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Research project (§ 26 & § 27)
Duration : 2021-07-15 - 2024-01-14

As part of the "Digital Transformation at the BMLRT", the planned project KIHoRiMo is to develop a digital flood risk monitoring system (HRMS) for the whole of Austria. In doing so, the potentials of modern geodata and innovative AI technologies will first be analyzed and then integrated into the HRMS, if necessary. In the project, the HyWa Institute will be responsible for coordinating the areas of flood monitoring, flooding and event scenarios, as well as predisposition analysis and current risk situation. The work will be coordinated and jointly developed with other project partners (ZAMG-meteorology/forecast; TU Vienna-soil moisture/floodplains; BOKU-land use/cover) and the activities in the "Earth-Observation-Data-Center (EODC)". The overall objective is to support the governmental crisis and disaster management (SKKM) in the broadest possible form with detailed information for efficient action within the risk cycle. The aim is to derive statements for the whole of Austria at any given time regarding the risk posed by a flood at a given point in time. In the project area "Flood Monitoring", coordinated by HyWa, the focus is on the presentation (forecast, monitoring) of flood inundation areas. In the project area "risk analysis", a modular prototype (service) for the presentation of the current development and forecasts of the consequences of a flood (affected areas, risk categories, user groups) is to be developed. In both areas, the optimal use of internal know-how and data (ministries, subordinate authorities, federal states), as well as networking with all available external systems should be ensured. Likewise, all available real-time measurements (sensors, trusted spotters, social media, etc.) should be used for resilient forecasts or feedback for system optimization. In this way, not only the SKMM but all groups of people and institutions involved in the risk cycle should benefit from the project.
Research project (§ 26 & § 27)
Duration : 2021-05-25 - 2024-06-30

Due to advancing climate change, temperature and weather conditions are changing and pose new challenges for the transport infrastructure. Therefore, ÖBB-Infrastruktur AG is intensively dealing with the effects of climate change on its facilities and operations. Two challenges of the adaptation process will be examined in more detail within the framework of this research project: The Alpine region is exposed to different meteorological phenomena. Transport infrastructure operators have the obligation to secure their facilities up to a defined design event. However, extreme weather events can extend far beyond the design events. Protective facilities can fail. Likewise, various natural hazard processes can occur simultaneously and even overlap. These situations usually mean danger to infrastructure as well as enormous economic damage. Due to global warming, an increase in extreme weather events is to be expected. In this regard, ÖBB-Infrastruktur AG operates a weather information system that serves to provide standardized forecasts, information and warnings of weather events such as heavy rain, snowfall, storms or heat. ÖBB-Infrastruktur AG operates its own power generation facilities to supply rail traffic in Austria. A large part of its own generation comes from its own hydroelectric power plants in Vorarlberg, Tyrol, Salzburg and Carinthia with catchment areas largely in the glaciated and non-glaciated Central Alps, as well as the Northern Limestone High Alps. In addition, ÖBB Infrastruktur AG is working on the expansion of photovoltaics and wind power. Changing climate and weather conditions influence the supply of renewable energy. The aim of the research project is to create a knowledge base with the help of climate models, on the basis of which transport infrastructure operators can take measures for climate change adaptation. To this end, the following research questions are to be addressed: - Development of an adapted, condensed sensor technology to improve the forecast of extreme weather events - Definition and forecasting of convective precipitation events - Development of a forecast for drought and wildfire risk - Development of a forecast for small-scale wildfire hazards - Analysis and quantification of the impact of climate change on the supply of renewable energy (solar, wind, hydro) - Forecast of expected, medium-term inflow changes in ÖBB's own storage reservoirs - Forecast of the expected, medium-term inflow changes to the run-of-river power plants - Forecast of expected generation from wind and PV
Research project (§ 26 & § 27)
Duration : 2021-06-01 - 2022-05-31

The short-term forecast (1-4h) for the Inn and Danube power plants is an economically important planning instrument for VERBUNG AG. However, the current forecasts via the model system COSERO are not satisfactory in phases of rising and falling discharge regimes. In the project, we will try to significantly improve the short-term forecasts with the help of machine learning procedures using all available input data. Methods that will be adapted and further developed are stepwise linear regression, random forest, XGBoost and feed foreward neural network. The existing COSERO model runs and the classical "Adaptive gain transfer function" concept serve as Benschmark models. In a first phase, the potential of the method will be analyzed for 2 selected power plants.

Supervised Theses and Dissertations