Articles | Volume 18, issue 8
Hydrol. Earth Syst. Sci., 18, 2975–2991, 2014
https://doi.org/10.5194/hess-18-2975-2014
Hydrol. Earth Syst. Sci., 18, 2975–2991, 2014
https://doi.org/10.5194/hess-18-2975-2014

Research article 13 Aug 2014

Research article | 13 Aug 2014

A comparison of three simple approaches to identify critical areas for runoff and dissolved reactive phosphorus losses

C. Hahn1,2, V. Prasuhn2, C. Stamm3, D. G. Milledge4, and R. Schulin1 C. Hahn et al.
  • 1ETH Zurich, Department of Environmental Systems Science, Zurich, Switzerland
  • 2Agroscope Reckenholz-Tänikon Research Station ART, Zurich, Switzerland
  • 3Eawag Swiss Federal Institute of Aquatic Science and Technology, Zurich, Switzerland
  • 4Durham University, Department of Geography, Durham, UK

Abstract. Diffuse phosphorus (P) losses are the main cause for eutrophication of surface waters in many regions. Implementing mitigation measures on critical source areas (CSAs) is seen to be the most effective way to reduce P losses. Thus, tools are needed that delineate CSAs on the basis of available data. We compared three models based on different approaches and sets of input data: the rainfall-runoff-phosphorus (RRP) model, the dominant runoff processes (DoRP) model, and the Sensitive Catchment Integrated Modeling Analysis Platform (SCIMAP). The RRP model is a parsimonious dynamic model using the topographic index and a binary soil classification to simulate discharge and P losses. The DoRP model distinguishes eight soil classes based on soil and geological maps. It does not account for topography when calculating runoff. SCIMAP assesses runoff risks solely on the basis of topography using the network index. Compared to surface runoff and soil moisture data available from a catchment in Switzerland, the RRP model and SCIMAP made better predictions than the DoRP model, suggesting that in our study area topography was more important for CSA delineation than soil data. Based on the results, we suggest improvements of SCIMAP to enable average risk predictions and the comparison of risk predictions between catchments.

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