We're excited to announce a new article published in the Journal of Hydrology: Regional Studies: 'Insights from a comparison of two hydrological modelling approaches in the Kwando (Cuando) River and the western tributaries of the Zambezi River basin'.
A collaboration with our colleagues at the World Wildlife Fund (WWF) and Rhodes University, the focus of the study was to compare the performance of two different hydrological modeling approaches – one a theory-guided machine learning model (HydroForecast), the other a conceptual model – specifically when set in a data-sparse region. The study outlines how the performance of HydroForecast performs better 'in terms of statistical fit between simulated and observed flows – than the conceptual model'.
To read the full article please visit this link, or find the PDF through our site here.
