Abstract1. Efficient extraction of soil water is essential for the productivity of plant communities. However, research on the complementary use of resources in mixed plant communities, and especially the impact of plant species richness on root water uptake, is limited. So far, these investigations have been hindered by a lack of methods allowing for the estimation of root water uptake profiles.2. The overarching aim of our study was to determine whether diverse grassland plant communities in general exploit soil water more deeply and whether this shift occurs all the time or only during times of enhanced water demand.3. Root water uptake was derived by analysing the diurnal decrease in soil water content separately at each measurement depth, thus yielding root water uptake profiles for 12 experimental grasslands communities with two different levels of species richness (4 and 16 sown species). Additional measurements of leaf water potential, stomatal conductance, and root traits were used to identify differences in water relations between plant functional groups.4. Although the vertical root distribution did not differ between diversity levels, root water uptake shifted towards deeper layers (30 and 60 cm) in more diverse plots during periods of high vapour pressure deficit. Our results indicate that the more diverse communities were able to adjust their root water uptake, resulting in increased water uptake per root area compared to less diverse communities (52% at 20 cm, 118% at 30 cm, and 570% at 60 cm depth) and a more even distribution of water uptake over depth. Tall herbs, which had lower leaf water potential and

Understanding the role of plants in soil water relations, and thus ecosystem functioning, requires information about root water uptake. We evaluated four different complex water balance methods to estimate sink term patterns and evapotranspiration directly from soil moisture measurements. We tested four methods. The first two take the difference between two measurement intervals as evapotranspiration, thus neglecting vertical flow. The third uses regression on the soil water content time series and differences between day and night to account for vertical flow. The fourth accounts for vertical flow using a numerical model and iteratively solves for the sink term. None of these methods requires any a priori information of root distribution parameters or evapotranspiration, which is an advantage compared to common root water uptake models. To test the methods, a synthetic experiment with numerical simulations for a grassland ecosystem was conducted. Additionally, the time series were perturbed to simulate common sensor errors, like those due to measurement precision and inaccurate sensor calibration. We tested each method for a range of measurement frequencies and applied performance criteria to evaluate the suitability of each method. In general, we show that methods accounting for vertical flow predict evapotranspiration and the sink term distribution more accurately than the simpler approaches. Under consideration of possible measurement uncertainties, the method based on regression and differentiating between day and night cycles leads to the best and most robust estimation of sink term patterns. It is thus an alternative to more complex inverse numerical methods. This study demonstrates that highly resolved (temporally and spatially) soil water content measurements may be used to estimate the sink term profiles when the appropriate approach is used