Abstract Multiple global datasets simulated by different land surface models (LSMs) are useful for providing information to decision-makers on the water balance in different subareas of a river basin. As a large basin covering a vast area, the Yellow River Basin (YRB) represents a typical case to evaluate the water cycle components in LSM products. The main objective of this study is to evaluate and compare multiple LSM products with respect to precipitation, runoff, evapotranspiration (ET) and terrestrial water storage anomaly (TWSA). The datasets analyzed include different Global Land Data Assimilation System (GLDAS) products, ERA-Interim/Land datasets, and augmented Noah LSM products with multiple parameterization options (Noah-MP) driven by different GLDAS forcing datasets. The evaluation is conducted with reference to gauge-based precipitation datasets, reconstructed natural streamflow and Gravity Recovery and Climate Experiment (GRACE)-derived TWSA. Several statistical metrics and the partitioning of runoff and ET were emphasized. The results show that the products generated diverse spatial patterns for the water cycle components. The ERA-Interim/Land data present the best performance almost for all water cycle components. The three models (variable infiltration capacity (VIC), Mosaic and community land model (CLM)) driven by GLDAS version 1 generated different but large systematic biases, and the Noah model performs the best among the four models. The Noah simulation of GLDAS version 2.0 (GLDAS-2.0) and the Noah-MP simulation with the Princeton Global Forcing also have systematically large biases for runoff. The different Noah-MP simulations perform better for runoff (although overestimated) than other models used in GLDAS, but present the poorest correlations of TWSA to GRACE-derived TWSA. The ensemble averages of multiple products perform the best for precipitation and ET than any other individual product but not for runoff.

中文翻译：

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黄河流域水收支的多种地表产品比较与评价

摘要 由不同地表模型 (LSM) 模拟的多个全球数据集有助于为决策者提供有关流域不同分区的水平衡信息。黄河流域（YRB）是一个面积广阔的大流域，是评估 LSM 产品中水循环成分的典型案例。本研究的主要目的是在降水、径流、蒸散 (ET) 和陆地储水异常 (TWSA) 方面评估和比较多个 LSM 产品。分析的数据集包括不同的全球土地数据同化系统 (GLDAS) 产品、ERA-Interim/土地数据集以及由不同 GLDAS 强迫数据集驱动的具有多个参数化选项的增强 Noah LSM 产品 (Noah-MP)。评估是参考基于仪表的降水数据集、重建的自然水流和重力恢复和气候实验 (GRACE) 得出的 TWSA 进行的。强调了几个统计指标以及径流和 ET 的划分。结果表明，这些产品为水循环组件产生了不同的空间模式。ERA-Interim/Land 数据显示了几乎所有水循环组件的最佳性能。由 GLDAS 版本 1 驱动的三个模型（可变渗透能力（VIC）、马赛克和社区土地模型（CLM））产生了不同但较大的系统偏差，而诺亚模型在四个模型中表现最好。GLDAS 2.0 版 (GLDAS-2.0) 的 Noah 模拟和使用普林斯顿全球强迫的 Noah-MP 模拟也对径流具有系统性较大的偏差。与 GLDAS 中使用的其他模型相比，不同的 Noah-MP 模拟对径流的表现更好（尽管被高估），但 TWSA 与 GRACE 衍生的 TWSA 的相关性最差。多个产品的集合平均值在降水和 ET 方面的表现优于任何其他单个产品，但在径流方面则不然。