A semi-mechanistic model for predicting daily variations in species-level live fuel moisture content

Balaguer-Romano, Rodrigo . (2022) A semi-mechanistic model for predicting daily variations in species-level live fuel moisture content. Agricultural and Forest Meteorology, vol. 323, (2022) 109022

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Título A semi-mechanistic model for predicting daily variations in species-level live fuel moisture content
Autor(es) Balaguer-Romano, Rodrigo
Materia(s) Física
Abstract Live Fuel Moisture Content (LFMC) is one of the main factors affecting forest ignitability as it determines the availability of existing live fuel to burn. Currently, LFMC is monitored through spectral vegetation indices or inferred from meteorological drought indices. While useful, neither approach provides mechanistic insights into species-specific LFMC variation and they are limited in the ability to forecast LFMC under altered future climates. Here, we developed a semi-mechanistic model to predict daily variation in LFMC across woody species from different functional types by adjusting a soil water balance model which estimates predawn leaf water potential (Ψpd). Our overarching goal was to balance the trade-off between biological realism, which enhances model applicability, and parameterization complexity, which may limit its value within operational settings. After calibration, model predictions were validated against a dataset comprising 1659 LFMC observations across peninsular Spain, belonging to different functional types and from contrasting climates. The overall goodness of fit for our model (R2 = 0.5) was better than that obtained by an existing models based on drought indices (R2 = 0.3) or spectral vegetation indices (R2 = 0.1). We observed the best predictive performance for seeding shrubs (R2 = 0.6) followed by trees (R2 = 0.5) and resprouting shrubs (R2 = 0.4). Through its relatively simple parameterization, the approach developed here may pave the way for a new generation of process-based models that can be used for operational purposes within fire risk mitigation scenarios.
Palabras clave wildfire
fire behaviour
drought stress
drought Code
remote sensing
Editor(es) Elsevier
Fecha 2022
Formato application/pdf
Identificador bibliuned:DptoFMyF-FCIE-Articulos-Rbalaguer-0001
DOI - identifier https://doi.org/10.1016/j.agrformet.2022.109022
ISSN - identifier 0168-1923
Nombre de la revista Agricultural and Forest Meteorology
Número de Volumen 323
Publicado en la Revista Agricultural and Forest Meteorology, vol. 323, (2022) 109022
Idioma eng
Versión de la publicación acceptedVersion
Tipo de recurso Article
Derechos de acceso y licencia http://creativecommons.org/licenses/by-nc-nd/4.0
Tipo de acceso Acceso abierto
Notas adicionales This is the Accepted Manuscript of an article published by ELSEVIER in "Agricultural and Forest Meteorology" on 15 August 2022, available online: https://doi.org/10.1016/j.agrformet.2022.109022
Notas adicionales Este es el manuscrito aceptado de un artículo publicado por ELSEVIER en "Agricultural and Forest Meteorology" el 15 Agosto 2022, disponible en línea: https://doi.org/10.1016/j.agrformet.2022.109022

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Creado: Thu, 16 Jun 2022, 18:37:19 CET