The coupled hydrology–human activity information (CHHAI) dataset: a global benchmark dataset for model comparison and evaluation
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Taylor & Francis
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To enhance hydrologic modeling, the hydrology community has developed benchmark datasets (e.g. Model Parameter Estimation Experiment, MOPEX), providing standardized data for model evaluation and parameter estimation. However, these datasets primarily focus on modeling natural hydrologic processes, leaving a critical gap in understanding the role of human influences. Here, we introduce the Coupled Hydrology-Human Activity Information (CHHAI) dataset, a benchmark dataset that integrates coupled human–water data from regions across all continents, excluding Antarctica. CHHAI incorporates data from 25 regions that cover various human impacts such as reservoir management, flood protection, river management policies, land use changes, and water use. 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 to support the development of improved strategies for managing coupled human–water systems.
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hydrology, datasets, models, hydrological modelling, water systems, basins