SEAMLESS-WAVE

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SEAMLESS-WAVE is a developing “SoftwarE infrAstructure for Multi-purpose fLood modElling at variouS scaleS” based on "WAVElets" and their versatile properties. The vision behind SEAMLESS-WAVE is to produce an intelligent and holistic modelling framework, which can drastically reduce iterations in building and testing for an optimal model setting, and in controlling the propagation of model-error due to scaling effects and of uncertainty due statistical inputs.

View the Project on GitHub ci1xgk/Fellowship_Webpage

Contact and acknowledgments

The development of SEAMLESS-WAVE is currently led by Georges Kesserwani supported by an EPSRC Fellowship Scheme. The science and thinking behind the development of SEAMLESS-WAVE is owed to following research grants:

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