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Self Learning Methodologies workshop
Date: January 2007
To develop a self-learning decision support system for the optimisation of lake and reservoir functions by:
1. Developing new hydroinformatics techniques: The first objective is to develop and demonstrate software and hardware technologies that will allow the coupled 3D hydrodynamic-water quality model ELCOM-CAEDYM to self-learn the coefficient set from in situ instrumentation, thereby producing more accurate model predictions of water quality.
2. Integrating state-of-the-art biotechnological techniques: The second objective is to adapt new emerging real-time molecular and cytometric techniques to current CWR real-time measurement methodologies, for the purpose of providing accurate in situ time series of biological variables. This development will focus on pathogens and bioindicators, however a later stage of the project will be used to explore the application of this technology to other taxa of interest within the ecosystem (e.g. cyanobacteria and photosynthetic eukaryotes).
3. Formulating a new sustainability framework: The third objective is to integrate the large amount of physical, chemical and biological information (observed and simulated) into a framework designed to support Decision Makers both in short-term management and long-term planning of lakes and reservoirs. The framework will be based on the Participatory and Integrated Planning (PIP) procedure and use the Index of Sustainable Functionality. Tools and methods will be developed and tested for the Marina Reservoir and its environs.
Venue Building: Waterhub
Venue Address: 82 Toh Guan East
Venue City: Singapore
Venue Country: Singapore
Organizers: Centre for Water Research, Australia, Public Utilities Board, Singapore
Sponsors:
Centre for Water Research, Australia
Public Utilities Board, Singapore
Contacts:
Caroline Wood
Centre for Water Research, Australia
Tan Kok Meng
Public Utilities Board, Singapore |
