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12/12/2025
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Le, V. T. (2025). Principal component analysis of factors influencing soil erosion on Da river basin, Vietnam. Journal of Water Resources & Environmental Engineering, 97, 126-131. https://dev.vojs.vn/index.php/jwree/article/view/27
Principal component analysis of factors influencing soil erosion on Da river basin, Vietnam
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Abstract
This study applies Principal Component Analysis (PCA) to identify and quantify the dominant factors influencing soil erosion in the Da River Basin, Vietnam. Using the Revised Universal Soil Loss Equation (RUSLE) and long-term hydro meteorological, soil, and land use data, ten key parameters were analyzed. PCA reduced these interrelated variables to four principal components explaining 77.3% of total variance. The first component, accounting for 36.7%, highlights rainfall erosivity, precipitation, and sand content as primary drivers of erosion. The second and third components represent the effects of slope, soil erodibility, and silt content, while the fourth reflects the influence of land management and conservation practices. Regression analysis confirmed a strong positive association between rainfall–soil texture interactions and erosion intensity.
Article Details
Keywords
Soil erosion, Da river basin, principal component analysis, erosion factors
References
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Kadam A.K et al. (2019), “Identification of erosion-prone areas using modified morphometric prioritization method and sediment production rate: a remote sensing and GIS approach”. Geomatics, Natural Hazards and Risk 10, 986–1006.
Le Van T, Ranzi R, Rulli M.C (2018), “Modeling Soil Erosion and Sediment Load for Red River Basin (Vietnam): Impact of Land Use Change and Reservoirs Operation”. IEEE Xplore, pp 1-6.
Meshram S.G, Sharma S.K (2017), “Prioritization of watershed through morphometric parameters: a PCA-based approach”. Appl Water Sci 7(3), 1505–1519.
Ranzi R, Le T.H, Rulli M.C (2012), “A RUSLE approach to model suspended sediment load in the Lo river (Vietnam): Effects of reservoirs and land use changes”. Journal of Hydrology 422-423, 17–29.
Renard K.G et al. (1997), “Predicting Soil Erosion by Water: A Guide to Conservation Planning with the Revised Universal Soil Loss Equation (RUSLE)”. Agriculture Handbook No.703, USDA, Washington DC.
Rulli M.C, Offeddu L, Santini M (2012), “Modeling post-fire water erosion mitigation strategies”. Hydrol. Earth Syst. Sci. 17, 2323–2337.
Wuttichaikitcharoen P, Babel M (2014), “Principal Component and Multiple Regression Analyses for the Estimation of Suspended Sediment Yield in Ungauged Basins of Northern Thailand”. Water 6, 2412–2435.
Damiba W.A.F et al. (2024), “Soil quality index (SQI) for evaluating the sustainability status of Kakia-Esamburmbur catchment under three different land use types in Narok County, Kenya”. Heliyon 10, e25611.
Kadam A.K et al. (2019), “Identification of erosion-prone areas using modified morphometric prioritization method and sediment production rate: a remote sensing and GIS approach”. Geomatics, Natural Hazards and Risk 10, 986–1006.
Le Van T, Ranzi R, Rulli M.C (2018), “Modeling Soil Erosion and Sediment Load for Red River Basin (Vietnam): Impact of Land Use Change and Reservoirs Operation”. IEEE Xplore, pp 1-6.
Meshram S.G, Sharma S.K (2017), “Prioritization of watershed through morphometric parameters: a PCA-based approach”. Appl Water Sci 7(3), 1505–1519.
Ranzi R, Le T.H, Rulli M.C (2012), “A RUSLE approach to model suspended sediment load in the Lo river (Vietnam): Effects of reservoirs and land use changes”. Journal of Hydrology 422-423, 17–29.
Renard K.G et al. (1997), “Predicting Soil Erosion by Water: A Guide to Conservation Planning with the Revised Universal Soil Loss Equation (RUSLE)”. Agriculture Handbook No.703, USDA, Washington DC.
Rulli M.C, Offeddu L, Santini M (2012), “Modeling post-fire water erosion mitigation strategies”. Hydrol. Earth Syst. Sci. 17, 2323–2337.
Wuttichaikitcharoen P, Babel M (2014), “Principal Component and Multiple Regression Analyses for the Estimation of Suspended Sediment Yield in Ungauged Basins of Northern Thailand”. Water 6, 2412–2435.