Determining the precise placement of hydrological stations on a simulated digital river network is crucial for constructing hydrological models applicable to process simulation, water resource management, and flood forecasting endeavors. To solve this problem, we categorized and scrutinized deviations between the simulated and their actual station locations, and proposed a novel automatic hydrological station relocation algorithm (ASRA). The algorithm was first validated in the Amazon Basin using Global Runoff Data Centre (GRDC) hydrological stations and 90 m × 90 m Shuttle Radar Topography Mission (SRTM) data, successfully correcting the spatial position and corresponding catchment area (CCA) of each station. Findings revealed that CCA inaccuracies were notably decreased, transitioning from an initial 7.62% when employing a conventional 5-km search radius to 5.43% after adopting an iteratively optimized, objective, and rational 8-km search radius. The ASRA method was subsequently applied to GRDC stations within the HDMA and HydroSHEDS data sets, successfully repositioning 8,339 and 8,026 stations respectively, all with catchment area deviations of less than 5%, thus either exceeding or at least equaling the precision of prior research efforts. A Python program was developed and incorporated into an ArcGIS toolbox that features user-friendly attributes, enabling swift computation and accurate rectification, as a result of building upon our method. In short, our study presents a fresh approach and a robust tool for tackling the inconsistencies of hydrological station locations. The updated global GRDC hydrological station locations specifically tailored for both HDMA and HydroSHEDS data sets, together with the toolbox developed, were accessible for download on the figshare platform.

中文翻译：

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一种新的自动水文站迁移算法（ASRA），用于将水文站移至模拟数字河网

确定模拟数字河网中水文站的精确位置对于构建适用于过程模拟、水资源管理和洪水预报工作的水文模型至关重要。为了解决这个问题，我们对模拟站位置与实际站位置之间的偏差进行了分类和审查，并提出了一种新颖的自动水文站重定位算法（ASRA）。该算法首先在亚马逊流域使用全球径流数据中心（GRDC）水文站和90 m × 90 m航天飞机雷达地形任务（SRTM）数据进行验证，成功校正了每个站的空间位置和相应的集水区（CCA）。结果表明，CCA的误差明显降低，从最初采用传统5公里搜索半径时的7.62%，转变为采用迭代优化、客观合理的8公里搜索半径后的5.43%。 ASRA 方法随后应用于 HDMA 和 HydroSHEDS 数据集中的 GRDC 站点，分别成功重新定位了 8,339 个和 8,026 个站点，所有流域面积偏差均小于 5%，从而超过或至少等于先前研究工作的精度。基于我们的方法，开发了一个 Python 程序并将其合并到 ArcGIS 工具箱中，该程序具有用户友好的属性，能够实现快速计算和准确校正。简而言之，我们的研究提出了一种新的方法和强大的工具来解决水文站位置的不一致问题。专为 HDMA 和 HydroSHEDS 数据集量身定制的更新后的全球 GRDC 水文站位置以及开发的工具箱均可在Figshare 平台上下载。