小流域设计洪水推求对防洪减灾至关重要，但传统方法存在参数提取繁琐、计算流程复杂、智能化水平低等问题。为此，本文提出一种基于多模态大语言模型智能体的小流域设计洪水自动化推求方法。该方法首先构建了一个融合空间插值栅格与数字化图表的多模态设计洪水参数集；其次，构建了一个以DeepSeek-V3为核心的智能体，并围绕其设计了包含数据服务、推理公式法和广东省综合单位线法计算服务的模块化API体系；最后，智能体通过工具调用机制，自主理解用户自然语言指令，自动规划并执行完整的设计洪水推求工作流程。以潖江流域为例进行的实例验证表明，本方法智能体能自主完成从任务解析到报告生成的全流程，且计算结果与广东水文水利设计计算软件平台高度一致。所提方法为解决复杂水文计算流程自动化提供了新的技术路径，验证了多模态大语言模型智能体在智慧水利领域应用的有效性与准确性。

The estimation of design floods in small watersheds is crucial for flood control and disaster mitigation. However, conventional methods suffer from drawbacks such as tedious parameter extraction, complex calculation processes, and a low degree of automation. To address these challenges, this paper presents an automated approach for design flood estimation in small watersheds based on a multi-modal large language model agent. The methodology first involves constructing a multi-modal parameter set for design floods, which integrates spatially interpolated grids with digitized charts. Subsequently, an intelligent agent is developed with DeepSeek-V3 as its core, supported by a modular API framework that provides services for data access, the Rational Method, and the Guangdong Provincial Comprehensive Unit Hydrograph method. Leveraging a tool-calling mechanism, the agent can autonomously interpret natural language instructions from users to plan and execute the entire workflow for design flood estimation. A case study on the Pajiang River Basin demonstrates that the agent can independently manage the full process, from task parsing to final report generation. The results show a high degree of consistency with those obtained from the official Guangdong Hydrological and Water Resources Design and Calculation Software Platform. This proposed method offers a novel technical path for automating complex hydrological calculations and validates the effectiveness and accuracy of multi-modal LLM agents in the field of smart water conservancy.