Estimate of the Reduction in the Impact of Rainwater on Road Degradation in the Mbanya Catchment Area

This article is part of the sustainable development of road infrastructure. It assesses the effects of rainwater on unpaved roads in the Mbanya catchment area between January 2019 and December 2023, and proposes mitigation measures. July is the month when the risk of deterioration on these unsealed roads is highest. The aim of the work is to limit the impact of rainwater on the deterioration of roads in the Mbanya catchment area. To this end, an experimental study was carried out to determine the initial water content in the soil and the quantity of quicklime needed to stabilise the soil. Genetic algorithms and neural networks were used to estimate the water content at different depths in the soil. The square correlation coefficient, with a value of around 0.72, and the root mean square error, with a value of around 0.37 on all the test data are performance indicators that demonstrate the high accuracy of the coupled genetic algorithm-neural network model. Porosity and the quantity of lime were used as input parameters for the model, and the results show that porosity and the quantity of lime have an influence on the evolution of the water content in the soil. The pavement construction project is possible on these unsealed roads in the Mbanya watershed, as the soils have a bearing capacity P ≥ .20MPa. However, the increase in water content can weaken as well as reduce the bearing capacity of the soil. Treating the soil with quicklime can lower the water content after water consumption and strengthen the bearing capacity.