Document Type : Original Article
Authors
1
Department of Water Engineering, Faculty of Agricultural Engineering, Sari Agricultural Sciences and Natural Resources University, Sari, Iran
2
Associate Professor. Department of Water Engineering. Sari Agricultural Sciences and Natural Resources University
3
Assistant Professor in Agrometeorology, Water Engineering Department, Sari Agricultural Sciences and Natural Resources University, Sari, Iran.
4
Professor at Department of Agricultural Engineering, Golestan Agricultural and Natural Resources Research and Education Center, Gorgan, Iran
Abstract
Given the extensive cultivation of maize in Iran, any initiative aimed at increasing water use efficiency contributes to reducing water consumption and enhancing food security in the country. One of the most influential factors affecting the growth and performance of crops is the impact of climate change. The present study aims to assess the impact of climate change and altering planting dates on the water productivity of maize in Gorgan County. Additionally, water productivity of maize under different irrigation treatments and planting dates is simulated using the WOFOST model for future conditions. The irrigation treatments include 100% (T1), 75% (T2), and 50% (T3) of the plant's water requirements. Hence, statistical SDSM and HadCM3 General Circulation Model were employed to downscale all scenarios of the fifth report for two thirty-year periods, 2020-2050 and 2050-2080. The results showed with increasing of irrigation water stress, the simulation error of irrigation water productivity increased, but no consistent trend was observed. In the period of 2050-2020, the highest irrigation water productivity was predicted in treatment T3 on 23 June, amounting to 4 kilograms per cubic meter, which represents a 1.9% reduction compared to the baseline period. During this period, the lowest irrigation water productivity was projected in treatment T1 on 2 June, amounting to 2.7 kilograms per cubic meter, indicating a 57.3% reduction compared to the baseline. Based on the simulated results, the optimal planting time for corn in Gorgan is on 23 June. With appropriate validation of the planting date, effective management can be implemented to adapt to the negative effects of climate change on corn water productivity. Choosing the best planting time, along with proper management, is an efficient solution in Gorgan to prevent reduced performance due to an inappropriate choice of planting date.
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