基于锦州春玉米田间试验的WOFOST模型参数的确定及性能评价
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摘要
利用2011—2015年在锦州地区开展的玉米分期播种试验资料,确定了玉米初始总干物量(TDWI)、比叶面积(SLA)、出苗时叶面积指数(LAIEM)及发育参数,并采用试错法确定出其他生理参数。利用相关系数、相对误差以及均方根误差验证模型对发育期、叶面积指数(LAI)和不同器官生物量的模拟性能来评价所确定参数的适应性。结果表明:80%花期的平均模拟误差为1.25 d,而75%成熟期的平均模拟误差为3.47 d,LAI和总地上生物量(TAGP)模拟值对实测值的解释能力分别达到0.8412和0.8945;模型模拟性能存在较明显的年际和播期差异,在干旱年较差,2012年(土壤水分适宜)和2015年(干旱) LAI和TAGP的均方根误差分别为0. 38 m~2·m~(-2)、9. 40 kg·hm~(-2)和0. 44 m~2·m~(-2)、22. 65kg·hm~(-2);模型性能随播期的偏离而下降,4月30日(适播期)与5月20日播期LAI和TAGP的均方根误差分别为0. 30 m~2·m~(-2)、15. 19 kg·hm~(-2)和0. 43 m~2·m~(-2)、25. 66kg·hm~(-2)。本研究将为东北春玉米作物模型参数的确定提供重要参考。
Correct parameters are the key prerequisite for the prediction of crop models.In this study,a series of important crop parameters including initial total crop dry weight(TDWI),specific leaf area(SLA),leaf area index at emergency(LAIEM),developing parameters and other physiological parameters were measured and determinated using the observation data and trialand-error method based on the experiment of different sowing dates for maize in Jinzhou during2011-2015.The adaptability of those parameters in WOFOST model was evaluated by testing the simulation accuracy of growth periods,leaf area index(LAI) and the biomass of different organs of maize with the methods of correlation coefficient,relative error(RE) and root mean square error(RMSE).The results showed that mean simulation errors for antheses and mature stages with 80% and 75% of the total samples were 1.25 and 3.47 days,respectively.The explanatory abilities of simulation to observation for LAI and total aboveground production(TAGP) were0.8412 and 0.8945,respectively.Besides,there were obvious inter-annual and sowing date differences for the model performances in simulating above-mentioned variables and their simulation accuracy were lower in dry year.Specifically,the RMSEs of LAI and TAGP were 0.38 m~2·m~(-2) and 9.40 kg·hm~(-2) in 2012 respectively when soil water content was under the suitable condition during the whole growing season,and were 0.44 m~2·m~(-2) and 22.65 kg·hm~(-2) in 2015 when maize suffered long-term drought.Furthermore,the model performed worse when the sowing date was deviated from the normal range.The RMSEs of LAI and TAGP were 0.30 m~2·m~(-2) and15.19 kg·hm~(-2) for the optimum sowing date on 30 April and 0.43 m~2·m~(-2) and 25.66 kg·hm-2 for the sowing date on 20 May.Our results provide an important reference for determining the crop model parameters of spring maize in northeast China.
Correct parameters are the key prerequisite for the prediction of crop models.In this study,a series of important crop parameters including initial total crop dry weight(TDWI),specific leaf area(SLA),leaf area index at emergency(LAIEM),developing parameters and other physiological parameters were measured and determinated using the observation data and trialand-error method based on the experiment of different sowing dates for maize in Jinzhou during2011-2015.The adaptability of those parameters in WOFOST model was evaluated by testing the simulation accuracy of growth periods,leaf area index(LAI) and the biomass of different organs of maize with the methods of correlation coefficient,relative error(RE) and root mean square error(RMSE).The results showed that mean simulation errors for antheses and mature stages with 80% and 75% of the total samples were 1.25 and 3.47 days,respectively.The explanatory abilities of simulation to observation for LAI and total aboveground production(TAGP) were0.8412 and 0.8945,respectively.Besides,there were obvious inter-annual and sowing date differences for the model performances in simulating above-mentioned variables and their simulation accuracy were lower in dry year.Specifically,the RMSEs of LAI and TAGP were 0.38 m~2·m~(-2) and 9.40 kg·hm~(-2) in 2012 respectively when soil water content was under the suitable condition during the whole growing season,and were 0.44 m~2·m~(-2) and 22.65 kg·hm~(-2) in 2015 when maize suffered long-term drought.Furthermore,the model performed worse when the sowing date was deviated from the normal range.The RMSEs of LAI and TAGP were 0.30 m~2·m~(-2) and15.19 kg·hm~(-2) for the optimum sowing date on 30 April and 0.43 m~2·m~(-2) and 25.66 kg·hm-2 for the sowing date on 20 May.Our results provide an important reference for determining the crop model parameters of spring maize in northeast China.
引文
蔡福,米娜,纪瑞鹏,等.2017.关键发育期干旱及复水过程对春玉米主要生理参数的影响.应用生态学报,28(11):3643-3652.
蔡福,明惠青,谢艳兵,等.2018.东北地区春玉米关键生育期干旱对根系生长的影响.气象与环境学报,34(2):75-81.
曹阳,杨婕,熊伟,等.2014.1961-2010年潜在干旱对我国夏玉米产量影响的模拟分析.生态学报,34(2):421-429.
陈思宁,赵艳霞,申双和,等.2013.基于PyWOFOST作物模型的东北玉米估产及精度评估.中国农业科学,46(14):2880-2893.
范志宣.2016.气候变化背景下基于作物模型的吉林省玉米潜在产量模拟(硕士学位论文).沈阳:沈阳农业大学.
方缘.2015.基于作物生长模型的玉米干旱损失评估(硕士学位论文).沈阳:沈阳农业大学.
何永坤,唐余学,张建平.2014.中国西南地区干旱对玉米产量影响评估方法.农业工程学报,30(23):185-191.
纪瑞鹏,车宇胜,朱永宁,等.2012.干旱对东北春玉米生长发育和产量的影响.应用生态学报,23(11):3021-3026.
李秀芬,马树庆,宫丽娟.2013.基于WOFOST的东北地区玉米生育期气象条件适宜度评价.中国农业气象,34(1):43-49.
李莹莹.2017.不同水分条件及复水对吉林省春玉米生长发育影响的模拟研究(硕士学位论文).南京:南京信息工程大学.
刘维,侯英雨,吴门新,等.2017.WOFOST模型在东北春玉米产区的验证与适应性评价.气象与环境科学,40(3):7-13.
栾庆祖,叶彩华,莫志鸿,等.2014.基于WOFOST模型的玉米干旱损失评估:以北京为例.中国农业气象,35(3):311-316.
麻雪艳,周广胜.2013.玉米叶面积指数动态模拟的最适野外观测资料.应用生态学报,24(6):1579-1585.
米娜,蔡福,张玉书,等.2017.不同生育期持续干旱对玉米的影响及其与减产率的定量关系.应用生态学报,28(5):1563-1570.
米娜,张玉书,蔡福,等.2016.土壤干旱胁迫对作物影响的模拟研究进展.生态学杂志,35(9):2519-2526.
孙琳丽,侯琼,马玉平,等.2016.WOFOST模型在内蒙古河套灌区模拟玉米生长全程的适应性.生态学杂志,35(3):800-807.
张德来,蔡福,史奎桥,等.2018.东北地区春玉米主要生理参数对拔节至灌浆期干旱的响应.气象与环境学报,34(4):134-138.
张建平,何永坤,王靖,等.2015.不同发育期干旱对玉米籽粒形成与产量的影响模拟.中国农业气象,36(1):43-49.
张建平,王春乙,赵艳霞,等.2012a.基于作物模型的低温冷害对我国东北三省玉米产量影响评估.生态学报,32(13):4132-4138.
张建平,赵艳霞,王春乙,等.2012b.不同发育期干旱对冬小麦灌浆和产量影响的模拟.中国生态农业学报,20(9):1158-1165.
张宁,张庆国,于海敬,等.2018.作物生长模拟模型的参数敏感性分析.浙江大学学报:农业与生命科学版,44(1):107-115.
张悦,邸万通,王晶晶,等.2017.北方农牧交错带间套作资源利用的研究进展.生态学杂志,36(9):2623-2632
赵锦,杨晓光,刘志娟,等.2014.全球气候变暖对中国种植制度的可能影响.Ⅹ:气候变化对东北三省春玉米气候适宜性的影响.中国农业科学,47(16):3143-3156.
中国气象局.1993.农业气象观测规范:上卷.北京:气象出版社.
Bai LP,Sui FG,Sun ZH,et al.2004.Effects of soil water stress on morphological development and yield of maize.Acta Ecologica Sinica,24:1556-1560.
Bonato O,Schulthess IF,Baumgartner J.1999.Simulation model for maize crop growth based on acquisition and allocation processes for carbohydrate and nitrogen.Ecological Modelling,124:11-28.
Boogaard HL,van Diepen CA,Rotter RP,et al.1998.User’s guide for the WOFOST 7.1 crop growth simulation model and WOFOST Control Center 1.5.Wageningen:DLOWinand Staring Centre.
Cheng ZQ,Meng JH,Wang YM.2016.Improving spring maize yield estimation at field scale by assimilating time-series HJ-1 CCD data into the Wofost model using a new method with fast algorithms.Remote Sensing,8:303.doi:10.3390/rs8040303.
Iizumi T,Yokozawa M,Nishimori M.2009.Parameter estimation and uncertainty analysis of a large-scale crop model for paddy rice:Application of a Bayesian approach.Agricultural and Forest Meteorology,149:333-348.
Jones JW,Hoogenboom G,Porter CH,et al.2003.The DSSATcropping system model.European Journal of Agronomy,18:235-265.
Jones JW,Keating BA,Porter CH.2001.Approaches to modular model development.Agricultural Systems,70:421-443.
Keating BA,Carberry PS,Hammer GL,et al.2003.An overview of APSIM,a model designed for farming systems simulation.European Journal of Agronomy,18:267-288.
Tao F,Zhang Z,Liu J,et al.2009.Modelling the impacts of weather and climate variability on crop productivity over a large area:A new process-based model development,optimization,and uncertainties analysis.Agricultural and Forest Meteorology,149:831-850.
van Oijen M,Cameron DR,Butterbach-Bahl K,et al.2011.ABayesian framework for model calibration,comparison and analysis:Application to four models for the biogeochemistry of a Norway spruce forest.Agricultural and Forest Meteorology,151:1609-1621.
van Oijen M,Reyer C,Bohn FJ,et al.2013.Bayesian calibration,comparison and averaging of six forest models,using data from Scots pine stands across Europe.Forest Ecology and Management,289:255-268.
Weiner J,Campbell LG,Pino J,et al.2009.The allometry of reproduction within plant populations.Journal of Ecology,97:1220-1233.
Yang JC,Zhang JH.2006.Grain filling of cereals under soil drying.New Phytologist,169:223-236.
Zhang JQ.2004.Risk assessment of drought disaster in the maize growing region of Songliao Plain,China.Agriculture,Ecosystems and Environment,102:133-153.
Zhang YH,LüHQ,Li S.2008.Applicability of crop water deficit index in agricultural drought monitoring.Meteorological Science and Technology,36:596-600.
蔡福,明惠青,谢艳兵,等.2018.东北地区春玉米关键生育期干旱对根系生长的影响.气象与环境学报,34(2):75-81.
曹阳,杨婕,熊伟,等.2014.1961-2010年潜在干旱对我国夏玉米产量影响的模拟分析.生态学报,34(2):421-429.
陈思宁,赵艳霞,申双和,等.2013.基于PyWOFOST作物模型的东北玉米估产及精度评估.中国农业科学,46(14):2880-2893.
范志宣.2016.气候变化背景下基于作物模型的吉林省玉米潜在产量模拟(硕士学位论文).沈阳:沈阳农业大学.
方缘.2015.基于作物生长模型的玉米干旱损失评估(硕士学位论文).沈阳:沈阳农业大学.
何永坤,唐余学,张建平.2014.中国西南地区干旱对玉米产量影响评估方法.农业工程学报,30(23):185-191.
纪瑞鹏,车宇胜,朱永宁,等.2012.干旱对东北春玉米生长发育和产量的影响.应用生态学报,23(11):3021-3026.
李秀芬,马树庆,宫丽娟.2013.基于WOFOST的东北地区玉米生育期气象条件适宜度评价.中国农业气象,34(1):43-49.
李莹莹.2017.不同水分条件及复水对吉林省春玉米生长发育影响的模拟研究(硕士学位论文).南京:南京信息工程大学.
刘维,侯英雨,吴门新,等.2017.WOFOST模型在东北春玉米产区的验证与适应性评价.气象与环境科学,40(3):7-13.
栾庆祖,叶彩华,莫志鸿,等.2014.基于WOFOST模型的玉米干旱损失评估:以北京为例.中国农业气象,35(3):311-316.
麻雪艳,周广胜.2013.玉米叶面积指数动态模拟的最适野外观测资料.应用生态学报,24(6):1579-1585.
米娜,蔡福,张玉书,等.2017.不同生育期持续干旱对玉米的影响及其与减产率的定量关系.应用生态学报,28(5):1563-1570.
米娜,张玉书,蔡福,等.2016.土壤干旱胁迫对作物影响的模拟研究进展.生态学杂志,35(9):2519-2526.
孙琳丽,侯琼,马玉平,等.2016.WOFOST模型在内蒙古河套灌区模拟玉米生长全程的适应性.生态学杂志,35(3):800-807.
张德来,蔡福,史奎桥,等.2018.东北地区春玉米主要生理参数对拔节至灌浆期干旱的响应.气象与环境学报,34(4):134-138.
张建平,何永坤,王靖,等.2015.不同发育期干旱对玉米籽粒形成与产量的影响模拟.中国农业气象,36(1):43-49.
张建平,王春乙,赵艳霞,等.2012a.基于作物模型的低温冷害对我国东北三省玉米产量影响评估.生态学报,32(13):4132-4138.
张建平,赵艳霞,王春乙,等.2012b.不同发育期干旱对冬小麦灌浆和产量影响的模拟.中国生态农业学报,20(9):1158-1165.
张宁,张庆国,于海敬,等.2018.作物生长模拟模型的参数敏感性分析.浙江大学学报:农业与生命科学版,44(1):107-115.
张悦,邸万通,王晶晶,等.2017.北方农牧交错带间套作资源利用的研究进展.生态学杂志,36(9):2623-2632
赵锦,杨晓光,刘志娟,等.2014.全球气候变暖对中国种植制度的可能影响.Ⅹ:气候变化对东北三省春玉米气候适宜性的影响.中国农业科学,47(16):3143-3156.
中国气象局.1993.农业气象观测规范:上卷.北京:气象出版社.
Bai LP,Sui FG,Sun ZH,et al.2004.Effects of soil water stress on morphological development and yield of maize.Acta Ecologica Sinica,24:1556-1560.
Bonato O,Schulthess IF,Baumgartner J.1999.Simulation model for maize crop growth based on acquisition and allocation processes for carbohydrate and nitrogen.Ecological Modelling,124:11-28.
Boogaard HL,van Diepen CA,Rotter RP,et al.1998.User’s guide for the WOFOST 7.1 crop growth simulation model and WOFOST Control Center 1.5.Wageningen:DLOWinand Staring Centre.
Cheng ZQ,Meng JH,Wang YM.2016.Improving spring maize yield estimation at field scale by assimilating time-series HJ-1 CCD data into the Wofost model using a new method with fast algorithms.Remote Sensing,8:303.doi:10.3390/rs8040303.
Iizumi T,Yokozawa M,Nishimori M.2009.Parameter estimation and uncertainty analysis of a large-scale crop model for paddy rice:Application of a Bayesian approach.Agricultural and Forest Meteorology,149:333-348.
Jones JW,Hoogenboom G,Porter CH,et al.2003.The DSSATcropping system model.European Journal of Agronomy,18:235-265.
Jones JW,Keating BA,Porter CH.2001.Approaches to modular model development.Agricultural Systems,70:421-443.
Keating BA,Carberry PS,Hammer GL,et al.2003.An overview of APSIM,a model designed for farming systems simulation.European Journal of Agronomy,18:267-288.
Tao F,Zhang Z,Liu J,et al.2009.Modelling the impacts of weather and climate variability on crop productivity over a large area:A new process-based model development,optimization,and uncertainties analysis.Agricultural and Forest Meteorology,149:831-850.
van Oijen M,Cameron DR,Butterbach-Bahl K,et al.2011.ABayesian framework for model calibration,comparison and analysis:Application to four models for the biogeochemistry of a Norway spruce forest.Agricultural and Forest Meteorology,151:1609-1621.
van Oijen M,Reyer C,Bohn FJ,et al.2013.Bayesian calibration,comparison and averaging of six forest models,using data from Scots pine stands across Europe.Forest Ecology and Management,289:255-268.
Weiner J,Campbell LG,Pino J,et al.2009.The allometry of reproduction within plant populations.Journal of Ecology,97:1220-1233.
Yang JC,Zhang JH.2006.Grain filling of cereals under soil drying.New Phytologist,169:223-236.
Zhang JQ.2004.Risk assessment of drought disaster in the maize growing region of Songliao Plain,China.Agriculture,Ecosystems and Environment,102:133-153.
Zhang YH,LüHQ,Li S.2008.Applicability of crop water deficit index in agricultural drought monitoring.Meteorological Science and Technology,36:596-600.