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首页> 外文期刊>Environmental research >Predicting the effectiveness of different mulching techniques in reducing post-fire runoff and erosion at plot scale with the RUSLE, MMF and PESERA models
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Predicting the effectiveness of different mulching techniques in reducing post-fire runoff and erosion at plot scale with the RUSLE, MMF and PESERA models

机译：使用RUSLE，MMF和PESERA模型预测不同覆盖技术在减少样地尺度上的火灾后径流和侵蚀方面的有效性

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摘要

Wildfires have become a recurrent threat for many Mediterranean forest ecosystems. The characteristics of the Mediterranean climate, with its warm and dry summers and mild and wet winters, make this a region prone to wildfire occurrence as well as to post-fire soil erosion. This threat is expected to be aggravated in the future due to climate change and land management practices and planning.The wide recognition of wildfires as a driver for runoff and erosion in burnt forest areas has created a strong demand for model-based tools for predicting the post-fire hydrological and erosion response and, in particular, for predicting the effectiveness of post-fire management operations to mitigate these responses.In this study, the effectiveness of two post-fire treatments (hydromulch and natural pine needle mulch) in reducing post-fire runoff and soil erosion was evaluated against control conditions (i.e. untreated conditions), at different spatial scales.The main objective of this study was to use field data to evaluate the ability of different erosion models: (i) empirical (RUSLE), (ii) semi-empirical (MMF), and (iii) physically-based (PESERA), to predict the hydrological and erosive response as well as the effectiveness of different mulching techniques in fire-affected areas.The results of this study showed that all three models were reasonably able to reproduce the hydrological and erosive processes occurring in burned forest areas. In addition, it was demonstrated that the models can be calibrated at a small spatial scale (0.5 m(2)) but provide accurate results at greater spatial scales (10 m(2)).From this work, the RUSLE model seems to be ideal for fast and simple applications (i.e. prioritization of areas-at-risk) mainly due to its simplicity and reduced data requirements. On the other hand, the more complex MMF and PESERA models would be valuable as a base of a possible tool for assessing the risk of water contamination in fire-affected water bodies and for testing different land management scenarios.
机译：野火已成为许多地中海森林生态系统的经常性威胁。地中海气候的特点是夏季温暖干燥，冬季温和潮湿，这使得该地区易于发生野火以及发生火后土壤侵蚀。由于气候变化以及土地管理实践和规划，这种威胁预计将在未来加剧。野火被广泛认为是烧毁森林地区径流和侵蚀的驱动力，因此对基于模型的工具进行预测的需求很大。火灾后的水文和侵蚀响应，特别是用于预测火灾后管理操作减轻这些响应的有效性。在这项研究中，两种火灾后处理（水覆盖和天然松针覆盖）在减少灾后影响方面的有效性在不同的空间尺度上对照控制条件（即未经处理的条件）评估了火灾径流和土壤侵蚀。本研究的主要目的是利用田间数据评估不同侵蚀模型的能力：（i）经验（RUSLE）， （ii）半经验（MMF）和（iii）物理（PESERA），以预测冷杉的水文和侵蚀响应以及不同覆盖技术的有效性这项研究的结果表明，所有这三个模型都能够合理地再现烧毁森林地区发生的水文和侵蚀过程。此外，已证明可以在较小的空间比例（0.5 m（2））上校准模型，但在较大的空间比例（10 m（2））上可以提供准确的结果。从这项工作来看，RUSLE模型似乎是主要由于其简单性和减少的数据需求，因此是快速和简单应用程序（即高风险区域的优先级）的理想选择。另一方面，更复杂的MMF和PESERA模型作为评估可能受火灾影响的水体中水污染风险和测试不同土地管理方案的可能工具的基础将很有价值。

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  • 来源
    《Environmental research》 |2018年第8期|365-378|共14页
  • 作者

    Vieira D. C. S.; Serpa D.; Nunes J. P. C.; Prats S. A.; Neves R.; Keizer J. J.;

  • 作者单位

    Univ Aveiro Ctr Environm & Marine Studies CESAM Dept Environm & Planning P-3810193 Aveiro Portugal|Univ Lisbon Inst Super Tecn MARETEC Av Rovisco Pais P-1049001 Lisbon Portugal;

    Univ Aveiro Ctr Environm & Marine Studies CESAM Dept Environm & Planning P-3810193 Aveiro Portugal;

    Univ Lisbon Fac Ciencias Ctr Ecol Evolut & Environm Changes P-1749016 Lisbon Portugal;

    Univ Lisbon Inst Super Tecn MARETEC Av Rovisco Pais P-1049001 Lisbon Portugal;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Modelling; Soil erosion; Post-fire; Land management; Mitigation;

    机译：造型;水土流失;射击后土地管理;减轻;

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