Abstract：
Environmental flow plays an important role in maintaining the health of river ecosystems and aquatic habitats. Although ecological regulation of environmental flow has attracted the attention of scientists, managing the world\'s reservoir-regulated rivers to better meet the needs of human being and ecosystems is a complex social challenge. To address the above issues, we constructed a model for optimizing reservoir operation based on a balance in achieving multi objectives among environmental flow, water supply and power generation (EWP). The model was solved using an intelligent multi-objective optimization algorithm (ARNSGA-III). The developed model was demonstrated in a large reservoir, Laolongkou Reservoir in the Tumen River. The results showed that the reservoir altered environmental flows mainly in terms of flow magnitude, peak, times, duration and frequency, which result in a sharp decrease in spawning fish, and degradation and replacement of vegetation along the channels. In addition, the mutual feedback relationship between the objectives of environmental flows, water supply and power generation is not static, but varies over time and space. The constructed model based on Indicators of Hydrologic Alteration (IHAs) can effectively guarantee the environmental flow at daily scale. In detail, the river ecological benefit increased by 64% in wet year, 68% in normal year, 68% in dry year after optimizing regulation of reservoir, respectively. This study will provide a scientific reference for the optimizing of the management in other rivers affected by dams.
摘要：
环境流动对维持河流生态系统和水生生境的健康起着重要作用。尽管环境流动的生态调控引起了科学家们的关注,管理世界上的水库管理河流，以更好地满足人类和生态系统的需求是一个复杂的社会挑战。为了解决上述问题，我们构建了一个基于环境流之间实现多目标平衡的水库优化调度模型，供水和发电（EWP）。使用智能多目标优化算法(ARNSGA-III)对模型进行求解。开发的模型在一个大型油藏中得到了证明，图们江老龙口水库。结果表明，水库主要从流量大小上改变了环境流量，峰值,times,持续时间和频率，这导致产卵鱼的急剧减少，以及沿河道植被的退化和更换。此外,环境流动目标之间的相互反馈关系，供水和发电不是静态的，但随着时间和空间的变化。所构建的基于水文蚀变指标(IHA)的模型可以有效保证日尺度的环境流量。详细来说,河流生态效益在潮湿年份增加了64%，正常年份为68%，水库优化调度后，干旱年68%，分别。该研究将为其他受大坝影响的河流的优化管理提供科学参考。
