# 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
Therefore, for all the experiments steady-state infiltration rates (\(i_{\text{s}}\)) were always reached before the end of the runs and after that the influence of hydrophobicity had ceased, so the \(K_{\text{s}}\) values estimated by the use of the SSBI method could be always properly estimated considering the last data points of the infiltration curves. Limiting the hydraulic characterization to the stabilized phase avoided the uncertainties due to specific shape of the cumulative infiltration and a no clear distinction between the early- and late-time infiltration process because soil hydrophobic phenomena [58]. In other words, the results presented in this study suggest that if hydrophobicity affects the first stage of a Beerkan infiltration test, the SSBI estimates should characterize the hydraulic property of the soil properly. We believe that this result has practical importance because the use the SSBI method allowed us to maintain the integrity of the dataset, and to compare the hydraulic behavior of different sites with different land uses, where soil hydrophobicity only occurs in some circumstance. Moreover, maintaining a small water head on the soil surface may be useful to study the infiltration process in macroporous repellent soils [48]. The SSBI method, covering the soil surface with a practically null depth of water, hence, lower than the commonly water-entry values for repellent soils [59], could allow the operator to characterize water infiltration occurring through either structural or other gaps in the water repellent layer or as fingered flow through zones of hydrophilic or less water repellent soil [60]. On the contrary, establishing several cm of ponded head of water on the infiltration surface is expected to overwhelm SWR [61]. In this investigation, the detection of hockey-stick-like shapes  
Figure 5: Comparison between the water drop penetration time, WDPT (s), and the failure rate of the BEST-steady algorithm (%). The picture represents water droplets resisting infiltration into forest soil due to the water repellency. suggested that maintaining a small water head on the soil surface helped to prevent excessive positive pressure from overcoming SWR [62], and allowed the detection of water repellency. Lower SWR was detected in wetter soils. The correlation between \(\theta_{i}\) and ln(WDPT) was significant (\(r=-0.67\), \(p=0.002\)) (Table 2). This result was in line with the reasoning that the soil water content governs the interaction between soil particles and amphiphilic organic molecules, resulting from degradation of tree tissues, that coat soil particles and may be responsible for SWR [45]. The transition from wettable to hydrophobic status (and vice versa) is generally associated to a critical range of soil moisture [63]. The lower water content of this range defines the condition below which the medium is water repellent, the higher identifies the condition above which the medium is wettable. \(K_{s}\) data were positively correlated to ln(WDPT). This is logical, since both macropore flow (which affects the magnitude of \(K_{s}\)) and water repellency phenomena were relevant at the remnant forest plots. In brief, the correlation between these two variables is not the result of a causal connection but the concomitancy of two processes: hydrophobia and macropore flow, which also lead to mainly subcritical water repellency. In addition, we conclude that hydrophobia had no effect on the estimation of the saturated hydraulic conductivity. Indeed, in opposite case, \(K_{sS}\) and ln(WDPT) would have a negative correlation. Consequently, we assumed that the SSBI method proved efficient for detecting SWR and estimating properly the soil saturated hydraulic conductivity, at the same time. Lastly, \(K_{sB}\) and \(K_{sS}\) had a positive correlation with a value close to unity. The two estimators provide close estimates, as discussed above with the FoD.