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生态学杂志 ›› 2024, Vol. 43 ›› Issue (3): 904-912.doi: 10.13292/j.1000-4890.202403.037

• 技术与方法 • 上一篇    

安吉白茶精细化气象灾害风险分析与区划

李时睿1,2,朱兰娟3,赵亮1,2,柏佳1,2,胡波4,许金萍5,孙睿1,2*
  

  1. 1北京师范大学地理科学学部遥感科学国家重点实验室, 北京 100875; 2北京师范大学地理科学学部北京市陆表遥感数据产品工程技术研究中心, 北京 100875; 3杭州市气象局, 杭州 310051; 4宁波市气象局, 浙江宁波 315012; 5安吉县气象局, 浙江安吉 313300)

  • 出版日期:2024-03-10 发布日期:2024-03-15

Refined meteorological risk analysis and zoning of Anji white tea.

LI Shirui1,2, ZHU Lanjuan3, ZHAO Liang1,2, BAI Jia1,2, HU Bo4, XU Jinping5, SUN Rui1,2*   

  1. (1State Key Laboratory of Remote Sensing Science, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China; 2Beijing Engineering Research Center for Global Land Remote Sensing Products, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China; 3Hangzhou Meteorological Department, Hangzhou 310051, China; 4Ningbo Meteorological Department, Ningbo 315012, Zhejiang, China; 5Anji County Meteorological Department, Anji 313300, Zhejiang China).

  • Online:2024-03-10 Published:2024-03-15

摘要: 气象灾害严重威胁茶产业高质量发展,开展气象灾害风险精细评价可为茶叶生产灾害精准防控提供科学依据。本文基于自然灾害风险理论、安吉县及周边7个国家气象站1971—2020年和安吉县23个区域自动气象站2012—2020年的逐日气象资料、15个乡镇农业社会经济统计资料,以及源于GF-2卫星遥感数据解译出的茶树种植现状分布图和DEM高程等多源信息,采用加权综合指数法、模糊层次分析法和GIS技术,对安吉白茶进行了精细化气象灾害风险分析与区划。结果表明:安吉白茶致灾因子危险性、孕灾环境暴露性的高值主要位于南部山区,承灾体脆弱性的高值集中于中部平原地区,防灾减灾能力的高值多位于中东部平原地区;综合考虑各因子的综合风险度,安吉白茶气象灾害风险可分为低风险、中风险和高风险3个等级;低风险区主要分布于安吉中北部平原区域,占安吉县地域面积的66.55%;中风险区主要分布于安吉西部、南部的中高海拔区域,占安吉县地域面积的30.54%;高风险区主要位于南部高海拔山区,占安吉县地域面积的3.01%;集成格点化的茶树种植现状,安吉县内61.21%的茶园分布在低风险区,38.17%的茶园分布在中风险区,0.62%的茶园分布在高风险区。基于茶树种植现状的气象灾害精细化风险区划可为安吉白茶的优化布局提供更加精准的科学依据。


关键词: 安吉白茶, 气象灾害, 模糊层次分析, 风险指数模型, 精细区划

Abstract: Meteorological disasters seriously threaten the high-quality development of tea industry. The refined assessment of meteorological disaster risks can provide scientific basis for the precise prevention and control of tea production disasters. Based on the natural disaster risk theory, the daily meteorological data of seven standard meteorological stations in Anji County and its surrounding areas from 1971 to 2020 as well as 23 automatic meteorological stations in Anji County from 2012 to 2020, statistical data of agricultural socioeconomy of 15 townships, and the multi-source information such as tea planting distribution map interpreted from GF-2 satellite remote sensing data and digital elevation model (DEM) data were adopted for calculation. We used the weighted comprehensive index method, fuzzy hierarchy analysis method, and Geographical Information System (GIS) technology to analyze the refined meteorological disaster risk and zoning for Anji white tea. The results showed that the maximum risk of the disaster factor and the maximum exposure of the disaster environment of Anji white tea were distributed in the high-altitude mountainous areas of the south, the highest value of the vulnerability of the disaster bearing body was distributed in the central plain, and the highest value of disaster prevention and mitigation ability was distributed in the central and eastern plain. Considering the comprehensive risk of each factor, the meteorological disaster risk of Anji white tea could be classified into three levels: low risk, medium risk, and high risk. The low-risk areas were mainly distributed in the north-central plain of Anji, accounting for 66.55% of the total area of Anji County. The medium-risk areas were mainly distributed in the middle and high altitude areas in the west and south of Anji County, accounting for 30.54% of the total area. The high-risk areas were mainly located in the high-altitude mountainous areas in the south, accounting for 3.01% of the total area. According to the tea planting map, 61.21%, 38.17%, and 0.62% of tea gardens in Anji County were distributed in low-risk, medium-risk, and high-risk areas, respectively. The refined risk zoning of meteorological disasters based on tea planting map could provide more accurate scientific basis for the management of Anji white tea.


Key words: Anji white tea, meteorological disaster, fuzzy analytic hierarchy process, risk index model, refined zoning