Estimation of soil particle size distribution—From Katchinski to USDA scheme
- 10.2991/ifeesm-17.2018.176How to use a DOI?
- Particle size distribution; soil texture; Sichuan basin.
For better use of soil particle size distribution (PSD) models and expand the use of large database held by national Soil Surveys (Katchinski's scheme) in China, 12 PSD models were proposed as the function of cumulative mass percentage of particles and diameter (mm) for 265 soil horizons (Katchinski's scheme) in a broader soil particle-size ranges, and together with 3 commonly used interpolations were validated to estimate the PSDs of USDA system especially particles <0.002mm and 0.02mm for other 49 soil horizons. The adjusted coefficient of determination (Adj. R2) and the Akaike's information criterion (AIC) were used to compare the quality of 12 numerical model fits. The ExpA and ExpD models with five parameters and Logistic model with four parameters showed relatively better performance. Correlation coefficient (r), absolute error (AE, %), and root mean square deviation (RMSD) were used to test the validation of the PSD models and interpolations on the soil particles <0.002 and 0.02mm, respectively. And it was noteworthy that the RMSDs yielded from interpolations were much larger than 12 models. Interpolations did not show any superiority towards numerical functions at particles <0.002 mm. Cubic spline interpolation performed worst with mean AE of 20% at particles <0.02 mm. This result suggested that the cubic spline interpolation could not use to estimate the soil particles <0.02 mm for Sichuan basin soil.
- © 2018, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Mao-Fen Li AU - Wei Wu AU - Hong-Bin Liu PY - 2018/02 DA - 2018/02 TI - Estimation of soil particle size distribution—From Katchinski to USDA scheme BT - Proceedings of the 2017 3rd International Forum on Energy, Environment Science and Materials (IFEESM 2017) PB - Atlantis Press SP - 940 EP - 946 SN - 2352-5401 UR - https://doi.org/10.2991/ifeesm-17.2018.176 DO - 10.2991/ifeesm-17.2018.176 ID - Li2018/02 ER -