Evaluation of particle size distribution models across various soil textures in Nashik district

Abstract

Accurate modeling of particle size distribution (PSD) is essential for understanding soil hydraulic properties and optimizing land management practices. This study evaluates the applicability of four PSD models—Fredlund et al. (2000), Skaggs et al. (2001), Fooladmand et al. (2004), and the Gray model (1,1) (Wu et al., 2009)—to describe PSD in diverse soil textures of Nashik district, Maharashtra, India. A total of 34 soil samples were collected across different soil textures, including clay, clay loam, sandy clay loam, and sandy loam. The PSD data were analyzed using conventional methods and fitted to the selected models. The performance of these models was assessed using statistical indicators such as root mean square error (RMSE), coefficient of determination (R²), adjusted R² (Adj R²), Akaike’s information criterion (AIC), mean absolute error (MAE), mean absolute percentage error (MAPE), and chi-square (χ²). The results indicated that the Fredlund model consistently outperformed the others, particularly for clay, sandy clay loam, and sandy loam soils, with the lowest RMSE, MAPE, and AIC values. The Gray model (1,1) showed the best performance for clay loam and sandy clay loam soils. The Skaggs and Fooladmand models demonstrated lower accuracy across the soil types tested. These findings highlight the superiority of the Fredlund model for accurate PSD predictions in the region, suggesting its potential for improving soil management strategies in diverse agro-ecological zones.