新疆棉花低温冷害动态监测研究
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摘要
[目的]实现新疆棉花冷害大范围动态实时监测,为棉花冷害减灾防灾提供技术支持。[方法]基于星地多源数据,将棉花动态发育期信息、反演的逐日平均气温、棉花冷害监测指标多要素相结合,对2000—2016年新疆棉花播种至五叶期、花铃期冷害动态进行监测。[结果]2003年、2010年、2014年春季,2003年和2009年夏秋季棉花冷害结果与《中国气象年鉴》灾害统计报道的冷害发生时间和位置相符合,与气象站点计算的逐日距平平均值统计规律能够相互印证。所获的逐日平均气温经验证,5个重点监测时段的模拟气温结果与气象站观测结果RMSE分别为1.92、1.96、1.94、1.80、1.86℃,所获日气温模拟精度基本满足冷害监测需求。[结论]该研究建立的冷害监测方法可以实现对新疆棉花大面积低温冷害的同步实时跟踪监测。
[Objective]To realize the large-scale dynamic real-time monitoring of cotton cold damage in Xinjiang and to provide technical support for the disaster reduction and prevention of cotton cold damage.[Method]Based on multi-source data and combined the cotton dynamic development phase information,the daily mean temperature of inversion and cotton cold damage monitoring indicators,this paper completed the dynamic monitoring of cotton cold damage from sowing to five-leaf and flower boll phase in Xinjiang during 2000-2016.[Result]The monitored results of cotton cold damage in spring of 2003,2010 and 2014 and summer and fall season of 2003 and 2009 were consistent with the time and location reported in China statistical yearbook of meteorological disasters,can mutually confirm with the statistical rule of daily anomaly average value calculated by the meteorological station. Estimated temperature by multiple regression equations was validated,the RMSE between the simulation and observation temperature were 1.92,1.96,1.94,1.80 and 1.86 ℃ in five key monitoring time stages, respectively. The obtained simulation accuracy of daily mean temperature basically met the monitoring requirements for cold damage.[Conclusion]The method of cold damage monitoring established in this paper can realize synchronous and real-time monitoring of large-scale cotton cold damage in Xinjiang.
[Objective]To realize the large-scale dynamic real-time monitoring of cotton cold damage in Xinjiang and to provide technical support for the disaster reduction and prevention of cotton cold damage.[Method]Based on multi-source data and combined the cotton dynamic development phase information,the daily mean temperature of inversion and cotton cold damage monitoring indicators,this paper completed the dynamic monitoring of cotton cold damage from sowing to five-leaf and flower boll phase in Xinjiang during 2000-2016.[Result]The monitored results of cotton cold damage in spring of 2003,2010 and 2014 and summer and fall season of 2003 and 2009 were consistent with the time and location reported in China statistical yearbook of meteorological disasters,can mutually confirm with the statistical rule of daily anomaly average value calculated by the meteorological station. Estimated temperature by multiple regression equations was validated,the RMSE between the simulation and observation temperature were 1.92,1.96,1.94,1.80 and 1.86 ℃ in five key monitoring time stages, respectively. The obtained simulation accuracy of daily mean temperature basically met the monitoring requirements for cold damage.[Conclusion]The method of cold damage monitoring established in this paper can realize synchronous and real-time monitoring of large-scale cotton cold damage in Xinjiang.
引文
[1] 姜逢清,杨德刚.新疆棉花产量构成要素分析[J].干旱区研究,2003,20(2):104-109.
[2] 邹陈,吉春容,杨举芳,等.北疆棉花阶段性延迟型冷害指标研究[C]//第27届中国气象学会年会现代农业气象防灾减灾与粮食安全分会场论文集.北京:中国气象学会,2010:8.
[3] 张超.积温距平指标在玉米低温冷害监测中的适用性分析[J].内蒙古科技与经济,2017(3):71-73.
[4] 单新兰,卫建国,韩颖娟.GIS和RS支持下宁夏水稻低温冷害监测预警[J].安徽农业科学,2011,39(3):1578-1581.
[5] 何燕,李政,徐世宏,等.GIS在水稻“寒露风”冷害监测预警中的应用[J].灾害学,2012,27(1):68-72.
[6] 程勇翔,王秀珍,郭建平,等.中国南方双季稻春季冷害动态监测[J].中国农业科学,2014,47(24):4790-4804.
[7] 孙欣.基于MODIS数据的东北地区气温反演及玉米冷害监测研究[D].沈阳:沈阳农业大学,2017.
[8] 张丽文.基于GIS和遥感的东北地区水稻冷害风险区划与监测研究[D].杭州:浙江大学,2013.
[9] 张丽文,刘志雄,肖玮钰,等.RS和GIS支持下的全天候气温构建在湖北水稻低温冷害监测中的应用[J].湖北农业科学,2017,56(24):4757-4761,4776.
[10] 张丽文,王秀珍,姜丽霞,等.用MODIS热量指数动态监测东北地区水稻延迟型冷害[J].遥感学报,2015,19(4):690-701.
[11] 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[J].作物学报,2011,37(10):1868-1878.
[12] 陈德.基于遥感和作物模型的东北水稻低温冷害监测评估[D].南京:南京信息工程大学,2017.
[13] 陈斐.长江中下游双季稻低温冷害监测研究[D].南京:南京信息工程大学,2014.
[14] 胡列群,武鹏飞,李新建,等.基于ETM+影像的棉花低温冷害遥感监测方法研究[J].中国农学通报,2011,27(4):459-463.
[15] 林海荣,李章成,周清波,等.基于ETM植被指数和冠层温度差异遥感监测棉花冷害[J].棉花学报,2009,21(4):284-289.
[16] 刘丹,于成龙,杜春英.基于遥感的东北地区水稻延迟型冷害动态监测[J].农业工程学报,2016,32(15):157-164.
[17] 傅玮东.终霜和春季低温冷害对新疆棉花播种期的影响[J].干旱区资源与环境,2001,15(2):38-43.
[18] 傅玮东,李新建,黄慰军.新疆棉花播种-开花期低温冷害的初步判断[J].中国农业气象,2007,28(3):344-346.
[19] 李芳.浅谈农六师低温冷害对棉花生长发育的影响[J].农业与技术,2013,33(1):101.
[20] 李世奎,霍治国,王素艳,等.农业气象灾害风险评估体系及模型研究[J].自然灾害学报,2004,13(1):77-87.
[21] 杨莲梅,李新建.新疆棉花障碍型冷害的天气成因[J].干旱区研究,2006,23(4):609-614.
[22] 程勇翔,潘灼坤,黄敬峰.作物发育期时空格局动态演示程序:2015SR033929[P].2014-08-14.
[23] 毛耀顺.中国气象年鉴[M].北京:气象出版社,2003.
[24] 《中国气象年鉴》编辑部.中国气象年鉴[M].北京:气象出版社,2009.
[25] 刘燕辉.中国气象年鉴[M].北京:气象出版社,2010.
[26] 许小峰.中国气象年鉴[M].北京:气象出版社,2014.
[2] 邹陈,吉春容,杨举芳,等.北疆棉花阶段性延迟型冷害指标研究[C]//第27届中国气象学会年会现代农业气象防灾减灾与粮食安全分会场论文集.北京:中国气象学会,2010:8.
[3] 张超.积温距平指标在玉米低温冷害监测中的适用性分析[J].内蒙古科技与经济,2017(3):71-73.
[4] 单新兰,卫建国,韩颖娟.GIS和RS支持下宁夏水稻低温冷害监测预警[J].安徽农业科学,2011,39(3):1578-1581.
[5] 何燕,李政,徐世宏,等.GIS在水稻“寒露风”冷害监测预警中的应用[J].灾害学,2012,27(1):68-72.
[6] 程勇翔,王秀珍,郭建平,等.中国南方双季稻春季冷害动态监测[J].中国农业科学,2014,47(24):4790-4804.
[7] 孙欣.基于MODIS数据的东北地区气温反演及玉米冷害监测研究[D].沈阳:沈阳农业大学,2017.
[8] 张丽文.基于GIS和遥感的东北地区水稻冷害风险区划与监测研究[D].杭州:浙江大学,2013.
[9] 张丽文,刘志雄,肖玮钰,等.RS和GIS支持下的全天候气温构建在湖北水稻低温冷害监测中的应用[J].湖北农业科学,2017,56(24):4757-4761,4776.
[10] 张丽文,王秀珍,姜丽霞,等.用MODIS热量指数动态监测东北地区水稻延迟型冷害[J].遥感学报,2015,19(4):690-701.
[11] 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[J].作物学报,2011,37(10):1868-1878.
[12] 陈德.基于遥感和作物模型的东北水稻低温冷害监测评估[D].南京:南京信息工程大学,2017.
[13] 陈斐.长江中下游双季稻低温冷害监测研究[D].南京:南京信息工程大学,2014.
[14] 胡列群,武鹏飞,李新建,等.基于ETM+影像的棉花低温冷害遥感监测方法研究[J].中国农学通报,2011,27(4):459-463.
[15] 林海荣,李章成,周清波,等.基于ETM植被指数和冠层温度差异遥感监测棉花冷害[J].棉花学报,2009,21(4):284-289.
[16] 刘丹,于成龙,杜春英.基于遥感的东北地区水稻延迟型冷害动态监测[J].农业工程学报,2016,32(15):157-164.
[17] 傅玮东.终霜和春季低温冷害对新疆棉花播种期的影响[J].干旱区资源与环境,2001,15(2):38-43.
[18] 傅玮东,李新建,黄慰军.新疆棉花播种-开花期低温冷害的初步判断[J].中国农业气象,2007,28(3):344-346.
[19] 李芳.浅谈农六师低温冷害对棉花生长发育的影响[J].农业与技术,2013,33(1):101.
[20] 李世奎,霍治国,王素艳,等.农业气象灾害风险评估体系及模型研究[J].自然灾害学报,2004,13(1):77-87.
[21] 杨莲梅,李新建.新疆棉花障碍型冷害的天气成因[J].干旱区研究,2006,23(4):609-614.
[22] 程勇翔,潘灼坤,黄敬峰.作物发育期时空格局动态演示程序:2015SR033929[P].2014-08-14.
[23] 毛耀顺.中国气象年鉴[M].北京:气象出版社,2003.
[24] 《中国气象年鉴》编辑部.中国气象年鉴[M].北京:气象出版社,2009.
[25] 刘燕辉.中国气象年鉴[M].北京:气象出版社,2010.
[26] 许小峰.中国气象年鉴[M].北京:气象出版社,2014.