Integrated flood risk assessment in Hunza-Nagar, Pakistan: unifying big climate data analytics and multi-criteria decision-making with GIS
Floods are a widespread natural disaster with substantial economic implications and far-reaching consequences. In Northern Pakistan, the Hunza-Nagar valley faces vulnerability to floods, posing significant challenges to its sustainable development. This study aimed to evaluate flood risk in the regi...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2024-02-01
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| Series: | Frontiers in Environmental Science |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fenvs.2024.1337081/full |
| _version_ | 1797316791521771520 |
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| author | Muhammad Ahsan Mukhtar Muhammad Ahsan Mukhtar Muhammad Ahsan Mukhtar Donghui Shangguan Donghui Shangguan Donghui Shangguan Yongjian Ding Yongjian Ding Yongjian Ding Muhammad Naveed Anjum Abhishek Banerjee Asim Qayyum Butt Asim Qayyum Butt Asim Qayyum Butt Nilesh yadav Da Li Da Li Da Li Qin Yang Qin Yang Qin Yang Amjad Ali Khan Amjad Ali Khan Ali Muhammad Ali Muhammad Ali Muhammad Bei Bei He Bei Bei He Bei Bei He |
| author_facet | Muhammad Ahsan Mukhtar Muhammad Ahsan Mukhtar Muhammad Ahsan Mukhtar Donghui Shangguan Donghui Shangguan Donghui Shangguan Yongjian Ding Yongjian Ding Yongjian Ding Muhammad Naveed Anjum Abhishek Banerjee Asim Qayyum Butt Asim Qayyum Butt Asim Qayyum Butt Nilesh yadav Da Li Da Li Da Li Qin Yang Qin Yang Qin Yang Amjad Ali Khan Amjad Ali Khan Ali Muhammad Ali Muhammad Ali Muhammad Bei Bei He Bei Bei He Bei Bei He |
| author_sort | Muhammad Ahsan Mukhtar |
| collection | DOAJ |
| description | Floods are a widespread natural disaster with substantial economic implications and far-reaching consequences. In Northern Pakistan, the Hunza-Nagar valley faces vulnerability to floods, posing significant challenges to its sustainable development. This study aimed to evaluate flood risk in the region by employing a GIS-based Multi-Criteria Decision Analysis (MCDA) approach and big climate data records. By using a comprehensive flood risk assessment model, a flood hazard map was developed by considering nine influential factors: rainfall, regional temperature variation, distance to the river, elevation, slope, Normalized difference vegetation index (NDVI), Topographic wetness index (TWI), land use/land cover (LULC), curvature, and soil type. The analytical hierarchy process (AHP) analysis assigned weights to each factor and integrated with geospatial data using a GIS to generate flood risk maps, classifying hazard levels into five categories. The study assigned higher importance to rainfall, distance to the river, elevation, and slope compared to NDVI, TWI, LULC, curvature, and soil type. The weighted overlay flood risk map obtained from the reclassified maps of nine influencing factors identified 6% of the total area as very high, 36% as high, 41% as moderate, 16% as low, and 1% as very low flood risk. The accuracy of the flood risk model was demonstrated through the Receiver Operating Characteristics-Area Under the Curve (ROC-AUC) analysis, yielding a commendable prediction accuracy of 0.773. This MCDA approach offers an efficient and direct means of flood risk modeling, utilizing fundamental GIS data. The model serves as a valuable tool for decision-makers, enhancing flood risk awareness and providing vital insights for disaster management authorities in the Hunza-Nagar Valley. As future developments unfold, this study remains an indispensable resource for disaster preparedness and management in the Hunza-Nagar Valley region. |
| first_indexed | 2024-03-08T03:23:31Z |
| format | Article |
| id | doaj.art-74bb5dca3d6f4640a9ff9a28eeaf0f4f |
| institution | Directory Open Access Journal |
| issn | 2296-665X |
| language | English |
| last_indexed | 2024-03-08T03:23:31Z |
| publishDate | 2024-02-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Environmental Science |
| spelling | doaj.art-74bb5dca3d6f4640a9ff9a28eeaf0f4f2024-02-12T04:45:36ZengFrontiers Media S.A.Frontiers in Environmental Science2296-665X2024-02-011210.3389/fenvs.2024.13370811337081Integrated flood risk assessment in Hunza-Nagar, Pakistan: unifying big climate data analytics and multi-criteria decision-making with GISMuhammad Ahsan Mukhtar0Muhammad Ahsan Mukhtar1Muhammad Ahsan Mukhtar2Donghui Shangguan3Donghui Shangguan4Donghui Shangguan5Yongjian Ding6Yongjian Ding7Yongjian Ding8Muhammad Naveed Anjum9Abhishek Banerjee10Asim Qayyum Butt11Asim Qayyum Butt12Asim Qayyum Butt13 Nilesh yadav14Da Li15Da Li16Da Li17Qin Yang18Qin Yang19Qin Yang20Amjad Ali Khan21Amjad Ali Khan22Ali Muhammad23Ali Muhammad24Ali Muhammad25Bei Bei He26Bei Bei He27Bei Bei He28State Key Laboratory of Cryospheric Science, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, ChinaUniversity of Chinese Academy of Sciences, Beijing, ChinaChina-Pakistan Joint Research Center on Earth Sciences, Chinese Academy of Sciences and Higher Education Commission of Pakistan, Islamabad, PakistanState Key Laboratory of Cryospheric Science, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, ChinaUniversity of Chinese Academy of Sciences, Beijing, ChinaChina-Pakistan Joint Research Center on Earth Sciences, Chinese Academy of Sciences and Higher Education Commission of Pakistan, Islamabad, PakistanState Key Laboratory of Cryospheric Science, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, ChinaUniversity of Chinese Academy of Sciences, Beijing, ChinaChina-Pakistan Joint Research Center on Earth Sciences, Chinese Academy of Sciences and Higher Education Commission of Pakistan, Islamabad, PakistanDepartment of Land and Water Conservation Engineering, Pir Mehr Ali Shah Arid Agriculture University, Rawalpindi, PakistanState Key Laboratory of Cryospheric Science, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, ChinaState Key Laboratory of Cryospheric Science, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, ChinaUniversity of Chinese Academy of Sciences, Beijing, ChinaChina-Pakistan Joint Research Center on Earth Sciences, Chinese Academy of Sciences and Higher Education Commission of Pakistan, Islamabad, PakistanState Key Laboratory of Geographic Information Science (Ministry of Education), School of Geographic Sciences, East China Normal University, Shanghai, ChinaState Key Laboratory of Cryospheric Science, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, ChinaUniversity of Chinese Academy of Sciences, Beijing, ChinaChina-Pakistan Joint Research Center on Earth Sciences, Chinese Academy of Sciences and Higher Education Commission of Pakistan, Islamabad, PakistanState Key Laboratory of Cryospheric Science, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, ChinaUniversity of Chinese Academy of Sciences, Beijing, ChinaChina-Pakistan Joint Research Center on Earth Sciences, Chinese Academy of Sciences and Higher Education Commission of Pakistan, Islamabad, PakistanState Key Laboratory of Cryospheric Science, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, ChinaUniversity of Chinese Academy of Sciences, Beijing, ChinaState Key Laboratory of Cryospheric Science, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, ChinaUniversity of Chinese Academy of Sciences, Beijing, ChinaChina-Pakistan Joint Research Center on Earth Sciences, Chinese Academy of Sciences and Higher Education Commission of Pakistan, Islamabad, PakistanState Key Laboratory of Cryospheric Science, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, ChinaUniversity of Chinese Academy of Sciences, Beijing, ChinaChina-Pakistan Joint Research Center on Earth Sciences, Chinese Academy of Sciences and Higher Education Commission of Pakistan, Islamabad, PakistanFloods are a widespread natural disaster with substantial economic implications and far-reaching consequences. In Northern Pakistan, the Hunza-Nagar valley faces vulnerability to floods, posing significant challenges to its sustainable development. This study aimed to evaluate flood risk in the region by employing a GIS-based Multi-Criteria Decision Analysis (MCDA) approach and big climate data records. By using a comprehensive flood risk assessment model, a flood hazard map was developed by considering nine influential factors: rainfall, regional temperature variation, distance to the river, elevation, slope, Normalized difference vegetation index (NDVI), Topographic wetness index (TWI), land use/land cover (LULC), curvature, and soil type. The analytical hierarchy process (AHP) analysis assigned weights to each factor and integrated with geospatial data using a GIS to generate flood risk maps, classifying hazard levels into five categories. The study assigned higher importance to rainfall, distance to the river, elevation, and slope compared to NDVI, TWI, LULC, curvature, and soil type. The weighted overlay flood risk map obtained from the reclassified maps of nine influencing factors identified 6% of the total area as very high, 36% as high, 41% as moderate, 16% as low, and 1% as very low flood risk. The accuracy of the flood risk model was demonstrated through the Receiver Operating Characteristics-Area Under the Curve (ROC-AUC) analysis, yielding a commendable prediction accuracy of 0.773. This MCDA approach offers an efficient and direct means of flood risk modeling, utilizing fundamental GIS data. The model serves as a valuable tool for decision-makers, enhancing flood risk awareness and providing vital insights for disaster management authorities in the Hunza-Nagar Valley. As future developments unfold, this study remains an indispensable resource for disaster preparedness and management in the Hunza-Nagar Valley region.https://www.frontiersin.org/articles/10.3389/fenvs.2024.1337081/fullflood risk assessmentgeospatial technologybig climate datamulti-criteria decision analysis (MCDA)Hunza Nagar Valleyfloods |
| spellingShingle | Muhammad Ahsan Mukhtar Muhammad Ahsan Mukhtar Muhammad Ahsan Mukhtar Donghui Shangguan Donghui Shangguan Donghui Shangguan Yongjian Ding Yongjian Ding Yongjian Ding Muhammad Naveed Anjum Abhishek Banerjee Asim Qayyum Butt Asim Qayyum Butt Asim Qayyum Butt Nilesh yadav Da Li Da Li Da Li Qin Yang Qin Yang Qin Yang Amjad Ali Khan Amjad Ali Khan Ali Muhammad Ali Muhammad Ali Muhammad Bei Bei He Bei Bei He Bei Bei He Integrated flood risk assessment in Hunza-Nagar, Pakistan: unifying big climate data analytics and multi-criteria decision-making with GIS Frontiers in Environmental Science flood risk assessment geospatial technology big climate data multi-criteria decision analysis (MCDA) Hunza Nagar Valley floods |
| title | Integrated flood risk assessment in Hunza-Nagar, Pakistan: unifying big climate data analytics and multi-criteria decision-making with GIS |
| title_full | Integrated flood risk assessment in Hunza-Nagar, Pakistan: unifying big climate data analytics and multi-criteria decision-making with GIS |
| title_fullStr | Integrated flood risk assessment in Hunza-Nagar, Pakistan: unifying big climate data analytics and multi-criteria decision-making with GIS |
| title_full_unstemmed | Integrated flood risk assessment in Hunza-Nagar, Pakistan: unifying big climate data analytics and multi-criteria decision-making with GIS |
| title_short | Integrated flood risk assessment in Hunza-Nagar, Pakistan: unifying big climate data analytics and multi-criteria decision-making with GIS |
| title_sort | integrated flood risk assessment in hunza nagar pakistan unifying big climate data analytics and multi criteria decision making with gis |
| topic | flood risk assessment geospatial technology big climate data multi-criteria decision analysis (MCDA) Hunza Nagar Valley floods |
| url | https://www.frontiersin.org/articles/10.3389/fenvs.2024.1337081/full |
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