Novel technique for developing flood hazard map by using AHP: a study on part of Mahanadi River in Odisha

被引:8
作者
Surwase, Tushar [1 ]
Manjusree, P. [1 ]
Nagamani, P., V [2 ]
Jaisankar, G. [3 ]
机构
[1] NRSC ISRO, RSAA, Disaster Management Support Grp, Hyderabad 500037, Andhra Pradesh, India
[2] NRSC ISRO, ECSA, Ocean Sci Grp, Hyderabad 500037, Andhra Pradesh, India
[3] Andhra Univ, Dept Geoengn, Visakhapatnam 530003, Andhra Pradesh, India
来源
SN APPLIED SCIENCES | 2019年 / 1卷 / 10期
基金
美国国家航空航天局;
关键词
Odisha; Mahanadi River; Spatial flood frequency map; AHP; GIS; RISK-ASSESSMENT; AVHRR; IMAGES; GIS;
D O I
10.1007/s42452-019-1233-6
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
In India, Odisha state experienced major natural hazards like floods and cyclones. Floods were experienced fifteen times during 2001-2018 and had two major catastrophic cyclones (super-cyclone 1999 and Phailin 2013). Flood is triggered due to meteorological, hydrological, and terrain conditions at any given place. Considering the terrain parameters namely elevation, slope, drainage density, soil and land use/land cover as the contributing factors for flood inundation, a new technique is developed to calculate flood hazard using analytical hierarchy process (AHP). Using multi-temporal satellite derived flood extent, spatial flood frequency map (SFFM) were generated based on the frequency of inundation. SFFM which represents the observed flood extent on ground at different magnitudes of flood and the terrain conditions on the ground are used synergistically for generating the hazard map. Part of Mahanadi River in Odisha which is highly flood-prone is taken for analysis in this study. More than 100 satellite data sets both microwave SAR and optical data acquired at different magnitudes of flood during 2001-2018 were analysed to prepare the SFFM maps. Pair wise comparison rating was given among flood producing factors and weightage of each factor was computed by using GIS based AHP and multi-criteria evaluation techniques. The individual derived weights (in percentage) of the contributing factors obtained were 50.874 for SFFM, 22.775 for elevation, 10.966 for drainage density, 7.225 for slope, 5.914 for land use and 2.936 for soil. Further, the layers were used in weighted overlay tool and respective weights in percentage were given for generating the flood hazard map in GIS environment. The flood hazard was classified into five hazard classes i.e. very high, high, moderate, low, and very low and corresponding hazard area was estimated to be 7467 ha, 12,871 ha, 28,700 ha, 35,518 ha and 292 ha respectively. These statistics and hazard map will help the concerned local authorities for formulating strategic policies for land use planning and minimize the effect of flood on agricultural land and human lives.
引用
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页数:14
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