All hydrological models need to be calibrated to obtain satisfactory streamflow simulations. Here we present a novel parameter regionalization approach that involves the optimization of transfer equations linking model parameters to climate and landscape characteristics. The optimization was performed in a fully spatially distributed fashion at high resolution (0.05°), instead of at lumped catchment scale, using an unprecedented database of daily observed streamflow from 4,229 headwater catchments (<5,000 km²) worldwide. The optimized equations were subsequently applied globally to produce parameter maps for the entire land surface including ungauged regions. The approach was evaluated using the Kling‐Gupta efficiency (KGE) and a gridded version of the hydrological model HBV. Tenfold cross validation was used to evaluate the generalizability of the approach and to obtain an ensemble of parameter maps. For the 4,229 independent validation catchments, the regionalized parameters yielded a median KGE of 0.46. The median KGE improvement (relative to uncalibrated parameters) was 0.29, and improvements were obtained for 88% of the independent validation catchments. These scores compare favorably to those from previous large catchment sample studies. The degree of performance improvement due to the regionalized parameters did not depend on climate or topography. Substantial improvements were obtained even for independent validation catchments located far from the catchments used for optimization, underscoring the value of the derived parameters for poorly gauged regions. The regionalized parameters—available via www.gloh2o.org/hbv—should be useful for hydrological applications requiring accurate streamflow simulations.

中文翻译：

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基于来自4,229个源头集水区的观测水流的全球完全分布式参数区域化

所有水文模型都需要进行校准以获得令人满意的水流模拟。在这里，我们提出了一种新颖的参数区域化方法，其中涉及将模型参数链接到气候和景观特征的传递方程式的优化。优化是使用高分辨率（0.05°）在空间上完全分布的方式进行的，而不是集水区的集总规模，它使用了前所未有的每日观测到的来自4,229个源头集水区（<5,000 km ²）在全球范围内。随后，将优化的方程式全局应用，以生成包括未覆盖区域在内的整个陆地表面的参数图。使用Kling-Gupta效率（KGE）和水文模型HBV的网格化版本对该方法进行了评估。十倍交叉验证用于评估该方法的通用性并获得参数图的整体。对于4,229个独立的验证流域，区域化参数得出的平均KGE为0.46。KGE改进的中位数（相对于未校准的参数）为0.29，88％的独立验证流域获得了改进。这些分数与以前的大型集水区样本研究的分数相比具有优势。由于区域化参数而导致的性能改善程度并不取决于气候或地形。即使对于独立的验证集水区也获得了实质性的改进，这些集水区距离用于优化的集水区较远，这突出了针对测量欠佳区域的导出参数的价值。可通过www.gloh2o.org/hbv获得的区域化参数对于需要精确模拟水流的水文应用很有用。