全国山洪灾害调查评价成果数据类型多样、数据量大、数据结构关系复杂、专业性强。全国汇总数据量超过100TB，省级平均数据量达到TB级，数据有效管理难度大。本文基于行政区划隶属关系和小流域两条主线出发，设计全国山洪灾害调查评价数据模型，建立了对象实体模型、梳理了对象关系，利用ETL技术进行海量数据的多级综合与集成，形成多级数据综合成果。在此基础上，基于面向服务软件架构进行数据管理软件平台设计与开发，实现了不同管理层级差异化信息组织、多维信息关联分析、在线分析汇总统计等功能。解决了全国山洪灾害调查评价工作中海量多源数据管理、不同业务层级需求差异化等问题，可为各级山洪灾害调查评价数据管理与共享提供参考。

The results of the national investigation and evaluation of mountain flood come in various data types and large data volume, with complicated data structure and high degree of specialization. The national data volume reaches 100T, and the average provincial-level data volume reaches TB scale. It is difficult to manage these data effectively. In this paper, we designed a data model for national investigation and evaluation of mountain flood based on administrative division and small watershed, and established an entity model of the objects and analyzed the relationships of the objects. We used ETL technology to realize multi-level aggregation and integration of massive data. On this basis, we designed and developed a data management platform based on the service-oriented software architecture, and realized various functions such as differentiated information organization of different management levels, multi-dimensional information correlation analysis, and online analysis and summary. The construction of this platform solved some problems in national mountain flood investigation and evaluation such as multi-source massive data management and differentiated demand of different business levels. It can provide reference for management and sharing of mountain flood investigation data at all levels.

国家自然科学基金项目（51579131）;中国水科院科研专项（JZ0145B042016；JZ0145C022017)