Articles | Volume 21, issue 7
https://doi.org/10.5194/hess-21-3915-2017
https://doi.org/10.5194/hess-21-3915-2017
Research article
 | Highlight paper
 | 
31 Jul 2017
Research article | Highlight paper |  | 31 Jul 2017

An intercomparison of approaches for improving operational seasonal streamflow forecasts

Pablo A. Mendoza, Andrew W. Wood, Elizabeth Clark, Eric Rothwell, Martyn P. Clark, Bart Nijssen, Levi D. Brekke, and Jeffrey R. Arnold

Related authors

Towards robust seasonal streamflow forecasts in mountainous catchments: impact of calibration metric selection in hydrological modeling
Diego Araya, Pablo A. Mendoza, Eduardo Muñoz-Castro, and James McPhee
Hydrol. Earth Syst. Sci., 27, 4385–4408, https://doi.org/10.5194/hess-27-4385-2023,https://doi.org/10.5194/hess-27-4385-2023, 2023
Short summary
To what extent does river routing matter in hydrological modeling?
Nicolás Cortés-Salazar, Nicolás Vásquez, Naoki Mizukami, Pablo A. Mendoza, and Ximena Vargas
Hydrol. Earth Syst. Sci., 27, 3505–3524, https://doi.org/10.5194/hess-27-3505-2023,https://doi.org/10.5194/hess-27-3505-2023, 2023
Short summary
Revisiting parameter sensitivities in the variable infiltration capacity model across a hydroclimatic gradient
Ulises M. Sepúlveda, Pablo A. Mendoza, Naoki Mizukami, and Andrew J. Newman
Hydrol. Earth Syst. Sci., 26, 3419–3445, https://doi.org/10.5194/hess-26-3419-2022,https://doi.org/10.5194/hess-26-3419-2022, 2022
Short summary
On the selection of precipitation products for the regionalisation of hydrological model parameters
Oscar M. Baez-Villanueva, Mauricio Zambrano-Bigiarini, Pablo A. Mendoza, Ian McNamara, Hylke E. Beck, Joschka Thurner, Alexandra Nauditt, Lars Ribbe, and Nguyen Xuan Thinh
Hydrol. Earth Syst. Sci., 25, 5805–5837, https://doi.org/10.5194/hess-25-5805-2021,https://doi.org/10.5194/hess-25-5805-2021, 2021
Short summary
Sensitivity and identifiability of rheological parameters in debris flow modeling
Gerardo Zegers, Pablo A. Mendoza, Alex Garces, and Santiago Montserrat
Nat. Hazards Earth Syst. Sci., 20, 1919–1930, https://doi.org/10.5194/nhess-20-1919-2020,https://doi.org/10.5194/nhess-20-1919-2020, 2020
Short summary

Related subject area

Subject: Catchment hydrology | Techniques and Approaches: Modelling approaches
Assessing the impact of climate change on high return levels of peak flows in Bavaria applying the CRCM5 large ensemble
Florian Willkofer, Raul R. Wood, and Ralf Ludwig
Hydrol. Earth Syst. Sci., 28, 2969–2989, https://doi.org/10.5194/hess-28-2969-2024,https://doi.org/10.5194/hess-28-2969-2024, 2024
Short summary
Impacts of climate and land surface change on catchment evapotranspiration and runoff from 1951 to 2020 in Saxony, Germany
Maik Renner and Corina Hauffe
Hydrol. Earth Syst. Sci., 28, 2849–2869, https://doi.org/10.5194/hess-28-2849-2024,https://doi.org/10.5194/hess-28-2849-2024, 2024
Short summary
Quantifying and reducing flood forecast uncertainty by the CHUP-BMA method
Zhen Cui, Shenglian Guo, Hua Chen, Dedi Liu, Yanlai Zhou, and Chong-Yu Xu
Hydrol. Earth Syst. Sci., 28, 2809–2829, https://doi.org/10.5194/hess-28-2809-2024,https://doi.org/10.5194/hess-28-2809-2024, 2024
Short summary
Developing a tile drainage module for the Cold Regions Hydrological Model: lessons from a farm in southern Ontario, Canada
Mazda Kompanizare, Diogo Costa, Merrin L. Macrae, John W. Pomeroy, and Richard M. Petrone
Hydrol. Earth Syst. Sci., 28, 2785–2807, https://doi.org/10.5194/hess-28-2785-2024,https://doi.org/10.5194/hess-28-2785-2024, 2024
Short summary
To bucket or not to bucket? Analyzing the performance and interpretability of hybrid hydrological models with dynamic parameterization
Eduardo Acuña Espinoza, Ralf Loritz, Manuel Álvarez Chaves, Nicole Bäuerle, and Uwe Ehret
Hydrol. Earth Syst. Sci., 28, 2705–2719, https://doi.org/10.5194/hess-28-2705-2024,https://doi.org/10.5194/hess-28-2705-2024, 2024
Short summary

Cited articles

Abdi, H.: Partial least squares regression and projection on latent structure regression, Wiley Interdiscip. Rev. Comput. Stat., 2, 97–106, https://doi.org/10.1002/wics.051, 2010.
Akaike, H.: A new look at the statistical model identification, IEEE Trans. Automat. Contr., 19, 716–723, https://doi.org/10.1109/TAC.1974.1100705, 1974.
Anderson, E.: National Weather Service River Forecast system – snow accumulation and ablation model, NOAA Tech. Memo. NWS HYDRO-17, 217 pp., 1973.
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.
BPA: 2010 Level Modified Streamflow: 1928–2008, DOE/BP-4352, Seasonal Volumes and Statistics, 2011.
Download
Short summary
Water supply forecasts are critical to support water resources operations and planning. The skill of such forecasts depends on our knowledge of (i) future meteorological conditions and (ii) the amount of water stored in a basin. We address this problem by testing several approaches that make use of these sources of predictability, either separately or in a combined fashion. The main goal is to understand the marginal benefits of both information and methodological complexity in forecast skill.