Der Einfluss einer möglichen Klimaänderung auf das Abflussgeschehen wurde anhand von vier österreichischen Testeinzugsgebieten – der Bregenzer Ache (Pegel Mellau), der Lavant (Pegel Fischering), der Traisen (Pegel Lilienfeld) und der Oberen Salzach (Pegel Mittersill) erforscht. Für diese Untersuchung wurden Ergebnisse (Niederschlag, Lufttemperatur) des regionalen Klimamodells REMO-UBA des deutschen Max Planck Instituts Hamburg verwendet und die Klimaänderungssignale bestimmt. Dabei fanden die Entwicklungsszenarien A1B und B1 Anwendung. Mit Hilfe eines stochastischen Wettergenerators wurden Tageswerte der Lufttemperatur und des Niederschlags generiert, wobei die Klimanormalperiode 1961–1990 als Referenzperiode und 2071–2100 als zukünftige Vergleichsperiode gewählt wurden. Anhand monatsweiser Analysen wurden Änderungstendenzen festgestellt und dokumentiert, wobei regional unterschiedliche Ergebnisse erzielt wurden. Generell wurden eine Niederschlagszunahme in den Wintermonaten und eine Reduktion in den Sommermonaten festgestellt. Gemeinsam mit zunehmenden Winterniederschlägen werden die Abflüsse im Winter erhöht, die Sommerabflüsse werden tendenziell geringer. An der Bregenzer Ache reduzieren sich die Hochwasserabflüsse um ca. 10 %, ebenso and der Oberen Salzach bei Szenario A1B. An der Lavant werden gleichbleibende bis gering ansteigende Hochwässer prognostiziert. An der Traisen wird ein deutlicher Anstieg, insbesondere bei Szenario B1 vorhergesagt. Das ereignisbezogene saisonale Auftreten von Hochwässern zeigt eine Verschiebung in Richtung kurz andauernder intensiver Regenereignisse.

This study assesses the impact of a changing climate on fish fauna by comparing the past mean state of fish assemblage to a possible future mean state. It is based on (1) local scale observations along an Inner-Alpine river called Mur, (2) an IPCC emission scenario (IS92a), implemented by atmosphere-ocean global circulation model (AOGCM) ECHAM4/OPYC3, and (3) a model-chain that links climate research to hydrobiology. The Mur River is still in a near-natural condition and water temperature in summer is the most important aquatic ecological constraint for fish distribution. The methodological strategy is (1) to use downscaled air temperature and precipitation scenarios for the first half of the twenty-first century, (2) to establish a model that simulates water temperature by means of air temperature and flow rate in order to generate water temperature scenarios, and (3) to evaluate the impact on fish communities using an ecological model that is driven by water temperature. This methodology links the response of fish fauna to an IPCC emission scenario and is to our knowledge an unprecedented approach. The downscaled IS92a scenarios show increased mean air temperatures during the whole year and increased precipitation totals during summer, but reduced totals for the rest of the annual cycle. These changes result in scenarios of increased water temperatures, an altered annual cycle of flow rate, and, in turn, a 70 m displacement in elevation of fish communities towards the river's head. This would enhance stress on species that rely on low water temperatures and coerce cyprinid species into advancing against retreating salmonids. Hyporhithral river sectors would turn into epipotamal sectors. Grayling (Thymallus thymallus) and Danube salmon (Hucho hucho), presently characteristic for the Mur River, would be superceded by other species. Native brown trout (Salmo trutta), already now under pressure of competition, may be at risk of losing its habitat in favour of invaders like the exotic rainbow trout (Oncorhynchus mykiss), which are better adapted to higher water temperatures. Projected changes in fish communities suggest an adverse influence on salmonid sport fishing and a loss in its high economic value.

The purpose of this investigation is to demonstrate the usability of objective methods to study the variability of precipitation and hence to contribute to a better understanding of spatial and seasonal variability of Austria's precipitation climate during the 20th century.This will be achieved by regionalizing the intra-annual variability of seasonal precipitation distributions during three non-overlapping 33 year samples (1901-33, 1934-66, 1967-99). Monthly precipitation totals were extracted at 31 Austrian stations from a homogenized long-term climate dataset provided by the Austrian weather service. Three statistical techniques, namely cluster analysis (CLA), rotated empirical orthogonal functions (REOFs) and an unsupervised learning procedure of artificial neural networks (ANNs), were utilized to find homogeneous precipitation regions.The results of summer (June, July, August (JJA)) and winter (December, January, February (DJF)) seasons are presented. The resulting homogeneous precipitation regions depend on season, period and method in this order. Hence, differences introduced by using different methods are small compared with those inferred by investigating different episodes and especially with those related to the seasons.During winter, three homogeneous precipitation regions are found, independent from the period considered. These regions can be assigned to different airflows dominating Austria's climate and triggering precipitation events during the cold season. The situation during summer is more complicated. Thus, at least four clusters are necessary to record the circumstances, which are caused by spatially inhomogeneous convective events such as thunderstorms. Copyright (C) 2003 Royal Meteorological Society.