刘瑞, 张亚红, 葛永琪, 胡伟, 蔡伟. 基于水氮因子的宁夏引黄灌区紫花苜蓿生长模拟模型[J]. 农业工程学报, 2019, 35(13): 102-112. DOI: 10.11975/j.issn.1002-6819.2019.13.011
    引用本文: 刘瑞, 张亚红, 葛永琪, 胡伟, 蔡伟. 基于水氮因子的宁夏引黄灌区紫花苜蓿生长模拟模型[J]. 农业工程学报, 2019, 35(13): 102-112. DOI: 10.11975/j.issn.1002-6819.2019.13.011
    Liu Rui, Zhang Yahong, Ge Yongqi, Hu Wei, Cai Wei. Alfalfa growth simulation model based on water and nitrogen factors in Ningxia irrigation area of Yellow River[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2019, 35(13): 102-112. DOI: 10.11975/j.issn.1002-6819.2019.13.011
    Citation: Liu Rui, Zhang Yahong, Ge Yongqi, Hu Wei, Cai Wei. Alfalfa growth simulation model based on water and nitrogen factors in Ningxia irrigation area of Yellow River[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2019, 35(13): 102-112. DOI: 10.11975/j.issn.1002-6819.2019.13.011

    基于水氮因子的宁夏引黄灌区紫花苜蓿生长模拟模型

    Alfalfa growth simulation model based on water and nitrogen factors in Ningxia irrigation area of Yellow River

    • 摘要: 针对苜蓿生长模型ALFAMOD在动态水分平衡模拟和氮素平衡模拟方面的不足,提出一种基于水氮因子的紫花苜蓿生长模拟模型(alfalfa growth simulation model based on water and nitrogen factors,ALFSIM-WN)。该模型以宁夏引黄灌区紫花苜蓿为研究对象,采用模块化设计方法,划分为作物动态模拟子模型、水分平衡模拟子模型和氮素平衡模拟子模型,对紫花苜蓿的产量进行模拟和估算。通过连续2 a(2016-2017)的田间试验,获取气象数据、土壤数据和田间管理数据,利用2016年数据确定了模型参数,并预测了2017年4茬次紫花苜蓿生长期、叶面积指数、土壤水分动态和产量,对模型模拟值和实际观测值进行了对比。结果表明:宁夏引黄灌区紫花苜蓿每年能收割3~4茬,与当地以饲草收割为目的的生长期相符,综合2017年4茬次数据发现模型模拟叶面积指数的平均相对误差在2.3%~17.6%,模拟土壤水分动态的平均相对误差在2.3%~17.6%,产量预测数据的平均相对误差在1.7%~16.2%。叶面积指数、土壤水分动态和产量的均方根误差分别在0.09~0.44、0.009~0.039 cm3/cm3和0.3~2.3 t/hm2。模型模拟精准度较高,说明该模型在宁夏引黄灌区适用性良好,可以作为一个有效的紫花苜蓿生长模拟预测工具在饲草种植中应用。

       

      Abstract: Abstract: Alfalfa plays an important role in dairy farms for economic and ecological reasons in northwest China. In order to manage the complex relations between alfalfa growth and environmental issues accurately and timely, the alfalfa simulation model has been widely studied. An alfalfa growth simulation model based on water and nitrogen factors (ALFSIM-WN) was proposed. The model was divided into 3 sub-models, including crop dynamic sub-model, water balance sub-model and nitrogen balance sub-model using modular design method. It took alfalfa in Ningxia irrigation area of Yellow River as research object and could simulate the growth dynamics of alfalfa under different water supply and variable fertilization. It also could estimate the yield of alfalfa. In order to verify the accuracy and applicability of ALFSIM-WN, experiments were carried out at grassland experiment area of Maosheng Grass Limited Company in Yinchuan (northwest China, N, E). The experimental alfalfa was Medicago sativa No.7. The irrigation methods included surface irrigation and subsurface drip irrigation. A split plot was designed as 2 experimental treatments. The 1st treatment was the irrigation amount which was divided into 5 irrigation levels including the surface irrigation (1 199 mm) and the subsurface drip irrigation (525, 600, 675, 750 mm). The 2nd treatment was nitrogen application rate which included 4 nitrogen application levels (0, 60, 120, 180 kg/hm2). A total of 17 treatments were designed in experiment. Different irrigation levels were carried out in batches according to different cuts and different growth period of alfalfa. Different nitrogen application levels were carried out in different cuts. Through 2 years experiments (2016-2017), model parameters had been determined using data from 2016, and growth parameters of alfalfa (such as growth period, leaf area index, soil moisture dynamics and yield) had been predicted based on gathering meteorological date, soil data and field management data of 2017. The comparison between simulated and observed was taken in this paper. The results showed that the simulated values by the model was in agreement with the trend of the observed values under different irrigation and nitrogen treatments, such as growth period, leaf area index, soil water content and yield of the alfalfa. Alfalfa in Ningxia irrigation area of Yellow River could harvest 3 to 4 times per year, the mean relative error of the growth period of alfalfa in 4 cuts simulated by the model was between 1.9% and 5.7%, which was consistent with the local growth period for forage. In addition, through analyzing the 4 cuts data in 2017, the mean relative error of leaf area index simulated by the model was between 2.3% and 17.6%, the mean relative error of soil water content simulated by the model was between 2.3% and 17.6%, and the mean relative error of yield simulated by the model was between 1.7% and 16.2%. The root mean square error of the leaf area index was between 0.09 and 0.44, the root mean square error of soil water content is between 0.009 and 0.039 cm3/cm3, and the root mean square error of yield was between 0.3 and 2.3 t/hm2. Therefore, the ALFSIM-WN had higher simulation accuracy in simulated growth period, leaf area index, soil water content and yield, indicating that the model has good application in Ningxia irrigation area of Yellow River and can be used as an effective simulation tool for alfalfa growth in forage planting.

       

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