Physically based modelling of climate change impact on snow cover dynamics in Alpine Regions using a stochastic weather generator (original) (raw)
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This paper presents an attempt at deterministically modeling spatially distributed snowmelt in an alpine cfitchment. The basin is 9.4 km 2 in area and elevations range from 1900 to 3050 m above sea level. The model makes use of digital terrain data with 25 m grid spacing. Energy balance components are calculated for ea6h grid element taking topographic. variations of solar radiation into account. For each grid element albedo and snow surface temperatures are simulated. Model performance is evaluated on the basis of snow cover depletion patterns as derived from weekly air photographs. The use of spatially distributed data allows for addressing individual model components. Results indicate that the basic model assumptions are realistic. Model inadequacies are shown to arise from processes not included in the model such as avalanching and long wave emission fxom surrounding terrain as well as inaccurate model parameters. Numerous papers have been published on distributed model components su:Ch as radiation [e.g., Dozier, 1980; Olyphant, 1986] and some papers on the distribution of water equivalent [Woo et al? 1983a; Elder et al., 1989]. However, no more than a few studies deal with spatially distributed sn0wmelt models. Charbonneau et al. [1981] presented a model which accounted for variations in shortwave radiation and snow surface temperature at slopes of different aspect.
A distributed grid-based model is used (1) to analyze the importance of selected model parameters, (2) to simulate spatial distributions of snow cover properties in a small basin and (3) for a comparison with less sophisticated models as typically used in operational applications. Results indicate that variations of water equivalent with slope and local relief are of utmost importance for realistic distributed simulations but more moderately influence mean basin melt. Snow cover variables of which spatial distributions are simulated include the thermal and hydraulic state of the pack and hourly melt water release. All variables exhibit substantial variations in space and time. They are primarily controlled by topography and the delay of melt water in deep packs. The grid model is compared with a snow band model and a parametric model. The latter estimates the snowpack's areal extent from water equivalent. Simulated snow-covered areas suggest the grid model to be the most realistic. Differences in terms of mean basin melt derive from different assumptions associated with model structure.
Journal of Hydrology, 2015
Snow is an important hydrological reservoir within the water cycle, particularly when the watershed includes a mountainous area. Modellers often overlook water stocked in snow pack and its influence on water distribution, especially when only some portions of the watershed is snow dominated. Snow is usually considered to improve hydrological modelling statistics, but without any regard for the realism of its representation or its influence on the hydrological cycle. This is all the more true when semidistributed models are used, often considered inadequate for spatially representing such phenomena. On the other hand, semi-distributed models are being increasingly used to realise water budget assessment at a regional scale and such studies should not be realised without a good representation of the snow pack. Lack of field measurements is also a frequent justification for avoiding validating simulated snow packs. In this study, remote sensing data provided by MODIS is combined with in situ data, enabling the validation of the snow pack simulated by the Soil and Water Assessment Tool (SWAT), a semidistributed, physically-based model, implemented over a partly snow-dominated watershed. Snow simulation was performed without complex algorithms or calibration procedures, using the elevation bands option included in the model and related snow parameters. Representation of snow cover and hydrological simulation were achieved by a standard automatic calibration of the model, over the 2000-2010 period, performed by SWAT-Cup/SUFI2, using six hydrological gauging stations along the fluvial continuum downstream of the snow-dominated area. Results highlight three important points: (i) Setup of elevation bands over mountainous headwater improved hydrological simulation performance, even well downstream of the snow-dominated area. (ii) SWAT produced a good spatial and temporal representation of the snow cover, using MODIS data, despite a slight overestimation at the end of the snow season on the highest elevation bands. A comparison of the model estimate of snowpack water content with in situ data revealed an underestimation in water content in the lower part of the watershed and a slight overestimation in its upper part. Those errors are linked and originate from difficulties of the model to incorporate very local spatial and temporal variations of the precipitation lapse rate. (iii) Elevation bands brought consistent changes in water distribution within the hydrological cycle of implemented watersheds, which are more in line with expected flow paths.
2022
From the micro to mesoscale, water and energy budgets of mountainous catchments are largely driven by topographic features such as terrain orientation, slope, steepness, elevation together with associated meteorological forcings such as precipitation, solar radiation and wind. This impact the snow deposition, melting and transport, which further impact the overall water cycle. However, this microscale variability is not well represented in Earth System Models due to coarse resolutions, and impacts of such resolution assumptions on simulated water and energy budget lack quantification. This study aims at exploring these effects on a 15.28 ha small mid-elevation (2000-2200 m) alpine catchment at Col du Lautaret (France). This grass-dominated catchment remains covered with snow for 5 to 6 months per year. The surface-subsurface coupled hyperresolution (10 m) distributed hydrological model ParFLOW-CLM is used to simulate the impacts of meteorological variability at spatio-temporal micro-scale on the water cycle. These include 3D simulations with spatially distributed forcing of precipitation, solar radiation and wind compared to 3D simulations with non-distributed forcing simulation. Our precipitation distribution method encapsulates the spatial snow distribution along with snow transport. The model simulates the snow cover dynamics and spatial variability through the CLM energy balance module and under the different combinations of distributed forcing. The resulting subsurface and surface water transfers are solved by the ParFLOW module. Distributed forcing induce a snowpack with a more spatially heterogeneous thickness, which becomes patchy during the melt season and shows a good agreement with the remote sensing images. This asynchronous melting results in a longer melting period and smoother hydrological response than the non-distributed forcing, which does not generate any patchiness. Amongst the tested distributed meteorological forcing that impacts the hydrology, precipitation distribution, including snow transportation, is the most important. Solar insolation distribution has an important impact in reducing evapotranspiration depending on the slope orientation. For the studied catchment mainly facing east, it adds small differential melting effect. Wind distribution in the energy budget calculation has a more complicated impact on our catchment as it participate to accelerate the melting when meteorological conditions are favourable but does not generate patchiness at the end in our test case. 1 Introduction Mountains are natural water reservoirs, which mitigate seasonal precipitation variability through snowpack accumulation, whose progressive melting helps meet the fresh water and energy demand all year long. Climate projections for warmer climate in the near and far future for these regions will impact this mitigation process. Earth System Models (ESMs) are then challenged to simulate water fluxes in mountainous catchments where highly variable topographic features and vegetation, soils and geological structures affect water transfers at different scales. In particular topography controls snow/rain precipitation estimation and partition uncertainties, snow redistribution, slope/aspect effect and hill-shading that leads to spatial differential melting (
The hydrological role of snow and glaciers in alpine river basins and their distributed modeling
Journal of Hydrology, 2003
A temperature index approach including incoming solar radiation was used as a sub-model in the gridded hydrological catchment model WaSiM-ETH to simulate the melt rate of glacierized areas. Melt water and rainfall are transformed into glacier discharge by using linear reservoir approaches. The complex WaSiM model was applied to three Swiss high-alpine river catchments with different portions of glacierized areas to simulate the discharges of the whole catchments. Gridded data sets of elevation, soil type, and land-use were used including meteorological input data from the network of MeteoSwiss. These data were spatially and temporally interpolated and modified according to exposition, slope and topographic shading. Continuous discharge simulations for the catchment areas were performed in a spatial resolution of 100 m and a temporal resolution of 1 h for the period 1981-2000 and compared with hourly discharge observations measured at the catchment outlets. To improve the calculation of glacier runoff, a seasonal varying radiation factor has been implemented in the glacier melt equation. The pronounced diurnal and seasonal fluctuations in discharge, which are typical of partly glacierized catchment areas, were simulated in a good agreement with the observed values.
Physically based approach to modelling distributed snowmelt in a small alpine catchment
1991
A distributed approach has been used to investigate the influence of topography on snowmelt processes for a small basin located in an open site, in the Eastern Italian Alps. Based on hourly records of shortwave radiation, the distributed fluxes of direct and diffused radiation are considered. Snow albedo variations in time and space are simulated, by using semiempirical formulae. Atmospheric emissivity is estimated by means of Satterlund's equation; the turbulent exchange components are evaluated in the light of the classical mixing-length theory, and the computations have been carried out by processing hourly records of air temperature, relative humidity, and wind speed. A continuous simulation covering five years shows the contribution of net shortwave flux to be dominant, and the concomitant spatial variability of snowpack melt to be not negligible. Although remote sensing techniques were not used directly to provide data input for continuous simulation, the possibility has been investgated to simulate distributed snow albedo from radiance levels measured by the Landsat 5-MSS sensor. The spatially-distributed framework could be utilized to improve the performance of simpler degree-day models.
Scenarios of Future Snow Conditions in Styria (Austrian Alps)
Journal of Hydrometeorology, 2015
A hydrometeorological model chain is applied to investigate climate change effects on natural and artificial snow conditions in the Schladming region in Styria (Austria). Four dynamically refined realizations of the IPCC A1B scenario covering the warm/cold and wet/dry bandwidth of projected changes in temperature and precipitation in the winter half-year are statistically downscaled and bias corrected prior to their application as input for a physically based, distributed energy-balance snow model. However, owing to the poor skills in the reproduction of past climate and snow conditions in the considered region, one realization had to be removed from the selection to avoid biases in the results of the climate change impact analysis. The model's capabilities in the simulation of natural and artificial snow conditions are evaluated and changes in snow conditions are addressed by comparing the number of snow cover days, the length of the ski season, and the amounts of technically produced snow as simulated for the past and the future. The results for natural snow conditions indicate decreases in the number of snow cover days and the ski season length of up to .25 and .35 days, respectively. The highest decrease in the calculated ski season length has been found for elevations between 1600 and 2700 m MSL, with an average decrease rate of ;2.6 days decade 21 . For the exemplary ski site considered, the ski season length simulated for natural snow conditions decreases from .50 days at present to ;40 days in the 2050s. Technical snow production allows the season to be prolonged by ;80 days and hence allows ski season lengths of ;120 days until the end of the scenario period in 2050.
ALPINE3D: a detailed model of mountain surface processes and its application to snow hydrology
Hydrological Processes, 2006
Current models of snow cover distribution, soil moisture, surface runoff and river discharge typically have very simple parameterizations of surface processes, such as degree-day factors or single-layer snow cover representation. For the purpose of reproducing catchment runoff, simple snowmelt routines have proven to be accurate, provided that they are carefully calibrated specifically for the catchment they are applied to. The use of more detailed models is, however, useful to understand and quantify the role of individual surface processes for catchment hydrology, snow cover status and soil moisture distribution.We introduce ALPINE3D, a model for the high-resolution simulation of alpine surface processes, in particular snow processes. The model can be driven by measurements from automatic weather stations or by meteorological model outputs. As a preprocessing alternative, specific high-resolution meteorological fields can be created by running a meteorological model. The core three-dimensional ALPINE3D modules consist of a radiation balance model (which uses a view-factor approach and includes shortwave scattering and longwave emission from terrain and tall vegetation) and a drifting snow model solving a diffusion equation for suspended snow and a saltation transport equation. The processes in the atmosphere are thus treated in three dimensions and are coupled to a distributed (in the hydrological sense of having a spatial representation of the catchment properties) one-dimensional model of vegetation, snow and soil (SNOWPACK) using the assumption that lateral exchange is small in these media. The model is completed by a conceptual runoff module. The model can be run with a choice of modules, thus generating more or less detailed surface forcing data as input for runoff generation simulations. The model modules can be run in a parallel (distributed) mode using a GRID infrastructure to allow computationally demanding tasks. In a case study from the Dischma Valley in eastern Switzerland, we demonstrate that the model is able to simulate snow distribution as seen from a NOAA advanced very high-resolution radiometer image. We then analyse the sensitivity of simulated snow cover distribution and catchment runoff to the use of different surface process descriptions. We compare model runoff simulations with runoff data from 10 consecutive years. The quantitative analysis shows that terrain influence on the radiation processes has a significant influence on catchment hydrology dynamics. Neglecting the role of vegetation and the spatial variability of the soil, on the other hand, had a much smaller influence on the runoff generation dynamics. We conclude that ALPINE3D is a valuable tool to investigate surface dynamics in mountains. It is currently used to investigate snow cover dynamics for avalanche warning and permafrost development and vegetation changes under climate change scenarios. It could also serve to test the output of simpler soil–vegetation–atmosphere transfer schemes used in larger scale climate or meteorological models and to create accurate soil moisture assessments for meteorological and flood forecasting. Copyright © 2006 John Wiley & Sons, Ltd.
Engineering, Technology & Applied Science Research, 2018
This study analyzes the response of various hydrological parameters and future water availability against anticipated climate variations in snow dominated alpine catchment in Austria. The parameters assessed are base flow, environmental flow, total flow, evapotranspiration, and snow cover duration. The distributed hydrological modeling system PREVAH is developed to assess the impacts through the combination of various climate change scenarios produced under the framework of the European project PRUDENCE. The model results clearly indicate an apparent shift from observed trends in monthly, seasonal and annual values. The mean annual changes observed by all model scenarios range between 45% to 60% decrease in snow cover duration, 15% to 20% increase in evapotranspiration, 5% to 15% decrease in base flow, and 15% to 25% decrease in total runoff values. However, mean annual changes observed in available water are marginal, just ranging from-3% to +2%. All regional model projections show more or less the same identical pattern of changes in analyzed parameters.
The Cryosphere Discussions
We evaluated distributed and semi-distributed modeling approaches to simulating the spatial and temporal evolution of snow and ice over an extended mountain catchment, using the Crocus snowpack model. The distributed approach simulated the snowpack dynamics on a 250-m grid, enabling inclusion of terrain shadowing effects. The semi-distributed approach simulated the snowpack dynamics for discrete topographic classes characterized by elevation range, aspect, and slope. This provided a categorical simulation that was subsequently spatially re-projected over the 250-m grid used for the distributed simulations. The study area (the upper Arve catchment, western Alps, France) is characterized by complex topography, including steep slopes, an extensive glaciated area, and snow cover throughout the year. Simulations were carried out for the period 1989–2015 using the SAFRAN meteorological forcing system. The simulations were compared using four observation datasets including point snow depth...