High availability of phosphorus in agricultural soils leads to increased phosphorus (P) losses from land to water and contributes to the eutrophication of surface water. The most important variable for the transport of soluble P via surface runoff is the labile P content in the top soil. Until now, a detailed understanding and quantitative estimates of the seasonal and spatial dynamics of labile P in the top soil layer at the catchment scale have been lacking.

The objective of this paper is to analyze the spatial and temporal variability of labile P and to quantify concentrations in the top soil by coupling the process-based one dimensional P soil model ANIMO with a hydrological model (WaSim-ETH). For testing the spatially distributed ANIMO model, a sampling scheme for soil P compounds was carried out. The scheme comprised of 80 sampling points in a 150 m grid in the 1.44 km² study catchment Schäfertal, Germany. For a period of 2 years water soluble P (WSP), total phosphorus (TP), oxalate extractable P/Fe + Al, pH value and C_org were analyzed. Close correlations with a high level of significance were observed between P compounds (from 0.733 to 0.737) and between P compounds and C_org (from 0.508 and 0.527). It was found that, in addition to crop rotation and management practice, spatial variability of WSP was controlled by topography affected microclimate and soil water balance. The combined modeling approach was successfully calibrated for WSP in the top soil with a R² of 0.94. Although the accuracy of simulation results for the validation period was lower, the model reasonably reproduced the spatial and seasonal variation of WSP. The simulations identified areas of high WSP concentrations and revealed a spring depression with low WSP concentrations in the top soil. The new modeling approach can be used to better understand WSP availability and P yield at the catchment scale.