Guo Jianping, Luan Qing, Wang Jingxuan, et al. Model construction of rainfall interception by maize canopy. J Appl Meteor Sci, 2020, 31(4): 397-404. DOI:  10.11898/1001-7313.20200402.
Citation: Guo Jianping, Luan Qing, Wang Jingxuan, et al. Model construction of rainfall interception by maize canopy. J Appl Meteor Sci, 2020, 31(4): 397-404. DOI:  10.11898/1001-7313.20200402.

Model Construction of Rainfall Interception by Maize Canopy

DOI: 10.11898/1001-7313.20200402
  • Received Date: 2020-03-19
  • Rev Recd Date: 2020-04-30
  • Publish Date: 2020-07-31
  • Rainfall is the main water source of crops. Crops maintain their normal growth and development by absorbing water from the soil. However, the role of rainfall is often overestimated in water resource evaluation and farmland water balance research because the rainfall interception effect of crop canopy is not considered. It is difficult to calculate crop interception quantitatively, which seriously restricts the impact assessment of rainfall on crops. Therefore, in order to determine the interception effect in different growth stages of maize under different rainfall, the rainfall interception experiment of maize is carried out at Jinzhou Agricultural Meteorological Experimental Station of Liaoning Province in 2018. A total of 10 rainfall levels (rainfall over 20 mm is designed for the measurement of saturated interception) and 8 leaf area indexes (representing 8 different growth periods) are examined in the experiment. The rainfall interception effect of maize canopy is systematically analyzed by simulation. Results show that under certain rainfall, the relationship between the interception of maize canopy and leaf area index conforms to the relationship of quadratic polynomial, exponential function and power function, among which the quadratic polynomial has the highest explanation rate. Under the assumption of fixed leaf area index, the rainfall interception of maize canopy is in accordance with the quadratic polynomial, exponential function, power function and logarithmic function. When leaf area index is above 3, the explanation rate of power function is the highest, and the relationship between saturated interception of maize and leaf area index is in accordance with the quadratic polynomial, exponential function and power function, among which the explanation rate of quadratic polynomial is the highest. The comprehensive leaf area index and rainfall analysis indicate a positive correlation between canopy interception and the square of leaf area index and the logarithm of rainfall. According to the traditional planting mode of maize in China, the maximum leaf area index of high-yield maize is generally about 5-6. Therefore, the maximum interception of a rainfall process is usually 1.5-2.3 mm. When leaf area index is less than 1, the rainfall interception of maize can be ignored. Results are of practical significance for the evaluation of the effectiveness of rainfall resources and the study of farmland water balance.
  • Fig. 1  The relationship between saturated interception and leaf area index

    Fig. 2  The relationship between interception and leaf area index under different rainfall levels

    Table  1  The fitting model for saturated interception and leaf area index

    类型 拟合模型 决定系数 样本量
    二次多项式模型 y=0.0744x2-0.0701x+0.0416 0.9609** 8
    指数函数模型 y=0.0188e1.1107x 0.9531** 8
    幂函数模型 y=0.1134x1.0511 0.9463** 8
    注:y表示饱和截留量,单位:mm;x表示叶面积指数。**表示拟合模型达到0.01显著性水平。
    DownLoad: Download CSV

    Table  2  The fitting model for interception and leaf area index

    降水量/mm 拟合模型 样本量 决定系数
    y=0.0038x2+0.027x+0.0064 8 0.9794**
    0.3 y=0.0119e0.7383x 8 0.8983**
    y=0.0475x0.7716 8 0.9699**
    y=0.0045x2+0.0407x+0.004 8 0.9934**
    0.7 y=0.0125e0.7393x 8 0.7900**
    y=0.0555x1.0226 8 0.9481**
    y=0.0197x2+0.0144x+0.0096 8 0.9809**
    1.2 y=0.0147e0.895x 8 0.9286**
    y=0.0637x1.0568 8 0.9479**
    y=0.0455x2-0.0631x+0.0324 8 0.9534**
    2.1 y=0.0162e0.8868x 8 0.9486**
    y=0.0911x0.8753 8 0.9384**
    y=0.0147x2+0.0436x+0.0072 8 0.966**
    2.7 y=0.0203e0.7453x 8 0.7447**
    y=0.0771x1.1306 8 0.9357**
    y=0.0306x2+0.0003x+0.0207 8 0.9648**
    3.0 y=0.0166e0.9196x 8 0.9148**
    y=0.1017x0.8736 8 0.9636**
    y=0.0322x2+0.0391x+0.0097 8 0.9921**
    7.8 y=0.0272e0.7986x 8 0.8618**
    y=0.119x1.0613 8 0.9450**
    注:y表示截留量,单位:mm;x表示叶面积指数。**表示拟合模型达到0.01显著性水平。
    DownLoad: Download CSV

    Table  3  The fitting model for interception and rainfall

    叶面积指数 拟合模型 样本量 决定系数
    1 y=0.0005x2+0.0017x+0.0389 7 0.4967
    y=0.0338e0.1046x 7 0.2349
    y=0.0405x0.1716 7 0.1124
    y=0.0107lnx+0.0436 7 0.2944
    2 y=-0.0007x2+0.0235x+0.077 7 0.8623**
    y=0.0887e0.1229x 7 0.7496*
    y=0.1047x0.2927 7 0.7567**
    y=0.0387lnx+0.1089 7 0.7403*
    3 y=-0.0046x2+0.0744x+0.1168 7 0.9738**
    y=0.1657e0.1371x 7 0.7489*
    y=0.1948x0.373 7 0.9864**
    y=0.0873lnx+0.207 7 0.9557**
    4 y=-0.0113x2+0.1553x+0.1542 7 0.9196**
    y=0.2595e0.1495x 7 0.6399*
    y=0.306x0.4298 7 0.9405**
    y=0.157lnx+0.3355 7 0.9345**
    5 y=-0.0206x2+0.2635x+0.201 7 0.836**
    y=0.3764e0.157x 7 0.554
    y=0.4436x0.4685 7 0.8779**
    y=0.2458lnx+0.5018 7 0.8668**
    注:y表示截留量,单位:mm;x表示降水量,单位:mm。*和**分别表示拟合模型达到0.05和0.01显著性水平。
    DownLoad: Download CSV

    Table  4  Interception rate of different leaf areas under some rainfall levels(unit:%)

    叶面积指数 降水量
    2 mm 5 mm 10 mm 20 mm
    1 2.7 1.8 1.3 0.8
    2 6.4 3.4 2.0 1.2
    3 12.7 5.7 3.3 1.8
    4 21.4 9.4 5.0 2.7
    5 32.7 13.9 7.3 3.8
    6 46.4 19.4 10.0 5.2
    DownLoad: Download CSV

    Table  5  Independent sample verification of fitting model

    降水量/mm 叶面积指数 截留量
    实测/mm 模拟/mm 误差/%
    1.4 0.0378 0.0051 0.0128 151.0
    0.1647 0.0140 0.0135 -3.6
    0.2647 0.0260 0.0146 -43.8
    0.7221 0.0307 0.0258 -16.0
    1.6381 0.0674 0.0799 18.5
    1.6928 0.0847 0.0844 -0.3
    2.5363 0.1883 0.1736 -7.8
    4.1837 0.5383 0.4504 -16.3
    2.0 0.1349 0.0113 0.0290 156.6
    0.1586 0.0133 0.0291 118.8
    0.8439 0.0420 0.0463 10.2
    1.3391 0.0567 0.0733 29.3
    1.9770 0.1107 0.1262 14.0
    2.1979 0.1427 0.1493 4.5
    2.6974 0.2701 0.2104 -22.1
    3.1516 0.3449 0.2768 -19.7
    DownLoad: Download CSV
  • [1]
    杨国庆, 王佳真, 孙萌萌.基于标准化降水指数的沧州干旱时空特征.干旱气象, 2019, 37(2):218-225. http://d.old.wanfangdata.com.cn/Periodical/ghqx201902004
    [2]
    慕臣英, 梁红, 纪瑞鹏, 等.沈阳春玉米不同生育阶段需水量及缺水量变化特征.干旱气象, 2019, 37(1):127-133. http://d.old.wanfangdata.com.cn/Periodical/ghqx201901014
    [3]
    谢五三, 王胜, 唐为安, 等.干旱指数在淮河流域的适用性对比.应用气象学报, 2014, 25(2):176-184. http://qikan.camscma.cn/jamsweb/article/id/20140207
    [4]
    程雪, 孙爽, 张方亮, 等.我国北方地区苹果干旱时空分布特征.应用气象学报, 2020, 31(1):63-73. doi:  10.11898/1001-7313.20200106
    [5]
    王石立, 娄秀荣, 沙奕卓.华北地区小麦水分亏缺状况初探.应用气象学报, 1995, 6(增刊I):42-48. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=QK199500597183
    [6]
    宋丽莉, 王春林, 董永春.水稻干旱动态模拟及干旱损失评估.应用气象学报, 2001, 12(2):226-233. http://qikan.camscma.cn/jamsweb/article/id/20010230
    [7]
    宋艳玲, 蔡雯悦, 柳艳菊, 等.我国西南地区干旱变化及对贵州水稻产量影响.应用气象学报, 2014, 25(5):550-558. http://qikan.camscma.cn/jamsweb/article/id/20140504
    [8]
    杨宏毅, 霍治国, 杨建莹, 等.江汉和江南西部春玉米涝溃指标及风险评估.应用气象学报, 2017, 28(2):237-246. doi:  10.11898/1001-7313.20170211
    [9]
    宋艳玲, 王建林, 田靳峰, 等.气象干旱指数在东北春玉米干旱监测中的改进.应用气象学报, 2019, 30(1):25-34. doi:  10.11898/1001-7313.20190103
    [10]
    王永利, 侯琼, 苗百岭, 等.内蒙古马铃薯干旱风险区划.应用气象学报, 2017, 28(4):504-512. doi:  10.11898/1001-7313.20170411
    [11]
    初征, 郭建平.未来气候变化对东北玉米品种布局的影响.应用气象学报, 2018, 29(2):165-176. doi:  10.11898/1001-7313.20180204
    [12]
    任玉玉, 千怀遂.河南省棉花气候适宜度变化趋势分析.应用气象学报, 2006, 17(1):87-93. http://qikan.camscma.cn/jamsweb/article/id/20060115
    [13]
    魏瑞江, 宋迎波, 王鑫.基于气候适宜度的玉米产量动态预报方法.应用气象学报, 2009, 20(5):622-627. http://qikan.camscma.cn/jamsweb/article/id/20090514
    [14]
    帅细强, 陆魁东, 黄晚华.不同方法在湖南省早稻产量动态预报中的比较.应用气象学报, 2015, 26(1):103-111. doi:  10.11898/1001-7313.20150111
    [15]
    周秋文, 颜红, 马龙生, 等.喀斯特地区典型针叶林的降雨截留分配效应.生态科学, 2016, 35(6):140-145. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=stkx201606019
    [16]
    周秋文, 马龙生, 颜红, 等.贵州省喀斯特阔叶林降雨截留分配特征.水土保持通报, 2016, 36(6):321-325. http://d.old.wanfangdata.com.cn/Periodical/stbctb201606056
    [17]
    周秋文, 朱红.基于Horton模型的涟江流域马尾松林冠截留模拟.生态科学, 2018, 37(2):43-49. http://d.old.wanfangdata.com.cn/Periodical/stkx201802006
    [18]
    马剑, 刘贤德, 金铭, 等.祁连山西水林区灌木林降雨截留特征.水土保持研究, 2017, 24(3):363-368. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=stbcyj201703062
    [19]
    白云, 苏德, 李新通, 等.井冈山国家级自然保护区林冠降雨截留模拟研究.长江流域资源与环境, 2015, 24(增刊I):70-77.
    [20]
    董玲玲, 康峰峰, 韩海荣, 等.辽河源3种林分降雨再分配特征及其影响因素.水土保持学报, 2018, 32(4):145-150. http://d.old.wanfangdata.com.cn/Periodical/trqsystbcxb201804023
    [21]
    刘春霞, 王玉杰, 王云琦.西南亚热带天然混交林林冠截留效应.东北林业大学学报, 2013, 41(7):9-14. http://d.old.wanfangdata.com.cn/Periodical/dblydxxb201307003
    [22]
    杨文强, 王艳萍, 张青峰.黄土高塬沟壑区苹果林冠截留特征.水土保持通报, 2013, 33(2):93-96. http://d.old.wanfangdata.com.cn/Periodical/stbctb201302020
    [23]
    Rutter A J, Kershaw K A, Robins P C, et al.A predictive model of rainfall interception in forests.1.Derivation of the model from observations in a plantation of Corsican pine.Agricultural Meteorology, 1972, 9:367-384. http://cn.bing.com/academic/profile?id=3d54473e5bb2b6e422d437d01716fbb3&encoded=0&v=paper_preview&mkt=zh-cn
    [24]
    Gash J H C.An analytical model of rainfall interception by forests.Quart J Roy Meteor Soc, 1979, 105(443):43-55. http://cn.bing.com/academic/profile?id=5dbd52ff3d8e84621333cafa38627d0f&encoded=0&v=paper_preview&mkt=zh-cn
    [25]
    刘战东, 刘祖贵, 张寄阳, 等.夏玉米降雨冠层截留过程及其模拟.灌溉排水学报, 2015, 34(7):13-17. http://d.old.wanfangdata.com.cn/Periodical/ggps201507003
    [26]
    马波, 李占斌, 马璠, 等.模拟降雨条件下玉米植株对降雨再分配过程的影响.生态学报, 2015, 35(2):497-507. http://d.old.wanfangdata.com.cn/Periodical/stxb201502031
    [27]
    马波, 马璠, 李占斌, 等.模拟降雨条件下作物植株对降雨再分配过程的影响.农业工程学报, 2014, 30(16):136-146. http://d.old.wanfangdata.com.cn/Periodical/nygcxb201416019
    [28]
    韩雪, 王力, 王艳萍.自然降雨条件下夏玉米冠层截留特征及影响因素.中国农业科学, 2014, 47(8):1541-1549. http://d.old.wanfangdata.com.cn/Periodical/zgnykx201408010
    [29]
    Van Dijk A I J, Bruijnzeel A L.Modelling rainfall interception by vegetation of variable density using an analytical model.Part 2.Model validation for a tropical upland mixed cropping system.J Hydrology, 2001, 247(3):239-262. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=15e44cd0e0911f6527eeaaec06e79895
    [30]
    Lamm R F, Manges L H.Portioning of sprinlier irrigation water by a corn canopy.Transactions of the ASABE, 2000, 43(3):909-918.
    [31]
    Steiner L J, Kanemansu T E, Clark N R.Spray losses and partitioning of water under a center pivot sprinkler system.Transactions of the ASABE, 1983, 26(4):1128-1134. http://cn.bing.com/academic/profile?id=a8adf55d14f35828a6c2fab8f482d0c4&encoded=0&v=paper_preview&mkt=zh-cn
    [32]
    王迪, 李久生, 饶敏杰.喷灌冬小麦冠层截留试验研究.中国农业科学, 2006, 39(9):1859-1864. http://d.old.wanfangdata.com.cn/Periodical/zgnykx200609019
    [33]
    郝芝建, 范兴科, 吴普特, 等.喷灌条件下夏玉米冠层对水量截留试验研究.灌溉排水学报, 2008, 27(1):25-27. http://d.old.wanfangdata.com.cn/Periodical/ggps200801007
    [34]
    Haynes L J.Ground rainfall under vegetative canopy of crops.Journal of the American Society of Agronomy, 1940, 32(3):176-184. http://cn.bing.com/academic/profile?id=cd30977e540028bd881a1e50f68edfbc&encoded=0&v=paper_preview&mkt=zh-cn
    [35]
    刘海军, 康跃虎, 王庆改.作物冠层对喷灌水分分布影响的研究进展.干旱地区农业研究, 2007, 25(2):137-142. http://d.old.wanfangdata.com.cn/Periodical/ghdqnyyj200702029
    [36]
    Seginer I.Net losses in sprinkler irrigation.Agricultural Meteorology, 1967, 4:281-291. http://cn.bing.com/academic/profile?id=a38138ea6fbb1565b6116dfd19f93e96&encoded=0&v=paper_preview&mkt=zh-cn
  • 加载中
  • -->

Catalog

    Figures(2)  / Tables(5)

    Article views (2966) PDF downloads(66) Cited by()
    • Received : 2020-03-19
    • Accepted : 2020-04-30
    • Published : 2020-07-31

    /

    DownLoad:  Full-Size Img  PowerPoint