Analysis of Daily Peaking and Run‐of‐River Operations with Flow Variability Metrics, Considering Subdaily to Seasonal Time Scales
Analysis of Daily Peaking and Run‐of‐River Operations with Flow Variability Metrics, Considering Subdaily to Seasonal Time Scales
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DOI：
10.1111/jawr.12228
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发表时间：
2014-12
期刊：
影响因子：
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通讯作者：
N. A. Haas;B. O’Connor;J. Hayse;M. Bevelhimer;T. Endreny
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作者：
N. A. Haas;B. O’Connor;J. Hayse;M. Bevelhimer;T. Endreny
环境流量是水电项目许可的重要考虑因素，因为运营流量的释放会对下游生态群落造成不利影响。流量变异性评估通常侧重于使用基于日平均流量值的指标来评估坝前和坝后条件。本研究使用次日流量和日流量数据来评估水电运行从日调峰到径流量变化对环境流量的响应。开发了一种分析工具来量化流量变异性指标，并应用于四个水电项目。使用每小时平均流量数据集，在99%的置信水平上，在操作之间观察到显着差异。每日上升及下跌的中位数分别平均下降34.5%及27.9%，而每小时上升及下跌的中位数则分别平均下降50.1%及50.6%。在每小时平均流量数据集中，操作流量制度的差异更为明显，而在每日平均流量数据集中，差异不太明显或不存在。这些结果对生态-流量关系的发展具有重要意义，该关系量化了流量对鱼类搁浅和迁移等过程的影响，以及栖息地的稳定性。结果表明，为了准确反映水电运行的性质，特别是对日调峰设施，流量变异性统计应采用次日数据集进行量化。
Environmental flows are an important consideration in licensing hydropower projects as operational flow releases can result in adverse conditions for downstream ecological communities. Flow variability assessments have typically focused on pre‐ and post‐dam conditions using metrics based on daily averaged flow values. This study used subdaily and daily flow data to assess environmental flow response to changes in hydropower operations from daily peaking to run‐of‐river. An analysis tool was developed to quantify flow variability metrics and was applied to four hydropower projects. Significant differences were observed between operations at the 99% confidence level in the median flow values using hourly averaged flow datasets. Median daily rise and fall rates decreased on average 34.5 and 27.9%, respectively, whereas median hourly rise and fall rates decreased on average 50.1 and 50.6%, respectively. Differences in operational flow regimes were more pronounced in the hourly averaged flow datasets and less pronounced or nonexistent in the daily averaged flow datasets. These outcomes have implications for the development of ecology‐flow relationships that quantify effects of flow on processes such as fish stranding and displacement, along with habitat stability. Results indicate that flow variability statistics should be quantified using subdaily datasets to accurately represent the nature of hydropower operations, especially for daily peaking facilities.