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ارزیابی و پهنه‌بندی وقوع مخاطرۀ سیلاب در پارک ملی گلستان | ||
| اکوهیدرولوژی | ||
| مقاله 17، دوره 6، شماره 4، دی 1398، صفحه 1055-1068 اصل مقاله (1.1 M) | ||
| نوع مقاله: پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22059/ije.2019.285430.1163 | ||
| نویسندگان | ||
| حسن فرامرزی1؛ سید محسن حسینی* 2؛ حمیدرضا پورقاسمی3؛ مهدی فرنقی4 | ||
| 1دانشجوی دکتری جنگل‌داری دانشگاه تربیت مدرس، دانشکدۀ منابع طبیعی و علوم دریایی نور، مازندران | ||
| 2استاد گروه جنگل‌داری دانشگاه تربیت مدرس، دانشکدۀ منابع طبیعی و علوم دریایی نور، مازندران | ||
| 3دانشیار بخش مهندسی منابع طبیعی و محیط زیست، دانشکدۀ کشاورزی، دانشگاه شیراز، شیراز | ||
| 4محقق مرکز GIS، گروه جغرافیای فیزیکی و علوم اکوسیستم، دانشگاه لند، سوئد | ||
| چکیده | ||
| شناسایی مناطق حساس به سیل، عنصر حیاتی و مهمی برای کنترل و کاهش تلفات سیل بهشمار میآید. هدف از تحقیق حاضر، شناسایی متغیرهای مهم در ایجاد مناطق سیلگیر و ارائۀ پتانسیل مخاطرۀ سیل پارک ملی گلستان با استفاده از تکنیکهای یادگیری ماشین شامل مدل جنگل تصادفی، درخت رگرسیون تقویت‌شده و آنتروپی بیشینه است. برای رسیدن به اهداف یادشده، ابتدا عوامل تأثیرگذار با توجه به مرور منابع تعیین شده و پایگاه دادهها ایجاد شد. در نهایت، با استفاده از تکنیکهای یادگیری ماشین مدلسازی مخاطرۀ سیل صورت گرفت و دقت این مدلها با استفاده از روش منحنی ROC و دادههای واقعی از رخداد سیل بررسی شد. نتایج مدلها، اهمیت زیاد متغیرهای ارتفاع از سطح دریا، میانگین دمای سالیانه، فاصله از آبراههها، بارش و فاصله از جادۀ ترانزیتی را در وقوع مخاطرۀ سیل نشان دادند. نتایج به‌دست‌آمده از درخت رگرسیون تقویت‌شده تأثیر متغیر ارتفاع از سطح دریا، میانگین دمای سالیانه، بارندگی و فاصله از آبراههها را به‌ترتیب، 9/38، 2/19، 6/13 و 13 درصد نشان داد. همچنین، در نتایج حاصل از آنتروپی بیشینۀ متغیرهای ارتفاع از سطح دریا، میانگین دما و جادۀ ترانزیتی به‌ترتیب با مقدار مشارکت 7/35، 4/22 و 5/19 درصد جزء متغیرهای مهم به‌دست آمدند. نتایج به‌دست‌آمده از ارزیابی صحت مدلها با استفاده از 30 درصد از دادههای وقوع سیل که در مدلسازی وارد نشده بود نیز دقت زیاد مدل درخت رگرسیون تقویت‌شده و جنگل تصادفی را با مقدار ROC، 99/0 و دقت مناسب آنتروپی بیشینه را با مقدار ROC، 89/0 نشان داد، بهطوری که نقشههای به‌دست‌آمده از این مدلها به طور مشترک 4500 هکتار از مساحت پارک را دارای احتمال زیاد خطر سیل برآورد کردند. | ||
| کلیدواژه‌ها | ||
| آنتروپی بیشینه؛ درخت رگرسیون تقویت‌شده؛ مخاطرۀ سیل؛ مدل جنگل تصادفی؛ مدیریت بحران | ||
| عنوان مقاله [English] | ||
| Assessment and Zoning of Flood Risk in Golestan National Park | ||
| نویسندگان [English] | ||
| Hassan Faramarzi1؛ Seyed Mohsen Hosseini2؛ Hamid Reza Pourghasemi3؛ Mahdi Farneghi4 | ||
| 1PhD Student, Department of Natural Resources, Tarbiat Modares University, Noor, Mzandaran | ||
| 2Professor, Department of Natural Resources, Tarbiat Modares University, Noor, Mzandaran | ||
| 3Associate Professor, Department of Natural Resources and Environment, Faculty of Agriculture, Shiraz University, Shiraz | ||
| 4GIS Center, Department of Physical Geography and Ecosystem Science, Lund University, Sweden | ||
| چکیده [English] | ||
| Identifying the flood susceptible areas is a vital and substantial element of disaster management to control and mitigate injuries of the natural hazards. The purpose of this study was to identify the important variables in creating flood areas and to present the potential hazard of flood in Golestan National Park (GNP) using machine learning techniques including random forest (RF), boosted regression tree (BRT) and maximum entropy (ME) models. In order to achieve these purposes, firstly, factors were determined by reviewing the relevant sources, and the databases were created by sorting out these factors. Finally, Flood risk modeling was done using machine learning techniques and the accuracy assessment were determined using the ROC method and real data recorded in nature. The results of the models showed the importance of elevation, distance from the river and transit road, moisture and maximum temperature variables in the event of flood hazard. So that the results of the BRT showed role elevation variable to be 38.9%, mean temperature 19/2 %, Rainfall 13/6 % and distance from the rivers 13% and the results of ME showed role elevation, mean temperature and distance of road variables to be respectively 35.7, 22/4 and 13.8%. The results of the accuracy assessment models using 30% of the data that were not included in the modeling the ROC value showed BRT and RF model with 0.99 values, and the proper accuracy ME was with value of 0.89. The maps obtained from these models estimated 4,500 hectares of park area among the high risk areas. | ||
| کلیدواژه‌ها [English] | ||
| Flood Hazards, Maximum Entropy, Random Forest, Boosted Regression Tree, Crisis Management | ||
| مراجع | ||
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