Detection of climate change impacts on canola yields and phenology (Chahrmahal va Bakhtiari case study)

  Climate has a key role in plant growth Therefore, it is clear that climate change will directly effect on sowing and harvesting of cultivate crops (FAO, 2013). Many scientists used APSIM to simulate the phenology and yield of canola. To understand the impact of climate change it is necessary to project the future climate based on different emission scenarios. These results must be combined with simulation models to predict crop yield and phenological stages. Assessment the impact of climate change on phenology and yield of agricultural crops in different regions show different results. The aim of this study was to investigate the impact of climate change on phenological stages and yield of Canola by APSIM-canola modules. Chaharmahl va bakhtiari in the southwestern of Iran is one of the main agricultural production zones is considered as the highest province of Iran. The soil physical properties were obtained from Agricultural Research center of Farokhshahr. Required meteorological data including precipitation, solar radiation, and daily maximum and minimum temperature were collected from 6 synoptic weather station in the study area. Data was used after quality control process. The meteorological data convert to compatible text format with APSIM.
Biometric data and phenology:Canola has several varieties. Okapi is one of the winter varieties which was recommended for the study area. Agrometeorological data, including phenology and biometry from 2001 to 2010 were gathered and summarized. Includes the canola yield and phenological stages containing planting, germination, emergence, the first true leaf, rosette, stop the growth of winter, budding, stem elongation, flowering, pod, ripening and harvesting. Farm management information such as the amount of fertilizer, irrigation and frost and pest were also recorded. A total of 1700 reported of phenological stages was used over the 10 years of crop evaluation.
Future climate data:Climate change data were downloaded from one of The World Climate Research Programme (WCRP) project so called Coordinated Regional Climate Downscaling Experiment (CORDEX). We used CORDEX MENA data in which the simulations were performed on a rotated grid with the pole at 180°W longitude and 90°N latitude.The domain covers roughly the region from about 27°W to 76°E longitude and 7°S to 45°N latitude. Simulations were carried out using two different resolutions: 0.44° (approx. 50 km) and 0.22° (approx. 25 km).
Model Description:Agricultural Production Systems Simulator (APSIM) known as a highly advanced simulator agricultural systems in the world. There are 43 selectable varieties of spring and winter canola on APSIM v 7.7, but none of them cultivated in the study area. Germination, emergence, end of juvenile phase, flower initiation, flowering, grain filling and maturating are seven simulation of the phenological stages. For simulation of each phonological stage, elapsed time from sowing to the first day of reaching at each stage was counted. Water stress, nutrition, photoperiod, and vernalization have influence on the phenological stages (Zhang et al., 2014).
Highest RMSE was calculated in the simulation of days after sowing to maturity (DTM) stage with 5 days and bias error was -0.7 days. Greatest bias error occurred in simulation of days after sowing to emergence (DTE). The correlation coefficient of the DTG and DTE was not statistically significant and this indicator in the other stages (P-Value = 0.01) is significant. The strongest correlation was obtained between observed and simulation of days after sowing to flower initiation (DTFI) and days after sowing to flowering (DTFL).
Because of the crop management, soil and water conditions, simulation was done in three cases of poor, middle and high management. The RMSE in estimating of yield was 329.8 kg/ha which included 7.2% of canola average yield on study area. The rate of Bias error was18.2 kg and correlation between actual and simulated data were 0.96. We consider every year Farm management, nutrient and irrigation in the simulation and results showed that APSIM has reliability skill in simulation
Based on scenario RCP8.5, considering : DTE, DTFI, DTFL, DTEGF and DTM stages will be reduce between 1 to 13 days the maximum reduction can be seen in the flowering and grain filling phases. However DTEJ will be raise and longer10 days.
The results of data from RCP4.5 showed that DTFL and DTEGF stages, will decrease from 2 to 3 days, the greatest rate of decline was observed in the flowering period. DTEJ, DTFI and DTM stages will rise. DTFI and DTM stages will be increased up to 3 day. And similar to RCP8.5, DTEJ will be raised up to 9 days. It is expected that with RCP8.5 scenario the average of yield on the optimal nutrition and management will be increased around 18%. Whereas in poor management conditions the yield will be increased 18 and 13.6 percent respectively.
RCP 4.5 in optimal nutrition and management will be inceased13.4% and in intermediate and poor management will raise around 14.3 and 13.6 percent. This suggests that without water limit, global warming will have a positive impact on canola yield in this area. The study showed, APSIM could simulate the yield of canola with RMSE 320 kg/ha. Results showed that with RCP8.5, phenological stages including of DTE, DTFL and DTEGF and DTM will be shorten. with RCP4.5 phenological stages including of DTFL and DTEGF will be shorten The higher rate of decline was observed by RCP 8.5 scenario. DTEJ on RCP 8.5 and RCP 4.5 will be respectively longer 10 days and 9 days. It is expected that ,canola yield will be risen with both studied scenarios in optimum nutrition is about18%, in average more than 13 percent and on low nutrient up to 18 percent.
Canola-Okapi yield increasing outlook in rejoin of Iran show a good potential on planting of this variety and this product will be develop on 2030 horizon