ارزیابی مخاطرۀ سیل با کاربرد GIS و RS در جنوب استان کرمان (مطالعۀ موردی: حوضۀ آبریز هامون- جازموریان)

نوع مقاله : پژوهشی

نویسندگان

1 کارشناس ارشد سنجش از دور زمین‌شناختی، گروه اکولوژی، پژوهشگاه علوم و تکنولوژی پیشرفته و علوم محیطی، دانشگاه تحصیلات تکمیلی صنعتی و فناوری پیشرفته، کرمان

2 استادیار گروه اکولوژی، پژوهشگاه علوم و تکنولوژی پیشرفته و علوم محیطی، دانشگاه تحصیلات تکمیلی صنعتی و فناوری پیشرفته، کرمان

3 دانشیار گروه اکولوژی، پژوهشگاه علوم و تکنولوژی پیشرفته و علوم محیطی، دانشگاه تحصیلات تکمیلی صنعتی و فناوری پیشرفته، کرمان

10.22059/ije.2023.354747.1712

چکیده

تهیۀ نقشۀ خطر سیل‏، نخستین گام در برنامه‌های مدیریت سیلاب است. در پژوهش حاضر به منظور ارزیابی مخاطرۀ سیلاب در حوضۀ آبریز هامون- جازموریان از 13 لایه تأثیرگذار در بحران سیل شامل ارتفاع، شیب، جهت شیب، انحنای توپوگرافی، تراکم زهکشی، فاصله از آبراهه، زمین‏شناسی، پوشش گیاهی، کاربری اراضی، بارندگی، شاخص رطوبت توپوگرافی، شاخص قدرت جریان و نوع خاک استفاده شد. برای اولویت‏بندی و تعیین وزن‏ها، روش فرایند تحلیل سلسله‌مراتبی (AHP) به صورت ماتریس مقایسات زوجی به کار گرفته شد. سپس هر لایه توسط مدل منطق فازی، بین 0 تا 1 فازی‏سازی شده و وزن‏های به‌دست‌آمده از روش AHP در آن‏ها ضرب شدند. در نهایت بر اساس روش ترکیب خطی‌ـ وزنی با تلفیق 13 لایۀ اطلاعاتی، نقشۀ پهنه‏بندی سیل‏گیری به ‏دست آمد. برای اعتبارسنجی نتایج و به عنوان یک واقعیت زمینی، روی هر یک از تصاویر ماهواره‏ای قبل و بعد از سیل به ‏طور جداگانه شاخص آب AWEI اعمال شده و با استفاده از روش تکنیک تعیین تغییرات، مناطق تحت تأثیر سیل مشخص شدند. این مناطق شامل اطراف پهنۀ هامون‌ـ جازموریان و مناطق نزدیک به آبراهه‏های اصلی هستند. نتایج حاصل از صحت‏سنجی نقشۀ مناطق سیل‌گیر نشان داد روش صحت‌سنجی گاما در سال‌های 1371 و 1395 به‌ترتیب با 96/97 ‌و 18/98 درصد بیشترین مطابقت را با نتایج تصاویر ماهواره‏ای دارد.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Assessment of flood risk using GIS and RS in the south of Kerman province (case study: Hamoon- Jazmoorian catchment)

نویسندگان [English]

  • Seyed Mohammad Hosseini 1
  • Sedigheh Mohamadi 2
  • Reza Hassanzadeh 2
  • Mehdi Honarmand 3
1 MSc, Department of Ecology, Institute of Science and High Technology and Environmental Sciences, Graduate University of Advanced Technology, Kerman, Iran
2 Assistant Professor, Department of Ecology, Institute of Science and High Technology and Environmental Sciences, Graduate University of Advanced Technology, Kerman, Iran
3 Associate Professor, Department of Ecology, Institute of Science and High Technology and Environmental Sciences, Graduate University of Advanced Technology, Kerman, Iran
چکیده [English]

This research set out to assess the flood risk in the Hamoon-Jazmoorian catchment applying 13 affecting factors as informative layers including elevation, slope, slope direction, topographic curvature, drainage density, distance from the waterway, geology, vegetation, land use, rainfall, topographic moisture index, flow strength index and soil type. To this end, the Analytical Hierarchy Process (AHP) method was applied in the form of a matrix of paired comparisons for prioritizeing and determineing the weight. Then each layer was made fuzzy between 0 and 1 by fuzzy logic model and the weights obtained by AHP method were multiplied in them. Next, based on the method of linear-weighted combination with the integration of 13 layers of information, a flood zoning map was obtained. Finally, the AWEI index was applied to each satellite image before and after the flood separately to validate the results as a ground reality, in which the areas affected by the flood situating around Hamoon-Jazmoorian and areas close to the main waterways were determined using the technique of changes determination. The results of the validation of the map of the flooded areas revealed that the gamma validation method in 1992 and 2016 has the highest consistent with the results of satellite images with 97.96 % and 98.18 % of similarity, respectively.

کلیدواژه‌ها [English]

  • flood risk map
  • Landsat satellite images
  • AWEI
  • AHP
  • fuzzy logic model
  • Kazemi A, Rezaei Moghaddam MH, Nikjoo MR, Hejazi MA, Khezri S. Zoning and Management of the hazards of Floodwater in the Siminehrood River Using the HEC–RAS Hydraulic Model. Environmental Management Hazards. 2016 Dec 21;3(4):379-93. [Persian]
  • Matkan A, Shakiba A, Pourali H, Azari H. Flood early warning with integration of hydrologic and hydraulic models, RS and GIS (Case Study: Madarsoo Basin, Iran). World Applied Sciences Journal. 2009;6(12):1698-704. [Persian]
  • Asare-Kyei D, Forkuor G, Venus V. Modeling flood hazard zones at the sub-district level with the rational model integrated with GIS and remote sensing approaches. Water. 2015; 7(7): 3531-64.

 

  • Kwang C, Osei EM. Accra flood modelling through application of geographic information systems (gis). Remote Sensing Techniques and Analytical Hierarchy Process. J Remote Sensing & GIS. 2017; 6(191): 2.
  • Youssef AM, Hegab MA. Flood-hazard assessment modeling using multicriteria analysis and GIS: a case study—Ras Gharib area, Egypt. InSpatial modeling in GIS and R for earth and environmental sciences. 2019; (229-257 pp.)
  • Cai T, Li X, Ding X, Wang J, Zhan J. Flood risk assessment based on hydrodynamic model and fuzzy comprehensive evaluation with GIS technique. International Journal of Disaster Risk Reduction. 2019; 35:101077.
  • Ogato GS, Bantider A, Abebe K, Geneletti D. Geographic information system (GIS)-Based multicriteria analysis of flooding hazard and risk in Ambo Town and its watershed, West shoa zone, oromia regional State, Ethiopia. Journal of Hydrology: Regional Studies. 2020; 27:100659.
  • Saghafi M, REZAEI MM. Evaluation of geomorphology method application for flood hazards risk classification using fuzzy logic (case study: Ojan Chay drainage basin). [Persian]
  • Ghanavati A, Babaei Aghdam F, Hemmati T, Rahimi M. Flood Potential Zoning Using Fuzzy Logic Model in GIS Environment (Case Study of Khayavchi Meshkinshshahr River Basin). Hydrogeomorphology Journal. 2015; 3:121-35. [Persian]
  • Darabi H, Shahedi K, Mardian M. Mapping possibility hazard and sensivity flood using frequency ratio in the watershed poul doab shazand. Journal of Watershed Engineering and Management. 2016;8(1): 68-79. [Persian]
  • Mousavi S, Roostaei S, Rostamzadeh H. Regional Flood Hazard assessment at the Sub-basin Scale Using Remote Sensing & Fuzzy logic. Iranian journal of Ecohydrology. 2018; 5(3): 829-41. [Persian]
  • Omidvar K, Mahmodabadi M, Safarpour F. A synoptic analysis of heavy rains February 2011 in southern and central regions of Iran (with emphasis on Kerman Province). Geography and Planning. 2015;19(51): 21-39. [Persian]
  • Choobak H., Kiyani MY. Geographical-cultural domain of Jazmorian in the archeological investigations of Iran.Sciences MODARES Human. 2005; 8(4): 31-67.
  • Mostofi A, Climatic atlas of Iran, Tehran university Press. 117 pp.
  • Ahmadi H., Esmaeilpour Y., Moradi A., Gholami H. Assessment of land Sensitivity to Desertification Hazard Using System Dynamics Approach in the Jazmourian basin. Journal of Water and Soil Conservation. 2019; 26(2), 211-224.
  • Pradhan B. Flood susceptible mapping and risk area delineation using logistic regression, GIS and remote sensing. Journal of Spatial Hydrology. 2010; 27: 9(2).
  • Botzen WJ, Aerts JC, Van den Bergh JC. Individual preferences for reducing flood risk to near zero through elevation. Mitigation and Adaptation Strategies for Global Change. 2013; 18:229-44.
  • Fernández DS, Lutz MA. Urban flood hazard zoning in Tucumán Province, Argentina, using GIS and multicriteria decision analysis. Engineering Geology. 2010;111(1-4):90-8.
  • Tehrany MS, Pradhan B, Jebur MN. Spatial prediction of flood susceptible areas using rule based decision tree (DT) and a novel ensemble bivariate and multivariate statistical models in GIS. Journal of hydrology. 2013; 504:69-79.
  • Das S, Pardeshi SD. Integration of different influencing factors in GIS to delineate groundwater potential areas using IF and FR techniques: a study of Pravara basin, Maharashtra, India. Applied Water Science. 2018;8:1-6.
  • Lee MJ, Kang JE, Jeon S. Application of frequency ratio model and validation for predictive flooded area susceptibility mapping using GIS. In2012 IEEE international geoscience and remote sensing symposium. 2012; 895-898 pp.
  • Donati L, Turrini MC. An objective method to rank the importance of the factors predisposing to landslides with the GIS methodology: application to an area of the Apennines (Valnerina; Perugia, Italy). Engineering Geology. 2002; 63(3-4):277-89.
  • Abubakar T, Azra EA, Mohammed C. Selecting suitable drainage pattern to minimize flooding in sangere village using GIS and remote Sensing. Global Journal of Geological Sciences. 2012; 10(2):129-40.
  • Cao C, Xu P, Wang Y, Chen J, Zheng L, Niu C. Flash flood hazard susceptibility mapping using frequency ratio and statistical index methods in coalmine subsidence areas. Sustainability. 2016; 8(9):948.
  • Horritt MS. Calibration of a two‐dimensional finite element flood flow model using satellite radar imagery. Water Resources Research. 2000; 36(11):3279-91.
  • Predick KI, Turner MG. Landscape configuration and flood frequency influence invasive shrubs in floodplain forests of the Wisconsin River (USA). Journal of Ecology. 2008; 96(1):91-102.
  • Mahmoud SH, Gan TY. Multi-criteria approach to develop flood susceptibility maps in arid regions of Middle East. Journal of Cleaner Production. 2018; 196: 216-29.
  • Samanta S, Koloa C, Kumar Pal D, Palsamanta B. Flood risk analysis in lower part of Markham river based on multi-criteria decision approach (MCDA). Hydrology. 2016; 3(3):29.
  • Brody SD, Zahran S, Maghelal P, Grover H, Highfield WE. The rising costs of floods: Examining the impact of planning and development decisions on property damage in Florida. Journal of the American Planning Association. 2007; 73(3):330-45.
  • Dinesh Kumar PK, Gopinath G, Seralathan P. Application of remote sensing and GIS for the demarcation of groundwater potential zones of a river basin in Kerala, southwest coast of India. International Journal of Remote Sensing. 2007; 28(24):5583-601.
  • Reneau SL. Stream incision and terrace development in Frijoles Canyon, Bandelier National Monument, New Mexico, and the influence of lithology and climate. Geomorphology. 2000; 32(1-2):171-93.
  • 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.
  • Firouzi F, Tavosi T, Mahmoudi P. Investigating the sensitivity of NDVI and EVI vegetation indices to dry and wet years in arid and semi-arid regions (Case study: Sistan plain, Iran). Scientific-Research Quarterly of Geographical Data (SEPEHR). 2019; (110):163-79. [Persian]
  • Benito G, Rico M, Sánchez-Moya Y, Sopeña A, Thorndycraft VR, Barriendos M. The impact of late Holocene climatic variability and land use change on the flood hydrology of the Guadalentín River, southeast Spain. Global and Planetary Change. 2010; 70(1-4):53-63.
  • Beckers A, Dewals B, Erpicum S, Dujardin S, Detrembleur S, Teller J, Pirotton M, Archambeau P. Contribution of land use changes to future flood damage along the river Meuse in the Walloon region. Natural Hazards and Earth System Sciences. 2013; 13(9):2301-18.
  • Soulsby C, Tetzlaff D, Hrachowitz M. Spatial distribution of transit times in montane catchments: conceptualization tools for management. Hydrological Processes. 2010; 24(22):3283-8.
  • Moore ID, Grayson RB, Ladson AR. Digital terrain modelling: a review of hydrological, geomorphological, and biological applications. Hydrological processes. 1991; 5(1):3-0.
  • Knighton AD. Downstream variation in stream power. Geomorphology. 1999; 29(3-4):293-306.
  • Kay AL, Jones RG, Reynard NS. RCM rainfall for UK flood frequency estimation. II. Climate change results. Journal of hydrology. 2006 Mar 1;318(1-4):163-72.
  • Segond ML, Wheater HS, Onof C. The significance of spatial rainfall representation for flood runoff estimation: A numerical evaluation based on the Lee catchment, UK. Journal of Hydrology. 2007 Dec 15;347(1-2):116-31.
  • Geris J, Tetzlaff D, McDonnell J, Soulsby C. The relative role of soil type and tree cover on water storage and transmission in northern headwater catchments. Hydrological Processes. 2015; 29(7):1844-60.
  • Pizzuto JE. Downstream fining in a network of gravel‐bedded rivers. Water Resources Research. 1995; 31(3):753-9.
  • Chaudhary P, Chhetri SK, Joshi KM, Shrestha BM, Kayastha P. Application of an Analytic Hierarchy Process (AHP) in the GIS interface for suitable fire site selection: A case study from Kathmandu Metropolitan City, Nepal. Socio-economic planning sciences. 2016; 53 (1):60-71.
  • Feyisa GL, Meilby H, Fensholt R, Proud SR. Automated Water Extraction Index: A new technique for surface water mapping using Landsat imagery. Remote sensing of environment. 2014; 1;140:23-35.
  • Jawak SD, Kulkarni K, Luis AJ. A review on extraction of lakes from remotely sensed optical satellite data with a special focus on cryospheric lakes. Advances in Remote Sensing. 2015;4(03):196.
  • Yahaya S, Ahmad N, Abdalla RF. Multicriteria analysis for flood vulnerable areas in Hadejia-Jama’are River basin, Nigeria. European Journal of Scientific Research. 2010;42(1):71-83.
  • Ghavidel Y., Ahmadi M., Hatami Zarneh D., Rezaei M. Identification of synoptic patterns of heavy rainfall manufacturers destructive floods in Jiroft city. Geography (Sheffield, England). 2014; 41(12): 161-178.
  • Soleimani Sardoo F., Rafiei Sardooi E., Mesbahzadeh T., Azareh A. Utilizing Sentinel 1 Images for Monitoring Damage of Flood Event in March 2020, the South of Kerman Province Based on Random Forest Algorithm, Iran-Watershed Management Science & Engineering. 2021; 15(53): 23-32 [Persian]
  • Ghazizadeh E., Ganji Z., Azhdari K., Determining the vulnerability of flood areas using HEC-RAS and GIS model (case study: agricultural lands of Halil Road river, Jiroft city), 2 nd Iranian National Congress of Irrigation and Drainage. 2016. Isfahan University of Technology