Knowledge Discovery and Information Fusion Tools for Collaborative Systems to Adaptively Manage Uncertain Hydrological Resources
There is a critical need to accurately and efficiently assess and manage water quantity. This is a challenge because water management is conducted under conditions of uncertainty about current and future water resources. Adaptive water management has become the policy heuristic 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.
The long-term goal of this project was to develop intelligent, scalable decision support tools for collaborative systems that incorporate uncertainty to analyze and integrate hydrological data and information. The framework is powered by knowledge discovery, information fusion and visualization tools, that: assist hydrologists developing comprehensive models and metrics for the analysis of the water cycle; supports decision makers in adaptive management determinations; increases confidence in water data for adaptive managers, policymakers, and water users; and helps policy makers study the social and legal impact on water users. The project addressed several research aspects of collaborative systems, including knowledge discovery and information fusion applied in a digital government domain.
Finally, we worked, as part of the project, with Hohai University (Nanjing, China) to develop cross-national research relevant to water management issues.