The input of phosphorus (P) into aquatic systems can result in eutrophication that might manifest in algal blooms and oxygen deficiency and, subsequently, in a poor ecological status. Substance emission modeling on a river basin scale can help to quantify phosphorus emissions into surface water bodies and to address mitigation measures. The prerequisite is that suitable input data are available. The purpose of this study is to develop a modeling approach that allows the prediction of realistic phosphorus concentrations in surface runoff. During large-scale artificial rain experiments at 23 agricultural sites, dissolved P concentrations in surface runoff and subsurface flow were measured. The characteristics of the experimental sites were investigated by taking and analyzing soil samples and requesting information on the management from the farmers. From the data collected, two linear models were derived. The first model allows the prediction of dissolved phosphorus concentration in surface runoff from PCAL
soil content. Applying the second model, the obtained concentration in surface runoff can be transferred to a concentration in subsurface flow. The resulting approaches were derived from realistic field experiments and, for the first time, allow the direct prediction of dissolved phosphorus concentrations in surface runoff and, in a second step, also in subsurface flow from spatially distributed PCAL
soil content data. Integrating these approaches into substance emission models can improve their accuracy and, subsequently, allows a better planning of measures for the reduction in phosphorus emissions into surface water bodies.
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