Ecological Indicators (Nov 2021)

Coupling linear spectral unmixing and RUSLE2 to model soil erosion in the Boubo coastal watershed, Côte d'Ivoire

  • Lenikpoho Karim Coulibaly,
  • Qingfeng Guan,
  • Tchimou Vincent Assoma,
  • Xin Fan,
  • Naga Coulibaly

Journal volume & issue
Vol. 130
p. 108092

Abstract

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Water erosion accelerates soil degradation through land use, land cover, and climate change. Accurate modeling of soil erosion is critical for assessment of environmental variables such as nutrient loss, reduction of soil fertility, and water quality degradation. Modeling of soil erosion can provide insights to conservation planners for formulating policies to prevent land degradation. However, when used for soil erosion modeling in Geographical Information Systems (GIS), application of the Revised Universal Soil Loss Eq. (2) (RUSLE2) is realized based on the assumption that the pixels of land use data are pure and that mixed land use units within pixels can be ignored, and this opposes the accurate estimation of regional soil erosion. The methodology developed in this study includes combination of the GIS-based RUSLE2 with linear spectral unmixing (LSU) to analyze the change in vegetation cover within a pixel and to improve the spatial representation of the soil erodibility factor using climate data derived from the Boubo coastal watershed. The findings reveal that the estimated monthly erosivity density in the Boubo coastal watershed for different months varies between 0.05 and 20.86 MJ mm ha-1h−1 year−1 in 1990 and 0.8 to 21.21 MJ mm ha-1h−1 year−1 in 2019. The geographical soil erodibility K-factor varied between 0.008 and 0.022 t.ha.h.ha−1.MJ−1.mm−1. The temporal soil erodibility KJ factor was highest in May 1990 (0.194) and June 2019 (0.2). Slopes varied between 0% and 56%, with LS values exceeding 16. The deforestation rate in the Boubo coastal watershed was 65.49% from 1992 to 2019. The mean soil loss rate in June was 0.048 t/ha/month in 1990 and was 0.073 t/ha/month in 2019. Sediment yield increased from 1.09 t/ha/yr in 1990 to 2.54 t/ha/yr in 2019. Based on the RUSLE2 empirical equation, it was inferred that the estimated sediment transport capacity increased during the baseline period. Further studies should be conducted to evaluate ecosystem management based on ecosystem services and sediment deposition in this area.

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