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Characterizing flood hazard risk in data-scarce areas, using a remote sensing and GIS-based flood hazard index

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Natural Hazards
Authors:
Martin Kabenge at Tongji University
Martin Kabenge
Joshua Elaru at GGGI
Joshua Elaru
  • GGGI
Hongtao Wang at Tongji University
Hongtao Wang
Li Fengting at Tongji University
Li Fengting
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The frequency in occurrence and severity of floods has increased globally. However, many regions around the globe, especially in developing countries, lack the necessary field monitoring data to characterize flood hazard risk. This paper puts forward methodology for developing flood hazard maps that define flood hazard risk, using a remote sensing and GIS-based flood hazard index (FHI), for the Nyamwamba watershed in western Uganda. The FHI was compiled using analytical hierarchy process and considered slope, flow accumulation, drainage network density, distance from drainage channel, geology, land use/cover and rainfall intensity as the flood causative factors. These factors were derived from Landsat, SRTM and PERSIANN remote sensing data products, except for geology that requires field data. The resultant composite FHI yielded a flood hazard map pointing out that over 11 and 18% of the study area was very highly and highly susceptible to flooding, respectively, while the remaining area ranged from medium to very low risk. The resulting flood hazard map was further verified using inundation area of a historical flood event in the study area. The proposed methodology was effective in producing a flood hazard map at the watershed local scale, in a data-scarce region, useful in devising flood mitigation measures.
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ORIGINAL PAPER
Characterizing flood hazard risk in data-scarce areas,
using a remote sensing and GIS-based flood hazard index
Martin Kabenge
1
•Joshua Elaru
1
•Hongtao Wang
1
•
Fengting Li
1
Received: 26 April 2017 / Accepted: 15 August 2017 / Published online: 24 August 2017
ÓSpringer Science+Business Media B.V. 2017
Abstract The frequency in occurrence and severity of floods has increased globally.
However, many regions around the globe, especially in developing countries, lack the
necessary field monitoring data to characterize flood hazard risk. This paper puts forward
methodology for developing flood hazard maps that define flood hazard risk, using a
remote sensing and GIS-based flood hazard index (FHI), for the Nyamwamba watershed in
western Uganda. The FHI was compiled using analytical hierarchy process and considered
slope, flow accumulation, drainage network density, distance from drainage channel,
geology, land use/cover and rainfall intensity as the flood causative factors. These factors
were derived from Landsat, SRTM and PERSIANN remote sensing data products, except
for geology that requires field data. The resultant composite FHI yielded a flood hazard
map pointing out that over 11 and 18% of the study area was very highly and highly
susceptible to flooding, respectively, while the remaining area ranged from medium to very
low risk. The resulting flood hazard map was further verified using inundation area of a
historical flood event in the study area. The proposed methodology was effective in pro-
ducing a flood hazard map at the watershed local scale, in a data-scarce region, useful in
devising flood mitigation measures.
Keywords Flood hazard index Remote sensing Data-scarce areas Analytical
hierarchy process
&Fengting Li
fengting@tongji.edu.cn
1
State Key Laboratory of Pollution Control and Resource Reuse Study, College of Environmental
Science and Engineering, Tongji University, Siping Rd 1239, Shanghai 200092, China
123
Nat Hazards (2017) 89:1369–1387
DOI 10.1007/s11069-017-3024-y
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
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