Understanding the impact of changes in land-use land-cover and rainfall patterns on soil erosion rates using the RUSLE model and GIS techniques: A study on the Nagavali River basin

Soil erosion is the most common type of land degradation, and it has become a global environmental issue that reduces soil productivity and water quality and is accelerated by human-induced activities. The Revised Universal Soil Loss Equation (RUSLE) model, which includes factors like rainfall, soil...

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Bibliographic Details
Published in:Journal of water and climate change 2022-07, Vol.13 (7), p.2648-2670
Main Authors: Yaswanth, Kottali, Kona, Meghana, Andra, Sai Kumar, Rathinasamy, Maheswaran
Format: Article
Language:English
Subjects:
Climate change
Climate variability
Correlation analysis
Datasets
Erosion rates
Forests
Geographic information systems
Geographical information systems
Human influences
Impact analysis
Information systems
Land cover
Land degradation
Land use
land-use land-cover change
nagavali river basin
Precipitation
Rainfall
Rainfall patterns
Remote sensing
River basins
River erosion
Rivers
rusle model
Soil conservation
Soil erosion
soil erosion rate
Soil loss
Soil water
Spatial distribution
Topography
Water quality
Wind
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Summary:Soil erosion is the most common type of land degradation, and it has become a global environmental issue that reduces soil productivity and water quality and is accelerated by human-induced activities. The Revised Universal Soil Loss Equation (RUSLE) model, which includes factors like rainfall, soil, land-cover, cultivation practices, and slope, was incorporated into the Geographic Information System (GIS) database to estimate average annual soil erosion rates in the Nagavali River basin (NRB) during 1990 and 2020, and this study also focuses on analyzing the impact of the land-use and land-cover (LULC) change, as well as climate variability on the annual average soil erosion rates in the NRB. Results indicate that the average annual soil erosion rate in the NRB ranged from 0 to 2364.46 t/ha/yr in the year 1990 was increased to 7857.21 t/ha/yr by the year 2020 as a result of an increase in rainfall and LULC changes over the study period. Based on the spatial distribution of soil erosion risk classes, it was identified that the area under the very severe erosion class increased drastically from 4.34 to 13.97%, while the area under the very slight erosion class got decreased between the years 1990 and 2020. Accordingly, a correlation analysis was carried out to determine the spatial correlation between the soil erosion pattern and changes in driver variables such as rainfall and land-use classes. These findings can be used to make well-informed decisions at the local and regional levels for the sake of soil conservation.
ISSN:2040-2244
2408-9354
DOI:10.2166/wcc.2022.016