Estimation of regional snowline elevation (RSLE) from MODIS images for seasonally snow covered mountain basins

Krajčí, Pavel; Holko, Ladislav; Perdigão, Rui A. P.; Parajka, J.

doi:10.1016/j.jhydrol.2014.08.064

Cited by 62 publications

(76 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The data have been used in a number of studies devoted to various aspects of snow hydrology (Holko et al, 2011) including climate change and vegetation impacts (Holko et al, 2009b;Kostka and Holko, 2000), modelling (Holko et al, 2003(Holko et al, , 2009a, remote sensing Krajčí et al, 2014) and isotopic studies (Holko et al, 2013;Penna et al, 2014).…”

Section: Materials and Methods Study Areamentioning

confidence: 99%

Experimental measurements for improved understanding and simulation of snowmelt events in the Western Tatra Mountains

Krajčí

Danko

Hlavčo

et al. 2016

Journal of Hydrology and Hydromechanics

Self Cite

View full text Add to dashboard Cite

Snow accumulation and melt are highly variable. Therefore, correct modeling of spatial variability of the snowmelt, timing and magnitude of catchment runoff still represents a challenge in mountain catchments for flood forecasting. The article presents the setup and results of detailed field measurements of snow related characteristics in a mountain microcatchment (area 59 000 m 2 , mean altitude 1509 m a. s. l.) in the Western Tatra Mountains, Slovakia obtained in winter 2015. Snow water equivalent (SWE) measurements at 27 points documented a very large spatial variability through the entire winter. For instance, range of the SWE values exceeded 500 mm at the end of the accumulation period (March 2015). Simple snow lysimeters indicated that variability of snowmelt and discharge measured at the catchment outlet corresponded well with the rise of air temperature above 0°C. Temperature measurements at soil surface were used to identify the snow cover duration at particular points. Snow melt duration was related to spatial distribution of snow cover and spatial patterns of snow radiation. Obtained data together with standard climatic data (precipitation and air temperature) were used to calibrate and validate the spatially distributed hydrological model MIKE-SHE. The spatial redistribution of input precipitation seems to be important for modeling even on such a small scale. Acceptable simulation of snow water equivalents and snow duration does not guarantee correct simulation of peakflow at shorttime (hourly) scale required for example in flood forecasting. Temporal variability of the stream discharge during the snowmelt period was simulated correctly, but the simulated discharge was overestimated.

show abstract

Section: Materials and Methods Study Areamentioning

confidence: 99%

Experimental measurements for improved understanding and simulation of snowmelt events in the Western Tatra Mountains

Krajčí

Danko

Hlavčo

et al. 2016

Journal of Hydrology and Hydromechanics

Self Cite

View full text Add to dashboard Cite

show abstract

“…Lapin et al (2007) evaluated changes in the number of days with snow at five stations in Tatra Results of the mean index of scatter analysis (i.e. variability around the snow line, Krajčí et al, 2014) show values between 3.4% in lowland and 12.2% in mountain basins, which is comparable or even less than found in Krajčí et al (2014).…”

Section: Discussionmentioning

confidence: 98%

“…Regional snow line elevation (SL) is determined from the MODIS satellite data by the RSLE methodology (Krajčí et al, 2014). The cornerstone of the approach is to find an elevation for which the sum of snow covered pixels below (P S ) and land pixels above the snow line (P L ) is minimized (Fig.…”

Section: Methodsmentioning

confidence: 99%

“…Therefore, we use linear interpolation to calculate snow line elevation for days when cloud coverage exceeds 70%. The selection of this threshold is based on previous investigations of Krajčí et al (2014). Interpolated SL values so allow consistent calculation of snow cover characteristics for all basins.…”

Section: Methodsmentioning

confidence: 99%

“…One of the most efficient approaches for the mountains is the snow line approach (Parajka et al, 2010). Krajčí et al (2014) proposed and evaluated a regional snow line elevation method (RSLE) in the upper Váh basin and reported an overall accuracy between 73% and 92%. The average accuracy in the forest exceeded 90% for the period January to March.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Variability of snow line elevation, snow cover area and depletion in the main Slovak basins in winters 2001–2014

Krajčí

Holko

Parajka

2016

Journal of Hydrology and Hydromechanics

Self Cite

View full text Add to dashboard Cite

Spatial and temporal variability of snow line (SL) elevation, snow cover area (SCA) and depletion (SCD) in winters 2001-2014 is investigated in ten main Slovak river basins (the Western Carpathians). Daily satellite snow cover maps from MODIS Terra (MOD10A1, V005) and Aqua (MYD10A1, V005) with resolution 500 m are used.The results indicate three groups of basins with similar variability in the SL elevation. The first includes basins with maximum elevations above 1500 m a.s.l. (Poprad, Upper Váh, Hron, Hornád). Winter median SL is equal or close to minimum basin elevation in snow rich winters in these basins. Even in snow poor winters is SL close to the basin mean. Second group consists of mid-altitude basins with maximum elevation around 1000 m a.s.l. (Slaná, Ipeľ, Nitra, Bodrog). Median SL varies between 150 and 550 m a.s.l. in January and February, which represents approximately 40-80% snow coverage. Median SL is near the maximum basin elevation during the snow poor winters. This means that basins are in such winters snow free approximately 50% of days in January and February. The third group includes the Rudava/Myjava and Lower Váh/Danube. These basins have their maximum altitude less than 700 m a.s.l. and only a small part of these basins is covered with snow even during the snow rich winters.The evaluation of SCA shows that snow cover typically starts in December and last to February. In the highest basins (Poprad, Upper Váh), the snow season sometimes tends to start earlier (November) and lasts to March/April. The median of SCA is, however, less than 10% in these months. The median SCA of entire winter season is above 70% in the highest basins (Poprad, Upper Váh, Hron), ranges between 30-60% in the mid-altitude basins (Hornád, Slaná, Ipeľ, Nitra, Bodrog) and is less than 1% in the Myjava/Rudava and Lower Váh/Danube basins. However, there is a considerable variability in seasonal coverage between the years. Our results indicate that there is no significant trend in mean SCA in the Snow depletion curves (SDC) do not have a simple evolution in most winters. The snowmelt tends to start between early February and the end of March. The snowmelt lasts between 8 and 15 days on average in lowland and high mountain basins, respectively. Interestingly, the variability in SDC between the winters is much larger than between the basins.

show abstract

Snowmelt characteristics in a pristine mountain catchment of the Jalovecký Creek, Slovakia, over the last three decades

Holko

Danko

Sleziak

2021

Hydrological Processes

Self Cite

View full text Add to dashboard Cite

The Jalovecký Creek catchment, Slovakia (area 22.2 km 2 , mean elevation 1500 m a.s. l.), is likely the last big valley complex in the Carpathian Mountains, in which the hydrological cycle is still governed by natural processes. Hydrological research is conducted there since the end of the 1980s. The overall mission of the research is to increase the knowledge about the hydrological cycle in the highest part of the Carpathians. The research agenda, briefly introduced in the first part of this article, is focused on water balance, snow accumulation and melt and runoff formation. Recent analysis of precipitation, discharge, snow cover and isotopic data from period 1989-2018 indicates that hydrological cycle has become more dynamic since 2014.Although several indicators suggest that it could be related to the cold part of the year, direct links with snow storage and the contribution of snowmelt water to catchment runoff were not confirmed. The second part of the article is therefore focused on an analysis of daily cycles in streamflow in March to June 1988-2018 to obtain a deeper insight into the snowmelt process. We describe characteristics of the cycles and examine their variability over the study period. The results indicate that less snow at the lowest elevations (800-1150 m a.s.l.) since 2009 could have influenced the cessation of the cycles in June since 2010. The possible role of the decreased amount of snow at the lowest elevations in changes in runoff characteristics is also suggested by an increase in time lags between maximum discharges during the events and maximum air temperatures preceding discharge maxima measured near the catchment outlet (at 750 m a.s.l.) in spring 2018 compared to springs with a similar number of streamflow cycles in the years 1988, 2000 and 2009. Wavelet analysis did not indicate changes in global power spectra in hourly discharge and air temperature data.

show abstract

Estimation of regional snowline elevation (RSLE) from MODIS images for seasonally snow covered mountain basins

Cited by 62 publications

References 13 publications

Experimental measurements for improved understanding and simulation of snowmelt events in the Western Tatra Mountains

Experimental measurements for improved understanding and simulation of snowmelt events in the Western Tatra Mountains

Variability of snow line elevation, snow cover area and depletion in the main Slovak basins in winters 2001–2014

Snowmelt characteristics in a pristine mountain catchment of the Jalovecký Creek, Slovakia, over the last three decades

Contact Info

Product

Resources

About