Centro de Investigación Forestal de Lourizán, Consellería do Medio Rural, Xunta de Galicia, P.O. Box. 127, 36080 Pontevedra, Spain.
Centro de Investigación Forestal de Lourizán, Consellería do Medio Rural, Xunta de Galicia, P.O. Box. 127, 36080 Pontevedra, Spain.
Environ Res. 2018 Aug;165:279-285. doi: 10.1016/j.envres.2018.04.008. Epub 2018 May 7.
Severe fire greatly increases soil erosion rates and overland-flow in forest land. Soil erosion prediction models are essential for estimating fire impacts and planning post-fire emergency responses. We evaluated the performance of a) the Revised Universal Soil Loss Equation (RUSLE), modified by inclusion of an alternative equation for the soil erodibility factor, and b) the Disturbed WEPP model, by comparing the soil loss predicted by the models and the soil loss measured in the first year after wildfire in 44 experimental field plots in NW Spain. The Disturbed WEPP has not previously been validated with field data for use in NW Spain; validation studies are also very scarce in other areas. We found that both models underestimated the erosion rates. The accuracy of the RUSLE model was low, even after inclusion of a modified soil erodibility factor accounting for high contents of soil organic matter. We conclude that neither model is suitable for predicting soil erosion in the first year after fire in NW Spain and suggest that soil burn severity should be given greater weighting in post-fire soil erosion modelling.
严重的火灾会大大增加林地的土壤侵蚀率和地表径流量。土壤侵蚀预测模型对于估算火灾影响和规划灾后应急响应至关重要。我们通过比较模型预测的土壤流失量和西班牙西北部 44 个实验性实地观测点火灾后第一年的土壤流失量，评估了 a) 修订后的通用土壤流失方程（RUSLE）和 b) 受干扰 WEPP 模型的性能。受干扰 WEPP 模型以前没有使用西班牙西北部的野外数据进行验证；其他地区的验证研究也非常稀缺。我们发现，两个模型都低估了侵蚀率。即使在纳入了考虑到土壤有机质含量高的修正土壤可蚀性因子后，RUSLE 模型的准确性仍然较低。我们的结论是，这两个模型都不适合预测西班牙西北部火灾后第一年的土壤侵蚀，建议在火灾后的土壤侵蚀建模中给予土壤燃烧严重程度更大的权重。
