Evaluating Cross-Drain Structures for Mitigating Highway Flooding in Recurring Flood Zones: A Case Study of Ubon Ratchathani Province, Thailand

Abstract

Recurring flooding represents a major natural hazard in Ubon Ratchathani, Thailand, causing significant disruptions to transportation and extensive damage. Recent disaster reports from the past five years emphasize that Ubon Ratchathani, a vital commercial and transportation hub in Northeastern Thailand, continues to experience frequent inundation events. While previous studies have examined highway flooding in Thailand, limited research has specifically addressed the optimization of cross-drainage structures in regions with high flood recurrence. Existing mitigation strategies often rely on generalized hydrological models, leading to inadequate drainage capacity. This study integrates hydrological modeling and field data to assess cross-drain performance, providing data-driven recommendations for enhancing highway flood resilience. The research employs hydrological modeling, specifically the MIKE Flood model, to analyze flood scenarios in areas characterized by moderate to high flood recurrence (4–8 occurrences per decade). It simulates drainage responses and evaluates the performance of existing infrastructure. The study investigates the current state of cross-drainage systems along Ubon Ratchathani Highway 2, covering 1,823.10 km2 and comprising 381 drainage units of 8 types. Runoff and peak flow rates for each drainage structure were computed, and simulations using MIKE 11 HD and MIKE 21 HD were conducted to simulate runoff conditions and river flow. The study highlights the need for targeted interventions, including increasing culvert dimensions, improving maintenance protocols, and integrating real-time flood monitoring systems. Implementing these measures can significantly enhance drainage performance and minimize the impact of recurring highway flooding. The MIKE Flood model successfully simulated flood extents in sub-areas M1 to M8, aligning closely with observed data, confirming the model's accuracy. The results provide essential flow dimension guidelines for future flood mitigation. These insights can help optimize cross-drainage structures, reducing economic losses and transportation disruptions in flood-prone areas like Ubon Ratchathani.