This paper analyses the possibilities of improving the precision of, and obtaining better, drainage density (Dd) input data for the Erosion Potential Method (EPM). This method is used for erosion assessments in karst areas that are characterised by torrential watercourses. The analysis is conducted in the Dubračina catchment in Croatia. Four different methodologies are used to derive a Dd map. The approaches use different assumptions and allow different spatial variability. The first two are commonly applied in the EPM. The Dd in the first case scenario corresponds to very low Dd and is homogenous throughout the entire catchment. In the second case, Dd is calculated on the sub-catchment level and varies from very low to medium. The third and fourth case scenarios provide the most spatially variant maps. The output of the third case is the actual Dd based on a topographic map, and the fourth potential Dd is based on a river network map derived from a Lidar digital elevation model. The third and fourth case scenarios provide better spatial variability for the Dd parameter, and both case scenarios are considered appropriate input data for the EPM and an improvement of the accuracy and precision of the EPM.

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The main focus in this article is given on the erosion potential method (EPM) modification. The aim was to provide a seasonal assessment, in addition to annual erosion assessment for the case study Dubračina catchment, Croatia. Seasonal assessment of erosion processes in the catchment will contribute to planning strategies that would benefit local community and enable the more appropriate and timely definition of erosion mitigation and protection measures. Original EPM was used for erosion intensity and sediment production assessment for two time periods: the past and the present time. The overall classification of erosion intensity categorises the erosion processes in the catchment as slight, although excessive erosion processes are present in some areas. For the method modification purpose, three main model parameters were changed: precipitation, soil protection coefficient and temperature. The greatest soil loss was found to occur in autumn, followed by summer, spring and winter period. The results indicated good erosion intensity and soil loss approximation obtained with the modified EPM and 13% soil loss deviation in comparison to the results obtained with original EPM. The erosion intensity, land cover map for both the present time and summer season and soil surface change over a two-year time period were verified.

This paper analyses the possibilities to derive drainage density map, a parameter used within Erosion Potential Method (EPM, Gavrilović), for the Dubračina catchment study area in better detail and precision. EPM method is used for erosion assessment in the karstic areas characterized by torrential rivers. In this paper, three different methodologies were used to derive drainage density map each using different assumptions and allowing different spatial variability. The third case of drainage density map provides most realistic spatial variance of the drainage density parameter with lower values along the edges of the catchment and higher values concentrated along the river and tributary intersections.

This paper examines the performance of the Erosion Potential Method (EPM or Gavrilović) and the model response to input data variations caused by choosing different sources of information for the same parameter. The research presented addresses the input data uncertainty via an analysis of the two model input parameters (the soil protection coefficient and the soil erodibility coefficient). The parameter uncertainty analysis is performed following two different approaches: uncertainty analyses of both the selected sample size and the entire population are conducted for an erosion assessment case study of the Dubračina River catchment, Croatia. The analysis indicated that, when changing the data source, significant changes in the model outcome values can occur (up to 47% for this case study). Future method modifications should consider the mitigation of these two parameters by potentially making structural changes in the model and therefore moderating the effect.