TY - JOUR
T1 - Improving Predictions of Fine Particle Immobilization in Streams
AU - Drummond, Jennifer
AU - Schmadel, Noah
AU - Kelleher, Christa
AU - Packman, Aaron
AU - Ward, Adam
N1 - Funding Information:
J. Drummond was supported by an NSF EAR-Postdoctoral Fellowship. A portion of Ward's time was supported by NSF EAR-1652293 and DOE DE-SC0019377. Monte Carlo and uncertainty analysis software are available as the Sensitivity and Uncertainty Analysis for Everyone (SAFE) package (http://www.bris.ac.uk/cabot/resources/safe-toolbox/). The MATLAB source code used to generate the model simulations and all data presented is available online (https://doi.org/10.6084/m9.figshare.7378028). Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government.
Funding Information:
J. Drummond was supported by an NSF EAR‐Postdoctoral Fellowship. A portion of Ward's time was supported by NSF EAR‐1652293 and DOE DE‐SC0019377. Monte Carlo and uncertainty analysis software are available as the Sensitivity and Uncertainty Analysis for Everyone (SAFE) package ( http://www.bris.ac.uk/cabot/resources/safe‐toolbox/ ). The MATLAB source code used to generate the model simulations and all data presented is available online ( https://doi.org/10.6084/m9.figshare.7378028 ). Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government.
Publisher Copyright:
©2019. American Geophysical Union. All Rights Reserved.
PY - 2019/12/16
Y1 - 2019/12/16
N2 - Fine particles are critical to stream ecosystem functioning, influencing in-stream processes from pathogen transmission to carbon cycling, all of which depend on particle immobilization. However, our ability to predict particle immobilization is limited by (1) availability of combined solute and particle tracer data and (2) identifying parameters that appropriately represent fine particle immobilization, due to the myriad of objective functions and model formulations. We found that improved predictions of the full distribution of possible fine particle residence times requires using an objective function that assesses both the peak and tailing of breakthrough curves together with solute tracers to constrain in-stream transport processes. The representation of immobilization processes was significantly improved when solute tracer data were combined with a particle model, starkly contrasting the common assumption that fine particles transport as washload. We develop a clear strategy for improving fine particle transport predictions, reshaping the potential role of fine particles in water quality management.
AB - Fine particles are critical to stream ecosystem functioning, influencing in-stream processes from pathogen transmission to carbon cycling, all of which depend on particle immobilization. However, our ability to predict particle immobilization is limited by (1) availability of combined solute and particle tracer data and (2) identifying parameters that appropriately represent fine particle immobilization, due to the myriad of objective functions and model formulations. We found that improved predictions of the full distribution of possible fine particle residence times requires using an objective function that assesses both the peak and tailing of breakthrough curves together with solute tracers to constrain in-stream transport processes. The representation of immobilization processes was significantly improved when solute tracer data were combined with a particle model, starkly contrasting the common assumption that fine particles transport as washload. We develop a clear strategy for improving fine particle transport predictions, reshaping the potential role of fine particles in water quality management.
KW - fine particles
KW - improved particle predictions
KW - mobile-immobile model
KW - parameter uncertainty
KW - particle immobilization
KW - river corridor
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U2 - 10.1029/2019GL085849
DO - 10.1029/2019GL085849
M3 - Article
AN - SCOPUS:85077052152
SN - 0094-8276
VL - 46
SP - 13853
EP - 13861
JO - Geophysical Research Letters
JF - Geophysical Research Letters
IS - 23
ER -