【中文介绍】

   径流数据对旱涝预警及水资源管理至关重要。陆面水文模式能够重现大流域的逐月径流。大气再分析数据也提供高时空分辨率的产流估计，但需要在中国流域进行详细的评估。本文采用CaMa-Flood汇流模型将5个陆面模式离线模拟（VIC-CN05.1、CLM-CFSR、CLM-ERAI、CLM-MERRA和CLM-NCEP）和3个大气再分析数据（ERAI/land, JRA55和MERRA-2）中的产流汇流到中国26个水文站点（1980-2008）。并计算了四个指标（相关系数R、标准差R、纳什效率系数NSE和相对误差RE）定量评估和比较了8个数据集的质量。所有数据集都低估了月径流的量级和标准差。模拟与观测的月径流相关系数高（大于0.61）。除了CLM-MERRA、MERRA-2和CLM-NCEP，其他产品能很好地模拟洪峰（NSE高达0.41）。总体来说，8个数据集的质量从好到差为：VIC-CN05.1、ERAI/land、JRA55、CLM-CFSR、CLM-ERAI、MERRA-2、CLM-MERRA和CLM-NCEP。

  【英文介绍】

  Previous studies have demonstrated that offline land surface models (LSMs) and global hydrological models (GHMs) can reasonably reproduce streamflow in large river basins. Global reanalyses supply fine spatiotemporal runoff estimates, but they are not fully intercompared and evaluated in China. This study assesses the routed-runoff from five offline LSM/GHM runs (VIC-CN05.1, CLM-CFSR, CLM-ERAI, CLM-MERRA, and CLM-NCEP) and three reanalysis datasets (ERAI/Land, JRA55, and MERRA-2) against the gauged streamflow (26 stations) in major Chinese river basins during 1980–2008. The Catchment-based Macro-scale Floodplain model (CaMa-Flood) is employed to route those runoff datasets to the hydrological stations. Four statistical quantities, including the correlation coefficient (R), standard deviation (STD), Nash–Sutcliffe efficiency coefficient (NSE), and relative error (RE), along with a ranking method, are used to quantify the quality of those products. The results show that the spatial patterns of both modeled and observed streamflow in summer are similar, but their magnitudes are different. Except for MERRA-2, the other products can reproduce well the interannual variability of streamflow in both the Yangtze and Yellow River basins. All products generally underestimate the magnitude and variance of monthly streamflow, while VIC-CN05.1 and JRA55 are closer to observations compared to other products. The correlation coefficients for all products are overall larger than 0.61, with the highest value (0.85) from VIC-CN05.1. In addition to CLM-MERRA, MERRA-2, and CLM-NCEP with relatively small precipitation, other products can simulate peak flow well with positive NSEs up to 0.41 (ERAI/Land). Considerable uncertainties exist among the eight products at the Yellow River outlet, which might be because the LSMs ignore frequent human activities. Based on the above statistics, performances of the eight runoff products are ranked in descending order as follows: VIC-CN05.1, ERAI/Land, JRA55, CLM-CFSR, CLM-ERAI, MERRA-2, CLM-MERRA, and CLM-NCEP, which provides a reference for flood/hydrological drought warning and hydroclimatic research in the future.

  【关键图表】

       【引用格式】       

   Miao, Y., and A. H. Wang, 2020: Evaluation of routed-runoff from land surface models and reanalyses using observed streamflow in Chinese river basins. J. Meteor. Res., 34(1), 73–87.