Title:

A Methodology to Account for Rising Groundwater in Flexible Pavement Analysis and Design

Many pavement design methods, including the widely adopted AASHTO 1993 empirical approach and most mechanistic-empirical (M-E) approaches only account for seasonal variation of subgrade modulus throughout the pavement life and use either a single stiffness measure or a single set of seasonal values for the whole subgrade layer. This limits their reliability under changing moisture conditions caused by rising groundwater tables (GWT) due to climate change, Sea Level Rise (SLR) or other factors. This study introduces a methodology to integrate temporal and spatial variations in subgrade modulus due to rising groundwater into existing empirical and M-E pavement design methods. The approach uses Soil-Water Characteristic Curve (SWCC) relationships to model moisture-dependent modulus changes and applies Layered Elastic Analysis (LEA) to derive equivalent modulus values. Predictive models were developed for all standard AASHTO subgrade soil classes, enabling more accurate pavement performance forecasts under varying groundwater conditions. To demonstrate application of this work, the predictive models were applied to predict pavement deterioration curves for empirical and M-E approaches that reflect evolving moisture conditions on pavement performance over time. The final output of this study is a set of predictive models that can be leveraged to improve pavement resilience by informing more effective decision-making, optimizing design strategies, and supporting proactive adaptation to changing moisture conditions.

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