Current health status of check dams and their flood control capacity amid frequent heavy rainfall events remain unclear, partially due to lack of a comprehensive and efficient method for health assessment targeting potential heavy rainfall pressures. To address this gap, this study developed a health assessment framework for check dams under heavy rainfall scenarios. This framework evaluated health of check dams based on structural composition and integrity, siltation capacity, and flood control pressure. Indicators for these three aspects were calculated based on a real-world 3D model and a high-resolution DEM generated by unmanned aerial vehicle (UAV) tilt photography for a typical watershed on the Loess Plateau. Applied to 138 check dams, the framework objectively classified 44% (61 dams) as unhealthy, highlighting its ability to pinpoint dams that simultaneously experience structural issues, full siltation, or extreme flood pressures. Furthermore, the assessment framework directly informed targeted management actions, identifying dams in need of repairs, height increases, spillway upgrades, or comprehensive improvements. At the sub-watershed level, this framework revealed clear spatial patterns of dam health issues, with over 70 % of unhealthy dams concentrated in the Majiagou and Tianjiagou sub-watersheds. Such spatially explicit outcomes underscore the utility of the framework in guiding prioritized monitoring and maintenance, particularly during critical flood seasons. The indicators used in the framework are both accessible and reliable, enhancing its suitability for large-scale application. Overall, this study offers a robust scientific and methodological foundation for the maintenance, reinforcement, and future planning of check dams in the Loess Plateau region.