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

Yi Liu, Yuefen Li, Paul Harris, Laura M. Cardenas, Robert M. Dunn, Hadewij Sint, Phil J. Murray, Michael R.F. Lee, Lianhai Wu*

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

8 Citations (Scopus)
314 Downloads (Pure)

Abstract

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.
Original languageEnglish
Pages (from-to)49-58
Number of pages10
JournalGeoderma
Volume315
Early online date7 Dec 2017
DOIs
Publication statusPublished - 1 Apr 2018

Keywords

  • North Wyke Farm Platform
  • Spatial heterogeneity
  • Grid-to-grid simulation

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