نوع مقاله : مقاله کامل
1 دانشجوی دکتری گروه جغرافیای طبیعی، دانشکدة علوم جغرافیایی و برنامه ریزی، دانشگاه اصفهان
2 دانشیار گروه جغرافیای طبیعی، دانشکدة علوم جغرافیایی و برنامه ریزی، دانشگاه اصفهان
3 استادیار بخش آب و خاک، مرکز تحقیقات جهاد کشاورزی شهر کرد
عنوان مقاله [English]
Climate has a key role in plant growth process and, therefore, it is clear that climate change will directly affect sowing and harvesting of cultivate crops. Many scientists used APSIM to simulate the phenology and yield of canola. To understand the impacts 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 of the impacts of climate change on phenology and yield of agricultural crops in different regions show different results. The aim of this study is to investigate the impacts of climate change on phenological stages and yield of Canola by APSIM-canola modules.
Materials and methods
Chaharmahl va Bakhtiari in the southwestern Iran is one of the main agricultural production zones in 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 obtained from 6 synoptic weather stations in the study area. The data were used after quality control process. The meteorological data have been converted into compatible text format with APSIM.
Biometric data and phenology
Canola has several varieties. Okapi is one of the winter varieties which were recommended for the study area. Agrometeorological data, including phenology and biometry from 2001 to 2010 were gathered and summarized. The canola phenological stages are including planting, germination, emergence, the first true leaf, rosette, ceasing of the winter growth, budding, stem elongation, flowering, pod, ripening and harvesting. Farming management information such as the amount of fertilizer, irrigation and frost and pest were also recorded. A total of 1700 phenological stages were 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. The simulations were carried out using two different resolutions: 0.44° (approx. 50 km) and 0.22° (approx. 25 km).
Agricultural Production Systems Simulator (APSIM) is 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 are now cultivated in the study area. Germination, emergence, end of juvenile phase, flower initiation, flowering, grain filling and maturating are seven simulations of the phenological stages.
Results and discussion
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).
The highest RMSE was in the simulation of the days after sowing to maturity (DTM) stage with 5 days and bias error was -0.7 days. Greatest bias error occurred in simulation of the 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 the days after sowing to flower initiation (DTFI) and the days after sowing to flowering (DTFL).
Because of the crop management, soil and water conditions, simulation was conducted in three cases of poor, middle and high management. The RMSE in estimation of yield was 329.8 kg/ha which included 7.2% of canola average yield on the study area. The rate of Bias error was 18.2 kg and correlation between actual and simulated data was 0.96. We considered every year of farm management, nutrient and irrigation in the simulation. The results showed that APSIM has reliability skill in simulation. Based on scenario RCP8.5, the DTE, DTFI, DTFL, DTEGF and DTM stages will be reduced from 1 to 13 days and the maximum reduction can be seen in the flowering and grain filling phases.
The results of data from RCP4.5 showed that DTFL and DTEGF stages will decrease from 2 to 3 days and that the greatest rate of decline was observed in the flowering period. DTEJ, DTFI and DTM stages will rise following that. DTFI and DTM stages will be increased up to 3 days. 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 to 18%; whereas in poor management conditions of the yield will be increased 18 and 13.6 percent.
RCP 4.5 in optimal nutrition and management will be increased 13.4% and in intermediate and poor management it will raise about 14.3 and 13.6 percent. This suggests that without water limit, global warming will have positive impacts on canola yield in this area.
The study revealed that APSIM could simulate the yield of canola with RMSE 320 kg/ha. The results showed that with RCP8.5, phenological stages including DTE, DTFL and DTEGF and DTM will be declined. With RCP4.5, phenological stages including DTFL and DTEGF will also be shortened. The higher rate of decline was observed by RCP 8.5 scenario. DTEJ on RCP 8.5 and RCP 4.5 will be longer in 10 days and 9 days, respectively. It is expected that canola yield will be increased in both studied scenarios in optimum nutrition about 18%, more than 13 percent in average and up to 18 percent on low nutrient. The outlook of Canola-Okapi yield increase in Iran show a good potential for planting of this variety and this product will be developed in 2030 plan.