Mapping precipitation in ungauged mountain sites.

This project aims to develop a methodology to estimate precipitation in ungauged mountain sites using dynamically downscaled climate model data and probabilistic post-processing techniques.

Probabilistic streamflow predictions in ungauged catchments.

This project aims to develop a methodology to estimate streamflow in ungauged catchments using neural processes, a novel machine learning technique that can provide probabilistic predictions, and large-sample hydrological datasets.

Improving the resolution of digital terrain maps.

This project aims to develop a methodology to improve the resolution of digital terrain maps using deep learning techniques and high-resolution remote sensing data.