基于COSIM模型的新疆棉花产量动态预报方法
|
摘要
该文在对棉花生长模拟模型COSIM进行模型调试、验证实现本地化应用的基础上,探讨运用作物模型进行棉花产量动态预报的方法,重点解决未知气象数据替代问题。作物模型应用于产量预报时,未来天气的不确定性是影响预报准确率的关键因子,该影响随着当年实际天气数据增多而减小。该文以近50 a的气象数据,依次替代预报日至收获期的气象数据(即预报日之前使用预报年当年气象数据,预报日之后使用替代年气象数据),模拟棉花生长发育和产量形成过程,以近50、40、30、20、10、5 a历史气候数据依次替代预报日之后的逐日数据获得的模拟产量平均值作为预报产量,根据对预报准确率进行比较,最终确定以近10 a实测数据替代获得的模拟产量平均值作为最终预报产量。经验证该预报方法对不同播种时间棉花产量动态预报的准确率在81.3%~99.6%,预测精度较好。作为案例分析,该文仅进行每月1次预测分析,实际应用中可进行逐日替代动态预报,经过进一步改进,提高预报精度,未来可望达到业务应用水平。
Xinjiang is the largest cotton producing area in China accounting for more than 50%of the total cotton production in China.So the accuracy of the prediction of cotton production in Xinjiang is particularly important.Based on calibration and validation of cotton growth model COSIM,in this paper,we used a dynamic prediction model for cotton yield forecast and focused on solving the problem of the unknown climatic data substitution during the prediction period.In the process of prediction,the model read the climatic data day by day.For predicting the growth,development and yield of cotton by the dynamic prediction model,in this study,we substituted the measured climatic data in the recent 50,30,20,10,and 5 years for the unknown climatic data from forecasting day to harvest day,respectively.Meanwhile,the climatic data measured in the year was input into the model before forecasting day.In this way,the cotton yield and development could be predicted day by day.To test the reliability of the method,an experiment with 5 different sowing date(April 10~(th),April 20~(th),April 30~(th),May10~(th),May 20~(th))was designed in 2011 at Wusu,Xinjiang(44°43′N,84°67′E).Each treatment was replicated 3 times.The cotton was harvested on September 10~(th),September 15th,September 21th,September 29th and October 5~(th),respectively.During the experiment,the growing stage of the cotton was recorded.The leaf area and biomass were determined.These parameter values were input into the COSIM model for cotton lint yield prediction.The model reliability was evaluated by comparing the simulated and measured values of lint yield and growing stages.For the simulation,the climatic data measured in 2011 was used.The results showed that the root mean square error(RMSE)of the cotton growing from emergence to flowering stage was 2.2-5.9 d.The determination coefficient was 0.99.For the lint yields simulations,the RMSE was 165.9 kg/hm~2.It indicated that the model was reliable in simulating cotton development and lint yield.Based on experimental results of treatment 1(sowing date was April 20th),we selected the best substitution one for the unknown climatic data from the5 schemes(climatic data of the recent 50,30,20,10,and 5 years)and then validated by the results from the other treatments.The results showed that the for the randomly selected 7 predicting time(April 1st,May 1~(st),June 1~(st),July 1~(st),August 1~(st),September 1~(st),October 1~(st)),the standard deviation of the measured and predicted lint yield of the 5 schemes from 50 to 5 years’climatic data was 171,123,82,86 and 106kg/hm~2,respectively.The predicting accuracy was above 87%compared with the measured values and above 83%compared with the simulated values for the lint yields.Among them,the accuracy in the predicting time after the sowing date was above 93%.Based on the predicting accuracy and the standard deviation,the best scheme was the 10 years’climatic data substation scheme.The validation of the best scheme using the results from the other treatments showed that predicting accuracy could reach 81.3%-99.6%,indicating the reliability of the best scheme for cotton lint yield prediction.Compared with a single station forecasting,the regional forecasting of cotton yield is more important to national macro-control.In a large region,cotton is not sowing on the same day but during a time period.Therefore,in predicting the regional cotton yield,the effect of sowing time should be taken into consideration.As a case,this study only does the forecast once a month.In practice,the daily dynamic forecast would be realized.
Xinjiang is the largest cotton producing area in China accounting for more than 50%of the total cotton production in China.So the accuracy of the prediction of cotton production in Xinjiang is particularly important.Based on calibration and validation of cotton growth model COSIM,in this paper,we used a dynamic prediction model for cotton yield forecast and focused on solving the problem of the unknown climatic data substitution during the prediction period.In the process of prediction,the model read the climatic data day by day.For predicting the growth,development and yield of cotton by the dynamic prediction model,in this study,we substituted the measured climatic data in the recent 50,30,20,10,and 5 years for the unknown climatic data from forecasting day to harvest day,respectively.Meanwhile,the climatic data measured in the year was input into the model before forecasting day.In this way,the cotton yield and development could be predicted day by day.To test the reliability of the method,an experiment with 5 different sowing date(April 10~(th),April 20~(th),April 30~(th),May10~(th),May 20~(th))was designed in 2011 at Wusu,Xinjiang(44°43′N,84°67′E).Each treatment was replicated 3 times.The cotton was harvested on September 10~(th),September 15th,September 21th,September 29th and October 5~(th),respectively.During the experiment,the growing stage of the cotton was recorded.The leaf area and biomass were determined.These parameter values were input into the COSIM model for cotton lint yield prediction.The model reliability was evaluated by comparing the simulated and measured values of lint yield and growing stages.For the simulation,the climatic data measured in 2011 was used.The results showed that the root mean square error(RMSE)of the cotton growing from emergence to flowering stage was 2.2-5.9 d.The determination coefficient was 0.99.For the lint yields simulations,the RMSE was 165.9 kg/hm~2.It indicated that the model was reliable in simulating cotton development and lint yield.Based on experimental results of treatment 1(sowing date was April 20th),we selected the best substitution one for the unknown climatic data from the5 schemes(climatic data of the recent 50,30,20,10,and 5 years)and then validated by the results from the other treatments.The results showed that the for the randomly selected 7 predicting time(April 1st,May 1~(st),June 1~(st),July 1~(st),August 1~(st),September 1~(st),October 1~(st)),the standard deviation of the measured and predicted lint yield of the 5 schemes from 50 to 5 years’climatic data was 171,123,82,86 and 106kg/hm~2,respectively.The predicting accuracy was above 87%compared with the measured values and above 83%compared with the simulated values for the lint yields.Among them,the accuracy in the predicting time after the sowing date was above 93%.Based on the predicting accuracy and the standard deviation,the best scheme was the 10 years’climatic data substation scheme.The validation of the best scheme using the results from the other treatments showed that predicting accuracy could reach 81.3%-99.6%,indicating the reliability of the best scheme for cotton lint yield prediction.Compared with a single station forecasting,the regional forecasting of cotton yield is more important to national macro-control.In a large region,cotton is not sowing on the same day but during a time period.Therefore,in predicting the regional cotton yield,the effect of sowing time should be taken into consideration.As a case,this study only does the forecast once a month.In practice,the daily dynamic forecast would be realized.
引文
[1]Woli P,Jones J W,Ingram K T,et al.Predicting crop yields with the agricultural reference index for drought[J].Journal of agronomy and crop science,2014,200(3):163-171.
[2]李曼华,薛晓萍,李鸿怡.基于气候适宜度指数的山东省冬小麦产量动态预报[J].中国农学通报,2012,28(12):291-295.Li Manhua,Xue Xiaoping,Li Hongyi.Dynamic prediction method for wheat yield based on climatic suitability index in Shandong Province[J].Chinese Agricultural Science Bulletin,2012,28(12):291-295.(in Chinese with English abstract)
[3]易谆,王晓东,陈刚,等.基于灰色预测和线性回归的烟叶产量预测模型[J].计算机应用,2013,33(S1):52-54.Yi Zhun,Wang Xiaodong,Chen Gang,et al.Forecast model of tobacco production based on grey dynamic model and multivariate linear regression[J].Journal of Computer Applications,2013,33(S1):52-54.(in Chinese with English abstract)
[4]杜春英,李帅,王晾晾,等.基于历史产量丰歉影响指数的黑龙江省水稻产量动态预报[J].中国农业气象,2010,31(3):427-430.Du Chunying,Li Shuai,Wang Liangliang,et al.Dynamic prediction method for rice yield based on influence index for bumper or poor harvest from historic yield in Heilongjiang Province[J].Chinese Journal of Agro meteorology,2010,31(3):427-430.(in Chinese with English abstract)
[5]严彩虹,李小明.基于灰色关联分析的新疆棉花产量气象影响因素研究[J].沙漠与绿洲气象,2012,6(5):51-53.Yan Caihong,Li Xiaoming.Meteorological factors influencing cotton yield in Xinjiang based on gray conjunction analysis[J].Desert and Oasis Meteorology,2012,6(5):51-53.(in Chinese with English abstract)
[6]王伟,黄义德,黄文江,等.作物生长模型的适用性评价及冬小麦产量预测[J].农业工程学报,2010,26(3):233-237.Wang Wei,Huang Yide,Huang Wenjiang,et al.Applicability evaluation of CERES-Wheat model and yield prediction of winter wheat[J].Transactions of the Chinese Society of Agricultural Engineering(Transactions of the CSAE),2010,26(3):233-237.(in Chinese with English abstract)
[7]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[J].应用气象学报,2008,19(1):71-81.Shuai Xiqiang,Wang Shili,Ma Yuping,et al.Assessment of meteorological condition effects and dynamic yield Forecasting based on rice growth model[J].Journal of Applied Meteorological Science,2008,19(1):71-81.(in Chinese with English abstract)
[8]黄晚华,薛昌颖,李忠辉,等.基于作物生长模拟模型的产量预报方法研究进展[J].中国农业气象,2009,30(增刊1):140-143.Huang Wanhua,Xue Changying,Li Zhonghui,et al.Research progresses in yield forecasting method based on crop growth simulation model in China[J].Chinese Journal of Agrometeorology,2009,30(Supp.1):140-143.(in Chinese with English abstract)
[9]Guillaume J,Elizabeth P,Liu J G.Using leaf area index,retrieved from optical imagery,in the STICS crop model for predicting yield and biomass of field crops[J].Field Crop Research,2012,131(2):63-74.
[10]任建强,陈仲新,唐华俊,等.基于遥感信息与作物生长模型的区域作物单产模拟[J].农业工程学报,2011,27(8):257-264.Ren Jianqiang,Chen Zhongxin,Tang Huajun,et al.Regional crop yield simulation based on crop growth model and remote sensing data[J].Transactions of the Chinese Society of Agricultural Engineering(Transactions of the CSAE),2011,27(8):257-264.(in Chinese with English abstract)
[11]黄健熙,武思杰,刘兴权,等.基于遥感信息与作物模型集合卡尔曼滤波同化的区域冬小麦产量预测[J].农业工程学报,2012,28(4):142-148.Huang Jianxi,Wu Sijie,Liu Xingquan,et al.Regional winter wheat yield forecasting based on assimilation of remote sensing data and crop growth model with Ensemble Kalman method[J].Transactions of the Chinese Society of Agricultural Engineering(Transactions of the CSAE),2012,28(4):142-148.(in Chinese with English abstract)
[12]陈劲松,黄健熙,林珲,等.基于遥感信息和作物模型同化的水稻估产方法研究[J].中国科学:信息科学,2010,4(增刊):173-183.Chen Jinsong,Huang Jianxi,Lin Hui,et al.Rice yield estimation by assimilation remote sensing into crop growth model[J].Science China:Information Sci,2010,4(Suppl):173-183.(in Chinese with English abstract)
[13]杨鹏,吴文斌,周清波,等.基于作物模型与叶面积指数遥感影响同化的区域单产估测研究[J].农业工程学报,2007,23(9):130-136.Yang Peng,Wu Wenbin,Zhou Qingbo,et al.Assimilating remotely sensed LAI into GIS-based EPIC model for yield assessment on regional scale[J].Transactions of the Chinese Society of Agricultural Engineering(Transactions of the CSAE),2007,23(9):130-136.(in Chinese with English abstract)
[14]Amor V M I,Narendra N D,James W H,et al.Assimilation of remotely sensed soil moisture and vegetation with a crop simulation model for maize yield prediction[J].Remote Sensing of Environment,2013,138(6):149-164.
[15]毛树春,李亚兵,冯璐,等.新疆棉花生产发展问题研究[J].农业展望,2014(11):43-51.Mao Shuchun,Li Yabing,Feng Lu,et al.Study on the development of Xinjiang cotton production[J].Agricultural Outlook,2014(11):43-51.(in Chinese with English abstract)
[16]Jin I Y.Predicting regional rice production in South Korea using spatial data and crop-growth modeling[J].Agricultural Systems,2003,77(1):23-38.
[17]廖要明,张强,陈德亮.中国天气发生器的降水模拟[J].地理学报,2004,59(5):689-698.Liao Yaoming,Zhang Qiang,Chen Deliang.Precipitation simulation in China with a weather generator[J].Acta Geographica Sinica,2004,59(5):689-698.(in Chinese with English abstract)
[18]李世娟,诸叶平.基于干湿期的随机天气发生器[J].农业工程学报,2014,30(11):118-124.Li Shijuan,Zhu Yeping.Stochastic weather generator based on dry and wet spells[J].Transactions of the Chinese Society of Agricultural Engineering(Transactions of the CSAE),2014,30(11):118-124.(in Chinese with English abstract)
[19]张徐杰,许月萍,高希超,等.CCSM3模式下汉江流域设计暴雨计算[J].水力发电学报,2012,31(4):49-53.Zhang Xujie,Xu Yueping,Gao Xichao,et al.Estimation of design storm in Han River basin with CCSM3 model[J].Journal of Hydroeletric Engineering,2012,31(4):49-53.(in Chinese with English abstract)
[20]王建林,宋迎波.棉花产量动态预测方法研究[J].中国棉花,2002,29(9):5-7.Wang Jianlin,Song Yingbo.Study on dynamic prediction method for cotton yield[J].China Cotton,2002,29(9):5-7.(in Chinese with English abstract)
[21]郑昌玲,杨霏云,王建林,等.早稻产量动态预报模型[J].中国农业气象,2007,28(4):412-416.Zheng Changling,Yang Feiyun,Wang Jianlin,et al.A study on dynamic prediction model of early rice yield per unit[J].Chinese Journal of Agrometeorology,2007,28(4):412-416.(in Chinese with English abstract)
[22]杨霏云,王建林.晚稻单产动态预测方法研究[J].气象科技,2005,33(5):433-436.Yang Feiyun,Wang Jianlin.A method for dynamically predicting late rice yields[J].Meteorological Science and Technology,2005,33(5):433-436.(in Chinese with English abstract)
[23]易雪,王建林,宋迎波,等.早稻产量动态集成预报方法研究[J].中国水稻科学,2011,25(3):307-313.Yi Xue,Wang Jianlin,Song Yingbo,et al.Study on dynamic Integrated prediction of early rice yield[J].Chinese Journal of Rice Science,2011,25(3):307-313.(in Chinese with English abstract)
[24]潘学标,李玉娥.新疆棉花生产区域评估系统研究[J].中国农业科学,2003,36(1):37-43.Pan Xuebiao,Li Yu’e.Study of cotton production regional assessment system[J].Scientia Agricultura Sinica,2003,36(1):37-43.(in Chinese with English abstract)
[25]潘学标,韩湘玲,董占山,等.棉花生长发育模拟模型COTGROW的建立Ⅰ光合作用和干物质生产与分配[J].棉花学报,1997,9(3):132-141.Pan Xuebiao,Han Xiangling,Dong Zhanshan,et al.Developed on cotton growth and development model COTGROWⅠPhotosynthesis and dry matter production and distribution[J].Cotton Science,1997,9(3):132-141.(in Chinese with English abstract)
[26]潘学标,韩湘玲,王延琴,等.棉花生长发育模拟模型COTGROW的建立Ⅱ发育与形态发生[J].棉花学报,1999,11(4):174-181.Pan Xuebiao,Han Xiangling,Wang Yanqin,et al.Developed on cotton growth and development model COTGROWⅡMorphological development[J].Cotton Science,1999,11(4):174-181.(in Chinese with English abstract)
[27]陈超,潘学标,李慧阳,等.基于COSIM模型的新疆棉花延迟型冷害指标分析[J].棉花学报,2009,21(3):201-205.Chen Chao,Pan Xuebiao,Li Huiyang,et al.Analysis of cotton delayed cool injury indices in Xinjiang based on COSIM[J].Cotton Science,2009,21(3):201-205.(in Chinese with English abstract)
[28]王雪姣,潘学标,陈超,等.基于COSIM模型的棉花冷害预测研究[J].棉花学报,2012,24(1):52-61.Wang Xuejiao,Pan Xuebiao,Chen Chao,et al.Forecasting cotton chilling damage based on COSIM[J].Cotton Science,2012,24(1):52-61.(in Chinese with English abstract)
[29]托丽娜,潘学标,廖要明,等.新疆棉花生产气候风险评估的模型方法初探[J].棉花学报,2005,17(2):122-124.Tuo Lina,Pan Xuebiao,Liao Yaoming,et al.Assessment of climate risk for cotton production in Xinjiang by cotton production regional assessment system[J].Cotton Science,2005,17(2):122-124.(in Chinese with English abstract)
[30]陈超,潘学标,张立祯,等.气候变化对石羊河流域棉花生产和耗水的影响[J].农业工程学报,2011,27(1):57-65.Chen Chao,Pan Xuebiao,Zhang Lizhen,et al.Impact of climate change on cotton production and water consumption in Shiyang River Basin[J].Transactions of the Chinese Society of Agricultural Engineering(Transactions of the CSAE),2011,27(1):57-65.(in Chinese with English abstract)
[31]王雪姣.气候变化对新疆棉花物候、产量和品质的影响与适应措施[D].北京:中国农业大学,2015.Wang Xuejiao.Impact and Adaptation of Climate Change on Cotton Phenology,Yield and Fiber Quality in Xinjiang[D].Beijing:China Agricultural University,2015.(in Chinese with English abstract)
[2]李曼华,薛晓萍,李鸿怡.基于气候适宜度指数的山东省冬小麦产量动态预报[J].中国农学通报,2012,28(12):291-295.Li Manhua,Xue Xiaoping,Li Hongyi.Dynamic prediction method for wheat yield based on climatic suitability index in Shandong Province[J].Chinese Agricultural Science Bulletin,2012,28(12):291-295.(in Chinese with English abstract)
[3]易谆,王晓东,陈刚,等.基于灰色预测和线性回归的烟叶产量预测模型[J].计算机应用,2013,33(S1):52-54.Yi Zhun,Wang Xiaodong,Chen Gang,et al.Forecast model of tobacco production based on grey dynamic model and multivariate linear regression[J].Journal of Computer Applications,2013,33(S1):52-54.(in Chinese with English abstract)
[4]杜春英,李帅,王晾晾,等.基于历史产量丰歉影响指数的黑龙江省水稻产量动态预报[J].中国农业气象,2010,31(3):427-430.Du Chunying,Li Shuai,Wang Liangliang,et al.Dynamic prediction method for rice yield based on influence index for bumper or poor harvest from historic yield in Heilongjiang Province[J].Chinese Journal of Agro meteorology,2010,31(3):427-430.(in Chinese with English abstract)
[5]严彩虹,李小明.基于灰色关联分析的新疆棉花产量气象影响因素研究[J].沙漠与绿洲气象,2012,6(5):51-53.Yan Caihong,Li Xiaoming.Meteorological factors influencing cotton yield in Xinjiang based on gray conjunction analysis[J].Desert and Oasis Meteorology,2012,6(5):51-53.(in Chinese with English abstract)
[6]王伟,黄义德,黄文江,等.作物生长模型的适用性评价及冬小麦产量预测[J].农业工程学报,2010,26(3):233-237.Wang Wei,Huang Yide,Huang Wenjiang,et al.Applicability evaluation of CERES-Wheat model and yield prediction of winter wheat[J].Transactions of the Chinese Society of Agricultural Engineering(Transactions of the CSAE),2010,26(3):233-237.(in Chinese with English abstract)
[7]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[J].应用气象学报,2008,19(1):71-81.Shuai Xiqiang,Wang Shili,Ma Yuping,et al.Assessment of meteorological condition effects and dynamic yield Forecasting based on rice growth model[J].Journal of Applied Meteorological Science,2008,19(1):71-81.(in Chinese with English abstract)
[8]黄晚华,薛昌颖,李忠辉,等.基于作物生长模拟模型的产量预报方法研究进展[J].中国农业气象,2009,30(增刊1):140-143.Huang Wanhua,Xue Changying,Li Zhonghui,et al.Research progresses in yield forecasting method based on crop growth simulation model in China[J].Chinese Journal of Agrometeorology,2009,30(Supp.1):140-143.(in Chinese with English abstract)
[9]Guillaume J,Elizabeth P,Liu J G.Using leaf area index,retrieved from optical imagery,in the STICS crop model for predicting yield and biomass of field crops[J].Field Crop Research,2012,131(2):63-74.
[10]任建强,陈仲新,唐华俊,等.基于遥感信息与作物生长模型的区域作物单产模拟[J].农业工程学报,2011,27(8):257-264.Ren Jianqiang,Chen Zhongxin,Tang Huajun,et al.Regional crop yield simulation based on crop growth model and remote sensing data[J].Transactions of the Chinese Society of Agricultural Engineering(Transactions of the CSAE),2011,27(8):257-264.(in Chinese with English abstract)
[11]黄健熙,武思杰,刘兴权,等.基于遥感信息与作物模型集合卡尔曼滤波同化的区域冬小麦产量预测[J].农业工程学报,2012,28(4):142-148.Huang Jianxi,Wu Sijie,Liu Xingquan,et al.Regional winter wheat yield forecasting based on assimilation of remote sensing data and crop growth model with Ensemble Kalman method[J].Transactions of the Chinese Society of Agricultural Engineering(Transactions of the CSAE),2012,28(4):142-148.(in Chinese with English abstract)
[12]陈劲松,黄健熙,林珲,等.基于遥感信息和作物模型同化的水稻估产方法研究[J].中国科学:信息科学,2010,4(增刊):173-183.Chen Jinsong,Huang Jianxi,Lin Hui,et al.Rice yield estimation by assimilation remote sensing into crop growth model[J].Science China:Information Sci,2010,4(Suppl):173-183.(in Chinese with English abstract)
[13]杨鹏,吴文斌,周清波,等.基于作物模型与叶面积指数遥感影响同化的区域单产估测研究[J].农业工程学报,2007,23(9):130-136.Yang Peng,Wu Wenbin,Zhou Qingbo,et al.Assimilating remotely sensed LAI into GIS-based EPIC model for yield assessment on regional scale[J].Transactions of the Chinese Society of Agricultural Engineering(Transactions of the CSAE),2007,23(9):130-136.(in Chinese with English abstract)
[14]Amor V M I,Narendra N D,James W H,et al.Assimilation of remotely sensed soil moisture and vegetation with a crop simulation model for maize yield prediction[J].Remote Sensing of Environment,2013,138(6):149-164.
[15]毛树春,李亚兵,冯璐,等.新疆棉花生产发展问题研究[J].农业展望,2014(11):43-51.Mao Shuchun,Li Yabing,Feng Lu,et al.Study on the development of Xinjiang cotton production[J].Agricultural Outlook,2014(11):43-51.(in Chinese with English abstract)
[16]Jin I Y.Predicting regional rice production in South Korea using spatial data and crop-growth modeling[J].Agricultural Systems,2003,77(1):23-38.
[17]廖要明,张强,陈德亮.中国天气发生器的降水模拟[J].地理学报,2004,59(5):689-698.Liao Yaoming,Zhang Qiang,Chen Deliang.Precipitation simulation in China with a weather generator[J].Acta Geographica Sinica,2004,59(5):689-698.(in Chinese with English abstract)
[18]李世娟,诸叶平.基于干湿期的随机天气发生器[J].农业工程学报,2014,30(11):118-124.Li Shijuan,Zhu Yeping.Stochastic weather generator based on dry and wet spells[J].Transactions of the Chinese Society of Agricultural Engineering(Transactions of the CSAE),2014,30(11):118-124.(in Chinese with English abstract)
[19]张徐杰,许月萍,高希超,等.CCSM3模式下汉江流域设计暴雨计算[J].水力发电学报,2012,31(4):49-53.Zhang Xujie,Xu Yueping,Gao Xichao,et al.Estimation of design storm in Han River basin with CCSM3 model[J].Journal of Hydroeletric Engineering,2012,31(4):49-53.(in Chinese with English abstract)
[20]王建林,宋迎波.棉花产量动态预测方法研究[J].中国棉花,2002,29(9):5-7.Wang Jianlin,Song Yingbo.Study on dynamic prediction method for cotton yield[J].China Cotton,2002,29(9):5-7.(in Chinese with English abstract)
[21]郑昌玲,杨霏云,王建林,等.早稻产量动态预报模型[J].中国农业气象,2007,28(4):412-416.Zheng Changling,Yang Feiyun,Wang Jianlin,et al.A study on dynamic prediction model of early rice yield per unit[J].Chinese Journal of Agrometeorology,2007,28(4):412-416.(in Chinese with English abstract)
[22]杨霏云,王建林.晚稻单产动态预测方法研究[J].气象科技,2005,33(5):433-436.Yang Feiyun,Wang Jianlin.A method for dynamically predicting late rice yields[J].Meteorological Science and Technology,2005,33(5):433-436.(in Chinese with English abstract)
[23]易雪,王建林,宋迎波,等.早稻产量动态集成预报方法研究[J].中国水稻科学,2011,25(3):307-313.Yi Xue,Wang Jianlin,Song Yingbo,et al.Study on dynamic Integrated prediction of early rice yield[J].Chinese Journal of Rice Science,2011,25(3):307-313.(in Chinese with English abstract)
[24]潘学标,李玉娥.新疆棉花生产区域评估系统研究[J].中国农业科学,2003,36(1):37-43.Pan Xuebiao,Li Yu’e.Study of cotton production regional assessment system[J].Scientia Agricultura Sinica,2003,36(1):37-43.(in Chinese with English abstract)
[25]潘学标,韩湘玲,董占山,等.棉花生长发育模拟模型COTGROW的建立Ⅰ光合作用和干物质生产与分配[J].棉花学报,1997,9(3):132-141.Pan Xuebiao,Han Xiangling,Dong Zhanshan,et al.Developed on cotton growth and development model COTGROWⅠPhotosynthesis and dry matter production and distribution[J].Cotton Science,1997,9(3):132-141.(in Chinese with English abstract)
[26]潘学标,韩湘玲,王延琴,等.棉花生长发育模拟模型COTGROW的建立Ⅱ发育与形态发生[J].棉花学报,1999,11(4):174-181.Pan Xuebiao,Han Xiangling,Wang Yanqin,et al.Developed on cotton growth and development model COTGROWⅡMorphological development[J].Cotton Science,1999,11(4):174-181.(in Chinese with English abstract)
[27]陈超,潘学标,李慧阳,等.基于COSIM模型的新疆棉花延迟型冷害指标分析[J].棉花学报,2009,21(3):201-205.Chen Chao,Pan Xuebiao,Li Huiyang,et al.Analysis of cotton delayed cool injury indices in Xinjiang based on COSIM[J].Cotton Science,2009,21(3):201-205.(in Chinese with English abstract)
[28]王雪姣,潘学标,陈超,等.基于COSIM模型的棉花冷害预测研究[J].棉花学报,2012,24(1):52-61.Wang Xuejiao,Pan Xuebiao,Chen Chao,et al.Forecasting cotton chilling damage based on COSIM[J].Cotton Science,2012,24(1):52-61.(in Chinese with English abstract)
[29]托丽娜,潘学标,廖要明,等.新疆棉花生产气候风险评估的模型方法初探[J].棉花学报,2005,17(2):122-124.Tuo Lina,Pan Xuebiao,Liao Yaoming,et al.Assessment of climate risk for cotton production in Xinjiang by cotton production regional assessment system[J].Cotton Science,2005,17(2):122-124.(in Chinese with English abstract)
[30]陈超,潘学标,张立祯,等.气候变化对石羊河流域棉花生产和耗水的影响[J].农业工程学报,2011,27(1):57-65.Chen Chao,Pan Xuebiao,Zhang Lizhen,et al.Impact of climate change on cotton production and water consumption in Shiyang River Basin[J].Transactions of the Chinese Society of Agricultural Engineering(Transactions of the CSAE),2011,27(1):57-65.(in Chinese with English abstract)
[31]王雪姣.气候变化对新疆棉花物候、产量和品质的影响与适应措施[D].北京:中国农业大学,2015.Wang Xuejiao.Impact and Adaptation of Climate Change on Cotton Phenology,Yield and Fiber Quality in Xinjiang[D].Beijing:China Agricultural University,2015.(in Chinese with English abstract)