| Using a long short-term memory (LSTM) neural network to boost river streamflow forecasts over the western United States KMR Hunt, GR Matthews, F Pappenberger, C Prudhomme Hydrology and Earth System Sciences 26 (21), 5449-5472, 2022 | 64 | 2022 |
| Evaluating the impact of post-processing medium-range ensemble streamflow forecasts from the European Flood Awareness System G Matthews, C Barnard, H Cloke, SL Dance, T Jurlina, C Mazzetti, ... Hydrology and Earth System Sciences 26 (11), 2939-2968, 2022 | 13 | 2022 |
| Connecting hydrological modelling and forecasting from global to local scales: Perspectives from an international joint virtual workshop A Dasgupta, L Arnal, R Emerton, S Harrigan, G Matthews, A Muhammad, ... Journal of Flood Risk Management, e12880, 2023 | 6 | 2023 |
| Co-design and co-production of flood forecast products: Summary of a hybrid workshop G Matthews, HL Cloke, SL Dance, E Hansford, C Mazzetti, C Prudhomme Bulletin of the American Meteorological Society 104 (5), E1058-E1066, 2023 | 1 | 2023 |
| Post-processed reforecasts of the European Flood Awareness System and related evaluation data G Matthews, C Barnard University of Reading, 2021 | 1 | 2021 |
| Global hydrological reanalyses: The value of river discharge information for world-wide downstream applications–The example of the Global Flood Awareness System GloFAS C Prudhomme, E Zsótér, G Matthews, A Melet, S Grimaldi, H Zuo, ... Meteorological Applications 31 (2), e2192, 2024 | | 2024 |
| Global hydrological reanalyses: the value of river discharge information for world-wide downstream applications C PRUDHOMME, E ZSOTER, G MATTHEWS, M ANGELIQUE, ... | | |
