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作 者:李莉[1,2] 匡昭敏[1,2] 莫建飞[1,2] 刘芳[3] 黄肖寒[3]
机构地区:[1]广西壮族自治区气象减灾研究所,南宁530022 [2]国家卫星气象中心遥感应用试验基地,南宁530022 [3]广西壮族自治区河池市气象局,河池547000
出 处:《应用气象学报》2016年第1期95-101,共7页Journal of Applied Meteorological Science
基 金:国家重点基础研究发展计划(2013CB430205);公益性行业(气象)科研专项(GYHY201406030);广西自然科学基金项目(2014GXNSFBA118219;2013GXNSFAA019282)
摘 要:为增强对广西甘蔗秋旱灾害的风险评估和应急管理能力,利用气象、植被、基础地理信息和社会经济数据,根据风险三角形理念,从广西甘蔗秋旱灾害的危险度、受灾可能性和承灾体脆弱度3个方面,选择因子构建甘蔗秋旱灾害风险评估的指标体系,采用层次分析法构造判断矩阵以确定各指标和因子的权重,构建评估模型,并计算广西甘蔗秋旱灾害风险指数,再基于GIS绘制广西甘蔗秋旱灾害风险区划,结果显示:高风险区和较高风险区主要分布在来宾和崇左等市的局部地区,低风险区主要分布在桂东南地区。利用灾情数据进行验证表明:广西甘蔗秋旱灾害风险分布与甘蔗灾情损失空间分布情况基本一致。Guangxi is one of the annual precipitation-rich regions of the country. However, seasonal drought oc- curs in high frequency because of spatiotemporal nonuniform distribution of rainfall. Seasonal drought has rather large influences on the agricultural production, especially on the sucrose industry, which is one of the most important economic pillar industries in Guangxi. Autumn is the critical elongation and sugar accu- mulation stage for sugarcane. Severe autumn drought will cause a decline in production, or which at sugar accumulation stage, will decrease sugar content, increase pectin weight, reduce sugar yield and recovery rate, and cause a decline in commodity quality. Therefore, it will affect the sugar market and the whole in- dustry chain, as well as sugarcane farmers and the local agricultural economy. In order to strengthen the risk assessment and emergency management capability of the autumn drought disasters of sugarcane, ac- cording to the concept of risk triangle, the autumn drought risk assessment indicator system is established. Indicators of system are determined according to drought risk, possibility of disaster, vulnerability of dis- aster bearing body, by use of meteorological data, vegetation, basic geographic information and socio-eco- nomic data from the database. The database is constructed for risk assessment of drought disasters of sug- arcane, including disaster-causing factors(such as rainfall), disaster-forming environment(such as topogra- phy, hydrographic net, vegetative cover, etc. ), disaster bearing body(such as sugarcane planting area, e- conomy, etc. ), and disaster prevention and mitigation capability(such as reservoir and other water conser- vancy facilities). Then factor weights are obtained by analytic hierarchy process(AHP), and the compre- hensive assessment model is established and calculated to get the disaster risk index, which are regionalized by geographic information system(GIS). The distribution indicates that the highest and higher risk ar
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