| چکیده انگلیسی مقاله |
Abstract
This study aimed to evaluate the mechanisms driving soil erosion and investigate the impact of erodibility on soil quality dynamics across the southern slopes of the Aladagh Mountains in North Khorasan Province. To achieve this, soil erosion was assessed using the Revised Universal Soil Loss Equation (RUSLE) model in conjunction with satellite data. The relationship between the erosion estimates and the Soil Quality Index (SQI) was analyzed using the Pearson’s correlation coefficient. The RUSLE model results indicated that approximately 90% of the region was classified under severe erosion, with soil loss values ranging from 20 to 40 tons/ha/year. In contrast, areas experiencing soil loss of less than 10 to 20 tons/ha/year accounted for about 8% of the total area. The spatial pattern of the SQI revealed significant heterogeneity with the lowest values—approximately 0.43—found in the central, western, and southwestern regions. Overlaying this pattern with the RUSLE model results indicated that areas with the poorest soil quality predominantly occurred in mountainous regions characterized by steep slopes and rocky outcrops with shallow soils. This phenomenon was attributed to low organic matter content, reduced water retention capacity, and high slope gradients. Correlation analysis demonstrated a strong negative relationship between erosion and soil quality across 82.69% of the total area.
Keywords: Runoff, Management, Land Degradation, Remote Sensing, Aladagh.
Introduction
Soil erosion refers to the detachment and transport of soil particles from surface layers, resulting in the degradation of soil quality and a decline in natural resource productivity. This global issue has severe consequences for agricultural lands, contributes to the sedimentation of dam reservoirs, and particularly affects soil quality on alluvial fan surfaces. Therefore, estimating soil losses, identifying vulnerable areas, and examining the underlying causes and mechanisms are essential steps for implementing effective soil conservation programs. The process of soil degradation is significantly influenced by environmental factors, including soil type, climate, topography, and vegetation, as well as their interactions. While many external variables play a critical role in the extent of soil erosion, intrinsic soil characteristics—such as soil texture, distribution of aggregates with varying physical properties, soil porosity, organic matter content, and soil biodiversity—can exacerbate the risk of erosion. This research aimed to assess: (1) the factors and mechanisms driving soil erosion development through a combination of remote sensing data and the Revised Universal Soil Loss Equation (RUSLE) model; (2) the Soil Quality Index (SQI) using OpenLandMap data and MODIS sensor products; and (3) the effects of the soil erodibility factor on changes in soil quality.
Materials & Methods
This study was conducted on the southern slopes of the Aladagh Mountains, which are classified as having a semi-arid climate according to the De Martonne climate index. The input data for the annual calculations of the RUSLE were sourced from several global datasets. To estimate the rainfall-runoff erosivity factor (R), high-resolution precipitation data from the CHIRPS dataset were utilized. The soil erodibility factor (K) was determined using the soil texture class map from OpenLandMap. The topographic factor (LS) was computed through spatial analysis of a Digital Elevation Model (DEM) obtained from SRTM with a resolution of 30 m. For a more accurate calculation of the cover-management factor (C), a combined approach was employed. This integrated annual land cover/use data from the MODIS sensor with time-series NDVI data to account for the simultaneous effects of land use type and vegetation density. To evaluate the SQI, the data on the physical, chemical, and topographic properties of the soil were utilized. Physical properties, such as the percentage of sand and clay, were extracted from the OpenLandMap dataset, while soil surface moisture was derived from the SMAP sensor product. For the assessment of chemical properties, pH and soil organic carbon data were sourced from global OpenLandMap products. NDVI and land surface temperature data were extracted from the MOD13Q1 and MOD11A1 products, respectively.
Research Findings
The results of the RUSLE model applied over a 20-year period indicated that approximately 90% of the total area fell within the severe erosion class with the estimated soil loss ranging from 20 to 40 tons/ha/year. Conversely, erosion classes with soil loss values of less than 10 to 20 tons/ha/year accounted for about 8% of the region. This distribution highlighted a significant potential for sediment production and land degradation within the basin, underscoring the need for effective management measures for natural resources. The spatial pattern of the SQI revealed considerable heterogeneity with the lowest index value—approximately 0.43—observed in the central, western, and southwestern parts of the region. Overlaying this pattern with the RUSLE model results showed that areas with the poorest soil quality were predominantly located in mountainous terrains characterized by steep slopes, rocky outcrops, and shallow soils. This situation was attributed to low organic matter content, inadequate water retention capacity, and steep gradients. Correlation analysis demonstrated a strong negative relationship between erosion and soil quality across 82.69% of the total area.
Discussion of Results & Conclusion
Soil erodibility is a critical index for assessing soil susceptibility to water erosion and predicting soil loss. Soil erodibility (K) value serves as an intrinsic factor, illustrating the vulnerability of soils to erosion; thus, a higher K value corresponds to more severe soil erosion. Soil erosion presents significant environmental, economic, and social challenges. The results of this study indicated that soil erodibility increased when alluvial material from collapsing gullies was deposited onto farmland. While precipitation was the primary external driver of erosion, soil erodibility remained a crucial internal factor. It was influenced by various characteristics, including soil texture, organic matter content, soil structure, and fundamental soil permeability. This research found a strong positive correlation between soil erodibility and factors, such as soil texture, slope, and organic matter content. The RUSLE model results revealed two concurrent phenomena. Firstly, there was an overall increasing trend in mean annual soil erosion, primarily driven by anthropogenic pressures, land use changes, and land degradation. Secondly, significant inter-annual fluctuations in soil erodibility and soil quality were observed, which were directly correlated with short-term climate variations, particularly the intensity and amount of annual precipitation. This underscored the vulnerability of the region’s ecological system to climatic fluctuations. Additionally, the findings established a significant inverse relationship between soil erosion and soil quality in the study area. Spatial analyses confirmed a strong negative correlation (82.69%) between these two variables, highlighting erosion as the primary factor diminishing soil quality. Consequently, areas with high rates of erosion spatially coincided with low soil quality, while regions with low erosion rates were associated with more favorable soil quality. Based on the results, the level of soil erodibility was significantly influenced by intrinsic soil properties, including soil organic matter content, soil texture, soil structure, and soil moisture and permeability. The relationship between erosion and soil characteristics revealed that erodibility decreased as soil organic matter content increased. This phenomenon could be attributed to the role of organic matter in enhancing the cohesion of soil aggregates. This inverse relationship underscores the urgent need for effective soil management and conservation practices in these regions, especially in areas that exhibit a strong negative correlation. Comprehensive soil and water conservation management plans are essential and should focus on restoring vegetation cover, implementing proper grazing management, promoting conservation agriculture techniques, and constructing engineering structures for erosion control in areas classified as experiencing severe erosion. Moreover, continuous monitoring of erosion status is critical for assessing the effectiveness of the management measures that have been implemented.
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