شناسایی مهم‌ترین متغیرهای محیطی در پیش‌بینی مکانی مناطق مستعد سیل‌گیری با استفاده از مدل بیشینه آنتروپی در بخشی از استان گلستان

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشجوی دکتری منابع آب، گروه مهندسی آب، واحد کرمانشاه، دانشگاه آزاد اسلامی، کرمانشاه، ایران

2 گروه مهندسی آب، واحد کرمانشاه، دانشگاه آزاد اسلامی، کرمانشاه، ایران

3 دانشیار گروه مهندسی آب، واحد کرمانشاه، دانشگاه آزاد اسلامی

4 گروه مهندسی آب، واحد کرمانشاه، دانشگاه ازاد اسلامی، کرمانشاه

چکیده

سیل یک بلای طبیعی مخرب طی سال­های گذشته بوده است. در پژوهش حاضر به منظور مدل­سازی و تهیه نقشه­ی مکانی مناطق مستعد سیل­گیری حوزه آبخیز سالیان­تپه واقع در استان گلستان با مساحت  47/4515 کیلومتر مربع، از مدل بیشینه آنتروپی که یکی از مدل­های پیشرفته داده­کاوی است استفاده شده است. بدین منظور در ابتدا براساس گزارش­های موجود و بررسی­های میدانی نقشه پراکنش سیل تهیه گردید. در ادامه سیزده متغیر اثرگذار به عنوان عوامل پیش­بینی کننده شامل طبقات ارتفاعی، درصد شیب، جهت شیب، بارندگی، فاصله از شبکه زهکشی، کاربری اراضی، سنگ شناسی، بافت خاک، انحنای طرح، انحنای پروفیل، شاخص رطوبت توپوگرافی، تراکم زهکشی و شاخص توان جریان، شناسایی و به مدل معرفی شدند. سپس سه سری متفاوت از نقاط وقوع خطر سیل (ds1, ds2, ds3) شامل 70 درصد برای آموزش و 30 درصد برای اعتبار سنجی مدل به صورت تصادفی آماده گردید، تا دقت و صداقت[1] مدل براساس شاخص ROC مورد ارزیابی قرار گیرد. نتایج نشان داد که مدل بیشینه آنتروپی با دقت عالی (بالای 90 درصد) مناطق مستعد سیل­گیری را پیش بینی نموده است. همچنین در این تحقیق درجه اهمیت متغیر­ها توسط مدل مورد بررسی قرار گرفت و نتایج نشان داد که دو عامل تراکم زهکشی (حدود 49درصد اهمیت) و فاصله از جریان (حدود 15درصد اهمیت) به‌عنوان مهم‌ترین عوامل محیطی مؤثر بر سیل­گیری منطقه مورد مطالعه، شناسایی شدند.



[1] robustness

کلیدواژه‌ها


عنوان مقاله [English]

Identification of the Most Important Environmental Variables in Spatial Prediction of Flood Prone Areas using the Maximum Entropy Model in Parts of Golestan Province

نویسندگان [English]

  • ehsan moradi 1
  • ahmad rajabi 2
  • saeid shabanlou 3
  • fariborz yosefvand 4
1 Ph.D. Candidate, Department of Water Engineering, Kermanshah Branch, Islamic Azad University, Kermanshah, Iran
2 Department of Water Engineering, Kermanshah Branch, Islamic Azad University, Kermanshah, Iran
3 Department of Water Engineering, Kermanshah Branch, Islamic Azad University, Kermanshah, Iran
4 water Dept., kermanshah branch, islamic azad university, kermanshah, iran
چکیده [English]

Flood is a destructive natural hazard over the recent years. In the current study, the maximum entropy model as an advanced data mining model was used to model and provide the spatial maps of flood prone areas in Saliantapeh Watershed, Golestan Province, with an area of 4515.47 km2. For this purpose, the flood inventory map was prepared based on available reports and field surveys. Then, 13 effective variables including the digital elevation model, slope percent, slope direction, rainfall, distance from drainage network, land use, lithology, soil texture, plan curvature, profile curvature, topographic moisture index, drainage density and flow capacity index were identified and introduced to the model. After that, three different series of  flood risk points (i.e. ds1, ds2, and ds3) including 70% for training and 30% for validation of the model were randomly prepared to evaluate the accuracy and robustance of the model based on the ROC Index. The results showed that the maximum entropy model with high accuracy (above 90%) predicted flood prone areas. Moreover, in this study, the degree of importance of the variables was investigated by the model and the results demonstrated that the two factors of the drainage density (about 49% of importance) and distance from the streamflow (about 15% of importance) were detected as the most important environmental factors affecting flood in the studied area.

کلیدواژه‌ها [English]

  • data mining model
  • flood predictors
  • ROC Curve
  • Robustness
  • Saliantapeh catchment
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