z-logo
open-access-imgOpen Access
Deterministic evaluation of ensemble streamflow predictions in Sweden
Author(s) -
Anna Johnell,
Göran Lindström,
Jonas Olsson
Publication year - 2007
Publication title -
hydrology research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.665
H-Index - 48
eISSN - 1996-9694
pISSN - 0029-1277
DOI - 10.2166/nh.2007.022
Subject(s) - streamflow , categorical variable , quartile , statistics , mean squared error , precipitation , environmental science , forecast skill , ensemble forecasting , quantitative precipitation forecast , econometrics , climatology , mathematics , meteorology , drainage basin , geography , geology , confidence interval , cartography
A system for ensemble streamflow prediction, ESP, has been operational at SMHI since July 2004, based on 50 meteorological ensemble forecasts from ECMWF. Hydrological ensemble forecasts are produced daily for 51 basins in Sweden. All ensemble members, as well as statistics (minimum, 25% quartile, median, 75% quartile and maximum), are stored in a database. This paper presents an evaluation of the first 18 months of ESP median forecasts from this system, and in particular their performance in comparison with today's categorical forecast. The evaluation was made in terms of three statistical measures: bias B , root mean square error RMSE and absolute peak flow error PE . For ESP forecasts the bias ranged between -20% and 80% with a systematic overestimation for Sweden as a whole. A comparison between bias in input precipitation and ESP output, respectively, revealed only a weak relationship, but streamflow overestimation is likely related mainly to model properties. The results from the streamflow forecast comparison showed that the ESP median in deterministic terms performs overall as well as the presently used categorical forecast. Further, ESP has the advantage of providing at least a qualitative measure of the uncertainty in the forecasts, with probability forecasts being the ultimate goal.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom