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Title: Simulation of high frequency nitrous oxide emissions from irrigated sub-tropical soils using DAYCENT

Author
item SCHEER, S - Queensland University Of Technology
item Del Grosso, Stephen - Steve
item PARTON, W - Colorado State University
item ROWLINGS, D - Queensland University Of Technology
item GRACE, P - Queensland University Of Technology

Submitted to: Ecological Applications
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 8/29/2013
Publication Date: 4/1/2014
Publication URL: http://dx.doi.org/10.1890/13-0570.1
Citation: Scheer, S., Del Grosso, S.J., Parton, W.J., Rowlings, D.W., Grace, P.R. 2014. Simulation of high frequency nitrous oxide emissions from irrigated sub-tropical soils using DAYCENT. Ecological Applications. 24:528–538.

Interpretive Summary: Nitrous oxide (N2O) is an important greenhouse gas that also contributes to ozone depletion in the upper atmosphere. The primary source of human caused N2O emissions is agricultural soils. Traditionally, N2O has been measured relatively infrequently (1 to 10 times per month) from experimental plots. A unique high temporal frequency dataset from an irrigated cotton-wheat rotation was used to test the agroecosystem model DayCent to simulate daily N2O emissions from sub-tropical vertisols under different irrigation intensities. Frequent sampling (8 to 10 times per day) helps to better quantify daily as well as seasonal and annual emissions. The DAYCENT ecosystem model was tested by comparing model outputs for crop yields and N2O emissions with field observations. DayCent was able to simulate the effect of different irrigation intensities on N2O fluxes and yield, although it tended to overestimate seasonal fluxes during the cotton season. DayCent accurately predicted soil moisture dynamics and the timing and magnitude of high fluxes associated with fertilizer additions and irrigation events. At the daily scale we found a high correlation of predicted and measured N2O fluxes, confirming that DayCent can be used to test agricultural practices for mitigating N2O emission from irrigated cropping systems. A 25 year scenario analysis indicated that N2O losses from irrigated cotton-wheat rotations on black vertisol soils in Australia can be substantially reduced by an optimized fertilizer and irrigation management (i.e. frequent irrigation and avoidance of excessive fertilizer application), while sustaining maximum yield potentials.

Technical Abstract: A unique high temporal frequency dataset from an irrigated cotton-wheat rotation was used to test the agroecosystem model DayCent to simulate daily N2O emissions from sub-tropical vertisols under different irrigation intensities. DayCent was able to simulate the effect of different irrigation intensities on N2O fluxes and yield, although it tended to overestimate seasonal fluxes during the cotton season. DayCent accurately predicted soil moisture dynamics and the timing and magnitude of high fluxes associated with fertilizer additions and irrigation events. At the daily scale we found a good correlation of predicted vs. measured N2O fluxes (r2 = 0.52), confirming that DayCent can be used to test agricultural practices for mitigating N2O emission from irrigated cropping systems. A 25 year scenario analysis indicated that N2O losses from irrigated cotton-wheat rotations on black vertisols in Australia can be substantially reduced by an optimized fertilizer and irrigation management (i.e. frequent irrigation, avoidance of excessive fertiliser application), while sustaining maximum yield potentials