江苏水稻高温热害气象指数保险风险综合区划
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摘要
以江苏省为例,利用1980-2015年气象资料和水稻观测数据,基于Logistic曲线方程构建高温热害保险气象指数,并分别采用正态分布、正态对数分布和Weibull分布三种参数模型,以及基于信息扩散方法的非参数模型对水稻高温热害发生概率进行拟合。通过拟合优度检验发现,非参数模型可以较好地估算江苏各县水稻孕穗-抽穗扬花阶段高温热害发生概率,进而结合最优拟合模型,考虑农业保险的经营需求,从致灾因子危险性、孕灾环境敏感性、承灾体易损性、防灾减灾能力四个方面出发,确定相应评估指数并构建综合指数,采用聚类分析的方法进行县级水平的水稻高温热害保险风险综合区划。评估分析表明,江苏水稻高温热害保险风险呈现"西南高东北低"的特征,中高风险区是需要依靠农业保险转移风险的重点关注区域。
Taking Jiangsu as an example, based on logistic curve equation, historical meteorological data and rice yield observations from 1980 to 2015 was used to construct the meteorological index of high temperature heat hazard insurance. After that, three parametric models included normal distribution, normal logarithmic distribution and Weibull distribution and non-parametric model based on information diffusion method were used to fit the occurrence probability of high temperature heat damage in rice. Through goodness-of-fit test, it was found that the non-parametric model could better estimate the probability of high temperature heat damage occurred during booting to heading and flowering stages of rice in each county of Jiangsu Province. Furthermore, combined with the optimal fitting model, considering the operational needs of agricultural insurance, the corresponding evaluation index was determined, while the comprehensive index was constructed from four aspects: the risk of disaster-causing factors,the sensitivity of disaster-pregnant environment, the vulnerability of disaster-bearing bodies and the ability of disaster prevention and mitigation. Based on that, cluster analysis was used to carry out the comprehensive risk zoning of high temperature heat injury insurance for rice at county level. Through evaluation and analysis of the zoning result, it was found that the risk of high temperature heat injury insurance of rice in Jiangsu presented the characteristics of "high in the southwest and low in the northeast". At the same time, it also pointed out that the moderate and high risk areas were the key regions which need to rely on agricultural insurance to transfer the risk.
Taking Jiangsu as an example, based on logistic curve equation, historical meteorological data and rice yield observations from 1980 to 2015 was used to construct the meteorological index of high temperature heat hazard insurance. After that, three parametric models included normal distribution, normal logarithmic distribution and Weibull distribution and non-parametric model based on information diffusion method were used to fit the occurrence probability of high temperature heat damage in rice. Through goodness-of-fit test, it was found that the non-parametric model could better estimate the probability of high temperature heat damage occurred during booting to heading and flowering stages of rice in each county of Jiangsu Province. Furthermore, combined with the optimal fitting model, considering the operational needs of agricultural insurance, the corresponding evaluation index was determined, while the comprehensive index was constructed from four aspects: the risk of disaster-causing factors,the sensitivity of disaster-pregnant environment, the vulnerability of disaster-bearing bodies and the ability of disaster prevention and mitigation. Based on that, cluster analysis was used to carry out the comprehensive risk zoning of high temperature heat injury insurance for rice at county level. Through evaluation and analysis of the zoning result, it was found that the risk of high temperature heat injury insurance of rice in Jiangsu presented the characteristics of "high in the southwest and low in the northeast". At the same time, it also pointed out that the moderate and high risk areas were the key regions which need to rely on agricultural insurance to transfer the risk.
引文
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[2]包云轩,刘维,高苹,等.气候变暖背景下江苏省水稻热害发生规律及其对产量的影响[J].中国农业气象,2012,33(2):289-296.Bao Y X,Liu W,Gao P,et al.Study on characteristics of rice heat damages in Jiangsu Province under the background of climate warming and its influence on the rice yield[J].Chinese Journal of Agrometeorology,2012,33(2):289-296.(in Chinese)
[3]张蕾,侯英雨,杨冰韵,等.长江流域一季稻高温热害分布特征及风险分析[J].自然灾害学报,2018,27(2):107-115.Zhang L,Hou Y Y,Yang B Y,et al.Spatial-temporal characteristics and risk analysis of heat stress hazard of single-season rice across Yangtze River reaches[J].Journal of Natural Disasters,2018,27(2):107-115.(in Chinese)
[4]杨舒畅,申双和,陶苏林.长江中下游地区一季稻高温热害时空变化及其风险评估[J].自然灾害学报,2016,25(2):78-85.Yang S C,Shen S H,Tao S L.Spatiotemporal variation and risk assessment of single-harvest rice heat injury along the middle and lower reaches of Yangtze River[J].Journal of Natural Disasters,2016,25(2):78-85.(in Chinese)
[5]吕开宇,张崇尚,邢鹂.农业指数保险的发展现状与未来[J].江西财经大学学报,2014,(2):62-69.Lv K Y,Zhang C S,Xing L.Current and future development situation of agricultural index insurance[J].Journal of Jiangxi University of Finance and Economics,2014,(2):62-69.(in Chinese)
[6]陈盛伟.农业气象指数保险在发展中个国家的应用及在我国的探索[J].保险研究,2010,3:82-88.Chen S W.Application of Agro-meteorological index insurance in developing countries and its exploration in China[J].Insurance Research,2010,3:82-88.(in Chinese)
[7]丁少群,庹国柱.论农作物保险区划及其理论依据:农作物保险区划研究之一[J].当代经济科学,1994,(3):64-69.Ding S Q,Tuo G Z.Discussion on the regionalization of crop insurance and its theoretical basis:study on the regionalization of crop insurance I[J].Contemporary Economic Science,1994,(3):64-69.(in Chinese)
[8]丁少群,庹国柱.农作物保险的危险单位区划研究:农作物保险区划研究之二[J].中国保险管理干部学院学报,1994,6.Ding S Q,Tuo G Z.Study on risk unit regionalization of crop insurance:study on the regionalization of crop insurance II[J].Journal of China Insurance Management Cadre College,1994,6.(in Chinese)
[9]庹国柱,丁少群.农作物保险风险分区和费率分区问题的探讨[J].中国农村经济,1994,(8):43-48.Tuo G Z,Ding S Q.Discussion on risk zoning and rate zoning of crop insurance[J].Rural Economy in China,1994,(8):43-48.(in Chinese)
[10]Sherrick B J.The accuracy of producers’probability beliefs:evidence and implications for insurance valuation[J].Journal of Agricultural and Resource Economics,2002,27(1):77-93.
[11]Ozaki V A,Ghosh S K,Goodwin B K,et al.Spatial-Temporal modeling of agricultural yield data with an application to pricing crop insurance contracts[J].American Journal of Agricultural Economics,2008,90:951-961.
[12]梁来存.我国粮食作物保险风险区划的实证研究[J].山西财经大学学报,2010,32(1):65-72.Liang L C.Empirical study on risk regionalization of food crop insurance in China[J].Journal of Shanxi Finance and Economics University,2010,32(1):65-72.(in Chinese)
[13]王克,张峭,Shingo Kimura.我国种植业保险的实施效果:基于5省份574个农户数据的模拟分析[J].保险研究,2014,(11):42-55.Wang K,Zhang Q,Shingo K.The implementing effect of planting insurance in China:based on the data of 574farmers in 5 provinces[J].Insurance Research,2014,(11):42-55.(in Chinese)
[14]韩婷,穆月英.北京市粮食作物保险费率厘定研究[J].中国农学通报,2015,31(18):247-255.Han T,Mu Y Y.Study on determining the insurance rate of grain crops in Beijing[J].Chinese Agricultural Science Bulletin,2015,31(18):247-255.(in Chinese)
[15]陈平,陶建平,赵玮.基于风险区划的农作物区域产量保险费率厘定研究:以湖北中稻县级区域产量保险为例[J].自然灾害学报,2013,22(2):51-60.Chen P,Tao J P,Zhao W.Study on premium rate determination of regional crop yield insurance based on risk regionalization:a case study of regional yield insurance of rice in Hubei Province on county level[J].Journal of Natural Disasters,2013,22(2):51-60.(in Chinese)
[16]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.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.(in Chinese)
[17]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.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.(in Chinese)
[18]方洁,陈家金.福建省春种马铃薯寒冻害风险区划[J].中国农业气象,2017,38(12):812-821.Fang J,Chen J J.Risk regionalization of cold and freezing damage to potato in spring planting region of Fujian Province based on geographic information systems[J].Chinese Journal of Agrometeorology,2017,38(12):812-821.(in Chinese)
[19]王志春,杨军,姜晓芳,等.基于GIS的内蒙古东部地区玉米低温冷害精细化风险区划[J].中国农业气象,2013,34(6):715-719.Wang Z C,Yang J,Jiang X F,et al.The refined risk division of maize chilling damage in eastern Inner Mongolia based on GIS[J].Chinese Journal of Agrometeorology,2013,34(6):715-719.(in Chinese)
[20]邢鹏,高涛,吕开宇,等.北京市蔬菜作物生产风险区划研究[J].中国农业资源与区划,2008,29(6):55-60.Xing P,Gao T,Lv K Y,et al.Studies on risk regional planning for fruits and vegetables production in Beijing[J].Agricultural Resources and Regionalization in China,2008,29(6):55-60.(in Chinese)
[21]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.Zhang Z J.Determination of the premium rate of crop yield index insurance based on comprehensive risk regionalization:a case study of soybean[J].Journal of Northeast Agricultural University(Social Science Edition),2016,14(4):1-6.(in Chinese)
[22]何青华.基于风险区划的农作物区域产量保险费率厘定研究:以河南省小麦保险为例[D].郑州:郑州大学,2015:1-10.He Q H.Research on the rate-making of crop area yield insurance based on risk zonation:a case study of wheat insurance in Henan Province[D].Zhengzhou:Zhengzhou University,2015:1-10.(in Chinese)
[23]牛浩,陈盛伟.基于风险区划的玉米区域产量保险费率厘定研究:以山东省17地市为例[J].保险研究,2016,(1):65-75.Niu H,Chen S W.Insurance rating research based on corn yield of different risk zones-supported by data from 17 cities in Shandong Province[J].Insurance Studies,2016,(1):65-75.(in Chinese)
[24]叶涛,史培军,王静爱.种植业自然灾害风险模型研究进展[J].保险研究,2014,(10):12-23.Ye T,Shi P J,Wang J A.A review on crop natural disaster risk models[J].Insurance Studies,2014,(10):12-23.(in Chinese)
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