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Modelling field scale spatial variation in water run-off, soil moisture, N(2)O emissions and herbage biomass of a grazed pasture using the SPACSYS model

In this study, we evaluated the ability of the SPACSYS model to simulate water run-off, soil moisture, N(2)O fluxes and grass growth using data generated from a field of the North Wyke Farm Platform. The field-scale model is adapted via a linked and grid-based approach (grid-to-grid) to account for...

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Autores principales: Liu, Yi, Li, Yuefen, Harris, Paul, Cardenas, Laura M., Dunn, Robert M., Sint, Hadewij, Murray, Phil J., Lee, Michael R.F., Wu, Lianhai
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Scientific Pub. Co 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5777021/
https://www.ncbi.nlm.nih.gov/pubmed/29615828
http://dx.doi.org/10.1016/j.geoderma.2017.11.029
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author Liu, Yi
Li, Yuefen
Harris, Paul
Cardenas, Laura M.
Dunn, Robert M.
Sint, Hadewij
Murray, Phil J.
Lee, Michael R.F.
Wu, Lianhai
author_facet Liu, Yi
Li, Yuefen
Harris, Paul
Cardenas, Laura M.
Dunn, Robert M.
Sint, Hadewij
Murray, Phil J.
Lee, Michael R.F.
Wu, Lianhai
author_sort Liu, Yi
collection PubMed
description In this study, we evaluated the ability of the SPACSYS model to simulate water run-off, soil moisture, N(2)O fluxes and grass growth using data generated from a field of the North Wyke Farm Platform. The field-scale model is adapted via a linked and grid-based approach (grid-to-grid) to account for not only temporal dynamics but also the within-field spatial variation in these key ecosystem indicators. Spatial variability in nutrient and water presence at the field-scale is a key source of uncertainty when quantifying nutrient cycling and water movement in an agricultural system. Results demonstrated that the new spatially distributed version of SPACSYS provided a worthy improvement in accuracy over the standard (single-point) version for biomass productivity. No difference in model prediction performance was observed for water run-off, reflecting the closed-system nature of this variable. Similarly, no difference in model prediction performance was found for N(2)O fluxes, but here the N(2)O predictions were noticeably poor in both cases. Further developmental work, informed by this study's findings, is proposed to improve model predictions for N(2)O. Soil moisture results with the spatially distributed version appeared promising but this promise could not be objectively verified.
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spelling pubmed-57770212018-04-01 Modelling field scale spatial variation in water run-off, soil moisture, N(2)O emissions and herbage biomass of a grazed pasture using the SPACSYS model Liu, Yi Li, Yuefen Harris, Paul Cardenas, Laura M. Dunn, Robert M. Sint, Hadewij Murray, Phil J. Lee, Michael R.F. Wu, Lianhai Geoderma Article In this study, we evaluated the ability of the SPACSYS model to simulate water run-off, soil moisture, N(2)O fluxes and grass growth using data generated from a field of the North Wyke Farm Platform. The field-scale model is adapted via a linked and grid-based approach (grid-to-grid) to account for not only temporal dynamics but also the within-field spatial variation in these key ecosystem indicators. Spatial variability in nutrient and water presence at the field-scale is a key source of uncertainty when quantifying nutrient cycling and water movement in an agricultural system. Results demonstrated that the new spatially distributed version of SPACSYS provided a worthy improvement in accuracy over the standard (single-point) version for biomass productivity. No difference in model prediction performance was observed for water run-off, reflecting the closed-system nature of this variable. Similarly, no difference in model prediction performance was found for N(2)O fluxes, but here the N(2)O predictions were noticeably poor in both cases. Further developmental work, informed by this study's findings, is proposed to improve model predictions for N(2)O. Soil moisture results with the spatially distributed version appeared promising but this promise could not be objectively verified. Elsevier Scientific Pub. Co 2018-04-01 /pmc/articles/PMC5777021/ /pubmed/29615828 http://dx.doi.org/10.1016/j.geoderma.2017.11.029 Text en © 2017 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Liu, Yi
Li, Yuefen
Harris, Paul
Cardenas, Laura M.
Dunn, Robert M.
Sint, Hadewij
Murray, Phil J.
Lee, Michael R.F.
Wu, Lianhai
Modelling field scale spatial variation in water run-off, soil moisture, N(2)O emissions and herbage biomass of a grazed pasture using the SPACSYS model
title Modelling field scale spatial variation in water run-off, soil moisture, N(2)O emissions and herbage biomass of a grazed pasture using the SPACSYS model
title_full Modelling field scale spatial variation in water run-off, soil moisture, N(2)O emissions and herbage biomass of a grazed pasture using the SPACSYS model
title_fullStr Modelling field scale spatial variation in water run-off, soil moisture, N(2)O emissions and herbage biomass of a grazed pasture using the SPACSYS model
title_full_unstemmed Modelling field scale spatial variation in water run-off, soil moisture, N(2)O emissions and herbage biomass of a grazed pasture using the SPACSYS model
title_short Modelling field scale spatial variation in water run-off, soil moisture, N(2)O emissions and herbage biomass of a grazed pasture using the SPACSYS model
title_sort modelling field scale spatial variation in water run-off, soil moisture, n(2)o emissions and herbage biomass of a grazed pasture using the spacsys model
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5777021/
https://www.ncbi.nlm.nih.gov/pubmed/29615828
http://dx.doi.org/10.1016/j.geoderma.2017.11.029
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