TOPMELT 1.0: a topography-based distribution function approach to snowmelt simulation for hydrological modelling at basin scale

• Main Authors: M. Zaramella, M. Borga, D. Zoccatelli, L. Carturan
• Format: Article
• Language: English
• Published: Copernicus Publications 2019-12-01
• Series: Geoscientific Model Development
• Online Access: https://www.geosci-model-dev.net/12/5251/2019/gmd-12-5251-2019.pdf

<p>Enhanced temperature-index distributed models for snowpack simulation, incorporating air temperature and a term for clear sky potential solar radiation, are increasingly used to simulate the spatial variability of the snow water equivalent. This paper presents a new snowpack model (termed TOPMELT) which integrates an enhanced temperature-index model into the ICHYMOD semi-distributed basin-scale hydrological model by exploiting a statistical representation of the distribution of clear sky potential solar radiation. This is obtained by discretizing the full spatial distribution of clear sky potential solar radiation into a number of radiation classes. The computation required to generate a spatially distributed water equivalent reduces to a single calculation for each radiation class. This turns into a potentially significant advantage when parameter sensitivity and uncertainty estimation procedures are carried out. The radiation index may be also averaged in time over given time periods. Thus, the model resembles a classical temperature-index model when only one radiation class for each elevation band and a temporal aggregation of 1 year is used, whereas it approximates a fully distributed model by increasing the number of the radiation classes and decreasing the temporal aggregation. TOPMELT is integrated within the semi-distributed ICHYMOD model and is applied at an hourly time step over the Aurino Basin (also known as the Ahr River) at San Giorgio (San Giorgio Aurino), a 614&thinsp;km<span class="inline-formula">²</span> catchment in the Upper Adige River basin (eastern Alps, Italy) to examine the sensitivity of the snowpack and runoff model results to the spatial and temporal aggregation of the radiation fluxes. It is shown that the spatial simulation of the snow water equivalent is strongly affected by the aggregation scales. However, limited degradation of the snow simulations is achieved when using 10 radiation classes and 4 weeks as spatial and temporal aggregation scales respectively. Results highlight that the effects of space–time aggregation of the solar radiation patterns on the runoff response are scale dependent. They are minimal at the scale of the whole Aurino Basin, while considerable impact is seen at a basin scale of 5&thinsp;km<span class="inline-formula">²</span>.</p>