T H; M KH; M Z; A GH
Abstract
Crop models are suitable for simulation of crop yield by different scenarios of deficit irrigation and salinity. In this research, the AquaCrop model was evaluated to simulate the soybean grain yield and biomass under different levels of salinity and deficit irrigation in Gorgan County during 2011 and ...
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Crop models are suitable for simulation of crop yield by different scenarios of deficit irrigation and salinity. In this research, the AquaCrop model was evaluated to simulate the soybean grain yield and biomass under different levels of salinity and deficit irrigation in Gorgan County during 2011 and 2012 growing seasons. The model was calibrated by experimental data of 2011 and validated with data of 2012. The experiment included three irrigation levels of 100%, 75% and 55% water requirement and three salinity levels of 0.7, 5 and 10 dS/m. Statistical indices of the results of validated model including RMSE, E, and d for grain yield were 0.225 ton/ha, 0.88 and 0.97, respectively, and for biomass, they were 0.718 ton/ha, 0.77 and 0.95, respectively. Results showed that grain yield decreased with decrease in the amount of irrigation water and increase in salinity level. Further analysis showed that the sensitivity of AquaCrop model to the canopy decline coefficient (CDC) was more than the other parameters at senescence and maximum canopy cover stages.
t h; m kh; m z
Abstract
Climate change affects precipitation and temperature patterns and, hence, may affect the crops yield. In this study investigated the simulation of grain yield and biomass of soybean under future climate in different irrigation treatments and different planting date as adaptation strategy using AquaCrop ...
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Climate change affects precipitation and temperature patterns and, hence, may affect the crops yield. In this study investigated the simulation of grain yield and biomass of soybean under future climate in different irrigation treatments and different planting date as adaptation strategy using AquaCrop model. For this purpose, the data of precipitation, minimum temperature, maximum temperature and sunshine hours and the LARS-WG statistical downscaling model was used from HadCM3 atmospheric general circulation model and under emission scenarios A2 and B1, in the periods 2011- 2038, 2039-2066 and 2067-2094. AquaCrop model was calibrated and validated by the data collected in the field before being used. Finally, the amount of grain yield and biomass simulated in future periods, for 6 different planting dates and for treatments of 100%, 75% and 55% water requirement. Based on the results, under emission scenarios A2 and B1 in 17 June for the period 2011- 2038 as compared to the base period (1981-2008), the amount of simulated biomass and grain yield, decreased, respectively, between 5 to 11.5% and 8.3 to 13.7% and for the period 2039-2066 increased, respectively, between 18.6 to 24% and 16 to 24.4%, and for the period 2067-2094 increased between 9 to 21.8% and 7.2 to 21.2%. Also, by selecting planting date of 20 June, the largest increase of biomass and grain yield were simulated for periods 2011-2038, 2039-2066, and 2067-2094 under the A2 and B1 scenarios. These results will be useful for future irrigation planning in Gorgan area.