Quantitative attribution of the drivers of Poyang Lake water level changes based on similarity analysis and the DA-GRU model

Study region The Poyang Lake basin, China. Study focus Poyang Lake (PYL) has experienced a pronounced decline in autumn water levels, yet the relative contributions of different drivers remain controversial. This study integrates similarity analysis with a Dragonfly Algorithm (DA) optimized Gated Recurrent Unit (GRU) model, forming a control variable framework that explicitly separates timing and magnitude effects of different drivers, enabling quantitative attribution of the effects of the Three Gorges Reservoir (TGR) regulation and channel morphological changes on PYL water level decline. New hydrological insights for the region The similarity analysis indicates a structural shift in the hydrological linkage between the Yangtze River and PYL after 2003, marked by a decoupling of mainstream discharge and lake water levels. Scenario simulations indicate that TGR regulation primarily alters the seasonal discharge regime, leading to earlier post-flood water level recession. In contrast, channel morphological changes, including riverbed incision and cross-sectional enlargement, emerge as the dominant and more persistent control on water level decline. Quantitative attribution shows that about 77% of PYL’s water level decline since 2003 is attributed to channel morphological changes, while about 23% is associated with TGR regulation. Overall, TGR regulation primarily influences the timing of water level decline, whereas channel morphological changes play a dominant role in determining its magnitude.

Authors

Institutions

Publication Details

Journal
Journal of Hydrology Regional Studies
Published
2026-10-13
DOI
https://doi.org/10.1016/j.ejrh.2026.104075
Primary Topic
Hydrology and Watershed Management Studies
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Quantitative attribution of the drivers of Poyang Lake water level changes based on similarity analysis and the DA-GRU model

Xingbo Wang, Yiman Tian, Lvze Duan, Hangyu Guo et al.
Journal of Hydrology Regional Studies
Hydrology and Watershed Management Studies
article

Quantitative attribution of the drivers of Poyang Lake water level changes based on similarity analysis and the DA-GRU model

Xingbo Wang, Yiman Tian, Lvze Duan, Hangyu Guo, Shuanghu Zhang
article en

Abstract

Study region The Poyang Lake basin, China. Study focus Poyang Lake (PYL) has experienced a pronounced decline in autumn water levels, yet the relative contributions of different drivers remain controversial. This study integrates similarity analysis with a Dragonfly Algorithm (DA) optimized Gated Recurrent Unit (GRU) model, forming a control variable framework that explicitly separates timing and magnitude effects of different drivers, enabling quantitative attribution of the effects of the Three Gorges Reservoir (TGR) regulation and channel morphological changes on PYL water level decline. New hydrological insights for the region The similarity analysis indicates a structural shift in the hydrological linkage between the Yangtze River and PYL after 2003, marked by a decoupling of mainstream discharge and lake water levels. Scenario simulations indicate that TGR regulation primarily alters the seasonal discharge regime, leading to earlier post-flood water level recession. In contrast, channel morphological changes, including riverbed incision and cross-sectional enlargement, emerge as the dominant and more persistent control on water level decline. Quantitative attribution shows that about 77% of PYL’s water level decline since 2003 is attributed to channel morphological changes, while about 23% is associated with TGR regulation. Overall, TGR regulation primarily influences the timing of water level decline, whereas channel morphological changes play a dominant role in determining its magnitude.

Journal of Hydrology Regional StudiesVol. 68
Hohai University (CN), China Institute of Water Resources and Hydropower Research (CN)
China Three Gorges Corporation
Openalex Percentile: Top 25%
Hydrology and Watershed Management Studies
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.