Forest composition effect on wildfire pattern and run-off regime in a Mediterranean watershed

Noa Ohana-Levi, Amir Givati, Tarin Paz-Kagan, Arnon Karnieli

Research output: Contribution to journalArticlepeer-review

4 Scopus citations


Fire may alter land cover throughout the landscape and affect run-off responses to rainfall events in a burnt watershed. Therefore, the challenge is to understand the interactions between forest composition and fire patterns in a karstic, Mediterranean watershed that affects the run-off regime. The aim of this research is to improve the understanding of the interactive effects of wildfire and land-cover change on the rainfall–run-off relationship in a first-order watershed. To achieve this goal, satellite imagery, official spatial data, and hydrological modelling were used to study forest composition in relation to extreme fire and to simulate run-off response for 2 rainfall events. The results show that an extreme wildfire had a greater impact on planted forest, composed mostly of pines, than on native species. Additionally, it was found that the land-cover alternation due to fire affected the run-off regime and contributed to an increase in maximum discharge and run-off volume for the 2 rainfall events by ~39–47%. During the regeneration period, the run-off response for the 2 rainfall events decreased by ~7.7–9%. Wildfires may impact the run-off response more profoundly as the plantation of pine trees increases. A greater increase in run-off response may endanger infrastructure in terms of flooding and affect the population well-being. Watershed management in areas where afforestation is considered should focus on planting native species that are less flammable rather than introducing combustible pines, thus reducing the hydrologic impacts of land-cover alteration due to wildfire, especially when climate warms and wildfires become more frequent and intense.

Original languageEnglish
Article numbere1936
Issue number4
StatePublished - 1 Jun 2018


  • forest fire
  • hydrological model
  • land-cover change
  • remote sensing


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