| 引用本文: | 李敏讷,王妍,王新源,李晓兵,林晨宇,陈小龙,陈求稳,石小涛.鱼类行为生态水力学模型研究现状与发展趋势.湖泊科学,2024,36(5):1323-1335. DOI:10.18307/2024.0502 |
| Li Minne,Wang Yan,Wang Xinyuan,Li Xiaobing,Lin Chenyu,Chen Xiaolong,Chen Qiuwen,Shi Xiaotao.Research status and trends of models integrating fish behavior and eco-hydraulic dynamics. J. Lake Sci.2024,36(5):1323-1335. DOI:10.18307/2024.0502 |
|
| |
|
|
| 本文已被：浏览 2090次 下载 1884次 |
码上扫一扫！ |
|
|
| 鱼类行为生态水力学模型研究现状与发展趋势 |
|
李敏讷1,2, 王妍1,2, 王新源1,2, 李晓兵3, 林晨宇1,2, 陈小龙1,2, 陈求稳4, 石小涛1,2
|
|
1.三峡大学, 三峡库区生态环境教育部工程研究中心, 宜昌 443002;2.三峡大学, 湖北省鱼类过坝技术国际科技合作基地, 宜昌 443002;3.中水北方勘测设计研究有限责任公司, 天津 300222;4.南京水利科学研究院生态环境研究所, 南京 210029
|
|
| 摘要: |
| 水利工程运行与鱼类资源保护如何协同发展,是我国水电开发与水生态环境保护需要重点开展的研究,其中基于鱼类行为学、生态水力学及计算机科学等多学科交叉融合的鱼类行为生态水力学模型为水电开发背景下鱼类行为响应及其生境质量演变提供了研究技术及评估新方法。鱼类运动模型的基本原理为以水动力环境为基础,通过融合鱼类行为规律实现鱼类运动过程的模拟。本研究系统调研和梳理总结了近20年来国内外鱼类行为生态水力学模型的相关研究,重点聚焦模型如何准确构建及合理运用。首先介绍了模型的基本结构及主要组成要素,重点阐述了不同生境尺度中鱼类行为规则设置时考虑的因素,包括过鱼设施微生境、坝区水环境及河流生态系统;然后详细剖析了鱼类运动模型科学构建及运用过程中的难点,包括鱼类行为规则的复杂多样性、行为模型与水动力模型的融合以及模型的有效和合理运用;最后从人工智能算法、多尺度与多维度信息融合以及模型对生境要素的预测运用3个方面对未来运动模型研究进行展望,为开展符合我国坝情、水情及鱼情的鱼类行为生态水力学模型研究工作提供一定的科学依据。 |
| 关键词: 鱼类行为 生态水力学 运动模型 不同生境 模型构建 模型运用 |
| DOI：10.18307/2024.0502 |
| 分类号: |
| 基金项目:国家自然科学基金优秀青年科学基金项目(51922065)、国家自然科学基金项目(52279069)、湖北省自然科学基金项目 (2023AFA005)和三峡库区生态环境教育部基金项目(KF2023-12)联合资助。 |
|
| Research status and trends of models integrating fish behavior and eco-hydraulic dynamics |
|
Li Minne1,2, Wang Yan1,2, Wang Xinyuan1,2, Li Xiaobing3, Lin Chenyu1,2, Chen Xiaolong1,2, Chen Qiuwen4, Shi Xiaotao1,2
|
|
1.Engineering Research Center of Eco-environment in Three Gorges Reservoir Region, Ministry of Education, China Three Gorges University, Yichang 443002, P. R. China;2.Hubei International Science and Technology Cooperation Base of Fish Passage, China Three Gorges University, Yichang 443002, P. R. China;3.China Water Resources Beifang Investigation, Design and Research Co., Ltd., Tianjin 300222, P. R. China;4.Eco-environmental Research Department, Nanjing Hydraulic Research Institute, Nanjing 210029, P. R. China
|
| Abstract: |
| In the context of hydropower development and aquatic ecological environmental protection, the synergistic development of hydropower operations and fishery resource conservation is a crucial research area. New models integrating fish behavior and eco-hydraulic dynamics provide novel techniques and assessment methods for understanding fish behavior responses and the dynamic changes in habitat quality associated with hydropower development. The fundamental principles of fish movement models are rooted in the hydraulic environment, simulating fish movement processes through the integration of fish behavior rules. This comprehensive study systematically reviews and summarizes relevant research on model integrating fish behavior and eco-hydraulic dynamics conducted over the past two decades, with a specific focus on the accurate construction and rational utilization of these models. This paper commenced by introducing the basic structure and key components of the models, emphasizing factors considered when establishing fish behavior rules at different habitat scales, including microhabitats around fish passage facilities, dam area water environments, and river ecosystems. Subsequently, it analyzed the challenges in the scientific construction and application processes of fish movement models, addressing issues such as the complex diversity of fish behavior rules, the integration of behavior models with hydraulic models, and the effective and rational application of these models. Lastly, this research provided a perspective on future studies of movement models, highlighting artificial intelligence algorithms, the fusion of multiscale and multidimensional information, and the application of models for predicting habitat elements. These insights serve as a scientific basis for conducting research on model integrating fish behavior and eco-hydraulic dynamics that align with dam conditions, water conditions, and fish conditions in China. |
| Key words: Fish behavior eco-hydraulics movement models different habitats model construction model application |
|
|
|
|
