Urban Building Flood Vulnerability Assessment in Erbil City: A Geospatial and AHP-Based Approach

Kaifi Chomani; Dleen  Mohammed Saleh Al-shrafany

doi:10.21271/ZJPAS.37.5.6

Authors

Kaifi Chomani 1Department of Geomatics (Surveying) Engineering, College of Engineering, Erbil, Salahaddin University-Erbil, Erbil ,Kurdistan Region, Iraq 2Civil Engineering Department, University of Raparin, Ranya, Sulaymaniyah, Iraq.
Dleen Mohammed Saleh Al-shrafany Department of Geomatics (Surveying) Engineering, College of Engineering, Erbil, Salahaddin University-Erbil, Erbil ,Kurdistan Region, Iraq

DOI:

https://doi.org/10.21271/ZJPAS.37.5.6

Keywords:

Flood vulnerability, GIS, Analytical Hierarchy Process, Flood risk zones, urban planning, Erbil city

Abstract

The frequency and intensity of flash floods increased substantially in recent years in the world which are the major risk for urban regions and environment. The objective of this comprehensive study is to assess the buildings vulnerable to flood hazards in Erbil city, Kurdistan region of Iraq using the integrated approaches of Geographic Information Systems (GIS), satellite remote sensing, and the Analytical Hierarchy Process (AHP). 14 flood-contributing parameters were used to map flood susceptible regions in the Erbil city. Rainfall, aspect, topographic wetness index (TWI), elevation, flow accumulation, lithology, soil data, normalized difference vegetation index (NDVI), normalized difference built-up index (NDBI), land use land cover (LULC), slope, stream power index (SPI), drainage density, and distance to roads were the factors that have been used to create flood susceptibility map (FSM). The FSM map showed considerable results with the accuracy of the 92.2%, using historical flood data to assess the accuracy. The results showed that 109 km2 (12.1%) of Erbil city area located in high and very high flood risk areas. Moreover, the outcome underscored startling results, showing that nearly half of buildings in Erbil city (47.6%) were located in high or very high flood risk areas. Additionally, the finding showed that 33853 (3.84%) and 69258 (7.85%) of population in Erbil city were located in very high and high risk flood zones, respectively. This study offers valuable insights for policy makers and urban planners, significantly contributing in monitoring urban environments, early warning systems, flood mitigation strategies and sustainable urban growth.

References

Abrar, M.F., Iman, Y.E., Mustak, M.B. and Pal, S.K., 2024. Assessment of vulnerability to flood risk in the Padma River Basin using hydro-morphometric modeling and flood susceptibility mapping. Environmental Monitoring and Assessment, 196(7), p.661.

Adedoja, T.B., Popoola, O.S., Alaga, T.A. and Akindejoye-Adesioye, A.E., 2023. Flood vulnerability mapping: a case study of Okoko Basin, Osogbo. Journal of Geographic Information System, 15(5), pp.580-596.

Akhtar, Z., Sajjad, M., Imran, M. and Ofli, F., 2023. Risk Mapping in Managing Flood Vulnerability in Disaster Management. In International Handbook of Disaster Research (pp. 743-776). Singapore: Springer Nature Singapore.

Al-Omari, A.A., Shatnawi, N.N., Shbeeb, N.I., Istrati, D., Lagaros, N.D. and Abdalla, K.M., 2024. Utilizing remote sensing and GIS techniques for flood hazard mapping and risk assessment. Civil Engineering Journal, 10(5), pp.1423-1436.

Al-Sababhah, N., 2023. Detection of flood-hazard-prone zones using GIS modeling and AHP method in urban areas: the case of Amman Governorate. Bulletin of Geography. Physical Geography Series, (24).

Al–Shwani, J.K.M., Saleh, S.A. and Al-Manmi, D.A.M.A., 2025. Identifying Areas Exposed to Potential Flash Floods and Drawing Map for Them Using Multi-Criteria Decision-Making Depending on GIS and AHP for Erbil Sub-Basin, Northern Iraq.

Ali, B.A. and Mawlood, D.K., 2023. Applying the SWMM Software Model for the High Potential Flood-Risk Zone for Limited Catchments in Erbil City Governorate. Zanco Journal of Pure and Applied Sciences, 35(4), pp.41-50.

Ali, B.A. and Mawlood, D.K., 2023. Urban Flood Simulation in Erbil City by Using Storm Water Management Model (SWMM). Zanco Journal of Pure and Applied Sciences, 35(5), pp.1-11.

Allafta, H. and Opp, C., 2021. GIS-based multi-criteria analysis for flood prone areas mapping in the trans-boundary Shatt Al-Arab basin, Iraq-Iran. Geomatics, Natural Hazards and Risk, 12(1), pp.2087-2116.

Askar, S., Zeraat Peyma, S., Yousef, M.M., Prodanova, N.A., Muda, I., Elsahabi, M. and Hatamiafkoueieh, J., 2022. Flood susceptibility mapping using remote sensing and integration of decision table classifier and metaheuristic algorithms. Water, 14(19), p.3062.

Aziz, S.Q., Saleh, S.M., Muhammad, S.H., Ismael, S.O. and Ahmed, B.M., 2023. Flood Disaster in Erbil City: Problems and Solutions. Environmental Protection Research, pp.303-318.

Azizah, V., Deffinika, I. and Arinta, D., 2022, July. The effect of land use changes on land surface temperature in malang city’s on 2016-2020. In IOP Conference Series: Earth and Environmental Science (Vol. 1066, No. 1, p. 012006). IOP Publishing.

Benítez, J., Delgado-Galván, X., Izquierdo, J. and Pérez-García, R., 2012. An approach to AHP decision in a dynamic context. Decision Support Systems, 53(3), pp.499-506.

Bouaziz, M., Eisold, S. and Guermazi, E., 2017. Semiautomatic approach for land cover classification: a remote sensing study for arid climate in southeastern Tunisia. Euro-Mediterranean Journal for Environmental Integration, 2(1), p.24.

Bui, Q.D., Luu, C., Mai, S.H., Ha, H.T., Ta, H.T. and Pham, B.T., 2023. Flood risk mapping and analysis using an integrated framework of machine learning models and analytic hierarchy process. Risk Analysis, 43(7), pp.1478-1495.

Buringh, P., 1957. Exploratory soil map of Iraq. Ministry of Agriculture, Baghdad.

Cabrera, J.S. and Lee, H.S., 2019. Flood-prone area assessment using GIS-based multi-criteria analysis: A case study in Davao Oriental, Philippines. Water, 11(11), p.2203.

Celone, M., Pecor, D.B., Potter, A., Richardson, A., Dunford, J. and Pollett, S., 2022. An ecological niche model to predict the geographic distribution of Haemagogus janthinomys, Dyar, 1921 a yellow fever and Mayaro virus vector, in South America. PLOS Neglected Tropical Diseases, 16(7), p.e0010564.

Chen, W. and Samuelson, F.W., 2014. The average receiver operating characteristic curve in multireader multicase imaging studies. The British journal of radiology, 87(1040), p.20140016.

Chomani, K., 2023. Assessing the impact of urbanization on flood hazards in Ranya city, using GIS and remote sensing. EURASIAN JOURNAL OF SCIENCE AND ENGINEERING, 9(3), pp.154-165.

Chomani, K., 2024. Evaluating the COVID-19 Lockdown’s Effects on Land Surface Temperature, NO2, and O3 in the Erbil City, Kurdistan Region of Iraq. Cihan University-Erbil Scientific Journal, 8(2), pp.84-92.

Chomani, K. and Manguri, S.B.H., 2024. Spatiotemporal Insights into Ranya's Land-Use Transformation using Time-Series Imagery. Polytechnic Journal, 14(1), p.9.

Chomani, K. and Pshdari, S., 2024. Evaluation of Different Classification Algorithms for Land Use Land Cover Mapping. Kurdistan Journal of Applied Research, 9(2), pp.13-22.

D’Allestro, P. and Parente, C., 2015. GIS application for NDVI calculation using Landsat 8 OLI images. International Journal of Applied Engineering Research, 10(21), pp.42099-42102.

Dano, U.L., Balogun, A.L., Matori, A.N., Wan Yusouf, K., Abubakar, I.R., Said Mohamed, M.A., Aina, Y.A. and Pradhan, B., 2019. Flood susceptibility mapping using GIS-based analytic network process: A case study of Perlis, Malaysia. Water, 11(3), p.615.

Das, S. and Pardeshi, S.D., 2018. Morphometric analysis of Vaitarna and Ulhas river basins, Maharashtra, India: using geospatial techniques. Applied Water Science, 8(6), p.158.

Dawood, A.H. and Mawlood, D.K., 2023. Flood Risk Analysis in Potential Points, Zerin City in Erbil as a Case Study. The Iraqi Geological Journal, pp.182-193.

Dawood, A.H., Mawlood, D.K. and Al-Ansari, N., 2021. Flood Modeling on Koya Catchment Area Using Hyfran, Web Map Service, and HEC-RAS Software. ARO-The Scientific Journal of Koya University, 9(2), pp.107-111.

Desalegn, H. and Mulu, A., 2021. Flood vulnerability assessment using GIS at Fetam watershed, upper Abbay basin, Ethiopia. Heliyon, 7(1).

Diaconu, D.C., Costache, R. and Popa, M.C., 2021. An overview of flood risk analysis methods. Water, 13(4), p.474.

Diriba, D., Takele, T., Karuppannan, S. and Husein, M., 2024. Flood hazard analysis and risk assessment using remote sensing, GIS, and AHP techniques: a case study of the Gidabo Watershed, main Ethiopian Rift, Ethiopia. Geomatics, Natural Hazards and Risk, 15(1), p.2361813.

Dwivedi, L., Pandey, R. and Tripathi, S., 2022. Remote sensing and GIS based morphometric characterization of Bichiya river watershed of Rewa district, MP. International Journal of Applied Research, 8(6), p.101.

Eryani, I.G.A.P., Jayantari, M.W. and Ramli, S., 2024. Determination of flood vulnerability level based on different numbers of indicators using AHP-GIS. SINERGI, 28(1), pp.13-22.

Fatah, K.K. and Mustafa, Y.T., 2022. Flood susceptibility mapping using an analytic hierarchy process model based on remote sensing and GIS approaches in Akre District, Kurdistan Region, Iraq. The Iraqi Geological Journal, pp.123-151.

Ghosh, D.K., Mandal, A.C., Majumder, R., Patra, P. and Bhunia, G.S., 2018. Analysis for mapping of built-up area using remotely sensed indices–A case study of Rajarhat Block in Barasat Sadar Sub-Division in West Bengal (India). Journal of Landscape Ecology, 11(2), pp.67-76.

Hariyono, M.I. and Kurniawan, A.A., 2022, September. The use of digital elevation model in a GIS for flood vulnerability: Case study of Sitiarjo Village Malang District East Java Indonesia. In IOP conference series: Earth and environmental science (Vol. 1039, No. 1, p. 012020). IOP Publishing.

Hoque, M.A.A., Tasfia, S., Ahmed, N. and Pradhan, B., 2019. Assessing spatial flood vulnerability at Kalapara Upazila in Bangladesh using an analytic hierarchy process. Sensors, 19(6), p.1302.

Huu Duy, N., Tuan Pham, L., Xuan Linh, N., Van Truong, T., Dang, D.K., Quang Hai, T. and Bui, Q.T., 2024. Flood risk assessment using machine learning, hydrodynamic modelling, and the analytic hierarchy process. Journal of Hydroinformatics, 26(8), pp.1852-1882.

Ibeabuchi, U., 2023. Lagos’ Vulnerability to Flood’s Changes Mapping Adopting Analytical Hierarchy Process Using Geographical Information System. Indonesian Journal of Multidisciplinary Science, 2(6), pp.2589-2608.

Ibrahim, J.R., 2021. Estimating the hazards of floods in the Gulasur Basin in the Sulaymaniyah Governorate-Kurdistan Region of Iraq. Journal of University of Anbar for Humanities, 2(2).

Ibrahim Mahmoud, M., Duker, A., Conrad, C., Thiel, M. and Shaba Ahmad, H., 2016. Analysis of settlement expansion and urban growth modelling using geoinformation for assessing potential impacts of urbanization on climate in Abuja City, Nigeria. Remote Sensing, 8(3), p.220.

Iliadis, C., Galiatsatou, P., Glenis, V., Prinos, P. and Kilsby, C., 2023. Urban flood modelling under extreme rainfall conditions for building-level flood exposure analysis. Hydrology, 10(8), p.172.

Jiménez‐Valverde, A., 2012. Insights into the area under the receiver operating characteristic curve (AUC) as a discrimination measure in species distribution modelling. Global Ecology and Biogeography, 21(4), pp.498-507.

Johnston, K., Ver Hoef, J.M., Krivoruchko, K. and Lucas, N., 2001. Using ArcGIS geostatistical analyst (Vol. 380). Redlands: Esri.

Sissakian, V.K., Al-Ansari, N., Adamo, N., Abdul Ahad, I.D. and Abed, S.A., 2022. Flood hazards in erbil City Kurdistan region Iraq, 2021: A case study. Engineering, 14(12), pp.591-601.

Kara, R. and Singh, P., 2024. Flood assessment for Lower Godavari basin by using the application of GIS-based analytical hierarchy process. International Journal of System Assurance Engineering and Management, pp.1-23.

Kaya, C.M. and Derin, L., 2023. Parameters and methods used in flood susceptibility mapping: a review. Journal of Water and Climate Change, 14(6), pp.1935-1960.

Khaddari, A., Jari, A., Chakiri, S., El Hadi, H., Labriki, A., Hajaj, S., El Harti, A., Goumghar, L. and Abioui, M., 2023. A comparative analysis of analytical hierarchy process and fuzzy logic modeling in flood susceptibility mapping in the Assaka Watershed, Morocco. Journal of Ecological Engineering, 24(8), pp.62-83.

Khaldi, L., Elabed, A. and El Khanchoufi, A., 2023. Quantitative assessment of the relative impacts of different factors on flood susceptibility modelling: case study of Fez-Meknes region in Morocco. In E3S Web of Conferences (Vol. 364, p. 02005). EDP Sciences.

Khoeun, C., Sok, T., Chan, R., Khe, S., Ich, I., Chan, K. and Oeurng, C., 2022, November. Assessing Flood Hazard Index using Analytical Hierarchy Process (AHP) and Geographical Information System (GIS) in Stung Sen River Basin. In IOP Conference Series: Earth and Environmental Science (Vol. 1091, No. 1, p. 012031). IOP Publishing.

Klingenstein, A., Haritoglou, I., Schaumberger, M.M., Nentwich, M.M., Hein, R. and Schaller, U.C., 2011. Receiver operating characteristic analysis: calculation for the marker ‘melanoma inhibitory activity’in metastatic uveal melanoma patients. Melanoma research, 21(4), pp.352-356.

Kohen, J., 1960. A coefficient of agreement for nominal scale. Educ Psychol Meas, 20, pp.37-46.

Li, J., Zheng, A., Guo, W., Bandyopadhyay, N., Zhang, Y. and Wang, Q., 2023. Urban flood risk assessment based on DBSCAN and K-means clustering algorithm. Geomatics, Natural Hazards and Risk, 14(1), p.2250527.

Lin, P., Pan, M., Wood, E.F., Yamazaki, D. and Allen, G.H., 2021. A new vector-based global river network dataset accounting for variable drainage density. Scientific data, 8(1), p.28.

M Amen, A.R., Mustafa, A., Kareem, D.A., Hameed, H.M., Mirza, A.A., Szydłowski, M. and M. Saleem, B.K., 2023. Mapping of flood-prone areas utilizing GIS techniques and remote sensing: a case study of Duhok, Kurdistan Region of Iraq. Remote Sensing, 15(4), p.1102.

Magureanu, M., Sfîrcoci, M., Copacean, L. And Cojocariu, L., 2023. Flood Risk Of Grasslands In The Mountain Area Of Western Romania. Life Science And Sustainable Development, 4(1), Pp.111-119.

Manfreda, S., Samela, C. and Troy, T.J., 2017. The use of DEM-based approaches to derive a priori information on flood-prone areas. In Flood monitoring through remote sensing (pp. 61-79). Cham: Springer International Publishing.

Mechentel, E., Dairi, S., Djebbar, Y. and HAMMAR, Y., 2024. Flash flood risk mapping using Analytic Hierarchy Process and machine learning: case of Souk-Ahras City, Northeastern Algeria.

Megahed, H.A., Abdo, A.M., AbdelRahman, M.A., Scopa, A. and Hegazy, M.N., 2023. Frequency ratio model as tools for flood susceptibility mapping in urbanized areas: A case study from Egypt. Applied Sciences, 13(16), p.9445.

Membele, G.M., Naidu, M. and Mutanga, O., 2022. Examining flood vulnerability mapping approaches in developing countries: A scoping review. International Journal of Disaster Risk Reduction, 69, p.102766.

Mikail, A.Q. and Hamad, R., 2023. Mapping Flood Vulnerability by Applying EBF And AHP Methods, in the Iraqi Mountain Region. Science Journal of University of Zakho, 11(1), pp.1-10.

Mishra, R., Pundir, A.K. and Ganapathy, L., 2017. Evaluation and prioritisation of manufacturing flexibility alternatives using integrated AHP and TOPSIS method: Evidence from a fashion apparel firm. Benchmarking: An International Journal, 24(5), pp.1437-1465.

Moharir, K., Singh, M., Pande, C.B. and Varade, A.M., 2024. GIS Based Delineation of Flood Susceptibility Mapping Using Analytic Hierarchy Process in East Vidarbha Region, India. In Geospatial Practices in Natural Resources Management (pp. 305-329). Cham: Springer International Publishing.

Mokhtari, E., Abdelkebir, B., Djenaoui, A. and Hamdani, N.E.H., 2024. Integrated analytic hierarchy process and fuzzy analytic hierarchy process for Sahel watershed flood susceptibility assessment, Algeria. Water Practice & Technology, 19(2), pp.453-475.

Mujib, M.A., Apriyanto, B., Kurnianto, F.A., Ikhsan, F.A., Nurdin, E.A., Pangastuti, E.I. and Astutik, S., 2021. Assessment of flood hazard mapping based on analytical hierarchy process (AHP) and GIS: application in kencong district, jember regency, Indonesia.

Mukhtar, M.A., Shangguan, D., Ding, Y., Anjum, M.N., Banerjee, A., Butt, A.Q., Li, D., Yang, Q., Khan, A.A., Muhammad, A. and He, B.B., 2024. Integrated flood risk assessment in Hunza-Nagar, Pakistan: unifying big climate data analytics and multi-criteria decision-making with GIS. Frontiers in Environmental Science, 12, p.1337081.

Mushtaq, F., Mahmood, K., Hamid, M.C. and Tufail, R., 2021. A Comparative Study of Support Vector Machine and Maximum Likelihood Classification to Extract Land Cover of Lahore District, Punjab, Pakistan. Pakistan Journal of Scientific & Industrial Research Series A: Physical Sciences, 64(3), pp.265-274.

Mustafa, A., Szydłowski, M., Veysipanah, M. and Hameed, H.M., 2023. GIS-based hydrodynamic modeling for urban flood mitigation in fast-growing regions: a case study of Erbil, Kurdistan Region of Iraq. Scientific reports, 13(1), p.8935.

Mustafa, B.Y., Faisal, M.D., Roeland, D.W., Ahmed, A.R. and Arbili, M.M., 2025. Flash Flood Hazard Mapping Using Analytical Hierarchy Process (AHP) and GIS Application: In the Barzan Area of Iraqi Kurdistan Region. Zanco Journal of Pure and Applied Sciences, 37(1), pp.108-125.

Nguyen, H.N., Fukuda, H. and Nguyen, M.N., 2024. Assessment of the Susceptibility of Urban Flooding Using GIS with an Analytical Hierarchy Process in Hanoi, Vietnam. Sustainability, 16(10), p.3934.

Osman, S.A. and Das, J., 2023. GIS-based flood risk assessment using multi-criteria decision analysis of Shebelle River Basin in southern Somalia. SN Applied Sciences, 5(5), p.134.

Ozkan, S.P. and Tarhan, C., 2016. Detection of flood hazard in urban areas using GIS: Izmir case. Procedia Technology, 22, pp.373-381.

Panday, D., Maharjan, B., Chalise, D., Shrestha, R.K. and Twanabasu, B., 2018. Digital soil mapping in the Bara district of Nepal using kriging tool in ArcGIS. PloS one, 13(10), p.e0206350.

Qi, W., Ma, C., Xu, H., Chen, Z., Zhao, K. and Han, H., 2021. A review on applications of urban flood models in flood mitigation strategies. Natural Hazards, 108, pp.31-62.

Ray, S.K., 2024. Flood risk index mapping in data scarce region by considering GIS and MCDA (FRI mapping in data scarce region by considering GIS and MCDA). Environment, Development and Sustainability, pp.1-53.

Saaty, T.L. and Vargas, L.G., 2012. Models, methods, concepts & applications of the analytic hierarchy process (Vol. 175). Springer Science & Business Media.

Samansiri, S., Fernando, T. and Ingirige, B., 2022. Advanced technologies for offering situational intelligence in flood warning and response systems: A literature review. Water, 14(13), p.2091.

Sarmah, T. and Das, S., 2018. Urban flood mitigation planning for Guwahati: A case of Bharalu basin. Journal of environmental management, 206, pp.1155-1165.

Shivhare, V., Kumar, A., Kumar, R., Shashtri, S., Mallick, J. and Singh, C.K., 2024. Flood susceptibility and flood frequency modeling for lower Kosi Basin, India using AHP and Sentinel-1 SAR data in geospatial environment. Natural Hazards, 120(13), pp.11579-11610.

Staponites, L. R., Barták, V., Bílý, M., and Simon, O. P., 2019. Performance of landscape composition metrics for predicting water quality in headwater catchments. Scientific reports 9(1), 14405.

Stevanovic, Z. M., M., 2003. Hydrogeology of Northern Iraq, Climate, Hydrology, Geomorphology & Geology. FAO 1, 1–122

Talha, S., Maanan, M., Atika, H., and Rhinane, H., 2019. Prediction of flash flood susceptibility using fuzzy analytical hierarchy process (Fahp) algorithms and Gis: a study case of guelmim region In Southwestern of Morocco. The international archives of the photogrammetry, remote sensing and spatial information sciences 42, 407-414.

Thannoun, R. G., and Ismaeel , O. A., 2024. Flood risk vulnerability detection based on the developing topographic wetness index tool in geographic information system. IOP Conference Series: Earth and Environmental Science, IOP Publishing.

Ullah, K., and Zhang, J., 2020. GIS-based flood hazard mapping using relative frequency ratio method: A case study of Panjkora River Basin, eastern Hindu Kush, Pakistan. Plos one 15(3), e0229153.

Vojtek, M., and Vojteková, J., 2019. Flood susceptibility mapping on a national scale in Slovakia using the analytical hierarchy process. Water 11(2), 364.

Yagoub, M., Alsereidi, A. A., Mohamed, E. A., Periyasamy, P., Alameri, R., Aldarmaki, S., and Alhashmi, Y., 2020. Newspapers as a validation proxy for GIS modeling in Fujairah, United Arab Emirates: identifying flood-prone areas. Natural Hazards 104, 111-141.

Zia, S., Shirazi, S. A., and Nasar-u-Minallah, M., 2021. Vulnerability assessment of urban floods in lahore, pakistan using gis based integrated analytical hierarchy approach: vulnerability assessment of urban floods in lahore. Proceedings of the Pakistan Academy of Sciences, A. Physical and Computational Sciences 58(1): 85-96.

Zzaman, R. U., Nowreen, S., Billah, M., and Islam, A. S., 2021. Flood hazard mapping of Sangu River basin in Bangladesh using multi‐criteria analysis of hydro‐geomorphological factors. Journal of Flood Risk Management 14(3), e12715.