<![CDATA[Transportation infrastructure, specifically roads, plays a vital role in supporting social and economic activities. However, road quality is susceptible to degradation caused by the increasing number of heavy vehicles and high traffic loads. In addition to traffic loads, poor drainage performance leading to water ponding also contributes significantly to road infrastructure damage. This study aims to evaluate road damage and analyze the correlation between drainage performance and road structural damage on Pangeran Tirtayasa Road, spanning a length of 6.6 km. The research methodology involved primary data collection through field surveys to determine the Pavement Condition Index (PCI) for every 50-meter segment. Additionally, dimensions of the existing drainage were measured to calculate runoff discharge. The relationship between runoff discharge and PCI values was then analyzed using the simple linear regression method. The evaluation results indicate highly varied road conditions; on the left lane, the majority of the road is in Very Poor (24 segments) and Poor (23 segments) condition, while the right lane is dominated by Very Poor (26 segments) and Very Good (22 segments) conditions. Hydraulic evaluation further proves that the existing drainage is inadequate, resulting in runoff flooding in 50 segments of Direction A and 67 segments of Direction B. Despite the occurrence of runoff, regression analysis shows that the correlation between runoff discharge and PCI values is very weak, at only 5.65% for Direction A and 3.12% for Direction B. In conclusion, while runoff discharge does influence road damage, the weak correlation is attributed to field anomalies where certain road segments were recently reconstructed—resulting in high PCI values—but the accompanying drainage systems were not improved. Based on these findings, the existing drainage dimensions need to be redesigned to prevent water runoff onto the road surface. Keywords: Road Damage, Pavement Condition Index (PCI), Drainage, Water Runoff, Linear Regression]]>
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