Evolutionary Prediction of Soil Loss from Observed Rainstorm Parameters in an Erosion Watershed Using Genetic Programming
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Date
2021
Journal Title
Journal ISSN
Volume Title
Publisher
Applied and Environmental Soil Science
Abstract
Various environmental problems such as soil degradation and landform evolutions are initiated by a natural process known as soil
erosion. Aggregated soil surfaces are dispersed through the impact of raindrop and its associated parameters, which were
considered in this present work as function of soil loss. In an attempt to monitor environmental degradation due to the impact of
raindrop and its associated factors, this work has employed the learning abilities of genetic programming (GP) to predict soil loss
deploying rainfall amount, kinetic energy, rainfall intensity, gully head advance, soil detachment, factored soil detachment, runoff,
and runoff rate database collected over a three-year period as predictors. +ree evolutionary trials were executed, and three models
were presented considering different permutations of the predictors. +e performance evaluation of the three models showed that
trial 3 with the highest parametric permutation, i.e., that included the influence of all the studied parameters showed the least error
of 0.1 and the maximum coefficient of determination (R2) of 0.97 and as such is the most efficient, robust, and applicable GP model
to predict the soil loss value.
Description
Keywords
Soil Loss, Rainstorm Parameters, Erosion Watershed, Genetic Programming
Citation
Onyelowe, K. C., Ebid, A. M., & Nwobia, L. (2021). Evolutionary Prediction of Soil Loss from Observed Rainstorm Parameters in an Erosion Watershed Using Genetic Programming. Applied and Environmental Soil Science, 2021. https://doi.org/10.1155/2021/2630123