Hydrography90m: A new high-resolution global hydrographic dataset
Hydrography90m: A new high-resolution global hydrographic dataset
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Hydrography90m：新的高分辨率全球水文数据集
DOI：
10.5194/essd-2022-9
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发表时间：
2022
影响因子：
11.4
通讯作者：
S. Domisch
中科院分区：
文献类型：
--
作者：
G. Amatulli;Jaime R. García Márquez;Tushar Sethi;Johannes Kiesel;Afroditi Grigoropoulou;Maria M Üblacker;L. Shen;S. Domisch
抽象的。溪流和河流的地理分布驱动着水文学、地貌学、地理学和生态学中的多种模式和过程。因此，在地球科学中，一个能以同样的精度，沿着它们的地形和拓扑特性，精确地划分小溪流和大河的水文测量网是必不可少的。然而，迄今为止还没有进行过这样的水文研究。也许同样重要的是，全球水文学中缺乏小型源头河流，因为据估计，这些河流占总河流长度的70%以上。我们的目标是填补这一空白，使用MERIT水文数字高程模型在3弧秒（在赤道90米），以获得一个全球无缝，标准化的水文网络，“水文90米”，与相应的流地形和拓扑信息。该网络的一个核心特征是最小的上游贡献面积，即0.05平方公里（或5公顷）的流量积累，以启动一个河流通道，这使我们能够提取源头河流通道详细。通过采用一套GRASS GIS水文模块，我们计算了范围内的上游流量累积和流向，共划定了160万个流域，并提取了全球7.26亿个独特的河流段及其相应的子流域。此外，我们还计算了河流地形变量，包括河流坡度、坡度、长度和曲率属性，以及河流拓扑变量，以实现网络路由和各种河流顺序分类。我们验证的空间精度和流量积累的水文90米对NHDPlus HR，一个独立的，国家的高分辨率水文网络数据集的美国。验证结果表明，新开发的水文90 m数据集具有最高的空间精度，与其他三个全球水文数据集相比，包含更多的河源河流通道。这种包容性的方法提供了一个重要的，长期overduebaseline评估实际径流在源头，并开辟了新的研究途径，高分辨率的研究，世界各地的地表水。因此，水文学90米提供了巨大的潜力，以促进以全球综合和标准化的方式评估淡水的数量和质量、淹没风险、生物多样性和保护以及资源管理目标。我们提供了所有计算层的可视化和下载在20° × 20°瓷砖在https://public.igb-berlin.de/index.php/s/od7neyLcYgi5qRp。虽然整个数据集可以直接用于标准GIS应用程序，但我们建议将其与开源QGIS和GRASS GIS软件中的水文模块无缝集成，以进一步定制数据并从中获得最佳效用。
Abstract. The geographic distribution of streams and rivers drives a multitude of patterns and processes in hy-drology, geomorphology, geography and ecology. Therefore, a hydrographic network that accurately delineatesboth small streams and large rivers with equal precision, along with their topographic and topological proper-ties, would be indispensable in the earth sciences. However, no such hydrographic study has been publishedto date. Perhaps equally critical is the absence of small headwater streams in global hydrographies, as theseare estimated to contribute to more than 70 % of overall stream length. We aimed to fill this gap by using theMERIT Hydro Digital Elevation Model at 3 arc-sec (∼90 m at the equator) to derive a globally seamless, stan-dardised hydrographic network, the "Hydrography90m", with corresponding stream topographic and topologicalinformation. A central feature of the network is the minimal upstream contributing area, i.e. flow accumulation,of 0.05 km2 (or 5 ha) to initiate a stream channel, which allowed us to extract headwater stream channels ingreat detail. By employing a suite of GRASS GIS hydrological modules, we calculated the range-wide upstreamflow accumulation and flow direction to delineate a total of 1.6 million drainage basins, and extracted globallya total of 726 million unique stream segments with their corresponding sub-catchments. In addition, we com-puted stream topographic variables comprising stream slope, gradient, length, and curvature attributes, as wellas stream topological variables to allow for network routing and various stream order classifications. We vali-dated the spatial accuracy and flow accumulation of Hydrography90m against NHDPlus HR, an independent,national high-resolution hydrographic network dataset of the United States. Our validation shows that the newlydeveloped Hydrography90m has the highest spatial precision, and contains more headwater stream channelscompared to three other global hydrographic datasets. This inclusive approach provides a vital, and long-overduebaseline for assessing actual streamflow in headwaters, and opens new research avenues for high-resolution stud-ies of surface water worldwide. Hydrography90m thus offers significant potential to facilitate the assessment offreshwater quantity and quality, inundation risk, biodiversity and conservation, as well as resource managementobjectives in a globally comprehensive and standardised manner. We provide all the computed layers for visual-isation and download in 20° × 20° tiles at https://public.igb-berlin.de/index.php/s/od7neyLcYgi5qRp. While the entire dataset can be used directly in standard GIS applications, we recommend its seamless integration with hydrological modules in open-source QGIS and GRASS GIS software to further customise the data and derive optimal utility from it.
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DOI：
10.1002/wat2.1504
发表时间：
2021-02
期刊：
Wiley Interdisciplinary Reviews: Water
影响因子：
--
作者：
M. Shanafield;Sarah A. Bourke;M. Zimmer;K. Costigan
通讯作者：
M. Shanafield;Sarah A. Bourke;M. Zimmer;K. Costigan
影响因子：
3.2
作者：
J. Hosen;G. Allen;Giuseppe Amatuli;Sara E. Breitmeyer;M. Cohen;B. Crump;Yuehan Lu;J. Payet;Brett A. Poulin;A. Stubbins;B. Yoon;P. Raymond
通讯作者：
J. Hosen;G. Allen;Giuseppe Amatuli;Sara E. Breitmeyer;M. Cohen;B. Crump;Yuehan Lu;J. Payet;Brett A. Poulin;A. Stubbins;B. Yoon;P. Raymond
影响因子：
4
作者：
W. Wollheim;Susana Bernal;Douglas A. Burns;J. Czuba;Charles T. Driscoll;Amy T. Hansen;Robert T. Hensley;Jacob D. Hosen;Shreeram Inamdar;S. Kaushal;L. Koenig;YueHan Lu;A. Marzadri;Peter A. Raymond;Durelle T. Scott;R. J. Stewart;P. Vidon;Ellen Wohl
通讯作者：
W. Wollheim;Susana Bernal;Douglas A. Burns;J. Czuba;Charles T. Driscoll;Amy T. Hansen;Robert T. Hensley;Jacob D. Hosen;Shreeram Inamdar;S. Kaushal;L. Koenig;YueHan Lu;A. Marzadri;Peter A. Raymond;Durelle T. Scott;R. J. Stewart;P. Vidon;Ellen Wohl
影响因子：
13.5
作者：
O'Loughlin, F. E.;Paiva, R. C. D.;Bates, P. D.
通讯作者：
Bates, P. D.
影响因子：
11.6
作者：
Shumilova, Oleksandra;Zak, Dominik;Zarfl, Christiane
通讯作者：
Zarfl, Christiane