Abstract. Large weighing lysimeters are currently the most precise method to directly measure all components of the terrestrial water balance in parallel via the built-in weighing system. As lysimeters are exposed to several external forces such as management practices or wind influencing the weighing data, the calculated fluxes of precipitation and evapotranspiration can be altered considerably without having applied appropriate corrections to the raw data. Therefore, adequate filtering schemes for obtaining most accurate estimates of the water balance components are required. In this study, we use data from the TERENO (TERrestrial ENvironmental Observatories) SoilCan research site in Bad Lauchstädt to develop a comprehensive filtering procedure for high-precision lysimeter data, which is designed to deal with various kinds of possible errors starting from the elimination of large disturbances in the raw data resulting e.g., from management practices all the way to the reduction of noise caused e.g., by moderate wind. Furthermore, we analyze the influence of averaging times and thresholds required by some of the filtering steps on the calculated water balance and investigate the ability of two adaptive filtering methods (the adaptive window and adaptive threshold filter (AWAT filter; Peters et al., 2014), and a new synchro filter applicable to the data from a set of several lysimeters) to further reduce the filtering error. Finally, we take advantage of the data sets of all 18 lysimeters running in parallel at the Bad Lauchstädt site to evaluate the performance and accuracy of the proposed filtering scheme. For the tested time interval of 2 months, we show that the estimation of the water balance with high temporal resolution and good accuracy is possible. The filtering code can be downloaded from the journal website as Supplement to this publication.
Determination of spatially differentiated water balance components including groundwater recharge on the Federal State level – A case study using the mGROWA model in North Rhine-Westphalia (Germany)