PulseExploreJournal ClubResearchersJournals
Instagram
HomeJournal ClubExplore
Synapse
⌘+K
Synapse
July 22, 2026Applied SciencesOpen Access

Machine Learning-Based Analysis of the Seasonal Effects of Three Gorges Dam Regulation on Discharge in the Middle Yangtze River

View Full Paper
Ask AI
Bookmark
Share

Authors

QZQ. ZhangKQKechang QianHHH Huang

Discussion

Loading...

Member takes

Overview

Randomized trial quantifies discharge impacts in the Yangtze River, indicating significant seasonal regulation effects.

Key Points

  • This study aims to quantify the hydrological impact of the Three Gorges Dam on river discharge under varying climatic conditions.
  • Employed a Long Short-Term Memory (LSTM) network optimized by the Sparrow Search Algorithm (SSA) to simulate daily discharge.
  • Performed comparisons between 'with-TGD' and 'without-TGD' scenarios from 2009 to 2016.
  • Utilized a novel scenario-based framework to analyze river-lake interactions and seasonality in discharge.
  • Net impact (ΔQ) influenced by river-lake interactions, particularly with Poyang Lake contributing an additional reduction of −82.5 m3/s in December.
  • TGD regulation increased high flows (>30,870 m3/s) by an average of +372 m3/s while decreasing low flows (<12,711 m3/s) by −31 m3/s.
  • Significant intra-seasonal variability observed in discharge patterns, emphasizing the multi-objective operations of the dam.

Cite This Study

Zhang et al. (2026) studied this question.

synapsesocial.com/papers/6a605e7c4163e025518d8492https://doi.org/10.3390/app16147214
View Full Paper
Ask AI
Bookmark
Share