Technical Abstract: Identification of flow and transport processes under natural boundary conditions in field soils is a complex task since most model parameters are not measurable at that scale. However, combining a numerical solution method of the governing flow and transport equations with an inverse optimization algorithm and detailed measurements of different state variables may be a promising tool for process identification. The objective of the paper is to evaluate how well a physically-based model can describe the flow and transport dynamics measured in-situ at a detailed temporal scale. The data consisted of depth-averaged time series of water content, pressure head and resident solute concentration data measured several times a day during 384 days. In a first approach, effective parameters are estimated using the time series for one depth and assuming a homogeneous soil profile. In a second approach, all time series are used simultaneously to estimate the parameters of a multi-layered soil profile. Water flow is described by the Richards' equation and solute transport either by the equilibrium convection-dispersion (CDE) or the physical non-equilibrium convection-dispersion (MIM) equation. To represent the dynamics of the water content and pressure head data, the multi-layered soil profile approach gave better results. Fitted soil hydraulic parameters were comparable with parameters obtained with other methods on the same soil. At larger depths, both the CDE- and MIM-model gave acceptable descriptions of the observed breakthrough data, although the MIM performed somewhat better in the tailing part. Both models underestimated significantly the fast breakthrough. To describe the breakthrough curves at the first depth, only the MIM with a mixing layer close to the soil surface gave acceptable results.