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Soil water retention and water flow simulation data

<p>The data is for the manuscript of a paper entitled &quot;<strong>Simulation of water flow and calculation of </strong><strong>the related physical quality indices as influenced by soil water retention curve fitting methods&quot;.</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>

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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