مجله آب و فاضلاب

مجله آب و فاضلاب

پهنه‌بندی سیل‌خیزی شهرستان کاشان بر اساس تحلیل سلسله مراتبی با استفاده از سیستم اطلاعات جغرافیایی

نوع مقاله : مقاله پژوهشی

نویسندگان
مهرداد خشوعی 1
احسان استکی 2
سامان امینی 2
1 استاد‌یار، گروه مهندسی عمران، دانشکده مهندسی، دانشگاه ‌کاشان، کاشان، ایران
2 دانشجوی کارشناسی ارشد مهندسی عمران، مهندسی و مدیریت منابع آب، دانشگاه کاشان، کاشان، ایران
10.22093/wwj.2025.521261.3491
چکیده
سیل یکی از مهم‌ترین بلایای طبیعی است که تأثیرات گسترده‌ای بر مناطق مختلف ایران، به‌ویژه شهرستان کاشان، دارد. این پدیده سالانه خسارات مالی قابل‌توجهی به زیرساخت‌های منطقه وارد کرده و منجر به آسیب‌های جانی نیز می‌شود. با توجه به اهمیت این موضوع، شناسایی و ارزیابی مناطق سیل‌خیز می‌تواند نقش مؤثری در کاهش خسارات و پیشگیری از اثرات مخرب سیلاب ایفا کند. بر این‌ اساس، این پژوهش به پهنه‌بندی سیل‌خیزی شهرستان کاشان در مرکز ایران پرداخت. در این پژوهش، از سیستم اطلاعات جغرافیایی به‌عنوان ابزاری کارآمد استفاده شد. در گام نخست، نقشه‌های رستری مرتبط با شاخص‌های مهم و تأثیرگذار بر سیل‌خیزی منطقه تهیه شد. این شاخص‌ها شامل متغیرهای محیطی و جغرافیایی مؤثر بر وقوع سیل هستند. سپس، این نقشه‌ها با استفاده از روش تحلیل سلسله مراتبی به‌عنوان یکی از روش‌های وزن‌دهی مناسب تحلیل شد و وزن‌های هر معیار و طبقه‌های مرتبط با آن‌ها مشخص شد. درنهایت، نقشه نهایی پهنه‌های سیل‌خیز با بهره‌گیری از ابزار محاسبه‌گر رستر در محیط GIS تولید شد. یافته‌ها نشان داد که حدود 30 درصد از مساحت شهرستان در پهنه با بیشترین خطر وقوع سیلاب قرار دارد؛ این بخش عمدتاً شامل نواحی شرقی با تراکم بالای جمعیت و توسعه شهری است. در مقابل، حدود ۶۰ درصد از مساحت شهرستان در پهنه با کمترین خطر وقوع سیلاب جای می‌گیرد که بیشتر در مناطق غربی با شیب ملایم و تراکم بالای پوشش گیاهی واقع شده است. نوآوری این پژوهش ترکیب هم‌زمان 12 شاخص محیطی و هیدرولوژیکی در چارچوب AHP-GIS و تمرکز بر شرایط اقلیم خشک کاشان بود. یافته‌های این پژوهش می‌تواند مبنای مناسبی برای برنامه‌ریزی مدیریت بحران و اجرای اقدامات پیشگیرانه در سطح شهرستان کاشان باشد.
کلیدواژه‌ها
پهنه‌بندی
سیل‌خیزی
سیستم اطلاعات جغرافیایی
مدل رقومی ارتفاع
تحلیل سلسله مراتبی

موضوعات

عنوان مقاله English

Flood Hazard Zoning of Kashan County Based on Analytical Hierarchy Process Using Geographic Information System

نویسندگان English

Mehrdad Khoshoei 1
Ehsan Esteki 2
Saman Amini 2
1 Assist. Prof. of Water Resources Management and Engineering, Faculty of Civil Engineering, University of Kashan, Kashan, Iran
2 MSc. Student in Civil Engineering, Water Resources Engineering and Management, Dept. of Civil Engineering, Faculty of Engineering, University of Kashan, Kashan, Iran
چکیده English

Flooding is one of the most significant natural disasters that has extensive impacts on various regions of Iran, particularly in Kashan County. Each year, this phenomenon causes considerable financial damage to local infrastructure and often results in human casualties. Given the importance of this issue, identifying and assessing flood-prone areas can play a crucial role in minimizing losses and preventing the destructive effects of floods. Accordingly, the present study focuses on flood susceptibility zoning in Kashan County, located in central Iran. In this research, Geographic Information System was employed as an effective analytical tool. In the first stage, raster maps related to key indicators influencing flood susceptibility were prepared. These indicators included environmental and geographical variables affecting flood occurrence. Subsequently, the maps were analyzed using the Analytical Hierarchy Process, one of the most widely used multi-criteria decision-making methods for weighting. The weights of each criterion and their respective classes were determined through this process. Finally, the flood susceptibility map was generated using the raster calculator tool within the GIS environment. The results indicate that approximately 30% of the county’s area falls within zones of high flood risk, primarily covering the eastern regions characterized by high population density and urban development. In contrast, about 60% of the area lies within low-risk zones, mostly located in the western parts of the county with gentle slopes and dense vegetation cover. The novelty of this study lies in the simultaneous integration of twelve environmental and hydrological indicators within the AHP-GIS framework, with a specific focus on the arid climatic conditions of Kashan. The findings of this research can serve as a valuable basis for disaster management planning and the implementation of preventive measures across Kashan County.

کلیدواژه‌ها English

Zoning
Flooding
Geographic Information System
Digital Height Model
Hierarchical Analysis
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), 2087-2116. https://doi.org/10.1080/19475705.2021.1955755.
Asgari, Sh., Safari, A. and Fathi, H., 2018. Investigation of flooding in Jafarabad catchment using factor analysis. Journal of Applied Research in Geographical Sciences, 18(50), 77-90. (In Persian). https://doi.org/10.29252/jgs.18.50.77.
Betrie, G. D., Mohamed, Y. A., Van Griensven, A. and Srinivasan, R., 2011. Sediment management modeling in the Blue Nile Basin using SWAT model. Hydrology and Earth System Sciences, 15(3), 807–818. https://doi.org/10.5194/hess-15-807-2011.
Braud, I., Fernandez, P. and Bouraoui F., 1998. Study of the rainfall-runoff process in the Andes region using a continuous distributed model. Journal of Hydrology, 216, 155-171. https://doi.org/10.1016/S0022-1694(98)00292-3.
Dang, N. M., Babel, M. S. and Luong, H. T., 2011. Evaluation of flood risk parameters in the Day River flood diversion area, Red River delta, Vietnam. Natural Hazards, 56, 169-194. https://doi.org/10.1007/s11069-010-9558-x.
Gao, H., Cai, H. and Duan, Z., 2018. Understanding the impacts of catchment characteristics on the shape of the storage capacity curve and its influence on flood flows. Hydrology Research, 49(1), 90-106. https://doi.org/10.2166/nh.2017.245.
Garrote, L. and Bras, R. L., 1994. A distributed model for real-time flood forecasting using digital elevation model. Journal of Hydrology, 167, 279-306. https://doi.org/10.1016/0022-1694(94)02592-Y.
Giannakis, E., Bruggeman, A., Djuma, H., Kozyra, J. and Hamme, J., 2016. Water pricing and irrigation across Europe: opportunities and constraints for adopting irrigation scheduling decision support systems. Water Science and Technology: Water Supply, 16(1), 245-252. https://doi.org/10.2166/ws.2015.136.
Goodarzi, M. R., Fatehifar, A. and Moradi, A., 2020. Predicting future flood frequency under climate change using Copula function. Water and Environment Journal, 34, 710-727. https://doi.org/10.1111/wej.12572.
Inci Tekeli, Y., Akgul, S., Dengiz, O. and Akuzum, T., 2005. Estimation of flood discharge for small watershed using SCS Curve Number and GIS. International Congress on River Basin Management, 527-537. [Link]
Islamy, A. and Molaei, A., 2005. Assessment of HEC-RAS model application in floodplain mapping: case study of Narmashir River in Bam. 2nd National Conference on Watershed Management and Water Resources, Kerman, Iran. (In Persian). [Link]
Karimi, P., Safaval, P. A., Azizi-Zarkash, M. M. K. and Kalashami, H. K., 2023. Flood risk zoning using GIS: case study of the Khorramabad flood in April 2019. Acta Hydrotechnica, 35(63), 89-100. https://doi.org/10.15292/acta.hydro.2022.07.
Khademi, F. and Akbari, M., 2014. Methods of flood control. National Conference on Flood Management and Engineering with Urban Flood Approach. (In Persian). [Link]
Khoshoei, M., Safavi, H. R. and Zamani, A. R., 2016. Design of drought monitoring system based on integrated index in Zayanderood River Basin-Iran. Journal of Water and Soil Science, 20, 27-43. (In Persian). https://doi.org/10.18869/acadpub.jstnar.20.75.27.
Khoshoei, M. and Safavi, H. R., 2023. Developing the drought index in natural and engineering sub-basins (case study: Zayandehrood Basin). Iran-Water Resources Research, 19(4), 48-61. (In Persian). https://doi.org/10.22034/IWRR.2023.173579.
Khoshoei, M., Safavi, H. R. and Kazemi, A., 2023. Integrated index for drought assessment in Isfahan Province. Journal of Water and Soil Science, 27(1), 113-136. (In Persian). https://doi.org/10.47176/jwss.27.1.28582.
Khoshoei, M., 2025. Estimation of water stress multivariable index (case study: Kashan City). Journal of Water and Soil Science, 29(2), 33-55. (In Persian). https://doi.org/10.47176/jwss.29.2.28583.
Khosravi, Kh., Nohani, E., Maroufinia, E. and Pourghasemi, H. R., 2016. A GIS-based flood susceptibility assessment and its mapping in Iran: a comparison between frequency ratio and weights-of-evidence bivariate statistical models with multi-criteria decision-making technique. Natural Hazards, 83, 947-987. https://doi.org/10.1007/s11069-016-2357-2.
Kundzewicz, Z. W., Kanae, S., Seneviratne, S. I., Handmer, J., Nicholls, N., Peduzzi, P. et al., 2014. Flood risk and climate change: global and regional perspectives. Hydrological Sciences Journal, 59(1), 1-28. https://doi.org/10.1080/02626667.2013.857411.
Lastra, J., Fernandez, E., Diez-Herrero, A. and Marquinez, J., 2008. Flood hazard delineation combining geomorphological and hydrological methods: an example in the Northern Iberian Peninsula. Natural Hazards, 45, 277-293. https://doi.org/10.1007/s11069-007-9164-8.
Levy, J. K., 2005. Multiple criteria decision making and decision support systems for flood risk management. Stochastic Environmental Research and Risk Assessment, 19, 438-447. https://doi.org/10.1007/s00477-005-0009-2.
Lumbroso, D. and Gaume, E., 2012. Reducing the uncertainty in indirect estimates of extreme flash flood discharges. Journal of Hydrology, 414-415, 16-30. https://doi.org/10.1016/j.jhydrol.2011.08.048
Malczewski, J., 1999. GIS and Multicriteria Decision Analysis. John Wiley and Sons. ISBN: 978-0-471-32944-2. [Link]
Masoudian, M. and Fenderski, N., 2014. Reducing urban flood damage using non-structural management. Watershed Management Research Journal, 5(10), 1-14. (In Persian). [Link]
Merz, B. and Bardossy, A., 1996. Effects of spatial variability on the rainfall runoff process in a small loess catchment. Journal of Hydrology, 212-213, 304-317. https://doi.org/10.1016/s0022-1694(98)00213-3.
Merz, B., Thieken, A. H., and Gocht, M., 2007. Flood Risk Mapping At the Local Scale: Concepts and Challenges. In Begum S., Stive, M. J. F. and Hall, J. W. ed. Flood Risk Management in Europe. pp. 231-251. Springer. [Link]
Morgan, R. P. C., 2009. Soil Erosion and Conservation. 3rd Edition. Blackwell Publishing, London: Longman. [Link]
Moayeri, M. and Entezari, M., 2008. Floods and an overview of floods in Isfahan Province. Journal of Human Settlements Planning Studies (Geographical Perspective), 3(6), 109-123. (In Persian). [Link]
NOAA National Severe Storms Laboratory. Severe weather 101: Flood types. National Oceanic and Atmospheric Administration. [Link]
Pathan, A. I. and Agnihotri, P. G., 2021. Application of new HEC-RAS version 5 for 1D hydrodynamic flood modeling through geospatial techniques: case of River Purna at Navsari, Gujarat, India. Modeling Earth Systems and Environment, 7(2), 1133-1144. https://doi.org/10.1007/s40808-020-00961-0.
Qaemi, H., Morid, S. and Abolghasem, Sh., 1996. Flood-susceptibility model of the Karkheh sub-basins. Niwar, (30), 10–27. (In Persian). [Link]
Rajabizadeh, Y., Ayyoubzadeh, S. A. and Zahiri, A., 2019. Flood survey of Golestan province in 2018-2019 and providing solutions for its control and management in the future. Journal of Eco Hydrology, 6(4), 921-942. (In Persian). https://doi.org/10.22059/IJE.2019.283004.1137.
Saaty, T. L., Vargas, L. and St, C., 2022. The Analytic Hierarchy Process. McGraw-Hill. ISBN: 978-1-4614-3597-6. [Link]
Saaty, T. L. and Vargas, L. G., 2012. Models, Methods, Concepts and Applications of the Analytic Hierarchy Process. Springer Science and Business Media. New York, NY. https://doi.org/10.1007/978-1-4614-3597-6.
Saghafian, B., Ghermezcheshmeh, B. and Nozari, H., 2005. Spatial distribution of flood intensity in hydrological units: a case study of the Dez River Basin. 5th Iranian Hydraulic Conference, Kerman, Iran. (In Persian). [Link]
Schueler, T. R., 1987. Controlling Urban Runoff: A Practical Manual for Planning and Designing Urban Best Management Practices. Metropolitan Washington Council of Governments, Washington, DC. 272. [Link]
Shaabani Bazneshin, A., Emadi, A. and Fazloula, R., 2016. Investigation of the flooding potential of basins and identification of flood-producing areas: case study of Neka Basin. Journal of Watershed Management Research, 7(14), 20-28. (In Persian). https://doi.org/10.29252/jwmr.7.14.28.
Shahabi, H., 2021. Application of artificial neural networks, frequency ratio, and evidential belief function models in flood susceptibility mapping in Haraz watershed. Urban Research and Planning Journal, 181-202. (In Persian). https://doi.org/20.1001.1.22285229.1400.12.45.9.3.
Shokrikochak, S., 2011. The role of sub-basins in flood severity in the Eydenk sub-watershed of the Maroon basin. MSc. Thesis in Water Resources Engineering, Shahid Chamran University of Ahvaz, Iran. (In Persian).
United Nations Office for Disaster Risk Reduction (UNDRR). Flash flood (MH0603). UNDRR Hazard Information Profiles. [Link]
United Nations Office for Disaster Risk Reduction (UNDRR). Snowmelt flood (MH0610). UNDRR Hazard Information Profiles. [Link]
Yamani, M. and Enayati, M., 2006. Analysis of flood data in relation to the geomorphologic characteristics of the Fashsand and Behjatabad basins. Geography Research, 47-57. (In Persian). [Link]
مجله آب و فاضلاب
دوره 36، شماره 2 - شماره پیاپی 157
خرداد و تیر 1404
صفحه 43-62