Seasonal, spatially distributed modelling of accumulation and melting of snow for computing runoff in a long‐term, large‐basin water balance model

Abstract

Abstract:In mountainous regions of mid latitudes, the accumulation and melting of snow plays an important role for the seasonal water balance. These processes not only exhibit a strong seasonality, but also a high spatial variability, which has to be accounted for when establishing distributed water balances in alpine environments. A methodology was developed for seasonal, spatially distributed modelling of accumulation and melting of snow and was embedded in a water balance model that uses only monthly values of precipitation and air temperature as meteorological input data. Hence, this methodology can also be applied in regions with limited data availability. The model uses a conceptual approach with a spatial resolution of a 1 km ð 1 km raster. Snow accumulation is computed from temperature and precipitation data. Snowmelt is computed with a temperature-index approach. A direct application of these simple concepts using monthly inputs would not yield satisfying results. Therefore, precipitation is disaggregated into rainfall and snowfall by using a transition range considering temporal variations of temperature within a month and the mean deviation of temperature on days with and without precipitation. For modelling snowmelt, two different approaches were tested to incorporate variable temperatures within a month. The model was applied for the whole of Austria (84 000 km 2 ) and simulated runoff was compared with observed runoff at 135 gauges for a 30 year period. The model performs best in high and medium mountainous catchments. Lower model performances are achieved in lowland catchments, where the contribution of snowmelt to river runoff decreases. It can be concluded that modelling accumulation and melting of snow in mountainous areas with monthly data yields good results if a temporal disaggregation of precipitation and temperature is applied.

A conceptual, distributed snow redistribution model

“…However, redistribution of snow requires only two additional parameters but allows for more realistic boundaries (see Kling et al, 2006) of the snowmelt factors (see Supplement of this article). However, more work needs to be carried out to account for that issue.…”

“…12). Yet, accounting for snow redistribution allows the modeller to use D U values within or close to the range proposed by Kling et al (2006), while the standard version of the model leads to the best results if higher and therefore unrealistic D U values are used (see the Supplement of this article).…”

Toward improved identification of hydrological models: A diagnostic evaluation of the “abcd” monthly water balance model for the conterminous United States

“…Similarly, most regions seem to require more sophisticated representations of the snow accumulation and melt process. It seems quite reasonable to suggest that some representation of the submonthly temporal and/or subcatchment spatial distributions of hydrological fluxes may actually prove to be critical [e.g., Kling et al, 2006], or perhaps some process-based formulation that approximates the terms of the energy balance using daily data [Walter et al, 2005]. And while, in some cases, it may be possible to parameterize these subscale processes to enable continued modeling at the monthly catchment scale, in other cases such an approach may fail with the only recourse being to model at some finer spa-tiotemporal scale.…”

Cloud removal methodology from MODIS snow cover product

“…The study by Singh et al (2006) in the Himalayan basin reported an 87% glacier melt contribution to the total runoff. Kling et al (2006) carried out a study for the whole of Austria and found the runoff coefficient for snowmelt in the alpine parts to be greater than 80%, and for the lowlands less than 50%.…”