2024-03-29T04:34:55Zhttp://digital.csic.es/dspace-oai/requestoai:digital.csic.es:10261/1814452019-05-16T13:36:16Zcom_10261_88com_10261_8col_10261_341
DIGITAL.CSIC
author
Kelleher, Christa
author
Ward, Adam S.
author
Knapp, Julia L.A.
author
Blaen, P. J.
author
Kurz, Marie J.
author
Drummond, Jennifer D.
author
Zarnetske, Jay P.
author
Hannah, David M.
author
Mendoza‐Lera, C.
author
Schmadel, N. M.
author
Datry, Thibault
author
Lewandowski, Jörg
author
Milner, A. M.
author
Krause, Stefan
2019-05-15T08:17:46Z
2019-05-15T08:17:46Z
2019
Water Resources Research 55 : DOI:10.1029/2018WR023585 (2019)
0043-1397
http://hdl.handle.net/10261/181445
1944-7973
Novel observation techniques (e.g., smart tracers) for characterizing coupled hydrological
and biogeochemical processes are improving understanding of stream network transport and
transformation dynamics. In turn, these observations are thought to enable increasingly sophisticated
representations within transient storage models (TSMs). However, TSM parameter estimation is prone to
issues with insensitivity and equifinality, which grow as parameters are added to model formulations.
Currently, it is unclear whether (or not) observations from different tracers may lead to greater process
inference and reduced parameter uncertainty in the context of TSM. Herein, we aim to unravel the role of
in‐stream processes alongside metabolically active (MATS) and inactive storage zones (MITS) using
variable TSM formulations. Models with one (1SZ) and two storage zones (2SZ) and with and without
reactivity were applied to simulate conservative and smart tracer observations obtained experimentally for
two reaches with differing morphologies. As we show, smart tracers are unsurprisingly superior to
conservative tracers when it comes to partitioning MITS and MATS. However, when transient storage is
lumped within a 1SZ formulation, little improvement in parameter uncertainty is gained by using a smart
tracer, suggesting the addition of observations should scale with model complexity. Importantly, our work
identifies several inconsistencies and open questions related to reconciling time scales of tracer
observation with conceptual processes (parameters) estimated within TSM. Approaching TSM with
multiple models and tracer observations may be key to gaining improved insight into transient storage
simulation as well as advancing feedback loops between models and observations within
hydrologic science.
eng
openAccess
Exploring Tracer Information and Model Framework Trade‐Offs to Improve Estimation of Stream Transient Storage Processes
artículo
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URL
https://digital.csic.es/bitstream/10261/181445/1/Drummond%202019.pdf
File
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edc03d76fac5534294d8341e2f54fdfd
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Drummond 2019.pdf