New study applies existing theory to predict floods

Study shows how Shannon`s Information Theory can also be applied to studying high water & flooding.

Washington: A new study shows how Shannon``s Information Theory can also be applied to studying high water and flooding.

Information theory, first devised in 1948 by Claude Shannon, sees information and uncertainty as numerical quantities, measured in ``bits``, that correspond with the extent to which the recipient of a message is surprised by that message (‘surprisal’).

The level of surprisal depends on how likely the recipient considered the event to be.

Steven Weijs found that models used a golden rule: the greater the amount of information, the better the decision.

In fact not only the flow of water, but also the flow of information from measurements, via models and predictions, to the final decision should be optimised. This would be achievable by assessing the models according to the amount of information comprised in their predictions.

The researchers hope that the information can be used to make more accurate predictions about flooding and enable better management of reservoirs to cope with high water levels.


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