Building Knowledge Discovery and Information Fusion Tools for Collaborative Systems to Adaptively Manage Uncertain Hydrological Resources

迫切需要准确和有效地评估和管理水量。这一挑战之所以更大，是因为水管理必须在当前和未来水资源不确定的情况下进行。适应性水管理已成为灵活的水管理所采用的政策启发式方法，以应对不断变化的物质和社会需求。适应性管理办法的中心挑战是需要量化观测到的水量测量的不确定性。这项研究将创建新的知识发现和信息融合算法来计算两个水印指标，并将它们嵌入到一个整体的知识管理系统中。长期目标是为协作系统开发智能、可扩展的决策支持工具，明确纳入不确定性，以分析和整合水文数据和信息。该提议的具体目标是：1.知识发现和信息融合：设计可扩展的算法，以(A)计算数据质量(QOD)、信息质量(QoI)和知识质量(QoK)，(B)将地理空间事件中的邻近性纳入时空数据挖掘，以及(C)整合异质、不完整和不确定的地理空间数据和信息。水资源计量：制定关于水资源状况的综合水资源计量--所有水资源在给定的时空时间点的综合状况。适应性管理：确定管理者和决策者用于适应性水管理的具体水指标。软件产品：构建一套基于Web的知识发现和信息融合工具，以分析、集成和可视化水文数据、水质指标及其质量。智力价值：拟议的研究将有助于知识发现和信息融合方法，这些方法明确地模拟和传播一般的不确定性，特别是地理空间分析。将在有效和高效的知识发现、信息融合和可视化工具的支持下，设计一个多个不同数据集的数字储存库的综合框架，以：1)协助水文学家制定水循环分析的综合模型和指标；2)支持决策者作出适应性管理决策；更广泛的影响：这项研究将推动三个学科的最新水平：(A)计算机科学，通过开发新的知识发现技术；(B)水文学，通过使用信息融合方法制定两个综合水资源计量标准；(C)水管理和其他应用，通过确定成功的适应性管理的重要参数。

There is a critical need to accurately and efficiently assess and manage water quantity. This challenge is made greater because water management must be conducted under conditions of uncertainty about current and future water resources. Adaptive water management has become the policy heuristic adopted for flexible water management that responds to ever changing physical and social demands. The central challenge of the Adaptive Management approach is the need to quantify the uncertainty in observed water measurements. This research will create new knowledge discovery and information fusion algorithms to compute two watermetrics and embed them in an overall knowledge management system. The long-term goal is to develop intelligent, scalable decision support tools for collaborative systems that explicitly incorporate uncertainty to analyze and integrate hydrological data and information. The specific objectives of the proposal are:1. Knowledge Discovery and Information Fusion: Design scalable algorithms to (a) compute Quality of Data (QoD) Quality of Information (QoI) and Quality of Knowledge (QoK), (b) incorporate proximity in geospatial events into spatio-temporal data mining and (c) integrate heterogeneous, incomplete, and uncertain geospatial data and information.2. Water Metrics: Develop an integrated water metric on Water Status - the integrated state of all water resources at a given point in space and time.3. Adaptive Management: Identify specific Water Metrics that managers and decision makers use for adaptive water management.4. Software Products: Build a suite of web-based knowledge discovery and information fusion tools to analyze, integrate and visualize hydrological data, water metrics and their quality. Intellectual Merit: The proposed research will contribute knowledge discovery and information fusion methods that explicitly model and propagate uncertainty in general and geospatial analysis in particular. An integrated framework of a digital repository of multiple and diverse data sets will be designed, powered by effective and efficient knowledge discovery, information fusion and visualization tools, that: i) assists hydrologists develop comprehensive models and metrics for the analysis of the water cycle; ii) supports decision makers in adaptive management decisions; and iii) helps policy makers study the social and legal impact on water users.Broader Impact: The research will advance the state of the art in three disciplines: (a) computer science, by developing novel knowledge discovery techniques, (b) hydrology, by developing two integrated water metrics using information fusion approach, and (c) water management and other applications, by identifying important parameters for successful adaptive management.