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© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 24 Oct 2018

Research article | 24 Oct 2018

Review status
This discussion paper is a preprint. A revision of the manuscript is under review for the journal Hydrology and Earth System Sciences (HESS).

Contribution of Potential Evaporation Forecasts to 10-day streamflow forecast skill for the Rhine river

Bart van Osnabrugge1,2, Remko Uijlenhoet2, and Albrecht Weerts1,2 Bart van Osnabrugge et al.
  • 1Deltares, Operational Water Management Department, Delft, The Netherlands
  • 2Wageningen University, Hydrology and Quantitative Water Management Group, Wageningen, The Netherlands

Abstract. Medium term hydrologic forecast uncertainty is strongly dependent on the forecast quality of meteorological variables. Of these variables, the influence of precipitation has been studied most widely, while temperature, radiative forcing and their derived product potential evapotranspiration (PET) have received little attention from the perspective of hydrological forecasting. This study aims to fill this gap by assessing the usability of potential evaporation forecasts for 10-day-ahead streamflow forecasting in the Rhine basin, Europe. In addition, the forecasts of the meteorological variables are compared with observations.

Streamflow reforecasts were performed with the daily wflow_hbv model used in previous studies of the Rhine using the ECMWF 20-year meteorological reforecast dataset. Meteorological forecasts were compared with observed rainfall, temperature, global radiation and potential evaporation for 148 subbasins. Secondly, the effect of using PET climatology versus using observation-based estimates of PET was assessed for hydrological state and for streamflow forecast skill.

We find that: (1) there is considerable skill in the ECMWF reforecasts to predict PET for all seasons, (2) using dynamical PET forcing based on observed temperature and satellite global radiation estimates results in lower evaporation and wetter initial states, but (3) the effect on forecasted 10-day streamflow is limited. Implications of this finding are that it is reasonable to use meteorological forecasts to forecast potential evaporation and use this is in medium-range streamflow forecasts. However, it can be concluded that an approach using PET climatology is also sufficient, most probably not only for the application shown here, but for most models similar to the HBV concept and for moderate climate zones.

As a by-product, this research resulted in gridded datasets for temperature, radiation and potential evaporation based on the Makkink equation for the Rhine basin. The datasets have a spatial resolution of 1.2×1.2km and an hourly timestep for the period from July 1996 through 2015. This dataset complements an earlier precipitation dataset for the same area, period and resolution.

Bart van Osnabrugge et al.
Interactive discussion
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Status: final response (author comments only)
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Bart van Osnabrugge et al.
Data sets

Gridded Hourly Temperature, Radiation and Makkink Potential Evaporation forcing for hydrological modelling in the Rhine basin B. van Osnabrugge and A. Weerts

Gridded precipitation dataset for the Rhine basin made with the genRE interpolation method B. van Osnabrugge, R. Uijlenhoet, and A. Weerts

Bart van Osnabrugge et al.
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Publications Copernicus
Short summary
A correct estimate of the amount of future precipitation is the most important factor in making a good streamflow forecast, but evaporation is also an important component that determines the future discharge of a river. However the relative relevance of detailed evaporation forecasts has not yet been studied extensively. In this study for the Rhine river we found that evaporation forecasts improved streamflow forecasts slightly compared to methods that use statistical information on climatology.
A correct estimate of the amount of future precipitation is the most important factor in making...