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

目前迫切需要准确和有效地评估和管理水量。由于必须在当前和未来水资源不确定的情况下进行水管理，这一挑战变得更加严峻。适应性水管理已成为灵活的水管理所采用的政策启发，以应对不断变化的物质和社会需求。适应性管理方法的核心挑战是需要量化观测到的水测量的不确定性。本研究将创造新的知识发现与资讯融合演算法，以计算两个水指标，并将其嵌入一个整体的知识管理系统。长期目标是为协作系统开发智能的、可扩展的决策支持工具，这些工具明确地将不确定性纳入分析和整合水文数据和信息。该提案的具体目标是：1.知识发现和信息融合：设计可扩展的算法来（a）计算数据质量（QoD）、信息质量（QoI）和知识质量（QoK），（B）将地理空间事件的邻近性纳入时空数据挖掘，（c）整合异构、不完整和不确定的地理空间数据和信息.水资源状况：制定一个关于水资源状况的综合水指标-在空间和时间的某一特定点上所有水资源的综合状况。适应性管理：确定管理者和决策者用于适应性水资源管理的具体水资源管理方法。软件产品：建立一套基于网络的知识发现和信息融合工具，以分析、整合和可视化水文数据、水指标及其质量。智力优势：拟议的研究将有助于知识发现和信息融合方法，明确建模和传播一般的不确定性和地理空间分析，特别是。将设计一个由多种多样的数据集组成的数字储存库的综合框架，由有效和高效的知识发现、信息融合和可视化工具提供动力，㈠协助水文学家开发用于分析水循环的综合模型和指标; ㈡支持决策者作出适应性管理决策;和iii）帮助决策者研究对水用户的社会和法律的影响。更广泛的影响：研究将在三个学科中推进最先进的技术：（a）计算机科学，开发新的知识发现技术，（B）水文学，利用信息融合方法开发两种综合水指标，（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.