Large weighable lysimeters allow a precise determination of the soil water balance and the quantification of both water exchange at the soil-atmosphere interface and the flux below the root zone toward the groundwater. If well embedded into an equally-vegetated environment, they reach a hitherto unprecedented accuracy in estimating precipitation (P) by rain, dew, fog, rime and snow, and evapotranspiration (ET). Lysimeters largely avoid errors made by traditional measurement systems, such as the wind error of Hellmann rain gauges, the island error of class-A pans, or errors from soil-water measurements that are subject to subsurface heterogeneity. If the amount of seepage water is added to the lysimeter mass, temporal changes of the lysimeter mass can be used to solve the water balance equation for atmospheric fluxes. Increasing mass indicates P, decreasing mass ET. The determination of the net water balance (sum of P and ET) is accurate and robust. A problem arises in the separate estimation of the underlying P and ET fluxes, because weight differences in specified time intervals are affected by stochastic fluctuations due to mechani- cal vibration, which may be caused by wind or other factors. The aim of this study is to evaluate algorithms that aim on eliminating the effects of these fluctuations and to estimate actual fluxes across the soil-atmosphere boundary and the soil water balance from lysimeter measurements. We use synthetic and real measured data from large lysimeters to test which strategies of data evaluation can be applied, and which degree of accuracy can be reached.
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