sajad rahimi moghaddam

Today, rapid population growth and economic development have increased demand for food, and climate change has affected food security worldwide. Climate change processes, including increasing the atmospheric carbon dioxide concentration, rising temperature, and fluctuation of precipitation, could directly affect agricultural products. Climate change also causes drought, which indirectly influences agricultural systems as water is the most important for grain yield and its quality. Arid and semi-arid regions are limited in terms of water resources and they are the most fragile regions faced with drought caused by climate change. Khuzestan province is one of the hot and arid regions in Iran which its agricultural crops (especially maize) are very sensitive to climate change. Irrigation schedules and various cultivars can be considered as the adaptation strategies according to the climate change conditions. In agricultural ecosystems, water consumption should be reduced, and grain yield should be increased as much as possible. Optimizing water consumption by improving water use efficiency (WUE) is essential for achieving agricultural sustainability in arid and semi-arid regions. Accordingly, modelling approach has been considered as a time-saving and low-cost way to study the effects of climate change and different treatments. The current study was conducted to investigate the effects of different irrigation management practices on maize grain yield and WUE under climate change conditions in order to optimize water consumption and WUE by using modeling approach.

The current study was carried out in several locations of Khuzestan province, including Dezful, Izeh, Bostan, and Ahwaz. The long-term climatic data of the studied locations were collected from the Iran Meteorological Organization. These data included minimum and maximum temperatures (°C), rainfall (mm), and solar radiation (MJ m-2) from 1980 to 2010. Angstrom equation was used for calculating the radiation based on sunshine hours. The climatic data were modified using WeatherMan software embedded in the DSSAT package. The future climate of Khuzestan province (2040-2070) was predicted by the MIROC5 general circulation model under the RCP4.5 climate scenario and using AgMIP methodology. According to the previous studies, the MIROC5 climatic model showed the highest accuracy in predicting the future climatic data of Khuzestan province. Two adaptation strategies, including cultivar and irrigation regime, were considered to mitigate the negative effects of climate change. The cultivars consisted of SC704 (late-maturity) and SC206 (mid-maturity), which had the highest area under cultivation in Khuzestan province. Irrigation regimes included three levels: 12-time irrigation (as farmers’ common practice), 10–time irrigation, and 14-time irrigation per growing season.

The results of the current study indicated that climate change had negative effects on maize grain yield as well as positive effects on average temperature during the growing season, evapotranspiration, and corn water use efficiency across the whole province. The results showed that the average grain yield and corn WUE in Khuzestan province in 2050 under the RCP4.5 scenario was -2% and -5.7%, respectively, compared to the baseline. In addition, mean temperature during the growing season and evaporation and transpiration increased by +12.6% and + 0.9% compared to the baseline. The results also showed that with the application of an optimal amount of irrigation regime (10-time irrigation), an increase in WUE and decrease in evapotranspiration were observed, which resulted in acceptable grain yield. Results also portrayed that applying the optimal irrigation level (10-time) along with a late maturity cultivar (SC704) showed the best performance in terms of grain yield (9433.9 kgha-1) and WUE (19.57 kgha-1 mm-1) in the province Khuzestan.

The results illustrated that by 2050, the average grain yield and WUE were reduced compared to the baseline period. However, the mean temperature and evapotranspiration over the growing season were increased. Totally, the results of the current study revealed that an optimal irrigation level 10 and suitable cultivar SC704 could mitigate the negative impacts of climate change on maize in the agroecosystems of Khuzestan province.

APSIM model was used to investigate yield and water requirement of maize in different planting dates under two emission scenarios (RCP4.5 and RCP8.5) at the three locations of Kermanshah province (Kermanshah, Kangavar and Eslamabad-Gharb). Climatic parameters were predicted using the AgMIP methodology. Results of this study indicated that in the future, average maize grain yield will be reduced in all locations, scenarios and planting dates (70 percent) compare to the baseline. Reasons for yield loss are increasing temperature over growing season (15.7%), decreasing length of growing season (4.7%) and is likely to concurrency time of flowering with extreme temperature. In addition, maize water requirement, on average, will be increased 14 percent is comparison to the baseline in all locations, scenarios and planting dates mainly due to rising temperature. In conventional planting date (4 May), crop water requirement of maize on average increased 12 percent under two emission scenarios compared with the baseline while on earlier and later planting dates, crop water requirement increased 15 and 7 percent, respectively. Due to the amount of higher cumulative rainfall during the growing season (54.27) on earlier planting dates (4 and 19 April) as well as lower yield loss compare to other planting dates (56 percent), earlier planting dates can be explained as adaptation strategy in order to achieve appropriate yield. The results also showed that among study locations, Eslamabad-Gharb and Kermanshah were the most suitable areas in terms of grain yield (4221.8 Kg.ha-1) and water requirement (1489.2 mm), respectively.

In order to study the competition effects of redroot pigweed (Amaranthus retroflexus) and millet (Panicum miliaceum) on maize performance under different rates of N fertilizer, a field experiment was conducted in 2009 in the research fields of Tarbiat Modares University in Tehran as a randomized complete block design with factorial arrangement of treatments and three replications. Accordingly, three factors included nitrogen fertilizer (75% optimum or 138 kg N ha-1, optimum or 184 kg N ha-1 and 125% optimum or 230 kg N ha-1), weed species (redroot pigweed and millet) and weed densities (5 and 25 plants m-1 for redroot pigweed and 7.5 and 37.5 plants m-1 for millet) consisted. Results showed that the highest grain yield (921.89 g m-2) was achieved in treatment 230 kg N ha-1 while the lowest yields (466.72 g m-2) belonged to treatment millet fertilized with 138 kg N ha-1. High densities of millet and redroot pigweed resulted in significant reductions in number of grains per row and the ear length. Differences in N application rates cause significant variations in biological yield and some of the yield components of maize. Overall, results indicated that in fields where a nitrophile species is the dominant, increasing N application rate beyond the optimum not only does not increase maize grain yield but also reduces its yield and causes pollution of environment.