Assessing the benefit of snow data assimilation for runoff modeling in Alpine catchments

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 ar...

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Main Authors: N. Griessinger, J. Seibert, J. Magnusson, T. Jonas
Format: Article
Language:English
Published: Copernicus Publications 2016-09-01
Series:Hydrology and Earth System Sciences
Online Access:http://www.hydrol-earth-syst-sci.net/20/3895/2016/hess-20-3895-2016.pdf
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spelling doaj-6dda2ca1dc144262bb3cbd17352b40c42020-11-24T22:41:32ZengCopernicus PublicationsHydrology and Earth System Sciences1027-56061607-79382016-09-012093895390510.5194/hess-20-3895-2016Assessing the benefit of snow data assimilation for runoff modeling in Alpine catchmentsN. Griessinger0J. Seibert1J. Magnusson2T. Jonas3WSL Institute for Snow and Avalanche Research SLF, Davos, SwitzerlandDepartment of Geography, University of Zurich, Zurich, SwitzerlandNorwegian Water Resources and Energy Directorate (NVE), Oslo, NorwayWSL Institute for Snow and Avalanche Research SLF, Davos, SwitzerlandIn 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.http://www.hydrol-earth-syst-sci.net/20/3895/2016/hess-20-3895-2016.pdf
collection DOAJ
language English
format Article
sources DOAJ
author N. Griessinger
J. Seibert
J. Magnusson
T. Jonas
spellingShingle N. Griessinger
J. Seibert
J. Magnusson
T. Jonas
Assessing the benefit of snow data assimilation for runoff modeling in Alpine catchments
Hydrology and Earth System Sciences
author_facet N. Griessinger
J. Seibert
J. Magnusson
T. Jonas
author_sort N. Griessinger
title Assessing the benefit of snow data assimilation for runoff modeling in Alpine catchments
title_short Assessing the benefit of snow data assimilation for runoff modeling in Alpine catchments
title_full Assessing the benefit of snow data assimilation for runoff modeling in Alpine catchments
title_fullStr Assessing the benefit of snow data assimilation for runoff modeling in Alpine catchments
title_full_unstemmed Assessing the benefit of snow data assimilation for runoff modeling in Alpine catchments
title_sort assessing the benefit of snow data assimilation for runoff modeling in alpine catchments
publisher Copernicus Publications
series Hydrology and Earth System Sciences
issn 1027-5606
1607-7938
publishDate 2016-09-01
description 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.
url http://www.hydrol-earth-syst-sci.net/20/3895/2016/hess-20-3895-2016.pdf
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