Representation of Horizontal Transport Processes in Snowmelt Modeling by Applying a Footprint Approach

The energy balance of an alpine snow cover significantly changes once the snow cover gets patchy. The local advection of warm air causes above-average snow ablation rates at the upwind edge of the snow patch. As lateral transport processes are typically not considered in models describing surface exchange, e.g., for hydrological or meteorological applications, small-scale variations in snow ablation rates are not resolved. The overall model error in the hydrological model Alpine3D is split into a contribution from the pure “leading edge effect” and a contribution from an increase in the mean air temperature due to a positive snow-albedo feedback mechanism. We found an overall model error for the entire ablation period of 4% for the almost flat alpine test site Gletschboden and 14% for the Wannengrat area, which is located in highly complex terrain including slopes of different aspects. Terrestrial laser scanning measurements at the Gletschboden test site were used to estimate the pure “leading edge effect” and reveal an increase in snow ablation rates of 25–30% at the upwind edge of a snow patch and a total of 4–6% on a catchment scale for two different ablation days with a snow cover fraction lower than 50%. The estimated increase of local snow ablation rates is then around 1–3% for an entire ablation period for the Gletschboden test site and approximately 4% for the Wannengrat test site. Our results show that the contribution of lateral heat advection is smaller than typical uncertainties in snow melt modeling due to uncertainties in boundary layer parameters but increases in regions with smaller snow patch sizes and long-lasting patchy snow covers in the ablation period. We introduce a new temperature footprint approach, which reproduces a 15% increase of snow ablation rates at the upwind edge of the snow patch, whereas observations indicate that this value is as large as 25%. This conceptual model approach could be used in hydrological models. In addition to improved snow ablation rates, the footprint model better represents snow mask maps and turbulent sensible heat fluxes from eddy-covariance measurements

Effects of Climate Forcing Uncertainty on High-Resolution Snow Modeling and Streamflow Prediction in a Mountainous Karst Watershed

Snow-dominated, karst watersheds present particular challenges to accurately modeling streamflow in response to differing climate conditions. This is due to the uneven distribution of snow within a basin, the varied melting rates due to terrain and climate, and the difficulty determining flow paths through karst conduits below ground. One possible solution to these challenges is to model snow at a fine scale, but climate variables are not available at these smaller spatial scales. The choices about which climate dataset to use, and how to downscale the data to a fine scale, will likely affect the accuracy of streamflow simulations. This comprises the primary goal of the thesis. For this project we simulated fine resolution snow processes using two climate datasets downscaled in two different ways and used the simulated snowmelt to feed a deep learning model that can learn patterns between the simulated snowmelt and observed streamflow to then simulate streamflow. The climate datasets differ significantly and resulted in highly different patterns of snow accumulation and melt. However, the deep learning model was able to learn the patterns with the different datasets and accurately generate streamflow for all climate datasets and downscaling methods

Stream temperature modeling in mountainous environments

Stream temperature is one of the key variables affecting the habitat suitability of numerous aquatic species. Over the past decades, research efforts on this topic have concentrated on low-land rivers of North-America, whereas mountainous environments have received much less attention - above all in Europe. The present thesis introduces two new models for stream temperature prediction in Alpine watersheds. Both are tested over selected catchments in Switzerland, a mountainous country which presents the advantage of possessing a dense network of automatic stream temperature measurement stations. The first model is specifically designed to provide stream temperature estimates in ungauged catchments, so as to compensate for the scarcity of temperature measurement sites in mountainous environments. Its design is based on a new statistical approach. As opposed to standard statistical models, which are common to many disciplines, the present one aims at incorporating some of the physics controlling stream temperature in its own structure. Its formulation is derived from an analytical solution to the equation describing the energy balance of an entire stream network. Some terms of this solution cannot be readily determined based on data available at the regional scale; they are approximated using standard statistical techniques. The resulting model is statistical in nature, but includes elements of thermodynamic principles. Its accuracy is shown to be similar to the one of a standard statistical model, its root mean square error being 1.3°C at the monthly time scale. In virtue of its physical basis, the model can be used to investigate into more detail the factors controlling stream temperature at the regional scale, as shown through a simple example. The second model is intended to provide deterministic stream temperature predictions, to be used for example in climate change studies. It builds upon an existing physically-based model, which has been entirely written anew in order to clarify its structure and ease future developments. Conceived as an add-on to the spatially distributed snow model Alpine3D, it simulates the flows of both water and energy within the catchment, based on a semi-distributed approach. Some components of the model can be represented using various alternatives; for example, three different techniques are available to simulate the temperature of subsurface runoff. This flexibility allows the model to be tuned to the specific needs of each user, but also permits a more thorough assessment of the simulation uncertainty by comparing the predictions of the various alternatives. Evaluation of the model in a high alpine watershed indicates that hourly mean discharge is reproduced with a Nash-Sutcliffe efficiency (NSE) of 0.82, and hourly mean stream temperature with a NSE of 0.78. Both models are shown to contribute to a better understanding of stream temperature dynamics in Alpine environments. Future work involves further research on the structure of the statistical model, as well as the application of the deterministic model within the framework of climate change studies

Small-scale spatio-temporal dynamics of snowmelt and its influence on runoff generation in a high Alpine catchment

Snow is one of the most complex materials occurring in nature. In clouds, it can be seen either as a crystal with various shapes or as a freshwater resource that will fall down to the Earth's surface. Once on the ground, it can be described as a thermodynamically unstable matrix or as a layered granular material with inherent structural weaknesses that ultimately result in avalanches. At high elevations or latitudes, snow slowly transforms into pure ice and supplies mass to glaciers and polar ice caps. Finally, it can also be seen as a relatively warm material close to its fusion point that will experience a phase change, melt, and infiltrate into the ground, ultimately feeding a river system. In this dissertation, we investigate several aspects of the latter definition by following the water particles from the hillslope to the river network. The playground of these experiments is a high Alpine catchment, the Dischma river basin in Switzerland. By combining a physically based and spatially distributed snow model with experimental data (snow lysimeter, snow depth, discharge), we examine, in the first two chapters, the influence of the spatial variability of snow and liquid water transport within the snowpack on runoff dynamics. The analysis, conducted from point scale to watershed scale, highlights the importance of having a realistic snowpack at peak accumulation to accurately model the hydrological response at the basin outlet. Additionally, we show how the energy fluxes driving the snow ablation change during the course of a year. In the third chapter, we put the modeling part aside and investigate experimentally the spatio-temporal variability of snow and its melt. Using an ultra-long range Terrestrial Laser Scanner (TLS), we measure the evolution of the snow cover at a very high spatial resolution on different hillslopes of the upper Dischma valley during the 2015 ablation season. Data analysis reveals that the ablation dynamics at the slope scale follow a bi-modal distribution of ablation rate with diverging behavior during the course of the melt season. The emergence of this bimodality is explained on the basis of associated limiting factors: mass and energy. To conclude this dissertation, we move away from the cryospheric world but still study the energy exchanges between the Earth's surface and the atmosphere. Towards this goal, a low-cost sensible heat flux sensor was developed. The instrument was tested and validated against a state-of-the-art reference. The sensor shows promising results by giving good estimates over different surface types (grass, gravel). In the future, it can be used to measure the spatial variability of sensible heat flux within a Wireless Sensor Network

Modelling snowpacks in topographically complex terrain during the winter accumulation season, Columbia River Basin, British Columbia, Canada

This dissertation investigates winter accumulation and snow cover change in the Columbia Mountains of British Columbia. In chapter 1, I start with an introduction that describes the study area, and then outlines the objectives and structure of this dissertation. In chapter 2, I examine the performance of two snow evolution models with different complexities (SnowModel and Alpine3D) at simulating winter glacier mass balance on four individual glaciers using two different forcing datasets, the Weather Research and Forecasting model (WRF) outputs and the North American Land Data Assimilation System (NLDAS). My results show that both models can simulate winter accumulation with less than 20% bias for each glacier, with SnowModel forced by WRF yielding the least overall bias. In chapter 3, I study the effect of wind on snow patterns to determine the impact of snow redistribution by wind in terms of erosion, deposition, and sublimation on winter mass balance estimation. The results demonstrate that modelled redistribution of snow by wind produces a visually realistic pattern of snow accumulation when compared to observed snow depth, but its impact on the glacier-averaged winter mass balance estimation is negligible (< 4%). The results also suggest that drifting snow sublimation is highly time and space dependent. Considering the model performance from previous chapters, in chapter 4, I analyzed the future snow cover change over the upper Columbia Basin under the Representative Concentration Pathway (RCP8.5) climate scenario by the end of the 21st century. I used downscaled climate projections of the Community Earth System Model (CESM1) by WRF, along with statistically downscaled data provided from the Pacific Climate Impacts Consortium (PCIC) to force SnowModel. The simulated snow maps represent a higher dynamically downscaled mean snow water equivalent (SWE) reduction – reaching up to 30% by the end of the century - than the statistically downscaled SWE reduction. While SWE reduction of more than 60% happens at lower and mid-elevations, altitudes higher than 2000 m are less vulnerable to climate change. I conclude this dissertation (Chapter 5) with a summary of the progress gained, study limitations, suggestions for future research, and research implications

Multi-Scale Modelling of Cold Regions Hydrology

Numerical computer simulations are increasingly important tools required to address both research and operational water resource issues related to the hydrological cycle. Cold region hydrological models have requirements to calculate phase change in water via consideration of the energy balance which has high spatial variability. This motivates the inclusion of explicit spatial heterogeneity and field-testable process representations in such models. However, standard techniques for spatial representation such as raster discretization can lead to prohibitively large computational costs and increased uncertainty due to increased degrees of freedom. As well, semi-distributed approaches may not sufficiently represent all the spatial variability. Further, there is uncertainty regarding which process conceptualizations are used and the degree of required complexity, motivating modelling approaches that allow testing multiple working hypotheses. This thesis considers two themes. In the first, the development of improved modelling techniques to efficiently include spatial heterogeneity, investigate warranted model complexity, and appropriate process representation in cold region models is addressed. In the second, the issues of non-linear process cascades, emergence, and compensatory behaviours in cold regions hydrological process representations is addressed. To address these themes, a new modelling framework, the Canadian Hydrological Model (CHM), is presented. Key design goals for CHM include the ability to: capture spatial heterogeneity in an efficient manner, include multiple process representations, be able to change, remove, and decouple hydrological process algorithms, work both at point and spatially distributed scales, reduce computational overhead to facilitate uncertainty analysis, scale over multiple spatial extents, and utilize a variety of boundary and initial conditions. To enable multi-scale modelling in CHM, a novel multi-objective unstructured mesh generation software *mesher* is presented. Mesher represents the landscape using a multi-scale, variable resolution surface mesh. It was found that this explicitly captured the spatial heterogeneity important for emergent behaviours and cold regions processes, and reduced the total number of computational elements by 50\% to 90\% from that of a uniform mesh. Four energy balance snowpack models of varying complexity and degree of coupling of the energy and mass budget were used to simulate SWE in a forest clearing in the Canadian Rocky Mountains. It was found that 1) a compensatory response was present in the fully coupled models’ energy and mass balance that reduced their sensitivity to errors in meteorology and albedo and 2) the weakly coupled models produced less accurate simulations and were more sensitive to errors in forcing meteorology and albedo. The results suggest that the inclusion of a fully coupled mass and energy budget improves prediction of snow accumulation and ablation, but there was little advantage by introducing a multi-layered snowpack scheme. This helps define warranted complexity model decisions for this region. Lastly, a 3-D advection-diffusion blowing snow transport and sublimation model using a finite volume method discretization via a variable resolution unstructured mesh was developed. This found that the blowing snow calculation was able to represent the spatial redistribution of SWE over a sub-arctic mountain basin when compared to detailed snow surveys and the use of the unstructured mesh provided a 62\% reduction in computational elements. Without the inclusion of blowing snow, unrealistic homogeneous snow covers were simulated which would lead to incorrect melt rates and runoff contributions. This thesis shows that there is a need to: use fully coupled energy and mass balance models in mountains terrain, capture snow-drift resolving scales in next-generation hydrological models, employ variable resolution unstructured meshes as a way to reduce computational time, and consider cascading process interactions

The evolution of mountain permafrost in the context of climate change:: towards a comprehensive analysis of permafrost monitoring data from the Swiss Alps

In the Swiss Alps, permafrost occurs discontinuously and commonly has a temperature close to 0 °C. A reduction of Alpine permafrost area and volume is expected in the course of atmospheric warming, but to date, limited evidence is available for Alpine permafrost degradation. Permafrost warming or thaw is accompanied by structural changes in the subsurface, which endanger infrastructure by increasing kinematic activity or slope instability. Changes in the permafrost impact sediment transport to the valley bottom as well as gravitational natural hazards such as rock falls, landslides or debris flows. For these reasons, the quantitative analysis of past and potential future changes in the Alpine permafrost is of great interest and importance. The objective of this PhD project was to investigate observational data from the Swiss Permafrost Monitoring Network PERMOS using an interdisciplinary approach and to develop new methods for the homogenisation and quantitative analysis of long-term monitoring data. The main focus was on assessing changes in the energy fluxes at the ground surface as a function of the snow cover, as well as on evaluating permafrost response to different meteorological conditions and events. This PhD project was part of the research project The Evolution of Mountain Permafrost in Switzerland (TEMPS, 2011-2015), which used combined observational and model-based approaches and aimed at improving the consistency and completeness of permafrost monitoring data. One achievement of this PhD thesis consists of the development of data processing algorithms for filling data gaps in temperature time series and the quantification of resulting uncertainties. Moreover, algorithms for the approximation of the thermal insulation effect of the snow cover based on ground surface temperature (GST) data were developed. This was of particular importance because snow information is usually not available for the points of interest. Furthermore, possibilities for estimating temperature variations at depth based on GST data were evaluated. The information obtained about the propagation of the thermal signal into the ground led to new insights into the temperature dependency of rock glacier creep, which were supported by observational data. Data from more than 20 study sites were made comparable in order to quantify differences at the site- and the regional scale. The GST variability proved to be almost as high at the site scale as at the regional scale. This was explained by heterogeneous topo-climatic conditions as well as by the variable snow cover in the geographic context of the Swiss Alps. The roughness of the terrain played a key role, since it modifies the thermal insulation effect of the snow. Coarse-blocky terrains require more snow to be thermally insulated from the atmosphere and freeze more rapidly compared to smooth ground surfaces. The seasonal GST pattern showed that differences among sites and years were large in early winter, whereas GST were less variable in the summer season. Many locations showed similar snow conditions and therefore similar seasonal and inter-annual GST variations, which could not be explained by variations in air temperature. Although no overall increase in GST was found, the data indicate persistent warm conditions at the ground surface since 2009. Ground temperatures (GT) experienced an overall warming trend down to several tens of m depth over the past 10-25 years. This warming was most distinct in relatively cold permafrost with temperatures below -1 °C. Since the GT at depths between 10-30 m influences the kinematic activity of rock glaciers, the surface deformation rates of the majority of the observed rock glaciers reached maxima between 2013 and 2015. Surface deformation rates quantified by photogrammetry for selected rock glaciers showed an increase in the order of 200-600 % compared to 1990-1995 and 400-800 % compared to 1960-1980. Long-lasting warm conditions at the ground surface were identified to be the cause of the rise in ground temperature and the increased kinematic activity of rock glaciers. Compared with air temperature, where direct effect on the ground is limited to the snow-free period, the snow cover and its onset in early winter had a much greater influence on the heat and energy exchange at the ground surface. After one or two snow-poor winters, permafrost was able to regenerate thermally. Strong ground cooling occurred between 2005 and 2007, which caused a temporary trend reversal in the warming ground temperatures, limiting the effect of the particularly warm air temperatures between June 2006 and May 2007. Since Alpine permafrost is not in equilibrium with the current climatic conditions, recovery periods of efficient winter cooling will probably play a key role for its future evolution and preservation. Overall, the results of this PhD project contribute to an improved process understanding and put observed ground thermal and kinematic phenomena in the context of past and potential future changes of permafrost in the Swiss Alps

Using wind fields from a high resolution atmospheric model for simulating snow dynamics in mountainous terrain

It is widely known that the snow cover has a major influence on the hydrology of Alpine watersheds. Snow acts as temporal storage for precipitation during the winter season. The stored water is later released as snowmelt and represents an important component of water supply for the downstream population of large mountain-foreland river systems worldwide. Modelling the amount and position of the snow water stored in the headwater catchments helps to quantify the available water resources and to estimate the timing of their release. The presented work investigates wind induced snow transport processes which are considered to be crucial for the snow distribution in Alpine catchments. In contradiction to the importance that is attributed to this process, there are only a few studies available which have quantified the transport intensities on the catchment scale. This can be attributed to the fact that the even today not much is known about the spatial characteristics of wind fields which are the driving force for snow transport processes. The presented thesis tries to overcome this lack of information by using physically based wind fields predicted by an atmospheric model (PSU_NCAR MM5 model) for the modelling of the snow cover (simulated by SnowModel). All of the used models are described in great detail in the literature, validated in many different regions, and can be seen as applicable with regard to the goal of this work. As snow transport processes are particularly important on a comparatively small scale a numerical inclusion of the responsible processes into regional models is inadequate. Hence, while this study itself mainly uses smaller scale physically based models, a parameterisation scheme is presented at the end of this thesis that is able to incorporate its main findings into larger scale models. All of the presented work was carried out at the Berchtesgaden National Park. The site is highly appropriate because of the extremely rough terrain and the good accessibility. Furthermore, the instrumentation of the area is comparatively good and the data sources (GIS, field campaign data) are excellent. The thesis deals with the winter seasons (August - July) 2003/2004 and 2004/2005. For this period, data of 5 meteorological stations, 1 field campaign and two Landsat ETM+ images were available. As mentioned before, physically based wind fields were used as input for the snow transport modelling. An operational coupling between atmospheric model and snow transport model was not pursued because of the high computational costs of the atmospheric model. Thus, a library of representative wind fields was produced in advance and linked to the snow transport model via operational German weather service Lokalmodell results. This becomes possible because of the comparability of a MM5 model layer with one of the Lokalmodell model layers. To link the wind field library to the snow model all of the predicted MM5 wind fields were characterised by information available from the Lokalmodell. This enable an easy detection of the MM5 wind field which is closest to the real climatic wind conditions at any Lokalmodell time step (1 hour). The produced MM5 wind fields have a spatial resolution of 200 meters. As an initial check if the snow cover simulation of SnowModel in association with the wind field library delivers adequate results with respect to the snow distribution, model runs were first carried out at the 200m scale. An analysis of the results showed that the coupled routine delivers acceptable results. It could be seen that with the use of the MM5 wind fields, the snow cover becomes more anisotropic and that transport processes over crests as well as sublimation processes are predicted to become more intensive. Nevertheless, a higher resolution was needed to quatify the effects and to validate the results. In a subsequent step the MM5 wind fields were downscaled to a 30m resolution. The downscaling procedure lead to a better agreement between modelled and measured wind speeds. The resulting 30m wind fields were used for high resolution model runs which were validated on the basis of the field campaign and remotely sensed data. A comparison with model runs using wind fields interpolated from station data showed that the runs performed with the MM5 wind fields deliver more consistent and comprehensible results. Subsequently, the validity of the model is discussed on the basis of selected results. High resolution model results indicated that snow transport processes are effective at high elevations but virtually negligible for regions below of 1800m a.s.l.. Furthermore, it could be seen that the correct estimation of snow transport from the surrounding areas to glaciers becomes possible by using the MM5 wind fields. Very high modelled sublimation rates at the mountains crests are discusses with respect to their importance on the water balance. Furthermore, the influence of preferential snow deposition and snow slides which were not numerically predicted in this work were discusses. Additionally, the applicability of atmospheric model results as input for land-surface models could be confirmed. In a final step a model scheme is presented that would make the generated information available for regional scale models. This model parameterization scheme which is based on the modelled 30m snow water equivalent distribution within the test area was used for this area. The scheme allows for a quick and simple description of the subscale snow heterogeneity in regional scale models. This can lead to considerable model improvements with respect to the description of the energy and moisture fluxes to and from the surface. An accurate description of these fluxes is essential for an accurate simulation of the melt period and, therefore, for an acceptable calculation of the runoff generation in larger scale models.Der Einfluss der Schneedecke auf die Hydrologie Alpiner Einzugsgebiete ist weithin bekannt und in der Literatur eindrucksvoll beschrieben. Saisonale Schneedecken fungieren als temporäre Speicher für den Niederschlag. Das gebundene Wasser wird den Fließgewässern verzögert als Schmelzwasser zugeführt und bestimmt damit zumindest zeitweise deren Abflusshöhe und –menge. Die Modellierung von mengenmäßigem Inhalt und räumlicher Ausdehnung des Schneespeichers ist hilfreich für die Quantifizierung der vorhandenen Wasserressourcen und für die Bestimmung des Zeitpunkts, zu dem die gespeicherten Wassermengen verfügbar werden. Die Intensität der Schneeschmelze hängt dabei, neben der absoluten räumlichen Lage, auch von der räumlichen Heterogenität der Schneedecke ab. In der vorliegenden Arbeit wurde der Einfluss von wind-induzierten Schneetransportprozessen auf die Heterogenität der Alpinen Schneedecke untersucht. Als Testgebiet wurde der Nationalpark Berchtesgaden ausgewählt. Dieses Testgebiet kann aufgrund seiner hohen Reliefenergie als ideal für die durchgeführten Untersuchungen gelten, da Schneetransportprozesse hier besonders effektiv sind. Die Instrumentierung des Parks ist im Hinblick auf die verfügbaren meteorologischen Stationen außerordentlich gut. Darüber hinaus liegen flächendeckende Informationen über die Geländehöhe und die Vegetation in Form eines hoch aufgelösten (10m) Geographischen Informationssystems (GIS) vor. Für den Untersuchungszeitraum (Wintersaison 2003/2004 und 2004/2005, jeweils gerechnet von August bis Juli) liegen Daten von 5 meteorologischen Stationen, einer Feldkampagne und zwei Landsat ETM+ Bildern vor. Windinduzierter Schneetransport wird in der Literatur häufig als der bestimmende Prozess für die Heterogenität der Schneedecken in gebirgigen Gebieten angesehen. In starkem Kontrast zu der diesem Prozess zugestandenen Bedeutung, steht die Anzahl der Veröffentlichungen, die die numerische Untersuchung der Effektivität desselben zum Inhalt haben. Das liegt vor allem in der Tatsache begründet, dass die Berechnung von qualitativ hochwertigen Windfeldern in gebirgigem Terrain bis heute nahezu unmöglich ist. Diese allerdings sind von zentraler Bedeutung, um quantitative Aussagen über die Richtung der Verlagerung von Schneemengen zu treffen, und um die entsprechenden Erosions- wie Akkumulationsgebiete zu lokalisieren. Für eine möglichst genaue Charakterisierung der Windfelder im Untersuchungsgebiet wurden in der vorliegenden Arbeit physikalisch basierte Windfelder mit Hilfe des PSU-NCAR MM5 Atmosphärenmodells berechnet. Diese wurden im Anschluss in dem etablierten Schneemodell SnowModel als Antrieb für die Schneetransportroutine (SnowTran-3D) verwendet. Da eine direkte Kopplung von Atmosphärenmodell und Schneemodell unter den heute gegebenen technischen Voraussetzungen zu einer unrealistisch hohen Modell-Laufzeit geführt hätte, wurde eine alternative Methode gewählt: die Windfelder wurden separat berechnet und eine Bibliothek repräsentativer Windfelder für das Untersuchungsgebiet erzeugt. Die zeitliche Synchronisation zwischen Windfeldbibliothek und Schneemodell wurde über das operationelle, mesoskalige Wettervorhersage-Modell des Deutschen Wetterdienstes (DWD), das Lokalmodell hergestellt. Dies wurde aufgrund der Tatsache möglich, dass bestimmte Modellausgaben von Lokalmodell und MM5 im 700 hPa Niveau vergleichbar sind. Um das richtige Windfeld für einen Schneemodellzeitschritt aus der zuvor erzeugten MM5 Windfeldbibliothek auszuwählen, wurden mittlere Windvektoren der MM5 Windfelder mit mittleren Vektoren der entsprechenden Lokalmodell Windfelder verglichen. So wurde es möglich, zu jedem Modellzeitschritt des Lokalmodells (eine Stunde) ein MM5 Windfeld zu selektieren und im Schneemodel anzuwenden. Die generierten MM5 Windfelder haben eine räumliche Auflösung von 200m. Für eine prinzipielle Überprüfung der Funktionalität des Schneemodels in Verbindung mit einer MM5 Windfeldbibliothek, wurden erste Schneemodelläufe auf der 200m Skala initialisiert. Die zugehörigen Ergebnisse waren plausibel und bestätigten die Anwendbarkeit der Kombination von Schneemodell und MM5 Windfeldern. Die Schneewasseräquivalentverteilung im Gebiet wurde durch die Applikation der MM5 Windfelder weniger abhängig von der allgemeinen niederschlagsbedingten Zunahme des Schneewasseräquivalents mit der Höhe. Ein Zusammenhang mit der Exposition des Geländes konnte nun auch aufgezeigt werden. Zudem konnten Transportprozesse über die Bergkämme hinweg simuliert werden. Eine Intensitätszunahme aller Transportterme unter Anwendung der MM5 Windfelder im Vergleich zu interpolierten Windfeldern konnte ebenfalls festgestellt werden. Die Ergebnisse auf der 200m Skala machten deutlich, dass für eine ausreichende und tiefgreifende Beschreibung und Validierung von Schneetransportprozessen ein feineres Modellgrid erforderlich ist. Als Konsequenz wurden die MM5 Windfelder auf eine Auflösung von 30m skaliert. Durch die Skalierungsprozedur konnte eine bessere Korrelation zwischen Stationsmessungen und MM5 Ergebnissen erreicht werden. Die resultierenden 30m Windfelder wurden für hochauflösende 30m Schneemodellläufe genutzt, die auf der Basis von Ergebnissen der durchgeführten Feldkampagnen und Fernerkundungsdaten validiert werden konnten. Auch hier konnte nachgewiesen werden, dass die unter Verwendung der MM5 Windfeldbibiliothek generierten Resultate von höherer Validität waren, als die Ergebnisse die mit Hilfe von interpolierten Windfeldern erzeugt wurden. Im Weiteren wurden die Modellergebnisse anhand ausgewählter Resultate diskutiert. Es konnte gezeigt werden, dass die Effektivität von Transportprozessen unter 1800m ü. NN. zu vernachlässigen ist und ab 2200m ü. NN. stark zunimmt. Zudem konnte unter Nutzung der MM5 Windfelder der Transport von Schnee auf vergletscherte Flächen modelliert werden. Hohe modellierte Sublimationsraten an den Gipfeln wurden diskutiert und ihre Wichtigkeit im Bezug auf die alpine Wasserbilanz aufgezeigt. Im Ganzen konnte nachgewiesen werden, dass die Einbindung von Ergebnisdaten von Atmosphärenmodellen zu einer deutlichen Verbesserung der Beschreibung der Prozesse an der Erdoberfläche führt. In einem letzten Schritt wurden die Ergebnisse der hochaufgelösten Schneemodellläufe genutzt, um die Schneedeckenheterogenität im Gebiet zu parametrisieren. Ziel war es, eine Möglichkeit aufzuzeigen, die generierte kleinskalige Information auch für regionale Landoberflächenmodelle nutzbar zu machen. Infolgedessen wurde eine einfach zu implementierende Routine für regionale Modelle vorgestellt, die die subskalige Beschreibung der Schneedeckenheterogenität erlaubt. Dies kann in entsprechendem Relief zu einer Verbesserung der Energie- und Feuchteflüsse in regionalen Modellen und damit zu einer akkurateren Beschreibung der Ablationsperiode der Schneedecke und der Abflussgenerierung führen