Testing simple approaches to map sediment mobilization hotspots after wildfires

The models currently used to predict post-fire soil erosion risks are limited by high data demands and long computation times. An alternative is to map the potential hydrological and sediment connectivity using indices to express the general properties of the landscape under evaluation and map the possible connectivity between the different parts of a catchment.

In this study, we aim to answer the question: Do these alternative approaches identify post-fire sediment mobilization hotspots?  To achieve this, we assess the spatial variability distribution of the location of soil erosion hotspots using the Index of Connectivity (IC), Revised Universal Soil Loss Equation (RUSLE model) and the Sediment Export (SE) and compare it to the simulation results of a more complex Landscape Evolution Model (LAPSUS model). Additionally, we evaluate statistical measures of association between the four tools. Furthermore, IC, RUSLE model and SE are used due to their simplistic representation of erosion and ease of application, and the LAPSUS model is used as the best representation of erosion and sediment transport in the study area.

Our results show that the three tools (IC, RUSLE model and SE) tested in this study are suitable for identifying sediment mobilization hotspots, i.e., areas where the erosion rates are above the 90^th percentile, in recently burnt areas, and differences between their performance are minor. These findings can be considered for post-fire and water contamination risk management, especially for fast prioritization of areas needing emergency post-fire intervention.