响应气候变化的棉花生长模拟与县域尺度产量评估  

Cotton Growth Simulation and County-Scale Yield Estimation in Response to Climate Change

作　　者：孟文博 王德胜[1,2] 张楠楠 费浩 唐梓涯 王涛 白铁成 MENG Wenbo;WANG Desheng;ZHANG Nannan;FEI Hao;TANG Ziya;WANG Tao;BAI Tiecheng(Southern Xinjiang Research Center for Information Technology in Agriculture,Tarim University,Alaer,Xinjiang 843300;College of Plant Science and Technology,Huazhong Agricultural University,Wuhan,Hubei 430070)

机构地区：[1]塔里木大学南疆农业信息技术研究中心,新疆阿拉尔843300 [2]华中农业大学植物科学与技术学院,湖北武汉430070

出　　处：《核农学报》2021年第7期1648-1657,共10页Journal of Nuclear Agricultural Sciences

基　　金：国家自然科学基金资助项目(61961035、32060259);新疆生产建设兵团科技新星计划项目(2018CB020);自治区研究生科研创新项目(XJ2020G284)。

摘　　要：为评估气象变化对棉花生长和县域尺度产量的影响,使用校正的CROPGRO-Cotton模型实现棉花生长模拟和响应气候变化的年际籽棉产量评估。2018年和2019年的田间试验数据被用于校正和验证CROPGRO-Cotton模型,结果表明校正的CROPGRO-Cotton模型对物候发育期模拟精度较好,出苗期、开花期、结铃期和吐絮期的模拟误差分别为+1、+3、+1和-2 d。模拟的生长期地上总产量(TAGP)和叶面积指数(LAI)与实测值吻合较好,D值为0.99,模拟的RMSE值分别为718 kg·hm^(-2)和0.29 m^(2)·m^(-2),显示了较高的TAGP模拟精度(10%<NRMSE≤20%)和极高的LAI模拟精度(NRMSE≤10%)。2002―2017年南疆19个县的官方统计产量被用于验证模型的区域模拟性能,结果表明,校正的棉花生长模型具有较高的全局估产性能,D值为0.55,NRMSE值为15.8%。不同年际籽棉产量评估的平均D值和NRMSE值分别为0.48和15.6%,不同区域的籽棉产量评估的平均D值和NRMSE值分别为0.44和16.8%,校正的模型均获得了较高的年际和区域产量评估精度(NRMSE≤20%)。研究结果可为分析气候变化对棉花生长和产量的影响提供一种定量分析方法。In order to assess the impact of meteorological changes on cotton growth and county-scale yield, a calibrated CROPGRO-Cotton model for simulating cotton growth and estimating county-level seed cotton yield in response to meteorological changes. Field experimental data in 2018 and 2019 were used to calibrate and validate CROPGRO-Cotton model, respectively. Field validation indicated that calibrated CROPGRO-Cotton model showed good simulation accuracy of phenology development time, with the errors of +1 day, +3 days, +1 day and-2 days for emergence, flowering, boll setting stage and boll opening stage, respectively. Simulated total aboveground production(TAGP) and leaf area index(LAI) during growth periods well agreed with measured values, with a D value of 0.99. RMSE values of simulated versus measured TAGP and LAI were 718 kg·hm^(-2) and 0.29 m^(2)·m^(-2), showing a high modeled accuracy for TAGP(10%<NRMSE≤20%) and extremely high accuracy for LAI(NRMSE≤10%). The official statistical yield of 19 counties from 2002 to 2017 was used to evaluate the accuracy of country-scale cotton yield assessment. Regional verification results showed that the calibrated CROPGRO-Cotton model had achieved high global yield estimation performance, with D of 0.55 and NRMSE of 15.8%. For seed cotton yield estimation of different years, the simulated average D and NRMSE value were equal to 0.48 and 15.6%, respectively. For seed cotton yield estimation of different regions, the simulated average D and NRMSE value were equal to 0.44 and 16.8%, respectively. The corrected models have a high accuracy of inter annual and regional yield assessment(NRMSE≤20%). This study can provide a quantitative analysis method for analyzing the impact of climate changes on cotton growth and yield.

关 键 词：棉花 CROPGRO-Cotton 气候变化 产量估算 生长模拟 

分 类 号：S562[农业科学—作物学] S162.54