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

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...

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Autores principales:	Lenikpoho Karim Coulibaly, Qingfeng Guan, Tchimou Vincent Assoma, Xin Fan, Naga Coulibaly
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2021
Materias:	Soil erosion RUSLE2 Linear spectral unmixing Climate change GIS Remote sensing Ecology QH540-549.5
Acceso en línea:	https://doaj.org/article/cea539842bb248899f4457fe1f46767e
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spelling	oai:doaj.org-article:cea539842bb248899f4457fe1f46767e2021-12-01T04:59:00ZCoupling linear spectral unmixing and RUSLE2 to model soil erosion in the Boubo coastal watershed, Côte d'Ivoire1470-160X10.1016/j.ecolind.2021.108092https://doaj.org/article/cea539842bb248899f4457fe1f46767e2021-11-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S1470160X21007573https://doaj.org/toc/1470-160XWater 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.Lenikpoho Karim CoulibalyQingfeng GuanTchimou Vincent AssomaXin FanNaga CoulibalyElsevierarticleSoil erosionRUSLE2Linear spectral unmixingClimate changeGISRemote sensingEcologyQH540-549.5ENEcological Indicators, Vol 130, Iss , Pp 108092- (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Soil erosion RUSLE2 Linear spectral unmixing Climate change GIS Remote sensing Ecology QH540-549.5
spellingShingle	Soil erosion RUSLE2 Linear spectral unmixing Climate change GIS Remote sensing Ecology QH540-549.5 Lenikpoho Karim Coulibaly Qingfeng Guan Tchimou Vincent Assoma Xin Fan Naga Coulibaly Coupling linear spectral unmixing and RUSLE2 to model soil erosion in the Boubo coastal watershed, Côte d'Ivoire
description	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.
format	article
author	Lenikpoho Karim Coulibaly Qingfeng Guan Tchimou Vincent Assoma Xin Fan Naga Coulibaly
author_facet	Lenikpoho Karim Coulibaly Qingfeng Guan Tchimou Vincent Assoma Xin Fan Naga Coulibaly
author_sort	Lenikpoho Karim Coulibaly
title	Coupling linear spectral unmixing and RUSLE2 to model soil erosion in the Boubo coastal watershed, Côte d'Ivoire
title_short	Coupling linear spectral unmixing and RUSLE2 to model soil erosion in the Boubo coastal watershed, Côte d'Ivoire
title_full	Coupling linear spectral unmixing and RUSLE2 to model soil erosion in the Boubo coastal watershed, Côte d'Ivoire
title_fullStr	Coupling linear spectral unmixing and RUSLE2 to model soil erosion in the Boubo coastal watershed, Côte d'Ivoire
title_full_unstemmed	Coupling linear spectral unmixing and RUSLE2 to model soil erosion in the Boubo coastal watershed, Côte d'Ivoire
title_sort	coupling linear spectral unmixing and rusle2 to model soil erosion in the boubo coastal watershed, côte d'ivoire
publisher	Elsevier
publishDate	2021
url	https://doaj.org/article/cea539842bb248899f4457fe1f46767e
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Coupling linear spectral unmixing and RUSLE2 to model soil erosion in the Boubo coastal watershed, Côte d'Ivoire

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