Cited by Mechanism of tidal driven vertical suspended sediment transport in Dumai Estuary

Study on the tidal variability related to flooding and hydroelectric operations in the Qiantang river estuary DOI

Huamin Zhou,

Haidong Pan, Min Gan

et al.

Estuarine Coastal and Shelf Science, Journal Year: 2024, Volume and Issue: 305, P. 108845 - 108845

Published: June 14, 2024

Language: Английский

Citations

An improved machine learning-based model to predict estuarine water levels DOI

Min Gan, Yongping Chen, Shunqi Pan

et al.

Ocean Modelling, Journal Year: 2024, Volume and Issue: 190, P. 102376 - 102376

Published: May 6, 2024

Language: Английский

Citations

Unravelling the spatiotemporal variation in the water levels of Poyang Lake with the variational mode decomposition model DOI

Min Gan, Xijun Lai, Yan Guo

et al.

Hydrological Processes, Journal Year: 2024, Volume and Issue: 38(7)

Published: July 1, 2024

Abstract Poyang Lake is a dynamic floodplain lake system that exhibits complex water level fluctuations and experiences significant regime changes over space time, which remains to be further explored. This study used the variational mode decomposition (VMD) model decompose Lake's levels from 1960 2022 at four key stations into six intrinsic functions (IMFs), namely IMF1–IMF6, representing variations on different time scales. The results present spatiotemporal heterogeneity. multi‐year variation (IMF1) accounts for 5.6%–12.4% of total displays northward decreasing trend, reflecting lake's river‐like characteristics. spectrum IFM1 also reveals 3.6‐year fluctuation mainly attributed tributary inflow, especially Ganjiang River. IMF1 differences between show abrupt decreases since 2000s, indicating impact concentrated sand mining activities northern central regions. annual (IMF2) most prominent, contributing 76.1%–88.4% variation, shows southward attenuation likely due weakening influence Yangtze River flow. intra‐annual scale (IMF3–IMF6) represents 6.0%–11.5% less spatial difference compared variations. VMD effectively separates signals frequency bands, providing insights interactions lake, tributaries, River, as well impacts human like mining, enhancing understanding dynamics. imply importance coping with decline Lake.

Language: Английский

Citations

Prediction of discharge in a tidal river using the LSTM-based sequence-to-sequence models DOI