ارزیابی و پهنه‌بندی خطر زمین ‌لغزش با استفاده از الگوریتم تطبیقی mabac و anp (مطالعه‌ی موردی: شهرستان نیر)

زمین لغزش ها، از پرحادثه ترین مخاطرات طبیعی دنیا می باشد و شناخت و پهنه بندی زمین لغزش می تواند در مدیریت، کنترل، مهار و کاهش میزان خسارات آن، موثر باشد. شهرستان نیر با توجه به وضعیت زمین شناسی، فیزیوگرافی، اقلیمی و انسانی، عمده شرایط لازم را جهت رخداد حرکاتلغزشی داراست و لذا هدف تحقیق حاضر، پهنه بندی خطر زمین لغزش در این شهرستان می باشد. در این مطالعه ابتدا، عوامل موثر جهت ایجاد لغزش در شهرستان نیر (شیب، طبقات ارتفاعی،کاربری اراضی، فاصله از راه ارتباطی، خاک، لیتولوژی، فاصله از گسل، فاصله از آبراهه وبارش) شناسایی شدند و سپس نسبت به تهیه ی لایه های اطلاعاتی در سامانه اطلاعات جغرافیایی اقدام گردید. در مرحله بعد وزن دهی عوامل مورد بررسی، با استفاده از روش anp و در محیط نرم افزار super decision انجام گردید و تحلیل و مدل سازی نهایی با استفاده از روش mabac به عنوان یکی از روش های تصمیم گیری چند معیاره، انجام شد. در نهایت، نقشه ی حاصله در پنج رده ی با خطر بسیار کم تا خطر بسیار زیاد طبقه بندی گردید. با توجه به نتایج مطالعه، عوامل کاربری اراضی، لیتولوژی، شیب و طبقات ارتفاعی بیشترین ضریب وزنی را به خود اختصاص دادند. همچنین، نتایج مطالعه نشان داد؛ به ترتیب 171/93 و 312/38 کیلومترمربع از مساحت شهرستان، در طبقات بسیار پرخطر و پرخطر، قرار دارند و مناطق بسیار پرخطر و پرخطر در سازندهایی با زیربنای سنگ سخت به همراه مواد رسوبی و سست سطحی، کاربریهای زراعی و مرتع، شیب های 35-20 درصد و ارتفاعات بیش از 1500 متر قرار دارند. به علاوه، با توجه به اعتبارسنجی نتایج مطالعه، می توان اذعان داشت که استفاده تلفیقی از روش های anp و mabac ، با سطح زیر منحنی 0/842 ، از دقت نسبی بالایی جهت مطالعه ی زمین لغزش برخوردار است. در نهایت می توان اظهار داشت، نظر به توان بالای شهرستان نیر، از لحاظ رخداد حرکات لغزشی، بایستی اقدامات حفاظتی، مدیریتی و آبخیزداری در سطح شهرستان مورد توجه مسئولان و دستگاه های ذی ربط قرار گیرد.

Landslide hazard assessment and zoning using MABAC and ANP adaptive algorithm (Case study: Nir city)

Extended abstractIntroductionLandslides are catastrophic and widespread, causing significant damage in many parts of the world (Hawk et al., 676: 2019; Rossi et al., 3: 2019). Massive landslides cause natural and external active factors, including natural geological factors (lithology or soil type, structural cohesion, shear strength of materials, groundwater conditions and its effect), slope geometry ( Slope, direction, height and curvature) and land or ground cover as well as external factors that generally cause landslides include rainfall, seismicity and human activities such as construction activities and soil preparation for agriculture in mountainous areas (Surbi And Farrokhnia, 36: 2018). Nir County, in terms of the special situation of the region, such as topography (having a mountainous face), steep slope, the presence of loose and unstable surface materials on resistant formations and climatic conditions (especially due to spring rains and snowmelt in spring) from It has a high potential for landslides and the most accidentprone area in the province is landslides.MethodologyIn this study, first the factors affecting landslides (including: slope, elevation, lithology, land use, soil, precipitation, distance through communication, distance from waterway and distance from fault), according to the natural and human conditions of the region. Was identified. In the next step, information layers related to each of the factors were prepared in the geographic information system environment. The information layers of Mizan curved lines, communication channels and waterway network were obtained by digitization from the topographic map of the city with a scale of 1: 50,000 and the slope and slope layers were prepared using a digital height model. The objectoriented classification and algorithm algorithm were then classified in the Ecognition software, and the results of the classification of users in the present study, both in terms of singleuse and in terms of total accuracy and statistics, are acceptable (greater than 85%), is related to the information produced. In order to prepare the soil map, the soil map of Ardabil province with a scale of 1: 50,000 has been used. The city rainfall map was prepared using meteorological and rain gauge station data and by obtaining the equation of Gradian precipitation P = 0.224 H83.54) and also the use of altitude digital model.Results In order to further document the validity of landslide potential zoning maps using ANP and MABAC methods, an attempt has been made in this section. According to the established criteria. Definitely adapting these standardized scores to the actual values recorded from the criteria obtained according to the digital maps will give a more tangible understanding of the result of the significant contribution. According to the table for the study of highrisk pixels, highrisk areas are mainly on the slope of 20 to 35 percent, and in this amount of slope, surface and generally fine materials that are prone to slip by absorbing water and increasing moisture to They reach a flooding level and begin to move as the shear stresses and material ruptures in the range increase. The study of land use criteria also indicates that agricultural and rangeland use has the highest percentage of risky areas, which due to noncompliance with crop rotation, cultivation on sloping lands and increasing soil moisture through irrigation and infiltration. Giving more water to the ground is acceptable. In addition, local people, by overgrazing their livestock in pastures, are destroying vegetation and accelerating the landslide process after torrential rains. Also, the highrisk lands introduced by the research method show that the highrisk lands are relatively close to the road, river and fault. In this regard, it can be said that the road factor has a very important role in creating slippery movements due to the overlap and removal of the heel of the slope and the change in the slope of the slopes. Because most road construction activities in the city (especially in rural and nomadic areas) are unprincipled and without regard to engineering principles, the construction of roads on the one hand due to the creation of trenches and weight change due to excavation and soil Lowering, overlapping the domain and destroying the domain support leads to landslides.ConclusionsIn this study, the risk of landslides in Nir County., using a combination of ANP and MABAC methods, has been investigated. The results of the study showed that land use factors, lithology, elevation and slope classes with the values of 0.152, 0.151, 0.13 and 0.132, respectively, had the highest weight coefficient and according to the study of the role and The importance of each of the factors involved in the formation of the landslide and also the results of using the final research and analysis method using the MACAC method, as one of the multicriteria decision analysis methods, are 14.05 and 25.52%, respectively. Studies are on very highrisk and highrisk classes. Due to the landslide zoning plan of Nayr city, very highrisk and highrisk areas are mainly on the slope of 20 to 35%. It can also be said that the results of this study indicate the high power of Nir County in terms of the occurrence of sliding movements.Keywords: Landslide, ANP, MABAC, Nir County.ReferencesHaque U, Paula F. d Silva Graziella Devoli, Pilz J, Zhao B, Khaloua A, Wilopoi W, Andersen P, Luk P, Lee J, Yamamoto T, Keellings D, Wuo J.H, E. Glass, 2019. The human cost of global warming: Deadly landslides and their triggers (1995–2014), Science of The Total Environment, Volume 682, pp 673684.Rossi, M. Guzzetti, F. Salvati, P. Donnini, M. Napolitano, E. Bianchi, C. 2019. A predictive model of societal landslide risk in Italy, EarthScience Reviews Volu 196, 102849: pp 119. Ahmadi, Hassan and Ali Talebi. 2001. Investigation of effective factors in creating mass movements (Ardal region of Chaharmahal Bakhtiari province), Iranian Journal of Natural Resources, Volume 4, Number 4, pp. 329323.Sorbi, A., Farrokhnia, A, 2018. Landslide hazard evaluation and zonation of KarajCHaluse road (North of Iran). International Journal of Geography and Geology. 7, No. 2, pp. 3544. 23057041.