| چکیده انگلیسی مقاله |
1- Introduction
Soil erosion is the most common type of land degradation occurring in arid and semi-arid areas, as well as in flooded areas, due to natural and human processes. Erosive factors lead to the loss of land fertility, transforming damaged areas into abandoned lands and disrupting the balance of natural ecosystems. Soil erosion, as an important environmental issue, poses a threat to the sustainability of natural resources and soil productivity, turning it into a major problem in many parts of the world. To address this challenge, evaluating soil erodibility and preparing a risk zoning map is one of the most important preventive measures. One of the methods for estimating soil erosion is the SLEMSA model, which utilizes basic environmental information to assess the amount of soil loss. Consequently, the present research aims to determine soil loss values and create zoning maps for high erosion areas using the SLEMSA model and remote sensing data. The results obtained from this study can assist organizational managers and executive departments in formulating effective plans to control soil erosion and contribute to the achievement of the country's sustainable development goals.
3- Methodology
The SLEMSA model divides the soil erosion environment into four physical systems: crops, climate, soil, and topography. These control variables are then integrated into three sub-models: the soil erodibility sub-model, topography sub-model, and vegetation sub-model. In this study, the topographic factor map is generated using two parameters: slope and domain length. These parameters are derived from the Digital Elevation Model (DEM), obtained from the SRTM Digital Elevation Data version 4 of the Google Earth Engine system, with a spatial resolution of 90 meters. To create the soil erodibility map, rain kinetic energy maps and soil erodibility factors are required. The Google Earth Engine System’s Global Precipitation Measured (GPM) v6 data was used to extract rain kinetic energy. Simultaneously, the soil erodibility factor was obtained from a geological formations map acquired from the World Soil Database (HWSD) for the year 2022. Additionally, a vegetation factor map was generated using ESA-CCI global land use data.
3- Results
The topographic factor map was created using slope and domain length maps. Based on this factor's map, it is evident that the highest values are in the high mountain areas of the basin. The soil erodibility factor map is prepared based on soil erodibility and rain kinetic energy. The results of the soil erosion factor map for this basin show that erosion is more evident in areas with weak and unstable formations mainly affected by the kinetic energy of rainfall. The vegetation factor map was prepared using released energy maps and land use maps. Considering the direct relationship between the vegetation factor and erosion, it can be concluded that the highest soil losses occur in areas with a higher vegetation factor. Consequently, the combination of topographical factors, erodibility, and vegetation indicates the amount of soil erosion in terms of tons per hectare per year. The research findings indicate that the marginal areas from the northeast to the southeast of the basin, in the altitude range of 1880 to 3622 meters, lack suitable vegetation due to the high altitude and slope. Also, due to the high amount of precipitation in these areas, an increase follows the speed of surface runoff. Additionally, sensitive formations in these areas contribute to intensifying soil erosion. Approximately 11.7% of the basin area is in the erosion risk group, with the erosion rate ranging from 37.1 to 67.7 tons per hectare per year. Planning, management, and control measures are needed to address soil erosion and protection in these high-risk areas.
4- Discussion & Conclusions
The results of this research indicate that approximately 96.61% of the region has a low to moderate erodibility rate. Meanwhile, the lowest erosion values are observed in the middle and outlet areas of the basin, characterized by lower altitudes and better vegetation conditions. These areas are more favorable in terms of sensitivity to erosion, and the presence of annual rainfall between 460 and 600 mm leads to a decrease in runoff, consequently reducing the rate of erosion. On the other hand, the highest amount of erosion can be seen in the Doab and Kakareza watersheds, attributed to inappropriate vegetation, annual rainfall exceeding 600 mm, and structures with low resistance. Finally, it can be said that in Iran, especially in Lorestan province, the lack of models to estimate erosion with limited data has become a significant challenge. Therefore, the purpose of this research was to investigate soil erosion in the Karkheh watershed of Lorestan province using the SLEMSA model. Utilizing simple environmental data, this model shows promising potential for estimating soil erodibility in the Karkheh watershed of Lorestan province.
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