نوع مقاله : مقاله پژوهشی
نویسندگان
1 دانشآموخته دکتری، گروه علوم و مهندسی آب، دانشکده آب و خاک، دانشگاه علوم کشاورزی و منابع طبیعی گرگان، گرگان، ایران
2 دانشیار، گروه علوم و مهندسی آب، دانشکده آب و خاک، دانشگاه علوم کشاورزی و منابع طبیعی گرگان، گرگان، ایران
3 استادیار پژوهش، موسسه تحقیقات برنج کشور، سازمان تحقیقات، آموزش و ترویج کشاورزی، رشت، ایران
4 استاد، گروه مهندسی آب، واحد لاهیجان، دانشگاه آزاد اسلامی، لاهیجان، ایران
چکیده
کلیدواژهها
موضوعات
عنوان مقاله [English]
نویسندگان [English]
Introduction:
The projected 60% increase in global food demand by 2050, along with growing limitations on water and nitrogen resources, highlights the urgent need to optimize input use in strategic crops such as rice. As a major irrigated cereal with high water requirements, rice production faces rising challenges related to water scarcity, low nitrogen use efficiency, and environmental concerns stemming from excessive fertilizer application. Effective irrigation and fertilization management—especially through distinguishing between green water (soil moisture from rainfall) and blue water (surface and groundwater withdrawals)—is essential for improving resource use efficiency. Process-based models like ORYZA2000 provide powerful tools for analyzing these management strategies. As a validated model widely used for rice systems, ORYZA2000 supports the evaluation of scenarios aimed at increasing productivity while reducing dependence on limited water resources under changing climatic conditions.
Research Methodology:
This study was conducted over two consecutive growing seasons at the experimental farm of the National Rice Research Institute in Rasht, Iran. A split-plot arrangement within a randomized complete block design with three replications was used, with 16 treatment combinations. Irrigation treatments included continuous flooding and irrigation 1, 3, and 5 days after surface water disappearance, while nitrogen levels consisted of 0, 60, 90, and 120 kg ha⁻¹. The hybrid cultivar ‘Bahar,’ known for its high yield potential and adaptability to Gilan’s climate, was grown. Field measurements of grain yield, biomass, leaf area index, and nitrogen uptake were used to calibrate and validate the ORYZA2000 model. Outputs from water balance simulations were then used to estimate green and blue water productivity indices and major water balance components.
Findings:
The highest grain yield (7.2 t ha⁻¹) occurred under irrigation 3 days after water disappearance combined with 120 kg N ha⁻¹. The ORYZA2000 model showed strong performance in simulating grain yield (NRMSE = 7–12%), biomass (NRMSE = 6–12%), total nitrogen (NRMSE = 8–15%), grain nitrogen (NRMSE = 9–10%), and leaf area index (NRMSE = 14–29%). For all variables except leaf area index, the model efficiency (EF) exceeded 0.65, and coefficients of determination (R² > 0.70) indicated a good match between simulated and observed data.
Across two years, the highest simulated water productivity indices were also obtained from the I3N4 treatment (irrigation 3 days after water disappearance + 120 kg N), including irrigation water productivity (WPI = 1.32), irrigation plus rainfall productivity (WPI+R = 0.84), transpiration productivity (WPT = 2.0), evapotranspiration productivity (WPET = 1.12), and evapotranspiration plus percolation productivity (WPETQ = 0.89). Separation of indices into green and blue components showed that this treatment provided the highest values for most blue and green water productivity indices. However, green water productivity (WPg) and green water transpiration productivity (WPTg) were highest under I4N4 (irrigation 5 days after water disappearance + 120 kg N) and I1N4 (continuous flooding + 120 kg N), respectively.
Conclusion:
Combined irrigation and nitrogen management plays a crucial role in enhancing rice yield and water productivity. The ORYZA2000 model demonstrated strong accuracy in simulating management scenarios and water balance components, making it a valuable decision-support tool for water and fertilizer management in rice systems. Incorporating the distinction between green and blue water further supports strategies to reduce irrigation demand and increase overall productivity under water-limited conditions. The model identified the most efficient irrigation-nitrogen combination for maximizing both blue and green water productivity. This is particularly important where irrigation water is dominant; for example, alternate wetting and drying with a three-day interval plus 120 kg N ha⁻¹ was the most effective treatment. These findings can guide resource optimization strategies at both farm and policy levels under varying levels of dependence on water sources
کلیدواژهها [English]
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