Document Type : Research Paper
Authors
1
Ph.D. Candidate, Department of Irrigation and Reclamation Engineering, Faculty of Agriculture, College of Agriculture and Natural Resources, University of Tehran, Tehran, Iran.
2
Department of Irrigation and Drainage, Faculty of Agricultural Technology and Engineering, University of Tehran, Karaj, Iran
3
Associate Professor, Department of Irrigation and Reclamation Engineering, Faculty of Agriculture, College of Agriculture and Natural Resources, University of Tehran, Tehran, Iran.
4
Professor, Department of Irrigation and Reclamation Engineering, Faculty of Agriculture, College of Agriculture and Natural Resources, University of Tehran, Tehran, Iran.
Abstract
Iran is facing a serious water crisis due to limited resources, climate change, and excessive extraction of groundwater, which has increased the importance of optimizing water consumption, especially in the agricultural sector. This study, aiming to improve agricultural water management, investigated an irrigation scheduling method based on canopy temperature (Tc) and Crop Water Stress Index (CWSI) for forage maize (SC704) under surface drip irrigation in Karaj. The experiment was conducted with three irrigation levels (60, 80, and 100 percent of water requirement) and three replications in the summer of 2024, and a handheld infrared thermometer was used to monitor corn leaf temperature. Using the empirical Idso method, upper and lower baselines and the CWSI for different irrigation treatments were determined. The average CWSI in irrigation treatments of 60, 80, and 100 percent of water requirement was calculated as 0.57, 0.48, and 0.29, respectively. Considering the non-stress treatment (full irrigation treatment), specific equations for determining irrigation timing during three different growth stages were respectively presented as (Tc–Ta)c = –0.0679(AVPD) + 3.8121, (Tc–Ta)c = –0.0341(AVPD) + 3.6628, and (Tc–Ta)c = –0.0653(AVPD) + 4.3019, based on air vapor pressure deficit (AVPD) and the temperature difference (Tc–Ta), which enables more precise and climate-adapted irrigation scheduling.
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