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Modelling responses of cotton growth and yield to pre-planting soil moisture with the CROPGRO-Cotton model for a mulched drip irrigation system in the Tarim Basin

机译:棉花生长棉花增长的响应及塔里木盆地覆盖滴灌系统的田间棉模型

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Pre-planting soil moisture plays an important role in regulating plant emergence rate and yield, yet there is a paucity of studies on the response of cotton growth and yield to pre-planting soil moisture in arid regions. In this study, the CROPGRO-Cotton model was used to simulate cotton growth and yield in a mulched drip irrigation system, with the interaction of different pre-planting soil water contents and irrigation levels during the cotton growing season. This was undertaken to determine the optimal pre-planting soil water contents and irrigation levels that would produce the highest cotton yield and biomass values in the model simulations. Experimental data of cotton phenology, and the biomass and yield at the maturing stage in 2017 and 2018 was used to calibrate and verify the DSSAT-CROPGRO-Cotton model outputs. Based on the calibrated CROPGRO-Cotton model, scenario simulation was performed using three irrigation levels (24 mm, 30 mm, 36 mm) and eight pre-planting soil water contents [1.2 theta(FC), 1.1 theta(FC), theta(FC) (field water holding capacity), 0.9 theta(FC), 0.8 theta(FC), 0.7 theta(FC,) 0.6 theta(FC), and 0.5 theta(FC)]. The results showed that the simulated cotton phenology and seed cotton yield produced by the calibrated CROPGRO-Cotton model showed good fits with the observed values, thus, satisfying the accuracy requirement for large-scale, mulched, drip irrigated cotton field simulations. However, large deviations were observed between simulated and observed biomass values. According to the simulations, the maximum seed cotton yield and biomass can be obtained from a pre-planting soil water content of 0.8 theta(FC) - theta(FC), and the maintenance of irrigation levels at 30-36 mm during the cotton growing season. These simulation results may serve as reference data for cotton crop production and irrigation management in the Tarim Basin.
机译:预植物土壤水分在调节植物出苗率和产量方面发挥着重要作用,但缺乏关于棉花生长的响应和在干旱地区预种植土壤水分的研究的研究。在这项研究中,农作物棉模型用于模拟棉花滴灌系统中的棉花生长和产量,在棉花生长季节不同预先种植土壤水含量和灌溉水平的相互作用。这是为了确定模拟模拟中的最佳预种植土壤水含量和灌溉水平。 2017年和2018年成熟阶段的棉酚类学实验数据以及生物量和产量,用于校准并验证DSSAT-CROM-COTNOL模型输出。基于校准的作品棉模型,使用三个灌溉水平(24mm,30毫米,36mm)和八个预种植土壤水含量进行情景模拟[1.2θ(fc),1.1θ(fc),θ( Fc)(现场水持量),0.9θ(Fc),0.8θ(Fc),0.7θ(Fc,)0.6θ(Fc)和0.5θ(Fc)]。结果表明,通过校准的作物棉花模型产生的模拟棉酚醛棉酚类棉花产量显示出良好的拟合值,因此,满足大规模,覆盖,滴灌棉田模拟的精度要求。然而,在模拟和观察到的生物质值之间观察到大偏差。根据模拟,可以从种植的土壤含水量为0.8θ(Fc) - θ(Fc)的最大种子棉产率和生物质,并在棉花生长期间维持30-36毫米的灌溉水平季节。这些仿真结果可以作为塔里木盆地棉田生产和灌溉管理的参考数据。

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