Abstract

Abstract. In Alpine catchments, snowmelt is often a major contribution to runoff. Therefore, modeling snow processes is important when concerned with flood or drought forecasting, reservoir operation and inland waterway management. In this study, we address the question of how sensitive hydrological models are to the representation of snow cover dynamics and whether the performance of a hydrological model can be enhanced by integrating data from a dedicated external snow monitoring system. As a framework for our tests we have used the hydrological model HBV (Hydrologiska Byråns Vattenbalansavdelning) in the version HBV-light, which has been applied in many hydrological studies and is also in use for operational purposes. While HBV originally follows a temperature-index approach with time-invariant calibrated degree-day factors to represent snowmelt, in this study the HBV model was modified to use snowmelt time series from an external and spatially distributed snow model as model input. The external snow model integrates three-dimensional sequential assimilation of snow monitoring data with a snowmelt model, which is also based on the temperature-index approach but uses a time-variant degree-day factor. The following three variations of this external snow model were applied: (a) the full model with assimilation of observational snow data from a dense monitoring network, (b) the same snow model but with data assimilation switched off and (c) a downgraded version of the same snow model representing snowmelt with a time-invariant degree-day factor. Model runs were conducted for 20 catchments at different elevations within Switzerland for 15 years. Our results show that at low and mid-elevations the performance of the runoff simulations did not vary considerably with the snow model version chosen. At higher elevations, however, best performance in terms of simulated runoff was obtained when using the snowmelt time series from the snow model, which utilized data assimilation. This was especially true for snow-rich years. These findings suggest that with increasing elevation and the correspondingly increased contribution of snowmelt to runoff, the accurate estimation of snow water equivalent (SWE) and snowmelt rates has gained importance.

Highlights

  • Snowmelt provides a dominant contribution to runoff and groundwater storages in mountainous regions

  • For the data assimilation for the full snow model used in this study we considered daily snow depth measurements from both manual and automatic monitoring stations

  • Based on daily runoff data measured over a period of years at 20 catchments in Switzerland, we evaluated the sensitivity of a conceptual hydrological modeling framework to snowmelt input from snow models of different complexity

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Summary

Introduction

Snowmelt provides a dominant contribution to runoff and groundwater storages in mountainous regions. In such areas, modeling snow processes is crucial for resource management as well as for flood and drought forecasting. Since erroneous simulations of snow accumulation can bias the amount and timing of simulated snowmelt, accurately modeling both processes is important for runoff predictions. Computational resources often constrain operational applications as timely model outputs are required. To cope with these challenges, many hydrological models make use of the temperature-index (TI) melt method instead of Published by Copernicus Publications on behalf of the European Geosciences Union

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