Modelling field scale spatial variation in water run-off, soil moisture, N2O emissions and herbage biomass of a grazed pasture using the SPACSYS model

A - Papers appearing in refereed journals

Liu, Y., Li, Y., Harris, P., Cardenas, L. M., Dunn, R. M., Sint, H. M., Murray, P. J., Lee, M. R. F. and Wu, L. 2018. Modelling field scale spatial variation in water run-off, soil moisture, N2O emissions and herbage biomass of a grazed pasture using the SPACSYS model. Geoderma. 315, pp. 49-58. https://doi.org/10.1016/j.geoderma.2017.11.029

AuthorsLiu, Y., Li, Y., Harris, P., Cardenas, L. M., Dunn, R. M., Sint, H. M., Murray, P. J., Lee, M. R. F. and Wu, L.
Abstract

In this study, we evaluated the ability of the SPACSYS model to simulate water run-off, soil moisture, N2O 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 N2O fluxes, but here the N2O predictions were noticeably poor in both cases. Further developmental work, informed by this study’s findings, is proposed to improve model predictions for N2O. Soil moisture results with the spatially distributed version appeared promising but this promise could not be objectively verified.

KeywordsNorth Wyke Farm Platform; Spatial heterogeneity; Grid-to-grid simulation
Year of Publication2018
JournalGeoderma
Journal citation315, pp. 49-58
Digital Object Identifier (DOI)https://doi.org/10.1016/j.geoderma.2017.11.029
Open accessPublished as ‘gold’ (paid) open access
FunderBiotechnology and Biological Sciences Research Council
Funder project or codeThe North Wyke Farm Platform [2012-2017]
Publisher's version
Output statusPublished
Publication dates
Online07 Dec 2017
Publication process dates
Accepted23 Nov 2017
Copyright licenseCC BY
PublisherElsevier Science Bv
ISSN0016-7061

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