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پهنه‌بندی رقومی شوری خاک سطحی با بکارگیری مدل جنگل تصادفی در اراضی شور دشت ایوانکی. | ||
| تحقیقات آب و خاک ایران | ||
| دوره 55، شماره 3، خرداد 1403، صفحه 431-447 اصل مقاله (1.98 M) | ||
| نوع مقاله: مقاله پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22059/ijswr.2024.370830.669645 | ||
| نویسندگان | ||
| لیلا جهانبازی؛ احمد حیدری* ؛ محمدحسین محمدی | ||
| گروه علوم و مهندسی خاک، دانشکده کشاورزی، دانشگاه تهران، تهران، ایران. | ||
| چکیده | ||
| هدف این مطالعه بررسی تغییرات مکانی شوری خاک با استفاده از مدل RF در بخشی از دشت ایوانکی (استان سمنان، 1398) بود. تعداد 104 نمونه به روش شبکه (فاصله 100 متر)، از 105 هکتار خاک‌های، واقع بر روی مارن و آبرفت‌های سنگریزه‌دار و کاربری پسته کاری با آبیاری جویچه‌ای و اراضی رها انجام شد. بیشترین EC خاک در اراضی رها شده و باغ پسته به ترتیب 2/173و 34 dSm-1 بود. عوامل شوری مواد مادری، کیفیت آب آبیاری، PET زیاد و خیز مویینه املاح بود. ضریب تبیین (R2) نقشه پیش‌بینی شوری توسط مدل RF مساوی 49/0 و مهم‌ترین شاخص‌های کمکی، شوری نرمال شده، خیسی توپوگرافی، سطح مبنای زهکش، پوشش گیاهی نرمال شده و پوشش گیاهی تعدیل شده خاک بودند. شاخص‌های نسبت طیفی داده‌های لندست 8، در پیش‌بینی تغییرات شوری اهمیت زیادی داشتند. از 5 متغیر کمکی موثر در مدل، 3 متغیر مربوط به شاخص‌های نسبت طیفی بود. دلیل اهمیت شاخص‌های نسبت طیفی در مدل، تجمع نمک در سطح خاک، و کاهش سهم متغیرهای زمین‌نما به دلیل مسطح بودن منطقه بود. کاربرد NDVI به تنهایی برای مطالعات شوری کافی نیست و استفاده از شاخص‌های شوری و رطوبت برای پیش‌بینی صحیح ضروری است. بررسی همبستگی بین متغیرهای کمکی و اجرای مدل حذف برگشتی نشان داد که متغیرهای کمکی زیاد، سبب افزایش پیچیدگی و خطا در پیش‌بینی میشود. روش حذف برگشتی با شناسایی مهم‌ترین متغیرها به ساده‌سازی مدل کمک کرد. نقشه پیش‌بینی شوری با مدل جنگل تصادفی با مشاهدات میدانی تطابق داشت و منطقه بحرانی شوری را به خوبی مشخص نمود. | ||
| کلیدواژه‌ها | ||
| آبیاری جویچه‌ای؛ تغییرات مکانی؛ خصوصیات خاک؛ نسبت طیفی؛ نقشه‌برداری رقومی | ||
| عنوان مقاله [English] | ||
| Soil salinity digital mapping using random forest model in saline lands of Eyvanekey plain | ||
| نویسندگان [English] | ||
| Leila Jahanbazi؛ Ahmad Heidari؛ Mohammad Hosein Mohammadi | ||
| Soil Science Department Faculty of Agriculture,, University of Tehran, Karaj, | ||
| چکیده [English] | ||
| This study aimed to investigate the spatial changes of soil salinity using RF model in a part of Eyvanekey Plain (Semnan Province 2018). Grid sampling with 100 m intervals (106 samples) was taken from 105 ha of soils developed on marl and gravely alluviums. The land uses were pistachio plantations with furrow irrigation and abandoned land. The maximum EC was (173.2 and 34 dS/m) in the abandoned and furrow irrigation pistachio plantations respectively. The main factors of salinization were saline marls, saline irrigation water, and high PET. The R2 for the salinity prediction map by RF model was 0.49, and the most important covariates were normalized difference salinity index (NDSI), topographic wetness index (TWI), Channel Network Base Level (CNBL), normalized difference vegetation index (NDVI), and modified soil vegetation index (SAVI). Spectral ratio indices derived from Landsat 8 contributed the most to the soil salinity prediction. Out of 5 main auxiliary variables, 3 variables are related to spectral ratio indices and the reason was the presence of salt on the soil in the studied area. Using NDVI with other salinity and moisture indices improved the salinity prediction model. Examining the results of covariates correlation and the implementation of recursive feature elimination showed that many covariates increase model complexity and prediction error. Recursive feature elimination helped to simplify the model by identifying the most important covariates. The salinity prediction map by random forest was consistent with the field observations and clearly defined the critical saline area. | ||
| کلیدواژه‌ها [English] | ||
| Digital soil mapping, Furrow irrigation, Soil properties, Spatial changes, Spectral ratio | ||
| مراجع | ||
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