4.7 Article

Mapping Flow-Obstructing Structures on Global Rivers

期刊

WATER RESOURCES RESEARCH
卷 58, 期 1, 页码 -

出版社

AMER GEOPHYSICAL UNION
DOI: 10.1029/2021WR030386

关键词

infrastructure; obstructions; participatory research; rivers; connectivity; fragmentation

资金

  1. SWOT Project Office at the NASA/Caltech Jet Propulsion Lab
  2. Welsh European Funding Office
  3. European Regional Development Fund [80761-SU-140]

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People have built various obstructions in rivers for different purposes, but due to the long and complex history of construction and removal, there is a lack of consistent global record. By using a consistent method and high-resolution images, a Global River Obstruction Database was established, recording different types of obstructions, with high classification consistency for obstructions fully intersecting rivers but lower consistency for partial obstructions.
To help store water, facilitate navigation, generate energy, mitigate floods, and support industrial and agricultural production, people have built and continue to build obstructions to natural flow in rivers. However, due to the long and complex history of constructing and removing such obstructions, we lack a globally consistent record of their locations and types. Here, we used a consistent method to visually locate and classify obstructions on 2.1 million km of large rivers (width >= 30 m) globally. We based our mapping on Google Earth Engine's high resolution images, which for many places have meter-scale resolution. The resulting Global River Obstruction Database (GROD) consists of 30,549 unique obstructions, covering six different obstruction types: dam, lock, low head dam, channel dam, and two types of partial dams. By classifying a subset of the obstructions multiple times, we are able to show high classification consistency (87% mean balanced accuracy) for the three types of obstructions that fully intersect rivers: dams, low head dams, and locks. The classification of the three types of partial obstructions are somewhat less consistent (61% mean balanced accuracy). Overall, by comparing GROD to similar datasets, we estimate GROD likely captured >90% of the obstructions on large rivers. We anticipate that GROD will be of wide interest to the hydrological modeling, aquatic ecology, geomorphology, and water resource management communities.

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