Soil erosion modelling of burned and mulched soils following a Mediterranean forest wildfire. (7th February 2023)

• Record Type: Journal Article
• Authors: Gonzalez‐Romero, Javier; Zema, Demetrio Antonio; Carrà, Bruno Gianmarco; Neris, Jonay; Fajardo, Alvaro; Plaza‐Álvarez, Pedro Antonio; Moya, Daniel; Peña‐Molina, Esther; de las Heras, Jorge; Lucas‐Borja, Manuel Esteban
• Is Part Of: Soil use and management. Volume 39:Number 2(2023)
• Page Start: 881
• Page End: 899
• Publication Date: 2023-02-07
• Subjects: calibration -- erosion model -- event scale -- plot scale -- postfire management -- soil loss; Soil management -- Periodicals; 631.4
• DOI: 10.1111/sum.12884
• Languages: English
• ISSNs: 0266-0032

Abstract

Abstract: Soil erosion modelling applied to burned forests in different global regions can be unreliable because of a lack of verification data. Here, we evaluated the following three erosion models: (1) Water Erosion Prediction Project (WEPP), (2) Morgan‐Morgan‐Finney (MMF) and (3) Universal Soil Loss Equation‐Modified (USLE‐M). Using field plots that were either untreated or mulched with straw, this study involved observations of soil loss at the event scale at a burned pine forest in Central Eastern Spain. The erosion predictions of the three models were analysed for goodness‐of‐fit. Optimization of the MMF model with a new procedure to estimate the C‐factor resulted in a satisfactory erosion prediction capacity in burned plots with or without the mulching treatment. The WEPP model underestimated erosion in the unburned areas and largely overestimated the soil loss in burned areas. The accuracy of soil loss estimation by the USLE‐M model was also poor. Calibration of the curve numbers and C‐factors did not improve the USLE‐M model estimation. Therefore, we conclude that an optimized MMF model was the most accurate way to estimate soil loss and recommend this approach for in Mediterranean burned forests with or without postfire mulching. This study gives land managers insight about the choice of the most suitable model for erosion predictions in burned forests.