Physicochemical Analysis of Parameters Influencing Soil Loss for a  Selected Location in North Central Nigeria Using Rainfall Simulator

Musa, John Jiya.; Akpoebidimiyen, Otuaro Ebierin; Dada, Pius Olusegun Olufemi; Chukwu, Eze Peter; dams-Suberu, Jamil

doi:10.5539/enrr.v12n2p14

Cited by 1 publication

(2 citation statements)

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“…Only a very few validated their studies, the notable ones were Egbueri et al (2022) which was based on a multi-criteria decision approach and therefore implied validating erosion susceptible areas rather than soil loss validation. The second was Musa et al (2021) who validated their work using soil loss from a rainfall simulator. The use of a rainfall simulator is good, but it does not replicate true soil loss from a natural environment.…”

Section: Limitationsmentioning

confidence: 99%

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A review of soil erosion modeling in Nigeria using the Revised Universal Soil Loss Equation model

Ezeh,

Igwe,

Asare

et al. 2024

Agrosystems Geosci & Env

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Soil erosion is a severe soil degradation problem that endangers the actualization of Sustainable Development Goals. It affects agricultural production by reducing soil fertility via topsoil translocation, leading to soil quality deterioration. A review of soil erosion modeling using the Revised Universal Soil Loss Equation (RUSLE) model shows that Nigeria lags behind other developing countries like Ethiopia despite the massive improvements provided by remote sensing and geographic information system (GIS) technologies. Fewer than 50 articles were found on the Google Scholar search engine that used the RUSLE model for empirical studies on soil erosion. Only four research articles were found on the ScienceDirect website. Additionally, there were differences in the findings from studies across Nigeria. Such disparities were due to differences in the approaches used to estimate key factors in the RUSLE model. Therefore, we recommend that the Ministries of Agriculture and Environment take soil erosion research seriously by adopting proactive soil conservation and management measures. Ensemble models can be used including machine learning approaches rather than focusing mainly on structural intervention. In addition, there should be a harmonized look‐up table for the cover management factor and conservation practices factor that fairly represent the various ecoclimatic regions. The limitations to the model's use are highlighted, and a way forward is suggested.

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Section: Limitationsmentioning

confidence: 99%

“…The second was Musa et al. (2021) who validated their work using soil loss from a rainfall simulator. The use of a rainfall simulator is good, but it does not replicate true soil loss from a natural environment.…”

Section: State Of Rusle Modeling In Nigeriamentioning

confidence: 99%