Updated method to incorporate soil nutrient heterogeneity caused by urine excretion into a process-based simulation model
Pasture production and nutrient cycling through grazed pastures are inherently difficult to model with process-based simulation models. This arises because the urine depositions from grazing livestock create extreme heterogeneity in soil nutrient concentrations and dynamics. They result in relatively small patches of soil with very high mineral nitrogen (N) concentrations with the remainder of the soil with low N concentrations. These variations are such that simply averaging over them will somewhat overestimate pasture production and vastly underestimate environmental losses such as N leaching and greenhouse gas emissions. Explicit representation of the heterogeneity will allow correct simulation of environmental losses, but this comes at the expense of long runtimes in simulations - runtimes that can make the model intractable to use. Here we outline an update to an existing method that preserves the most important part of the heterogeneity while still allowing tractable runtimes for simulations. While we applied this method to grazed pasture systems, it could be extended to other sources of heterogeneity such as spatially variable fertiliser management. A method to model non-uniform applications of nutrients to soils in simulation models Captures the major implications of the non-uniformity on soil and plant processes The method is computationally efficient resulting in tractable simulations.
Authors
- Rogerio Cichota (ORCID: https://orcid.org/0000-0002-1618-986X)
- Dean Holzworth (ORCID: https://orcid.org/0009-0009-5427-2048)
- V. O. Snow
- Olle Hartvigson
Institutions
- Commonwealth Scientific and Industrial Research Organisation (AU)
- Lincoln University (NZ)
- Agriculture and Food (AU)
Publication Details
- Journal
- MethodsX
- Published
- 2026-01-07
- DOI
- https://doi.org/10.1016/j.mex.2026.103790
- Primary Topic
- Soil Carbon and Nitrogen Dynamics
- Type
- article
- Field-Weighted Citation Impact
- 0.00