Dr. Konrad Bogner

Function

scientific staff member

Mountain Hydrology and Mass Movements

Hydrological Forecasts

Contact

konrad.bogner(at)wslto make life hard for spam bots.ch

+41 44 739 24 95+41 44 739 24 95

Swiss Federal Research Institute WSL
Zürcherstrasse 111
8903 Birmensdorf

Site

Birmensdorf Bi LG D 08

FURTHER INFORMATION

Projects

Analyse der Warnkette anhand von zwei Unwetterereignissen im Jahr 2020

Zwei heftige Starkniederschlagsereignisse im Spätsommer 2020 (28.-30. August und 1.-4. Oktober) führten zu erheblichem Hochwasser in der Südschweiz. In dieser Studie wird die gesamte Warnkette von der meteorologischen Vorhersage bis hin zu den Massnahmen in den Kantonen/Gemeinden analysiert.

Demonstrator for flexible SHP (SmallFlex): Real-time hydrological forecasts

Dans ce projet, la valeur ajoutée des prévisions hydrologiques à très court terme (< 6 h) et à long terme (1 mois) pour l'exploitation d'une petite centrale hydroélectrique alpine (Gletsch-Oberwald) est étudiée.

Risks for small hydropower plants associated with climate change

estimate the impact of climate change on the inflow in a snowmelt dominated tributary of a small hydropower plant using a stochastic 2-dimensional weather generator, a high-resolution energy balance snow cover and a gridded hydrological model

Ensemble predictions

The project HEPS4Power explores the use of extended-range hydrological ensemble predictions systems (HEPS) for improving the operations and revenues of hydropower systems.

IFKIS Hydro Sihl

WSL develops and operates a probabilistic flood forecasting system for the pre-alpine catchment of the river Sihl. Floods can be detected early through a series of daily performed predictions.

Publications WSL

Scientific publication article peer reviewed

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. doi: 10.1029/2019WR025280

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.). doi: 10.3390/su11123328

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. doi: 10.5194/hess-23-493-2019

Bogner, K.; Liechti, K.; Zappa, M., 2018: Error correcting and combining multi-model flood forecasting systems. In: Gourbesville, P.; Cunge, J.; Caignaert, G. (eds), 2018: Advances in hydroinformatics. SimHydro 2017 - choosing the right model in applied hydraulics. SimHydro conference 2017, Nice, France. 569-578. doi: 10.1007/978-981-10-7218-5_40

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. doi: 10.1029/2017JD027923