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Dynamic analysis of soil erosion and sediment yield engrossment involving rainfall, land use and land cover impacts using GIS-based RUSLE & SDR modeling: southern western Ghats River Basin of Kerala, India.
- Source :
-
Geosciences Journal . Dec2024, Vol. 28 Issue 6, p959-980. 22p. - Publication Year :
- 2024
-
Abstract
- Soil erosion inventory of a river basin is vital for effective soil conservation and sustainable development considering the ongoing Global change. In the current study, gross soil erosion rates (A) are estimated for a mountainous river in a tropical climate, the Karamana River Basin (KRB), southern India by utilizing the Revised Universal Soil Loss Equation (RUSLE). The RUSLE model computes 'A', as a product function of five variables; rainfall erosivity (R), soil erodibility (K), topographic factor (LS), crop management factor (C), and erosion control practice factor (P). To compute these five parameters, the digital elevation model, slope, normalized vegetation index (NDVI), rainfall and land use/land cover (LULC) are used along with the texture data of soil samples collected from KRB. The estimated A values range between 0 to 738.44 t ha−1 year−1, with an average of 10.22 t ha−1 year−1 whereas the sediment yield (SY) estimated by utilizing the sediment delivery ratio (SDR) model ranges between 0 to 246.68 t ha−1 year−1 with an average of 1.58 t ha−1 year−1 for KRB. For further validation, a soil erosion potential index (SEPI) map is developed to identify the soil erosion-prone zones of KRB using the geo-environmental thematic maps following the analytic hierarchy process (AHP). Finally, rainfall impacts on soil erosion are evaluated and quantified for KRB, considering the recent marked variations in rainfall that are induced by the extreme climatic events (cyclones/high rainfall/floods) along the West coast of India. The outcome of this study suggests that increasing rainfall by one standard deviation of the long-term average causes a significant increase in low and medium soil erosion regions. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 12264806
- Volume :
- 28
- Issue :
- 6
- Database :
- Academic Search Index
- Journal :
- Geosciences Journal
- Publication Type :
- Academic Journal
- Accession number :
- 180501376
- Full Text :
- https://doi.org/10.1007/s12303-024-0042-0