Abstract: Under the combined effects of climate change, intensified human activities, and structural aging, dam safety hazards have long been a major concern in reservoir safety management in China. The dispersed and unstructured nature of dam distress information limits its effective utilization. Existing understanding of dam safety hazards has mainly relied on expert experience and small-scale engineering statistics, while nationwide statistical analyses are rarely seen. In this study, based on the national dam basic information database and safety evaluation reports of more than 20, 000 defective reservoir dams identified over the past 10 years, artificial intelligence techniques are used to extract and structurize hazard information, resulting in the preliminary construction of a nationwide reservoir dam distress database. Statistical analyses are conducted from the dimensions of engineering scale, completion time, dam type, dam height, and geographic location to analyze dam safety hazard characteristics at the national scale, and corresponding countermeasures and suggestions are proposed. The results show that seepage-related and structural safety issues are the two most prominent hazard types. Flood control safety hazards are most prominent in medium and small reservoirs, particularly for small reservoirs in northern regions such as the Songliao and Yellow River basins. Seismic safety hazards are relatively concentrated in the Haihe and Southwest Rivers region. Metal structure problems are more prominent in large and medium reservoirs. This study provides technical support for reservoir dam safety management in China, decision-making regarding hazard elimination and reinforcement of defective reservoirs, and the establishment of a long-term effective mechanism.