Vol.30, NO.5, 2019
Turn off MathJax
Article Contents
Article Navigation >  Journal of Applied Meteorological Science  > 2019  >  30(5): 528-542
Ma Yuping, Huo Zhiguo, Wang Peijuan, et al. The construction and application of Chinese agrometeorological model(CAMM1.0). J Appl Meteor Sci, 2019, 30(5): 528-542. DOI:  10.11898/1001-7313.20190502.
Citation: Ma Yuping, Huo Zhiguo, Wang Peijuan, et al. The construction and application of Chinese agrometeorological model(CAMM1.0). J Appl Meteor Sci, 2019, 30(5): 528-542. DOI:  10.11898/1001-7313.20190502.
shu

The Construction and Application of Chinese AgroMeteorological Model(CAMM1.0)

DOI: 10.11898/1001-7313.20190502

  • Chinese Academy of Meteorological Sciences, Beijing 100081

  • Received Date: 2019-05-10
  • Rev Recd Date: 2019-07-24
  • Publish Date: 2019-09-30
    Abstract
  • In order to develop an agrometeorological model suitable for regional agricultural planting in China, China AgroMeteorological Model version 1.0(CAMM1.0) is established by improving and reconstructing the process and innovative application of existing oversea simulation methods.CAMM1.0 makes several improvements in process of agrometeorological model. It improves crop development process model by using average temperature intensity and soil moisture, improves crop leaf photosynthesis, dry matter distribution and leaf area expansion process model by using soil moisture, expands crop evapotranspiration process model by evaporation ratio method, establishes winter wheat plant height model based on development process. Based on the remote sensing information, the crop irrigation model, data assimilation model, crop growth and assessment model are also constructed. Main functions of CAMM1.0 include real-time crop growth simulation and customized user simulation. The former outputs real-time crop growth state variables, environmental variables and growth evaluation day by day. And the latter can produce customized products. CAMM1.0 can simulate the crop development, photosynthesis and plant height very well. However, the simulation is slightly weak on the process of soil moisture change, and the simulated yield is also slightly low. The assessed trend of summer maize in drought decreasing and waterlogging increasing by CAMM1.0 in Huaihe River Basin is consistent with the observation. Improving the key mechanism of crop growth enhances the response of CAMM1.0 to the environment. The construction of characteristic regional model improves its ability to simulate the growth process of Chinese crops, and realizes the regionalization of the model. The customized operation platform via the Internet is convenient for the agrometeorological application.CAMM1.0 constructs an online real-time operation platform to make the application and extension of the model and further development of the core module more convenient. Some of its sub-modules are constructed by multiple methods, which is more convenient for multi-model integration. The plugin method makes it easy for the model applicating, developing and updating. However, the mechanism of CAMM1.0 is still far from perfect, and the next step is to work on the response of agricultural production to climate change and various meteorological disasters. CAMM1.0 is expected to improve the theoretical level of agrometeorological simulation in China and provide technical solutions for related operational services.
    • FullText(HTML)
    References(66)

  • Fig. 1  Mechanisms of Chinese AgroMeteorological Model(CAMM1.0)

    DownLoad: Full-Size Img PowerPoint

    Fig. 2  Changes of dry matter partitioning coefficients of wheat with development stage(DVS)

    DownLoad: Full-Size Img PowerPoint

    Fig. 3  Trends of winter wheat plant height with accumulated heat unit(THU)

    DownLoad: Full-Size Img PowerPoint

    Fig. 4  The relationship of winter wheat plant height difference to average(AHU) and accumulated heat unit(THU)

    DownLoad: Full-Size Img PowerPoint

    Fig. 5  Running platform of Chinese AgroMeteorological Model(CAMM1.0)

    DownLoad: Full-Size Img PowerPoint

    Fig. 6  Relationship between measured and simulated winter wheat developments in China by CAMM1.0 from 2017 to 2018

    DownLoad: Full-Size Img PowerPoint

    Fig. 7  Relationship between measured and simulated photosynthetic rate of summer maize by three-leaf photosynthesis models

    DownLoad: Full-Size Img PowerPoint

    Fig. 8  Relationship between measured and simulated total aboveground dry weight of summer maize in Henan by remote sensing data assimilation model from 2010 to 2011

    DownLoad: Full-Size Img PowerPoint

    Fig. 9  Relationship between measured and simulated winter wheat yield and total dry weight aboveground in China by CAMM1.0 in 2018

    DownLoad: Full-Size Img PowerPoint

    Fig. 10  Evaluation of growth in time trend and spatial distribution of summer maize in North China by CAMM1.0 in 2013

    DownLoad: Full-Size Img PowerPoint

    Fig. 11  Assessment of summer maize drought and flood disasters in Huaihe River Basin by CAMM1.0

    DownLoad: Full-Size Img PowerPoint
  • [1]
    冯秀藻, 陶炳炎.农业气象学.北京:气象出版社, 1991.
    [2]
    王馥棠.农业气象作物产量预报概述.气象科技, 1983, 6(2):36-41. http://www.cnki.com.cn/Article/CJFDTotal-QXKJ198302007.htm
    [3]
    刘树泽.有关农业气象数值模拟和模式的研究.气象科技, 1980, 3(4):14-16. http://www.cnki.com.cn/Article/CJFDTotal-QXKJ198004005.htm
    [4]
    刘树泽.国外农业气象模式的研究与应用.世界农业, 1986(6):31-33. http://www.cnki.com.cn/Article/CJFDTotal-SJNY198606012.htm
    [5]
    冯定原.农业气象模式的应用.世界农业, 1984(11):61-63.
    [6]
    龚绍先.谈谈农业气象模式.甘肃气象, 1985(3):12-16. http://www.cnki.com.cn/Article/CJFDTotal-GSQX198503004.htm
    [7]
    朱履宽.我国在农业气象模式方面的研究概况.中国农业气象, 1993, 14(2):46-50. http://www.cnki.com.cn/Article/CJFDTotal-ZGNY199302014.htm
    [8]
    de Wit C T.Photosynthesis of Leaf Canopies//Agricultural Research Report No.663.Wageningen: PUDOC, 1965: 57.
    [9]
    Duncan W G, Loomis R S, Williams W A, et al.A model for simulating photosynthesis in plant communities.Hilgardia, 1967, 38:181-205. doi:  10.3733/hilg.v38n04p181
    [10]
    van Keulen H.Simulation of Water Use and Herbage Growth in Arid Regions//Simulation Monographs.Wageningen: PUDOC, 1975: 176.
    [11]
    de Wit C T.Simulation of Assimilation, Respiration and Transpiration of Crops//Simulation Monographs.Wageningen: PUDOC, 1978: 141.
    [12]
    de Wit C T, Brouwer R, Penning de Vries F W T.The Simulation of Photosynthetic Systems//Proceedings of the International Biological Program/Plant Production Technical Meeting.Wageningen: PUDOC, 1970: 47-70.
    [13]
    Penning de Vries F W T, Jansen D M, Ten Berge H F M, et al.Simulation of Ecophysiological Processes of Growth in Several Annual Crops//Monographs.Wageningen: PUDOC, 1989: 271.
    [14]
    Penning de Vries F W T, van Laar H H.Simulation of Growth Processes and the Model BACROS//Simulation Monographs. Wageningen: PUDOC, 1982: 114-135.
    [15]
    van Diepen C A, Wolf J, Van Keulen H, et al.WOFOST:A simulation model of crop production.Soil Use Manage, 1989, 5:16-24. doi:  10.1111/j.1475-2743.1989.tb00755.x
    [16]
    Duncan W G, Hesketh J D.Net photosynthetic rates, relative leaf growth rates, and leaf numbers of 22 races of maize grown at eight temperatures.Crop Sci, 1968:670-674. https://www.researchgate.net/publication/250109103_Net_Photosynthetic_Rates_Relative_Leaf_Growth_Rates_and_Leaf_Numbers_of_22_Races_of_Maize_Grown_at_Eight_Temperatures1
    [17]
    高亮之, 金之庆, 黄耀, 等.水稻计算机模拟模型及其应用之一水稻钟模型——水稻发育动态的计算机模型.中国农业气象, 1989, 10(3):3-10. http://www.cnki.com.cn/Article/CJFDTotal-ZGNY198903001.htm
    [18]
    Supit I, Hooyer A A, van Diepen C A.System Description of the WOFOST 6.0, Crop Simulation Model Implemented in CGMS, Vol 1: Theory and Algorithms.EUR Publication 15956, Agricultural Series, 1994.
    [19]
    Keating B A, Carberry P S, Hammer G L, et al.An overview of APSIM, a model designed for farming systems simulation.Eur J Agron, 2003, 18(3/4):267-288. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=17e327e37a013e98660da99db3a371de
    [20]
    Hoogenboom G, Wilkens P W, Tsuji G Y.DSSAT V3 Volume 4.Hawaii: University of Hawaii, 1999: 286.
    [21]
    Kapetanaki G, Rosenzweig C.Impact of climate change on maize yield in Central and Northern Greece:A simulation study with ceres-maize.Mitig Adapt Strat Gl, 1997, 1(3):251-271. doi:  10.1007/BF00517806
    [22]
    Ceglar A, Bogataj L K.Simulation of maize yield in current and changed climatic conditions:Addressing modelling uncertainties and the importance of bias correction in climate model simulations.Eur J Agron, 2012, 37(1):83-95. doi:  10.1016/j.eja.2011.11.005
    [23]
    金之庆, 葛道阔, 郑喜莲, 等.评价全球气候变化对我国玉米生产的可能影响.作物学报, 1996, 22(5):513-524. doi:  10.3321/j.issn:0496-3490.1996.05.001
    [24]
    Yin X, Chasalow S D, Dourleijn C J, et al.Coupling estimated effects of QTLs for physiological traits to a crop growth model:Predicting yield variation among recombinant inbred lines in barley.Heredity, 2000, 85(6):539-549. doi:  10.1046/j.1365-2540.2000.00790.x
    [25]
    王石立, 马玉平.作物生长模拟模型在我国农业气象业务中的应用研究进展及思考.气象, 2008, 34(6):3-10. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=qx200806001
    [26]
    高亮之.农业模型学基础.香港:天马图书有限公司, 2004:1-320.
    [27]
    秦鹏程, 刘敏, 万素琴, 等.不完整气象资料下基于作物模型的产量预报方法.应用气象学报, 2016, 27(4):407-416. http://qikan.camscma.cn/jams/ch/reader/view_abstract.aspx?file_no=20160403&flag=1
    [28]
    侯英雨, 张蕾, 吴门新, 等.国家级现代农业气象业务技术进展.应用气象学报, 2018, 29(6):641-656. http://qikan.camscma.cn/jams/ch/reader/view_abstract.aspx?file_no=20180601&flag=1
    [29]
    马玉平, 王石立, 王馥棠.作物模拟模型在农业气象业务应用中的研究初探.应用气象学报, 2005, 16(3):293-303. doi:  10.3969/j.issn.1001-7313.2005.03.003
    [30]
    郭建平.农业气象灾害监测预测技术研究进展.应用气象学报, 2016, 27(5):620-630. http://qikan.camscma.cn/jams/ch/reader/view_abstract.aspx?file_no=20160510&flag=1
    [31]
    王馥棠.中国气象科学研究院农业气象研究50年进展.应用气象学报, 2006, 17(6):778-785. doi:  10.3969/j.issn.1001-7313.2006.06.015
    [32]
    Yin X, Struik P C.Modelling the crop:From system dynamics to systems biology.J Exp Bot, 2010, 61(8):2171-2183. doi:  10.1093/jxb/erp375
    [33]
    Parent B, Tardieu F.Can current crop models be used in the phenotyping era for predicting the genetic variability of yield of plants subjected to drought or high temperature?J Exp Bot, 2014, 65(21):6179-6189. doi:  10.1093/jxb/eru223
    [34]
    潘学标, 韩湘玲, 石元春.COTGROW:棉花生长发育模拟模型.棉花学报, 1996, 8(4):180-188.
    [35]
    冯利平, 高亮之, 金之庆, 等.小麦发育期动态模拟模型的研究.作物学报, 1997, 23(4):418-424. doi:  10.3321/j.issn:0496-3490.1997.04.005
    [36]
    王恩利, 段向荣, 吴连海, 等.作物生产力估算与评价软件(CPAM)的设计与应用.计算机农业应用, 1991(1):18-23. http://www.cnki.com.cn/Article/CJFDTotal-JSJN199101003.htm
    [37]
    高亮之, 金之庆.RCSODS-水稻栽培计算机模拟优化决策系统.计算机农业应用, 1993(3):14-20. http://www.cnki.com.cn/Article/CJFD1993-JSJN199303002.htm
    [38]
    殷新佑.水稻生长日历模拟模型及其应用的研究——Ⅰ."源活性"子模型——水稻干物质生产、消耗、分配与积累的模拟.江西农业大学学报, 1991, 13(2):107-112. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=QK000001846127
    [39]
    吴玮, 马玉平, 俄有浩, 等.GECROS模型在黄淮海地区模拟夏玉米生长的适应性评价.作物学报, 2015, 41(1):123-135. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=zuowxb201501014
    [40]
    孙琳丽, 景元书, 马玉平, 等.基于Downhill-Simplex算法的观测数据与作物生长模型同化方法研究.中国农业气象, 2012, 33(4):555-566. doi:  10.3969/j.issn.1000-6362.2012.04.013
    [41]
    马玉平, 王石立, 张黎, 等.基于遥感信息的华北冬小麦区域生长模型及模拟研究.气象学报, 2005, 63(2):204-215. doi:  10.3321/j.issn:0577-6619.2005.02.007
    [42]
    帅细强, 王石立, 马玉平, 等.基于水稻生长模型的气象影响评价和产量动态预测.应用气象学报, 2008, 19(1):71-81. doi:  10.3969/j.issn.1001-7313.2008.01.010
    [43]
    Brown D M, Chapman L J.Soybean Ecology.Ⅱ.Development-temperature-moisture relationships from field studies.Agron J, 1960, 52(9):496-499. doi:  10.2134/agronj1960.00021962005200090002x
    [44]
    马玉平, 王石立, 李维京.基于作物生长模型的玉米生殖期冷害致灾因子研究.作物学报, 2011, 37(9):1642-1649. doi:  10.3969/j.issn.1000-2561.2011.09.010
    [45]
    Matthews R B, Hunt L A.GUMCAS:A model describing the growth of cassava (Manihot esculenta L. Crantz).Field Crop Res, 1994, 36(1):69-84. doi:  10.1016/0378-4290(94)90054-X
    [46]
    马玉平, 张黎, 孙琳丽, 等.持续性温强和土壤水分对玉米发育进程的影响及其模拟.中国农学通报, 2015, 3(3):186-193. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=zgnxtb201503031
    [47]
    van Diepen C A, Rappoldt C, Wolf J, et al.Crop Growth Simulation Model WOFOST.Wageningen: Centre for World Food Study, 1988: 299.
    [48]
    Thornley J H M.Mathematical Models in Plant Physiology.1976.
    [49]
    马玉平, 孙琳丽, 马晓群.黄淮海地区夏玉米对干旱和涝渍的生理生态反应.干旱地区农业研究, 2016, 34(4):85-93. http://d.old.wanfangdata.com.cn/Periodical/ghdqnyyj201604013
    [50]
    Farquhar G D, von Caemmerer S, Berry J A.A biochemical model of photosynthetic CO2 assimilation in leaves of C 3 species.Planta, 1980, 149(1):78-90. doi:  10.1007/BF00386231
    [51]
    Farquhar G D.On the nature of carbon isotope discrimination in C4 species.Australian Journal of Plant Physiology, 1983, 10:205-226.
    [52]
    Collatz G J, Ribas Carbo M, Berry J.A Coupled photosynthesis stomatal conductance model for leaves of C4 plants.Australian Journal of Plant Physiology, 1992, 19:519-538. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=6cdea827d77c20d2fff7d8cf59e18b82
    [53]
    Goudriaan J.A simple and fast numerical method for the computation of daily totals of crop photosynthesis.Agric For Meteorol, 1986, 38(1):249-254. https://www.researchgate.net/publication/201997481_On_the_Nature_of_Carbon_Isotope_Discrimination_in_C_4_Species
    [54]
    Yin X Y, Laar H H V.Crop Systems Dynamics: An Ecophysiological Simulation Model for Genotype-by-environment Interactions.Wageningen: PUDOC, 2005: 1-45.
    [55]
    Suyker A E, Verma S B.Interannual water vapor and energy exchange in an irrigated maize-based agroecosystem.Agric For Meteorol, 2008, 148(3):417-427. doi:  10.1016/j.agrformet.2007.10.005
    [56]
    Kustas W P, Norman J M.Evaluation of soil and vegetation heat flux predictions using a simple two-source model with radiometric temperatures for partial canopy cover.Agric For Meteorol, 1999, 94(1):13-29. doi:  10.1016/S0168-1923(99)00005-2
    [57]
    Norman J M, Kustas W P, Humes K S.Source approach for estimating soil and vegetation energy fluxes in observations of directional radiometric surface temperature.Agric For Meteorol, 1995, 77(3):263-293. https://www.sciencedirect.com/science/article/pii/016819239502265Y
    [58]
    Richard A G, Pereira S L, Raes D, et al.Crop evapotranspiration-Guidelines for computing crop water requirements.FAO Irrigation and Drainage Paper, 1998, 56:300. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=39b4e4c88f284fc748b237b847e48ba6
    [59]
    Yann C, Thomas A.Improving Spatial Resolution of ET Seasonal for Irrigated Rice in Zhanghe, China.22nd Asian Conference on Remote Sensing, 2001.
    [60]
    Xia W, Wang P, Huo Z, et al.Crop drought identification index for winter wheat based on evapotranspiration in the Huang-Huai-Hai Plain, China.Agr Ecosyst Environ, 2018, 263:18-30. doi:  10.1016/j.agee.2018.05.001
    [61]
    季劲钧, 胡玉春.一个植物冠层物理传输和生理生长过程的多层模式.气候与环境研究, 1999, 4(2):25-37. http://www.cnki.com.cn/Article/CJFDTotal-QHYH902.002.htm
    [62]
    黄玫.中国陆地生态系统水、热通量和碳循环模拟研究.北京: 中国科学院地理科学与资源研究所, 2005.
    [63]
    刘布春, 王石立, 庄立伟, 等.基于东北玉米区域动力模型的低温冷害预报应用研究.应用气象学报, 2003, 14(5):616-625. doi:  10.3969/j.issn.1001-7313.2003.05.012
    [64]
    马玉平, 王石立, 李维京.基于作物生长模型的东北玉米冷害监测预测.作物学报, 2011, 37(10):1868-1878. doi:  10.3969/j.issn.1000-2561.2011.10.016
    [65]
    孙琳丽, 马玉平, 景元书, 等.基于约束性分析的数据与作物模型同化方法.应用气象学报, 2013, 24(3):287-296. doi:  10.3969/j.issn.1001-7313.2013.03.004
    [66]
    Wu D, Wang P, Jiang C, et al.Measured phenology response of unchanged crop varieties to long-term historical climate change.Int J Plant Prod, 2018, DOI: 10.1007/s42106-018-0033-z.
    • Relative Articles
    • Supplements(0)
    • Cited By
  • 加载中
  • -->

Catalog

    Figures(11)

    Get Citation
    PDF
    XML
    Article views (6440) PDF downloads(107) Cited by()
    • Received : 2019-05-10
    • Accepted : 2019-07-24
    • Published : 2019-09-30
    Journal Online
    Contact

    © 2020 Journal of Applied Meteorological Science   京ICP备15006967号-1

    Supported by Beijing Renhe Information Technology Co. Ltd

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return