Integrated optimization and coordination of cascaded reservoir operations: Balancing flood control, sediment transport and ecosystem service

River, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 6, 2025

Abstract Exploring optimal operational schemes for synergistic development is crucial sustainable management in river basins. This study introduces a multi‐objective optimization framework aimed at analyzing the interplay among flood control, ecological integrity, and desilting objectives under varying water‐sediment conditions. The encompasses reservoir operation, scheme decision, trade‐off analysis competing objectives. To address model, an elite mutation‐based particle swarm (MOPSO) algorithm that integrates genetic algorithms (GA) developed. coupling coordination degree employed decision‐making, allowing adjustment of weight ratios to investigate trade‐offs between research focuses on Sanmenxia Xiaolangdi cascade reservoirs Yellow River, utilizing three representative hydrological years: 1967, 1969, 2002. findings reveal that: (1) proposed model effectively generates Pareto fronts operations, facilitating recommendation based degrees; (2) as conditions shift from flooding drought, competition intensifies control While compete during dry years, they demonstrate synergies normal years ( r = 0.22); conversely, are consistently competitive across all typical with strongest observed year −0.95); (3) advantages conferred increase drought. However, promotion objective requires more complex trade‐offs. provides methodological approach sediment management, considerations clusters. Moreover, methodologies presented herein can be extended other water resource systems decision‐making.

Language: Английский

The Impact of the Three Gorges Reservoir Operations on Hydraulic Characteristics in the Backwater Region: A Comprehensive 2D Modeling Study

Water, Journal Year: 2024, Volume and Issue: 16(14), P. 2045 - 2045

Published: July 19, 2024

The Three Gorges Reservoir (TGR), a landmark of human engineering, has significantly altered the hydrodynamics and ecology its surrounding environment. Our research explores hydrodynamic ecological changes in TGR, focusing on their implications for reservoir-induced water quality resource issues. We designed 2D model implemented 15 operational scenarios with an advanced dynamic storage capacity method TGR during flood season, drawdown impoundment periods. simulations well reproduced predicted levels, discharge rates, thermal conditions providing critical insights. improved precision level simulations. This approach achieved modeling errors below 0.2 m when compared to real measurements from seven stations. performed detailed analysis sensitive, sub-sensitive, insensitive areas three reservoir operation period showed most extensive impact range (468 km river channel), while had least (76 channel). Furthermore, we quantified delay temperature waves these periods, observing maximum approximately 120 minimum less than 10 km, which underscores variability responses under different scenarios. findings reveal complex sensitivities varied modes, aiding development eutrophication resources control strategies. application provides insights management strategies large dam systems globally, informing future policy-making, ensuring sustainable effective systems.

Language: Английский

Identification of the Runoff Evolutions and Driving Forces during the Dry Season in the Xijiang River Basin

Water, Journal Year: 2024, Volume and Issue: 16(16), P. 2317 - 2317

Published: Aug. 17, 2024

During the dry season, river flow gradually diminishes, and surface water dries up. Therefore, investigation of runoff during season is great practical significance for rational allocation resource management. Based on hydrological station data from Xijiang River Basin (XRB) 1961 to 2020, this study examines trend periodic characteristics dry-season runoff, identifies fluctuation variability in investigates main circulation factor combinations influencing dynamic changes runoff. The results indicate following: (1) variations are basically consistent across sub-basins XRB period, with minimum (21.96 × 108 m3) maximum (54.67 average monthly occurring February October, respectively; (2) interannual-scale exhibits periodicity 3.53 years 7.5 years; (3) using Bayesian estimator abrupt seasonal change algorithm (BEAST), a point probability 20.5% occurs 1983, confidence interval 1980 1986; (4) based cross wavelet approach, solar sunspots identified as primary contributing XRB, exhibiting significant 8–14 resonance cycle negative correlation high-energy phase 1972 2006. These findings offer new perspective understanding evolution variations, which crucial accurate prediction, early warning, resources season.

Language: Английский