Assessment and Prediction of Effects of Geo-Environmental Hazards on Road Infrastructure Using an Ensemble Modeling Approach: A Case Study of Limuru - Mai Mahiu - Narok Road and Its Environs, Kenya

In pursuit of a climate-resilient road infrastructure, the present study focused on the assessment and prediction of the aggregated effects of flooding and land subsidence on the Limuru - Mai Mahiu - Narok road in Kenya. The study used datasets which include: rainfall, land use land cover, normalized difference vegetation index, curve numbers, topographic wetness index, river density, slope, slope-length factor, soil texture, landforms, sediment transportation index and lineaments. A GIS-ensemble modeling approach coupling the multi-criteria decision analysis (MCDA) and principal component analysis (PCA) was used to simulate the combined effects of flooding and land subsidence on the road infrastructure for the year 1991, 2002, 2011 and 2021. Cellular automata-Markov chain analysis was used to predict the combined effects of flooding and land subsidence for the year 2030. The results revealed that the Limuru - Mai Mahiu - Narok road was prone to moderate, high and extremely high vulnerability levels. The vulnerability was dire in the year 2002 where about 77.4% of the road’s manifested moderate, high and extremely high vulnerability levels. Besides, the road was least susceptible in the year 2021 since only about 49.1% of its length revealed moderate, high, and extremely high vulnerability levels. The prediction results depicted that by the year 2030, the length of the road infrastructure that would be vulnerable to moderate, high, and extremely high levels would increase by about 13.52%. The research findings provide essential information that would assist in the identification and implementation of appropriate engineering and non-engineering interventions to the affected sections, thus promoting resilience of the road.