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Stream water age distributions controlled by storage dynamics and nonlinear hydrologic connectivity: Modeling with high‐resolution isotope data

To assess the influence of storage dynamics and nonlinearities in hydrological connectivity on time‐variant stream water ages, we used a new long‐term record of daily isotope measurements in precipitation and streamflow to calibrate and test a parsimonious tracer‐aided runoff model. This can track t...

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Autores principales: Soulsby, C., Birkel, C., Geris, J., Dick, J., Tunaley, C., Tetzlaff, D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4949550/
https://www.ncbi.nlm.nih.gov/pubmed/27478255
http://dx.doi.org/10.1002/2015WR017888
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author Soulsby, C.
Birkel, C.
Geris, J.
Dick, J.
Tunaley, C.
Tetzlaff, D.
author_facet Soulsby, C.
Birkel, C.
Geris, J.
Dick, J.
Tunaley, C.
Tetzlaff, D.
author_sort Soulsby, C.
collection PubMed
description To assess the influence of storage dynamics and nonlinearities in hydrological connectivity on time‐variant stream water ages, we used a new long‐term record of daily isotope measurements in precipitation and streamflow to calibrate and test a parsimonious tracer‐aided runoff model. This can track tracers and the ages of water fluxes through and between conceptual stores in steeper hillslopes, dynamically saturated riparian peatlands, and deeper groundwater; these represent the main landscape units involved in runoff generation. Storage volumes are largest in groundwater and on the hillslopes, though most dynamic mixing occurs in the smaller stores in riparian peat. Both streamflow and isotope variations are generally well captured by the model, and the simulated storage and tracer dynamics in the main landscape units are consistent with independent measurements. The model predicts that the average age of stream water is ∼1.8 years. On a daily basis, this varies between ∼1 month in storm events, when younger waters draining the hillslope and riparian peatland dominates, to around 4 years in dry periods when groundwater sustains flow. This variability reflects the integration of differently aged water fluxes from the main landscape units and their mixing in riparian wetlands. The connectivity between these spatial units varies in a nonlinear way with storage that depends upon precipitation characteristics and antecedent conditions. This, in turn, determines the spatial distribution of flow paths and the integration of their contrasting nonstationary ages. This approach is well suited for constraining process‐based modeling in a range of northern temperate and boreal environments.
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spelling pubmed-49495502016-07-28 Stream water age distributions controlled by storage dynamics and nonlinear hydrologic connectivity: Modeling with high‐resolution isotope data Soulsby, C. Birkel, C. Geris, J. Dick, J. Tunaley, C. Tetzlaff, D. Water Resour Res Research Articles To assess the influence of storage dynamics and nonlinearities in hydrological connectivity on time‐variant stream water ages, we used a new long‐term record of daily isotope measurements in precipitation and streamflow to calibrate and test a parsimonious tracer‐aided runoff model. This can track tracers and the ages of water fluxes through and between conceptual stores in steeper hillslopes, dynamically saturated riparian peatlands, and deeper groundwater; these represent the main landscape units involved in runoff generation. Storage volumes are largest in groundwater and on the hillslopes, though most dynamic mixing occurs in the smaller stores in riparian peat. Both streamflow and isotope variations are generally well captured by the model, and the simulated storage and tracer dynamics in the main landscape units are consistent with independent measurements. The model predicts that the average age of stream water is ∼1.8 years. On a daily basis, this varies between ∼1 month in storm events, when younger waters draining the hillslope and riparian peatland dominates, to around 4 years in dry periods when groundwater sustains flow. This variability reflects the integration of differently aged water fluxes from the main landscape units and their mixing in riparian wetlands. The connectivity between these spatial units varies in a nonlinear way with storage that depends upon precipitation characteristics and antecedent conditions. This, in turn, determines the spatial distribution of flow paths and the integration of their contrasting nonstationary ages. This approach is well suited for constraining process‐based modeling in a range of northern temperate and boreal environments. John Wiley and Sons Inc. 2015-09 2015-09-26 /pmc/articles/PMC4949550/ /pubmed/27478255 http://dx.doi.org/10.1002/2015WR017888 Text en © 2015. The Authors. This is an open access article under the terms of the Creative Commons Attribution (http://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Articles
Soulsby, C.
Birkel, C.
Geris, J.
Dick, J.
Tunaley, C.
Tetzlaff, D.
Stream water age distributions controlled by storage dynamics and nonlinear hydrologic connectivity: Modeling with high‐resolution isotope data
title Stream water age distributions controlled by storage dynamics and nonlinear hydrologic connectivity: Modeling with high‐resolution isotope data
title_full Stream water age distributions controlled by storage dynamics and nonlinear hydrologic connectivity: Modeling with high‐resolution isotope data
title_fullStr Stream water age distributions controlled by storage dynamics and nonlinear hydrologic connectivity: Modeling with high‐resolution isotope data
title_full_unstemmed Stream water age distributions controlled by storage dynamics and nonlinear hydrologic connectivity: Modeling with high‐resolution isotope data
title_short Stream water age distributions controlled by storage dynamics and nonlinear hydrologic connectivity: Modeling with high‐resolution isotope data
title_sort stream water age distributions controlled by storage dynamics and nonlinear hydrologic connectivity: modeling with high‐resolution isotope data
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4949550/
https://www.ncbi.nlm.nih.gov/pubmed/27478255
http://dx.doi.org/10.1002/2015WR017888
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