scholarly journals Can a snow structure model estimate snow characteristics relevant to reindeer husbandry?

Rangifer ◽  
2014 ◽  
Vol 34 (1) ◽  
pp. 37 ◽  
Author(s):  
Sirpa Rasmus ◽  
Jouko Kumpula ◽  
Jukka Siitari
Keyword(s):  
Snow Cover ◽  
Annual Reports ◽  
Ground Vegetation ◽  
Reproduction Rate ◽  
Mold Growth ◽  
Reindeer Herding ◽  
Model Estimate ◽  
Reindeer Husbandry ◽  
Meteorological Observations ◽  
Snow Model

Snow affects foraging conditions of reindeer e.g. by increasing the energy expenditures for moving and digging work or, in contrast, by making access of arboreal lichen easier. Still the studies concentrating on the role of the snow pack structure on reindeer population dynamics and reindeer management are few. We aim to find out which of the snow characteristics are relevant for reindeer in the northern boreal zone according to the experiences of reindeer herders and is this relevance seen also in reproduction rate of reindeer in this area. We also aim to validate the ability of the snow model SNOWPACK to reliably estimate the relevant snow structure characteristics. We combined meteorological observations, snow structure simulations by the model SNOWPACK and annual reports by reindeer herders during winters 1972-2010 in the Muonio reindeer herding district, northern Finland. Deep snow cover and late snow melt were the most common unfavorable conditions reported. Problematic conditions related to snow structure were icy snow and ground ice or unfrozen ground below the snow, leading to mold growth on ground vegetation. Calf production percentage was negatively correlated to the measured annual snow depth and length of the snow cover time and to the simulated snow density. Winters with icy snow could be distinguished in three out of four reported cases by SNOWPACK simulations and we could detect reliably winters with conditions favorable for mold growth. Both snow amount and also quality affects the reindeer herding and reindeer reproduction rate in northern Finland. Model SNOWPACK can relatively reliably estimate the relevant structural properties of snow. Use of snow structure models could give valuable information about grazing conditions, especially when estimating the possible effects of warming winters on reindeer populations and reindeer husbandry. Similar effects will be experienced also by other arctic and boreal species.

Process-based simulation of snow cover evolution in ski resorts using the AMUNDSEN model: results and validation

2020 ◽  
Author(s):  
Florian Hanzer ◽  
Daniel Günther ◽  
Ulrich Strasser ◽  
Valentina Premier ◽  
Mattia Callegari ◽  
...  
Keyword(s):  
Snow Cover ◽  
Management Strategies ◽  
Physical Factors ◽  
Ambient Conditions ◽  
Future Evolution ◽  
Ski Resort ◽  
Ski Resorts ◽  
Temperature And Humidity ◽  
Meteorological Observations ◽  
Snow Model

<p>Snow management, i.e., snowmaking and grooming, is an integral part of modern ski resort operation. While the current snow cover distribution on the slopes is often well known thanks to the usage of advanced monitoring techniques, estimates about its future evolution are usually lacking. Management-enabled numerical snowpack models driven by meteorological forecasts can help to fill this gap. In the frame of the H2020 project PROSNOW such software tools are developed to be run on an operational basis with the aim to optimize snow management as well as the use of water and energy resources. As part of PROSNOW, model simulations for the ski resorts Seefeld and Obergurgl (both Austria) as well as Colfosco and San Vigilio (both Italy) are performed with the physically based snow model AMUNDSEN. In its particular snow management module, both socioeconomic and physical factors are considered, the former concerning the decision when, where and how much snow should be produced, and the latter considering the snowmaking conditions, i.e., how much snow can be produced in the current ambient conditions (in terms of temperature and humidity) and the given ski resort infrastructure (number and efficiency of snow guns, water availability, etc.).</p><p>In our contribution we show the implementation of snowmaking and grooming practices in the AMUNDSEN model, its adaptation to individual ski resorts, and how different potential snow management strategies are accounted for. Model results obtained using historical meteorological observations and hindcast simulations are validated against observations from numerous data sources such as Sentinel-2 snow cover maps, distributed snow depth measurements from groomers, temperature and humidity measurements from snow guns as well as water consumption recordings.</p>

scholarly journals Assimilation of snow cover and snow depth into a snow model to estimate snow water equivalent and snowmelt runoff in a Himalayan catchment

2017 ◽  
Vol 11 (4) ◽  
pp. 1647-1664 ◽  
Author(s):  
Emmy E. Stigter ◽  
Niko Wanders ◽  
Tuomo M. Saloranta ◽  
Joseph M. Shea ◽  
Marc F. P. Bierkens ◽  
...  
Keyword(s):  
Kalman Filter ◽  
Data Assimilation ◽  
Snow Cover ◽  
Climate Sensitivity ◽  
Snow Depth ◽  
Snow Water Equivalent ◽  
Snowmelt Runoff ◽  
Snow Water ◽  
Snow Model

Abstract. Snow is an important component of water storage in the Himalayas. Previous snowmelt studies in the Himalayas have predominantly relied on remotely sensed snow cover. However, snow cover data provide no direct information on the actual amount of water stored in a snowpack, i.e., the snow water equivalent (SWE). Therefore, in this study remotely sensed snow cover was combined with in situ observations and a modified version of the seNorge snow model to estimate (climate sensitivity of) SWE and snowmelt runoff in the Langtang catchment in Nepal. Snow cover data from Landsat 8 and the MOD10A2 snow cover product were validated with in situ snow cover observations provided by surface temperature and snow depth measurements resulting in classification accuracies of 85.7 and 83.1 % respectively. Optimal model parameter values were obtained through data assimilation of MOD10A2 snow maps and snow depth measurements using an ensemble Kalman filter (EnKF). Independent validations of simulated snow depth and snow cover with observations show improvement after data assimilation compared to simulations without data assimilation. The approach of modeling snow depth in a Kalman filter framework allows for data-constrained estimation of snow depth rather than snow cover alone, and this has great potential for future studies in complex terrain, especially in the Himalayas. Climate sensitivity tests with the optimized snow model revealed that snowmelt runoff increases in winter and the early melt season (December to May) and decreases during the late melt season (June to September) as a result of the earlier onset of snowmelt due to increasing temperature. At high elevation a decrease in SWE due to higher air temperature is (partly) compensated by an increase in precipitation, which emphasizes the need for accurate predictions on the changes in the spatial distribution of precipitation along with changes in temperature.

scholarly journals Wealth of nomads – an exploratory analysis of livestock inequality in the Saami reindeer husbandry

2021 ◽  
Author(s):  
Marius Warg Næss ◽  
Bård-Jørgen Bårdsen
Keyword(s):  
Primary Source ◽  
Wealth Inequality ◽  
External Factors ◽  
Social Differentiation ◽  
Reindeer Herding ◽  
Reindeer Husbandry ◽  
The Poor ◽  
Wealth Inequalities ◽  
Rank Differences ◽  
Over Time

Social inequality is pervasive in contemporary human societies. Nevertheless, there is a view that livestock, as the primary source of wealth, limits the development of inequalities, making pastoralism unable to support complex or hierarchical organisations. Thus, complex nomadic pastoral organisation is predominantly caused by external factors, i.e., historically nomadic political organisation mirrored the neighbouring sedentary population's sophistication. Using governmental statistics on reindeer herding in Norway (2001 - 2018), this study demonstrates nothing apparent in the pastoral adaptation with livestock as the main base of wealth that level wealth inequalities and limits social differentiation. This study found that inequality was generally decreasing in terms of the Gini coefficient and cumulative wealth. For example, the proportion owned by the wealthy decreased from 2001 to 2018, while the proportion owned by the poor increased. Nevertheless, rank differences persist over time with minor changes. Especially, being poor is stable: around 50% of households ranked as poor in 2001 continued to be so in 2018. In sum, results from this study indicate that pastoral wealth inequality follows the same patterns as all forms of wealth. Wealth accumulates over time, and because the highest earners can save much of their income (i.e., newborn livestock), low earners cannot. High earners can thus accumulate more and more wealth over time, leading to considerable wealth inequalities.

scholarly journals Evaluation of CLASS Snow Simulation over Eastern Canada

2017 ◽  
Vol 18 (5) ◽  
pp. 1205-1225 ◽  
Author(s):  
Diana Verseghy ◽  
Ross Brown ◽  
Libo Wang
Keyword(s):  
Snow Cover ◽  
Land Surface ◽  
Snow Water Equivalent ◽  
Climate Model ◽  
Regional Climate ◽  
Eastern Canada ◽  
Fractional Snow Cover ◽  
Forest Regions ◽  
Snow Water ◽  
Snow Model

Abstract The Canadian Land Surface Scheme (CLASS), version 3.6.1, was run offline for the period 1990–2011 over a domain centered on eastern Canada, driven by atmospheric forcing data dynamically downscaled from ERA-Interim using the Canadian Regional Climate Model. The precipitation inputs were adjusted to replicate the monthly average precipitation reported in the CRU observational database. The simulated fractional snow cover and the surface albedo were evaluated using NOAA Interactive Multisensor Snow and Ice Mapping System and MODIS data, and the snow water equivalent was evaluated using CMC, Global Snow Monitoring for Climate Research (GlobSnow), and Hydro-Québec products. The modeled fractional snow cover agreed well with the observational estimates. The albedo of snow-covered areas showed a bias of up to −0.15 in boreal forest regions, owing to neglect of subgrid-scale lakes in the simulation. In June, conversely, there was a positive albedo bias in the remaining snow-covered areas, likely caused by neglect of impurities in the snow. The validation of the snow water equivalent was complicated by the fact that the three observation-based datasets differed widely. Also, the downward adjustment of the forcing precipitation clearly resulted in a low snow bias in some regions. However, where the density of the observations was high, the CLASS snow model was deemed to have performed well. Sensitivity tests confirmed the satisfactory behavior of the current parameterizations of snow thermal conductivity, snow albedo refreshment threshold, and limiting snow depth and underlined the importance of snow interception by vegetation. Overall, the study demonstrated the necessity of using a wide variety of observation-based datasets for model validation.

scholarly journals Inter-Comparison of two Snow Models with Different Complexity using Data from an Alpine Site

2002 ◽  
Vol 33 (1) ◽  
pp. 15-26 ◽  
Author(s):  
U. Strasser ◽  
P. Etchevers ◽  
Y. Lejeune
Keyword(s):  
Mass Balance ◽  
Snow Cover ◽  
Good Correspondence ◽  
Snow Albedo ◽  
Avalanche Forecasting ◽  
Physically Based ◽  
Forecasting System ◽  
Snow Model ◽  
Using Data ◽  
Hydrological Applications

This contribution describes the modelization of the snow cover evolution with the two physically based snow models CROCUS and ESCIMO at the Col de Porte station (1,325 m a.s.l., French Alps) for the three subsequent seasons 1994/95–1996/97. CROCUS is a detailed, multi-layer snow model developed for the operational avalanche forecasting system of METEO France, whereas ESCIMO is a one-layer energy and mass balance snow model for hydrological applications. The snow albedo function parameters for ESCIMO are calibrated in 1994/95. In the first verification season (1995/96), the results of the two models show a good correspondence, whereas in the second (1996/97) they differ significantly. For this season a considerable gain in performance of ESCIMO is achieved by recalibration of the snow albedo function parameters.

scholarly journals A new Snow-SVAT to simulate the accumulation and ablation of seasonal snow cover beneath a forest canopy

2004 ◽  
Vol 50 (169) ◽  
pp. 171-182 ◽  
Author(s):  
Melody J. Tribbeck ◽  
Robert J. Gurney ◽  
Elizabeth M. Morris ◽  
David W. C. Pearson
Keyword(s):  
Solar Radiation ◽  
Snow Cover ◽  
Forest Canopy ◽  
Correlation Coefficients ◽  
Field Measurements ◽  
Radiation Model ◽  
Physically Based ◽  
Boreal Ecosystem ◽  
Snow Model

AbstractA new snow—soil—vegetation—atmosphere transfer (Snow-SVAT) scheme, which simulates the accumulation and ablation of the snow cover beneath a forest canopy, is presented. The model was formulated by coupling a canopy optical and thermal radiation model to a physically based multi-layer snow model. This canopy radiation model is physically based yet requires few parameters, so can be used when extensive in situ field measurements are not available. Other forest effects such as the reduction of wind speed, interception of snow on the canopy and the deposition of litter were incorporated within this combined model, SNOWCAN, which was tested with data taken as part of the Boreal Ecosystem—Atmosphere Study (BOREAS) international collaborative experiment. Snow depths beneath four different canopy types and at an open site were simulated. Agreement between observed and simulated snow depths was generally good, with correlation coefficients ranging between r2 = 0.94 and r2 = 0.98 for all sites where automatic measurements were available. However, the simulated date of total snowpack ablation generally occurred later than the observed date. A comparison between simulated solar radiation and limited measurements of sub-canopy radiation at one site indicates that the model simulates the sub-canopy downwelling solar radiation early in the season to within measurement uncertainty.

Evaluating the snow component of a flood forecasting model

2012 ◽  
Vol 43 (6) ◽  
pp. 762-779 ◽  
Author(s):  
T. Nester ◽  
R. Kirnbauer ◽  
J. Parajka ◽  
G. Blöschl
Keyword(s):  
Spatial Analysis ◽  
Snow Cover ◽  
Flood Forecasting ◽  
Hydrologic Model ◽  
Balance Model ◽  
Efficiency Measures ◽  
Open Land ◽  
Forested Areas ◽  
Snow Model ◽  
Alpine Catchments

The objective of this study is to evaluate the snow routine of a semi-distributed conceptual water balance model calibrated to streamflow data alone. The model is used for operational flood forecasting in 57 catchments in Austria and southern Germany with elevations ranging 200–3,800 m a.s.l. We compared snow water equivalents (SWE) simulated by the hydrologic model with snow covered area (SCA) derived from a combined product of MODIS (version 5) Terra and Aqua satellite data for the period 2003–2009 using efficiency measures and a spatial analysis. In the comparison, thresholds for percent catchment snow cover and a cut-off water equivalent need to be chosen with care as they affect the snow model efficiency. Results indicate that the model has a tendency to underestimate snow cover in prealpine areas and forested areas while it performs better in alpine catchments and open land. The spatial analysis shows that for 88% of the analysed model area snow cover is modelled correctly on more than 80% of the days. The space borne snow cover data proved to be very useful for evaluating the snow model. We therefore suggest that the snow data will be similarly useful for data assimilation in real time flood forecasting.

Managing predators, managing reindeer: contested conceptions of predator policies in Finland's southeast reindeer herding area

Polar Record ◽  
2011 ◽  
Vol 47 (3) ◽  
pp. 218-230 ◽  
Author(s):  
Hannu I. Heikkinen ◽  
Outi Moilanen ◽  
Mark Nuttall ◽  
Simo Sarkki
Keyword(s):  
Actor Network Theory ◽  
Modern Human ◽  
Complex Case ◽  
Conservation Strategies ◽  
Reindeer Herding ◽  
Human Environment ◽  
Reindeer Husbandry ◽  
Research Findings ◽  
Conservation Projects ◽  
Theoretical Considerations

ABSTRACTPreserving biodiversity and establishing healthy and thriving populations of predator animals are the expressed aims of many wildlife and ecosystem conservation projects and initiatives. However, such conservation strategies are often in conflict with the traditions, practices and land-use priorities of local communities. This article concentrates on the situation concerning the predation of reindeer (mainly by wolves) in Finland's southeast reindeer herding area and its immediate vicinity, but makes reference to the broader situation of predation and reindeer herding in Finland. Based on analysis of statistics and interviews with local stakeholders, the research findings refer to the intermingled contradictions related to conceptual, statistical and other management relevant knowledge and resulting problems, for example, in conservation hunting licensing. The article concludes that the wolf comprises a complex case for nature conservation initiatives and sustainable reindeer husbandry and that, in practice, it has particular implications compared to other policy approaches to dealing with the problem of animal predators. The article ends with some theoretical considerations as to whether we can improve our understanding of modern human-environment relations by deriving ideas from the actor-network theory debates.

scholarly journals Introducing Hysteresis in Snow Depletion Curves to Improve the Water Budget of a Land Surface Model in an Alpine Catchment

2014 ◽  
Vol 15 (2) ◽  
pp. 631-649 ◽  
Author(s):  
Claire Magand ◽  
Agnès Ducharne ◽  
Nicolas Le Moine ◽  
Simon Gascoin
Keyword(s):  
Snow Cover ◽  
Land Surface ◽  
Water Budget ◽  
Land Surface Model ◽  
Surface Model ◽  
Depletion Curve ◽  
Physically Based ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
The Difference ◽  
Snow Model

Abstract The Durance watershed (14 000 km2), located in the French Alps, generates 10% of French hydropower and provides drinking water to 3 million people. The Catchment land surface model (CLSM), a distributed land surface model (LSM) with a multilayer, physically based snow model, has been applied in the upstream part of this watershed, where snowfall accounts for 50% of the precipitation. The CLSM subdivides the upper Durance watershed, where elevations range from 800 to 4000 m within 3580 km2, into elementary catchments with an average area of 500 km2. The authors first show the difference between the dynamics of the accumulation and ablation of the snow cover using Moderate Resolution Imaging Spectroradiometer (MODIS) images and snow-depth measurements. The extent of snow cover increases faster during accumulation than during ablation because melting occurs at preferential locations. This difference corresponds to the presence of a hysteresis in the snow-cover depletion curve of these catchments, and the CLSM was adapted by implementing such a hysteresis in the snow-cover depletion curve of the model. Different simulations were performed to assess the influence of the parameterizations on the water budget and the evolution of the extent of the snow cover. Using six gauging stations, the authors demonstrate that introducing a hysteresis in the snow-cover depletion curve improves melting dynamics. They conclude that their adaptation of the CLSM contributes to a better representation of snowpack dynamics in an LSM that enables mountainous catchments to be modeled for impact studies such as those of climate change.

Growth response of Norway spruce saplings in two forest gaps in the Swiss Alps to artificial browsing, infection with black snow mold, and competition by ground vegetation

2006 ◽  
Vol 36 (11) ◽  
pp. 2782-2793 ◽  
Author(s):  
Catherine Cunningham ◽  
Niklaus E Zimmermann ◽  
Veronika Stoeckli ◽  
Harald Bugmann
Keyword(s):  
Snow Cover ◽  
Norway Spruce ◽  
Model Performance ◽  
Swiss Alps ◽  
Ground Vegetation ◽  
Strong Impact ◽  
European Alps ◽  
Snow Mold ◽  
Forest Gaps ◽  
Sapling Growth

Black snow mold (Herpotrichia juniperi (Duby) Petr.) infection and browsing byungulates influence the growth of Norway spruce (Picea abies (L.) Karst.) saplings in subalpine forests in the European Alps. To isolate the impacts of artificial browsing (clipping of shoots) and snow mold infection on growth, we conducted a 2 year field experiment with planted saplings in two forest gaps in the subalpine zone of the Swiss Alps. In the first year (2003) saplings responded slightly positively to clipping and negatively to snow mold infection; sapling growth behavior was site-specific (ANOVA, r2 = 0.35). In 2004, saplings responded negatively to clipping, snow mold infection, long-lasting snow cover, and shading by ground vegetation (ANOVA, r2 = 0.59). The difference in mean annual growth rates between noninfected and infected saplings was large; long-lasting snow was found to enhance snow mold coverage. Removing these variables from general linear models strongly reduced model performance (d2 = 0.32 for the full model, d2 = 0.23 for no clipping, d2 = 0.16 for no snow cover). Sapling growth was negatively related to shading by ground vegetation, especially in 2004. We conclude that these biotic factors have a strong impact on growth, both individually and in combination, and that their effect is enhanced by interaction with environmental factors such as snow duration.

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