Engineering

Volume 14, Issue 7 (July 2022)

ISSN Print: 1947-3931   ISSN Online: 1947-394X

Google-based Impact Factor: 0.66  Citations  

Determination of a Mathematical Model of Erosion Taking into Account the Intensity of Rainfall and Soil Slopes from the Global MNT Model

HTML  XML Download Download as PDF (Size: 1827KB)  PP. 274-284  
DOI: 10.4236/eng.2022.147022    103 Downloads   487 Views  

ABSTRACT

Our study is being carried out in the Wouri Estuary more precisely in the Nylon area, Douala. This area is influenced by abundant rainfall which promotes the phenomenon of rain erosion. This erosion contributes to the degradation of structures and soils. To better understand and predict this phenomenon of rainfall erosion, we set out to establish a mathematical model that takes into account precipitation and topography. To this end, the data collected in the field and in the laboratory made it possible. First, we graphically modeled the variation of the potential as a function of the intensity of rainfall and the slope of the ground. Next, we identified a mathematical model from cubic spline surface interpolation. Finally, we obtained the mathematical model which makes it possible to evaluate and predict the erosion potential. The results obtained allowed to have an erosion potential of 153.67 t/ha/year with field data and 153.94 t/ha/year with laboratory data. We compared the results obtained with those existing in the literature on the same study site. This comparison made it possible to validate the established mathematical model. This mathematical model is a decision support tool and can predict problems related to water, erosion and the environment.

Share and Cite:

Mbiakouo-Djomo, E. , Odi-Enyegue, T. , Abanda, A. , Tchemou, G. , Djiofack-Tiagho, U. , Tcheukam-Toko, D. , Réné, N. , Fokwa, D. and Njeugna, E. (2022) Determination of a Mathematical Model of Erosion Taking into Account the Intensity of Rainfall and Soil Slopes from the Global MNT Model. Engineering, 14, 274-284. doi: 10.4236/eng.2022.147022.

Cited by

No relevant information.

Copyright © 2024 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.