TY - JOUR
T1 - Newspapers as a validation proxy for GIS modeling in Fujairah, United Arab Emirates
T2 - identifying flood-prone areas
AU - Yagoub, M. M.
AU - Alsereidi, Aishah A.
AU - Mohamed, Elfadil A.
AU - Periyasamy, Punitha
AU - Alameri, Reem
AU - Aldarmaki, Salama
AU - Alhashmi, Yaqein
N1 - Funding Information:
The authors acknowledged the financial support from UAE University Research Affair Office under the Summer Undergraduate Research Experiences (SURE) Program 2019–2020 (Fund No.: G00003135). Thanks to the editorial board of Natural Hazard journal and the anonymous reviewers for their constructive suggestions and insights. Gratitude is extended to USGS, Fujairah Municipality, UAE Strom Center, Department of Civil Aviation, World Weather, FAO, Mr. Shehab Majud, Dr. Goepel KD, Dr. Tareefa Alsumaiti, Dr. Khalid Husein, Dr. Sharif H and all who provided support for this project.
Funding Information:
This research was funded by the United Arab Emirate University-Research Affairs—SURE Plus 2019/2020 (Project No. G00003135). The views and conclusions are those of the authors and should not be taken as those of the sponsor. Acknowledgements
Funding Information:
The authors acknowledged the financial support from UAE University Research Affair Office under the Summer Undergraduate Research Experiences (SURE) Program 2019?2020 (Fund No.: G00003135). Thanks to the editorial board of Natural Hazard journal and the anonymous reviewers for their constructive suggestions and insights. Gratitude is extended to USGS, Fujairah Municipality, UAE Strom Center, Department of Civil Aviation, World Weather, FAO, Mr. Shehab Majud, Dr. Goepel KD, Dr. Tareefa Alsumaiti, Dr. Khalid Husein, Dr. Sharif H and all who provided support for this project.
Publisher Copyright:
© 2020, The Author(s).
PY - 2020/10/1
Y1 - 2020/10/1
N2 - The UN Office for Disaster Risk Reduction listed 10 reasons businesses should reduce their disaster exposure, including risk factoring, which cannot be achieved without historical data about hazards, their locations, magnitudes, and frequencies. Substantial hazard data are reported by newspapers, which could add value to disaster management decision making. In this study, a text-mining program extracted keywords related to floods’ geographic location, date, and damages from newspaper analyses of flash floods in Fujairah, UAE, from 2000–2018. The paper describes extracting such information as well as geocoding and validating flood-prone areas generated through geographic information system (GIS) modeling. The generation of flood-prone areas was based on elevation, slope, land use, soil, and geology coupled with topographic wetness index, topographic position index, and curve number. Analytical Hierarchy Process (AHP) produced relative weight for each factor, and GIS map algebra generated flood-prone areas. AHP inclusion helped minimize weight subjectivity among various experts. Of all areas, 85% are considered medium and low flood-prone zones, mainly mountainous areas. However, the 15% that are high/very high are dominated by urban areas in low coastal plains, predisposing them to flash floods. Eighty-four percent of flood events reported by newspapers were in areas rated as high/very high flood-prone zones. In the absence of flood records, newspapers reports can be used as a reference. Policymakers should assess whether flood-prone area models offer accurate analyses. These findings are useful for organizations related to disaster management, urban planning, insurance, archiving, and documentation.
AB - The UN Office for Disaster Risk Reduction listed 10 reasons businesses should reduce their disaster exposure, including risk factoring, which cannot be achieved without historical data about hazards, their locations, magnitudes, and frequencies. Substantial hazard data are reported by newspapers, which could add value to disaster management decision making. In this study, a text-mining program extracted keywords related to floods’ geographic location, date, and damages from newspaper analyses of flash floods in Fujairah, UAE, from 2000–2018. The paper describes extracting such information as well as geocoding and validating flood-prone areas generated through geographic information system (GIS) modeling. The generation of flood-prone areas was based on elevation, slope, land use, soil, and geology coupled with topographic wetness index, topographic position index, and curve number. Analytical Hierarchy Process (AHP) produced relative weight for each factor, and GIS map algebra generated flood-prone areas. AHP inclusion helped minimize weight subjectivity among various experts. Of all areas, 85% are considered medium and low flood-prone zones, mainly mountainous areas. However, the 15% that are high/very high are dominated by urban areas in low coastal plains, predisposing them to flash floods. Eighty-four percent of flood events reported by newspapers were in areas rated as high/very high flood-prone zones. In the absence of flood records, newspapers reports can be used as a reference. Policymakers should assess whether flood-prone area models offer accurate analyses. These findings are useful for organizations related to disaster management, urban planning, insurance, archiving, and documentation.
KW - Flash floods
KW - Flood-prone area map
KW - GIS
KW - Newspapers
KW - Text mining
KW - UAE
UR - http://www.scopus.com/inward/record.url?scp=85088040152&partnerID=8YFLogxK
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U2 - 10.1007/s11069-020-04161-y
DO - 10.1007/s11069-020-04161-y
M3 - Article
AN - SCOPUS:85088040152
SN - 0921-030X
VL - 104
SP - 111
EP - 141
JO - Natural Hazards
JF - Natural Hazards
IS - 1
ER -