Articles | Volume 22, issue 5
https://doi.org/10.5194/hess-22-2953-2018
https://doi.org/10.5194/hess-22-2953-2018
Research article
 | 
18 May 2018
Research article |  | 18 May 2018

The development and evaluation of a hydrological seasonal forecast system prototype for predicting spring flood volumes in Swedish rivers

Kean Foster, Cintia Bertacchi Uvo, and Jonas Olsson

Related authors

Technical Note: Initial assessment of a multi-method approach to spring-flood forecasting in Sweden
J. Olsson, C. B. Uvo, K. Foster, and W. Yang
Hydrol. Earth Syst. Sci., 20, 659–667, https://doi.org/10.5194/hess-20-659-2016,https://doi.org/10.5194/hess-20-659-2016, 2016
Short summary

Related subject area

Subject: Water Resources Management | Techniques and Approaches: Modelling approaches
Process-based three-layer synergistic optimal-allocation model for complex water resource systems considering reclaimed water
Jing Liu, Yue-Ping Xu, Wei Zhang, Shiwu Wang, and Siwei Chen
Hydrol. Earth Syst. Sci., 28, 1325–1350, https://doi.org/10.5194/hess-28-1325-2024,https://doi.org/10.5194/hess-28-1325-2024, 2024
Short summary
Joint optimal operation of the South-to-North Water Diversion Project considering the evenness of water deficit
Bing-Yi Zhou, Guo-Hua Fang, Xin Li, Jian Zhou, and Hua-Yu Zhong
Hydrol. Earth Syst. Sci., 28, 817–832, https://doi.org/10.5194/hess-28-817-2024,https://doi.org/10.5194/hess-28-817-2024, 2024
Short summary
Employing the generalized Pareto distribution to analyze extreme rainfall events on consecutive rainy days in Thailand's Chi watershed: implications for flood management
Tossapol Phoophiwfa, Prapawan Chomphuwiset, Thanawan Prahadchai, Jeong-Soo Park, Arthit Apichottanakul, Watchara Theppang, and Piyapatr Busababodhin
Hydrol. Earth Syst. Sci., 28, 801–816, https://doi.org/10.5194/hess-28-801-2024,https://doi.org/10.5194/hess-28-801-2024, 2024
Short summary
How to account for irrigation withdrawals in a watershed model
Elisabeth Brochet, Youen Grusson, Sabine Sauvage, Ludovic Lhuissier, and Valérie Demarez
Hydrol. Earth Syst. Sci., 28, 49–64, https://doi.org/10.5194/hess-28-49-2024,https://doi.org/10.5194/hess-28-49-2024, 2024
Short summary
Inferring reservoir filling strategies under limited-data-availability conditions using hydrological modeling and Earth observations: the case of the Grand Ethiopian Renaissance Dam (GERD)
Awad M. Ali, Lieke A. Melsen, and Adriaan J. Teuling
Hydrol. Earth Syst. Sci., 27, 4057–4086, https://doi.org/10.5194/hess-27-4057-2023,https://doi.org/10.5194/hess-27-4057-2023, 2023
Short summary

Cited articles

Arheimer, B., Lindström, G., and Olsson, J.: A systematic review of sensitivities in the Swedish flood-forecasting system, Atmos. Res., 100, 275–284, 2011. 
Arnal, L., Wood, A. W., Stephens, E., Cloke, H. L., and Pappenberger, F.: An efficient approach for estimating streamflow forecast skill elasticity, J. Hydrometeorol., 18, 1715–1729, 2017. 
Beckers, J. V. L., Weerts, A. H., Tijdeman, E., and Welles, E.: ENSO-conditioned weather resampling method for seasonal ensemble streamflow prediction, Hydrol. Earth Syst. Sci., 20, 3277–3287, https://doi.org/10.5194/hess-20-3277-2016, 2016. 
Bennett, J. C., Wang, Q. J., Li, M., Robertson, D. E., and Schepen, A.: Reliable long-range ensemble streamflow forecasts: Combining calibrated climate forecasts with a conceptual runoff model and a staged error model, Water Resour. Res., 52, 8238–8259, 2016. 
Berg, P., Bosshard, T., and Yang, W.: Model consistent pseudo-observations of precipitation and their use for bias correcting regional climate models, Climate, 3, 118–132, 2015. 
Download
Short summary
Hydropower makes up nearly half of Sweden's electrical energy production. Careful reservoir management is required for optimal production throughout the year and accurate seasonal forecasts are essential for this. In this work we develop a seasonal forecast prototype and evaluate its ability to predict spring flood volumes, a critical variable, in northern Sweden. We show that the prototype is better than the operational system on average 65 % of the time and reduces the volume error by ~ 6 %.