Climate-driven soil suction variation using a natural-order Fourier series approach

In unsaturated soil practice, the near-ground-surface moisture flow is commonly evaluated using 1-dimensional (1D) suction diffusion equation. This study presents application of a Natural-Order Fourier Series (NOFS) approach for representing monthly climate-driven variations near ground surface, which boundary condition that generally difficult to adequately model. The NOFS incorporates an algorithmic selection criterion optimize order series improve capture seasonal shifts and extreme climate periods, while maintaining acceptable computation efficiency. climate-soil interaction expressed published empirical relationships between rainfall, temperature, index properties. An example validation proposed presented measured properties historical weather data at site in Denver, Colorado USA. Key findings from performance stability studies five locations United States associated with differing regions are discussed. Limitations recommendations implementation also included. capturing changes surface can be efficiently implemented numerical analyses governed by moisture-dependent mechanical behavior help time, stability, stochastic simulations.