scholarly journals Snow cover as a morphogenic agent determining ground climate, landforms and runoff in the Valdecebollas massif, Cantabrian Mountains

2020 ◽  
Vol 46 (1) ◽  
pp. 81-102 ◽  
Author(s):  
A. Pisabarro
Keyword(s):  
Snow Cover ◽  
Physical Environment ◽  
Satellite Images ◽  
Runoff Generation ◽  
Cantabrian Mountains ◽  
Data Loggers ◽  
Geomorphological Map ◽  
Snow Distribution ◽  
Geomorphological Processes ◽  
Early Snowmelt

Snowfalls are important meteorological events affecting the physical environment of the Cantabrian Mountains. This work analyzes the effects of snow on several elements such as relief, landforms, ground climate and snowmelt waters. The ground thermal regime and associated parameters were studied using temperature data loggers and satellite images and were described in combination with observed geomorphological processes and landforms. A geomorphological map was drawn up and trends in climate patterns and runoff were calculated. Ground temperature monitoring in warm years is not optimal, though allow to know the limit conditions for developing cold processes. Results show that geomorphological processes are not significant and that solifluction deriving from snowmelt, is the only active process in years without freeze or with thick snow cover. Snowfall evolution in recent decades in correlation with flow water and climate features provide the certainty that snow distribution also affects efficacy in runoff generation and moves the flow peak in rivers due to early snowmelt.

scholarly journals Ground thermal regime in the vicinity of relict rock glaciers (Cantabrian Mountains, NW Spain)

Finisterra ◽  
2012 ◽  
Vol 44 (87) ◽  
Author(s):  
Javier Santos-González ◽  
Rosa González-Gutiérrez ◽  
Amélia Gómes-Villar ◽  
José Redondo-Vega
Keyword(s):  
Snow Cover ◽  
Thermal Regime ◽  
Strong Influence ◽  
Temperature Data ◽  
Ground Temperature ◽  
Cantabrian Mountains ◽  
Nw Spain ◽  
Freeze Thaw ◽  
Rock Glaciers ◽  
Frost Penetration

Ground temperature data obtained from 2002 to 2007 in sites near relict rock glaciers in the cantabrian mountains, at altitudes between 1500 and 2300 meters is analysed. Snow cover lasted between 3 and 9 months and had a strong influence on the thermal regime. When snow was present, the soil was normally frozen in the first 5 to 10 cm, but daily freeze-thaw cycles were rare. In well developed soils located at sunny faces frost penetration rarely reached more than 10 cm. on the contrary in shady and windy faces with scarce snow cover, frost penetration reached, at least, 40 cm. In persistent snow patches the temperature was stable at 0 ºc, even in relict rock glaciers, where subnival winter air fluxes appear to have been very rare.

scholarly journals Snow Cover and Snow Persistence Changes in the Mocho-Choshuenco Volcano (Southern Chile) Derived From 35 Years of Landsat Satellite Images

2021 ◽  
Vol 9 ◽  
Author(s):  
Roberto O. Chávez ◽  
Verónica F. Briceño ◽  
José A. Lastra ◽  
Daniel Harris-Pascal ◽  
Sergio A. Estay
Keyword(s):  
Snow Cover ◽  
Satellite Images ◽  
Remote Sensing Data ◽  
Landsat Images ◽  
Microbial Composition ◽  
Mountain Areas ◽  
Pixel Resolution ◽  
Temperature Changes ◽  
Soil Microbial ◽  
Landsat Satellite

Mountain regions have experienced above-average warming in the 20th century and this trend is likely to continue. These accelerated temperature changes in alpine areas are causing reduced snowfall and changes in the timing of snowfall and melt. Snow is a critical component of alpine areas - it drives hibernation of animals, determines the length of the growing season for plants and the soil microbial composition. Thus, changes in snow patterns in mountain areas can have serious ecological consequences. Here we use 35 years of Landsat satellite images to study snow changes in the Mocho-Choshuenco Volcano in the Southern Andes of Chile. Landsat images have 30 m pixel resolution and a revisit period of 16 days. We calculated the total snow area in cloud-free Landsat scenes and the snow frequency per pixel, here called “snow persistence” for different periods and seasons. Permanent snow cover in summer was stable over a period of 30 years and decreased below 20 km2 from 2014 onward at middle elevations (1,530–2,000 m a.s.l.). This is confirmed by negative changes in snow persistence detected at the pixel level, concentrated in this altitudinal belt in summer and also in autumn. In winter and spring, negative changes in snow persistence are concentrated at lower elevations (1,200–1,530 m a.s.l.). Considering the snow persistence of the 1984–1990 period as a reference, the last period (2015–2019) is experiencing a −5.75 km2 reduction of permanent snow area (snow persistence > 95%) in summer, −8.75 km2 in autumn, −42.40 km2 in winter, and −18.23 km2 in spring. While permanent snow at the high elevational belt (>2,000 m a.s.l.) has not changed through the years, snow that used to be permanent in the middle elevational belt has become seasonal. In this study, we use a probabilistic snow persistence approach for identifying areas of snow reduction and potential changes in alpine vegetation. This approach permits a more efficient use of remote sensing data, increasing by three times the amount of usable scenes by including images with spatial gaps. Furthermore, we explore some ecological questions regarding alpine ecosystems that this method may help address in a global warming scenario.

scholarly journals Hydrological effects of Norway spruce and European beech on snow cover in a mid-mountain region of the Polana mts., Slovakia / Hydrologický vplyv smreka obyčajného a buka lesného na snehovú pokrývku v stredohorských polohách pohoria poľana na slovensku

2012 ◽  
Vol 60 (4) ◽  
pp. 319-332 ◽  
Author(s):  
Matus Hribik ◽  
Tomas Vida ◽  
Jaroslav Skvarenina ◽  
Jana Skvareninova ◽  
Lubomir Ivan
Keyword(s):  
Snow Cover ◽  
Norway Spruce ◽  
Forest Canopy ◽  
Biosphere Reserve ◽  
European Beech ◽  
Mountain Region ◽  
Runoff Generation ◽  
Forest Stands ◽  
Snow Melting ◽  
Beech Stand

The paper evaluates the results of a 6-year-monitoring of the eco-hydrological influence of Norway spruce (Picea abies (L.) Karst.) and European beech (Fagus silvatica L.) forest stands on the hydro-physical properties of snow cover. The experiment was carried out in the artificially regenerated 20-25-year-old forest stands approaching the pole timber stage in the middle mountain region of the Polana Mts. - Biosphere reserve situated at about 600 m a.s.l. during the period of maximum snow supply in winters of years 2004 - -2009. Forest canopy plays a decisive role at both the snow cover duration and spring snow melting and runoff generation. A spruce stand is the poorest of snow at the beginning of winter. High interception of spruce canopy hampers the throughfall of snow to soil. During the same period, the soil surface of a beech stand accumulates greater amount of snow. However, a spruce stand accumulates snow by creating snow heaps during the periods of maximum snow cumulation and stand´s microclimate slows down snow melting. These processes are in detail discussed in the paper. The forest stands of the whole biosphere reserve slow down to a significant extent both the snow cover melting and the spring runoff of the whole watershed.

scholarly journals Rapid changes in snow cover at low elevations in the Sierra Nevada, California, U.S.A.

1997 ◽  
Vol 25 ◽  
pp. 367-370 ◽  
Author(s):  
Richard Kattelmann
Keyword(s):  
Snow Cover ◽  
Sierra Nevada ◽  
Mountain Range ◽  
Rainfall Runoff ◽  
Runoff Generation ◽  
Distributed Models ◽  
Rapid Changes ◽  
Spatially Distributed ◽  
Precipitation Type ◽  
River Forecasting

Snow cover in the intermittent snow zone of the Sierra Nevada can occupy more than 10 000 km2 of the mountain range, but it has received relatively little attention in river forecasting. Snow is deposited at lower elevations only during the cold storms of winter, and remains there only for a few days or weeks. When cold storms have created a thin snow cover at low elevations, a subsequent warm storm can melt this snow in just a few hours and increase the runoff response dramatically. Operational hydrological models and river-forecasting procedures have tended to overlook contributions from the intermittent-snow zone, focusing instead on rainfall-runoff or melt from the snowpack zone at higher elevations. Data-collection efforts are minimal in this zone, too. Ideally, spatially distributed models of snowmelt and runoff generation are needed to account for the typically large differences in snow cover on different aspects in the intermittent snow zone. Although aircraft and satellite imagery would be most desirable to monitor the distribution of snow cover in the intermittent-snow zone, even a few climate stations that report precipitation type and snow presence would be a major improvement over the present situation in the Sierra Nevada.

scholarly journals High resolution snow distribution data from complex Arctic terrain: a tool for model validation

2002 ◽  
Vol 2 (3/4) ◽  
pp. 147-155 ◽  
Author(s):  
Ch. Jaedicke ◽  
A. D. Sandvik
Keyword(s):  
High Resolution ◽  
Snow Cover ◽  
Numerical Models ◽  
The Arctic ◽  
Distribution Data ◽  
Blowing Snow ◽  
Data Set ◽  
Meteorological Model ◽  
Drift Model ◽  
Snow Distribution

Abstract. Blowing snow and snow drifts are common features in the Arctic. Due to sparse vegetation, low temperatures and high wind speeds, the snow is constantly moving. This causes severe problems for transportation and infrastructure in the affected areas. To minimise the effect of drifting snow already in the designing phase of new structures, adequate models have to be developed and tested. In this study, snow distribution in Arctic topography is surveyed in two study areas during the spring of 1999 and 2000. Snow depth is measured by ground penetrating radar and manual methods. The study areas encompass four by four kilometres and are partly glaciated. The results of the surveys show a clear pattern of erosion, accumulation areas and the evolution of the snow cover over time. This high resolution data set is valuable for the validation of numerical models. A simple numerical snow drift model was used to simulate the measured snow distribution in one of the areas for the winter of 1998/1999. The model is a two-level drift model coupled to the wind field, generated by a mesoscale meteorological model. The simulations are based on five wind fields from the dominating wind directions. The model produces a satisfying snow distribution but fails to reproduce the details of the observed snow cover. The results clearly demonstrate the importance of quality field data to detect and analyse errors in numerical simulations.

scholarly journals Snow-Cover Area and Runoff Variation under Climate Change in the West Kunlun Mountains

Water ◽  
2019 ◽  
Vol 11 (11) ◽  
pp. 2246 ◽  
Author(s):  
Ma ◽  
Yan ◽  
Zhao ◽  
Kundzewicz
Keyword(s):  
Climate Change ◽  
Snow Cover ◽  
River Basin ◽  
River Flow ◽  
Initial Increase ◽  
Runoff Generation ◽  
The West ◽  
Snow Cover Area ◽  
Kunlun Mountains ◽  
West Kunlun

In recent years, the climate in the arid region of Northwest China has become warmer and wetter; however, glaciers in the north slope of the West Kunlun Mountains (NSWKM) show no obvious recession, and river flow is decreasing or stable. This contrasts with the prevalent response of glaciers to climate change, which is recession and initial increase in glacier discharge followed by decline as retreat continues. We comparatively analyzed multi-timescale variation in temperature–precipitation–snow cover-runoff in the Yarkant River Basin (YRK), Karakax River Basin (KRK), Yurungkax River Basin (YUK), and Keriya River Basin (KRY) in the NSWKM. The Mann–Kendall trend and the mutation–detection method were applied to data obtained from an observation station over the last 60 years (1957–2017) and MODIS snow data (2001–2016). NSWKM temperature and precipitation have continued to increase for nearly 60 years at a mean rate of 0.26 °C/decade and 5.50 mm/decade, respectively, with the most obvious trend (R2 > 0.82) attributed to the KRK and YUK. Regarding changes in the average snow-cover fraction (SCF): YUK (SCF = 44.14%) > YRK (SCF = 38.73%) > KRY (SCF = 33.42%) > KRK (SCF = 33.40%). Between them, the YRK and YUK had decreasing SCA values (slope < −15.39), while the KRK and KRY had increasing SCA values (slope > 1.87). In seasonal variation, the SCF of the three of the basins reaches the maximum value in spring, with the most significant performance in YUK (SCF = 26.4%), except for YRK where SCF in spring was lower than that in winter (−2.6%). The runoff depth of all river basins presented an increasing trend, with the greatest value appearing in the YRK (5.78 mm/decade), and the least value in the YUK (1.58 mm/decade). With the runoff response to climate change, temperature was the main influencing factor of annual and monthly (summer) runoff variations in the YRK, which is consistent with the runoff-generation rule of rivers in arid areas, which mainly rely on ice and snow melt for water supply. However, this rule was not consistent for the YUK and KRK, as it was disturbed by other factors (e.g., slope and slope direction) during runoff generation, resulting in disruptions of their relationship with runoff. This research promotes the study of the response of cold and arid alpine regions to global change and thus better serve regional water resources management.

scholarly journals Topographic control of snow distribution in an alpine watershed of western Canada inferred from spatially-filtered MODIS snow products

2009 ◽  
Vol 13 (3) ◽  
pp. 319-326 ◽  
Author(s):  
J. Tong ◽  
S. J. Déry ◽  
P. L. Jackson
Keyword(s):  
Snow Cover ◽  
Correlation Coefficients ◽  
Time Correlation ◽  
Spatial Filter ◽  
Maximum Difference ◽  
Cloud Coverage ◽  
Snow Cover Extent ◽  
Snow Distribution ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Snow Cover Duration

Abstract. A spatial filter (SF) is used to reduce cloud coverage in Moderate Resolution Imaging Spectroradiometer (MODIS) 8-day maximum snow cover extent products (MOD10A2) from 2000–2007, which are obtained from MODIS daily snow cover extent products (MOD10A1), to assess the topographic control on snow cover fraction (SCF) and snow cover duration (SCD) in the Quesnel River Basin (QRB) of British Columbia, Canada. Results show that the SF reduces cloud coverage and improves by 2% the accuracy of snow mapping in the QRB. The new product developed using the SF method shows larger SCF and longer SCD than MOD10A2, with higher altitudes experiencing longer snow cover and perennial snow above 2500 m. The gradient of SCF with elevation (d(SCF)/dz) during the snowmelt season is 8% (100 m)−1. The average ablation rates of SCF are similar for different 100 m elevation bands at about 5.5% (8 days)−1 for altitudes <1500 m with decreasing values with elevation to near 0% (8 days)−1 for altitudes >2500 m. Different combinations of slopes and aspects also affect the SCF with a maximum difference of 20.9% at a given time. Correlation coefficients between SCD and elevation attain 0.96 (p<0.001). Mean gradients of SCD with elevation are 3.8, 4.3, and 11.6 days (100 m)−1 for the snow onset season, snowmelt season, and entire year, respectively. The SF decreases the standard deviations of SCDs compared to MOD10A2 with a maximum difference near 0.6 day, 0.9 day, and 1.0 day for the snow onset season, snowmelt season, and entire year, respectively.

scholarly journals Use of satellite-derived data for characterization of snow cover and simulation of snowmelt runoff through a distributed physically based model of runoff generation

2010 ◽  
Vol 14 (2) ◽  
pp. 339-350 ◽  
Author(s):  
L. S. Kuchment ◽  
P. Romanov ◽  
A. N. Gelfan ◽  
V. N. Demidov
Keyword(s):  
Snow Cover ◽  
Initial Conditions ◽  
Tree Cover ◽  
Special Focus ◽  
Snowmelt Runoff ◽  
Runoff Generation ◽  
Runoff Simulation ◽  
Physically Based Model ◽  
Physically Based ◽  
Derived Data

Abstract. A technique of using satellite-derived data for constructing continuous snow characteristics fields for distributed snowmelt runoff simulation is presented. The satellite-derived data and the available ground-based meteorological measurements are incorporated in a physically based snowpack model. The snowpack model describes temporal changes of the snow depth, density and water equivalent (SWE), accounting for snow melt, sublimation, refreezing melt water and snow metamorphism processes with a special focus on forest cover effects. The remote sensing data used in the model consist of products include the daily maps of snow covered area (SCA) and SWE derived from observations of MODIS and AMSR-E instruments onboard Terra and Aqua satellites as well as available maps of land surface temperature, surface albedo, land cover classes and tree cover fraction. The model was first calibrated against available ground-based snow measurements and then applied to calculate the spatial distribution of snow characteristics using satellite data and interpolated ground-based meteorological data. The satellite-derived SWE data were used for assigning initial conditions and the SCA data were used for control of snow cover simulation. The simulated spatial distributions of snow characteristics were incorporated in a distributed physically based model of runoff generation to calculate snowmelt runoff hydrographs. The presented technique was applied to a study area of approximately 200 000 km2 including the Vyatka River basin with catchment area of 124 000 km2. The correspondence of simulated and observed hydrographs in the Vyatka River are considered as an indicator of the accuracy of constructed fields of snow characteristics and as a measure of effectiveness of utilizing satellite-derived SWE data for runoff simulation.

Ingredients of German flood events

2020 ◽  
Author(s):  
Ralf Merz ◽  
Larisa Tarasova ◽  
Stefano Basso
Keyword(s):  
Soil Moisture ◽  
Snow Cover ◽  
Rainfall Intensity ◽  
Machine Learning Techniques ◽  
Rainfall Runoff ◽  
Flood Events ◽  
Runoff Generation ◽  
Regional Variability ◽  
Large Variability ◽  
Runoff Events

&lt;p&gt;Floods can be caused by a large variety of different processes, such as short, but intense rainfall bursts, long rainfall events, which are wetting up substantial parts of the catchment, or rain on snow cover or frozen soils. Although there is a plethora on studies analysing or modelling rainfall-runoff processes, it is still not well understood, what rainfall and runoff generation conditions are needed to generate flood runoff and how these characteristics vary between catchments. In this databased approach we decipher the ingredients of flood events occurred in 161 catchments across Germany. For each catchment rainfall-runoff events are separated from observed time series for the period 1950-2013, resulting in about 170,000 single events. A peak-over-threshold approach is used to select flood events out of these runoff events. For each event, spatially and temporally distributed rainfall and runoff generation characteristics, such as snow cover and soil moisture, as well as their interaction are derived. Then we decipher those event characteristics controlling flood event occurrence by using machine learning techniques.&lt;/p&gt;&lt;p&gt;On average, the most important event characteristic controlling flood occurrence in Germany is, as expected, event rainfall volume, followed by the overlap of rainfall and soil moisture and the extent of wet areas in the catchment (area with high soil moisture content). Rainfall intensity is another important characteristic. However, a large variability in its importance is noticeable between dryer catchments where short rainfall floods occur regularly and wetter catchments, where rainfall intensity might be less important for flood generation. To analyse the regional variability of flood ingredients, we cluster the catchments according to similarity in their flood controlling event characteristics and test how good the flood occurrence can be predicted from regionalised event characteristics. Finally, we analyse the regional variability of the flood ingredients in the light of climate and landscape catchment characteristics.&lt;/p&gt;

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