1. Home
  2. 2023-V9-I3
  3. Assessing the impact of urbanization on flood hazards in Ranya city, using GIS and remote sensing

Article Views: 578

PDF Downloads: 136

  • Date of Publication : 2024-01-21 Article Type : Research Article
  • Assessing the impact of urbanization on flood hazards in Ranya city, using GIS and remote sensing

    Kaifi Chomani ¹*


    ¹ Civil Engineering Department, University of Raparin, Ranya, Sulaymaniyah, Kurdistan Region 46012, Iraq.
    *Corresponding Author

    ORCID :

    Kaifi Chomani : https://orcid.org/0000-0001-7323-2281

    DOI :


    Article History

    Received: 2023-06-13

    Revised: 2024-01-15

    Accepted: 2024-01-17


    Flooding is a major threat to people and the environment all over the world. Ranya city has experienced an increase in flooding as a result of demographic shifts, variations in land use land cover (LULC), and urban development. The objective of this research is to assess the effects of urban growth on flooding in Ranya over a 23-year period. The nine factors used to evaluate flood risk maps were elevation, rainfall, topographic wetness index (TWI), stream power index (SPI), LULC, slope, aspect, drainage density, and distance to roads. Flood hazard and LULC maps were created and analysed using The Analytic Hierarchy Process (AHP), geographic information system (GIS), and satellite remote sensing data for the years 2000 and 2023. The result revealed from 2000 to 2023, the settlement and agricultural area increased by approximately 25 and 9.6%, respectively, while barren land decreased by 34.8%. The 0.09% annual growth in the built-up area was a major factor in the expansion of Ranya's high flood-risk areas. Low, moderate, high, and very high categories were used to define the flood risk areas in Ranya. In zones with a very high flood risk, the extent of the flood hazard area in 2023 increased by 1.9% compared to 2000, while it decreased by 11.4% in zones with a low flood risk. Urban areas, and especially city centres, are significantly more likely to experience flooding. Ranya has seen an enormous increase in the amount of flood-prone areas in the last 23 years due to the city's urbanisation. This study used AHP technique that enables researchers to efficiently monitor the urban environment, which may then be used to substantially reduce damages in Ranya City's flood-prone zones. It also assists decision-makers and state officials in understanding how urban growth affects the environment.

    Keywords :

    Flood Hazard; GIS; Urbanization; AHP; Remote Sensing; Ranya

    [1]    Khosravi K, Shahabi H, Pham BT, Adamowski J, Shirzadi A, Pradhan B, et al. A comparative assessment of flood susceptibility modeling using multi-criteria decision-making analysis and machine learning methods. Journal of Hydrology. 2019; 573: 311-23. https://doi.org/10.1016/j.jhydrol.2019.03.073
    [2]    Malik S, Pal SC, Chowdhuri I, Chakrabortty R, Roy P, Das B. Prediction of highly flood prone areas by GIS based heuristic and statistical model in a monsoon dominated region of Bengal Basin. Remote Sensing Applications: Society and Environment. 2020; 19: 100343. https://doi.org/10.1016/j.rsase.2020.100343.
    [3]    Markantonis V, Meyer V, Lienhoop N. Evaluation of the environmental impacts of extreme floods in the Evros River basin using Contingent Valuation Method. Natural hazards. 2013; 69: 1535-49. https://doi.org/10.1007/s11069-013-0762-3.
    [4]    Borzi G, Roig A, Tanjal C, Santucci L, Tejada Tejada M, Carol E. Flood hazard assessment in large plain basins with a scarce slope in the Pampean Plain, Argentina. Environmental Monitoring and Assessment. 2021; 193: 1-14. https://doi.org/10.1007/s10661-021-08988-1.
    [5]    Malik S, Pal SC, Arabameri A, Chowdhuri I, Saha A, Chakrabortty R, et al. GIS-based statistical model for the prediction of flood hazard susceptibility. Environment, Development and Sustainability. 2021; 23: 16713-43. https://doi.org/10.1007/s10668-021-01377-1.
    [6]    Samanta RK, Bhunia GS, Shit PK, Pourghasemi HR. Flood susceptibility mapping using geospatial frequency ratio technique: a case study of Subarnarekha River Basin, India. Modeling Earth Systems and Environment. 2018; 4: 395-408. https://doi.org/10.1007/s40808-018-0427-z.
    [7]    Aryal D, Wang L, Adhikari TR, Zhou J, Li X, Shrestha M, et al. A model-based flood hazard mapping on the southern slope of Himalaya. Water. 2020;12(2):540. https://doi.org/10.3390/w12020540.
    [8]    Prama M, Omran A, Schröder D, Abouelmagd A. Vulnerability assessment of flash floods in Wadi Dahab Basin, Egypt. Environmental Earth Sciences. 2020; 79: 1-17. https://doi.org/10.1007/s12665-020-8860-5.
    [9]    Petrucci O, Aceto L, Bianchi C, Bigot V, Brázdil R, Pereira S, et al. Flood fatalities in Europe, 1980–2018: Variability, features, and lessons to learn. Water. 2019;11(8):1682. https://doi.org/10.3390/w11081682.
    [10]    Wang X, Xia J, Dong B, Zhou M, Deng S. Spatiotemporal distribution of flood disasters in Asia and influencing factors in 1980–2019. Natural Hazards. 2021;108(3):2721-38. https://doi.org/10.1007/s11069-021-04798-3.
    [11]    Hajat S, Ebi KL, Kovats S, Menne B, Edwards S, Haines A. The human health consequences of flooding in Europe and the implications for public health: a review of the evidence. Applied Environmental Science and Public Health. 2003; 1: 13-21.
    [12]    Christensen JH, Christensen OB. Severe summertime flooding in Europe. Nature. 2003;421(6925):805-6. https://doi.org/10.1038/421805a.
    [13]    Costache R, Arabameri A, Blaschke T, Pham QB, Pham BT, Pandey M, et al. Flash-flood potential mapping using deep learning, alternating decision trees and data provided by remote sensing sensors. Sensors. 2021;21(1):280. https://doi.org/10.3390/s21010280.
    [14]    Roy P, Pal SC, Chakrabortty R, Chowdhuri I, Malik S, Das B. Threats of climate and land use change on future flood susceptibility. Journal of Cleaner Production. 2020; 272: 122757. https://doi.org/10.1016/j.jclepro.2020.122757.
    [15]    Saha A, Pal SC, Arabameri A, Blaschke T, Panahi S, Chowdhuri I, et al. Flood susceptibility assessment using novel ensemble of hyperpipes and support vector regression algorithms. Water. 2021;13(2):241. https://doi.org/10.3390/w13020241.
    [16]    Takeuchi K, Chavoshian A, Simonovic SP. Floods: from risk to opportunity. J Flood Risk Manag. 2018; 11: e12046. https://doi.org/10.1111/jfr3.12046.
    [17]    Cred U. Economic Losses, Poverty & Disasters 1998-2017. Université Catholique de Louvain (UCL), Brussels, Belgium. 2018;33.
    [18]    Natarajan S, Radhakrishnan N. Flood hazard delineation in an ungauged catchment by coupling hydrologic and hydraulic models with geospatial techniques—A case study of Koraiyar basin, Tiruchirappalli City, Tamil Nadu, India. Environmental Monitoring and Assessment. 2020;192(11):689. https://doi.org/10.1007/s10661-020-08650-2.
    [19]    UCAR. 2010 [Available from: https://www.meted.ucar.edu/.
    [20]    Sunkpho J, Ootamakorn C. Real-time flood monitoring and warning system. Songklanakarin Journal of Science & Technology. 2011;33(2).
    [21]    Minh PT, Tuyet BT, Thao TTT. Application of ensemble Kalman filter in WRF model to forecast rainfall on monsoon onset period in South Vietnam. Science of the Earth. 2018;40(4):367-94. https://doi.org/10.15625/0866-7187/40/4/13134.
    [22]    Malczewski J. GIS‐based multicriteria decision analysis: a survey of the literature. International journal of geographical information science. 2006;20(7):703-26. https://doi.org/10.1080/13658810600661508.
    [23]    Rahmati O, Zeinivand H, Besharat M. Flood hazard zoning in Yasooj region, Iran, using GIS and multi-criteria decision analysis. Geomatics, Natural Hazards and Risk. 2016;7(3):1000-17. https://doi.org/10.1080/19475705.2015.1045043.
    [24]    Zope P, Eldho T, Jothiprakash V. Impacts of urbanization on flooding of a coastal urban catchment: a case study of Mumbai City, India. Natural Hazards. 2015; 75: 887-908. https://doi.org/10.1080/19475705.2015.1045043.
    [25]    Dewan AM, Yamaguchi Y. Land use and land cover change in Greater Dhaka, Bangladesh: Using remote sensing to promote sustainable urbanization. Applied geography. 2009;29(3):390-401. http://dx.doi.org/10.1016/j.apgeog.2008.12.005.
    [26]    Zope PE, Eldho TI, Jothiprakash V. Impacts of land use–land cover change and urbanization on flooding: A case study of Oshiwara River Basin in Mumbai, India. CATENA. 2016;145:142-54 DOI: https://doi.org/10.1016/j.catena.2016.06.009.
    [27]    USGS. 2023 [Available from: https://earthexplorer.usgs.gov/.
    [28]    Melesse AM, Shih S. Spatially distributed storm runoff depth estimation using Landsat images and GIS. Computers and Electronics in Agriculture. 2002;37(1-3):173-83. https://doi.org/10.1016/S0168-1699(02)00111-4.
    [29]    CCKP. 2023 [Available from: https://climateknowledgeportal.worldbank.org/.
    [30]    ThiknH. 2023 [Available from: https://thinkhazard.org/en/.
    [31]    Ahmed A, Al Maliki A, Hashim B, Alshamsi D, Arman H. Flood Susceptibility Mapping of the Northern Iraq Using Morphometric and Principal Component Analyses. 2023. https://doi.org/10.1038/s41598-023-39290-4.
    [32]    Suriya S, Mudgal B. Impact of urbanization on flooding: The Thirusoolam sub watershed–A case study. Journal of hydrology. 2012; 412: 210-9. https://doi.org/10.1016/j.jhydrol.2011.05.008.
    [33]    Milly PC, Betancourt J, Falkenmark M, Hirsch RM, Kundzewicz ZW, Lettenmaier DP, et al. Stationarity is dead: Whither water management? Science. 2008;319(5863):573-4. https://doi.org/10.1126/science.1151915https://doi.org/10.1016/j.jhydrol.2011.05.008.
    [34]    Dewan AM, Kumamoto T, Nishigaki M. Flood hazard delineation in greater Dhaka, Bangladesh using an integrated GIS and remote sensing approach. Geocarto International. 2006;21(2):33-8. https://doi.org/10.1080/10106040608542381.
    [35]    Qi H, Altinakar MS. A GIS-based decision support system for integrated flood management under uncertainty with two dimensional numerical simulations. Environmental Modelling & Software. 2011;26(6):817-21. https://doi.org/10.1016/j.envsoft.2010.11.006.
    [36]    Pramojanee P, Tanavud C, Yongchalermchai C, Navanugraha C, editors. An application of GIS for mapping of flood hazard and risk area in Nakorn Sri Thammarat Province, South of Thailand. Proceedings of International Conference on Geo-Information for Sustainable Management; 1997.
    [37]    Kourgialas NN, Karatzas GP. Flood management and a GIS modelling method to assess flood-hazard areas—a case study. Hydrological Sciences Journal–Journal des Sciences Hydrologiques. 2011;56(2):212-25. https://doi.org/10.1080/02626667.2011.555836.
    [38]    González-Arqueros ML, Mendoza ME, Bocco G, Castillo BS. Flood susceptibility in rural settlements in remote zones: The case of a mountainous basin in the Sierra-Costa region of Michoacán, Mexico. Journal of environmental management. 2018; 223: 685-93. https://doi.org/10.1016/j.jenvman.2018.06.075.
    [39]    Wheater H, Jakeman A, Beven K. Progress and directions in rainfall-runoff modelling. 1993.
    [40]    Bulti DT, Abebe BG. A review of flood modeling methods for urban pluvial flood application. Modeling earth systems and environment. 2020; 6: 1293-302. https://doi.org/10.1007/s40808-020-00803-z.
    [41]    Tehrany MS, Kumar L. The application of a Dempster–Shafer-based evidential belief function in flood susceptibility mapping and comparison with frequency ratio and logistic regression methods. Environmental earth sciences. 2018; 77: 1-24. https://doi.org/10.1007/s12665-018-7667-0.
    [42]    Falah F, Rahmati O, Rostami M, Ahmadisharaf E, Daliakopoulos IN, Pourghasemi HR. Artificial neural networks for flood susceptibility mapping in data-scarce urban areas.  Spatial modeling in GIS and R for Earth and Environmental Sciences: Elsevier; 2019. p. 323-36. https://doi.org/10.1016/B978-0-12-815226-3.00014-4.
    [43]    Dodangeh E, Panahi M, Rezaie F, Lee S, Bui DT, Lee C-W, et al. Novel hybrid intelligence models for flood-susceptibility prediction: Meta optimization of the GMDH and SVR models with the genetic algorithm and harmony search. Journal of Hydrology. 2020; 590: 125423. https://doi.org/10.1016/j.jhydrol.2020.125423.
    [44]    Wang Y, Hong H, Chen W, Li S, Panahi M, Khosravi K, et al. Flood susceptibility mapping in Dingnan County (China) using adaptive neuro-fuzzy inference system with biogeography based optimization and imperialistic competitive algorithm. Journal of environmental management. 2019; 247: 712-29. https://doi.org/10.1016/j.jenvman.2019.06.102.
    [45]    Zhu G-N, Hu J, Qi J, Gu C-C, Peng Y-H. An integrated AHP and VIKOR for design concept evaluation based on rough number. Advanced Engineering Informatics. 2015;29(3):408-18. https://doi.org/10.1016/j.aei.2015.01.010.
    [46]    Qaiser K, Yuan Y, Lopez R. Urbanization impacts on flooding in the Kansas River Basin and evaluation of wetlands as a mitigation measure. Transactions of the ASABE. 2012;55(3):849-59.
    [47]    Sissakian VK, Al-Ansari N, Adamo N, Abdul Ahad ID, Abed SA. Flood Hazards in Erbil City Kurdistan Region Iraq, 2021: A Case Study. Engineering. 2022;14(12):591-601. https://doi.org/10.4236/eng.2022.1412044.
    [48]    Askar S, Zeraat Peyma S, Yousef MM, Prodanova NA, Muda I, Elsahabi M, et al. Flood Susceptibility Mapping Using Remote Sensing and Integration of Decision Table Classifier and Metaheuristic Algorithms. Water. 2022;14(19):3062. https://doi.org/10.3390/w14193062.
    [49]    Gigović L, Pamučar D, Božanić D, Ljubojević S. Application of the GIS-DANP-MABAC multi-criteria model for selecting the location of wind farms: A case study of Vojvodina, Serbia. Renewable energy. 2017; 103: 501-21. https://doi.org/10.1016/j.renene.2016.11.057.
    [50]    Zhong Q-b, Chen F. Trajectory planning for biped robot walking on uneven terrain–Taking stepping as an example. CAAI Transactions on intelligence technology. 2016;1(3):197-209. https://doi.org/10.1016/j.trit.2016.10.009.
    [51]    Gigović L, Pamučar D, Bajić Z, Milićević M. The combination of expert judgment and GIS-MAIRCA analysis for the selection of sites for ammunition depots. Sustainability. 2016;8(4):372. https://doi.org/10.3390/su8040372.
    [52]    Sowmya K, John C, Shrivasthava N. Urban flood vulnerability zoning of Cochin City, southwest coast of India, using remote sensing and GIS. Natural Hazards. 2015; 75: 1271-86.
    [53]    Wang Y, Li Z, Tang Z, Zeng G. A GIS-based spatial multi-criteria approach for flood risk assessment in the Dongting Lake Region, Hunan, Central China. Water resources management. 2011; 25: 3465-84. https://doi.org/10.1007/s11069-014-1372-4.
    [54]    Gerl T, Bochow M, Kreibich H. Flood damage modeling on the basis of urban structure mapping using high-resolution remote sensing data. Water. 2014;6(8):2367-93. https://doi.org/10.3390/w6082367.
    [55]    Chau VN, Holland J, Cassells S, Tuohy M. Using GIS to map impacts upon agriculture from extreme floods in Vietnam. Applied Geography. 2013; 41: 65-74. https://doi.org/10.1016/j.apgeog.2013.03.014.
    [56]    Kazakis N, Kougias I, Patsialis T. Assessment of flood hazard areas at a regional scale using an index-based approach and Analytical Hierarchy Process: Application in Rhodope–Evros region, Greece. Science of the Total Environment. 2015; 538: 555-63. https://doi.org/10.1016/j.scitotenv.2015.08.055.
    [57]    Papaioannou G, Vasiliades L, Loukas A. Multi-criteria analysis framework for potential flood prone areas mapping. Water resources management. 2015; 29: 399-418. https://doi.org/10.1007/s11269-014-0817-6.
    [58]    Meyer V, Scheuer S, Haase D. A multicriteria approach for flood risk mapping exemplified at the Mulde river, Germany. Natural hazards. 2009; 48: 17-39. https://doi.org/10.1007/s11069-008-9244-4.
    [59]    Gigović L, Pamučar D, Bajić Z, Drobnjak S. Application of GIS-interval rough AHP methodology for flood hazard mapping in urban areas. Water. 2017;9(6):360. https://doi.org/10.3390/w9060360.
    [60]    Fernández D, Lutz MA. Urban flood hazard zoning in Tucumán Province, Argentina, using GIS and multicriteria decision analysis. Engineering Geology. 2010;111(1-4):90-8. http://dx.doi.org/10.1016/j.enggeo.2009.12.006.
    [61]    Siddayao GP, Valdez SE, Fernandez PL. Analytic hierarchy process (AHP) in spatial modeling for floodplain risk assessment. International Journal of Machine Learning and Computing. 2014;4(5):450. https://doi.org/10.7763/IJMLC.2014.V4.453.
    [62]    Liu H, Tang H, Xiao W, Guo Z, Tian L, Gao Y. Sequential Bag-of-Words model for human action classification. CAAI Transactions on Intelligence Technology. 2016;1(2):125-36. 
    [63]    Bathrellos G, Karymbalis E, Skilodimou H, Gaki-Papanastassiou K, Baltas E. Urban flood hazard assessment in the basin of Athens Metropolitan city, Greece. Environmental Earth Sciences. 2016; 75: 1-14. https://doi.org/10.1007/s12665-015-5157-1.
    [64]    Liu H, Wang C, Gao Y. Scene-adaptive hierarchical data association and depth-invariant part-based appearance model for indoor multiple objects tracking. CAAI Transactions on Intelligence Technology. 2016;1(3):210-24.
    [65]    GKSAT. 2023 [Available from: https://www.gksat.tv/.
    [66]    KTV. 2023 [Available from: https://kurdistantv.net/.
    [67]    KPD. 2023 [Available from: https://www.kurdipedia.org/.
    [68]    PUK. 2023 [Available from: https://www.pukmedia.com/.
    [69]    XENDAN. 2023 [Available from: https://www.xendan.org/.
    [70]    K24. 2023 [Available from: https://www.kurdistan24.net/en.
    [71]    Gaznayee HAA, Al-Quraishi AMF, Mahdi K, Messina JP, Zaki SH, Razvanchy HAS, et al. Drought Severity and Frequency Analysis Aided by Spectral and Meteorological Indices in the Kurdistan Region of Iraq. Water. 2022;14(19):3024. https://doi.org/10.3390/w14193024.
    [72]    Mustafa N. ARIDITY INDEX BASED ON TEMPERATURE AND RAINFALL DATA FOR KURDISTAN REGION-IRAQ. The Journal of The University of Duhok. 2018; 21: 65-80. https://doi.org/10.26682/sjuod.2018.21.1.6.
    [73]    Ghosh A, Kar SK. Application of analytical hierarchy process (AHP) for flood risk assessment: a case study in Malda district of West Bengal, India. Natural Hazards. 2018; 94: 349-68. https://doi.org/10.1007/s11069-018-3392-y.
    [74]    Allafta H, Opp C. 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. 2021;12(1):2087-116. https://doi.org/10.1080/19475705.2021.1955755.
    [75]    Aydin MC, Sevgi Birincioğlu E. Flood risk analysis using gis-based analytical hierarchy process: a case study of Bitlis Province. Applied Water Science. 2022;12(6):122. https://doi.org/10.1007/s13201-022-01655-x.
    [76]    ESRI. 2023 [Available from: https://www.esri.com/.
    [77]    Termeh SVR, Kornejady A, Pourghasemi HR, Keesstra S. Flood susceptibility mapping using novel ensembles of adaptive neuro fuzzy inference system and metaheuristic algorithms. Science of the Total Environment. 2018; 615: 438-51. https://doi.org/10.1016/j.scitotenv.2017.09.262.
    [78]    Khan SI, Hong Y, Wang J, Yilmaz KK, Gourley JJ, Adler RF, et al. Satellite remote sensing and hydrologic modeling for flood inundation mapping in Lake Victoria basin: Implications for hydrologic prediction in ungauged basins. IEEE Transactions on Geoscience and Remote Sensing. 2010;49(1):85-95. https://doi.org/10.1109/TGRS.2010.2057513.

     author = {Chomani, Kaifi},
     title = {Assessing the impact of urbanization on flood hazards in Ranya city, using GIS and remote sensing},
     journal = {Eurasian J. Sci. Eng},
     volume = {9},
     number = {3},
     pages = {154-165},
     year = {2023}

    Chomani, K. (2023). Assessing the impact of urbanization on flood hazards in Ranya city, using GIS and remote sensing. Eurasian J. Sci. Eng, 9(3),154-165.


    Chomani K. "Assessing the impact of urbanization on flood hazards in Ranya city, using GIS and remote sensing." Eurasian J. Sci. Eng, 9.3, (2023), pp.154-165.


    Chomani, K. (2023) "Assessing the impact of urbanization on flood hazards in Ranya city, using GIS and remote sensing", Eurasian J. Sci. Eng, 9(3), pp.154-165.


    Chomani K. Assessing the impact of urbanization on flood hazards in Ranya city, using GIS and remote sensing. Eurasian J. Sci. Eng. 2023; 9(3):154-165.


    Under Development

    Under Development

    Under Development

  • Assessing the impact of urbanization on flood hazards in Ranya city, using GIS and remote sensing