Center for Climate Change Adaptation

Innsbruck, Austria

Center for Climate Change Adaptation

Innsbruck, Austria
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Hastik R.,University of Innsbruck | Basso S.,Eawag - Swiss Federal Institute of Aquatic Science and Technology | Geitner C.,University of Innsbruck | Haida C.,Center for Climate Change Adaptation | And 5 more authors.
Renewable and Sustainable Energy Reviews | Year: 2015

Summary Expansion of renewable energies (=RE) is a key measure in climate change mitigation. For this expansion mountainous areas are regarded as specifically suitable because of their high-energy potential. However, mountains also are biodiversity hot-spots and provide scenic landscapes and therefore offer high natural and cultural value. Preserving this natural and cultural value whilst intensifying RE, is expected to increase land use conflicts. This is of great concern in particular for vulnerable areas such as the Alps. Reconciling RE expansion with the preservation of natural and cultural values and thus minimizing environmental impacts represents one of the most important challenges now. For this a systematic assessment of the wide range of impacts is needed. This literature review scrutinizes RE resources which are relevant in the Alpine region and their effects on the environment by applying the Ecosystem Service approach. Thereby, we identified possible environmental constraints when exploiting Alpine RE potentials and generated recommendations for future strategies on expanding RE. The outcomes highlight the strong need for interdisciplinary research on RE and environmental conflicts. Interdisciplinary approaches such as the concept of Ecosystem Services can help to cover the wide range of aspects associated with these particular human-environment interrelations. © 2015 Elsevier Ltd. All rights reserved.

Hanzer F.,Center for Climate Change Adaptation | Hanzer F.,University of Innsbruck | Helfricht K.,Austrian Academy of Sciences | Marke T.,University of Innsbruck | Strasser U.,University of Innsbruck
Cryosphere | Year: 2016

In this study, the fully distributed, physically based hydroclimatological model AMUNDSEN is set up for catchments in the highly glacierized Ötztal Alps (Austria, 558km2 in total). The model is applied for the period 1997-2013, using a spatial resolution of 50m and a temporal resolution of 1h. A novel parameterization for lateral snow redistribution based on topographic openness is presented to account for the highly heterogeneous snow accumulation patterns in the complex topography of the study region. Multilevel spatiotemporal validation is introduced as a systematic, independent, complete, and redundant validation procedure based on the observation scale of temporal and spatial support, spacing, and extent. This new approach is demonstrated using a comprehensive set of eight independent validation sources: (i) mean areal precipitation over the period 1997-2006 derived by conserving mass in the closure of the water balance, (ii) time series of snow depth recordings at the plot scale, (iii-iv) multitemporal snow extent maps derived from Landsat and MODIS satellite data products, (v) the snow accumulation distribution for the winter season 2010/2011 derived from airborne laser scanning data, (vi) specific surface mass balances for three glaciers in the study area, (vii) spatially distributed glacier surface elevation changes for the entire area over the period 1997-2006, and (viii) runoff recordings for several subcatchments. The results indicate a high overall model skill and especially demonstrate the benefit of the new validation approach. The method can serve as guideline for systematically validating the coupled components in integrated snow-hydrological and glacio-hydrological models. © 2016 Author(s).

Schober J.,Center for Climate Change Adaptation | Schober J.,University of Innsbruck | Schneider K.,Center for Climate Change Adaptation | Helfricht K.,Center for Climate Change Adaptation | And 5 more authors.
Journal of Hydrology | Year: 2014

In the present paper multi-temporal Lidar (Light detection and ranging) data and Landsat images are used to assess the spatial variability of snow at the end of the accumulation season (April-May) in a glacierized catchment (167km2) in Tyrol, Austria. Snow cover characteristics in the Tyrolean Alps have been analysed using regular snow measurements and snow course data. Results are used for the conversion of basin-wide Lidar snow depth into snow water equivalent (SWE). When considering different possible error sources, uncertainties of the mean basin-wide SWE obtained from Lidar are between 12% and 16%. Available distributions of SWE and snow covered area (SCA) in the catchment are used for the calibration and validation of the fully distributed hydrological model SES. The study focuses especially on the simulation of snow accumulation and the corresponding variability of snow. Observed accumulation patterns are related to the topography (elevation, slope and curvature), and according parameter settings of the hydrological model are derived by means of Monte Carlo simulations. The majority of the model runs simulates SCA for various datasets with an accuracy of 85-95%. The paper demonstrates that using SWE data is superior to SCA for constraining model parameter ranges. Results at the watershed scale are in agreement with respect to the total water volume of the snow cover with deviations lower than 5% between SWE from Lidar or from the hydrological model. © 2014 Elsevier B.V.

Helfricht K.,Austrian Academy of Sciences | Helfricht K.,Center for Climate Change Adaptation | Lehning M.,Institute for Snow and Avalanche Research SLF | Lehning M.,Ecole Polytechnique Federale de Lausanne | And 2 more authors.
Geografiska Annaler, Series A: Physical Geography | Year: 2015

Snow deposition and redistribution are major drivers of snow cover dynamics in mountainous terrain and contribute to the mass balance of alpine glaciers. The quantitative understanding of inhomogeneous snow distribution in mountains has recently benefited from advances in measuring technologies, such as airborne laser scanning (ALS). This contribution further advances the quantitative understanding of snow distribution by analysing the areas of maximum surface elevation changes in a mountain catchment with large and small glaciers. Using multi-annual ALS observations, we found extreme surface elevation changes on rather thin borders along the glacier margins. While snow depth distribution patterns in less extreme terrain have presented high inter-annual persistence, there is little persistence of those extreme glacier accumulations between winters. We therefore interpret the lack of persistence as the result of a predominance of gravity-driven redistribution, which has an inherently higher random component because it does not occur with all conditions in all winters. In highly crevassed zones, the lidar-derived surface elevation changes are caused by a complex interaction of ice flux divergence, the propagation of crevasses and snow accumulation. In general, the relative contribution of gravitational mass transport to glacier snow cover volume was found to decrease for glaciers larger than 5 km2 in the investigated region. We therefore suggest that extreme accumulations caused by gravitational snow transport play a significant role in the glacier mass balance of small to medium-size glaciers and that they may be successfully parameterized by simple mass redistribution algorithms, which have been presented in the literature. © 2015 Swedish Society for Anthropology and Geography.

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