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
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:
- Jan. 2018 - Mar. 2023, EPSRC Fellowship Scheme, “Smart forecasting: joined-up flood forecasting (FF) infrastructure with uncertainties”, funder ID: “EP/R007349/1”.
- Mar. 2014 - Jul 2015, EPSRC First Grant Scheme, “Unified flood model with optimal zooming and linking at multiple scales”, funder ID: “EP/K031023/1”.
- Aug. 2013 - Feb. 2014, DAAD Short-Term Grant, “Transforming flood risk modelling: collaborative research schedule with RWTH Aachen”, funder ID: “A1372005”.