All Outputs (2)

Including spatial distribution in a data-driven rainfall-runoff model to improve reservoir inflow forecasting in Taiwan (2014)
Journal Article
Meng-Jung, T., Abrahart, R., Mount, N. J., & Chang, F. (2014). Including spatial distribution in a data-driven rainfall-runoff model to improve reservoir inflow forecasting in Taiwan. Hydrological Processes, 28(3), https://doi.org/10.1002/hyp.9559

Multi-step ahead inflow forecasting has a critical role to play in reservoir operation and management in Taiwan during typhoons as statutory legislation requires a minimum of 3-hours warning to be issued before any reservoir releases are made. Howeve... Read More about Including spatial distribution in a data-driven rainfall-runoff model to improve reservoir inflow forecasting in Taiwan.

Sensitivity analysis for comparison, validation and physical-legitimacy of neural network-based hydrological models (2014)
Journal Article
Dawson, C., Mount, N. J., Abrahart, R., & Louis, J. (2014). Sensitivity analysis for comparison, validation and physical-legitimacy of neural network-based hydrological models. Journal of Hydroinformatics, 16(2), https://doi.org/10.2166/hydro.2013.222

This paper addresses the difficult question of how to perform meaningful comparisons between neural network-based hydrological models and alternative modelling approaches. Standard, goodness-of-fit metric approaches are limited since they only assess... Read More about Sensitivity analysis for comparison, validation and physical-legitimacy of neural network-based hydrological models.