Identifiability of transient storage model parameters along a mountain stream

Authors

  • C. Kelleher,

    Corresponding author
    1. Department of Civil and Environmental Engineering, Pennsylvania State University, University Park, Pennsylvania, USA
    2. Division of Earth and Ocean Sciences, Nicholas School of the Environment, Duke University, Durham, North Carolina, USA
    • Corresponding author: C. Kelleher, Division of Earth and Ocean Sciences, Nicholas School of the Environment, Box 90328, Duke University, Durham, NC 27708, USA. (christakelleher@gmail.com)

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  • T. Wagener,

    1. Department of Civil and Environmental Engineering, Pennsylvania State University, University Park, Pennsylvania, USA
    2. Department of Civil Engineering, University of Bristol, Bristol, UK
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  • B. McGlynn,

    1. Division of Earth and Ocean Sciences, Nicholas School of the Environment, Duke University, Durham, North Carolina, USA
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  • A. S. Ward,

    1. Department of Earth and Environmental Science, University of Iowa, Iowa City, Iowa, USA
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  • M. N. Gooseff,

    1. Department of Civil and Environmental Engineering, Colorado State University, Fort Collins, Colorado, USA
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  • R. A. Payn

    1. Department of Land Resources and Environmental Sciences, Montana State University, Bozeman, Montana, USA
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Abstract

[1] Transient storage models are widely used in combination with tracer experiments to characterize stream reaches via calibrated parameter estimates. These parameters quantify the main transport and storage processes. However, it is implicitly assumed that calibrated parameters are uniquely identifiable and hence provide a unique characterization of the stream. We investigate parameter identifiability along with the stream conditions that control identifiability for 10 breakthrough curves (BTC) for 100 m pulse injections along Stringer Creek, Montana, USA. Identifiability is assessed through global, variance-based sensitivity analysis of the one-dimensional transport with inflow and storage model (OTIS). Results indicate that the main channel area parameter A and the dispersion coefficient D were the most sensitive parameters and, therefore, likely to be identifiable across all timescales and reaches. Identifiability of transient storage zone size As fell into two categories along Stringer Creek. As was identifiable for lower elevation regions, corresponding to a constrained valley, higher stream slopes, and in-channel roughness, but not for upper stream regions, corresponding to a wider valley floor, flatter stream slopes, and low roughness. The storage zone exchange parameter α was nonidentifiable across all study reaches. Our results suggest that only some of the processes represented in the model will be relevant and, therefore, identifiable for pulse injection data. As such, calibrated parameter estimates should be accompanied by an assessment of parameter sensitivity or uncertainty. We also show that parameter identifiability varies with stream setting along Stringer Creek, suggesting that physical characteristics directly influence the identification of dominant stream processes.

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