engleski

Applicability analysis of erosion assessment methods based on defined criteria and available data

In recent decades there has been a significant development of erosion assessment methods that simultaneously followed the development of computer technologies, as well as Geographic Information Systems (GIS) and Satellite Imagery, thus enabling more detailed information`s about topography, land use and vegetation cover, as well as broaden the possibilities for the application of more demanding erosion analysis. There are several papers that deal with the application of various erosion assessment methods depending on the needed scale [1, 2, 3] (from global to catchment size), erosion type (gully, rill, bank, sheet) [3] and their assessments by criteria such as prediction accuracy, erosion processes, needed data and calibration [8]. Within this paper twenty-two different erosion assessment methods are analysed and compared with the purpose to define the relevance of each used criterion, better understanding of erosion processes, as well as to give future guidance for simplifying the procedure of choosing the appropriate method based on available data and relevant criteria. Methods encompassed with this analysis are Pacific Southwest Inter-Agency Committee (PSIAC), PSIAC adapted version, The vegetation-surface material-drainage density (VSD), Erosion Potential Method–Gavrilovic (EPM), Factorial Scouring Model (FSM), Erosion hazard units (EHU), Soil Loss Estimation Model for Southern Africa (SLEMSA), CORINE erosion risk maps, Coleman and Scatena scoring model (CSSM), Fleming and Kadhimi scoring model (FKSM), Wallingford scoring model (WSM), Universal Soil Loss Equation (USLE), Revised Universal Soil Loss Equation (RUSLE), RIVM Model, INRA Model, SCALES Model, Fournier, Water Erosion Prediction Model (WEPP), Soil and Water Assessment Tool (SWAT), Morgan-Morgan-Finney (MMF), Annualized Agricultural Non-Point Source Pollution (AGNPS) and Modified Universal Soil Loss Equation (MUSLE) [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]. There are fifty one used criteria within these methods that can be divided into ten main groups (soil, climate and precipitation, runoff, water network, topography, vegetation cover and land use, upland erosion, channel erosion and sediment transport, catchment characteristics and other). Ten most used criteria are precipitation, erosivity or rain intensity (72.73%), slope angle (72.73%), soil erodibility (68.18%), percentage of vegetation cover (40.91%), cover type (36.36%), runoff (31.82%), agricultural practice (31.82%), soil type (22.73%), slope length (22.73%), agricultural land (13.64%), all of which represent only five out of ten criteria groups (topography, climate and precipitation, soil, vegetation cover and land use, runoff). By group statistic, where at least one of the group criteria is used in each method, vegetation cover and land use, can be considered the most significant one, with the use percentage of 95.45%, followed both by soil and topography groups with 86.36% and climate and precipitation with 81.82%. There is a minimum gap of 45% between the use of first four group criteria and the rest of the groups (eg. Runoff is fifth by 36.36%). Taking into consideration conducted analysis and complementing it with the knowledge about erosion processes obtained from the literature, significance of the criteria can be concluded. Since, rainfall is considered the most important detaching agent and erodibility and type of the soil define susceptibility of the soil to detachment, these criteria can be considered the most important ones. When detached, soil is transported further by erosion agents (eg. running water) during which topography (eg. slope angle) has a major impact upon the distance, speed and pathways for the runoff and sediment transport, imposing this criteria as relevant when making methodology selection. Agricultural practice, the growth cycle of the plants, % of vegetation cover, the constructions sites, excavation of mineral resources, form vegetation cover and land use group. If not managed properly, this criteria can contribute to the increase of erosion detached sediment, and therefore needs to be taken into consideration [12, 13, 14]. The first step to predict erosion and its severity on the area of interest is choosing the methodology to apply. The restrictions of scale applicability of a method, and type of erosion the method deals with, has already been covered within literature [1, 2, 3]. The accessibility of a data is often the crucial factor in the process of method selection. For this reason it is necessary to take into consideration all four criteria (scale, erosion type, criteria significance and available data) in order to make the best method selection. Today, continuous development of technology has enabled new and more detailed spatially variant data, as well as provided various different sources for the same data category (such as landcover). That also brought the challenges for appropriate data selection within various sources, where each decision made will have its own impact on the final result. The proposed methodology has been applied on Dubracina Catchment Area in Croatia by which the choice of applicable methods was narrowed to: Gavrilovic, FKSM and Fournier method. The Gavrilovic method has been developed for catchments with karstic terrain and torrential rivers, as well as taking into consideration the previously mentioned significant criteria, all of which are available and correspond to the Dubracina Catchment. The challenge was to choose one over several available data of the same type but different source, or combining them into one secondary data with the help of GIS (eg. vegetation cover and land use). Also some elements included in the method were not available for previous researches in such detail and spatial variance (eg. drainage density) and some were available as limited number of point sources (eg. precipitation) thus making additional challenge in transferring them to spatially variant data.

erosion assessment methods; significant criteria; method selection; data availability

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