollutant source within the Basin. A common feature of all hydrologic and water quality models is the ability to perform mass balances. This paper describes the use of a number of state-of-the-art sensor technologies that have been deployed to obtain water and salinity mass balances for a 60,000 ha tract of seasonally managed wetlands in the San Joaquin River Basin of California. These sensor technologies are being combined with more traditional environmental monitoring techniques to support real-time salinity management (RTSM) in the River Basin. Two of these new technology applications: YSI-Econet (which supports continuous flow and salinity monitoring of surface water deliveries and seasonal wetland drainage); and electromagnetic salinity mapping (a remote sensing technology for mapping soil salinity in the surface soils) – have not previously been reported in the literature. Continuous sensor deployments that experience more widespread use include: weather station sensor arrays – used to estimate wetland pond evaporation and moist soil plant evapotranspiration; high resolution multi-spectral imagery – used to discriminate between and estimate the area of wetland moist soil plant vegetation; and groundwater level sensors – used primarily to estimate seepage losses beneath a wetland pond during flood-up. Important issues associated with quality assurance of continuous data are discussed and the application of a state-of-the-art software product AQUARIUS, which streamlines the process of data error correction and dissemination, is described as an essential element of ensuring successful RTSM implementation in the San Joaquin River Basin.     

长江流域水文气象信息服务体系设计与实践

长江流域水文气象信息服务体系涵盖水文气象信息收集、预报产品制作、信息管理及成果发布全流程.通过阐述信息服务体系的设计思想、总体框架、系统功能和应用实践,说明水文气象信息服务在防洪减灾、水工程调度、河流水质保护、水资源管理与保护方面的应用情况.信息服务体系以长江流域水库群信息共享平台、水情App和预报调度系统为基础进行融...     

Ontology-based facility data model for energy management

Context: Definition of a comprehensive facility data model is a prerequisite for providing more advanced energy management systems capable of tackling the underlying heterogeneity of complex infrastructures, thus providing more flexible data interpretation and event management, advanced communication and control system capabilities. Objective: This paper proposes one of the possible implementations of a facility data model utilizing the concept of ontology as part of the contemporary Semantic Web paradigm. Method: The proposed facility ontology model was defined and developed to model all the static knowledge (such as technical vendor data, proprietary data types, and communication protocols) related to the significant energy consumers of the target infrastructure. Furthermore, this paper describes the overall methodology and how the common semantics offered by the ontology were utilized to improve the interoperability and energy management of complex infrastructures. Initially, a core facility ontology, which represents the generic facility model providing the general concepts behind the modelling, was defined. Results: In order to develop a full-blown model of the specific facility infrastructure, Malpensa and Fiumicino airports in Italy were taken as a test-bed platform in order to develop the airport ontology owing to the variety of the technical systems installed at the site. For the development of the airport ontology, the core facility ontology was first extended and then populated to reflect the actual state of the target airport facility. Conclusion: The developed ontology was tested in the environment of the two pilots, and the proposed solution proved to be a valuable link between separate ICT systems involving equipment from various vendors, both on syntax and semantic level, thus offering the facility managers the ability to retrieve high-level information regarding the performance of significant energy consumers.     

A Bayesian method for multi-pollution source water quality model and seasonal water quality management in river segments

Excessive pollutant discharge from multi-pollution resources can lead to a rise in downriver contaminant concentration in river segments. A multi-pollution source water quality model (MPSWQM) was integrated with Bayesian statistics to develop a robust method for supporting load (I) reduction and effective water quality management in the Harbin City Reach of the Songhua River system in northeastern China. The monthly water quality data observed during the period 2005–2010 was analyzed and compared, using ammonia as the study variable. The decay rate (k) was considered a key factor in the MPSWQM, and the distribution curve of k was estimated for the whole year. The distribution curves indicated small differences between the marginal distribution of k of each period and that water quality management strategies can be designed seasonally. From the curves, decision makers could pick up key posterior values of k in each month to attain the water quality goal at any specified time. Such flexibility is an effective way to improve the robustness of water quality management. For understanding the potential collinearity of k and I, a sensitivity test of k for I_2i (loadings in segment 2 of the study river) was done under certain water quality goals. It indicated that the posterior distributions of I_2i show seasonal variation and are sensitive to the marginal posteriors of k. Thus, the seasonal posteriors of k were selected according to the marginal distributions and used to estimate I_2i in next water quality management. All kinds of pollutant sources, including polluted branches, point and non-point source, can be identified for multiple scenarios. The analysis enables decision makers to assess the influence of each loading and how best to manage water quality targets in each period. Decision makers can also visualize potential load reductions under different water quality goals. The results show that the proposed method is robust for management of multi-pollutant loadings under different water quality goals to help ensure that the water quality of river segments meets targeted goals.     

松辽流域水资源监控平台运维的分层管理

为保障水资源监控管理信息平台能发挥投资效益,对松辽流域水资源监控管理信息平台开展持续的运行维护。按照信息系统管理框架分层分级管理,有效理清维护对象和重点环节,通过有序有效的运行维护,确保平台的业务能力支撑作用,加深信息部门和业务部门领域的相互认识,从运维端对水利业务信息化项目的运行维护进行规范,并推广到同类项目的运行维护中。     

Modeling the fate of down-the-drain chemicals in whole watersheds: New version of the GREAT-ER software

The geo-referenced regional exposure assessment tool for European rivers (GREAT-ER) designed for the prediction of spatially explicit exposure concentrations of typical down-the-drain chemicals in whole river basins was improved. New features for scenario creation and analyses were amended for use in river basin management or within the Water Framework Directive implementation process. Improvements of the new model version are exemplary illustrated by means of an extensive case study for the pharmaceutical diclofenac in the German watershed of Ruhr River, a tributary of River Rhine. Comparison with monitoring data corroborates the capability of the probabilistic model to realistically predict spatial surface water concentration ranges for non-persistent chemicals. Based on the evaluation of the actual contamination, two management scenarios are investigated in terms of their reduction potential. The analysis demonstrates how the model allows for a priori evaluation of mitigation strategies.     

A Metadata Service for Integrated Management of Knowledges Related to Coastal Areas

The research outlined in this paper is part of a wider research program named SYSCOLAG (Coastal and LAGoonal SYStems in Languedoc-Roussillon area, France) dedicated to sustainable coastal management. The main objective of this program is to build up a communication infrastructure to improve the exchange of information and knowledge between the various scientific disciplines involved in the research. In order to ensure the sharing of resources without affecting the autonomy and independance of the partners, we propose a three-level infrastructure (resources, federation and knowledge access) based on a metadata service (using ISO 19115 standard for geographic information metadata) completed by a common vocabulary (ontology).The Syscolag research program (COastal and LAGoonal SYStems) is funded by Languedoc Roussillon authority.Julien Barde is currently a Ph.D. student in Computer Science at the LIRMM (the Computer Science, Robotic and Microelectronic Laboratory of the University of Montpellier II, France) under the guidance of Thérèse Libourel and Pierre Maurel since 2002. He works for a research program of Integrated Coastal Management to improve knowledge sharing between the stakeholders of Languedoc Roussillon coastal area. He has received his engineer/M.Sc. degrees in Oceanology Sciences and Spatial Information Treatment from the National Superior Agronomic School of Rennes (ENSAR, Brittany, France) in 2000 and 2001. He has experience in Computer Science, Remote sensing, GIS and oceanology.Thérèse Libourel is a Senior Lecturer in Computer Science from the Conservatoire National des Arts et Métiers (CNAM), currently at the LIRMM (the Computer Science, Robotic and Microelectronic Laboratory of the University of Montpellier II, France) since 1994. She holds a Ph.D. and a habilitation thesis in Computer Science from the University of Montpellier II (France). Among others, her research interests are oriented towards object oriented design, reuse of software components, object oriented databases and evolution, and data models for spatial and temporal information systems.Pierre Maurel is a research engineer in Cemagref (France). He received his Diploma on Agronomy Engineering from ESAP high school (France) in 1986 and his M.Sc. on quantitative geography in 1990 from Avignon University (France). In the past, he performed research and teaching in satellite image processing and GIS for environmental and water applications. His current scientific interests include the development of methods for the design of multi-partners geographic information systems, the use of metadata within Spatial Data Infrastructures and the integration of Geographic Information technologies to support public participation in the field of Integrated River Basin Management (HarmoniCOP European project).     

Application of artificial neural networks for water quality prediction

The term “water quality” is used to describe the condition of water, including its chemical, physical, and biological characteristics. Modeling water quality parameters is a very important aspect in the analysis of any aquatic systems. Prediction of surface water quality is required for proper management of the river basin so that adequate measure can be taken to keep pollution within permissible limits. Accurate prediction of future phenomena is the life blood of optimal water resources management. The artificial neural network is a new technique with a flexible mathematical structure that is capable of identifying complex non-linear relationships between input and output data when compared to other classical modeling techniques. Johor River Basin located in Johor state, Malaysia, which is significantly degrading due to human activities and development along the river. Accordingly, it is very important to implement and adopt a water quality prediction model that can provide a powerful tool to implement better water resource management. Several modeling methods have been applied in this research including: linear regression models (LRM), multilayer perceptron neural networks and radial basis function neural networks (RBF-NN). The results showed that the use of neural networks and more specifically RBF-NN models can describe the behavior of water quality parameters more accurately than linear regression models. In addition, we observed that the RBF finds a solution faster than the MLP and is the most accurate and most reliable tool in terms of processing large amounts of non-linear, non-parametric data.

     

西南河流源区数据管理与共享平台研究

西南河流源区是我国水资源和水能资源的重要储备，国家自然科学基金委员会设立的“西南河流源区径流变化和适应性利用重大研究计划”改善该地区基础数据资料匮乏状况。为发挥该重大研究计划延续性作用，亟需研发西南河流源区数据管理与共享平台。从数据管理与共享角度出发，梳理出多源异构数据集成、数据质量保障、数据全流程管理、数据共享、专题数据展示等功能需求，提出“数据存储—应用支撑—业务逻辑— 应用视图”平台框架，实现西南河流源区多源异构数据的一致性存储、“数据上传—评审—下载—评价”全流程管理及专题数据二三维一体化可视化展示。以数据质量为主线，提出“规范元数据体系 + 数据评审”双重质量控制流程。结合繁杂的数据类型和日益增加的数据量对数据管理提出更高要求，探究未来数据平台改进方向与思路。该研究将为研发适用于西南河流源区数据管理与共享的平台奠定坚实基础。     

Towards improving usage and management of supplies in healthcare: An ontology-based solution for sharing knowledge

The goal of this work is to contribute to an improvement in the management and usage of medical items in hospitals by developing an ontology-driven solution that organizes and describes clearly related knowledge. Experts in the purchasing and management of hospital supplies (administrative and clinical) were invited to participate at different stages of the ontology-based system development. As a result of the first stage, the HealthCatalog ontology was developed. This ontology models generic items included in a health catalog and their management. Secondly, a further refinement of the ontology was conducted by specifically studying the case of gloves. Twenty-seven references of different glove types were modeled and included in the ontology during the stage two. A prototype was then developed as a proof of concept and for the evaluation of the ontology. Finally, a usability evaluation was planned to improve the ontology and obtain feedback from experts after testing the system. Experts involved in the evaluation stressed its potential use in a real clinical environment and the benefits it would bring in terms of cost and sharing knowledge among clinical personnel. Our proposed ontology-based system provides an understandable and organized solution to capture knowledge regarding item management and usage. It addresses the integration challenge of health catalogs while providing a framework for collaborative sharing and knowledge acquisition among clinicians.     

基于WebGIS的北江流域水资源信息查询系统研制

本文简单叙述了北江流域水资源概况和WebGIS技术方案,并就系统设计及特色功能作了简要介绍。综合运用计算机、水文水资源、地理信息系统、网络通信等技术,将水资源业务需求与WebGIS技术相结合,成功研制了适用于北江流域的水资源信息查询系统,实现了水资源信息的快速检索查询,为水资源的科学管理、合理配置等决策提供技术支撑。     

珠江水旱灾害防御“四预”平台建设与应用

数字孪生珠江先行先试建设以数字孪生技术为支撑，基于珠江流域管理需求，率先开展水旱灾害防御业务应用建设。结合珠江委当前信息化现状，对照“四预”相关技术要求，深入分析目前珠江流域水旱灾害防御业务应用仍然存在“预演”能力不足的问题。为解决此项难题，开展水利三维可视化仿真技术、水利模型管理及服务技术研究，研发了水利三维可视化仿真、模型管理及服务技术。搭建了水旱灾害防御相关数据底板，构建了模型平台和知识平台开发具有“四情”态势感知、分级分类智能预警、多维多尺度场景全链条预演的珠江水旱灾害防御“四预”平台，为珠江流域水旱灾害防御工作提供支撑。     

嫩江干流水量调度流程研究与典型应用建设

结合松辽流域水资源调度管理业务流程研究,以嫩江干流水量调度为典型应用,建立松辽流域水资源调配决策支持系统体系框架,重点实现嫩江干流水量调度子系统建设。通过对调度计划实时监控、方案编制及优化、方案总结评价及会商决策等5个方面的业务功能设计优化与实现,提高业务人员的工作效率和业务系统实用性。为嫩江干流水量调度和流域最严格水资源红线管理提供科学的参考依据和技术支撑,也为水资源管理信息化建设与业务的深度融合进行探索和提供参考。     

疏勒河流域水资源管理决策支持信息系统设计

世界银行贷款的疏勒河农业综合开发暨移民安置工程的实施,使流域内水土资源得到了极大规模的开发与利用,但同时也产生了湿地萎缩、植被退化、土地沙化和盐渍化等一系列较为严重的水环境问题。为实现流域整体生态、社会、经济效益的统一,保证区域经济与社会的可持续发展,建立科学、可靠、操作性强的流域水资源管理决策支持信息系统是实现上述目标的根本保障。在分析系统需求的基础上,结合疏勒河流域水资源特点对系统的结构、系统功能、系统实现等方面进行了 初步探讨,认为疏勒河流域水资源管理决策支持信息系统应是一个以硬件、系统软件、组织机构以及水资源数据为基础,“3S”技术及水资源管理专业模型为支撑的,集数据的采集、传输、存储、管理、分析、决策、输入、输出为一体的集成系统,以进行疏勒河流域水资源的评价、科学管理和决策。     

本体存储技术研究

Ontology是对一个特定领域中重要概念的共享的形式化的描述,由于具有明确性和共享性,它可以作为领域内不同主体之间进行交流的语义基础;更进一步的,Ontology可以帮助机器理解文档表达的语义信息.语义网络是Ontology的一个重要应用场景,Ontology用来描述网络资源的语义,从而使机器具有自动管理网络信息的能力.那么巨大的数据规模是语义网络环境下Ontology数据存储管理面临的一个突出问题,所以介绍了本体存储的方法、存储模式及几种典型的本体存储管理系统.讨论了当前本体存储模式的问题并展望了未来的发展方向.     

本体存储技术研究

Ontobgy是对一个特定领域中重要概念的共享的形式化的描述,由于具有明确性和共享性,它可以作为领域内不同主体之同进行交流的语义基础;更进一步的,Ontology可以帮助机器理解文档表达的语义信息。语义网络是Ontology的一个重要应用场景,Ontolcgy用来描述网络资源的语义,从而使机器具有自动管理网络信息的能力。那么巨大的数据规模是语义网络环境下Ontology数据存储管理面临的一个突出问题,所以介绍了本体存储的方法、存储模式及几种典型的本体存储管理系统。讨论了当前本体存储模式的问题并展望了未来的发展方向。     

Scenario analysis for the role of sanitation infrastructures in integrated urban wastewater management

Traditionally, the sanitation infrastructures of most of the Urban Wastewater Systems (UWSs) have been managed individually, without considering the many relationships among the sewer systems, Wastewater Treatment Plants (WWTPs) and receiving waters. The main objective of WWTP management was to comply with the emission limits, without considering the ecological state of the receiving waters. However, the European Union approved the Water Framework Directive (WFD) in 2000 that changes the conventional practice by introducing the integrated approach concept in the hydraulic infrastructure management. The same Directive also promotes the availability and use of decision support tools for water management, specifically where water resources are becoming increasingly scarce. This paper describes the work conducted in the Besòs catchment (Catalonia, NE of Spain) in order to deal with this European legislation. A study site was selected to develop an integrated model as a support tool for the UWS management. Specifically, two sewer systems, their WWTPs and a reach of the Congost River (a tributary of the Besòs River) have been modelled. The selected software to model flow and water quality were Infoworks CS, GPS-X and Infoworks RS for the sewer systems, WWTPs and stream reach, respectively. Besides these, a specific program was developed to be used as a data transfer interface between software. Once this model integration platform was built, and taking into account the expert knowledge of the managers, several management scenarios were defined including some critical events such as industrial spills, rainfall episodes, inhibition of nitrification, WWTP shutdowns, obstruction of a sewer system conduit and episodes of minimum river flow rates as well as potential control actions such as the implementation of storage tanks or the use of bypasses between sewer systems or WWTPs. All these scenarios were modelled and simulated and the results obtained were then analysed, focusing the attention on the river water quality, with the main objective being to gain relevant knowledge to deal with the tested scenarios.     

Domain ontology graph model and its application in Chinese text classification

This paper proposes an ontology learning method which is used to generate a graphical ontology structure called ontology graph. The ontology graph defines the ontology and knowledge conceptualization model, and the ontology learning process defines the method of semiautomatic learning and generates ontology graphs from Chinese texts of different domains, the so-called domain ontology graph (DOG). Meanwhile, we also define two other ontological operations—document ontology graph generation and ontology graph-based text classification, which can be carried out with the generated DOG. This research focuses on Chinese text data, and furthermore, we conduct two experiments: the DOG generation and ontology graph-based text classification, with Chinese texts as the experimental data. The first experiment generates ten DOGs as the ontology graph instances to represent ten different domains of knowledge. The generated DOGs are then further used for the second experiment to provide performance evaluation. The ontology graph-based approach is able to achieve high text classification accuracy (with 92.3 % in f-measure) over other text classification approaches (such as 86.8 % in f-measure for tf–idf approach). The better performance in the comparative experiments reveals that the proposed ontology graph knowledge model, the ontology learning and generation process, and the ontological operations are feasible and effective.     

Bridging the gap between product lifecycle management and sustainability in manufacturing through ontology building

Green manufacturing has been a major concern in recent years. As product lifecycle management strategies embrace sustainability within its spectrum of multi-disciplinary efforts, it has become crucial that manufacturing companies have the ability to exchange product and process related data with emphasis on sustainability not only amongst its internal information systems like CAD, CAPP and ERP, but also throughout their supply chain and other stakeholders. Industry demands solutions for interoperability between heterogeneous systems that can account for the necessary semantics in order to establish seamless, unambiguous information sharing of data from a product's cradle to its grave. One of the most promising approaches to overcome these issues is the use of ontologies that serve as interlingua, for translating between local data structures. The present research proposes an ontology that relates sustainability terms to product and process data entities through semantic ties.     

Ontology-based concept similarity in Formal Concept Analysis

Both domain ontologies and Formal Concept Analysis (FCA) aim at modeling concepts, although with different purposes. In the literature, a promising research area concerns the role of FCA in ontology engineering, in particular, in supporting the critical task of reusing independently developed domain ontologies. With this regard, the possibility of evaluating concept similarity is acquiring an increasing relevance, since it allows the identification of different concepts that are semantically close. In this paper, an ontology-based method for assessing similarity between FCA concepts is proposed. Such a method is intended to support the ontology engineer in difficult activities that are becoming fundamental in the development of the Semantic Web, such us ontology merging and ontology mapping and, in particular, it can be used in parallel to existing semi-automatic tools relying on FCA.