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Due to the environmental and socio-economic importance of mountainous regions, it is crucial to understand causes and consequences of climatic changes in those sensitive landscapes. Daily resolution alpine climate data from Switzerland covering an elevation range of over 3,000m between 1981 and 2017 have been analysed using highly resolved trends in order to gain a better understanding of features, forcings and feedbacks related to temperature changes in mountainous regions. Particular focus is put on processes related to changes in weather types, incoming solar radiation, cloud cover, air humidity, snow/ice and elevation dependency of temperature trends. Temperature trends in Switzerland differ depending on the time of the year, day and elevation. Warming is strongest during spring and early summer with enhanced warming of daytime maximum temperatures. Elevation-based differences in temperature trends occur during autumn and winter with stronger warming at lower elevations. We attribute this elevation-dependent temperature signal mainly to elevation-based differences in trends of incoming solar radiation and elevation-sensitive responses to changes in frequencies of weather types. In general, effects of varying frequencies of weather types overlap with trends caused by transmission changes in short- and long-wave radiation. Temperature signals arising from snow/ice albedo feedback mechanisms are probably small and might be hidden by other effects.
Elevation-dependent compensation effects in snowmelt in the Rhine River Basin upstream gauge Basel
(2021)
In snow-dominated river basins, floods often occur during early summer, when snowmelt-induced runoff superimposes with rainfall-induced runoff. An earlier onset of seasonal snowmelt as a consequence of a warming climate is often expected to shift snowmelt contribution to river runoff and potential flooding to an earlier date. Against this background, we assess the impact of rising temperatures on seasonal snowpacks and quantify changes in timing, magnitude and elevation of snowmelt. We analyse in situ snow measurements, conduct snow simulations and examine changes in river runoff at key gauging stations. With regard to snowmelt, we detect a threefold effect of rising temperatures: snowmelt becomes weaker, occurs earlier and forms at higher elevations. Due to the wide range of elevations in the catchment, snowmelt does not occur simultaneously at all elevations. Results indicate that elevation bands melt together in blocks. We hypothesise that in a warmer world with similar sequences of weather conditions, snowmelt is moved upward to higher elevation. The movement upward the elevation range makes snowmelt in individual elevation bands occur earlier, although the timing of the snowmelt-induced runoff stays the same. Meltwater from higher elevations, at least partly, replaces meltwater from elevations below.
The presence of impermeable surfaces in urban areas hinders natural drainage and directs the surface runoff to storm drainage systems with finite capacity, which makes these areas prone to pluvial flooding. The occurrence of pluvial flooding depends on the existence of minimal areas for surface runoff generation and concentration. Detailed hydrologic and hydrodynamic simulations are computationally expensive and require intensive resources. This study compared and evaluated the performance of two simplified methods to identify urban pluvial flood-prone areas, namely the fill–spill–merge (FSM) method and the topographic wetness index (TWI) method and used the TELEMAC-2D hydrodynamic numerical model for benchmarking and validation. The FSM method uses common GIS operations to identify flood-prone depressions from a high-resolution digital elevation model (DEM). The TWI method employs the maximum likelihood method (MLE) to probabilistically calibrate a TWI threshold (τ) based on the inundation maps from a 2D hydrodynamic model for a given spatial window (W) within the urban area. We found that the FSM method clearly outperforms the TWI method both conceptually and effectively in terms of model performance.
The presence of impermeable surfaces in urban areas hinders natural drainage and directs the surface runoff to storm drainage systems with finite capacity, which makes these areas prone to pluvial flooding. The occurrence of pluvial flooding depends on the existence of minimal areas for surface runoff generation and concentration. Detailed hydrologic and hydrodynamic simulations are computationally expensive and require intensive resources. This study compared and evaluated the performance of two simplified methods to identify urban pluvial flood-prone areas, namely the fill–spill–merge (FSM) method and the topographic wetness index (TWI) method and used the TELEMAC-2D hydrodynamic numerical model for benchmarking and validation. The FSM method uses common GIS operations to identify flood-prone depressions from a high-resolution digital elevation model (DEM). The TWI method employs the maximum likelihood method (MLE) to probabilistically calibrate a TWI threshold (τ) based on the inundation maps from a 2D hydrodynamic model for a given spatial window (W) within the urban area. We found that the FSM method clearly outperforms the TWI method both conceptually and effectively in terms of model performance.
As a consequence of increasing winter rainfall totals and intensities over the second half of the 20th century, signs of increased flooding probability in many areas of the Rhine and Meuse basins have been documented. These changes affecting rainfall characteristics are most evidently due to an increase in westerly atmospheric circulation types. Land use changes, particularly urbanization, can have significant local effects in small basins (headwaters) with respect to flooding, especially during heavy local rainstorms, but no evidence exists that land use change has had significant effects on peak flows in the rivers Rhine and Meuse. For the 21st century, most global circulation models suggest higher winter rainfall totals. Most hydrological simulations of the Rhine-Meuse river basins suggest an increased flooding probability, with a progressive shift of the Rhine from a 'rain-fed/meltwater' river into a mainly 'rain-fed' river. A very limited effect of changes in land use on the discharge regime seems to exist for the main branches of the Meuse and Rhine rivers. For mesoscale basins, future changes in peak flows depend on the changes in the variability of extreme precipitations in combination with land use changes. Copyright (C) 2004 John Wiley Sons, Ltd
Study region: Tisza and Prut catchments, originating on the slopes of the Carpathian mountains. Study focus: The study reported here investigates (i) climate change impacts on flood risk in the region, and (ii) uncertainty related to hydrological modelling, downscaling techniques and climate projections. The climate projections used in the study were derived from five GCMs, downscaled either dynamically with RCMs or with the statistical downscaling model XDS. The resulting climate change scenarios were applied to drive the eco-hydrological model SWIM, which was calibrated and validated for the catchments in advance using observed climate and hydrological data. The changes in the 30-year flood hazards and 98 and 95 percentiles of discharge were evaluated for the far future period (2071-2100) in comparison with the reference period (1981-2010). New hydrological insights for the region: The majority of model outputs under RCP 4.5 show a small to strong increase of the 30-year flood level in the Tisza ranging from 4.5% to 62%, and moderate increase in the Prut ranging from 11% to 22%. The impact results under RCP 8.5 are more uncertain with changes in both directions due to high uncertainties in GCM-RCM climate projections, downscaling methods and the low density of available climate stations.