Simulating Grain Yield and Water Use Efficiency in Dominant Maize Cultivars under Water Limited a Climate Change Conditions

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.