删除或更新信息,请邮件至freekaoyan#163.com(#换成@)

基于危险性评估的福建省茶叶寒冻害保险费率厘定

本站小编 Free考研考试/2022-01-01

陶红超1,,
陈家金2, 3,,,
陈志彪1,
黄川容2,
孙朝锋2,
吴立2
1.福建师范大学湿润亚热带生态地理过程教育部重点实验室/福建师范大学地理科学学院 福州 350007
2.福建省气象服务中心 福州 350001
3.福建省灾害天气重点实验室 福州 350001
基金项目: 福建省科技计划项目2018Y0002
福建省科技计划项目2019Y01010202

详细信息
作者简介:陶红超, 主要从事自然地理研究。E-mail:463687964@qq.com
通讯作者:陈家金, 主要从事农业气象灾害风险研究。E-mail:cjj8284@163.com
中图分类号:F840.66

计量

文章访问数:134
HTML全文浏览量:11
PDF下载量:122
被引次数:0
出版历程

收稿日期:2020-03-15
录用日期:2020-07-02
刊出日期:2020-11-01

Determination of premium rates for tea cold-frost damage in Fujian Province based on risk assessment

TAO Hongchao1,,
CHEN Jiajin2, 3,,,
CHEN Zhibiao1,
HUANG Chuanrong2,
SUN Chaofeng2,
WU Li2
1. Key Laboratory for Humid Subtropical Eco-geographical Processes of the Ministry of Education, Fujian Normal University/College of Geographical Sciences, Fujian Normal University, Fuzhou 350007, China
2. Fujian Meteorological Service Center, Fuzhou 350001, China
3. Fujian Key Laboratory of Severe Weather, Fuzhou 350001, China
Funds: Science and Technology Project of Fujian Province2018Y0002
Science and Technology Project of Fujian Province2019Y01010202

More Information
Corresponding author:CHEN Jiajin, E-mail:cjj8284@163.com


摘要
HTML全文
(1)(5)
参考文献(38)
相关文章
施引文献
资源附件(0)
访问统计

摘要
摘要:为了提高福建省复杂地形下不同风险区的茶叶寒冻害保险费率设计的合理性,首先利用福建省历年气象数据、茶叶产量和灾情资料,计算茶叶不同寒冻害等级的减产率和出现概率,以此确定不同县域的茶叶寒冻害保险纯费率及基准费率,再结合寒冻害危险性区划,确定不同风险区域不同触发条件下的区域保险费率。结果表明:福建省茶叶在极端低温4℃以下的保险触发条件下,西北部区域海拔200 m以下、200~600 m、600~900 m和900 m以上地域保险费率分别为1.4%、4.5%、7.2%和10.2%;东北部区域海拔200 m以下、200~600 m、600~900 m和900 m以上的地域保险费率分别为0.9%、2.6%、4.8%和6.4%;西南部区域海拔300 m以下、300~700 m、700~1 100 m和1 100 m以上的地域保险费率分别为0.5%、2.3%、4.0%和5.5%;东南部区域海拔300 m以下、300~700 m、700~1 100 m和1 100 m以上的地域保险费率分别为0.5%、1.9%、3.9%和5.4%。总体上看,区域保险费率随着地理位置北移和海拔高度的增加而增加,研究成果可为福建省茶叶寒冻害指数保险产品的设计提供费率精算的技术支持。
关键词:茶叶保险/
寒冻害/
危险性区划/
差异费率
Abstract:The aim of this study was to improve the rationale of the premium damage insurance rate design for cold-frost damage in tea plants from different risk areas in Fujian Province. In doing so, we first calculated the tea yield decrement rate, both grade and probability of cold-frost damage occurrence by using historical data, so as to determine the pure rate and benchmark rate of cold-frost damage insurance for tea within each county of Fujian Province. Then, we determined the regional premium damage insurance rates for the conditions of each risk area and different triggers, combined with the cold-frost damage risk zoning area. The results showed that under the trigger condition for tea plants damage in Fujian Province, i.e., extremely low temperatures below 4℃, the regional premium damage insurance rates were 1.4%, 4.5%, 7.2%, and 10.2%, respectively, in the northwest area for < 200 m, 200-600 m, 600-900 m, and >900 m altitudes. At the same time, the regional premium damage insurance rates were 0.9%, 2.6%, 4.8%, and 6.4%, respectively, in the northeast area for < 200 m, 200-600 m, 600-900 m, and >900 m altitudes. The regional premium damage insurance rates were 0.5%, 2.3%, 4.0%, and 5.5%, respectively, in the southwest area for < 300 m, 300-700 m, 700-1 100 m, and >1 100 m altitudes. Moreover, the regional premium rates were 0.5%, 1.9%, 3.9%, and 5.4%, respectively, in the southeast area for < 300 m, 300-700 m, 700-1 100 m, and >1 100 m altitudes. In general, the regional premium damage insurance rate increased with latitude and altitude. These results can provide technical support for the actuarial calculation of the premium damage insurance rate in relation to the design of insurance products for the cold-frost damage index of tea plants in Fujian Province.
Key words:Tea insurance/
Cold-frost damage/
Risk division/
Differential rate

HTML全文


图1福建省茶叶寒冻害危险性区划
Figure1.Division of risk of tea cold-frost damage in Fujian Province


下载: 全尺寸图片幻灯片

表1茶叶不同等级寒冻害的平均减产率及出现概率
Table1.Average yield reduction rates and occurrence probabilities of different grades of tea cold-frost damage
区域
Region
站点
Station
平均减产率 Average yield reduction rate (%)寒冻害出现概率 Probability of cold-frost damage (%)
极端最低温度 Extrememinimum temperature (℃)
(3, 4](2, 3](1, 2](0, 1](-1, 0](-2, -1](-∞, -2](3, 4](2, 3](1, 2](0, 1](-1, 0](-2, -1](-∞, -2]
西北部
Northwest
建瓯 Jian’ou 0.4 0.6 0.8 1.0 ??1.2 ??1.4 ??1.5 16.7 22.9 ??8.3 12.5 ??4.2 ??2.1 ??6.3
建阳 Jianyang 0.6 1.0 1.4 1.8 ??2.3 ??2.7 ??2.9 18.8 12.5 10.4 10.4 14.6 ??4.2 ??6.3
延平 Yanping 5.5 6.4 7.4 8.3 ??9.2 10.2 10.7 ??6.3 ??6.3 10.4 ??2.1 ??0.0 ??4.2 ??0.0
邵武 Shaowu 0.6 1.7 2.9 4.0 ??5.2 ??6.3 ??6.9 14.6 10.4 10.4 10.4 14.6 10.4 10.4
顺昌 Shunchang 0.9 1.4 1.9 2.4 ??3.0 ??3.5 ??3.8 27.1 10.4 ??4.2 10.4 ??8.3 ??2.1 ??4.2
沙县 Shaxian 1.7 2.4 3.2 3.9 ??4.7 ??5.4 ??5.8 22.9 ??2.1 14.6 ??4.2 ??4.2 ??2.1 ??4.2
永安 Yong’an 4.4 4.8 5.2 5.6 ??6.1 ??6.5 ??6.7 16.7 ??4.2 ??8.3 ??4.2 ??6.3 ??0.0 ??4.2
三明辖区 Sanming District 3.8 5.9 7.9 9.9 12.0 14.0 15.0 16.7 ??4.2 ??8.3 ??4.2 ??6.3 ??2.1 ??0.0
浦城 Pucheng 1.1 1.5 1.8 2.1 ??2.4 ??2.8 ??2.9 ??6.3 16.7 14.6 20.8 20.8 ??2.1 10.4
松溪 Songxi 1.0 2.4 3.7 5.1 ??6.5 ??7.9 ??8.6 ??6.3 16.7 20.8 14.6 14.6 ??2.1 ??8.3
武夷山 Wuyishan 2.9 3.4 4.0 4.5 ??5.0 ??5.5 ??5.8 ??8.3 12.5 25.0 16.7 ??8.3 ??4.2 ??8.3
政和 Zhenghe 3.3 4.7 6.1 7.5 ??8.9 10.3 11.0 ??7.0 23.3 20.9 11.6 ??7.0 ??4.7 ??2.3
建宁 Jianning 0.9 1.8 2.8 3.7 ??4.6 ??5.6 ??6.1 10.4 14.6 ??6.3 16.7 18.8 ??2.1 27.1
明溪 Mingxi 3.1 4.5 5.9 7.4 ??8.8 10.2 10.9 14.6 14.6 14.6 12.5 16.7 ??4.2 12.5
宁化 Ninghua 2.6 3.3 4.0 4.7 ??5.4 ??6.1 ??6.4 12.5 10.4 14.6 18.8 10.4 14.6 10.4
清流 Qingliu 0.7 1.1 1.5 1.9 ??2.3 ??2.7 ??2.9 12.5 12.5 22.9 ??6.3 12.5 ??2.1 12.5
泰宁 Taining 4.1 5.1 6.1 7.0 ??8.0 ??9.0 ??9.5 16.7 14.6 16.7 12.5 ??6.3 14.6 12.5
将乐 Jiangle 2.4 4.5 6.7 8.9 11.0 13.2 14.3 20.8 10.4 10.4 ??6.3 ??2.1 ??4.2 ??6.3
光泽 Guangze 2.0 2.9 3.8 4.8 ??5.7 ??6.6 ??7.1 ??8.3 14.6 10.4 12.5 14.6 10.4 20.8
均值 Average 2.2 3.1 4.1 5.0 ??5.9 ??6.8 ??7.3 13.9 12.3 13.3 10.9 10.0 ??4.9 ??8.8
东北部
Northeast
连江 Lianjiang 4.3 5.3 6.2 7.1 ??8.0 ??8.9 ??9.4 20.8 ??4.2 ??8.3 ??2.1 ??4.2 ??0.0 ??0.0
罗源 Luoyuan 3.9 4.8 5.7 6.6 ??7.6 ??8.5 ??9.0 20.8 ??6.3 ??6.3 ??6.3 ??2.1 ??0.0 ??0.0
闽侯 Minhou 1.7 2.0 2.3 2.7 ??3.0 ??3.4 ??3.6 12.5 ??4.2 ??4.2 ??4.2 ??0.0 ??0.0 ??0.0
闽清 Minqing 4.4 5.5 6.5 7.5 ??8.6 ??9.6 10.1 22.9 ??4.2 10.4 ??4.2 ??2.1 ??0.0 ??2.1
永泰 Yongtai 2.4 3.1 3.9 4.6 ??5.3 ??6.1 ??6.5 16.7 18.8 ??4.2 10.4 ??2.1 ??2.1 ??2.1
福安 Fu’an 4.2 5.4 6.7 8.0 ??9.3 10.6 11.2 ??8.3 14.6 10.4 ??4.2 ??2.1 ??0.0 ??2.1
福鼎 Fuding 1.1 1.6 2.1 2.6 ??3.1 ??3.6 ??3.8 22.9 25.0 10.4 ??6.3 ??4.2 ??2.1 ??2.1
蕉城 Jiaocheng 3.6 4.6 5.6 6.6 ??7.6 ??8.6 ??9.1 10.4 ??6.3 ??2.1 ??2.1 ??0.0 ??0.0 ??0.0
霞浦 Xiapu 1.2 1.8 2.3 2.9 ??3.4 ??4.0 ??4.2 22.9 12.5 ??4.2 ??6.3 ??0.0 ??0.0 ??0.0
古田 Gutian 2.2 3.1 4.0 4.9 ??5.8 ??6.7 ??7.1 16.7 18.8 14.6 ??8.3 ??2.1 ??6.3 ??2.1
大田 Datian 3.5 4.3 5.0 5.8 ??6.6 ??7.3 ??7.7 18.8 16.7 ??8.3 ??2.1 ??4.2 ??2.1 ??4.2
尤溪 Youxi 3.3 5.1 6.8 8.6 10.3 12.1 13.0 12.5 16.7 ??4.2 12.5 ??4.2 ??0.0 ??6.3
德化 Dehua 1.6 2.7 3.9 5.0 ??6.2 ??7.4 ??7.9 12.5 18.8 14.6 ??8.3 ??4.2 ??6.3 ??2.1
屏南 Pingnan 0.4 0.6 0.9 1.2 ??1.5 ??1.8 ??1.9 ??2.1 ??2.1 14.6 14.6 22.9 18.8 25.0
寿宁 Shouning 0.1 0.7 1.3 1.9 ??2.5 ??3.1 ??3.4 ??0.0 ??0.0 14.6 14.6 25.0 20.8 25.0
柘荣 Zherong 1.0 1.6 2.1 2.7 ??3.3 ??3.9 ??4.2 ??0.0 ??4.2 16.7 25.0 22.9 14.6 16.7
周宁 Zhouning 1.1 1.2 1.3 1.5 ??1.6 ??1.7 ??1.8 ??0.0 ??2.1 10.4 25.0 18.8 22.9 20.8
均值 Average 2.3 3.1 3.9 4.7 ??5.5 ??6.3 ??6.7 13.0 10.3 ??9.3 ??9.2 ??7.1 ??5.6 ??6.5
西南部
Southwest
华安 Hua’an 3.7 4.4 5.1 5.8 ??6.5 ??7.2 ??7.6 ??8.3 ??2.1 ??2.1 ??2.1 ??4.2 ??0.0 ??0.0
南靖 Nanjing 3.3 3.8 4.3 4.8 ??5.3 ??5.9 ??6.1 ??6.3 ??4.2 ??4.2 ??4.2 ??0.0 ??0.0 ??0.0
连城 Liancheng 5.8 6.4 7.0 7.7 ??8.3 ??8.9 ??9.2 18.8 20.8 12.5 ??2.1 ??4.2 ??6.3 ??2.1
新罗 Xinluo 4.2 5.0 5.8 6.5 ??7.3 ??8.1 ??8.5 18.8 ??2.1 ??4.2 ??2.1 ??6.3 ??0.0 ??0.0
上杭 Shanghang 0.7 0.8 1.0 1.2 ??1.4 ??1.6 ??1.7 10.4 ??6.3 ??6.3 ??2.1 ??4.2 ??2.1 ??0.0
武平 Wuping 1.1 1.4 1.6 1.9 ??2.1 ??2.4 ??2.5 14.6 14.6 14.6 ??2.1 ??4.2 ??0.0 ??4.2
永定 Yongding 1.6 2.0 2.4 2.8 ??3.2 ??3.6 ??3.8 10.4 10.4 ??2.1 ??4.2 ??4.2 ??4.2 ??0.0
漳平 Zhangping 1.8 2.3 2.8 3.3 ??3.8 ??4.2 ??4.5 10.4 ??6.3 ??4.2 ??4.2 ??2.1 ??2.1 ??2.1
长汀 Changting 2.7 3.5 4.4 5.3 ??6.2 ??7.1 ??7.5 10.4 14.6 16.7 12.5 12.5 ??2.1 ??8.3
均值 Average 2.8 3.3 3.8 4.4 ??4.9 ??5.4 ??5.7 12.0 ??9.0 ??7.4 ??3.9 ??4.6 ??1.9 ??1.9
东南部
Southeast
福清 Fuqing 1.1 1.3 1.5 1.7 ??1.9 ??2.1 ??2.2 ??4.2 ??2.1 ??2.1 ??2.1 ??0.0 ??0.0 ??0.0
长乐 Changle 2.4 3.1 3.8 4.5 ??5.2 ??5.9 ??6.2 14.6 ??2.1 ??2.1 ??0.0 ??2.1 ??0.0 ??0.0
莆田 Putian 3.5 4.1 4.6 5.1 ??5.7 ??6.2 ??6.5 ??4.2 ??4.2 ??2.1 ??2.1 ??0.0 ??0.0 ??0.0
仙游 Xianyou 3.9 4.0 4.2 4.3 ??4.4 ??4.5 ??4.6 ??4.2 ??8.3 ??4.2 ??2.1 ??0.0 ??0.0 ??0.0
安溪 Anxi 4.1 4.8 5.5 6.1 ??6.8 ??7.5 ??7.9 ??4.2 ??2.1 ??4.2 ??0.0 ??0.0 ??0.0 ??0.0
南安 Nan’an 1.9 2.1 2.4 2.7 ??3.0 ??3.3 ??3.4 ??4.2 ??4.2 ??2.1 ??0.0 ??0.0 ??0.0 ??0.0
永春 Yongchun 1.4 1.7 2.1 2.5 ??2.9 ??3.3 ??3.5 ??6.3 ??4.2 ??4.2 ??6.3 ??0.0 ??0.0 ??0.0
惠安 Hui’an 4.4 5.1 5.8 6.6 ??7.3 ??8.0 ??8.4 ??0.0 ??0.0 ??2.1 ??0.0 ??0.0 ??0.0 ??0.0
泉州辖区
Quanzhou District
5.8 6.6 7.4 8.2 ??9.1 ??9.9 10.3 ??2.1 ??2.1 ??0.0 ??0.0 ??0.0 ??0.0 ??0.0
厦门 Xiamen 3.8 4.7 5.5 6.4 ??7.2 ??8.1 ??8.5 ??0.0 ??2.1 ??0.0 ??0.0 ??0.0 ??0.0 ??0.0
平和 Pinghe 2.3 2.8 3.2 3.7 ??4.1 ??4.6 ??4.8 ??8.3 ??6.3 ??0.0 ??4.2 ??0.0 ??0.0 ??0.0
长泰 Changtai 3.4 4.1 4.7 5.4 ??6.0 ??6.7 ??7.0 ??2.1 ??4.2 ??2.1 ??0.0 ??0.0 ??0.0 ??0.0
诏安 Zhao’an 3.1 3.8 4.5 5.2 ??5.8 ??6.5 ??6.8 ??6.3 ??2.1 ??2.1 ??0.0 ??0.0 ??0.0 ??0.0
龙海 Longhai 2.9 3.1 3.3 3.5 ??3.7 ??3.9 ??4.0 ??0.0 ??6.3 ??0.0 ??0.0 ??0.0 ??0.0 ??0.0
云霄 Yunxiao 6.4 7.2 8.0 8.7 ??9.5 10.3 10.7 ??6.3 ??0.0 ??0.0 ??0.0 ??0.0 ??0.0 ??0.0
漳浦 Zhangpu 3.0 3.4 3.9 4.4 ??4.9 ??5.3 ??5.6 ??4.2 ??0.0 ??2.1 ??0.0 ??0.0 ??0.0 ??0.0
漳州辖区
Zhangzhou District
3.9 4.6 5.4 6.1 ??6.9 ??7.6 ??8.0 ??2.1 ??4.2 ??0.0 ??0.0 ??0.0 ??0.0 ??0.0
福州辖区
Fuzhou District
1.4 1.4 1.5 1.5 ??1.6 ??1.6 ??1.6 10.4 ??4.2 ??4.2 ??0.0 ??0.0 ??0.0 ??0.0
均值 Average 3.3 3.8 4.3 4.8 ??5.3 ??5.9 ??6.1 ??4.6 ??3.2 ??1.9 ??0.9 ??0.1 ??0.0 ??0.0


下载: 导出CSV
表2福建省各区域茶叶寒冻害保险平均纯费率及基准保险费率
Table2.Average premium rate and benchmark premium rate for tea cold-frost damage insurance in Fujian Province
区域
Region
纯费率
Pure rate (%)
基准保险费率
Benchmark insurance rate (%)
西北部 Northwest 3.13 4.47
东北部 Northeast 2.08 2.98
西南部 Southwest 1.61 2.29
东南部 Southeast 0.34 0.49
福建省 Fujian Province 1.83 2.62


下载: 导出CSV
表3福建省茶叶寒冻害风险等级指标及权重
Table3.Index and weight of risk grade of tea cold-frost damage in Fujian Province
表征指标
Indicator
风险等级 Risk level
轻度 Mild 中度 Moderate 重度 Severe 严重 Most serious
极端最低气温
Extreme minimum temperature (Td, ℃)
2 < Td≤4 0 < Td≤2 -2 < Td≤0 Td≤-2
指标权重 Index weight 0.108 9 0.173 4 0.269 2 0.448 5


下载: 导出CSV
表4福建省茶叶寒冻害不同风险区危险性指数均值及区域风险订正系数
Table4.Mean value of risk index and correction coefficient of regional risk in different risk areas of tea cold-frost damage of Fujian Province
项目
Project
区域
Region
海拔高度 Altitude (m) 区域
Region
海拔高度 Altitude (m)
< 200 200~600 600~900 > 900 < 300 300~700700~1 100 > 1 100
指数均值
Average of index
西北部
Northwest
0.15 0.49 0.80 1.13 西南部
Southwest
0.11 0.46 0.80 1.10
订正系数
Correction coefficient
0.31 1.00 1.62 2.29 0.24 1.00 1.74 2.41
指数均值
Average of index
东北部
Northeast
0.15 0.45 0.81 1.08 东南部
Southeast
0.10 0.38 0.78 1.08
订正系数
Correction coefficient
中低海拔县
Middle and low altitude county
0.33 1.00 1.81 2.42 1.00 3.93 8.01 11.05
高海拔县
High altitude county
0.18 0.55 1.00 1.34


下载: 导出CSV
表5福建省茶叶寒冻害不同区域不同触发条件下的区域保险费率
Table5.Regional premium rates of tea cold-frost damage under different trigger conditions in different regions of Fujian Province ?%
触发条件
Trigger condition (Td) (℃)
区域
Region
海拔高度 Altitude (m) 区域
Region
海拔高度 Altitude (m)
< 200 200~600 600~900 > 900 < 300 300~700700~1 100 > 1 100
Td≤4 西北部
Northwest
1.37 4.47 7.24 10.24 西南部
Southwest
0.54 2.29 3.98 5.52
Td≤3 1.25 4.05 6.57 9.30 0.42 1.78 3.09 4.28
Td≤2 1.09 3.55 5.76 8.15 0.32 1.33 2.32 3.21
Td≤1 0.86 2.78 4.51 6.37 0.22 0.92 1.60 2.22
Td≤0 0.64 2.08 3.37 4.76 0.16 0.67 1.16 1.60
Td≤-1 0.41 1.33 2.16 3.05 0.08 0.32 0.55 0.76
Td≤-2 0.25 0.83 1.34 1.90 0.04 0.16 0.28 0.39
Td≤4 东北部
Northeast
0.87 2.64 4.78 6.39 东南部
Southeast
0.49 1.93 3.93 5.43
Td≤3 0.70 2.12 3.84 5.13 0.30 1.19 2.42 3.35
Td≤2 0.54 1.63 2.95 3.95 0.15 0.58 1.18 1.62
Td≤1 0.39 1.19 2.16 2.88 0.05 0.20 0.41 0.57
Td≤0 0.25 0.76 1.38 1.84 0.01 0.03 0.07 0.09
Td≤-1 0.16 0.48 0.87 1.17 0.00 0.00 0.00 0.00
Td≤-2 0.10 0.29 0.52 0.70 0.00 0.00 0.00 0.00


下载: 导出CSV

参考文献(38)
[1]赵慧.福建茶产业发展现状与对策建议[J].发展研究, 2018, (6):71-76 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=fzyj201806014
ZHAO H. Development status and countermeasures of Fujian tea industry[J]. Development Research, 2018, (6):71-76 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=fzyj201806014
[2]福建省统计局.福建统计年鉴[M].北京:中国统计出版社, 2019
Fujian Bureau of Statistics. Fujian Statistical Yearbook[M]. Beijing:China Statistics Press, 2019
[3]尤志明, 杨如兴, 张文锦, 等.不同农艺措施对茶树冻害后产量恢复的影响初报[J].茶叶科学技术, 2010, (2):1-2 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=cykxjs201002001
YOU Z M, YANG R X, ZHANG W J, et al. Preliminary report on the effects of different agronomic measures on the yield recovery of tea trees after freezing damage[J]. Tea Science and Technology, 2010, (2):1-2 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=cykxjs201002001
[4]王春乙, 张继权, 霍治国, 等.农业气象灾害风险评估研究进展与展望[J].气象学报, 2015, 73(1):1-19 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=qxxb201501001
WANG C Y, ZHANG J Q, HUO Z G, et al. Prospects and progresses in the research of risk assessment of agro-meteorological disasters[J]. Acta Meteorologica Sinica, 2015, 73(1):1-19 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=qxxb201501001
[5]陈家金, 黄川容, 孙朝锋, 等.福建省茶叶气象灾害致灾危险性区划与评估[J].自然灾害学报, 2018, 27(1):198-207 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=zrzhxb201801023
CHEN J J, HUANG C R, SUN C F, et al. Disaster-causing hazard division and evaluation of meteorological disasters for tea in Fujian Province[J]. Journal of Natural Disasters, 2018, 27(1):198-207 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=zrzhxb201801023
[6]宋博, 穆月英, 侯玲玲, 等.基于CVW的我国农业气象指数保险支付意愿分析——以浙江柑橘种植户为例[J].保险研究, 2014, (2):54-63
SONG B, MU Y Y, HOU L L, et al. Analysis on willingness to pay for agricultural weather index insurance in China based on CVM:A case study on citrus growers in Zhejiang Province[J]. Insurance Studies, 2014, (2):54-63
[7]匡昕, 陈嵘徐.油桃冻害气象指数保险设计[J].浙江农业学报, 2014, 26(6):1660-1666 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=zjnyxb201406044
KUANG X, CHEN R X. Design of weather-based index insurance contract for nectarine freezing[J]. Acta Agriculturae Zhejiangensis, 2014, 26(6):1660-1666 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=zjnyxb201406044
[8]周军伟, 董放, 陈盛伟.低温冻害气象指数保险研究综述[J].山东农业大学学报:社会科学版, 2014, 16(1):73-78 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=sdnydxxb-shkxb201401015
ZHOU J W, DONG F, CHEN S W. Review of research on cryogenic injury meteorological index insurance[J]. Journal of Shandong Agricultural University:Social Science Edition, 2014, 16(1):73-78 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=sdnydxxb-shkxb201401015
[9]朱俊生.中国天气指数保险试点的运行及其评估——以安徽省水稻干旱和高温热害指数保险为例[J].保险研究, 2011, (3):19-25 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=bxyj201103002
ZHU J S. The pilot operation of the weather index insurance and its appraisal-Using Anhui rice drought and high temperature disaster index insurance as an example[J]. Insurance Studies, 2011, (3):19-25 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=bxyj201103002
[10]TEIXEIRA E I, FISCHER G, VAN VELTHUIZEN H, et al. Global hot-spots of heat stress on agricultural crops due to climate change[J]. Agricultural and Forest Meteorology, 2013, 170:206-215 doi: 10.1016/j.agrformet.2011.09.002
[11]CHEN S L, MIRANDA M J. Modeling Texas dryland cotton yields, with application to crop insurance actuarial rating[J]. Journal of Agricultural and Applied Economics, 2008, 40(1):239-252 doi: 10.1017/S107407080002808X
[12]姜会飞.农业保险费率和保费的计算方法研究[J].中国农业大学学报, 2009, 14(6):109-117 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=zgnydxxb200906020
JIANG H F. A new method for calculating fair crop yield premium rate and premium[J]. Journal of China Agricultural University, 2009, 14(6):109-117 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=zgnydxxb200906020
[13]OZAKI V A, GOODWIN B K, SHIROTA R. Parametric and nonparametric statistical modelling of crop yield:Implications for pricing crop insurance contracts[J]. Applied Economics, 2008, 40(9):1151-1164 doi: 10.1080/00036840600749680
[14]TURVEY C G, WEERSINK A, CELIA CHIANG S H. Pricing weather insurance with a random strike price:The Ontario ice-wine harvest[J]. American Journal of Agricultural Economics, 2006, 88(3):696-709 doi: 10.1111/j.1467-8276.2006.00889.x
[15]MARLETTO V, VENTURA F, FONTANA G, et al. Wheat growth simulation and yield prediction with seasonal forecasts and a numerical model[J]. Agricultural and Forest Meteorology, 2007, 147(1/2):71-79
[16]LU Y, RAMIREZ O A, REJESUS R M, et al. Empirically evaluating the flexibility of the Johnson family of distributions:A crop insurance application[J]. Agricultural and Resource Economics Review, 2008, 37(1):79-91 doi: 10.1017/S1068280500002161
[17]曲思邈, 王冬妮, 郭春明, 等.玉米干旱天气指数保险产品设计——以吉林省为例[J].气象与环境学报, 2018, 34(2):92-99 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=lnqx201802012
QU S M, WANG D N, GUO C M, et al. Insurance product design based on maize drought weather index:A case study in Jilin Province[J]. Journal of Meteorology and Environment, 2018, 34(2):92-99 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=lnqx201802012
[18]屈振江, 周广胜.中国产区苹果越冬冻害的风险评估[J].自然资源学报, 2017, 32(5):829-840 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=zrzyxb201705010
QU Z J, ZHOU G S. The risk assessment of winter injury in main apple-producing regions of China[J]. Journal of Natural Resources, 2017, 32(5):829-840 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=zrzyxb201705010
[19]王丽红, 杨汭华, 田志宏, 等.非参数核密度法厘定玉米区域产量保险费率研究——以河北安国市为例[J].中国农业大学学报, 2007, 12(1):90-94 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=zgnydxxb200701019
WANG L H, YANG R H, TIAN Z H, et al. Maize GRP rate of premium deciding by nonprarametric kernel density:A case study on Anguo City, Hebei Province[J]. Journal of China Agricultural University, 2007, 12(1):90-94 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=zgnydxxb200701019
[20]金志凤, 胡波, 严甲真, 等.浙江省茶叶农业气象灾害风险评价[J].生态学杂志, 2014, 33(3):771-777 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=stxzz201403031
JIN Z F, HU B, YAN J Z, et al. Agro-meteorological disaster risk evaluation of tea planting in Zhejiang Province[J]. Chinese Journal of Ecology, 2014, 33(3):771-777 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=stxzz201403031
[21]陈超, 庞艳梅, 刘佳.四川省水稻高温热害风险及灾损评估[J].中国生态农业学报(中英文), 2019, 27(4):554-562 http://www.ecoagri.ac.cn/zgstny/ch/reader/view_abstract.aspx?flag=1&file_no=2019-0406&journal_id=zgstny
CHEN C, PANG Y M, LIU J. Assessment of risk and yield loss of rice in Sichuan Province due to heat stress[J]. Chinese Journal of Eco-Agriculture, 2019, 27(4):554-562 http://www.ecoagri.ac.cn/zgstny/ch/reader/view_abstract.aspx?flag=1&file_no=2019-0406&journal_id=zgstny
[22]杨太明, 孙喜波, 刘布春, 等.安徽省水稻高温热害保险天气指数模型设计[J].中国农业气象, 2015, 36(2):220-226 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=zgnyqx201502013
YANG T M, SUN X B, LIU B C, et al. Design on weather indices model for insurance of rice heat damage in Anhui Province[J]. Chinese Journal of Agrometeorology, 2015, 36(2):220-226 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=zgnyqx201502013
[23]王春乙, 张亚杰, 张京红, 等.海南省芒果寒害气象指数保险费率厘定及保险合同设计研究[J].气象与环境科学, 2016, 39(1):108-113 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=hnqx201601015
WANG C Y, ZHANG Y J, ZHANG J H, et al. Determination of the premium rate based on the weather indices of chilling injury in mangoes and contract design in Hainan Province[J]. Meteorological and Environmental Sciences, 2016, 39(1):108-113 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=hnqx201601015
[24]LOU W P, QIU X F, WU L H, et al. Scheme of weather-based indemnity indices for insuring against freeze damage to citrus orchards in Zhejiang, China[J]. Agricultural Sciences in China, 2009, 8(11):1321-1331 doi: 10.1016/S1671-2927(08)60344-2
[25]娄伟平, 吴利红, 陈华江, 等.柑橘气象指数保险合同费率厘定分析及设计[J].中国农业科学, 2010, 43(9):1904-1911 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=zgnykx201009017
LOU W P, WU L H, CHEN H J, et al. Analysis and design of premium rates determined for weather-based index insurance contract of citrus[J]. Scientia Agricultura Sinica, 2010, 43(9):1904-1911 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=zgnykx201009017
[26]陈盛伟, 李彦.区域性苹果低温冻害气象指数保险产品设计——以山东省栖霞市为例[J].保险研究, 2015, (12):78-87 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=667770445
CHEN S W, LI Y. Meteorological index insurance design for regional apple low temperature freezing disaster:With a case study of Qixia City in Shandong Province[J]. Insurance Studies, 2015, (12):78-87 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=667770445
[27]孙擎, 杨再强, 殷剑敏, 等.江西早稻高温逼熟气象灾害指数保险费率的厘定[J].中国农业气象, 2014, 35(5):561-566 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=zgnyqx201405013
SUN Q, YANG Z Q, YIN J M, et al. Estimation of premium rates of high temperature disaster for early rice in Jiangxi[J]. Chinese Journal of Agrometeorology, 2014, 35(5):561-566 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=zgnyqx201405013
[28]杨平, 张丽娟, 赵艳霞, 等.黄淮海地区夏玉米干旱风险评估与区划[J].中国生态农业学报, 2015, 25(1):110-118 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=stnyyj201501014
YANG P, ZHANG L J, ZHAO Y X, et al. Risk assessment and zoning of drought for summer maize in the Huang-Huai-Hai Region[J]. Chinese Journal of Eco-Agriculture, 2015, 25(1):110-118 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=stnyyj201501014
[29]陈家金, 王加义, 黄川容, 等.福建省引种台湾青枣的寒冻害风险分析与区划[J].中国生态农业学报, 2013, 21(12):1537-1544 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=stnyyj201312012
CHEN J J, WANG J Y, HUANG C R, et al. Risk analysis and regionalization of cold and freezing damage to Taiwan-based Zizyphus mauritiana in Fujian Province[J]. Chinese Journal of Eco-Agriculture, 2013, 21(12):1537-1544 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=stnyyj201312012
[30]张宗军.基于综合风险区划的农作物产量指数保险费率厘定——以大豆为例[J].东北农业大学学报:社会科学版, 2016, 14(4):1-6 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=dbnydxxb-shkxb201604001
ZHANG Z J. Determination of insurance premium rate of crop yield index based on comprehensive risk zoning:Taking soybean as an example[J]. Journal of Northeast Agricultural University:Social Science Edition, 2016, 14(4):1-6 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=dbnydxxb-shkxb201604001
[31]徐建华.现代地理学中的数学方法[M].北京:高等教育出版社, 2004:224-250
XU J H. Mathematic Methods for Modern Geography[M]. Beijing:Higher Education Press, 2004:224-250
[32]何超, 李萌, 李婷婷, 等.多目标综合评价中四种确定权重方法的比较与分析[J].湖北大学学报:自然科学版, 2016, 38(2):172-178 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=hbdxxb201602015
HE C, LI M, LI T T, et al. Comparison and analysis of the four methods of determining weights in multi-objective comprehensive evaluation[J]. Journal of Hubei University:Natural Science, 2016, 38(2):172-178 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=hbdxxb201602015
[33]陈家金, 王加义, 黄川容, 等.基于AHP-EWM方法的福建省农业气象灾害风险区划[J].自然灾害学报, 2016, 25(3):58-66 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=zrzhxb201603007
CHEN J J, WANG J Y, HUANG C R, et al. Risk division of agro-meteorological disasters in Fujian Province based on AHP-EWM method[J]. Journal of Natural Disasters, 2016, 25(3):58-66 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=zrzhxb201603007
[34]曹雯, 成林, 杨太明, 等.河南省冬小麦拔节-抽穂期干旱天气指数保险研究[J].气象, 2019, 45(2):274-281
CAO W, CHENG L, YANG T M, et al. Study on weather index insurance of drought damage at jointing-heading stage of winter wheat in Henan Province[J]. Meteorological Monthly, 2019, 45(2):274-281
[35]吴荣军, 史继清, 关福来, 等.基于风险区划的农业干旱保险费率厘定——以河北省冬麦区为例[J].气象, 2013, 39(12):1649-1655 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=qx201312014
WU R J, SHI J Q, GUAN F L, et al. Agricultural drought premium ratemaking based on risk zoning for winter wheat region in Hebei Province[J]. Meteorological Monthly, 2013, 39(12):1649-1655 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=qx201312014
[36]刘凯文, 刘可群, 邓爱娟, 等.基于开花期地域差异的中稻高温热害天气指数保险设计[J].中国农业气象, 2017, 38(10):679-688 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=zgnyqx201710007
LIU K W, LIU K Q, DENG A J, et al. Weather index insurance design of middle-season rice heat damage based on regional difference of flowering stage[J]. Chinese Journal of Agrometeorology, 2017, 38(10):679-688 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=zgnyqx201710007
[37]娄伟平, 吉宗伟, 邱新法, 等.茶叶霜冻气象指数保险设计[J].自然资源学报, 2011, 26(12):2050-2060 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=zrzyxb201112006
LOU W P, JI Z W, QIU X F, et al. Design of weather index insurance contact for tea frost[J]. Journal of Natural Resources, 2011, 26(12):2050-2060 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=zrzyxb201112006
[38]张京红, 黄海静, 王春乙, 等.基于产量风险的海南荔枝寒害保险费率研究[J].热带气象学报, 2015, 31(6):862-868 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=rdqxxb201506014
ZHANG J H, HUANG H J, WANG C Y, et al. Study on insurance rates of litchi chilling injury based on production risk in Hainan[J]. Journal of Tropical Meteorology, 2015, 31(6):862-868 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=rdqxxb201506014

相关话题/气象 保险 设计 农业 地理