Research

Climate change has an impact on the hydrology in the March catchment. Climate change modelling studies for catchments in this region show reduced soil moisture and increasing drought stress in the summer months. The aim of this project is to investigate which ecological measures can be taken to improve water retention in the Lower Austrian March catchment area. The results should support land users, regional policy and administration in adapting to climate change. The study focusses in detail on the following three topics: 1. climate forecasts and extreme precipitation 2. causes of declining water availability and challenges 3. nature-based options for action and their potential

The estimation of energy production losses due to residual or environmental flows was carried out around 20 years ago. That assessment was based on simplified assumptions, especially regarding the hydrology and small hydropower. The improved availability of data, as well as findings from measures already implemented, should now help to provide a more accurate estimate of generation losses. The analyses will not only update the figures from the previous, but also determine the effects of gradual increases in residual flow until the full implementation of the WFD.

One of the important tasks of Austrian Power Grid AG (APG) is the medium-term forecast of energy production from hydropower plants in order to be able to coordinate and plan the availability and utilization of the Austrian electricity grid accordingly. The objective of the planned project is to improve the medium-term forecast (24, 48 and 72 hours) for the "medium" small hydropower plants. An initial focus will be placed on the Salzburg model region, where the data situation for the development and implementation of AI forecasting methods is very good. This initial feasibility study will be divided into several phases: In consultation with the client, initially two AI methods (XGBoost, and Long-Short-Term-Memory (LSTM) models) will be tested and optimized with the VTW's as the sole input variables for the locations of the CHP plants. In further steps, static catchment area characteristics (topography, soil, geology, climate, vegetation) are integrated into the methods as additional information. External drivers such as precipitation and weather forecasts from ZAMG/GeoSphere or model-based estimates of the so-called snow-water equivalent of the existing snow cover are then taken into account.