安全与环境学报

为了解决船闸应急管理能力评价中指标体系主客观权重分配合理性不足、管理能力的不确定性难以定量表征等问题，研究建立一套科学可靠的应急管理能力评价模型，以为内河航运安全畅通运行提供技术支持。首先，基于“预防、预警、响应、恢复”4个维度，构建包含11个二级指标与31个三级指标的应急管理能力评价体系；其次，采用改进熵权法优化指标权重分配，组合应用灰色聚类与云模型，综合量化应急管理风险的随机性与模糊性；最后，通过结果对比实现应急管理能力等级的判定。在实例应用中，改进熵权法可揭示各指标间的重要性差异，并明确“应急处置与救援”与“预防与应急准备”为应急管理判定的主要驱动因素，两者权重合计超过60%；灰色聚类与云模型组合应用管理能力的等级评价，克服了单一方法在等级临界值判定中的局限性，实现了系统薄弱环节的精准识别。基于案例评价结果，研究提出针对两个船闸的“补短板–强核心”与“固优势–稳边界”的差异化应急能力提升策略，为内河船闸应急管理能力的精准化改善与应急资源优化配置提供了理论依据与实践参考。

To address the significant issues of insufficient rationality in the subjective and objective weight allocation of the indicator system， as well as the challenges in accurately quantifying the uncertainty of management capability in evaluating ship lock emergency management capabilities， this study aims to establish a scientific， reliable， and practically applicable evaluation model for emergency management capabilities. This model provides robust technical support for the safe， efficient， and seamless operation of inland waterway transportation systems. Based on the four core dimensions of emergency management—namely "prevention， early warning， response， and recovery"—a comprehensive evaluation system was constructed， consisting of 11 secondary indicators and 31 tertiary indicators that cover all key aspects of ship lock emergency management. The improved entropy weight method was employed to optimize the allocation of indicator weights， reducing subjective biases. Additionally， the grey clustering method was integrated with the cloud model to comprehensively quantify the inherent randomness and fuzziness associated with emergency management risks. This approach allows for the scientific and accurate determination of emergency management capability levels through multi-method result comparison and verification. In the case application， the improved entropy weight method revealed significant differences in the importance of various evaluation indicators， highlighting that "emergency disposal and rescue" and "prevention and emergency preparedness" are the primary driving factors for emergency management evaluation， with their combined weight exceeding 60%. The combined use of the grey clustering method and the cloud model effectively overcame the limitations of single-method approaches in determining critical level values， allowing for precise identification of the system's weak links. Based on detailed case evaluation results， this study proposes targeted improvement strategies for emergency capabilities: "strengthening weak points and consolidating core competencies" and "stabilizing advantages and securing boundary capabilities" for two specific ship locks. These strategies provide a valuable theoretical foundation and practical operational guidance for the targeted enhancement of inland waterway ship lock emergency management capabilities and the rational optimization of emergency resource allocation.