جستجوی مقالات مرتبط با کلیدواژه « agmip » در نشریات گروه « زراعت »

The present research was conducted to simulate the impact of climate change on irrigated barley in Lorestan and Hamadan provinces. For this purpose, nine regions including Aligudarz, Borujerd, Khorramabad, Kuhdasht, Pol-e Dokhtar, Hamedan, Malayer, Nahavand, and Kabudarahang were selected in the two provinces. The APSIM-barley model was employed to simulate the growth and development of irrigated barley. Firstly, the APSIM-barley model was evaluated using two independent field experiments. The first experiment was conducted in Khorramabad to calibrate the crop model; while the second experiment was done in Hamedan to validate the crop model. The future climate was projected using the AgMIP methodology under two scenarios (RCP4.5 and RCP8.5) for the period 2040-2070. The results of the model validation showed that the crop model was able to simulate barley yield and biomass with nRMSE of 16.4% and 13.3%, respectively. Additionally, the results indicated that on average across the study locations, barley grain yield would decrease by 3.8% and 5.7% under RCP4.5 and RCP8.5, respectively. However, in Pol-e Dokhtar, barley grain yield is projected to increase by 1.3% and 4.8% under RCP4.5 and RCP8.5, respectively. Based on these findings, adaptation strategies should be considered in the future to prevent the reduction of irrigated barley yield in the studied provinces.

Among the field crops in Iran, wheat is one of the most importance crops and it is anticipated that country demand to this crop will be increased in the future. On the other hand, to improve the resilience and efficiency of agricultural systems, it seems to be urgent to anticipate the effects of climate change (changes in CO2, temperature and rainfall) on crops particularly on wheat in arid and semi-arid regions. So, this study was conducted to simulate yield and water use efficiency of wheat in four locations in the future (2050)

In this research, future projection (2050) was conducted in four locations in Khorasan Razavi province (Ghoochan, Gonabad, Sabzevar and TorbateHeydariyeh), Iran by using long term climate data at baseline (2010-1980) under two emission scenarios (RCP4.5 and RCP8.5). Future climatic scenarios were produced using the delta scenario of the CMIP5 General Circulation Model (GCM) and the climate scenario generation tools in R as introduced in the Agricultural Model Intercomparison and Improvement Project (AgMIP). A Global Circulation Model (MPI-ESM-MR) was applied. APSIM-Wheat model was used to simulate growth, yield and water use efficiency of wheat. Regarding CO2 concentration, two scenarios were considered: CC scenario (climate change along with increasing CO2 concentration) and FC scenario (climate change without increasing CO2 concentration).

Simulated results showed that average of growth season temperature in study locations in future will be increased by 1.6 ºC and rainfall will be decreased by 5.85 percent, in comparison with baseline. In CC, the average of yield increased 4.91 percent under RCP4.5 and 4.77 percent under RCP8.5. However, in FC the average of yield decreased (except Gonabad) 4.98 and 7.56 percent under two RCPs, respectively. In addition, water use efficiency in CC increased by 12.21 and 15.35 percent for RCP4.5 and RCP8.5, respectively. However, under FC, WUE increased 0.33 percent for RCP4.5 and decreased 0.41 percent for RCP8.5. Also, the finding of this study suggested that changing sowing date as two weeks earlier in Gonabad and Sabzevar will increase yield and water use efficiency, and two weeks later in TorbateHeydariyeh will relief the decreased yield.

Results of the current study showed that if the climate change accompanied with increasing CO2 concentration, the negative effect of climate change on wheat growth and yield would be compensated Also, changing sowing date in future will have further positive impacts on wheat yield and water use efficiency.

Rising temperature as consequences of climate change could affect on the various processes such as photosynthesis, respiration, partitioning of assimilates and ultimately grain yield of agricultural crops. The present experiment was conducted to simulate the impacts of climate change on maize grain yield under two future climate change scenarios (RCP4.5 and RCP8.5) using APSIM model in three counties of Kermanshah province (Kermanshah, Kangavar and Eslamabad Gharb). Future climate data were projected by using long-term climatic data for the baseline period of 1980-2010 and AgMIP methodology for the mid-future (2040-2070). The results showed that, on average, the mean temperature increased up to 11 and 23 percent under RCP4.5 and RCP8.5 scenarios when compared to the baseline, respectively. The maximum and minimum grain yields in the baseline were obtained in Kangavar (14399 kg.ha-1) and Kermanshah (7741 kg.ha-1), respectively. Simulation results also showed that average temperature during growing season rised (0.5 and 2 ˚C under RCP4.5 and RCP8.5, respectively) and length of growing season decreased (5 and 6 percent under RCP4.5 and RCP8.5, respectively) which resulted in a reduction in maize grain yield from 69 to 90 percent under RCP4.5 and RCP8.5, respectively. Results illustrated that under climate change conditions, flowering of maize may coincide with high temperatures and this may reduce maize grain yield, therefore, it can be suggested that changing the sowing dates in the target regions prevents the coincidence of the critical flowering stage with heat stress.

Heat stress caused by climate change will become a restriction for maize production in the future (Cairns et al., 2013). Damage of heat stress is very strong when is occurred in a critical stages of plant growth (particularly in the flowering phase) (Teixeira et al., 2013). Non-coincidentally of flowering stage with high temperature can be reduced the negative effects of heat stress, especially in climate change conditions (Zheng et al., 2012). In this theme, a useful change in the management practices such as early planting dates (Zheng et al., 2012; Liu et al., 2013) could be considered to avoid heat stress and reduce production risk, especially climate change situations. Khuzestan province in terms of grain maize has the highest cultivated area in Iran (Anonymous, 2013). Based on this and according to the impact of climate change on reducing maize yield in the Khuzestan province (Abbas Torki et al., 2011), this study tries to assess the risk of heat stress in grain maize at the Khuzestan province under rising temperature conditions caused by climate change.
This research was conducted in six locations of Khuzestan Province to investigate the risk assessment due to heat stress in maize in the future climate change. Accordingly, the future climate in the study areas was generated using long-term (1980-2009) climate data of the baseline (included minimum and maximum temperatures, rainfall and global radiation) and AgMIP technique under two climate scenarios (RCP4.5 and RCP8.5) for the future period of 2040 -2069. Long-term simulation experiments consisted of three sowing dates (3st February, 19st February and 5th March), six locations (Ahwaz, Behbahan, Dezful, Izeh, Ramhormoz and Shushtar), two future climate scenarios (RCP4.5 and RCP8.5) in 30 years. In total, around 1620 simulation experiments were carried out. To assess the risk of heat stress on maize, it was considered the time (phase), frequency and intensity of maize threshold temperatures in its sensitive phenological phases. To this end, flowering and grain formation phases of maize were noted as the most sensitive to high temperature stress. In this study, APSIM crop model was used for simulation of maize growth and yield. The OriginPro 9.1 and R software were used to draw figures and perform statistical analyses.
Results indicated that the average temperature during the growing season in the Khuzestan province was increased under RCP4.5 and RCP8.5 (8.5 and 34.57 percent, respectively) in comparison to the baseline (27.2 °C). The highest temperature rise was obtained in the Ramhormoz (27.2 °C) on 5th March under RCP8.5. Also, the highest temperature rise during the growing season under RCP4.5 obtained in Shushtar (27.2 °C) on 19st February. In the baseline, on average, grain yield and the number of grains/m-2 in the Khuzestan province were obtained 8.8 t ha-1 and 2305.7. These values in 2050 were 8.5 and 8.7 t ha-1 and 2227.3 and 2254.3 grains/m-2 for RCP4.5 and RCP8.5, respectively. When average across sowing dates, locations and periods, the cumulative probability function for economic yield, non-economic yield and zero yield were 45.4, 13.5 and 41.2 %, respectively for common sowing dates. Under, earlier sowing date (3 February) the cumulative probability for economic yield was higher than the other sowing dates both in future and the baseline periods (65.2 percent).
Overall, the results of this study showed that common sowing date which is used by most farmers (19st February) in Khuzestan province was not optimal for both current and future periods while the early sowing date (3st February) in most locations could be considered as an effective adaptation strategy to reduce the amount of extreme temperatures risk in future and to increase grain yield under the current conditions.