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بررسی حساسیت به رخ‌داد سیل در آبخیز عموقین با کاربرد فرآیند تحلیل سلسله‌مراتبی | ||
| پژوهش های آبخیزداری | ||
| مقاله 9، دوره 34، شماره 2 - شماره پیاپی 131، تیر 1400، صفحه 108-123 اصل مقاله (1.58 M) | ||
| نوع مقاله: پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22092/wmej.2021.128834.1295 | ||
| نویسنده | ||
| یاسر حسینی* | ||
| دانشیار دانشکده کشاورزی و منابع طبیعی مغان- دانشگاه محقق اردبیلی | ||
| چکیده | ||
| آگاهی از آب‌دهی سیل در پژوهش‌های بهره‌وری از منابع آب و کاهش‌دادن زیان‌های سیل اهمیت زیادی دارد. این پژوهش با هدف به‌کاربردن سامانه‌ی تحلیل سلسله‌مراتبی برای تعیین‌کردن منطقه‌های پرخطر از نظر سیل‌گیری در آبخیز عموقین، استان اردبیل، انجام شد. مساحت آبخیز 78 کیلومتر مربع است. برای تعیین‌کردن مقدار شماره‌ی منحنی منطقه، تلفیق نقشه‌ی کاربری زمین و گروه نفوذپذیری خاک (B، C، و D) به‌کار برده شد، که برای سال 1394 به‌اندازه‌ی 78/7 برآورد شد. شاخص‌های موثر بر سیلاب شامل شیب، شماره‌ی منحنی، فاصله از رودخانه، توان فرسایش آبراه، شاخص رطوبت پستی‌بلندی، جهت شیب، بارندگی، و ارتفاع بررسی، و لایه‌های موثر بر خطر سیل‌خیزی به نُه رده طبقه‌بندی شد .نقشه‌ی پهنه‌بندی خطر سیل‌گیری با پنج رده‌ی خیلی کم، کم، متوسط، زیاد، و خیلی زیاد به‌دست آمد. نتیجهها نشان داد که بیش‌ترین تاثیر بر خطر سیل‌گیری از شماره‌ی منحنی نفوذ بود. فاصله از رودخانه و اندازه‌ی بارندگی در رده‌های بعدی اهمیت، و کم‌ترین شاخص تاثیرگزار شکل شیب بود. نتیجهها نشان‌داد که 0/64 و 4/4% از منطقه‌ی بررسی‌شده به‌ترتیب منطقه‌های با خطرسیل‌خیزی زیاد و خیلی کم است. | ||
| کلیدواژه‌ها | ||
| آبخیز؛ اردبیل؛ تحلیل حساسیت؛ تحلیل سلسله‌مراتبی؛ سیلاب | ||
| عنوان مقاله [English] | ||
| Assessing the Flooding Susceptibility in the Amuqin Watershed Using the Analytical Hierarchy Process Method | ||
| نویسندگان [English] | ||
| Yaser Hoseini | ||
| Moghan College of Agriculture and Natural resources, University of Mohaghegh Ardabili, Ardabil, Iran | ||
| چکیده [English] | ||
| Knowledge of the flood discharge rate is of the utmost importance in water resources utilization and flooding damage mitigation studies. Therefore, the aim of the current research was mainly to assess the Analytical Hierarchy Process (AHP) method to predict the flooding susceptibility of the Amughin Basin, located in the Province of Ardabil. The basin¢s area is approximately 78 km2. The curve number (CN) of the basin was found by integrating the land use maps with the soil hydrologic groups namely: B, C, D. The CN was estimated 78.7 the year for 2015. Different effective factors, namely: the slope percentage, land curvature, distance from the river, topographic wetness index, stream power index (SPI), and the CN were used in the application of the AHP method, and the effective layers were classified into nine classes. A flooding into susceptibility map was constructed and classified into five classes with very low, low, moderate, high, and very high susceptibility. The results indicated that the CN was the most prominent in flooding susceptibility; the distance to the river and the amount of rain occupied the next priorities. The lowest factor in the flooding susceptibility was related to the plan curvature. Moreover, the results indicated that about 0.64% and 4.4% of the study area were categorize with high and very low sensitivities, respectively. | ||
| کلیدواژه‌ها [English] | ||
| Watershed, Ardabil, susceptibility analysis, Analytical Hierarchy Process, flooding | ||
| مراجع | ||
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Abdullah AF, Vojinovic Z, Rahman AA. 2013. A methodology for processing raw LiDAR data to support urban flood modelling framework (Case study: Kuala Lumpur Malaysia). In: Rahman AA, Boguslawski P, Gold C, Said M (eds) Developments in multidimensional spatial data models. Springer, Berlin, pp 49–68. Amir Ahmadi A, Mohammadnia M, Golshani N. 2015. Analysis of geomorphological factors influencing the flood using the HEC-HMS model. Hydro Geomorphology, 1(3):21–42. (In Persian). Anderson JR, Hardy ET, Roach JT, Witmer RE. 1976. A land use and land cover classification system for use with remote sensor data. U.S. Geol. Survey prof. Paper 964. U.S. Government Printing Office, Washington, DC. Alizadeh A. 2001. Principals of applied hydrology, Mashhad, Astan Ghods Razavi press, 13th edition, (In Persian). Azam M, Hyung SK, Seung JM. 2017. Development of flood alert application in Mushim stream watershed Korea. International Journal of Disaster Risk Reduction. 21(3): 11–26. Badri B, Zare Bidaki R, Honarbakhsh A, Atashkhar F. 2014. Prioritization of flooding potential in Beheshtabad Sub Basins. Natural Geography Research, 48(1): 143–158. (In Persian). Fernandez DS, Lutz MA. 2010. Urban flood Hazard Zoning in Tucumán Province, Argentina, Using GIS and Multicriteria Decision Analysis. Engineering Geology. 111(4): 90–98. García-Pintado J, Neal JC, Mason DC, Dance SL, Bates PD. 2013. Scheduling satellite-based SAR acquisition for sequential assimilation of water level observations into flood modeling. Journal of Hydrology. 495(1): 252–266. Ghasemi A, Salajegheh A, Malekian A, Esmaliouri A. 2019. Investigation of flooding and causative factors in Balegli Chay Watershed by GIS, RS, and AHP techniques, Journal of Environmental Studies. 40(2(: 389–400. (In Persian). Hoseini Y, Ramezani Moghaddam J, Abdolalizadeh Z. 2019. Evaluating the impact of land use changes on flooding and flood runoff in Amuqin Drainage Basin. Journal of Natural Environmental Hazards. 8(22): 145–163. (In Persian). Khairizadeh-Arugh M, Maleki J, Amunia H. 2019. Zoning of flood risk potential in Mardeghai catchment using model ANP. Quantitative Geomorphology Research. 1(3): 39–56. (In Persian). Khosravi K, Pourghasemi HR, Chapi K, Bahri M. 2016. Flash flood susceptibility analysis and its mapping using different bivariate models in Iran: a comparison between Shannon’s entropy, statistical index, and weighting factor models. Environmental Monitoring and Assessment. 188(12): 658–692. Khosroshahi M, Saghfian B. 2003. Investigating the role of watershed sub-basin participation in basin flood intensity. Journal of Research and Construction. 59(2): 67–75. (In Persian). Li N. 2002. The flood risk management system based on GIS. PhD Paper. Beijing: China Institute of Water Resource and Hydropower Research. 156 p. Lu L, Shi Zh, Yin W, Zhu D, Sai N, Leung C, Chong F, Leia L. 2009. A fuzzy analytic hierarchy process (FAHP) approach to eco-environmental vulnerability assessment for the Danjiangkou Reservoir Area. China Ecological Modeling. 220(23): 3439–3447. Moghadasi N, Karimirad I. Vahedberdi Sh. 2017. Assessing the impact of land use changes and rangeland and forest degradation on flooding using watershed modeling system. Journal of Rangeland Science, 7(2): 93–106. Nouri H, Shahedi K, Habibnezhad R, Kavian A, Faramarzi M. 2019. Susceptibility to flooding in the Razavar Watershed using analytical hierarchy process method, Journal of Natural Environmental Hazards. 8(19):35–50. (In Persian). Oh HJ, Pradhan B. 2011. Application of a neuro-fuzzy model to landslide- susceptibility mapping for shallow landslides in a hilly area, Computers & Geosciences. 37(9): 1264–1276. Pradhan B. 2009. Flood susceptible mapping and risk area delineation using logistic regression, GIS and remote sensing. Journal of Spatial Hydrology. 9: 1–18 Rasulzadeh A, Azartaj E, Farzi P. 2016. Derivation and investigation of regional flood analysis models as a function of return period (Case study: Ardabil Province). Journal of Water and Soil Conservation. 22(4):261–268. (In Persian). Razavi Termeh V, Malek MR. 2017. Flood susceptibility mapping using ensemble of evidential belief (EBF) function with analytical hierarchy process (AHP) (Case study: Jahrom Township). Geospatial Engineering Journal. 8 (3) :1–15. Samanta R, Bhunia G, Shit P, Pourghasemi HR. 2018. Flood susceptibility mapping using geospatial frequency ratio technique: a case study of Subarnarekha River Basin, India. Modeling Earth Systems and Environment. 4(1): 395–408. Shannon CE. 1948. A mathematical theory of communication, Bell Telephone System Technical Publications. Tehrany MS, Pradhan B, Jebur MN. 2014. Flood susceptibility mapping using a novel ensemble weights-of-evidence and support vector machine models in GIS. Journal of Hydrology. 512(2):332–343. Tehrany MS, Pradhan B, Jebur MN. 2015. Flood susceptibility analysis and its verification using a novel ensemble support vector machine and frequency ratio method. Stochastic Environmental Research and Risk Assessment. 29(4): 1149–1165. | ||
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