بررسی تغییرپذیری ماهانة فرسایش خاک در آبخیز معرف کسیلیان با استفاده از مدل RUSLE

نوع مقاله : پژوهشی

نویسندگان

1 دانش‌آموختة کارشناسی ارشد گروه مهندسی آبخیزداری، دانشکدة منابع‌طبیعی، دانشگاه تربیت مدرس، نور

2 دانشیار گروه مهندسی آبخیزداری، دانشکدة منابع‌طبیعی، دانشگاه تربیت مدرس، نور

3 استادیار گروه مهندسی آبخیزداری، دانشکدة منابع‌طبیعی، دانشگاه تربیت مدرس، نور

10.22092/wmrj.2023.362691.1545

چکیده

مقدمه و هدف
یکی از رایج‌ترین انواع نابودی خاک، فرسایش خاک به‌وسیلة عامل‌های باران و رواناب است. فرسایش خاک باعث کاهش کیفیت خاک در محل فرسایش می‌شود و رسوب به‌وجود آمده از فرسایش نیز باعث ایجاد مشکلاتی در درون و خارج از آبخیز می‌شود. به‌دلیل هزینة زیاد اندازه‌گیری فرسایش خاک و تولید رسوب، مدل‌های متنوعی برای برآورد شدت این متغیرها در مقیاس‌های مختلف مکانی و زمانی پیشنهادشده است. از این میان معادلة جهانی اصلاح‌شدة هدررفت خاک  (RUSLE) هم به‌دلیل وجود داده‌های لازم برای عامل‌های ورودی مدل و هم امکان اجرا به‌شکل توزیعی، به‌طور گسترده‌ در همة نقاط جهان استفاده‌شده است.
مواد و روش‌ها
این پژوهش با هدف برآورد فرسایش خاک با استفاده از مدل RUSLE در مقیاس ماهانه در سال 2021 برای آبخیز معرف کسیلیان انجام ‌شد. ابتدا نقشة توزیعی پنج عامل مدل RUSLE تهیه شد. از آنجایی که متغیرهای پوشش‌گیاهی و بارش در مقیاس ماهانه تغییر قابل توجهی داشتند، تغییرات زمانی عامل‌های مزبور منجر به پویایی سامانة آبخیز و تغییرات ماهانه فرسایش خاک ‌شد. هم‌چنین، عامل‌های فرسایش‌پذیری خاک، پستی‌بلندی و مدیریت زمین‌ به‌عنوان عامل‌های ایستا در نظر گرفته شد. سرانجام عامل‌های پنج‌گانه مدل در نرم‌افزار Arc GIS در یکدیگر ضرب شدند و نقشه‌های توزیعی فرسایش در مقیاس‌های ماهانه، فصلی و سالانه تهیه شد.
نتایج و بحث
با توجه به نقشه‌های توزیعی ماهانه، فصلی و سالانة فرسایش خاک، بیش‌ترین و کم‌ترین فرسایش ماهانة خاک به‌ترتیب 1/13 و 0/13 تن در هکتار در ماه‌های نوامبر و آوریل رخ داد. میانگین شدت فرسایش خاک در فصل‌های بهار، تابستان، پاییز و زمستان به‌ترتیب 1/32، 2/74، 2/99 و 1/52 تن در هکتار به‌دست آمد. بنابراین، کم‌ترین فرسایش فصلی خاک به‌ترتیب در بهار و زمستان و بیش‌ترین آن به‌ترتیب در پاییز و تابستان بود. سرانجام می‌توان گفت فرسایش خاک در نیمة دوم سال بیش‌تر از نیمة اول بود. میانگین شدت فرسایش خاک در آبخیز معرف کسیلیان 8/56 تن در هکتار در سال برآورد شد.
نتیجه‌گیری و پیشنهادها
نتایج نشان داد فرسایش در بخش گسترده‌ای از آبخیز بررسی‌شده، کم بود و فقط دامنه‌های با شیب زیاد به‌ویژه با پوشش ‌گیاهی کم شامل مراتع و زمین‌های زراعی رهاشده، مستعد فرسایش تشدیدی خاک بودند. بر اساس نتایج این پژوهش فرسایش خاک به‌دلیل تبدیل کاربری‌های جنگل و مرتع به زمین‌های کشاورزی و باغی و حتی مسکونی، افزایش یافت. سرانجام پیشنهاد می‌شود که با استفاده از راهکارهای مدیریتی و اقدام‌های حفاظت خاک به‌ویژه در دامنه‌ها و مناطق با شیب زیاد از تغییر کاربری زمین‌ جلوگیری شود.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Investigating the Monthly Variability of Soil Erosion in the Kasilian Representative Watershed Using RUSLE Model

نویسندگان [English]

  • Fatemeh Sarouneh 1
  • Abdulvahed Khaledi Darvishan 2
  • Vahid Moosavi 3
1 Former M.Sc. Student, Department of Watershed Management, Faculty of Natural Resources, Tarbiat Modares University, Noor, Iran
2 Associate Professor, Department of Watershed Management, Faculty of Natural Resources, Tarbiat Modares University, Noor, Iran
3 Assistant Professor, Department of Watershed Management, Faculty of Natural Resources, Tarbiat Modares University, Noor, Iran
چکیده [English]

Introduction and Goal
One of the most common types of soil degradation is soil erosion under the influence of rain and runoff factors. Soil erosion reduces the quality of the soil in the place of erosion, and also the sediment resulting from erosion causes problems inside and outside the watershed. Due to the high cost of measuring soil erosion and sediment yield, various models have been developed to estimate the intensity of these variables in different spatial and temporal scales. Among these, the revised universal soil loss equation (RUSLE) has been widely used in all parts of the world for reasons including the availability of data required for model input factors and the possibility of implementing it in a distributed format.
Materials and Methods
The present study was conducted in order to estimate soil erosion using the RUSLE model on a monthly scale for 2021 in the Kasilian Watershed. First, a distribution map of the five factors of the RUSLE model was prepared. Since the variables of vegetation cover and precipitation have a significant change on a monthly scale, therefore, the temporal changes of the mentioned factors lead to the dynamics of the watershed system and the monthly changes of soil erosion. Furthermore, soil erodibility factors, topography and land management were considered as static factors. Finally, the five factors of the model were multiplied together in Arc GIS software and erosion distribution maps were prepared on monthly, seasonal and annual scales.
Results and Discussion
According to the monthly, seasonal and annual distribution maps of soil erosion, the highest and lowest monthly soil erosion occurred in November and April with values of 1.13 and 0.13 tons per hectare, respectively. Also, the average intensity of soil erosion in spring, summer, autumn and winter seasons was 1.32, 2.74, 2.99 and 1.52 tons per hectare respectively. Therefore, spring and winter seasons respectively had the least and autumn and summer seasons had the highest contribution in the annual soil erosion. It can also be said that more soil erosion has occurred in the second half of the year compared to the first half. Finally, the average intensity of soil erosion in the Kasilian Watershed was estimated at 8.56 tons per hectare per year.
Conclusion and Suggestions
The results showed that a large part of the study watershed has low erosion and only the steep slopes, especially with low vegetation, including rangelands and abandoned agricultural lands, are prone to accelerated soil erosion. Specifically, soil erosion has increased due to the conversion of forest and rangeland into agricultural and orchard and even residential land. Finally, it is suggested to prevent the land use change by using land management solutions and soil conservation measures, especially in high slopes.

کلیدواژه‌ها [English]

  • Distributed models
  • land use change
  • RUSLE model
  • soil conservation
  • soil erodibility
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