HydroCraft: an efficient online platform for hydrological modeling integrated with a large language model agent
Mahmut Tudaji, Fuqiang Tian, Xiannan Wu
Tsinghua University
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摘要与影响
Hydrological modeling is essential for water resources management but often requires specialized expertise, creating a significant barrier to its broad application. To address this challenge, we developed HydroCraft, a web-based platform designed to democratize the modeling process. HydroCraft provides a comprehensive and integrated workflow for basin extraction, driving data generation, parameter calibration, and result visualization, enabling rapid modeling for any watershed globally. Key features of the platform include: an adaptive watershed delineation method that optimizes the distribution of computational units based on user-defined sub-basin area thresholds; the integration of three hydrological models (THREW, Xin’anjiang, and Miyun Hydrological Model) suitable for diverse climatic and geological conditions; and the incorporation of a Large Language Model (LLM) agent, which serves as a robust assistant to provide guidance and automated task execution. Users only need a device with a web browser and an internet connection to perform advanced hydrologic simulations. Two case studies (user-driven vs. LLM-agent-assisted) demonstrated the platform’s efficiency and intelligence. The platform advances hydrological modeling toward greater intelligence and accessibility, providing support for applications such as water resource management and flood forecasting
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物理Environmental Monitoring and Data Management
Hydrology and Watershed Management Studies · Hydrological Forecasting Using AI
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