Mo Li , Kun Hu , Qiang Fu , Aizheng Yang , Xiaofang Wang , Pingan Zhang , Wenhao Dong , Zhenyi Sun
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引用次数: 0
Abstract
The unique freeze‒thaw cycle in cold regions complicates irrigation. Field monitoring and experiments simulated the water cycle during thawing and growing periods, analyzing hydraulic connections. This led to coupling a hydrological balance model, the Environmental Policy Integrated Climate (EPIC) model, and a carbon emission model into a multi-objective optimization framework for rice irrigation, aiming to enhance production, save water, and reduce emissions. Using Monte Carlo simulation and the Non-dominated Sorting Genetic Algorithm III (NSGA-III), dynamic water distribution plans were developed considering precipitation variability. Modeling the 0–60 cm soil layer as continuous improved soil moisture simulation, resulted in soaking irrigation with 16 %–21.8 % water savings. Optimized irrigation increased maximum yield by 1.6 %–4.7 %, reduced carbon emissions per unit yield by 16.4 %–18.6 %, and saved 7.7 %–9.5 % water compared to conventional methods. Key allocation periods are tillering and jointing-booting initiation, optimizing distributions for 57 %–72 % of the growth period, supporting sustainable water management in cold-region rice paddies.
期刊介绍:
Environmental Modelling & Software publishes contributions, in the form of research articles, reviews and short communications, on recent advances in environmental modelling and/or software. The aim is to improve our capacity to represent, understand, predict or manage the behaviour of environmental systems at all practical scales, and to communicate those improvements to a wide scientific and professional audience.