Access to supplementary with AWD irrigation increased the stability of grain yield, and crop and water productivity, irrespective of the onset of rainfall or time of crop establishment. Alternatively, in years when an early onset was observed, late planting in the season reduced the use of rain water by 95% while increasing the irrigation water requirement by 11% compared with planting at rainfall onset. When the onset of rainfall is delayed, crop modelling scenarios using the validated APSIM model showed an increased dependence on supplementary irrigation for rice cultivation. 3 a and b shows how well the inverse meta-model approximates the relationship between crop yield and profile AWC that is contained within APSIM. The same analysis revealed that an early onset to the rainy season resulted in longer seasons with more rain than late onset. The model with three nodes proved slightly better at approximating APSIM than that with two nodes (CV R 2 values were 0.76 and 0.74, respectively). This would require some low level programming though - not trivial. More sophisticated would be to use an inter-process mechanism like sockets to do the connection between APSIM and Python/R - same idea as above but will run quicker and is more flexible. This is a consequence of the current practice of setting the date for crop establishment at pre-season cultivation meetings without a scientifically-validated rainfall forecast. That other process could be an R or python script. A climatic analysis indicated that the farmers regularly establish rice crops 2–4 weeks after the rainfall onset. totally rainfed or rainfed with supplementary irrigation). with rainfall onset or date-specific planting), variety and/or water management practice (i.e. Competing in the Age of AI: Strategy and Leadership When Algorithms and Networks Run the World Karim R. The model estimated the grain yield of rice under moisture-limited farmer-field conditions with a strong fit (n = 24, R2 > 0.97, RMSE = 484 kg ha−1), across cultivation year, season, time of establishment (i.e. Therefore, we parameterised and evaluated the APSIM–Oryza model for two widely grown Sri Lankan short- and medium-duration rice varieties. Benefits of aligning crop establishment with the onset of rainfall to reduce dependency on supplementary irrigation and improve crop and water productivities have not yet been quantified in Sri Lanka. rainfed or rainfed with supplementary alternate wetting-and-drying (AWD) irrigation) farmer-field conditions in tropical South-Asia has received little attention in modelling exercises. Once properly parameterised, the model performed well in simulating the diversity of cropping systems to which it was applied with RMSEs generally less than observed experimental standard deviations (indicating robust model performance), and with. Despite its importance, the crop productivity (kg ha−1) and water productivity (kg ha−1 mm−1) of rice under moisture-limited (i.e. APSIMs performance was statistically assessed against assembled replicated experimental datasets. The APSIM–Oryza model has been used worldwide to evaluate the impact of diverse management practices on the growth of rice (Oryza sativa L.).
0 kommentar(er)
