Application of random forest regression in modelling long-term average groundwater recharge in Africa
Inspired by the research by MacDonald et al. 2021 who created the first continental map of groundwater recharge using a spatial model. Here random forest regression is applied to obtain a recharge map at a spatial resolution of 0.5 degree with a significantly higher level of detail than the previous map, and a high resolution map at 0.1 degree.
This code is a part of a thesis submitted to the University College London for the Degree of Master of Science.
Refer to the following paper (preprint) for complete study: Pazola et al. 2023