A coupled metabolic-hydraulic model and calibration scheme for estimating whole-river metabolism during dynamic flow conditions
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Conventional methods for estimating whole‐stream metabolic rates from measured dissolved oxygen dynamics do not account for the variation in solute transport times created by dynamic flow conditions. Changes in flow at hourly time scales are common downstream of hydroelectric dams (i.e., hydropeaking), and hydrologic limitations of conventional metabolic models have resulted in a poor understanding of the controls on biological production in these highly managed river ecosystems. To overcome these limitations, we coupled a two‐station metabolic model of dissolved oxygen dynamics with a hydrologic river routing model. We designed calibration and parameter estimation tools to infer values for hydrologic and metabolic parameters based on time series of water quality data, achieving the ultimate goal of estimating whole‐river gross primary production and ecosystem respiration during dynamic flow conditions. Our case study data for model design and calibration were collected in the tailwater of Glen Canyon Dam (Arizona, U.S.A.), a large hydropower facility where the mean discharge was 325 m3 s−1and the average daily coefficient of variation of flow was 0.17 (i.e., the hydropeaking index averaged from 2006 to 2016). We demonstrate the coupled model's conceptual consistency with conventional models during steady flow conditions, and illustrate the potential bias in metabolism estimates with conventional models during unsteady flow conditions. This effort contributes an approach to solute transport modeling and parameter estimation that allows study of whole‐ecosystem metabolic regimes across a more diverse range of hydrologic conditions commonly encountered in streams and rivers.
Payn, R. A., Hall, R. O., Kennedy, T. A., Poole, G. C., & Marshall, L. A. (2017). A coupled metabolic-hydraulic model and calibration scheme for estimating whole-river metabolism during dynamic flow conditions. Limnology and Oceanography: Methods, 15(10), 847–866. doi:10.1002/lom3.10204
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