Exploring the value of machine learning for weighted multi-model combination of an ensemble of global hydrological models
(2019)
Journal Article
Zaherpour, J., Mount, N., Gosling, S., Dankers, R., Eisner, S., Gerten, D., …Wada, Y. (2019). Exploring the value of machine learning for weighted multi-model combination of an ensemble of global hydrological models. Environmental Modelling and Software, 114, 112-128. https://doi.org/10.1016/j.envsoft.2019.01.003
This study presents a novel application of machine learning to deliver optimised, multi-model combinations (MMCs) of Global Hydrological Model (GHM) simulations. We exemplify the approach using runoff simulations from five GHMs across 40 large global... Read More about Exploring the value of machine learning for weighted multi-model combination of an ensemble of global hydrological models.