天津市武清区日光温室风灾风险时空特征分析
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摘要
利用天津市武清区2009—2016年最大风速资料,基于风灾强度评估模型对武清区日光温室风灾进行风险评估,分析风灾风险空间变化特征。基于风灾时间分布特征参数,分析风灾集中度和集中期。利用2013—2016年日光温室风灾灾情数据,对分析结果进行验证。研究结果表明,近8年武清区日光温室仅出现轻度及中度风灾,所占比例分别为94.55%、5.45%。经验证,武清区日光温室风灾发生时间特征及空间风险区划结果准确。日光温室风灾集中程度具有分化性,中度风灾发生重心较轻度的集中。日光温室风灾重点防御时间为春季。风灾风险指数空间分布差异明显,中部、东部风灾风险指数较大,北部风灾风险指数较小,因此,北部可作为日光温室推广发展重点规划区域。
Using the maximum wind speed data of 2009—2016, based on the assessment model of wind disaster intensity and the characteristic parameters of time distribution, the study evaluated the wind disaster risk of the solar greenhouse, including the degree and the period of concentration of wind disaster risk.The wind hazard data of 2013—2016 in Wuqing district was used to verify the results. According to the results, only slight and moderate wind disasters occurred in the solar greenhouse in Wuqing district, and the proportion was 94.55% and 5.45% respectively in the past eight years. It's verified that the spatial and temporal characteristics of wind hazard of solar greenhouse are accurate. The concentration degree of wind disasters in the solar greenhouse is differentiated, moderate wind disaster is more concentrated than slight disaster. Spring is the key time to prevent the wind disasters on solar greenhouse.Wind disaster risk indices of the spatial distribution were obviously different, the risk indices in the central and the eastern regions were larger than other areas and the risk index in the northern region was relatively smaller. Therefore the north of Wuqing district can be used as a key planning area to develop the solar greenhouse.
Using the maximum wind speed data of 2009—2016, based on the assessment model of wind disaster intensity and the characteristic parameters of time distribution, the study evaluated the wind disaster risk of the solar greenhouse, including the degree and the period of concentration of wind disaster risk.The wind hazard data of 2013—2016 in Wuqing district was used to verify the results. According to the results, only slight and moderate wind disasters occurred in the solar greenhouse in Wuqing district, and the proportion was 94.55% and 5.45% respectively in the past eight years. It's verified that the spatial and temporal characteristics of wind hazard of solar greenhouse are accurate. The concentration degree of wind disasters in the solar greenhouse is differentiated, moderate wind disaster is more concentrated than slight disaster. Spring is the key time to prevent the wind disasters on solar greenhouse.Wind disaster risk indices of the spatial distribution were obviously different, the risk indices in the central and the eastern regions were larger than other areas and the risk index in the northern region was relatively smaller. Therefore the north of Wuqing district can be used as a key planning area to develop the solar greenhouse.
引文
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[2]宫志宏,董朝阳,于红,等.节能型日光温室智能加温控制系统设计[J].中国农业气象,2017,38(6):361-368.
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[9]方翀,王西贵,盛杰,等.华北地区雷暴大风的时空分布及物理量统计特征分析[J].高原气象,2017,36(5):1-18.
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[12]王琼,魏瑞江,王荣英,等.河北日光温室气象灾害影响和气象服务评估[J].中国农业气象,2014,35(6):682-689.
[13]张淑杰,孙立德,马成芝,等.东北日光温室最大风荷载特征及风灾预警指标研究[J].资源科学,2015,37(1):211-218.
[14]杨再强,张波,薛晓萍,等.设施塑料大棚风洞试验及风压分布规律[J].生态学报,2012,32(24):7730-7737.
[15]闫俊月,周磊,周长吉,等.塑料大棚设计中基本风压取值方法[J].农业工程学报,2014,30(12):171-176.
[16]俞海洋,李婷,陈笑娟,等.河北省近30年大风时空分布及成灾特征分析[J].灾害学,2017,32(2):59-63.
[17]阎访,岳艳霞,张秉祥,等.石家庄地区大风日数气候变化特征[J].气象与环境学报,2013,29(2):81-88.
[18]陈思宁,黎贞发,柳芳,等.天津新型日光温室风灾风险评估及区划[J].中国农学通报,2017,33(2):115-120.
[19]王世通.天津市武清区日光温室类型及蔬菜主要茬口效益调查[J].中国蔬菜,2018(4):93-95.
[20]吴春艳,李慧君,叶彩华.北京地区玉米风灾损失定量评估模型研究[J].气象与环境科学,2015,38(1):114-118.
[21]邱博,张录军,谭慧慧.中国大风集中程度及气候趋势研究[J].气象科学,2013,33(5):543-548.
[22]刘贤赵,李嘉竹,宿庆,等.基于集中度与集中期的径流年内分配研究[J].地理科学,2007,27(6):791-795.
[23]苗运玲,张云惠,卓世新,等.东疆地区汛期降水集中度和集中期的时空变化特征[J].干旱气象,2017,35(6):949-956.
[24]杨再强,张婷华,黄海静,等.北方地区日光温室气象灾害风险评价[J].中国农业气象,2013,34(3):342-349.
[25]黄川容.北方日光温室风灾风险分析及预警[D].南京:南京信息工程大学,2012.
[26]陈妮娜,蒋大凯,王瀛,等.辽宁省设施农业大风和暴雪致灾指标[J].江苏农业科学,2013,41(11):386-387.
[27]李宁,李春,韩玥,等.天津市西青区日光温室农业气象灾害分析[J].北方园艺,2017(12):51-54.
[2]宫志宏,董朝阳,于红,等.节能型日光温室智能加温控制系统设计[J].中国农业气象,2017,38(6):361-368.
[3]赵淑兰,李春,张绍祥,等.天津市北辰区设施农业温光气候资源变化分析[J].气象与环境科学,2013,36(1):32-35.
[4]杜子璇,刘忠阳,曹淑超.低温冷害对河南省设施农业的影响分析[J].气象与环境科学,2014,37(1):5-12.
[5]陈宇,吴曼丽,陈艳秋,等.辽宁省大风天气对设施农业的影响[J].江苏农业科学,2015,43(9) :407-409.
[6]郭小芹,刘明春,陈立夫,等.河西东部设施农业风灾指标设计及其特征研究[J].中国农学通报,2016,32(8):122-128.
[7]黄川容,杨再强,刘洪,等.北京日光温室风灾风险分析及区划[J].自然灾害学报,2012,21(3):43-49.
[8]吴紫煜,姚雯,李超,等.京津冀地区中 α尺度飑线过程中大风特征分析及成因初探[J].气象与环境科学,2016,39(2):90-98.
[9]方翀,王西贵,盛杰,等.华北地区雷暴大风的时空分布及物理量统计特征分析[J].高原气象,2017,36(5):1-18.
[10]李艳芳,程胜,吴彬.2012年4月2日华东灾害性飑线大风成因分析[J].气象与环境科学,2014,37(4):59-65.
[11]费海燕,王秀明,周小刚,等.中国强雷暴大风的气候特征和环境参数分析[J].气象,2016,42(12):1513-1521.
[12]王琼,魏瑞江,王荣英,等.河北日光温室气象灾害影响和气象服务评估[J].中国农业气象,2014,35(6):682-689.
[13]张淑杰,孙立德,马成芝,等.东北日光温室最大风荷载特征及风灾预警指标研究[J].资源科学,2015,37(1):211-218.
[14]杨再强,张波,薛晓萍,等.设施塑料大棚风洞试验及风压分布规律[J].生态学报,2012,32(24):7730-7737.
[15]闫俊月,周磊,周长吉,等.塑料大棚设计中基本风压取值方法[J].农业工程学报,2014,30(12):171-176.
[16]俞海洋,李婷,陈笑娟,等.河北省近30年大风时空分布及成灾特征分析[J].灾害学,2017,32(2):59-63.
[17]阎访,岳艳霞,张秉祥,等.石家庄地区大风日数气候变化特征[J].气象与环境学报,2013,29(2):81-88.
[18]陈思宁,黎贞发,柳芳,等.天津新型日光温室风灾风险评估及区划[J].中国农学通报,2017,33(2):115-120.
[19]王世通.天津市武清区日光温室类型及蔬菜主要茬口效益调查[J].中国蔬菜,2018(4):93-95.
[20]吴春艳,李慧君,叶彩华.北京地区玉米风灾损失定量评估模型研究[J].气象与环境科学,2015,38(1):114-118.
[21]邱博,张录军,谭慧慧.中国大风集中程度及气候趋势研究[J].气象科学,2013,33(5):543-548.
[22]刘贤赵,李嘉竹,宿庆,等.基于集中度与集中期的径流年内分配研究[J].地理科学,2007,27(6):791-795.
[23]苗运玲,张云惠,卓世新,等.东疆地区汛期降水集中度和集中期的时空变化特征[J].干旱气象,2017,35(6):949-956.
[24]杨再强,张婷华,黄海静,等.北方地区日光温室气象灾害风险评价[J].中国农业气象,2013,34(3):342-349.
[25]黄川容.北方日光温室风灾风险分析及预警[D].南京:南京信息工程大学,2012.
[26]陈妮娜,蒋大凯,王瀛,等.辽宁省设施农业大风和暴雪致灾指标[J].江苏农业科学,2013,41(11):386-387.
[27]李宁,李春,韩玥,等.天津市西青区日光温室农业气象灾害分析[J].北方园艺,2017(12):51-54.
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