Contribution of potential evaporation forecasts to 10-day streamflow forecast skill for the Rhine River

Abstract

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, and (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 also 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 1.2×1.2 km and an hourly time step for the period from July 1996 through 2015. This dataset complements an earlier precipitation dataset for the same area, period and resolution.

Comparison of probabilistic post-processing approaches for improving numerical weather prediction-based daily and weekly reference evapotranspiration forecasts

“…Here, reliability refers to statistical consistency (as in Toth et al, 2003), which is met when the observations are statistically indistinguishable from the forecast ensembles (Wilks, 2011). To obtain the rank histogram, we get the rank of the observation when merged into the ordered ensemble of ET 0 forecasts and then plot the rank's histogram.…”

“…Even more recently, Sloughter et al (2010) extended the original BMA method of Raftery et al (2005) for wind speed by considering a gamma distribution for modeling the distribution of every member of the ensemble, which considerably improved the CRPS, the absolute errors, and the coverage. Vanvyve et al (2015) and Zhang et al (2015), in comparison, used the analog method following the methodology of Delle Monache (2013). Accurate solar radiation forecasting is particularly challenging because it requires a detailed representation of the cloud fields (Verzijlbergh et al, 2015), which are usually not resolved well by the NWP models.…”

A Vision for Hydrological Prediction

“…Pathways for facing these challenges have recently merged. For instance, in IMPREX, a high-resolution (both temporally and spatially) dataset of area-average precipitation, temperature and potential evapotranspiration (based on satellite downwelling shortwave radiation) was developed for the Rhine River and used to verify the ECMWF ensemble weather forecasts [21,22]. These high-resolution datasets have the advantage of better representing the heterogeneities that are not captured by the relatively coarse grid scale of the atmospheric model.…”

A distributed simple dynamical systems approach (dS2 v1.0) for computationally efficient hydrological modelling at high spatio-temporal resolution

“…The model was applied at a 1 km 2 resolution, using distributed forcing. We used the same forcing data as Melsen et al (2016a), where the data are interpolated using the pre-processing tool WINMET of the PREVAH modelling system (Viviroli et al, 2009;Fundel and Zappa, 2011). For a more detailed explanation of the basin and the data used, we refer to Melsen et al (2016a).…”