کد مقاله کد نشریه سال انتشار مقاله انگلیسی ترجمه فارسی نسخه تمام متن
4572818 1332395 2017 5 صفحه PDF ندارد دانلود رایگان
عنوان انگلیسی مقاله
Predicting soil particle density from clay and soil organic matter contents
ترجمه فارسی عنوان
پیش بینی چگالی ذرات تثبیت خاک از خاک رس و مقدار ماده آلی خاک
کلمات کلیدی
چگالی ذرات خاک؛ خاک مواد آلی؛ خشت؛ تابع انتقالی؛ پسرفت
Soil particle density; Soil organic matter; Clay; Pedotransfer function; Regression
موضوعات مرتبط
مهندسی و علوم پایه علوم زمین و سیارات فرآیندهای سطح زمین
چکیده انگلیسی


• Clay and SOM content of the calibration data both influenced particle density (P < 0.0001).
• Clay and sand + silt particles have densities of ~ 2.86 and ~ 2.65 Mg m− 3, respectively.
• Soil particle density can be accurately predicted from clay and SOM contents.

Soil particle density (Dp) is an important soil property for calculating soil porosity expressions. However, many studies assume a constant value, typically 2.65 Mg m− 3 for arable, mineral soils. Few models exist for the prediction of Dp from soil organic matter (SOM) content. We hypothesized that better predictions may be obtained by including the soil clay content in least squares prediction equations. A calibration data set with 79 soil samples from 16 locations in Denmark, comprising both topsoil and subsoil horizons, was selected from the literature. Simple linear regression indicated that Dp of clay particles was approximately 2.86 Mg m− 3, while that of sand + silt particles could be estimated to ~ 2.65 Mg m− 3. Multiple linear regression showed that a combination of clay and SOM contents could explain nearly 92% of the variation in measured Dp. The clay and SOM prediction equation was validated against a combined data set with 227 soil samples representing A, B, and C horizons from temperate North America and Europe. The new prediction equation performed better than two SOM-based models from the literature. Validation of the new clay and SOM model using the 227 soil samples gave a root mean square error and mean error of 0.041 and + 0.013 Mg m− 3, respectively. Predictions were accurate for all levels of SOM content in the validation data set. The model gave very precise predictions for soils with clay contents lower than 0.3 kg kg− 1, while a moderate over-prediction was observed for soils very high in clay. Finally, we developed a texture-enhanced curvilinear model that will be useful for predicting Dp of soils with high contents of clay and in particular SOM.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Geoderma - Volume 286, 15 January 2017, Pages 83–87
نویسندگان
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