Researchers developed a kite-shaped model to assess the level of risk of water contamination from manure. The model identifies four factors affecting risk: accumulated microbial burden, landscape transfer potential, infrastructure, and social and economic obstacles.
A team of researchers is using data from the 2001 census to build a model of the UK population, which will be used to test the consequences of different demographic trends and policy decisions. The model can be projected into the future to explore how different scenarios may play out.
A new intelligent sensor system could provide rapid and specific warnings of local flooding, reducing damage costs. The system uses grid computing to analyze data from sensors in flood-prone areas, making it possible to issue targeted warnings in time for action.
A new workflow language, Martlet, enables the analysis of large datasets in a changing environment by adjusting to data requirements at runtime. This approach has potential for use in various e-Science applications and demonstrates how core computer science can be used to meet exciting challenges.
The UK e-Science Programme has been recognized for its innovative grid implementation, investing over $450 million in R&D and deployment. The program enables collaborative working by making computing power accessible across networks.