【中文介绍】

  缺乏长期高精度的地表观测给我国水文气象研究带来了很大的不确定性。本文基于陆面水文模式（VIC 4.2.d, Variable Infiltration Capacity version 4.2.d）模拟构建了1961~2017年中国0.25°×0.25°逐日地表水文数据集（VIC-CN05.1）。其中，大气驱动数据为基于站点观测的CN05.1而土壤质地和水力性质参数来源于基于野外调查的高精度土壤数据集。VIC-CN05.1包含了产流、蒸散发、土壤湿度、积雪等水文变量和潜热/感热通量等地表热通量。本文采用多套地面站点观测和卫星反演数据，通过计算相对误差（RE）、纳什效率系数（NSE）以及相关系数（R）定量评估了该数据集。结果如下：VIC-CN05.1和UNH/GRDC的季节性产流在大多数流域吻合较好，尤其是在珠江、长江和东南流域（RE≤7%且NSE≥0.87）。VIC-CN05.1能较好地重现26个水文站在1980~2008年的逐月径流序列。在长白山、海北灌木和前燕州通量站，模拟与观测的2003~2005逐月潜热通量的平均NSE为0.61。而在中国东北部、中东部以及青藏高原中部，模拟和站点实测（438站点）的0~10cm逐月土壤湿度异常值的平均R达到0.8。在中国东北与西北区域，模拟的积雪深度、雪水当量和积雪覆盖与观测一致。除了西北流域，模拟的2003~2016年逐月地表水储量变化和GRACE卫星观测值在其他流域（尤其是在长江、黄河和淮河流域最好）的NSE均为正值且平均R为0.41。该地表水文数据集（VIC-CN05.1）受益于较准确的大气驱动数据、先进的参数化方案以及更真实的土壤性质，可作为中国水文气象研究的基准数据集，用于陆面模式的评估和长期的趋势分析等。

  【英文介绍】

  The lack of long-term consistent observational hydrological datasets over large scales brings great uncertainties to hydroclimatic research in China. This paper describes a daily 0.25°×0.25° terrestrial hydrological dataset (VIC-CN05.1) for China during 1961-2017. The dataset is simulated by the latest variable infiltration capacity (VIC) model and driven by pure station-based atmospheric forcings and high-resolution soil parameters based on field surveys. Multiple observational (in situ and remote sensing) products and five statistical metrics, including biases, relative error (RE), root mean square error (RMSE), Nash-Sutcliffe efficiency coefficient (NSE), and correlation coefficient (R), are used to validate the model outputs. The results indicate that the seasonal cycles of simulated total runoff and composite runoff from the University of New Hampshire and Global Runoff Data Centre (UNH/GRDC) show good agreement in the Yangtze, southeast, and Pearl River basins, with positive REs≤7% and NSEs≥0.87. At the Changbaishan, Haibei Shrubland, and Qianyanzhou flux towers, VIC-CN05.1 reproduces the monthly latent heat fluxes well during 2003-2005. The monthly modeled 0-10 cm soil moisture anomalies are highly correlated to in situ measurements (438 stations) during 2003-2016, with mean R=0.80. The spatial patterns of simulated and observed snow depth, snow water equivalent (SWE), and snow cover in winter are generally consistent in the northeastern and northwestern China. Except for the northwest basin, the simulated monthly terrestrial water storage changes in most river basins (particularly the Yangtze, Huai, and Yellow River basins) match well with observations based on the Gravity Recovery and Climate Experiment (GRACE) during 2003-2016, with positive NSEs and mean R=0.41. This terrestrial hydrology dataset is valuable for hydroclimatic research in China, such as model evaluations and long-term trend analyses.

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  【引用格式】       

   Miao, Y., and A. Wang, 2020: A daily 0.25° × 0.25° hydrologically based land surface flux dataset for conterminous China, 1961–2017. J. Hydrol., 590, 125413, doi: 10.1016/j.jhydrol.2020.125413.