Includes four functions: RFactor_calc(), RFactor_est(), KFactor() and SoilLoss(). The rainfall erosivity factors can be calculated or estimated, and soil erodibility will be estimated by the equation extracted from the monograph. Soil loss will be estimated by the product of five factors (rainfall erosivity, soil erodibility, length and steepness slope, cover-management factor and support practice factor. In the future, additional functions can be included. This efforts to advance research in soil and water conservation, with fast and accurate results.

A collection of functions for reading soil data from U.S. Department of Agriculture Natural Resources Conservation Service (USDA-NRCS) and National Cooperative Soil Survey (NCSS) databases.

Function for the computation of fractal dimension based on mass of soil particle size distribution by Tyler & Wheatcraft (1992) <doi:10.2136/sssaj1992.03615995005600020005x>. It also provides functions for calculation of mean weight and geometric mean diameter of particle size distribution by Perfect et al. (1992) <doi:10.2136/sssaj1992.03615995005600050012x>.

Implements a physics-informed one-dimensional convolutional
    neural network (CNN1D-PINN) for estimating the complete soil water
    retention curve (SWRC) as a continuous function of matric potential,
    from soil texture, organic carbon, bulk density, and depth.
    The network architecture ensures strict monotonic decrease of
    volumetric water content with increasing suction by construction,
    through cumulative integration of non-negative slope outputs
    (monotone integral architecture). Four physics-based residual
    constraints adapted from Norouzi et al. (2025) <doi:10.1029/2024WR038149>
    are embedded in the loss function: (S1) linearity at the dry end
    (pF in [5, 7.6]); (S2) non-negativity at pF = 6.2;
    (S3) non-positivity at pF = 7.6; and (S4) a near-zero derivative
    in the saturated plateau region (pF in [-2, -0.3]). Includes tools
    for data preparation, model training, dense prediction, performance
    metrics, texture classification, and publication-quality visualisation.