Benchmarking Data-Driven Rainfall-Runoff Models in Great Britain: A comparison of LSTM-based models with four lumped conceptual models

Abstract

Data for our benchmarking study of 2 LSTM based models compared against four traditional (lumped-conceptual) hydrological models (Lane et al 2019) for Great Britain. These models were trained using data from CAMELS GB (Coxon et al 2020) and using the model training and inference structure at [neuralhydrology](https://github.com/neuralhydrology/neuralhydrology). References: Coxon, Gemma, et al. "CAMELS-GB: hydrometeorological time series and landscape attributes for 671 catchments in Great Britain." <em>Earth System Science Data</em> 12.4 (2020): 2459-2483.APA Lane, Rosanna A., et al. "Benchmarking the predictive capability of hydrological models for river flow and flood peak predictions across over 1000 catchments in Great Britain." <em>Hydrology and Earth System Sciences</em> 23.10 (2019): 4011-4032.APA