With the rapid development of water conservancy engineering and infrastructure construction, there are many safety hazards in the construction process of water conservancy engineering, so it is of great significance to study the potential hazards in the construction process. In this context, this paper proposes a task scenario-based association mining method for hydraulic engineering hidden danger records. By analyzing transaction characteristics, the traditional Apriori algorithm is improved to optimize pruning results and generate hidden danger association rules. The research results of this paper have been successfully applied to the investigation and management of hidden dangers in the Xinmenghe dredging project. Based on the mapping of association rules driven by task scenarios, hidden dangers association rules in specific task scenarios are mined to assist construction safety managers in hidden dangers investigation, which reduces the complexity of the algorithm, reduces the running time of the algorithm and improves the efficiency of the algorithm.