CAJ | 학술논문

[目的]探讨利用WOFOST模型对玉米生物量进行模拟实现动态预报玉米产量的方法.[方法]利用辽宁省1981～2005年气象资料和产量资料采用WOFOST模型对作物生长进行模型模拟和改进,建立玉米生长动力统计预报模型,进行预报检验,并对模拟得到的玉米地上干物重和穗干物重与实际产量进行比较分析.[结果]对玉米穗干物重量与产量的模拟效果在辽宁西部和南部最好,在东部地区一般,中部和北部地区较差.辽宁省西部、南部和东部地区可以用模拟生物量反映实际产量的变化.模拟结果与实际产量对比表明,1981～2005年,模型预报准确率在80%以上的年份占31%以上,最高值出现在岫岩地区,达85%.[结论]模型对辽宁省干旱地区以及正常年份和一般干旱年份玉米产量变化的模拟能力较好,对极端气候年份模拟较差.
[목적]탐토이용WOFOST모형대옥미생물량진행모의실현동태예보옥미산량적방법.[방법]이용요녕성1981～2005년기상자료화산량자료채용WOFOST모형대작물생장진행모형모의화개진,건립옥미생장동력통계예보모형,진행예보검험,병대모의득도적옥미지상간물중화수간물중여실제산량진행비교분석.[결과]대옥미수간물중량여산량적모의효과재료녕서부화남부최호,재동부지구일반,중부화북부지구교차.요녕성서부、남부화동부지구가이용모의생물량반영실제산량적변화.모의결과여실제산량대비표명,1981～2005년,모형예보준학솔재80%이상적년빈점31%이상,최고치출현재수암지구,체85%.[결론]모형대요녕성간한지구이급정상년빈화일반간한년빈옥미산량변화적모의능력교호,대겁단기후년빈모의교차.
[Objective] The study aimed to discuss the method of realizing the dynamic forecast on the maize yield by simulating the maize biomass on base of WOFOST model.[Method]Based on the meteorological data and crop yield data of Liaoning Province during 1981-2005, the crop growth were simulated with WOFOST model and the model was improved to develop a dynamical statistic forecast model for the maize growth, then the model were validated for the forecast of maize yield. The simulated biomass weigh and dry matter weight of ear in maize were compared with the actual maize yield. [Result] The simulating effect of dry matter weight of ear in maize with the maize yield was best in west and south areas in Lioaning Province, that in east area was general and that in middle and north areas was worst. The change of actual yield of maize in west, south and east areas in Liaoning province could be reflected by simulating the maize biomass. The comparisons on the simulated results with the actual yield showed that the years in 1981-2005 in which the model forecast accuracy rate was over 80% accounted for above 31%, with the highest value appeared in Xiuyan area, being 85%.[Conclusion] The model was good at simulating the change of the maize yield in semi-arid region in Liaoning province and as well in common years and in dry years, but it was worst in extreme climate years.