Abstract. Few parametric expressions for the soil water retention curve are suitable for dry conditions. Furthermore, expressions for the soil hydraulic conductivity curves associated with parametric retention functions can behave unrealistically near saturation. We developed a general criterion for water retention parameterizations that ensures physically plausible conductivity curves. Only 3 of the 18 tested parameterizations met this criterion without restrictions on the parameters of a popular conductivity curve parameterization. A fourth required one parameter to be fixed.We estimated parameters by shuffled complex evolution (SCE) with the objective function tailored to various observation methods used to obtain retention curve data. We fitted the four parameterizations with physically plausible conductivities as well as the most widely used parameterization. The performance of the resulting 12 combinations of retention and conductivity curves was assessed in a numerical study with 751 days of semiarid atmospheric forcing applied to unvegetated, uniform, 1 m freely draining columns for four textures.Choosing different parameterizations had a minor effect on evaporation, but cumulative bottom fluxes varied by up to an order of magnitude between them. This highlights the need for a careful selection of the soil hydraulic parameterization that ideally does not only rely on goodness of fit to static soil water retention data but also on hydraulic conductivity measurements.Parameter fits for 21 soils showed that extrapolations into the dry range of the retention curve often became physically more realistic when the parameterization had a logarithmic dry branch, particularly in fine-textured soils where high residual water contents would otherwise be fitted.

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1 15 ABSTRACT 16 Plant phenology, which describes the timing of plant development, is a major aspect of 17 plant response to environment and for crops, a major determinant of yield. Many studies have 18 focused on comparing model equations for describing how phenology responds to climate but 19 the effect of crop model calibration, also important for determining model performance, has 20 received much less attention. The objectives here were to obtain a rigorous evaluation of 21 prediction capability of wheat phenology models, to analyze the role of calibration and to 22 document the various calibration approaches. The 27 participants in this multi-model study 23were provided experimental data for calibration and asked to submit predictions for sites and 24 years not represented in those data. Participants were instructed to use and document their 25 "usual" calibration approach. Overall, the models provided quite good predictions of 26 phenology (median of mean absolute error of 6.1 days) and did much better than simply using 27 the average of observed values as predictor. The results suggest that calibration can 28 compensate to some extent for different model formulations, specifically for differences in 29 simulated time to emergence and differences in the choice of input variables. Conversely, 30 different calibration approaches were associated with major differences in prediction error 31 between the same models used by different groups. Given the large diversity of calibration 32 approaches and the importance of calibration, there is a clear need for guidelines and tools to 33 aid with calibration. Arguably the most important and difficult choice for calibration is the 34 choice of parameters to estimate. Several recommendations for calibration practices are 35 proposed. Model applications, including model studies of climate change impact, should 36 focus more on the data used for calibration and on the calibration methods employed. 37

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Abstract. Nitrous oxide (N 2 O) emissions from Australian grain cropping systems are highly variable due to the large variations in soil and climate conditions and management practices under which crops are grown. Agricultural soils contribute 55% of national N 2 O emissions, and therefore mitigation of these emissions is important. In the present study, we explored N 2 O emissions, yield and emissions intensity in a range of management practices in grain crops across eastern Australia with the Agricultural Production Systems sIMulator (APSIM). The model was initially evaluated against experiments conducted at six field sites across major grain-growing regions in eastern Australia. Measured yields for all crops used in the experiments (wheat, barley, sorghum, maize, cotton, canola and chickpea) and seasonal N 2 O emissions were satisfactorily predicted with R 2 = 0.93 and R 2 = 0.91 respectively. As expected, N 2 O emissions and emissions intensity increased with increasing nitrogen (N) fertiliser input, whereas crop yields increased until a yield plateau was reached at a site-and crop-specific N rate. The mitigation potential of splitting N fertiliser application depended on the climate conditions and was found to be relevant only in the southern grain-growing region, where most rainfall occurs during the cropping season. Growing grain legumes in rotation with cereal crops has great potential to reduce mineral N fertiliser requirements and so N 2 O emissions. In general, N management strategies that maximise yields and increase N use efficiency showed the greatest promise for N 2 O mitigation.

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