Improved Empirical Representation of Plant Responses to Waterlogging for Simulating Crop Yield

Waterlogging causes apparent reductions in crop yields around the world. Crops undergo plant responses and adaptations due primarily to the reduction in soil oxygen concentrations in the plant root zone that occur during waterlogged conditions. Current methods of assessing and quantifying crop yield reductions due to waterlogging, such as the sum of excess water (SEW) and stress day index (SDI) accumulating methods, and the models DRAINMOD, Agricultural Production Systems Simulator (APSIM), and Salt Water And Groundwater MANagement (SWAGMAN) Destiny (Destiny) do not include plant physiological adaptation processes that may limit or avoid reductions in crop yield. This paper analyses results from field trials to create a unifying concept that recognizes the various responses and adaptations of crops to waterlogging. We propose an empirical three stage representation of crop responses and adaptations during waterlogging. Stage one represents increased plant function with unlimited water and adequate soil oxygen concentrations for root respiration for up to 3 d. Stage two follows and represents plant response to declining soil oxygen concentrations oft en resulting in decreased plant function. Finally, stage three represents species dependant plant adaptations. We test the sensitivity of SWAGMAN Destiny using our three stage empirical representation to estimate yield reductions due to waterlogging. Results are consistent with field trial observations, with decreased yield compared to simulations using 10% air-filled pore space as the waterlogging criteria. We suggest the three stage empirical representation for specific crops can be used to improve simulation model estimations of crop yields due to waterlogging.