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The value of subseasonal hydrometeorological forecasts to hydropower operations: how much does preprocessing matter?
Anghileri, D., Monhart, S., Zhou, C., Bogner, K., Castelletti, A., Burlando, P., & Zappa, M. (2019). The value of subseasonal hydrometeorological forecasts to hydropower operations: how much does preprocessing matter? Water Resources Research, 55(12), 10159-10178. https://doi.org/10.1029/2019WR025280
Machine learning techniques for predicting the energy consumption/production and its uncertainties driven by meteorological observations and forecasts
Bogner, K., Pappenberger, F., & Zappa, M. (2019). Machine learning techniques for predicting the energy consumption/production and its uncertainties driven by meteorological observations and forecasts. Sustainability, 11(12), 3328 (22 pp.). https://doi.org/10.3390/su11123328
Subseasonal hydrometeorological ensemble predictions in small- and medium-sized mountainous catchments: benefits of the NWP approach
Monhart, S., Zappa, M., Spirig, C., Schär, C., & Bogner, K. (2019). Subseasonal hydrometeorological ensemble predictions in small- and medium-sized mountainous catchments: benefits of the NWP approach. Hydrology and Earth System Sciences, 23(1), 493-513. https://doi.org/10.5194/hess-23-493-2019
Error correcting and combining multi-model flood forecasting systems
Bogner, K., Liechti, K., & Zappa, M. (2018). Error correcting and combining multi-model flood forecasting systems. In P. Gourbesville, J. Cunge, & G. Caignaert (Eds.), Springer Water. Advances in hydroinformatics. SimHydro 2017 - choosing the right model in applied hydraulics (pp. 569-578). https://doi.org/10.1007/978-981-10-7218-5_40
Skill of hydrological extended range forecasts for water resources management in Switzerland
Bogner, K., Liechti, K., Bernhard, L., Monhart, S., & Zappa, M. (2018). Skill of hydrological extended range forecasts for water resources management in Switzerland. Water Resources Management, 32(3), 969-984. https://doi.org/10.1007/s11269-017-1849-5
Skill of subseasonal forecasts in Europe: effect of bias correction and downscaling using surface observations
Monhart, S., Spirig, C., Bhend, J., Bogner, K., Schär, C., & Liniger, M. A. (2018). Skill of subseasonal forecasts in Europe: effect of bias correction and downscaling using surface observations. Journal of Geophysical Research D: Atmospheres, 123(15), 7999-8016. https://doi.org/10.1029/2017JD027923
Technical note: combining quantile forecasts and predictive distributions of streamflows
Bogner, K., Liechti, K., & Zappa, M. (2017). Technical note: combining quantile forecasts and predictive distributions of streamflows. Hydrology and Earth System Sciences, 21(11), 5493-5502. https://doi.org/10.5194/hess-21-5493-2017
Post-Processing of stream flows in Switzerland with an emphasis on low flows and floods
Bogner, K., Liechti, K., & Zappa, M. (2016). Post-Processing of stream flows in Switzerland with an emphasis on low flows and floods. Water, 8(4), 115 (20 pp.). https://doi.org/10.3390/w8040115
Regionalization of post-processed ensemble runoff forecasts
Skøien, J. O., Bogner, K., Salamon, P., Smith, P., & Pappenberger, F. (2016). Regionalization of post-processed ensemble runoff forecasts. A. H. Schumann, G. Bloschl, A. Castellarin, J. Dietrich, S. Grimaldi, U. Haberlandt, … S. Vorogushyn (Eds.), Proceedings of the international association of hydrological sciences (IAHS): Vol. 373. (pp. 109-114). Presented at the 7th international water resources management conference of ICWRS. https://doi.org/10.5194/piahs-373-109-2016
Building a multimodel flood prediction system with the TIGGE archive
Zsótér, E., Pappenberger, F., Smith, P., Emerton, R. E., Dutra, E., Wetterhall, F., … Balsamo, G. (2016). Building a multimodel flood prediction system with the TIGGE archive. Journal of Hydrometeorology, 17(8), 2923-2940. https://doi.org/10.1175/JHM-D-15-0130.1
Trends in the predictive performance of raw ensemble weather forecasts
Hemri, S., Scheuerer, M., Pappenberger, F., Bogner, K., & Haiden, T. (2014). Trends in the predictive performance of raw ensemble weather forecasts. Geophysical Research Letters, 41(24), 9197-9205. https://doi.org/10.1002/2014GL062472