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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...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier Scientific Pub. Co
2018
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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. |
format | Online Article Text |
id | pubmed-5777021 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Elsevier Scientific Pub. Co |
record_format | MEDLINE/PubMed |
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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