TY - JOUR
T1 - Modelling field scale spatial variation in water run-off, soil moisture, N2O emissions and herbage biomass of a grazed pasture using the SPACSYS model
AU - Liu, Yi
AU - Li, Yuefen
AU - Harris, Paul
AU - Cardenas, Laura M.
AU - Dunn, Robert M.
AU - Sint, Hadewij
AU - Murray, Phil J.
AU - Lee, Michael R.F.
AU - Wu, Lianhai
PY - 2018/4/1
Y1 - 2018/4/1
N2 - 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.
AB - 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.
KW - North Wyke Farm Platform
KW - Spatial heterogeneity
KW - Grid-to-grid simulation
UR - http://www.scopus.com/inward/record.url?scp=85037532048&partnerID=8YFLogxK
U2 - 10.1016/j.geoderma.2017.11.029
DO - 10.1016/j.geoderma.2017.11.029
M3 - Article (Academic Journal)
C2 - 29615828
SN - 0016-7061
VL - 315
SP - 49
EP - 58
JO - Geoderma
JF - Geoderma
ER -