TY - JOUR
T1 - Mapping Flow-Obstructing Structures on Global Rivers
AU - Yang, Xiao
AU - Pavelsky, Tamlin M.
AU - Ross, Matthew R.V.
AU - Januchowski-Hartley, Stephanie R.
AU - Dolan, Wayana
AU - Altenau, Elizabeth H.
AU - Belanger, Michael
AU - Byron, Danesha
AU - Durand, Michael
AU - Van Dusen, Ian
AU - Galit, Hailey
AU - Jorissen, Michiel
AU - Langhorst, Theodore
AU - Lawton, Eric
AU - Lynch, Riley
AU - Mcquillan, Katie Ann
AU - Pawar, Sayali
AU - Whittemore, Aaron
N1 - Funding Information:
SWOT Project Office at the NASA/Caltech Jet Propulsion Lab
Welsh European Funding Office and European Regional Development Fund. Grant Number: 80761-SU-140
Publisher Copyright:
© 2022. American Geophysical Union. All Rights Reserved.
PY - 2022/1/5
Y1 - 2022/1/5
N2 - 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.
AB - 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.
KW - connectivity
KW - fragmentation
KW - infrastructure
KW - obstructions
KW - participatory research
KW - rivers
UR - http://www.scopus.com/inward/record.url?scp=85123724311&partnerID=8YFLogxK
U2 - 10.1029/2021WR030386
DO - 10.1029/2021WR030386
M3 - Article
AN - SCOPUS:85123724311
SN - 0043-1397
VL - 58
SP - 1
EP - 10
JO - Water Resources Research
JF - Water Resources Research
IS - 1
M1 - e2021WR030386
ER -