Post-fire management effects on hillslope-stream sediment connectivity in a Mediterranean forest ecosystem

Forest fires intensify sediment transport and aggravate local and off-site consequences of soil erosion. This study evaluates the influence of post-fire measures on structural and functional sediment connectivity (SC) in five fire-affected Mediterranean catchments, which include 929 sub-catchments, by using the "aggregated index of connectivity" (AIC) at two temporal scenarios: I) immediately after the fire and before implementing post-fire practices ('Pre-man'), and II) two years after the fire ('Post-man'). The latter includes all the emergency stabilization practices, that are hillslope barriers, check-dams and afforestation. The stream system was set as the target of the computation (STR), to be representative of intense rainfall-runoff events with effective sediment delivery outside the catchments. Output normalization (AIC_N) allows comparing the results of the five basins between them. The sedimentological analysis is based on specific sediment yield (SSY) -measured at the check-dams installed after the fire -, and this data is used for output evaluation. Stream density and slope variables were the most influential factors on AIC_N-STR results at the sub-catchment scale. Post-fire hillslope treatments (barriers when built in high densities and afforestation) significantly reduced AIC_N-STR in comparison with untreated areas in both structural and functional approaches. Despite the presence of hillslope treatments, the higher erosive rainfall conditions resulted in higher AIC_N-STR values in the Post-man scenario (functional approach). A positive and good correlation was found between the measured SSY and the AIC_N-STR changes due to the post-fire practices and vegetation recovery, showing the good correspondence of the computation results and the real sediment dynamics of the studied catchments. Overall, AIC_N demonstrated to be a useful and versatile tool for post-fire management, which needs further research to optimize its applicability.