Global alluvial channel patterns

Quantitative analysis of alluvial channel patterns is essential in fluvial science, as their morphology both reflects and influences river behavior through interactions with water and sediment regimes, landscape processes, and human interventions. However, a comprehensive global study to identify predominant channel patterns and their underlying mechanisms remains lacking. Here, we map global alluvial channel patterns using high-resolution satellite observations. Our results reveal a hidden dominance of anabranching channels that surprisingly constitute half (51%) of total reach length globally, exceeding meandering (24%), straight (18%), and braided (7%) channels. In non-mountainous settings, anabranching channels dominate most continents except Oceania. They are not confined to typical alluvial lowland systems, also comprising 50% of alluvial tracts in mountains. While anabranching is typically associated with gentle slopes and expansive floodplains, these conditions are not exclusive determinants. The prevalence of anabranching channels transforms fundamental perspectives on global river systems, posing challenges for the fluvial geomorphology community.

Authors

Institutions

Publication Details

Journal
Nature Communications
Published
2026-01-21
DOI
https://doi.org/10.1038/s41467-026-68569-z
Primary Topic
Hydrology and Sediment Transport Processes
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Global alluvial channel patterns

Lian Feng Lian Feng, Qiuqi Luo, Edgardo Manuel Latrubesse, Xuehui Pi et al.
Nature Communications
Hydrology and Sediment Transport Processes
article

Global alluvial channel patterns

Lian Feng Lian Feng, Qiuqi Luo, Edgardo Manuel Latrubesse, Xuehui Pi, Wenhui Qiu, Edward Park, Hongwei Fang, Dongfeng Li, Yan Liu, Chunmiao Zheng, Pan Liu
article en

Abstract

Quantitative analysis of alluvial channel patterns is essential in fluvial science, as their morphology both reflects and influences river behavior through interactions with water and sediment regimes, landscape processes, and human interventions. However, a comprehensive global study to identify predominant channel patterns and their underlying mechanisms remains lacking. Here, we map global alluvial channel patterns using high-resolution satellite observations. Our results reveal a hidden dominance of anabranching channels that surprisingly constitute half (51%) of total reach length globally, exceeding meandering (24%), straight (18%), and braided (7%) channels. In non-mountainous settings, anabranching channels dominate most continents except Oceania. They are not confined to typical alluvial lowland systems, also comprising 50% of alluvial tracts in mountains. While anabranching is typically associated with gentle slopes and expansive floodplains, these conditions are not exclusive determinants. The prevalence of anabranching channels transforms fundamental perspectives on global river systems, posing challenges for the fluvial geomorphology community.

Nature CommunicationsVol. 17(1)
Tongji University (CN), University of Nottingham Ningbo China (CN), Nanyang Technological University (SG), Peking University (CN), Southern University of Science and Technology (CN), Wuhan University (CN), Henan Academy of Sciences (CN), Earth Observatory of Singapore (SG), State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing (CN), Aerospace Information Research Institute (CN), Universidade Federal de Goiás (BR)
Openalex Percentile: Top 84%
Hydrology and Sediment Transport Processes
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.