What is wrong with post‐fire soil erosion modelling? A meta‐analysis on current approaches, research gaps, and future directions

• Autor(a) principal: Lopes, A. R.
• Data de Publicação: 2021
• Outros Autores: Girona-García, A., Corticeiro, S., Martins, R., Keizer, J., Vieira, D. C. S.
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10773/29587
• topic: Erosion model; Infiltration; Burn severity; Model efficiency; Meta‐analysis

In the near future, a higher occurrence of wildfires is expected due to climate change, carrying social, environmental, and economic implications. Such impacts are often associated with an increase of post‐fire hydrological and erosive responses, which are difficult to predict. Soil erosion models have been proven to be a valuable tool in the decision‐making process, from emergency response to long‐term planning, however, they were not designed for post‐fire conditions, so they need to be adapted to include fire‐induced changes. In the recent years, there has been an increasing number of studies testing different models and adaptations for the prediction of post‐fire soil erosion. However, many of these adaptations are being applied without field validation or model performance assessment. Therefore, this study aims to describe the scientific advances in the last twenty years in post‐fire soil erosion modelling research and evaluate model adaptations to burned areas that aim to include: i) fire‐induced changes in soil and ground cover, ii) fire‐induced changes in infiltration, iii) burn severity, and iv) mitigation measures in their predictions. This study also discusses the strengths and weaknesses of those approaches, suggests potential improvements, and identifies directions for future research. Results show that studies are not homogeneously distributed worldwide, neither according to the model type used, nor by regions most affected by wildfires. During calibration, 73% of the cases involved model adaptation to burned conditions, and only 21% attempted to accommodate new processes. Burn severity was addressed in 75% of the cases, whilst mitigation measures were simulated in 27%. Additionally, only a minor percentage of model predictions were validated with independent field data (17%) or assessed for uncertainties (13%). Therefore, further efforts are required on the adaptation of erosion models to burned conditions to be widely used for post‐fire management decision.