Coupled Hydrology-Human Activity Information (CHHAI) dataset

To enhance hydrologic modeling, the hydrology community has developed benchmark datasets, such as those from the Model Parameter Estimation Experiment (MOPEX) and the Distributed Model Intercomparison Project (DMIP), which provide standardized input data for model evaluation and parameter estimation. However, these past experiments and datasets primarily focus on modeling natural hydrologic processes, leaving a critical gap in understanding the role of human influences. Human activities, including dam operations, river channelization, groundwater pumping, irrigation, inter-basin water transfers, and urbanization, can profoundly alter local hydrologic systems. These effects vary widely across the world, presenting unique challenges that require comprehensive data to address. In response, a wide range of sociohydrological frameworks and coupled human-water models have been developed to explicitly incorporate human activities into hydrologic modeling. As the demand for incorporating human behavior into models grows, there is an increasing need for reliable, human-water datasets that capture these interactions for validation, verification and model comparison. Inspired by MOPEX, we introduce the Coupled Hydrology-Human Activity Information (CHHAI) dataset, a benchmark dataset that integrates coupled human-water data from river and lake basins across all continents, excluding Antarctica. CHHAI incorporates data from over twenty basins that cover various human impacts such as reservoir management, flood protection, river management policies, land use changes, and water use and withdrawal. Each basin reflects distinct challenges, providing a diverse and globally representative resource for researchers studying these processes. By offering standardized datasets for modeling and analysis, CHHAI aims to enhance our understanding of interactions between people and water and support the development of improved strategies for managing coupled human-water systems.

为提升水文模拟研究水平，水文领域学界已构建诸多基准数据集，例如模型参数率定实验（Model Parameter Estimation Experiment, MOPEX）与分布式模型对比实验（Distributed Model Intercomparison Project, DMIP）所产出的数据集，它们可为模型评估与参数率定提供标准化输入数据。然而，过往此类实验与数据集主要聚焦于自然水文过程模拟，在厘清人类活动影响作用方面存在关键研究空白。人类活动包括大坝调度、河道整治、地下水开采、灌溉、跨流域调水以及城市化等，可对局地水文系统造成深刻改变。这类影响在全球范围内差异显著，带来了独特的研究挑战，亟需配套的综合数据予以应对。为此，学界已开发出一系列社会水文框架与人水耦合水文模型，旨在将人类活动明确纳入水文模拟流程。随着将人类行为纳入模型的需求日益增长，开发可靠的人水耦合数据集以刻画二者间的相互作用，用于模型验证、校验与对比分析的呼声愈发高涨。受MOPEX研究启发，本研究推出了耦合水文-人类活动信息数据集（Coupled Hydrology-Human Activity Information, CHHAI），这是一套基准数据集，整合了除南极洲外全球各大陆河湖流域的人水耦合数据。CHHAI涵盖20余个流域的数据，覆盖水库调度、防洪减灾、河道管理政策、土地利用变化以及用水与取水等多种人类影响类型。每个流域均体现出独特的研究挑战，可为从事相关过程研究的学者提供具备多样性与全球代表性的研究资源。通过为模拟与分析提供标准化数据集，CHHAI旨在加深我们对人与水相互作用的理解，并为优化人水耦合系统的管理策略提供支撑。