摘要
基于福建省福清站2017—2019年气象站数据及设施大棚同期的小气候数据,分别采用多元线性回归、BP神经网络和极限学习机(ELM)等方法构建设施小气候模拟模型,再用1990—2019年18个气象站的气象数据反演室内小气候数据,结合设施番茄高温高湿等级指标,研究福建省设施番茄高温高湿时空规律。结果表明:多元线性回归模型模拟室内最高气温和最低气温效果最好,RMSE分别为2.19和1.20℃,R^(2)为0.87和0.96;BP神经网络方法模拟最高相对湿度效果最好,RMSE为3.77%,R^(2)为0.65。结合设施作物的灾害指标可知,福建省北部、中部地区二级高温高湿灾害发生频数逐年上升,且增幅显著,中部地区三级灾害发生频数逐年减少;各地出现二级灾害概率较大,北、中部出现一级灾害的概率较小,南部出现三级灾害的概率较小。设施番茄在5—7月遭遇的气象灾害等级较高,分布在西北部;8—10月灾害等级最低,全境大部分为二级,部分沿海地区仅出现一级灾害。本研究结果为设施番茄的气象布局及环境调控提供科学依据。
Based on the meteorological data of Fuqing Station in Fujian Province and the microclimate data of the facility greenhouses from 2017 to 2019,we used multiple linear regression,BP neural network and extreme learning machine(ELM)to construct the simulation models of the facility microclimate.The indoor microclimate data were retrieved from the meteorological data of 18 meteorological stations from 1990 to 2019.Combined with the high temperature and high humidity grade index of facility tomato,we examined the spatial and temporal pattern of high temperature and high humidity of facility tomato in Fujian Province.The results showed that the maximum and minimum indoor air temperatures were best simulated by multiple linear regression model,with RMSE being 2.19 and 1.20℃,and R^(2) being 0.87 and 0.96,respectively.BP neural network method was the best one to simulate the maximum relative humidity,with RMSE being 3.77%and R^(2) being 0.65.Combined with facility crop disaster indicators,the frequency of level-2 high temperature and high humidity disasters in the northern and central regions of Fujian Province significantly increased year by year,while the frequency of level-3 disasters in the central region decreased year by year.The probability of level-2 disasters was high across all regions,the probability of level-1 disasters was small in the north and central regions,and the probability of level-3 disasters was small in the south.The meteorological disaster level of facility tomato was high during May to July,and distributed in the northwest of Fujian.The disaster level was the lowest from August to October,with level 2 in most of the whole province and level 1 only in some coastal areas.The results provide scientific basis for meteorological layout and environmental regulation of facility tomato.
作者
杨柳
张琪
杨再强
陈家金
黄川容
YANG Liu;ZHANG Qi;YANG Zai-qiang;CHEN Jia-jin;HUANG Chuan-rong(Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters,Nanjing University of Information Science and Technology,Nanjing 210044,China;Jiangsu Provincial Key Laboratory of Agrometeorology 9 Nanjing 210044,China;Fujian Meteorological Service Center,Fuzhou 350000,China)
出处
《生态学杂志》
CAS
CSCD
北大核心
2022年第6期1149-1155,共7页
Chinese Journal of Ecology
基金
国家重点研究开发计划(2019YFD1002202)
国家自然科学基金项目(41975142)资助。
关键词
连栋温室
小气候
模拟模型
高温高湿
时空分布
greenhouse
microclimate
simulation model
high temperature and humidity disaster
spatial and temporal distribution