نوع مقاله : مقاله پژوهشی
نویسندگان
1 کارشناسی ارشد مخاطرات محیطی، گروه ژئومورفولوژی، دانشکده منابع طبیعی، دانشگاه کردستان.
2 دانشیار و عضو هیات علمی گروه ژئومورفولوژی، دانشکده منابع طبیعی، دانشگاه کردستان
3 گروه پژوهشی مطالعات محیطی دریاچه زریبار، پژوهشکده کردستانشناسی، دانشگاه کردستان، سنندج، ایران.
4 گروه مرتع و آبخیزداری، دانشکده منابع طبیعی، دانشگاه کردستان
5 دانشیار و عضو هیات علمی گروه مرتع و آبخیزداری، دانشکده منابع طبیعی، دانشگاه کردستان
چکیده
سیل دومین بلای طبیعی است که سالانه خسارات زیادی را به جوامع انسانی وارد میآورد. در این میان شهرها و مراکز جمعیتی، بیشترین ریسک و احتمال خسارت فیزیکی قابل لمس ناشی از وقوع سیل را دارا هستند. شهر سنندج به دلیل احاطه شدن به وسیله کوهها و تپهها پتانسیل بالایی در تولید رواناب و انتقال آن به سطح شهر را دارد.بنابراین هدف از این مطالعه پیشبینی مکانی مخاطره سیلاب در شهر سنندج در استان کردستان با استفاده از الگوریتمهای شاخص آماری (SI) و مدل تابع شواهد قطعی (EBF) هم به صورت منفرد و هم به صورت ترکیبی در محیط GIS است.فاکتورهای مؤثر بر وقوع سیل که در این مطالعه در نظر گرفته شدند شامل درصد شیب، جهت شیب، ارتفاع، فاصله از رودخانه، تراکم رودخانه، تجمع جریان، کاربری اراضی، انحنای شیب، لیتولوژی، فاصله از معابر، تراکم معابر، فاصله از ساختمان، تراکم ساختمان و میزان بارندگی بود. پس از جمعآوری اطلاعات و لایههای مورد نیاز، نقشه پیشبینی مکانی حساسیت سیلاب در شهر سنندج تهیه شد. به منظور ارزیابی عملکرد مدلها از سطح زیر نمودار AUC به دست آمده از منحنی ROC استفاده گردید. با توجه به معیار ارزیابی مورد استفاده در این مطالعه (ROC) و با توجه به دادههای اعتبارسنجی، مدل تابع شواهد قطعی (840/0) نسبت به مدل شاخص آماری (827/0) در پهنهبندی خطر سیلخیزی در منطقه مورد نظر دارای بهترین عملکرد بود. در مدل ترکیبی SI-EBF همچنین میزان صحت با توجه به دادههای اعتبارسنجی برابر 849/0 بود که این نشان داد، عملکرد مدل ترکیبی SI-EBF در پیشبینی مکانی خطر سیلاب در مطالعه حاضر نتایج بهتری نسبت به مدلهای منفرد داشته است.در نهایت نتایج مطالعه نشان داد که تراکم ساختمانی و معابر شهری عوامل اصلی در وقوع سیلاب شهر سنندج هستند که براساس نقشه پهنهبندی خطر سیل ارائه شده میتوان اقدامات مدیریتی مناسبی را برای کاهش خسارتها و تلفات ناشی از سیل انجام داد.
کلیدواژهها
موضوعات
عنوان مقاله [English]
Flood hazard mapping in Sanandaj using combined models of statistical index and evidential belief function
نویسندگان [English]
- Mahnaz Azadtalab 1
- Himan Shahabi 2 3
- Ataollah Shirzadi 4
- Kamran Chapi 5
1 Master of Environmental Hazards, Department of Geomorphology, Faculty of Natural Resources, University of Kurdistan, Iran.
2 Associate Professor, Department of Geomorphology, Faculty of Natural Resources, University of Kurdistan, Iran.
3
4 Department of Rangeland and Watershed Management, Faculty of Natural Resources, University of Kurdistan, Sanandaj, Iran.
5 Associate Professor, Department of Rangeland and Watershed Management, Faculty of Natural Resources, University of Kurdistan, Sanandaj, Iran.
چکیده [English]
The flood is the second natural disaster in terms of the damage that it causes to human societies every year. At the same time, cities and population centers are exposed to the highest risk and potential for physical damage caused by flood events. The growing trend of floods in Iran in recent years indicates that most parts of the country are at risk. According to the conducted studies, about forty large and small floods occur annually in different parts of the country. Since the flood is the most devastating disaster in the world and a serious threat to life, preparation of flood hazard maps is essential in identification of flood-sensitive areas, and is one of the first steps taken to reduce damage. It should be noted that researchers can easily identify areas with high risk using flood hazard maps to prevent damage. In the modeling of research on natural and environmental hazards such as floods, the complexity of natural systems makes it difficult to use physical models, highlighting the use of hybrid models as a suitable alternative. Therefore, it is necessary to provide appropriate methods and suggestions for estimation of runoff and flood in areas with high risk in order to prevent their occurrence.
In recent years, a large number of statistical and probabilistic models have been used for flood hazard mapping, and GIS has been used as a basic analysis tool for spatial management and data manipulation due to its capability of managing large amounts of spatial data. Furthermore, it is possible using GIS prediction models to partition urban areas in terms of flood hazard. The obtained hazard maps can be used for identification of areas with high flood hazard. Today, the accuracy of flood susceptibility maps in urban areas can be increased using hybrid GIS models rather than single ones. Therefore, the purpose of this study was to predict the risk of flood in the city of Sanandaj, Kurdistan Province, Iran using hybrid models in the GIS environment. The factors considered in this study as influencing the occurrence of flood included inclination, slope, elevation, distance from the river, river density, flow accumulation, land use, gradient curvature, lithology, distance from the passage, road density, distance from the building, building density, and rainfall. After collecting the required data and layers, we used two algorithms, including the definitive statistical index (SI) and the evidential belief function (EBF), both in isolation and in combination. The locations of flood susceptibility in Sanandaj were predicted. In order to assess the performance of the model, the AUC curve obtained from the ROC curve was used. According to the adopted assessment criteria (ROC) and the validation data, the EBF model (0.840) exhibited better performance than the SI model (0.827) in flood hazard mapping in the area under investigation. The accuracy rate of the hybrid SI-EBF model was 0.849 based on the ROC results, which demonstrated that the hybrid model performed better in prediction of the spatial hazard of flood than the single models. Finally, the results of the study showed that Sanandaj flood spurts resulted from various environmental and human factors, which can be handled using flood hazard maps and appropriate management measures to reduce flood damage.
کلیدواژهها [English]
- Hybrid model
- Hazard mapping
- Statistical index
- Evidential belief function
- Sanandaj
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