Norwegian Water Resources and Energy Direct. NVE

Oslo, Norway

Norwegian Water Resources and Energy Direct. NVE

Oslo, Norway

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Andreassen L.M.,Norwegian Water Resources and Energy Direct. NVE | Huss M.,University of Fribourg | Huss M.,ETH Zurich | Melvold K.,Norwegian Water Resources and Energy Direct. NVE | And 3 more authors.
Journal of Glaciology | Year: 2015

Glacier volume and ice thickness distribution are important variables for water resource management in Norway and the assessment of future glacier changes. We present a detailed assessment of thickness distribution and total glacier volume for mainland Norway based on data and modelling. Glacier outlines from a Landsat-derived inventory from 1999 to 2006 covering an area of 2692 ± 81 km2 were used as input. We compiled a rich set of ice thickness observations collected over the past 30 years. Altogether, interpolated ice thickness measurements were available for 870km2 (32%) of the current glacier area of Norway, with a total ice volume of 134 ± 23 km3. Results indicate that mean ice thickness is similar for all larger ice caps, and weakly correlates with their total area. Ice thickness data were used to calibrate a physically based distributed model for estimating the ice thickness of unmeasured glaciers. The results were also used to calibrate volume-area scaling relations. The calibrated total volume estimates for all Norwegian glaciers ranged from 257 to 300 km3.


Blanchet J.,University Grenoble Alpes | Blanchet J.,French National Center for Scientific Research | Touati J.,University Grenoble Alpes | Touati J.,French National Center for Scientific Research | And 3 more authors.
Natural Hazards and Earth System Sciences | Year: 2015

Simulation methods for design flood analyses require estimates of extreme precipitation for simulating maximum discharges. This article evaluates the multi-exponential weather pattern (MEWP) model, a compound model based on weather pattern classification, seasonal splitting and exponential distributions, for its suitability for use in Norway. The MEWP model is the probabilistic rainfall model used in the SCHADEX method for extreme flood estimation. Regional scores of evaluation are used in a split sample framework to compare the MEWP distribution with more general heavy-tailed distributions, in this case the Multi Generalized Pareto Weather Pattern (MGPWP) distribution. The analysis shows the clear benefit obtained from seasonal and weather pattern-based subsampling for extreme value estimation. The MEWP distribution is found to have an overall better performance as compared with the MGPWP, which tends to overfit the data and lacks robustness. Finally, we take advantage of the split sample framework to present evidence for an increase in extreme rainfall in the southwestern part of Norway during the period 1979-2009, relative to 1948-1978. © 2015 Author(s).

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