Abstract:
شناسایی مناطق حسّاس و تهیة نقشة پهنهبندی خطر زمینلغزش، گام مهمّی در مسیر پیشگیری و کاهش خسارتهای ناشی از وقوع این پدیده است. حوضة هشتجین با داشتن چهرة کوهستانی و با توجّه به وضعیّت زمینشناسی، لیتولوژی، اقلیمی و انسانی، شرایط لازم را برای شکلگیری حرکات لغزشی دارد؛ بنابراین هدف نوشتار پیش رو پهنهبندی خطر زمینلغزش در این منطقه است. در پژوهش حاضر حسّاسیت زمینلغزش برای حوضة آبریز هشتجین با توجّه به ارزیابی کارایی نتایج حاصل از دو مدل رگرسیون لجستیک و آنفیس برای دستیابی به هدف پژوهش، تجزیه و تحلیل شد. با استفاده از تفسیر عکسهای هوایی و بازدید میدانی، مناطق شاهد بهعنوان متغیّر وابسته، با جی.پی.اِس ثبت و درادامه عوامل مؤثّر بر ایجاد زمینلغزش در منطقه شامل شیب، جهت، خطوط ارتفاعی، فاصله از آبراهه، فاصله از گسل، فاصله از جاده، زمینشناسی، کاربری اراضی و بارش با توجّه بهمرور منابع مختلف، مطالعات میدانی و مشورت با کارشناسان شناسایی شد؛ سپس در محیط آرک جی.آی.اِس لایهها بهمثابة متغیّر مستقل تهیه و با ورود لایههای مذکور به محیط نرمافزار ترست، متلب بهترتیب مدل رگرسیون لجستیک و آنفیس اجرا شدند. نقشة نهایی خطر زمینلغزش منطقه در پنج کلاس خطرپذیری تهیه شد. در پژوهش حاضر از 25% نمونههای شاهد بهعنوان دادههای آزمون، بهمنظور سنجش میزان صحّت مدلهای مورد بررسی، استفاده شد. نتایج صحّتسنجی کارایی مدلهای پیشگفته با اجرای منحنی راک نشان داد که دقّت مدل آنفیس و رگرسیون لجستیک بهترتیب برابر 23/88% و 45/86% بوده است. نتایج بر اساس مدل انفیس بیانگر آن است که حدود 4854 هکتار، معادل 6/20% از منطقة هشتجین از نظر مخاطرة زمینلغزش در کلاسة زیاد و خیلیزیاد قرار دارند.
Landslides are one of the most important environmental processes, especially in mountainous landscapes. Identifying sensitive areas and preparing a landslide risk zoning map is an important step in preventing and reducing the damage caused by this phenomenon. Hashtjin basin, with its mountainous face and considering the geological, lithological, climatic and human conditions, has the necessary conditions for the formation of landslides; therefore, the current study aims at landslide risk zoning in the given area. Therefore, landslide sensitivity analysis for Hashtjin watershed is evaluated according to the efficiency of the results obtained from two models of logistic regression and Anfis to achieve the research goal. Using the interpretation of aerial photographs and field visits, control areas, as a dependent variable, were recorded by GPS. Then, the factors affecting landslides in the area including slope, direction, elevation lines, distance from waterway, distance from fault, distance from road, geology, land use and rainfall were identified according to various sources, field studies and consultation with experts; Then, layers were prepared as independent variables in GIS Arc environment. Moreover, logistic and ANFIS regression models were implemented by entering the aforesaid layers into TERRSET and MATLAB software environment, respectively. The final landslide hazard map of the area was prepared in 5 hazard classes. In this study, 25% of the control samples were used as test data to measure the accuracy of the studied models. The results of validation of the performance of the mentioned models by performing the ROC curve showed that the accuracy of Anfis model and logistic regression were equal to 88.23 and 86.45%, respectively. The findings from Enfis model reveal that approximately 4854 hectares, equivalent to 20.6% of the Hashtjin area are in high and very high class in terms of landslide risk. Extended Abstract 1-Introduction Landslides are defined as the displacement of soil under the influence of gravity. It is one of the most destructive and catastrophic geological hazards that has a lot of harmful impacts on human societies every year, including economic damage, destruction of infrastructure and environmental problems. Identifying landslide-prone areas and mass movements is a necessity for natural resource management and development planning. In this regard, mapping landslide-prone areas is one of the most important steps required for planning and decision-making in the field of land use. Mass movements are in special situations. Iran, with its mainly mountainous topography, high tectonic and seismic activity, climatic and geological diversity, has natural conditions for a wide range of landslides. Hashtjin watershed located in Ardabil province, which is geomorphologically the western and northern part of the mountain basin and consists of high slopes with high slopes, is no exception to this rule. The study of landslide distribution in this basin shows that a lot of landslides have occurred and have high potential from unstable slopes. Based on field observations, several landslides have occurred in this area and more landslides are very likely to occur. In fact, it is necessary to pay attention to the landslides of this time zone. 2-Materials and Methods In order to investigate the status of landslides in the past, as educational sample points, and also to determine the factors affecting its occurrence in Hashtjin region, first the aerial photographs of the region during the period from 2015 to 2020 were reviewed. Then, Aerial reconnaissance and adaptation to terrestrial realities were carried out with the help of the natives of the area to confirm the findings from photo interpretation. By field survey, 41 landslides were identified in the study area and the position and limits of each of them were recorded using a GPS device. At the same time, the factors affecting the occurrence of landslides in the region were determined in the field visit including slope, direction, elevation lines, distance from the waterway, distance from the road, lithology status and land cover / land use. In this study, slope, direction and elevation lines maps were prepared using DEM (digital elevation model) ten meters ASTER. Besides, the waterway map of the area was drawn using ARC / Hydro plugin. The road map of the region was also obtained from the data of the Ministry of Roads and Urban Development. Also, the lithological status map of the region was digitized from the geological map with the scale of 1: 100000. Slope, direction, elevation, lithology and land cover / land use maps that needed to be classified were also classified after scoring. 3-Results and Discussion Comparison of lithological map (Figure 6) with spatial distribution of landslides (Figure 2) and logistic regression equation (Equation 12) and zoning maps obtained from quantitative research models (Figures 10 and 12) show the decisive effect of lithology on landslide occurrence in the given study area. In terms of the percentage of the area in high and very high risk classes, both methods indicate almost similar results, so that it can be claimed that approximately 23% of the study area is in high and very high risk class, which are mainly in the western part of the area, Hashtjin. A set of conditions has made landslides very likely to occur in parts of the study area. Nevertheless, the dispersion of specific geological formations that provide very favorable conditions for slope instability in the form of mass destruction are of paramount importance. Most of the landslides in the area occurred on the lithological units of the old alluvial sediment units, the basaltic trachea unit and the worn surface andesite trachea unit. The findings from zoning and spatial prediction of both models show the zones corresponding to these units have a high probability of landslides. This poses a serious threat to the settlements and infrastructure located on these zones. The construction of communication roads on these landslide-sensitive units has not only increased the risks of landslides, but also triggered slope instability. As a result, slope, slope direction and height play a decisive role in the occurrence of landslides on these lithological units. 4-Conclusion The results of Table (No. 3) illustrate that about 6100 hectares, equivalent to 26% of the Hashtjin area is in high and very high class in terms of landslide risk. According to the results presented in Table (No. 4) based on the fuzzy-neural model, it is revealed that about 4854 hectares, equivalent to 20.6% of the Hashtjin area is in high and very high classes in terms of slippery land. The results of the unique ROC analysis showed that exactly the fuzzy-neural model is better and more acceptable than the logistic regression model.
Machine summary:
بـر اساس مشاهدات ميداني زمين لغزش هاي متعددي در اين منطقه اتفاق افتاده و احتمال وقوع زمين لغـزش هـاي 1- Haque 2- Rossi 3- Chen 4- Chang 5- Foerster 6- Aghdam 7- Broeckx 8- Colkesen 9- Das 10- Dou ديگر نيز بسيار است .
1- Le 2- Polykretis 3 - Chalkias 4- Vojtekova & Vojtek 5- Gigovic 6- Li Zhu 7- Analytic Network Process (ANP) معرفي منطقۀ مورد بررسي حوضۀ آبخيز هشتجين طبق تقسيمات کشوري در دهستان خورش رستم از توابع شهرستان خلخـال و در اسـتان اردبيل واقع شده است و از نظر موقعيت جغرافيايي در '١٤°٤٨ تا "١٣ '٣١ °٤٨ طـول شـرقي و "٠٣ '٢٢ °٣٧ تا '٣٠ °٣٧عرض شمالي قرار دارد (شکل ١)، به طوري که روستاي هشتجين با جمعيتي برابر شش هـزار نفـر و بـا اقليم معتدل و نيمه خشک در مرکز آن واقع شده است .
در نوشتار پيش رو به منظور پردازش داده ها دو سري اطلاعات براي تحليل در سيسـتم شـبکۀ عصـبي استفاده ميشود: اول نقشۀ زمين لغزش هاي موجود و دوم نقشۀ پهنه هايي کـه احتمـال زمـين لغـزش در آن هـا بسيار پايين است .
در واقع ، براي بررسي و شناخت شرايطي کـه منجر به بروز زمين لغزش در مکان خاصي شده است ، تهيۀ نقشۀ توزيـع جغرافيـايي زمـين لغـزش هـا ضـرورت 1- Ayalew & Yamagishi 2- Adaptive Neuro-Fuzzy Inference Systems (ANFIS) مي يابد.
نقشۀ نتايج حاصل از پهنه بندي زمين لغزش با استفاده از مدل فازي - عصبي بر اساس شـکل ١٥ نشان داده شده است .