Planning Nondestructive Culvert Network Condition Inspections: A Dual-Risk Assessment Approach

Culvert inspection programs often rely on uniform, calendar-based visual inspections informed by culvert condition or age. However, visual methods are subjective, incapable of detecting internal defects, and inefficient as they fail to account for variations in hazard exposure and deterioration rates. Condition-based prioritization typically supports reactive maintenance by identifying damage only after deterioration has occurred, whereas hazard-exposure-based monitoring enables proactive or prescriptive maintenance by addressing failure mechanisms in advance. Nondestructive testing (NDT) offers a more diagnostic alternative but is constrained by cost and logistical complexity. Full-network deployment of NDT is neither feasible nor necessary; targeted planning is essential for efficiency. This study presents a dual-risk reinforced concrete culvert NDT deployment framework that integrates independently estimated hydraulic inadequacy and structural weakness serviceability hazard rates into a joint-risk metric. Hazard rates for 2,190 culverts in Ethiopia were derived from Γ-frailty Cox proportional hazards models. Kendall’s τ ≈ 0.043(p = 0.0102) indicated negligible dependence between hazards, supporting aggregation via a weighted geometric mean and retaining a copula-based fallback for stronger dependence. Culverts were classified into four joint-risk quadrants using 66th percentile cutoffs, and composite scores were mapped to five NDT intervals: annual, biennial, triennial, quinquennial, and decennial. Optimized through brute-force grid search and benchmarked against a uniform three-year cycle over 30 years, the strategy reduced inspection labor hours by 35% while capturing 80% of cumulative joint risk within the top 53% of culverts. This framework offers transportation agencies a scalable, data-driven approach to prioritize inspections, enhance safety, and reduce costs.