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Technical Note : Initial assessment of a multi-method approach to spring-flood forecasting in Sweden

Olsson, J. LU ; Uvo, C. B. LU orcid ; Foster, K. LU and Yang, W. LU (2016) In Hydrology and Earth System Sciences 20(2). p.659-667
Abstract

Hydropower is a major energy source in Sweden, and proper reservoir management prior to the spring-flood onset is crucial for optimal production. This requires accurate forecasts of the accumulated discharge in the spring-flood period (i.e. the spring-flood volume, SFV). Today's SFV forecasts are generated using a model-based climatological ensemble approach, where time series of precipitation and temperature from historical years are used to force a calibrated and initialized set-up of the HBV model. In this study, a number of new approaches to spring-flood forecasting that reflect the latest developments with respect to analysis and modelling on seasonal timescales are presented and evaluated. Three main approaches, represented by... (More)

Hydropower is a major energy source in Sweden, and proper reservoir management prior to the spring-flood onset is crucial for optimal production. This requires accurate forecasts of the accumulated discharge in the spring-flood period (i.e. the spring-flood volume, SFV). Today's SFV forecasts are generated using a model-based climatological ensemble approach, where time series of precipitation and temperature from historical years are used to force a calibrated and initialized set-up of the HBV model. In this study, a number of new approaches to spring-flood forecasting that reflect the latest developments with respect to analysis and modelling on seasonal timescales are presented and evaluated. Three main approaches, represented by specific methods, are evaluated in SFV hindcasts for the Swedish river Vindelälven over a 10-year period with lead times between 0 and 4 months. In the first approach, historically analogue years with respect to the climate in the period preceding the spring flood are identified and used to compose a reduced ensemble. In the second, seasonal meteorological ensemble forecasts are used to drive the HBV model over the spring-flood period. In the third approach, statistical relationships between SFV and the large-sale atmospheric circulation are used to build forecast models. None of the new approaches consistently outperform the climatological ensemble approach, but for early forecasts improvements of up to 25% are found. This potential is reasonably well realized in a multi-method system, which over all forecast dates reduced the error in SFV by ∼4%. This improvement is limited but potentially significant for e.g. energy trading.

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Please use this url to cite or link to this publication:
author
; ; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
in
Hydrology and Earth System Sciences
volume
20
issue
2
pages
9 pages
publisher
European Geophysical Society
external identifiers
  • scopus:84958225375
ISSN
1027-5606
DOI
10.5194/hess-20-659-2016
language
English
LU publication?
yes
id
8fa19a5c-92a1-484d-8d75-e0c8f067d6a6
date added to LUP
2018-11-01 12:15:34
date last changed
2022-03-17 18:46:44
@article{8fa19a5c-92a1-484d-8d75-e0c8f067d6a6,
  abstract     = {{<p>Hydropower is a major energy source in Sweden, and proper reservoir management prior to the spring-flood onset is crucial for optimal production. This requires accurate forecasts of the accumulated discharge in the spring-flood period (i.e. the spring-flood volume, SFV). Today's SFV forecasts are generated using a model-based climatological ensemble approach, where time series of precipitation and temperature from historical years are used to force a calibrated and initialized set-up of the HBV model. In this study, a number of new approaches to spring-flood forecasting that reflect the latest developments with respect to analysis and modelling on seasonal timescales are presented and evaluated. Three main approaches, represented by specific methods, are evaluated in SFV hindcasts for the Swedish river Vindelälven over a 10-year period with lead times between 0 and 4 months. In the first approach, historically analogue years with respect to the climate in the period preceding the spring flood are identified and used to compose a reduced ensemble. In the second, seasonal meteorological ensemble forecasts are used to drive the HBV model over the spring-flood period. In the third approach, statistical relationships between SFV and the large-sale atmospheric circulation are used to build forecast models. None of the new approaches consistently outperform the climatological ensemble approach, but for early forecasts improvements of up to 25% are found. This potential is reasonably well realized in a multi-method system, which over all forecast dates reduced the error in SFV by ∼4%. This improvement is limited but potentially significant for e.g. energy trading.</p>}},
  author       = {{Olsson, J. and Uvo, C. B. and Foster, K. and Yang, W.}},
  issn         = {{1027-5606}},
  language     = {{eng}},
  month        = {{02}},
  number       = {{2}},
  pages        = {{659--667}},
  publisher    = {{European Geophysical Society}},
  series       = {{Hydrology and Earth System Sciences}},
  title        = {{Technical Note : Initial assessment of a multi-method approach to spring-flood forecasting in Sweden}},
  url          = {{http://dx.doi.org/10.5194/hess-20-659-2016}},
  doi          = {{10.5194/hess-20-659-2016}},
  volume       = {{20}},
  year         = {{2016}},
}