eZ flow metrics: Using z‐scores to estimate deviations from natural flow in the Colorado River below Glen Canyon Dam

River flow patterns are primary drivers of lotic ecosystems, and hundreds of metrics have been developed to quantify flow attributes. Although existing metrics have been a powerful tool in designing environmental flows, they are often developed with specific resources in mind and are rarely directly...

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Veröffentlicht in:River research and applications 2024-08
Hauptverfasser: Palmquist, Emily C., Deemer, Bridget R., Metcalfe, Anya N., Kennedy, Theodore A., Bair, Lucas S., Fairley, Helen C., Grams, Paul E., Sankey, Joel B., Yackulic, Charles B.
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Sprache:eng
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Zusammenfassung:River flow patterns are primary drivers of lotic ecosystems, and hundreds of metrics have been developed to quantify flow attributes. Although existing metrics have been a powerful tool in designing environmental flows, they are often developed with specific resources in mind and are rarely directly comparable with each other (i.e., units are often different). Here, we focus on natural flows as the resource of interest and develop z‐score metrics that measure the naturalness of regulated flows, incorporating natural means and interannual variation. These “eZ metrics” summarize whole year, subdaily, and functional flow patterns as standard deviations from natural such that their values are directly comparable. We illustrate their utility with a case study from the Colorado River downstream of Glen Canyon Dam in Arizona, USA. We calculated metrics for 1964–2022, spanning >5 decades of changing water policy, hydropower generation, and flow experimentation. We evaluate four options for estimating natural baseline flows. Across metrics, we found that subdaily stage variation deviated the most from baseline. Flows to satisfy regional water policy and power demands altered metrics more than designer flows (which target specific resource outcomes), and years with low water releases were closest to natural. Most of the designer flows have not made flow patterns more natural, due to incorrect seasonal timing, small magnitude, or short duration. By explicitly considering interannual variability and quantifying how regulated flows differ from natural using standard deviations, these metrics can inform management when the goal is to restore a natural flow regime.
ISSN:1535-1459
1535-1467
DOI:10.1002/rra.4360