Degree–day factors for snow and ice for Dokriani Glacier, Garhwal Himalayas

Singh, Pratap; Kumar, Naresh; Arora, Manohar

doi:10.1016/s0022-1694(00)00249-3

Cited by 137 publications

(107 citation statements)

References 12 publications

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“…The degree-day factor for ice can be assumed to be higher than for snow because of the higher snow albedo, meaning that the utilization of the available energy is lower for snow than for ice (Braithwaite and Olesen, 1989;Rango and Martinec, 1995). This theoretical consideration has been confirmed by hydro-glaciological studies (Singh et al, 2000).…”

Section: Selection Of An Initial Parameter Set By Random Generationmentioning

confidence: 80%

A conceptual glacio-hydrological model for high mountainous catchments

Schaefli

Hingray

Niggli

et al. 2005

Hydrol. Earth Syst. Sci.

194

196

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Abstract. In high mountainous catchments, the spatial precipitation and therefore the overall water balance is generally difficult to estimate. The present paper describes the structure and calibration of a semi-lumped conceptual glaciohydrological model for the joint simulation of daily discharge and annual glacier mass balance that represents a better integrator of the water balance. The model has been developed for climate change impact studies and has therefore a parsimonious structure; it requires three input times series -precipitation, temperature and potential evapotranspiration -and has 7 parameters to calibrate. A multi-signal approach considering daily discharge and -if available -annual glacier mass balance has been developed for the calibration of these parameters. The model has been calibrated for three different catchments in the Swiss Alps having glaciation rates between 37% and 52%. It simulates well the observed daily discharge, the hydrological regime and some basic glaciological features, such as the annual mass balance.

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Section: Selection Of An Initial Parameter Set By Random Generationmentioning

confidence: 80%

A conceptual glacio-hydrological model for high mountainous catchments

Schaefli

Hingray

Niggli

et al. 2005

Hydrol. Earth Syst. Sci.

194

196

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“…The study of Kuusisto (1980) in Finland found DDF S to increase sharply in early April, approximately doubling during this month due to increasing solar radiation. Singh and Kumar (1996) and Singh et al (2000) demonstrated a seasonal decrease of DDF S with increasing albedo due to seasonal changes of land surface characteristics. Spatial variations of basin topography, such as elevation, terrain slope, aspect and terrain shading change the spatial energy conditions for snowmelt and lead to significant variations of DDF S (Marsh et al, 2012;Bormann et al, 2014).…”

Section: Z H He Et Al: Estimating Degree-day Factors From Modis Fomentioning

confidence: 95%

“…Melt runoff models generally fall into two categories: energy balance models, and temperature-index models (Rango and Martinec, 1979;Howard, 1996;Kane et al, 1997;Singh et al, 2000;Fierz et al, 2003). Temperature-index models operating on a basin wide scale are much more popular for operational purposes due to the following four reasons (Hock, 2003): (1) wide availability of air temperature data, (2) relatively easy interpolation and forecasting possibilities of air temperature, (3) generally good model performance and (4) computational simplicity.…”

Section: Introductionmentioning

confidence: 99%

Estimating degree-day factors from MODIS for snowmelt runoff modeling

Parajka

Tian

et al. 2014

Hydrol. Earth Syst. Sci.

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Abstract. Degree-day factors are widely used to estimate snowmelt runoff in operational hydrological models. Usually, they are calibrated on observed runoff, and sometimes on satellite snow cover data. In this paper, we propose a new method for estimating the snowmelt degree-day factor (DDF S ) directly from MODIS snow covered area (SCA) and ground-based snow depth data without calibration. Subcatchment snow volume is estimated by combining SCA and snow depths. Snow density is estimated to be the ratio between observed precipitation and changes in the snow volume for days with snow accumulation. Finally, DDF S values are estimated to be the ratio between changes in the snow water equivalent and difference between the daily temperature and the melt threshold value for days with snow melt. We compare simulations of basin runoff and snow cover patterns using spatially variable DDF S estimated from snow data with those using spatially uniform DDF S calibrated on runoff. The runoff performances using estimated DDF S are slightly improved, and the simulated snow cover patterns are significantly more plausible. The new method may help reduce some of the runoff model parameter uncertainty by reducing the total number of calibration parameters. This method is applied to the Lienz catchment in East Tyrol, Austria, which covers an area of 1198 km 2 . Approximately 70 % of the basin is covered by snow in the early spring season.

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“…All the parameters except the DDF have been estimated as monthly average values from the historical dataset of input variables obtained from the previously mentioned meteorological stations. DDF is represented as an annually constant value, obtained from an experimental study done in a snow and glacier fed basin in western Himalayas 25 . The initial LR value has been approximated to the mean monthly near-surface LR between two meteorological stations, Kaza and Kalpa (Figure 1), since LR between Kaza and Namigia has been found to have exceptionally high values (of the order of 2.4C/100 m).…”

Section: Methodsmentioning

confidence: 99%

Investigating the Performance of Snowmelt Runoff Model Using Temporally Varying Near-Surface Lapse Rate in Western Himalayas

Kulshrestha¹,

Ramsankaran²,

Kumar³

et al. 2018

Current Science

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The present study assesses the effect of accounting the temporal variation of near-surface lapse rate in the conceptual, degree-day snowmelt runoff model simulations in a cold-desert region of Himalayas. The nearsurface lapse rate over Spiti basin shows seasonal variation during a year. The results obtained show that the inclusion of monthly variation of lapse rate in the hydrological modelling is able to capture the observed hydrograph more efficiently than when an annually constant value of lapse rate is employed. Based on our results and considering the available data, a monthly representation of near-surface lapse rates in the temperature index based models is recommended for Himalayan basins.

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Degree–day factors for snow and ice for Dokriani Glacier, Garhwal Himalayas

Cited by 137 publications

References 12 publications

A conceptual glacio-hydrological model for high mountainous catchments

A conceptual glacio-hydrological model for high mountainous catchments

Estimating degree-day factors from MODIS for snowmelt runoff modeling

Investigating the Performance of Snowmelt Runoff Model Using Temporally Varying Near-Surface Lapse Rate in Western Himalayas

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