Details of Award
NERC Reference : NE/N004817/1
Real-time forecasting of algal blooms in reservoirs
Grant Award
- Principal Investigator:
- Professor K Beven, Lancaster University, Lancaster Environment Centre
- Grant held at:
- Lancaster University, Lancaster Environment Centre
- Science Area:
- Earth
- Freshwater
- Overall Classification:
- Unknown
- ENRIs:
- Natural Resource Management
- Pollution and Waste
- Science Topics:
- Community Ecology
- Population Ecology
- Intelligent & Expert Systems
- Biogeochemical Cycles
- Water Quality
- Abstract:
- Algal blooms are a significant problem for water management worldwide and are costly to manage (e.g. costing an estimated #50 million per year in the UK at 2003 rates). Water companies are faced with problems such as blocked filters, poor taste and odour and, in more extreme cases, high levels of algal-derived toxins. There are a number of management strategies that can be implemented, often in a reactive way. It is therefore advantageous to be able to predict when an algal bloom is likely to occur. In a previous NERC funded project (UKLEON - NE/I007407/1; http://www.ecn.ac.uk/what-we-do/science/projects/ukleon), forecasts of algal blooms in lakes have been made with acceptable accuracy. The forecasts are made using a computer model which describes the growth of algal communities given weather forecasts. For this to be achievable, adequate data is required to be able to run the model and to be able to inform us of when the model is providing a good representation of the lake system. Adequate data availability is a critical part of the forecasting system and can be costly, so there is a requirement to balance the costs of data collection and modelling against the costs of managing algal blooms. The proposed project has the overall objective of defining the water industry's requirement for an algal forecasting system for reservoirs and to determine the likely cost-effectiveness of such a system. Information on the costs associated with different management strategies will be assessed against the costs associated with data collection, model calibration and implementation. These costs will vary based upon: - The accuracy of the forecasts for the required forecast period (e.g. 3, 5 or 10 days ahead). - The characteristics of the reservoir and its catchment. - The level of historic data available for setting up the forecasting system. If such a system is proven to be cost effective the potential for positive impacts on water supply management within the UK, the EU and world wide are significant both in terms of water quality and cost savings.
- NERC Reference:
- NE/N004817/1
- Grant Stage:
- Completed
- Scheme:
- Innovation
- Grant Status:
- Closed
- Programme:
- Follow on Fund Pathfinder
This grant award has a total value of £17,029
FDAB - Financial Details (Award breakdown by headings)
| DI - Other Costs | Indirect - Indirect Costs | DA - Investigators | DA - Estate Costs | DI - Staff | DA - Other Directly Allocated |
|---|---|---|---|---|---|
| £13,562 | £1,201 | £255 | £585 | £1,400 | £26 |
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