# Assessing Water Infiltration and Soil Water Repellency in Brazilian Atlantic Forest Soils
## 3 Results and Discussion
### Comparing BEST versus SSBI Estimates Under Soil Water Repellency Conditions  
BEST-steady failed to estimate \(K_{s}\) in case of convex-shaped cumulative infiltration curves, which led to negative \(b_{s}\) values and consequently to null \(K_{sB}\). The \(K_{sB}\) data ranged between 4.5 and 1394 mm h\({}^{-1}\) (almost three orders of magnitude). The BEST-steady algorithm yielded physically plausible estimates (i.e., positive \(K_{s}\) values) for 108 of 126 infiltration runs (i.e., 85.7% of cases). The percentage of successful runs was of 95.2% both for the pasture and restored forest (40 of 42 runs). With reference to the remnant forest, BEST led to a failure rate value of 33.3%, leading to lacks of estimates for 14 of 42 infiltration runs. In these cases, cumulative infiltration curves had convex shapes, which are typical for hydrophobia i.e., [42; 45; 46]. Such hydrophobia may result from significant amounts of organic matter content i.e., [52; 53; 54], originating from fauna and flora activities [55]. Soil texture also plays a major role on SWR, in particular, SWR is expected to increase for decreasing clay content. In this sense, our plots (i.e., F5U, R3U, R3D, P1M) with more sand content exhibited higher WDPT values. On the other hand, for the forest plots (i.e., F6U, F6M, F6D) the significant amounts of organic matter had a main role in generating relevant WDPT values also on finer textured soils [23; 56]. The BEST-steady algorithm was unable to provide positive \(K_{s}\) values, showing that BEST can only be used when the soil does not exhibit hydrophobic effect, as suggested by [PERSON] et al. [57]. As shown in Figure 5, at increasing failure rates of the BEST method corresponded higher WDPT values, suggesting that where hydrophobic condition occurred, mainly in the remnant forest plots, it was the main cause of failure of BEST-steady. More specifically, BEST-steady requires both the slope  
Figure 4: Empirical cumulative distribution function plot of the factors of difference between the saturated soil hydraulic conductivity values estimated by the BEST -steady (\(K_{sB}\)) and SSBI methods (\(K_{sS}\)). \(K_{sS}\) data were estimated considering \(\lambda_{c}\) = 83 mm (blue solid line) and the mean \(\lambda_{c}\) values estimated for each sampled plot from the MDI experiments carried out with a suction of 0 and \(-\)20 mm (red dashed line). and the intercept of regression line fitted to the last data points on the \(I\) vs. \(t\) plot. The magnitude of b\({}_{\text{s}}\) depends on the entire cumulative infiltration curve (including the transient phase) [58; 59], therefore that term is sensitive to SWR that impedes the early wetting phase of the infiltration process. When soil hydrophobicity occurred, the \(I\) vs. \(t^{0.5}\) plot exhibited the characteristic \"hockey-stick-like\" shape [46], hiding the estimation of \(K_{\text{s}}\) trough BEST-steady [42]. On the other hand, SSBI differs by the term expressing steady-state condition, considering exclusively the final infiltration rate [13]. The exclusive use of this term allowed to consider only the final stage of the infiltration process, i.e., when the hydrophobicity effect on infiltration was diminished. In this investigation eighteen Beerkan infiltration tests exhibited a clear hockey-stick-like shape, mainly at the remnant forest plots, that allowed calculation of WRCT as the intersection point of two straight lines, representing the initial and the late stages of \(I\) vs. \(t^{0.5}\) relationships [45] (Figure 2b). Table 1 shows the results of the WRCT and the equilibration time calculations. Water repellency always affected the very early stage of the infiltration process since the WRCT values raged between 14 and 93 s, and they were always lower than the \(t_{\text{s}}\) values.