Exploring the Correlation Between Winter Severity Indices and Winter Maintenance Costs: Insights and Comparative Analysis from Nationwide Practices

Abstract

Winter maintenance operations are essential for safe and efficient transportation, yet unpredictable weather introduces major challenges in cost and material planning. A single severe snowfall can deplete resources midway through the season, while milder-than-expected winters may result in unused surpluses. The Winter Severity Index (WSI) provides a standardized measure of winter intensity, offering a promising tool to address these challenges. This study explores the relationship between WSIs and winter maintenance costs through a nationwide survey of state DOTs and Clear Roads survey data. The Clear Roads survey analysis involves regression models, assessing the relationship between the Accumulated Winter Season Severity Index (AWSSI) and winter maintenance expenditures across different U.S. climate divisions. AWSSI was used not as a recommended tool for operations, but as a nationally available and consistent index to investigate whether winter severity is statistically associated with cost trends on a broad scale. The study also assessed nonlinear regression models, which yielded similar results to linear models; the linear model was, therefore, retained for its simplicity and interpretability. Results show significant correlation within various climate clusters, indicating that weather severity can explain cost variability. The study reveals that WSIs can improve winter maintenance budget management, but their effectiveness is regionally nuanced. Customized WSIs are essential to improve resource planning, as the findings indicate that AWSSI does not work optimally in all geographic contexts. The study also identified best practices by state departments of transportation (DOTs), such as integrating WSIs with real-time tools such as the Road Weather Information Service and the Maintenance Decision Support System, to enhance planning accuracy and responsiveness.