Location: Northwest Watershed Research CenterTitle: Process-based modeling of temperature and water profiles in the seedling recruitment zone: Part II. Seedling emergence timing
|BULLIED, W - University Of Guelph|
|BULLOCK, PAUL - University Of Manitoba|
|VAN ACKER, RENE - University Of Guelph|
Submitted to: Agricultural and Forest Meteorology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 10/9/2013
Publication Date: 3/3/2014
Citation: Bullied, W.J., Flerchinger, G.N., Bullock, P.R., Van Acker, R.C. 2014. Process-based modeling of temperature and water profiles in the seedling recruitment zone: Part II. Seedling emergence timing. Agricultural and Forest Meteorology. 188:104-120. DOI: 10.1016/j.agrformet.2013.10.007
Interpretive Summary: Seedling germination models can be used to predict seedling emergence and weed recruitment for better weed management, but these models require knowledge of temperature and moisture conditions near the soil surface that are difficult to obtain. The feasibility of using computer simulated temperature and moisture conditions from the Simultaneous Heat and Water (SHAW) in conjunction with a seedling germination and recruitment model was investigated. Results showed that rates of seed emergence predicted by a seedling germination model using simulated soil temperature and moisture provided representative predictions of seedling emergence for spring wheat. By using process-based modeling to predict timing of crop and weed emergence, pre-emergent pesticides can be used to better target weeds.
Technical Abstract: Predictions of seedling emergence timing for spring wheat are facilitated by process-based modeling of the microsite environment in the shallow seedling recruitment zone. Hourly temperature and water profiles within the recruitment zone for 60 days after planting were simulated from the process-based simultaneous heat and water (SHAW) model using local and non-local microclimatic data. Linear mixed-effects models indicated that simulated thermal and hydrothermal time accumulations were similar to measurements. Emergence timing was fitted using the Gompertz equation. Simulations averaged across depth had quicker emergence timing of wheat at inflection by 20°Cd for thermal time and 23 MPa°Cd for hydrothermal time models, equating to 1.3 days earlier in the DAP model. Seedling emergence rates were similar between simulations and measurements. The recruitment depth of spring wheat over time was fitted with a Beta function which was positively skewed with early recruitment of a large number of seedlings from a moderate depth and late recruitment by a small number of seedlings from a shallow depth. The time of simulated Beta maxima was greater by 39°Cd for thermal time and 3 MPa°Cd for hydrothermal time, and 1.5 d less than the measured maxima for the DAP model. The 95 % confidence intervals for the fitted simulation and measured Beta functions overlapped for the entire duration of the distribution for all time scale models. Process-based simulations of soil temperature and soil water in the seedling recruitment zone provided representative predictions of seedling emergence timing for spring wheat.