Improving the accuracy of flood inundation forecasts through remote sensing and in situ measurements

Flood inundation models serve as important tools in flood risk management. However, these models make use of as well uncertain input data as model paramters which reduce their predictive skill. In this project, it will be investigated whether assimilating both remote sensing observations of flood extent and in situ measurements within the flood plain can improve flood inundation model predictions.