Estimation of soil erosion has become the need of the hour because accelerated rates of soil erosion are affecting the capacity of reservoirs to store water and soil fertility. The present study aim is assessing soil erosion in the Sindhphana catchment using GIS and Remote Sensing (RS) based Revised Universal Soil Loss Equation (RUSLE) modelling. There is a lack of detailed data on soil erosion in semi-arid regions like Marathwada, Maharashtra on sub-catchment-level or land use/categories level. This is one of the hurdles in effective conservation planning and sustainable watershed management. The rate of soil erosion depends on topographic factors, land-use land-cover patterns, soil characteristics and rainfall distribution. To assess the variations in rates of soil erosion throughout the catchment, these factors are analysed using the RUSLE model. The model uses rainfall (R), soil erodibility factor (K), slope length (L), slope steepness (S), cover management factor (C) and conservation practices factor (P)as factors to assess the rate of soil erosion in the sub-catchments of the Sindaphana catchment. The results showed that soil erosion ranging from < 5 t ha− 1 year− 1 (very slight) to > 40 t ha− 1 year− 1 (very severe), with an average annual erosion rate of 36.66 t ha− 1 year− 1. The significant part of the catchment (68.2%) is covered under the very slight erosion category, contributing only 1.3% to the total soil loss. On the other hand, the area with very severe erosion potential (> 40 t ha− 1 year− 1), accounts for 15.9% of the total catchment area, but contribute around 93.7% of the total soil loss. It is found that the Kundka sub-catchment has the highest soil erosion (7043737 t ha− 1 year− 1) among 12 sub-catchments, with 36% of its area found under very severe erosion (> 40 t ha− 1 year− 1) category. It is also found that there are seasonal variations in soil loss, 80% of the total soil loss in the wet season (wet season average – 28 t ha− 1 year− 1 ) and only 20% in the dry season (average 10 t ha− 1 year− 1). The wet season, with its higher rainfall intensity, exacerbates soil erosion, especially in areas where land management practices are inadequate, such as insufficient ground cover during rainfall events. On the other hand, during the dry season, soil loss is minimized due to less intense rainfall. These findings emphasize significant seasonal variations in soil erosion. Multiple Regression analysis is employed to find the relative importance of the factors under consideration (RKLSCP). The result of regression show that soil erosion is more sensitive to topographic factors (L and S) than the other factors. Identification of sub-catchment with high rate of erosion and the most important factor that plays key role in soil erosion in the study area will further help identify apt soil and water practices at the sub catchment-level.

Soil Erosion Assessment of Sindhphana Catchment, Maharashtra, India, Using RUSLE and GIS and Remote Sensing Technique

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发表日期：

2026年1月20日

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D. B. Gadkari,
N. B. Bankar

摘要

Estimation of soil erosion has become the need of the hour because accelerated rates of soil erosion are affecting the capacity of reservoirs to store water and soil fertility. The present study aim is assessing soil erosion in the Sindhphana catchment using GIS and Remote Sensing (RS) based Revised Universal Soil Loss Equation (RUSLE) modelling. There is a lack of detailed data on soil erosion in semi-arid regions like Marathwada, Maharashtra on sub-catchment-level or land use/categories level. This is one of the hurdles in effective conservation planning and sustainable watershed management. The rate of soil erosion depends on topographic factors, land-use land-cover patterns, soil characteristics and rainfall distribution. To assess the variations in rates of soil erosion throughout the catchment, these factors are analysed using the RUSLE model. The model uses rainfall (R), soil erodibility factor (K), slope length (L), slope steepness (S), cover management factor (C) and conservation practices factor (P)as factors to assess the rate of soil erosion in the sub-catchments of the Sindaphana catchment. The results showed that soil erosion ranging from < 5 t ha^− 1 year^− 1 (very slight) to > 40 t ha^− 1 year^− 1 (very severe), with an average annual erosion rate of 36.66 t ha^− 1 year^− 1. The significant part of the catchment (68.2%) is covered under the very slight erosion category, contributing only 1.3% to the total soil loss. On the other hand, the area with very severe erosion potential (> 40 t ha^− 1 year^− 1), accounts for 15.9% of the total catchment area, but contribute around 93.7% of the total soil loss. It is found that the Kundka sub-catchment has the highest soil erosion (7043737 t ha^− 1 year^− 1) among 12 sub-catchments, with 36% of its area found under very severe erosion (> 40 t ha^− 1 year^− 1) category. It is also found that there are seasonal variations in soil loss, 80% of the total soil loss in the wet season (wet season average – 28 t ha^− 1 year^− 1 ) and only 20% in the dry season (average 10 t ha^− 1 year^− 1). The wet season, with its higher rainfall intensity, exacerbates soil erosion, especially in areas where land management practices are inadequate, such as insufficient ground cover during rainfall events. On the other hand, during the dry season, soil loss is minimized due to less intense rainfall. These findings emphasize significant seasonal variations in soil erosion. Multiple Regression analysis is employed to find the relative importance of the factors under consideration (RKLSCP). The result of regression show that soil erosion is more sensitive to topographic factors (L and S) than the other factors. Identification of sub-catchment with high rate of erosion and the most important factor that plays key role in soil erosion in the study area will further help identify apt soil and water practices at the sub catchment-level.