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Designation of Flood Risk Zones Using the Geographic Information System Technique and Remote Sensing Data in Wasit, Iraq

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Floods are a great concern for people and infrastructure, and this is an is‑sue which has increased in several regions around the globe in recent years. This study aims to evaluate flood risk areas and create a flood risk map using in‑tegrated remote sensing data and a geographic information system (GIS) in the Wasit governorate – eastern Iraq. Specifically, GIS‑based multi‑criteria analy‑sis (MCA) was used to map flood hazard areas using a four‑criteria layer which is as follows: flow accumulation, slope, rainfall, and elevation. These four layers are standardized and combined using the overlay approach in ArcGIS software and a final map was produced. The study area was divided into five zones based on the results map, namely: very low, low, medium, high, and very high, according to the flood risk area. The resulting map indicates that over 60% of the study area is likely to experience a high and very high level of propensity of flooding. This study could be useful for government planners and decision‑makers to predict potential flooding areas and enhance flood management plans.
Rocznik
Strony
129--140
Opis fizyczny
Bibliogr. 24 poz., rys.
Twórcy
  • Middle Technical University, Technical Institute of Baquba, Baquba, Diyala – Iraq
  • Middle Technical University, Technical Institute of Baquba, Baquba, Diyala – Iraq
  • Middle Technical University, Technical Institute of Baquba, Baquba, Diyala – Iraq
  • School of Engineering, Faculty of Engineering and Informatics, University of Bradford, Bradford, UK
Bibliografia
  • [1] Hewitt K.: Regions of Risk: A Geographical Introduction to Disasters. Longman, Essex 1997.
  • [2] Rincón D., Khan U., Armenakis C.: Flood risk mapping using GIS and multi criteria analysis: A greater Toronto area case study. Geosciences (Switzerland), vol. 8(8), 2018, 275. https://doi.org/10.3390/geosciences8080275.
  • [3] Zhou Q., Su J., Leng G., Peng J.: The Role of Hazard and Vulnerability in Mod ulating Economic Damages of Inland Floods in the United States Using a Survey Based Dataset. Sustainability, vol. 11(13), 2019, 3754. https://doi.org/ 10.3390/su11133754.
  • [4] Tehrany M.S., Lee M., Pradhan B., Jebur M.N., Lee S.: Flood susceptibility mapping using integrated bivariate and multivariate statistical models. Environmental Earth Sciences, vol. 72, 2014, pp. 4001–4015. https://doi.org/10.1007/s12665 014 3289 3.
  • [5] 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, vol. 7(3), 2016, pp. 1000–1017. https://doi.org/10.1080/19475705.2015.1045043.
  • [6] Dano U.L., Balogun A.L., Matori A.N., Wan Yusouf K., Rimi Abubakar I., Mohamed S., Ahmed M., Aina Y.A., Pradhan B.: Flood susceptibility mapping using GIS based analytic network process: A case study of Perlis, Malaysia. Water, vol. 11(3), 2019, 615. https://doi.org/10.3390/w11030615.
  • [7] Bui D.T., Pradhan B., Nampak H., Bui Q.T., Tran Q.A., Nguyen Q.P.: Hybrid artificial intelligence approach based on neural fuzzy inference model and metaheuristic optimization for flood susceptibility modeling in a high-frequency tropical cyclone area using GIS. Journal of Hydrology, vol. 540, 2016, pp. 317–330. https://doi.org/10.1016/j.jhydrol.2016.06.027.
  • [8] Tomaszewski B., Judex M., Szarzynski J., Radestock C., Wirkus L.: Geographic information systems for disaster response: A review. Journal of Homeland Security and Emergency Management, vol. 12(3), 2015, pp. 571–602. https://doi.org/10.1515/jhsem 2014 0082.
  • [9] Trnka J.: Hazmat Transportation Accidents: Introducing GIS as a core Information System in Emergency management. Final Thesis. Linköpings Universitet. Institutionen för datavetenskap – IDA, Linköpings 2002.
  • [10] Al Abadi A.M., Shahid S., Al Ali A.K.: A GIS based integration of catastrophe theory and analytical hierarchy process for mapping flood susceptibility: a case study of Teeb area, Southern Iraq. Environmental Earth Sciences, vol. 75(8), 2016, 687. https://doi.org/10.1007/s12665 016 5523 7.
  • [11] Al Saady Y.I., Al Suhail Q.A., Al Tawash B.S., Othman A.A.: Drainage network extraction and morphometric analysis using remote sensing and GIS mapping techniques (Lesser Zab River Basin, Iraq, and Iran). Environmental Earth Sciences, vol. 75(18), 2016, 1243. https://doi.org/10.1007/s12665 016 6038 y.
  • [12] Jaber H.S., Mansor S., Pradhan B., Ahmad N.: Rainfall–runoff modelling and water balance analysis for Al Hindiyah barrage, Iraq using remote sensing and GIS. Geocarto International, vol. 32(12), 2017, pp. 1407–1420. https://doi.org/ 10.1080/10106049.2016.1213889.
  • [13] Abdulrazzaq Z.T., Aziz N.A., Mohammed A.A.: Flood modelling using satellite based precipitation estimates and digital elevation model in eastern Iraq. International Journal of Advanced Geosciences, vol. 6(1), 2018, pp. 72–77. https://doi.org/10.14419/ijag.v6i1.8946.
  • [14] Al Abadi A.M.: Mapping flood susceptibility in an arid region of southern Iraq using ensemble machine learning classifiers: a comparative study. Arabian Journal of Geosciences, vol. 11(9), 2018, 218. https://doi.org/10.1007/s12517 018 3584 5.
  • [15] Iraqi Red Crescent Society: Wasit and Maysan are most affected by torrents and the Iraqi Red Crescent mobilizes its relief teams to provide shelter, food and relief assistance. 14 April 2019. https://reliefweb.int/report/iraq/wasit and maysan are most affected torrents and iraqi red crescent mobilizes its relief [access: 18.11.2020].
  • [16] Obeydi A.L., AAl Hummadi S.K., ALSaady A.H.: Early flood detection using SAR images and remote sensing techniques case study Kut city in Iraq. IOP Conference Series: Materials Science and Engineering, vol. 737, 2020, 012221. https://doi.org/10.1088/1757899X/737/1/012221.
  • [17] Dang N.M., Babel M.S., Luong H.T.: Evaluation of food risk parameters in the Day River Flood Diversion Area, Red River Delta, Vietnam. Natural Hazards, 56, 2010, pp. 169–194. https://doi.org/10.1007/s11069 010 9558 x.
  • [18] Al Hassany G.S.: Study the Flood of 2015 in Wasit Province in Iraq. Indian Journal of Natural Sciences, vol. 9(51), 2018, pp. 15811–15816.
  • [19] Shamkhi M.S., Azeez J.M.R., Abdul Sahib A.A.: Morphologic and Engineering Characteristics of Watersheds (A Case Study: East Wasit Watersheds that Feed the Al Shewicha Trough – Iraq). IOP Conference Series: Materials Science and Engineering, vol. 870, 2020, 012115. https://doi.org/10.1088/1757 899X/870/1/012115.
  • [20] Muslim R.I., Issa M.J., AL Obaidi B.S.: Environmental Assessment of heavy metals Concentration and Distribution in Surface Soils of Wasit Governorate/ Iraq. Iraqi Journal of Science, vol. 60(4), 2019, pp. 803–818.
  • [21] Malczewski J.: GIS based multicriteria decision analysis: a survey of the literature. International Journal of Geographical Information Science, vol. 20(7), 2006, pp. 703–726. https://doi.org/10.1080/13658810600661508.
  • [22] Schäuble H., Marinoni O., Hinderer M.: A GIS based method to calculate flow accumulation by considering dams and their specific operation time. Computers & Geosciences, vol. 34(6), 2008, pp. 635–646. https://doi.org/10.1016/j.cageo. 2007.05.023.
  • [23] Kwak Y., Kondoh A.: A study on the extraction of multifactor influencing floods from RS image and GIS data; a case study in Nackdong Basin, S. Korea. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol. 37, part B8, 2008, pp. 421–426.
  • [24] Camarasa Belmonte A.M., Segura Beltran F.: Flood events in Mediterranean ephemeral streams (ramblas) in Valencia region, Spain. Catena, vol. 45(3), 2001, pp. 229–249. https://doi.org/10.1016/S0341 8162(01)00146 1.
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021)
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-a81df221-bb2b-4524-b9f9-a01d76215ec0
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