Assessing the value of seasonal hydrological forecasts for improving water resource management: insights from a pilot application in the UK

Peñuela, Andres; Hutton, Christopher; Pianosi, Francesca

doi:https://doi.org/10.5194/hess-24-6059-2020

Articles | Volume 24, issue 12

https://doi.org/10.5194/hess-24-6059-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/hess-24-6059-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 24, issue 12

Research article

|

23 Dec 2020

Research article |

| 23 Dec 2020

Assessing the value of seasonal hydrological forecasts for improving water resource management: insights from a pilot application in the UK

Andres Peñuela, Christopher Hutton, and Francesca Pianosi

Supplement

https://doi.org/10.5194/hess-24-6059-2020-supplement

Data sets

iRONS (interactive Reservoir Operation Notebooks and Software) A. Peñuela and F. Pianosi https://doi.org/10.5281/zenodo.4277646

The Subseasonal to Seasonal (S2S) Prediction Project Database (https://apps.ecmwf.int/datasets/data/s2s-reforecasts-instantaneous-accum-ecmf/levtype=sfc/type=cf/) F. Vitart, C. Ardilouze, A. Bonet, A. Brookshaw, M. Chen, C. Codorean, M. Déqué, L. Ferranti, E. Fucile, M. Fuentes, H. Hendon, J. Hodgson, H.-S. Kang, A. Kumar, H. Lin, G. Liu, X. Liu, P. Malguzzi, I. Mallas, M. Manoussakis, D. Mastrangelo, C. MacLachlan, P. McLean, A. Minami, R. Mladek, T. Nakazawa, S. Najm, Y. Nie, M. Rixen, A. W. Robertson, P. Ruti, C. Sun, Y. Takaya, M. Tolstykh, F. Venuti, D. Waliser, S. Woolnough, T. Wu, D.-J. Won, H. Xiao, R. Zaripov, and L. Zhang https://doi.org/10.1175/BAMS-D-16-0017.1

Short summary

In this paper we evaluate the potential use of seasonal weather forecasts to improve reservoir operation in a UK water supply system. We found that the use of seasonal forecasts can improve the efficiency of reservoir operation but only if the forecast uncertainty is explicitly considered. We also found the degree of efficiency improvement is strongly affected by the decision maker priorities and the hydrological conditions.