Estimation of potential soil erosion reduction using GIS-based RUSLE under different land cover management models: A case study of Pale Municipality, B&H

Abstract

Spatial assessment of soil erosion is an important indicator of ecological soil change and global environmental changes. This is especially true for countries with rich forest cover such as Bosnia and Herzegovina. In this study, the risk of soil erosion was assessed using the Revised Universal Soil Loss Equation (RUSLE) model and the impact of changes in the forest ecosystem, current conditions were compared with possible future forest management scenarios, and measures and solutions were proposed to reduce soil erodibility in vulnerable areas of the Pale Municipality in Bosnia and Herzegovina. The studied area is at increased risk of soil erosion due to natural conditions (mountain relief, climate change, and the frequency of extreme climatic events—drought and heavy rains, which occur more and more frequently in a short period of time) and due to anthropogenic factors, such as large-scale deforestation and conversion of mountain areas for tourism purposes, tracing and construction of ski slopes and ski resorts in general, and expansion of settlements. All this leads to threats to water conservation areas, landslides, floods, forest fires, and additional reduction of forest areas due to drying of forests and expansion of settlements. GIS as a tool provides us with a quick and accurate way to find possible solutions to problems resulting from the intensive use and inadequate monitoring. In this study, we have tried to offer possible solutions and show the benefits that can be obtained by varying the factors that affect soil erodibility and depend on vegetation cover, that is, land use (C-factor). This study presents the application of RUSLE methods in combination with GIS for the purpose of planning economic activities, such as winter tourism development in the community of Pale. An increase in soil loss due to inappropriate land use was found, with the average annual soil loss due to deforestation in the ski area increasing to 909.43 t ha−1 year−1.

Advancing Soil Erosion Assessment: Application of Remote Sensing and Geospatial Techniques in Bulango Ulu Reservoir Basin

“…This spatial pattern aligns with the expectation that areas with more pronounced slopes will have higher potential for soil erosion. The phenomena suggests that soil erosion increases with slope length and steepness (21). It is in line with the fundamental principles of soil erosion.…”

“…In soil erosion modelling, the slope-length and gradient parameter are critical for calculating overland flow (surface runoff). The topographic factor is computed using Eq (5 and 8) (Moore and Burch (1986) in Golijanin et al, 2022).…”

“…However, the use of geographic information systems (GIS) to integrate existing soil erosion models, field data, and data provided by remote sensing technologies appears to be an asset for future research (18,19). Many scientific studies have been conducted in the last decade to characterize soil erosion in large areas using remote sensing and GIS technologies (20,21). These investigations indicated that these methodologies presented extremely good information concerning soil erosion zones, such as types of soil, lithological units, and coverage of vegetation, at a low cost and with a high degree of accuracy (20).…”

“…The RUSLEbased assessment showed that the estimated total annual potential soil erosion can be estimated using remote sensing and GIS data. Generating accurate soil erosion maps in GIS environment is very important to locate the areas with high soil erosion and to develop adequate soil erosion prevention techniques (21).…”

Evaluation of Rainfall Erosivity in the Western Balkans by Mapping and Clustering ERA5 Reanalysis Data

“…However, data about water erosion rates in the WB countries were not included. Instead, contemporary research regarding the WB region was conducted only in sub-regional studies based on the precipitation data for smaller territories covering [12,[24][25][26][27][28][29][30][31][32][33][34][35][36][37][38][39][40][41] or partial regional studies based on gridded rainfall datasets [42].…”