Prediction of dissolved reactive phosphorus losses from small agricultural catchments: calibration andvalidation of a parsimonious model

Abstract

Eutrophication of surface waters due to diffuse phosphorus (P) losses continues to bea severe water quality problem world-wide, causing the loss of ecosystem functions ofthe respective water bodies. Phosphorus in runoffoften originates from a small fractionof a catchment only. Targeting mitigation measures to these critical source areas (CSA) is expected to be most efficient and cost-effective, but requires suitable tools.Here we investigated the capability of the parsimonious Rainfall-Runoff-Phosphorus(RRP) model to identify CSA in grassland-dominated catchments based on readilyavailable soil and topographic data. After simultaneous calibration on runoffdata fromfour small hilly catchments on the Swiss Plateau, the model was validated on a different catchment in the same region without further calibration. The RRP model adequatelysimulated the discharge and dissolved reactive P (DRP) export from the validationcatchment. Sensitivity analysis showed that the model predictions were robust with re-spect to the classification of soils into “poorly drained” and “well drained”, based onthe available soil map. Comparing spatial hydrological model predictions with field data from the validation catchment provided further evidence that the assumptions under-lying the model are valid and that the model adequately accounts for the dominant Pexport processes in the target region. Thus, the parsimonious RRP model is a valu-able tool that can be used to determine CSA. Despite the considerable predictive un-certainty regarding the spatial extent of CSAs the RRP can provide guidance for the implementation of mitigation measures. The model helps to identify those parts of acatchment where high DRP losses are expected or can be excluded with high confi-dence. Legacy P was predicted to be the dominant source for DRP losses and thus, incombination with hydrologic active areas, a high risk for water quality.