Modelling near-surface soil temperature and moisture for germination response predictions of post-wildfire seedbeds

A major contributor to degradation on rangelands in the western United States is the expansion of undesirable annual weeds following wildfire or other disturbance. The Simultaneous Heat and Water (SHAW) model was applied to three soil types (loamy sand, sandy loam, and silt loam) to simulate near-surface soil temperature and water for predicting potential seed germination in post-wildfire revegetation. Three parameterization methods including initial parameter estimates, calibrated parameters, and measured moisture-release curve parameters were compared to assess the effect of parameter uncertainty on germination prediction. Initial parameters for the sandy loam soil resulted in an underprediction of germination times by 4.7 days for cheatgrass to 12.8 days for bluebunch wheatgrass compared to germination estimated from measured soil temperature and water conditions. Initial parameters resulted in predicted germination within 2 days of estimates for the other two soils. Model calibration to optimize the surface 20-cm water-content did not necessarily improve predicted germination. Model simulations using measured moisture-release curves resulted in germination prediction within a few days relative to estimates for all sites. Results suggest that the model can be used for long-term simulations of seedbed microclimate necessary to evaluate potential germination response of revegetation species and their weedy competitors.