Hydrology; Hydropower; Climatology; Water_resources; Extended_Range_Predictions; Uncertainty; Meteorology
Monhart Samuel, Zappa Massimiliano, Spirig Christoph, Schär Christoph, Bogner Konrad (2018), Subseasonal hydrometeorological ensemble predictions in small-and medium-size mountainous catchments: Benefits of the NWP approach, in Hydrology and Earth System Sciences Discussions
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, in Journal of Geophysical Research: Atmospheres
, 123(15), 7999-8016.
Bogner Konrad, Liechti Katharina, Bernhard Luzi, Monhart Samuel, Zappa Massimiliano (2018), Skill of Hydrological Extended Range Forecasts for Water Resources Management in Switzerland, in Water Resources Management
, 32(3), 969-984.
Bogner Konrad, Liechti Katharina, Zappa Massimiliano (2016), Post-Processing of Stream Flows in Switzerland with an Emphasis on Low Flows and Floods., in Water
, 8(4), 115.
In recent years large progresses have been achieved in the operational prediction of floods and hydrological drought with up to ten days lead time. Both the public and the private sectors are currently using probabilistic runoff forecast in order to monitoring water resources and take actions when critical conditions are to be expected. The use of extended-range predictions with lead times exceeding 10 days is not yet established. The hydropower sector in particular might have large benefits from using hydro meteorological forecasts for the next 15 to 60 days in order to optimize the operations and the revenues from their watersheds, dams, captions, turbines and pumps.The new Swiss Competence Centers in Energy Research targets at boosting research related to energy issues in Switzerland. We think that operational extended-range hydro meteorological predictions have the potential to become very valuable tools for fine tuning the production of energy from hydropower systems. The project team covers a specific system-oriented value chain starting from the collection and forecast of meteorological data (MeteoSwiss), leading to the operational application of state-of-the-art hydrological models (WSL) and terminating with the experience in data presentation and power production forecasts for end-users (e-dric.ch). All the projects partners have running collaborations with partners from the hydropower sector. Most notably we can cite “Elettricità della Svizzera Italiana” (WSL), Alpiq (edric.ch) and “Groupe E” (edric.ch). We are sure we can create a positive dialog within this specific value chain and deliver after the project the proof that hydropower production can profit from hydro meteorological forecasts.The PhD student will investigate how such forecasts might be issued, refined and published for providing the hydropower sector with information (abundance/scarcity/drought) for decision making. The list of possible applications includes: (a) predictions of inflows (b) reduction/minimization of spillover (c) planning of maintenance of captions (d) indications on possible floods (e.g. closing captions to avoid obstruction by debris) (e) co-ordination of production from a network with multiple stakeholders.The project builds upon synergies with funded running projects in the framework of CCHydro (WSL), NCCR Climate III (MeteoSwiss), MAP D-PHASE (MeteoSwiss and WSL), NRP61 DROUGHT-CH (WSL).The requested grant of about (CHF 250’000) is allocated for funding a joint PhD project (WSL and MeteoSwiss), for establishing a link between science and end-users via an industrial partner that will develop specific products (e-dric). Some funding is allocated to buy a server (including backup solution) for operational computations of hydropower forecasts.The project team will organize workshops and establish dialog where we will present our findings to stakeholders and industrial partners linked to SCCER and potentially interested in operative deployment of our R&D outcomes.