شناسایی مناطق مستعد سیل‌خیزی در حوضه آبریز یامچی با پایش ‏شاخص‌های طیفی و ‏داده‌های ماهواره‌ای

زینالی, بتول; فروتن, مهدی

doi:10.22034/hyd.2025.66392.1784

شناسایی مناطق مستعد سیل‌خیزی در حوضه آبریز یامچی با پایش ‏شاخص‌های طیفی و ‏داده‌های ماهواره‌ای

نوع مقاله : کاربردی

نویسندگان

¹ استاد آب و هواشناسی گروه جغرافیای طبیعی، دانشکده علوم اجتماعی، دانشگاه محقق اردبیلی

² ‏ دانشجوی دکتری آب و هواشناسی، گروه جغرافیای طبیعی، دانشکده علوم اجتماعی، دانشگاه محقق اردبیلی، اردبیل.‏

10.22034/hyd.2025.66392.1784

چکیده

این پژوهش با رویکردی کاربردی و تحلیلی، به شناسایی نواحی مستعد سیل‌خیزی در حوضه آبخیز یامچی ‏پرداخته ‏است. در ابتدا، داده‌های دبی روزانه ایستگاه‌های لای، نیر و یامچی طی سال‌های 2014 تا 2021 از ‏شرکت آب منطقه‌ای استان اردبیل ‏جمع‌آوری شد. سپس، پارامترهای محیطی مؤثر شامل شیب زمین، ‏فاصله از آبراهه، کاربری اراضی و رطوبت خاک در محیط ‏ArcGIS‏ و گوگل ارث انجین ترسیم شدند. ‏همچنین، شاخص‌های طیفی ‏NDWI، ‏AWEI، ‏WRI‏ و ‏LSWI‏ از تصاویر ‏لندست 8 استخراج گردید. پس از ‏استانداردسازی متغیرها، مدل جنگل تصادفی رگرسیونی با 100 درخت تصمیم آموزش داده ‏شد. 70 درصد ‏داده‌ها برای آموزش و 30 درصد برای آزمون مدل استفاده شد. عملکرد مدل با شاخص‌های آماری ‏R²‎‏ و ‏MSE‏ به ترتیب برابر با 9353/0 و 000210/0 ارزیابی شد. در نهایت نواحی مستعد سیل‌خیزی شناسایی ‏گردیدند. به‌منظور اعتبارسنجی، رویداد سیل آوریل 2017 به‌عنوان نمونه موردی تحلیل شد. نتایج نشان ‏داد که بخش شمالی حوضه، به ‏دلیل ارتفاع زیاد، شیب تند، رطوبت خاک ۳۵ درصد و مقادیر بالای ‏AWEI‏ ‏و ‏WRI، بیشترین پتانسیل برای وقوع سیل‌خیزی ‏را دارد. ‏در مقابل، نواحی مرکزی و جنوبی به علت شیب ‏ملایم‌تر و رطوبت کمتر خاک، احتمال کمتری برای سیل‌خیزی ‏نشان دادند. مدل جنگل تصادفی صحت ‏این الگو را تأیید کرد و عملکرد آن با منحنی ‏ROC‏ و مقدار ‏AUC‏ برابر با 616/0، قابل قبول ارزیابی شد. ‏تحلیل داده‌های راداری نیز نشان داد که بازتاب سیگنال‌ها در مناطق شمالی، پیش و پس از وقوع سیلاب، ‏تغییر محسوسی داشته و بیانگر تمرکز منابع آبی در این بخش از حوضه است.‏

کلیدواژه‌ها

موضوعات

اقلیم شناسی

عنوان مقاله [English]

Identifying flood-prone areas in the ‎Yamchi ‎watershed ‎by monitoring spectral indices and ‎satellite ‎data

نویسندگان [English]

Batool Zeinali ¹
Mahdi Frotan ²

¹ Professor of Climatology, Department of physical Geography, Faculty of Social Sciences, University of Mohaghegh Ardabili

² Ph.D. Student of Climatology, Department of Physical Geography, Faculty of Social Sciences, University of Mohaghegh Ardabili, Ardabil, Iran‎

چکیده [English]

In this study, first, daily discharge data of Lai, Nir, and Yamchi stations were collected from the Regional Water Company of Ardabil Province during the years 2014 to 2021. Then, effective environmental parameters including land slope, distance from the waterway, land use, and soil moisture were plotted in ArcGIS and Google Earth Engine. Also, spectral indices NDWI, AWEI, WRI, and LSWI were extracted from Landsat 8 images. After standardizing the variables, a regression random forest model was trained with 100 decision trees. 70% of the data was used for training and 30% for testing the model. The performance of the model was evaluated with statistical indices R² and MSE equal to 0.9353 and 0.000210, respectively. Finally, flood-prone areas were identified. For validation purposes, the April 2017 flood event was analyzed as a case study. The results showed that the northern part of the basin has the highest potential for flooding due to its high elevation, steep slope, 35% soil moisture, and high AWEI and WRI values. In contrast, the central and southern areas showed a lower probability of flooding due to their gentler slope and lower soil moisture. The random forest model confirmed the accuracy of this model, and its performance was assessed as acceptable with an ROC curve and an AUC value of 0.616. Radar data analysis also showed that the signal reflectance in the northern areas changed significantly before and after the flood, indicating the concentration of water resources in this part of the basin.

کلیدواژه‌ها [English]

Flood
99% ‎‎percentile
spectral ‎‎indices
random forest ‎‎‎(RF)
Yamchi ‎‎watershed Ardabil

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