Many studies suggest that high-density rain gauge networks are required to capture the rainfall heterogeneities necessary to accurately describe the components of the hydrological cycle. However, equipping and maintaining a high-density rain gauge network will also involve high costs. Although many studies provided useful insights on the required accuracy of rainfall estimates to accurately describe the components of the hydrological cycle, most of these studies focused on streamflow simulations, large river basins or urban environments. The objective of this study is therefore to evaluate the impact of uncertainties in areal rainfall, estimated at several spatial resolutions, on hydrological simulations of a small ∼6.5 km² rural lowland catchment. The approach followed in this study is to force a calibrated spatially-distributed hydrological model (SPHY) with rainfall retrieved from an X-band radar and various synthetic rainfall products, calculated using bootstrap samples of a varying number of radar pixels, treated as virtual rain gauge locations within the catchment. This enables us to determine the most appropriate resolution of rainfall data to accurately describe the hydrology of a small rural lowland catchment. We found that the use of one rain gauge to estimate the catchment's areal rainfall may lead to a potential error of more than six times the average hourly rainfall. This may lead to uncertainties in simulated discharge that approach 60% of the average hourly discharge. More than 40 rain gauges are required to reduce the potential error in areal rainfall estimation to values <0.1 mm h⁻¹. The associated uncertainty in discharge simulations is 20% if 10 rain gauges are used, and 10% if 40 rain gauges are used. The simulation of soil moisture contents and evapotranspiration rates are hardly affected by the number of rain gauges used to estimate the areal rainfall, which is due to the high saturated hydraulic conductivities of the top-soil. At least 12 gauges per km² are required to capture the spatial rainfall variation that is present in radar rainfall estimates. Analysis of an individual 18-h rainfall event revealed that the uncertainty in peak areal rainfall estimated using one rain gauge may range between −100% and 600%. The associated uncertainty in simulated discharge for this event ranges between −67 and 233%. With 25 rain gauges the uncertainty in simulated discharge is still in the range of −17 to 33%.

Because of global warming, the hydrologic behavior of the Rhine basin is expected to shift from a combined snowmelt-and rainfall-driven regime to a more rainfall-dominated regime. Previous impact assessments have indicated that this leads, on average, to increasing streamflow by ~30% in winter and spring and decreasing streamflow by a similar value in summer. In this study, high-resolution (0.088°) regional climate scenarios conducted with the regional climate model REMO (REgional MOdel) for the Rhine basin are used to force a macroscale hydrological model. These climate scenarios are based on model output from the ECHAM5-Max Planck Institute Ocean Model (MPI-OM) global climate model, which is in turn forced by three Special Report on Emissions Scenarios (SRES) emission scenarios: A2, A1B, and B1. The Variable Infiltration Capacity model (VIC; version 4.0.5) is used to examine changes in streamflow at various locations throughout the Rhine basin. Average streamflow, peak flows, low flows, and several water balance terms are evaluated for both the first and second half of the twenty-first century. The results reveal a distinct contrast between those periods. The first half is dominated by increased precipitation, causing increased streamflow throughout the year. During the second half of the century, a streamflow increase in winter/spring and a decrease in summer is found, similar to previous studies. This is caused by 1) temperature and evapotranspiration, which are considerably higher during the second half of the century; 2) decreased precipitation in summer; and 3) an earlier start of the snowmelt season. Magnitudes of peak flows increase during both periods, and the magnitudes of streamflow droughts increase only during the second half of the century.

In many climate impact studies hydrological models are forced with meteorological data without an attempt to assess the quality of these data. The objective of this study was to compare downscaled ERA15 (ECMWF-reanalysis data) precipitation and temperature with observed precipitation and temperature and apply a bias correction to these forcing variables. Precipitation is corrected by fitting it to the mean and coefficient of variation (CV) of the observations. Temperature is corrected by fitting it to the mean and standard deviation of the observations. It appears that the uncorrected ERA15 is too warm and too wet for most of the Rhine basin. The bias correction leads to satisfactory results, precipitation and temperature differences decreased significantly, although there are a few years for which the correction of precipitation is less satisfying. Corrections were largest during summer for both precipitation and temperature. For precipitation alone large corrections were applied during September and October as well. Besides the statistics the correction method was intended to correct for, it is also found to improve the correlations for the fraction of wet days and lag-1 autocorrelations between ERA15 and the observations. For the validation period temperature is corrected very well, but for precipitation the RMSE of the daily difference between modeled and observed precipitation has increased for the corrected situation. When taking random years for calibration, and the remaining years for validation, the spread in the mean bias error (MBE) becomes larger for the corrected precipitation during validation, but the overal average MBE has decreased.

The Meuse is an important river in Western Europe, which is almost exclusively rain-fed. Projected changes in precipitation characteristics due to climate change, therefore, are expected to have a considerable effect on the hydrological regime of the river Meuse. We focus on an important tributary of the Meuse, the Ourthe, measuring about 1600 km2. The well-known hydrological model HBV is forced with three high-resolution (0.088°) regional climate scenarios, each based on one of three different IPCC CO2 emission scenarios: A1B, A2 and B1. To represent the current climate, a reference model run at the same resolution is used. Prior to running the hydrological model, the biases in the climate model output are investigated and corrected for. Different approaches to correct the distributed climate model output using single-site observations are compared. Correcting the spatially averaged temperature and precipitation is found to give the best results, but still large differences exist between observations and simulations. The bias corrected data are then used to force HBV. Results indicate a small increase in overall discharge, especially for the B1 scenario during the beginning of the 21st century. Towards the end of the century, all scenarios show a decrease in summer discharge, partially because of the diminished buffering effect by the snow pack, and an increased discharge in winter. It should be stressed, however, that we used results from only one GCM (the only one available at such a high resolution). It would be interesting to repeat the analysis with multiple models.

The hydrological regime of the Rhine basin is expected to shift from a combined snowmelt-rainfall regime to a more rainfall-dominated regime because of climate change, leading to more extreme flood peaks and low flows. Land use changes may reinforce the effects of this shift through urbanization or may counteract them through, for example, afforestation. In this study, we investigate the effect of projected land use change scenarios on river discharge. Sensitivity of mean and extreme discharge in the Rhine basin to land use changes is investigated at various spatial scales. The variable infiltration capacity (VIC) (version 4.0.5) model is used for hydrological modeling forced by a high-resolution atmospheric data set spanning the period 1993-2003. The model is modified to allow for bare soil evaporation and canopy evapotranspiration simultaneously in sparsely vegetated areas, as this is more appropriate for simulating seasonal effects. All projected land use change scenarios lead to an increase in streamflow. The magnitude of the increase, however, varies among subbasins of different scales from about 2% in the upstream part of the Rhine (about 60,000 km₂) to about 30% in the Lahn basin (about 7000 km₂). Streamflow at the basin outlet proved rather insensitive to land use changes because over the entire basin affected areas are relatively small. Moreover, projected land use changes (urbanization and conversion of cropland into (semi)natural land or forest) have opposite effects. At smaller scales, however, the effects can be considerable.