DOI: 10.5194/hess-20-3895-2016
Scopus记录号: 2-s2.0-84988700641
论文题名: Assessing the benefit of snow data assimilation for runoff modeling in Alpine catchments
作者: Griessinger N ; , Seibert J ; , Magnusson J ; , Jonas T
刊名: Hydrology and Earth System Sciences
ISSN: 10275606
出版年: 2016
卷: 20, 期: 9 起始页码: 3895
结束页码: 3905
语种: 英语
Scopus关键词: Catchments
; Climate models
; Hydrology
; Monitoring
; Reservoir management
; Reservoirs (water)
; Runoff
; Snow melting systems
; Time series
; Weather forecasting
; Accurate estimation
; Data assimilation
; Hydrological modeling
; Hydrological models
; Reservoir operation
; Runoff simulation
; Snow water equivalent
; Snow-cover dynamics
; Snow
; assessment method
; catchment
; data assimilation
; drought
; flood
; hydrological modeling
; reservoir
; runoff
; snow cover
; snow water equivalent
; snowmelt
; spatial distribution
; Switzerland
; Hepatitis B virus
英文摘要: 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 Byräns 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. © 2016 Author(s). Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/78726
Appears in Collections: 气候变化事实与影响
There are no files associated with this item.
作者单位: WSL Institute for Snow, Avalanche Research SLF, Davos, Switzerland; Department of Geography, University of Zurich, Zurich, Switzerland; Norwegian Water Resources and Energy Directorate, Oslo, Norway
Recommended Citation:
Griessinger N,, Seibert J,, Magnusson J,et al. Assessing the benefit of snow data assimilation for runoff modeling in Alpine catchments[J]. Hydrology and Earth System Sciences,2016-01-01,20(9)