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Comparing different application procedures of the water drop penetration time test to assess soil water repellency in a fire affected Sicilian area

  • Autori: Tinebra, Ilenia; Alagna, Vincenzo; Iovino, Massimo; Bagarello, Vincenzo*
  • Anno di pubblicazione: 2019
  • Tipologia: Articolo in rivista (Articolo in rivista)
  • Parole Chiave: Field sampling; Small-scale spatial variability; Soil hydrophobicity; Water drop penetration time test; Earth-Surface Processes
  • OA Link:


The Water Drop Penetration Time (WDPT) technique was applied in two subsequent years (2016 and 2017) to check surface soil water repellency (SWR) in a Sicilian mountain area affected by a wildfire on June 2016. A total of 93 sites were sampled and from 3 to 100 droplets were used to characterize a site. The detected SWR varied with the severity of the wildfire, being practically absent in the unburnt control area and slight to extreme in the burnt areas. The percentage of extremely repellent sites increased with wildfire severity. SWR vanished one year after the passage of the fire in sites where fire severity was moderate but it persisted in the case of a severe wildfire. In general, the number of applied droplets at a site (from 3 to 100) and the SWR classification methodology (modal class, mean of the measured WDPTs) did not have a strong impact on SWR assessment. However, the data collected with the first few droplets (i.e. three or four) could help to make choices about the number of droplets to be used to reliably characterize a site. If all the initially used droplets give clear signals of wettable conditions, it is plausible to believe that a small number of droplets will be enough to characterize the site. If signs of water repellency are detected, then it could be advisable to use larger samples sizes. Complementing a detailed information on the spatial distribution of wildfire severity with a WDPT experiment appears appropriate to establish where fire mitigation techniques should promptly be implemented after the fire. Experimental developments with larger databases are advisable to improve our ability to capture spatial and temporal variability of SWR.