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.