基于AHP_熵权法的孟印缅地区洪水灾害风险评估被引量：93

Flood risk assessment in Bangladesh, India and Myanmar based on the AHP weight method and entropy weight method

导出

摘要孟印缅三国地处亚热带与热带季风气候区,因自然条件制约,洪涝灾害频繁发生,对"孟中印缅经济走廊"建设将会带来重大影响。开展孟印缅地区的洪水风险评估可为"孟中印缅经济走廊"的建设安全提供必要的信息和科技支撑。利用1980—2016年的降水数据,结合河网、数字高程和土地利用等数据,选取雨季降雨量、暴雨天数、高程、坡度、河网密度、植被覆盖度、土壤可蚀性、人口密度、地均GDP和土地利用10个指标,采用层次分析法和AHP_熵权法对孟印缅地区的洪水灾害风险分布进行了比较研究。研究表明:孟印缅地区高风险区和较高风险区分别占总面积的1.05%和28.76%,高风险区主要分布在印度北部的恒河平原、印度东北部的阿萨姆邦、孟加拉国大部分地区和缅甸南部。受自然、人口和经济条件的制约,孟加拉国是孟印缅三国中洪水风险最高的国家,高风险区和较高风险区分别占总面积的10.61%和65.87%。层次分析法和AHP_熵权法结果间的比较表明,后者比前者识别出更大范围的洪水高风险区。本研究为中国开展周边国家自然灾害的风险评估提供了有效的方法,有助于推进国家孟中印缅经济走廊的建设。 The Bangladesh,India and Myanmar(BIM)region has subtropical and tropical monsoon climates.Floods frequently occur around here.Assessing the flood risk in BIM region is important for the safety construction of the BCIM-EC.Based on datasets of precipitation from 1980 to 2016,river network,elevation,land use and etc.,we selected ten indexes,namely,rainy season rainfall,rainstorm days,elevation,slope,drainage density,vegetation coverage,soil erodibility,population density,GDP,and land use.A comparative study of flood risk in BIM region is presented using the analytic hierarchy process(AHP)and the AHP_entropy methods.Based on the assessed results,about 1.05%and 28.76%of the BIM region have high risk and moderate to high risk.High risk zones in the BIM region were primarily concentrated on the Ganges Plain in northern India,Assam State in northeastern India,most of Bangladesh and southern Myanmar.Bangladesh is the country with the highest risk among three countries.The results show that high risk areas and moderate to high risk areas take up 10.61%and65.87%of the total area of Bangladesh,respectively.Comparisons between results from AHP and AHP_entropy show that the latter yields a wider range of high flooding risk than the former.The study could provide an effective method for other neighboring countries of China in estimating the flood hazard areas,which can promote the construction of the BCIM-EC.

作者刘媛媛王绍强王小博江东 N H Ravindranath Atiq Rahman Nyo Mar Htwe Tartirose Vijitpan LIU Yuanyuan;WANG Shaoqiang;WANG Xiaobo;JIANG Dong;N H Ravindranath;Atiq Rahman;Nyo Mar Htwe;Tartirose Vijitpan(Key Laboratory of Ecosystem Network Observation and Modeling,Institute of Geographic Sciences and Natural Resources Research,CAS,Beijing 100101,China;College of Resources and Environment at University of Chinese Academy of Sciences,Beijing 100049,China;School of Geography and Information Engineering,China University of Geosciences,Wuhan 430074,China;Centre for Sustainable Technologies,India Institute of Science,Bangalore 560012,India;Bangladesh Centre for Advanced Studies,Dhaka 1212,Bangladesh;Yezin Agricultural University,Naypyitaw 15000,Myanmar;United Nations Environment Programme-International Ecosystem Management Partnership,Beijing 100101,China)