This is a project which is currently making use of HPC facilities at Newcastle University. It is active.
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This project will investigate the impact that land cover and climate change has on stream flow in the UK, using a physically based, spatially distributed, fully gridded hydrological model called SHETRAN. We will develop annual land cover scenes by using random forest classification of satellite imagery to fill in authoritative land cover dataset gaps, and dynamically update land cover parameterization in SHETRAN to better model historical stream flows. Future land cover and climate scenarios will then be used to estimate future UK stream flows, starting with several pilot catchments followed by scaling nationally. HPC infrastructure will be used for 1) earth observation/ remote sensing land cover classification, which uses random forest machine learning techniques, and 2) for running the physically based, spatially distributed hydrological model, SHETRAN.