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An Artificial Neural Network to Simulate Surface Runoff and Soil Erosion in Burned Forests

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Intelligent Distributed Computing XIV (IDC 2021)

Part of the book series: Studies in Computational Intelligence ((SCI,volume 1026))

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Abstract

Few experiences of Artificial Neural Networks (ANNs) for hydro-logical predictions in forest soils after wildfire and post-fire treatments are available in literature. To fill this gap, an ANN model has been adapted to predict surface runoff and soil erosion in Mediterranean burned pine forests (Central Spain), and tested against hydro-logical observations at plot scale throughout 2 years. The model gave very accurate runoff and erosion predictions in burned and non-burned soils as well as for all soil treatments (mulching and/or logging or not). Although further experimental tests are needed to validate the ANN applicability to soils in burned and treated forests in other ecosystems, the use of ANN may be useful for landscape planners as decision support system for the integrated assessment and management of forests.

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Author information

Authors and Affiliations

  1. DIMES, University of Calabria, Rende (CS), Italy

    Lidia Fotia

  2. Departamento de Ciencia y Tecnología Agroforestal y Genética, Universidad de Castilla La Mancha, Campus Universitario s/n, C.P. 02071, Albacete, Spain

    Manuel Esteban Lucas-Borja

  3. DIIES, University “Mediterranea”, Reggio Calabria, Italy

    Domenico Rosaci

  4. Department of Psychology, University of Milano Bicocca, Milano (MI), Italy

    Giuseppe M. L. Sarné

  5. Department AGRARIA, University “Mediterranea” of Reggio Calabria, Località Feo di Vito, 89122, Reggio Calabria, Italy

    Demetrio Antonio Zema

Authors
  1. Lidia Fotia
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  2. Manuel Esteban Lucas-Borja
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  3. Domenico Rosaci
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  4. Giuseppe M. L. Sarné
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  5. Demetrio Antonio Zema
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Corresponding author

Correspondence to Demetrio Antonio Zema .

Editor information

Editors and Affiliations

  1. Computer Systems Engineering Department, Universidad Politécnica de Madrid, Madrid, Spain

    David Camacho

  2. DIIES Department, University of Reggio Calabria, Reggio Calabria, Italy

    Domenico Rosaci

  3. Department of Psychology, University of Milan Bicocca, Milan, Italy

    Giuseppe M. L. Sarné

  4. DICEAM Department, University of Reggio Calabria, Reggio Calabria, Italy

    Mario Versaci

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Fotia, L., Lucas-Borja, M.E., Rosaci, D., Sarné, G.M.L., Zema, D.A. (2022). An Artificial Neural Network to Simulate Surface Runoff and Soil Erosion in Burned Forests. In: Camacho, D., Rosaci, D., Sarné, G.M.L., Versaci, M. (eds) Intelligent Distributed Computing XIV. IDC 2021. Studies in Computational Intelligence, vol 1026. Springer, Cham. https://doi.org/10.1007/978-3-030-96627-0_11

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