Monthly streamflow forecasting at varying spatial scales in the Rhine basin

Schick, Simon; Rössler, Ole Kristen; Weingartner, Rolf (2018). Monthly streamflow forecasting at varying spatial scales in the Rhine basin. Hydrology and earth system sciences, 22(2), pp. 929-942. European Geosciences Union EGU 10.5194/hess-22-929-2018

hess-22-929-2018.pdf - Published Version
Available under License Creative Commons: Attribution (CC-BY).

Download (1MB) | Preview

Model output statistics (MOS) methods can be used to empirically relate an environmental variable of interest to predictions from earth system models (ESMs). This variable often belongs to a spatial scale not resolved by the ESM. Here, using the linear model fitted by least squares, we regress monthly mean streamflow of the Rhine River at Lobith and Basel against seasonal predictions of precipitation, surface air temperature, and runoff from the European Centre for Medium-Range Weather Forecasts. To address potential effects of a scale mismatch between the ESM's horizontal grid resolution and the hydrological application, the MOS method is further tested with an experiment conducted at the subcatchment scale. This experiment applies the MOS method to 133 additional gauging stations located within the Rhine basin and combines the forecasts from the subcatchments to predict streamflow at Lobith and Basel. In doing so, the MOS method is tested for catchments areas covering 4 orders of magnitude. Using data from the period 1981–2011, the results show that skill, with respect to climatology, is restricted on average to the first month ahead. This result holds for both the predictor combination that mimics the initial conditions and the predictor combinations that additionally include the dynamical seasonal predictions. The latter, however, reduce the mean absolute error of the former in the range of 5 to 12 %, which is consistently reproduced at the subcatchment scale. An additional experiment conducted for 5-day mean streamflow indicates that the dynamical predictions help to reduce uncertainties up to about 20 days ahead, but it also reveals some shortcomings of the present MOS method.

Item Type:

Journal Article (Original Article)


08 Faculty of Science > Institute of Geography > Physical Geography > Unit Hydrology
10 Strategic Research Centers > Oeschger Centre for Climate Change Research (OCCR)
08 Faculty of Science > Institute of Geography
08 Faculty of Science > Institute of Geography > Physical Geography

UniBE Contributor:

Schick, Simon; Rössler, Ole Kristen and Weingartner, Rolf


900 History > 910 Geography & travel
500 Science > 550 Earth sciences & geology




European Geosciences Union EGU




Simon Andreas Schick

Date Deposited:

01 May 2018 14:43

Last Modified:

22 Oct 2019 21:07

Publisher DOI:





Actions (login required)

Edit item Edit item
Provide Feedback