| 引用本文: | 程俊翔,徐力刚,姜加虎.生态最相关水文指标的优选及其在洞庭湖环境流量估算中的应用.湖泊科学,2018,30(5):1235-1245. DOI:10.18307/2018.0507 |
| CHENG Junxiang,XU Ligang,JIANG Jiahu.Optimal selection of the most ecologically relevant hydrologic indicators and its application for environmental flow calculation in Lake Dongting. J. Lake Sci.2018,30(5):1235-1245. DOI:10.18307/2018.0507 |
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| 生态最相关水文指标的优选及其在洞庭湖环境流量估算中的应用 |
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程俊翔1,2, 徐力刚1,2,3, 姜加虎1,2
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1.中国科学院南京地理与湖泊研究所, 中国科学院流域地理学重点实验室, 南京 210008;2.中国科学院大学, 北京 100049;3.江西省山江湖开发治理委员会办公室, 南昌 330046
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| 摘要: |
| 水文改变指标（IHA）能够较为全面地描述水文状况，在评估水文情势改变及其生态系统影响方面具有广泛的应用.尽管该指标体系较为完善，但是数量众多的水文变量仍然存在信息冗余问题.根据洞庭湖城陵矶水文站1955-2014年的径流量数据，采用主成分分析（PCA）筛选了生态最相关水文指标（ERHIs），结合ERHIs改进了用于估算环境流量的变化范围法（RVA），并将其应用在洞庭湖出口的环境流量估算中.基于PCA选取了年最大90日流量、年最小3日流量、年最小流量出现时间、3月流量、6月流量、流量逆转次数和低流量年内平均历时7个变量作为洞庭湖出口的ERHIs.纵向和横向的对比分析都表明选取的ERHIs是合理的.ERHIs不仅有效缓解了IHA的冗余性问题，还有利于抓住最关键的生态水文变量.根据ERHIs改进的RVA方法在设定洞庭湖出口环境流量时，极大地简化原来的众多管理目标，对生态水文研究、水资源管理和生态保护都具有重要的参考价值和借鉴意义. |
| 关键词: 生态水文 水文改变指标 冗余性 主成分分析 环境流量 洞庭湖 |
| DOI：10.18307/2018.0507 |
| 分类号: |
| 基金项目:国家重点研发计划项目（2018YFC0407600）、国家自然科学基金项目（41771235，41661018）、江西省重点研发计划项目（20171BBH80015）、江苏高校水处理技术与材料协同创新中心项目和江西省科学院重点科研（对外合作）项目（2018-YZD2-03）联合资助. |
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| Optimal selection of the most ecologically relevant hydrologic indicators and its application for environmental flow calculation in Lake Dongting |
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CHENG Junxiang1,2, XU Ligang1,2,3, JIANG Jiahu1,2
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1.Key Laboratory of Watershed Geographic Sciences, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, P. R. China;2.University of Chinese Academy of Sciences, Beijing 100049, P. R. China;3.Office of Mountain-River-Lake Development Committee of Jiangxi Province, Nanchang 330046, P. R. China
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| Abstract: |
| The method of indicators of hydrologic alteration (IHA) provides a relatively comprehensive way to describe the full range of hydrological regimes and is used globally to assess hydrological alteration and its ecosystem influence. This method is relatively sound, while it still has potential redundancy problems caused by a large number of variables in it. Therefore, the principal component analysis (PCA) was used to select the most ecologically relevant hydrologic indicators (ERHIs), based on the flow data at Chenglingji, a standard observation station of Lake Dongting, from 1955 to 2014. The method of range of variability approach (RVA) was improved by the selected ERHIs and was used to estimate environmental flow in the outlet of Lake Dongting. Based on the results of PCA, seven ERHIs were selected:annual maximum 90-day flow, annual minimum 3-day flow, Julian date of each annual 1-day minimum, March flow, June flow, number of hydrologic reversals and median duration of low pulses. It was proved that the seven selected ERHIs were reasonable with the comparison to previous studies and the redundancy analysis. ERHIs not only reduce the redundancy of IHA but also help to grasp the key component of eco-hydrological variables. Moreover, the improved RVA method greatly simplified the original management targets in estimating environmental flow in the outlet of Lake Dongting. This study is of great value and significance for eco-hydrological research, water resources management and ecological protection. |
| Key words: Eco-hydrology indicators of hydrologic alteration redundancy principal component analysis environmental flow Lake Dongting |
