Soil water retention and water flow simulation data
<p>The data is for the manuscript of a paper entitled "<strong>Simulation of water flow and calculation of </strong><strong>the related physical quality indices as influenced by soil water retention curve fitting methods".</strong></p> <p>Accurate fitting of soil water retention curve (SWRC) parameters is crucial in the modeling of soil water flow and the assessment of soil quality. The un-weighted least squares regression (ULS) is the most common approach applied for fitting the SWRC functions to the observed data-points in order to optimize their parameters. However, the variance of SWRC data varies in different water contents; therefore, unlike the wet-end of the SWRC, the ULS method may not be sufficiently effective in estimating its dry-end. This study examined the differences between parameter approximations achieved by the ULS and the weighted least-squares (WLS) in the SWRC. Then, an analysis of both approaches in the simulation of water redistribution and the related soil physical quality indicators (SPQIs) was done. Accordingly</p>
ShareScore
32/100
Overall dataset sharing score
Score breakdown
These five areas show where the dataset supports — or may limit — practical reuse.
- Stewardship
- 4
- Harmonization
- 4
- Access
- 16
- Reuse readiness
- 8
- Engagement
- 0