The importance of soil data availability on erosion modeling

The accurate estimation of soil erodibility is essential for the proper simulation of erosion. The parameter, describing the soil's susceptibility to the erosive actions of precipitation and surface runoff, is expressed in the RUSLE (Revised Universal Soil Loss Equation) by the K factor. The latter is at most cases empirically estimated (due to the scarcity of soil data) discarding key attributes like organic matter content and granulometry. The study aims to assess the effect of the different K factor computation methodologies (empirical, based on bedrock lithology and stratigraphy; analytical, based on soil data) on soil erosion, at the Kalamas River catchment, located at Epirus, Northwestern Greece. To that end, RUSLE was implemented (both annually and multi-annually for the period 1987-02) at its two comprising subcatchments (Soulopoulo Bridge, Kioteki), once for every different K approximation. The study area's geology was described based on the Greek IGME (Institute of Geological and Mining Exploration) geological maps (1:50,000). The soil data (field samples) were provided by the Greek NAGREF (National Agricultural Research Foundation), the EU (European Union) and the Greek PCAGGCA (Payment and Control Agency for Guidance and Guarantee Community Aid). Provided that all other parameters (R, LS, C, P) remain unchanged, the model's results were depended on the alternative K factor values. Regarding the latter, the implementation (thus the K computation methodology) that performed best was the analytical one by displaying the highest convergence between simulated and “observed” {calculated based on field measurements, provided by the Greek PPC (Public Power Corporation)} sediment yield.