پتانسیل سیل‌خیزی حوضه‌های آبریز استان کردستان با به‌کارگیری شاخص‌های مورفومتری و تحلیل‌های آماری

سیل یکی از مهم ترین مخاطرات تهدیدکننده جامعه بشری محسوب می شود. در دهه های اخیر با افزایش جمعیت و تغییر اقلیم اثرات این مخاطره بیشتر شده است. مطالعه ویژگی های حوضه ها که میزان سیل خیزی با آن در ارتباط است می تواند به مدیریت صحیح این مخاطره کمک نماید. استان کردستان با اقلیم نیمه خشک و تغییر پذیری زیاد بارش از پتانسیل بالایی برای این مخاطره برخوردار است. در این مقاله پتانسیل سیل خیزی حوضه های استان کردستان شامل حوضه های قرارگرفته در داخل استان و مشترک با استان های مجاور با استفاده از شاخص های مورفومتری و هیدروگرافی محاسبه گردید. با این هدف و بر اساس عوامل توپوگرافی و هیدرولوژی سطحی 18 حوضه شناسایی و مورد ارزیابی قرار گرفتند. در ادامه پژوهش آبراهه ها بر اساس روش استرالر طبقه بندی و سپس 12 پارامتر شاخص در ارتباط با سیل خیزی شامل طول حوضه، تراکم زهکشی، نسبت انشعاب، فراوانی آبراهه ها، طول جریان سطحی، ضریب فرم حوضه، شکل حوضه، ضریب کشیدگی، ضریب گردی، ضریب فشردگی، نسبت بافت و مساحت برای تمام حوضه ها محاسبه گردید. از نرم افزارهای gis و excel به منظور تسهیل محاسبات و استخراج داده ها و spss برای طبقه بندی و نیز استاندارد کردن داده ها استفاده شد. نتایج نشان داد که حوضه های آبخیز موردمطالعه بر اساس پارامترهای موردمطالعه در دو خوشه قرار می گیرند. به ترتیب خوشه 1 دارای 11 حوضه شامل حوضه های بیجار، گل تپه، تپه اسماعیل، بوکان، رزاب، سقز، انگوران، قروه، سنندج، تکاب و شاهین دژ و خوشه 2 دارای 7 حوضه شامل حوضه های پاوه، سردشت، بانه، روانسر، کامیاران، مریوان و قزلچه می باشد. همچنین نتایج مقایسه ای بیانگر قرارگیری حوضه های خوشه 1 در شرق و حوضه های خوشه 2 در غرب محدوده موردمطالعه است. مجموع برآوردها و تحلیل های آماری نشان دهنده پتانسیل سیل خیزی بیشتر حوضه های شرقی با وجود بارندگی بیشتر حوضه های غربی است که دلیل بارز آن ناشی از شرایط توپوگرافی، پوشش گیاهی و لیتولوژیکی خاص حوضه های شرقی است.

Landslides susceptibility mapping using hybrid model of Bayes' theorem & ANP, Case Study: Ahar drainage basin South boundary (From Nasirabad to Sattar Khan dam)

IntroductionMass movements and landslides are considered the most destructive natural hazards. The study predicts landslide location using conditional probability theory (Bayesian theorem), on the southern edge of the Ahar drainage basin (From Nasirabad to Sattar Khan dam),, on the landslide occurred in the past by the objectoriented approach extracting and identifying been conducted. Using Bayesian probability theory correlation between parameters and landslide areas (twothirds of landslide areas) to determine the weight of all categories of parameters were obtained. According to the map obtained by any of the parameters weight class, class of high silt old alluvial terraces are in layers, average pasture land in between classes, directions north and northwest, steep grade 525 the distance of 270125 meters from the river greatest impact on weight and landslides in the area. The accuracy of landslide susceptibility maps using a third (12 points slip) landslide areas were evaluated. The result showed that the model with the predictability and kappa coefficient 0/93 and 0/945 percent of high and very high risk of landslides in class acceptable accuracy in evaluating and landslide susceptibility mapping.Materials MethodsIn this study, objectoriented method to extract landslides, the IRS P 6 bands of satellite images were proper. Multiresolution segmentation algorithm was then applied for the segment. Among the different scales, scale 35 was chosen as the appropriate scale and form factor and compression factor each respectively 0.2 and 0/5 were selected and specific conditions of each class at the end of the definition, classification was carried out in the last stage to win to assess the landslide susceptibility in the region of evidence weight method is used. This model is useful as a model and tested in different fields, such as the study of mass movements, mineral research and mapping underground springs.ANP Method:Network analysis process is one of the MCDM techniques and in behalf of the compensation models. This model of hierarchical control, clusters, elements, and elements is an interaction between clusters. In general, the implementation of network analysis process model can be described in four stages as follows. 1. Build the model and create a lattice structure 2 binary comparison and determine the priority vectors that are actually similar to those in the analytic hierarchy process in the network analysis process repeated measures conducted in the screw. 3. The formation of primary and uneven super matrix. 4. The weighted matrix (5) formed Super eventually formed the super matrix.weight of evidence(WofE):weight of evidence(WofE) is a statistical method based on probability theory. This model represents relationships between an event landslides occurred and causative factors predisposing factors landslide estimates. In 1988, the model was used for mineral exploration. It is used to assess the landslide susceptibility. If causal factors (predisposing factors landslide) to B, class B i and landslides occurred in each parameter to consider S, then the Bayesian theory to calculate the conditional probability of landslides (S) in certain class (B i), can be used the following equation: In this study, using 10 natural and human parameters (lithology, distance from fault, distance from the river, rainfall, land slope, slope, land use, density of vegetation(NDVI) and sediment transport index(STI) stream power index (SPI) and topographic wetness index (TWI) zonation action has been taken.Discussion of ResultsAccording to maps and information provided by a layer formation, and are old alluvial terraces conglomerate, the greatest impact and the weight to be allocated. Tuff, siltignimbrite alternating with layers of sandstone and conglomerate is the next category. Pyroxene and andesite rock formations as well as the other layers of the lowest weight and effect in landslides in the region. Among the different classes of land, pasture medium with the most weight had the greatest impact on landslide occurred that can focus in relation to human activities and population centers in these areas. Among the different tilt directions, directions north and northwest and the southern and southeastern most minimal impact on land sliding. Also, the slope of 155 and 2515 have the highest impact and landslides have weight. Class 270 125 meters away from the river layer also have the greatest impact on landslides.ConclusionIn this study, potential zoning landslides type South Bank Ahar drainage basin to the dam of the village of Nasirabad Khan, was evaluated. To do this, set the parameters of natural and man and landslides type occurred in the area (70 percent landslide) and ANP and Bayes' theorem is used to combine the two models. According mapped the western and southern parts of the North East region in terms of range and landslides has the greatest potential landslides. According to Table 3, 29/17% of the land as a regional study area with high potential for landslides have been considered. To assess the final map of 30% was used for regional landslide to the accuracy of the model used for zoning. Based on the results obtained from the assessment and placement of a significant percentage of the landslide in the floor with high sensitivity and very much (57/05) the accuracy of the model used in the occurrence of landslide susceptibility zoning acceptable and good.