Assessment of Road Deterioration in Desert Environments Using a Quantitative Index and a MultipleLinear Regression Model: A Case Study of Idlim Road between Murzuq and Traghen
Keywords:
Road Maintenance, Distress Index (DI), Geographic Information Systems (GIS), Quantitative Analysis, Predictive Modeling, Desert Roads, Road SafetyAbstract
This study aims to evaluate the structural and functional condition of the Idlim road connecting the cities of Murzuq and Traghen in southwestern Libya, in light of the suspension of maintenance activities since 2013, and to analyze the resulting engineering, economic, and social impacts. The study adopts a quantitative analytical approach supported by field surveys and traffic data analysis. In addition, the Distress Index (DI) was employed as a quantitative tool to assess the current level of deterioration, while Geographic Information Systems (GIS) were utilized to analyze the spatial variation along the road.
Furthermore, a mathematical model was developed to predict the future condition of the road under continued absence of maintenance. The results indicate a significant increase in DI values, reflecting an advanced stage of deterioration and a continuous upward trend, which implies an accelerated loss of functional performance. The spatial analysis also revealed variability in deterioration levels across different segments of the road, influenced by environmental conditions and traffic loads, particularly heavy trucks.
The predictive results suggest that the road is approaching functional failure if no intervention is implemented, which negatively affects transportation costs, road safety, and the efficiency of essential services. The scientific contribution of this study lies in presenting an integrated analytical framework that combines quantitative assessment, spatial analysis, and future prediction, providing a practical model applicable to road evaluation and maintenance in desert environments.
The study recommends adopting maintenance strategies based on scientific analysis and enhancing the use of modern monitoring technologies to improve infrastructure performance and ensure its sustainability.
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