ارزيابی تاثير مدل¬ رقومی ارتفاع، روش زمين آمار و شاخص¬های گياهی در برآورد فرسايش خاک (مطالعه موردی: آبخيز ريمله)
محورهای موضوعی : کشاورزی، مرتع داری، آبخیزداری و جنگلداری
صالح آرخی
1
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افشین شعبانی
2
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سید حسین روشان
3
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بنیامین عشقی
4
1 - 1- دانشیار گروه جغرافیا، دانشکده علوم انسانی، دانشگاه گلستان، گرگان، ایران
2 - دانش‌آموخته کارشناسی ارشد، گروه سنجش از دور و سیستم اطلاعات جغرافیایی، دانشکده جغرافیا، دانشگاه تهران، تهران، ایران
3 - دانشگاه علوم کشاورزی و منایع طبیعی ساری
4 - دانشجوی کارشناسی ارشد سیستم اطلاعات جغرافیایی، گروه مهندسی نقشه برداری، دانشکده فنی، موسسه غیرانتفاعی لامعی گرگانی، گرگان، ایران
کلید واژه: هدررفت خاک, توسعه پايدار, GIS, RS, RUSLE.,
چکیده مقاله :
فرسايش خاک از معضلات مهم آبخيزهاي کشور است و به عنوان يکي از مهمترين موانع دست¬يابي به توسعه پايدار کشاورزي و منابع طبيعي به‌شمار می‌رود. دقت بالای پارامترهای ورودی مدل RUSEL موجب تخمین دقیق‌تر هدررفت و فرسایش خاک می‌شود. در این مطالعه، ضمن تلفیق مدل جهانی فرسایش خاک RUSLE با سنجش از دور (RS) و سامانه اطلاعات جغرافیایی (GIS)، پارامترهای فرسایندگی باران (R)، پوشش گياهي (C) و طول و درجه شيب (LS) با روش‌های مختلف تهیه شدند. بدین ترتیب، عامل فرسایندگی باران بر اساس داده‌های 25 ساله، 13 ایستگاه باران‌سنجی و روش‌های کریجینگ معمولی، ساده و عام بدست آمد. عامل پوشش گیاهی نیز بر مبنای شاخص‌های NDVI، IPVI و NDBI با استفاده از تصاویر ماهواره لندست 8 تولید شدند. عامل طول و درجه شیب نیز بر اساس مدل رقومی ارتفاع ماهواره SRTM با قدرت تفکیک‌های 30 و 90 متر و مجموعه NED با قدرت تفکیک 10 متر تهیه شد. در نهایت با 9 ترکیب میزان فرسایش و بار رسوبی با مدل RUSLE در حوضه برآورد شد. نتایج نشان داد که میانگین هدر رفت خاک، ترکیب شاخص گیاهی NDBI، طول و درجه شیب حاصل از مدل رقومی ارتفاع NED با قدرت تفکیک 10 متر و عامل فرسایندگی باران حاصل از روش درون‌یابی کریجینگ ساده برابر با 84/16 (تن در سال) می‌باشد و در مقایسه با رسوب مشاهده‌ای (5/16 تن در سال) به عنوان ترکيب مناسب انتخاب شد. بر این اساس شاخص NDBI در ترکيب با ساير عوامل نسبت به شاخص NDVI کارايي بیشتری در تهیه فاکتور پوشش گياهي مدل RUSLE دارد.
Soil erosion is one of the important problems of watersheds in the country and is considered as one of the most important obstacles to achieving sustainable development of agriculture and natural resources. The high accuracy of the input parameters of the RUSEL model leads to a more accurate estimation of soil loss and erosion. In this study, while integrating the RUSLE model with remote sensing (RS) and geographic information system (GIS), parameters of rainfall erosivity (R), vegetation cover (C) and slope and length (LS) were prepared with different methods. In this way, the rainfall erosivity factor was obtained based on 25 years of data, 13 rain gauge stations and ordinary, simple and universal kriging methods. Vegetation factor was also produced based on NDVI, IPVI and NDBI indices using Landsat 8 satellite images. The length factor and slope were also prepared based on the SRTM DEM with 30- and 90-meters and NED with 10 meters. Finally, with 9 combinations, the amount of erosion and sediment estimated with the RUSLE model in the watershed. The results showed that the mean soil loss, the composition of the NDBI index, the length and slope steepness obtained from the NED with 10 meters resolution and the rainfall erosivity factor obtained from the simple kriging method is equal to 16.84 (t/y). And compared to the observed sediment (16.5 t/y). Based on this, the NDBI index in combination with other factors is more effective than the NDVI index in preparing the cover factor of the RUSLE model.
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