What does this research mean for the field?

A modified three-dimensional van Genuchten model that incorporates a nonlinear organic content function applied to residual and saturated water contents accurately predicts continuous soil water retention characteristics across varying organic amendment levels. Novelty: ClaimNovelty.METHODOLOGICAL. Consensus alignment: ConsensusAlignment.NEUTRAL.

What question did this study set out to answer?

This research aims to develop a modified model for soil water retention characteristics using organic material amendments.

May 19, 2026

Modeling the Impacts of Amended Organic Material on Soil Water Retention Using a Generalized van Genuchten Framework

Puntos clave

This research aims to develop a modified model for soil water retention characteristics using organic material amendments.
Introduced a novel unified soil water retention model by modifying the van Genuchten equation.
Conducted laboratory experiments to create soil moisture–pressure head datasets for varying organic content levels (0% to 80%).
Utilized a genetic algorithm for model parameter estimation and calibration for the modified VGOC model.
The best-performing model configuration used a nonlinear organic content function, yielding continuous SWRCs.
Generated a generalized equation VGOC(θ-h-OC) capable of representing soil water retention across all organic amendment levels.
Demonstrated strong model performance across different organic content levels, confirming its applicability and robustness.

Resumen

In the eco-scientific interaction between soil and water, the organic material acts as a vital catalyst in shaping the soil water retention (SWR) characteristics and fulfilling the requirements of sustainable agricultural systems. To understand the behavior of SWR curves (SWRCs) under varying organic content (OC), a novel unified SWR model is introduced by modifying the widely adopted van Genuchten (VG) equation. An assortment of functions of OC (f(OC|A,B),A,B as function constants) is introduced in the original VG framework as multiplicative factors to the original VG-model parameters (θr, θs, α, n); thereby converting the existing two-dimension model, VG(θ,h|θr,θs,α,n) to a three-dimensional OC-incorporated VG-model, VGOC(θ,h,OC|A,B). Forty different configurations of VGOC models are created by incorporating f(OC) and providing the original VG parameters of the native soil as inherent inputs to the VGOC model, which are subsequently utilized for generating a family of SWRCs. Laboratory experiments are conducted to generate the soil moisture–pressure head (θ-h) dataset for soil samples amended with different organic content (0% to 80% by weight) utilizing the pressure plate apparatus. For model calibration, genetic algorithm is employed to estimate the model parameters, resulting in a generalized VGOC(θ-h-OC) equation for any amendment level in the native soil. Model performance evaluation indicates that the configuration where a nonlinear OC-function (f(OC)=1+A×OCB) multiplies with θr and θs yields the best representative family of SWRCs across all the organic amendment levels in soil. The major contribution of the study is the modified VGOC equation that is capable of producing the continuous variation of θ-h-OC values with a generalized VGOC(θ-h-OC) relationship, which was previously discrete in the third dimension (along OC). Furthermore, the methodology is illustrated on various similar studies and it performed proficiently, thereby demonstrating the robustness, applicability, and compactness of the proposed three-variable VGOC(θ,h,OC) model for organically amended soils.

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Cite This Study

Amberia et al. (Sun,) studied this question.

synapsesocial.com/papers/6a0bfe2d166b51b53d37977d https://doi.org/https://doi.org/10.1061/jhyeff.heeng-6711

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