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Analysis of Daily Peaking and Run-of-River Operations with Flow Variability Metrics, Considering Subdaily to Seasonal Time Scales

Journal Article · · Journal of the American Water Resources Association
DOI:https://doi.org/10.1111/jawr.12228· OSTI ID:1361060
 [1];  [1];  [1];  [2];  [3]
  1. Environmental Science Division, Argonne National Laboratory, Building 240 9700 South Cass Avenue Argonne Illinois 60439
  2. Environmental Science Division, Oak Ridge National Laboratory, Oak Ridge Tennessee 37831
  3. Department of Environmental Resources Engineering, State University of New York-College of Environmental Science and Forestry, Syracuse New York 13210

  Environmental flows are an important consideration in licensing hydropower projects  because operational flow releases can result in adverse conditions to 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 subdaily to seasonal flow variability metrics and was applied    to four hydropower projects that underwent operational changes based on regulatory requirements.  Results indicate that the distribution of flows is significantly different between daily-peaking and run-of- river operations and that daily-peaking operations are flashier than run-of-river operations; these  differences are seen using hourly-averaged flow datasets and are less pronounced or not noticeable  using daily-averaged flow datasets.  Of all variability metrics analyzed, hydrograph rise and fall rates  were the most sensitive to using daily versus subdaily flow data. This outcome has implications for the    development of flow-ecology relationships that quantify effects of rate of change on processes such as  fish stranding and displacement, along with habitat stability. The quantification of flow variability    statistics should be done using subdaily datasets and metric to accurately represent the nature of  hydropower operations , especially for facilities that utilize daily-peaking operations. 

Research Organization:
Argonne National Lab. (ANL), Argonne, IL (United States)
Sponsoring Organization:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Wind Energy Technologies Office (EE-4WE)
DOE Contract Number:
AC02-06CH11357
OSTI ID:
1361060
Journal Information:
Journal of the American Water Resources Association, Journal Name: Journal of the American Water Resources Association Journal Issue: 6 Vol. 50; ISSN 1093-474X
Country of Publication:
United States
Language:
English

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