Understanding runoff changes in the Yarlung Zangbo (YZ) basin is crucial for water resource management on the Tibetan Plateau (TP), but has been hindered by sparse data. This study provides a comprehensive hydrometeorological dataset for the YZ basin spanning 1961–2024, including both daily meteorological variables and hydrological components. The dataset integrates observations from 26 meteorological stations, 15 hydrological stations, and hydrological model simulations. Specifically, it includes: (1) daily meteorological variables (precipitation, mean, maximum, and minimum temperature, and wind speed) at both 26 meteorological stations and a 10-km gridded scale; and (2) daily total runoff and its components (snowmelt, glacier runoff, and rainfall runoff) at the 10-km gridded scale, derived from a physically based hydrological model. The meteorological fields were extended using a random forest–based machine learning approach combined with ERA5 reanalysis data, while the hydrological variables were generated from physically based hydrological model simulations. To facilitate direct application of hydrological station data, the gridded daily hydrological data for 1961–2024 were further routed to 15 hydrological stations. The generated dataset was validated against in situ meteorological at different scales and hydrological observations and compared with other meteorological products, demonstrating good applicability in the YZ. This dataset is available at the National Tibetan Plateau Data Center. The dataset enables basin-wide simulations of hydrological processes across multiple scales and provides a valuable resource for assessing water cycle dynamics and their responses to climate and cryospheric changes in the YZ basin.
Sun et al. (Fri,) studied this question.