An intelligent and adaptable grid-based flood monitoring and warning system.
Daniel Hughes, Philip Greenwood, Gordon S. Blair, Florian Pappenberger, Geoffrey Coulson, Paul J. Smith, Keith Beven
Abstract
Daniel Hughes, Philip Greenwood, Gordon S. Blair, Florian Pappenberger, Geoffrey Coulson, Paul J. Smith, Keith Beven
Abstract
Flooding is a growing problem in the UK. It has a significant effect on residents, businesses and commuters in flood-prone areas. The cost of damage caused by flooding correlates closely with the warning time given before a flood event, and this makes flood monitoring and prediction critical to minimizing the cost of flood damage. This paper describes a wireless sensor network for flood warning which is not only capable of integrating with remote fixed-network grids for computationally-intensive flood modeling purposes, but is also capable of performing on-site flood modeling by organising itself as a 'local grid'. The combination of these two modes of grid computation-local and remote-yields significant benefits. For example, local computation can be used to provide timely warnings to local stakeholders, and a combination of local and remote computation can inform adaptation of the sensor network to maintain optimal performance in changing environmental conditions.
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Flooding is a growing problem in the UK. It has a significant effect on residents, businesses and commuters in flood-prone areas. The cost of damage caused by flooding correlates closely with the warning time given before a flood event, and this makes flood monitoring and prediction critical to minimizing the cost of flood damage. This paper describes a wireless sensor network for flood warning which is not only capable of integrating with remote fixed-network grids for computationally-intensive flood modeling purposes, but is also capable of performing on-site flood modeling by organising itself as a 'local grid'. The combination of these two modes of grid computation-local and remote-yields significant benefits. For example, local computation can be used to provide timely warnings to local stakeholders, and a combination of local and remote computation can inform adaptation of the sensor network to maintain optimal performance in changing environmental conditions.
Key concepts: Flood myth, Flood warning, Flooding (psychology), Grid, Warning system, Computer science, Computation, Wireless sensor network