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Title: D3.3.2 / deliverable
Language: English
Description: The first stage of the fuel database is presented.
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Title: Monitoring Forests at the Management Unit Level for Fire Prevention and Control (FIREGUARD) / FIREGUARD
Language: English
Description: The project addresses fire prevention and control in the Mediterranean region. The main focus is on long-term fire prevention. Fire prevention, pre-suppression, and suppression all require information on fuel characteristics (e.g. composition, structure, spatial distribution), infrastructure, and terrain (topography). This information is designed for the district and sector forest unit level but is capable of being integrated to higher levels, as necessary. An Internet application to assist forest managers in long-term fire prevention management was created.The project finished and ran from 2002 to 2005.
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Title: PiroPinus version 2.0 /
Language: English
Description: PiroPinus is a prescribed burning guide for maritime pine (Pinus pinaster) stands in the form of a spreadsheet, conceived for operational use in the planning and evaluation of hazard reduction burns in natural fuels, i.e. slash from pruning or thinning is not present. It can also be used as a research tool for fire modelling purposes. Potential users are urged to try the guide in other medium- to long-needled pines (P. pinea, P. canariensis, P. radiata, P. nigra, P. halepensis), especially when the understorey is composed of Mediterranean-type species. PiroPinus is a all-in-one user-friendly tool that integrates models based on observed, real-world, fire behaviour and effects. Unlike other available tools, PiroPinus has the ability to: 1. Reflect local stand and fuel conditions in the output; 2. Assess the likelihood of sustained fire spread and quantify marginal burning conditions. Fire modelling systems using properly developed custom fuel models can be used to obtain accurate estimates of fire behaviour. However, such systems perform poorly at the high-end of the moisture content range and are not able to produce site-specific estimates. PiroPinus is composed of several interrelated or stand-alone worksheets for distinct objectives: (1) FUEL. Data entry of basic fuel and stand descriptors to assess fuel load and fire behaviour and effects; (2) RX WIN. Prescription window (general burning conditions); (3) RX DEV. Prescription development, the definition of burning conditions to avoid undesired fire impacts on trees and the forest floor; (4) MOIST. Fuel moisture content, to estimate the moisture contents of surface fine dead fuels and decomposing litter; (5) FIRE. Ignition and fire behaviour, to assess the likelihood of fire spread and quantify fire characteristics; (6) IGN PLAN. Assessment and optimization of area treatment rate; (7) TREES. Fire impact on trees, to assess canopy damage and mortality; (8) FUEL DYN. Fuel dynamics, to estimate fuel consumption and post-burn accumulation; (9) POST-FIRE. Post-burn assessment of fire behaviour and effects; (10) WEATH. Wind speed estimation and Canadian Forest Fire Danger Rating System (for regional planning).
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Title: D3.1-2a Review of knowledge gaps and proposal for fuel data collection and test runs /
Language: English
Description: A review of the different aspects of fuel moisture research was conducted. The following knowledge (research) gaps can be identified: (a) The horizontal spatial variability of dead fuel moisture in relation to vegetation (e.g., stand structure, crown closure, stem density, litter and duff depth, etc.) and topographic characteristics (aspect, slope, soil depth and type, etc.) needs to be measured and modelled in the field. (b) The temporal (diurnal and seasonal) variation in dead and live fuel moisture content as related to changes in meteorological parameters (air relative humidity and temperature, insolation and cloudiness, wind speed and duration, etc) needs to be measured in the field for all the dominant Mediterranean fuel types at the species level, to the extent possible. For fire-stricken geographical regions of the Mediterranean Basin, extensive data bases of seasonal fuel moisture data per species or fuel type must be created and, subsequently, converted through statistical analysis to empirical models of fuel moisture prediction, refined for every species or fuel complex. (c) Equilibrium moisture content (EMC) sorption (adsorption and desorption) curves of dead fuels as a function of air relative humidity and temperature need to be created for the fuels of all the dominant species. (d) The fuel moisture timelag (TL) concept needs to be reassessed and measured in dead fuels from different species in relation to the fuel moisture sorption phase (adsorption or desorption), in order to account for the moisture hysteretic effects of dead fuels during the wetting or drying process. (e) A physical model that predicts canopy (crown) live fuel moisture content variations in terms of stand and tree phenological and physiological characteristics and soil water balance has to be formulated. (f) A comparison between actual measurements of dead fuel moisture with the moisture content of fuel analogues (i.e., fuel moisture sticks) is necessary in order to validate the precision of the analogues in fuel moisture assessment. (g) The relationship between dead and live fuel moisture and drought (prolonged period of high temperatures and low air and soil humidity) needs to be further investigated, and in particular, the response of shrub and tree species moisture content to drought. The use of the newly formed SPI (Standard Precipitation Index) drought index might be useful in the correlation with fuel moisture, in addition to the traditionally used KBDI and Palmer indexes. In view of the expected global warming and climatic change, this research aspect of fuel moisture could be very significant in the future. (h) The moisture of extinction (ME) of dead and live fuels must be measured in the field (in situ) with a long series of ignition experiments in different fuel types and, subsequently, correlated with the existing fuel moisture content and meteorological parameters in the field, into regression and probabilistic models. ME values of the most significant Mediterranean fuel types must be measured in the laboratory and in the field. (i) The condensation (water vapour that originates from the atmosphere in the form of dew on the surface of dead fuels) and the latent heat of vaporisation of free water from the fuel particle surface are two terms that are currently neglected and must be taken into account in future physical models of dead fuel moisture content. (j) The optimal temporal (time) step for monitoring vegetation moisture content (greenness) via satellite imagery needs to be determined in dead and live Mediterranean fuel complexes.
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Title: D3.1-5 Probability of ignition modelling in forest fuels – First results /
Language: English
Description: Following a similar approach to previous research, and aiming to cover gaps in the literature on ignition, especially in regard to Mediterranean conditions, the present study focuses on the following: (1) To evaluate the threshold of fuel moisture content that allows a fire to start. A range of fuel types (pine needles, grass and Quercus coccifera leaves) are examined, as are different ignition sources (kitchen matches, cigarettes, machinery sparks and electrical discharge), with the presence/absence of wind in order to determine the probability of ignition of selected natural dead fuels (MAICh); and (2) To measure the probability of ignition of annual live herbaceous fuels, at various moisture contents, in the field (AUTh). Fuel moisture content (FMC) is used as the main predictor variable throughout these experiments because it has a major effect on fuel ignitability, is easily altered and can be accurately measured. Only the first results of the study are presented within this deliverable: (1) Probability of ignition of pine needles (Pinus halepensis) with kitchen matches and cigarettes as ignition sources conducted in the wind tunnel of MAICh. (2) Probability of ignition of grass (Hyparrhenia hirta) with kitchen matches as an ignition source conducted in the wind tunnel of MAICh. (3) Some preliminary test of pine needles with machinery sparks as well as grass with cigarettes conducted in the wind tunnel of MAICh. (4) Fuel moisture extinction in live annual herbaceous plants (Avena barbata) in the field (AUTh). The final results will be presented within deliverable D 3.1-10 due in month 46 of the project.
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Title: D3.1-10 Fire occurence: relationships with fuel moisture content and remotely-sensed plant phenology data: final results (merged with D3.1-9) /
Language: English
Description: Fire is a basic ecological factor that contributes to determine vegetation diversity and dynamics in time and space. Fuel characteristics play an essential role in fire ignition and propagation; at the landscape scale fuel availability and flammability are closely related to the vegetation phenology that directly affects wildfire pattern in time and space. In this view, the annual NDVI profiles derived from high temporal resolution satellites, like SPOT Vegetation, represent an effective tool for monitoring the coarse-scale vegetation seasonal timing. The objective of this study thus consists in quantifying the explanatory power of multitemporal NDVI profiles on the fire regime characteristics of the potential natural vegetation (PNV) types of Sardinia (Italy) over a five-year period (2000-2004). The results obtained show a good association between the NDVI temporal dynamics of the PNV of Sardinia and the corresponding fire regime characteristics, emphasizing the role of the bioclimatic timing of the vegetation in controlling the coarse-scale wildfire spatio-temporal distribution of Sardinia. By providing a sound phytogeographical framework for describing different wildfire regimes, PNV maps can thus be considered helpful cartographic documents for fire management strategies at the landscape scale.
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Title: D3.3-1 Review of data structures for fuel database and protocols for fuel description /
Language: English
Description: Our overall goal in this work package can be defined as follows: “the systematic collection, storage and processing of knowledge on fuels for different users, with different needs, at different scales in order to assess the fuel complex and its fire potential from combustion to the landscape level”. We intend to: (1) collect, store and process existing knowledge on: (i) fuel acquisition protocols / fuel sampling methods; (ii) resulting fuel data categories & fuel models; (iii) allocation of fuel data categories & models to different fire behaviour & fire models at different scales. (2) generate, collect, store and process new knowledge on: (i) which fuel data protocol /fuel sampling method for which purpose at which scale? (ii) user needs: which user needs what at which scale, why & when/how often? This can be achieved by developing a knowledge platform with a single, on-line point of access. This will allow fire ecologists, modellers and managers (and eventually the general public) to access information on definitions, techniques for monitoring fuels, key fuel descriptors with regards to fire behaviour and impact and existing fuel models (Table 1). The system will help to harmonize fire control planning and experimental fire procedures across Europe, where many different approaches are in use (see EUFIRELAB report: UNIT2: D-01-02-01/06 http://www.eufirelab.org/). The system should provide a ‘Clearing House’ for data and information relating to fuel. This may be partly through the collection and storage of data in a single integrated system, and partly through the collection of metadata about information that will be stored elsewhere. We also propose to develop a wiki or bliki to which the fire community can contribute.
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Title: D3.4-2 Review of fuel description methods /
Language: English
Description: The scope of this state-of-the-art is to give an overview on existing fuel description methods and their respective field protocols. Wildland fuels characteristics can be viewed as a hierarchy of levels of increasing complexity, from the cell, fuel particle to the fuel complex or stand and landscape level. The emphasis put on each hierarchy of fuel properties in this document will reflect the type of information required, which is, first of all, related to the approach taken to model fire behaviour.
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Title: D3.4-1 Georeferenced database of representative sites including ecological data /
Language: English
Description: The first part of this deliverable gives an overview of the different study sites in the different countries (France, Greece, Spain, Morocco, Tunisia) involved in fuel description and mapping. The second part of the deliverable is dedicated to the description of the main vegetation types. The third part gives some examples of the plots that are described and some sampling methods, but a more detailed state-of-the-art will be given in D3.4-2. Then, in a fourth part, a list of the available data on the study sites is given. This list is detailed in an annexed table file. Study sites are also georeferenced in a GIS file.
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Title: D2.1-4 Measurements of thermal degradation, ignition and combustion on representative Boreal and Mediterranean fuels /
Language: English
Description: The work presented in this report is a part of the research effort done to improve the knowledge on the thermal degradation of forest fuels. The understanding of these processses is of vital importance for the development of physical fire behaviour models . Thermogravimetric analysis (TGA) and Differential Scanning Calorimetry (DSC) are thermal analysis techniques that provide information on the thermal behaviour of different fuel samples and these data may facilitate the better understanding of the mechanisms of ignitability and combustibility of forest fuels with different chemical composition. The thermal degradation of 10 forest species common in the Mediterranean region has been compared using TGA and DSC techniques. Almost all the tested species demonstrated similar pyrolitic behaviour, except Eucalyptus camaldulensis. Heat Release Rate (HRR) of a fuel is among the most important parameters for understanding combustion process, fire characteristics and propagation rates. It serves to define parameters such as flame geometry and temperature fields. In a previous work, different partners with different bench-scale equipments to measure HRR curves as well as concentrations of the different gaseous by-products of the fuel combustion put in common their expertise testing common samples. This common work and conclusions about experimental conditions to test forest fuel in bench-scale calorimeters was presented in a previous document (deliverable "D2.1-1 Methods for the experimental study combustion adapted to forest fuels and recommendations for modelling"). In this report some result obtained by a Mass Loss Calorimeter with an open-path FTIR spectroscopic system in Pinus pinea and Cistus laurifolius are presented to study the influence on the HRR, carbon monoxide and carbon dioxide curves of parameters like the fuel moisture content or the bulk density of the tested sample. Besides, a Flame Propagation Apparatus has been used to apply oxygen consumption calorimetry for HRR and a FTIR has been used to measure gas concentrations of combustion products in smoke. Results on several pine needles (analyzing flow and species influences) and boreal moss are presented. A Flame Propagation Apparatus (FPA) joined to a FTIR gas analyzer is used to continue previous studioes on pine needles in order to better understand the different regimes for the combustion dynamics of forest fuels. Also Boreal moss has been tested as a new fuel common in Northern Europe. The aim was to investigate the possible differences in behaviour between this fuel and pine needles.
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Title: D3.1-8 Dead fuel moisture modelling and validation /
Language: English
Description: This report presents the final results of researches developed about dead fuel moisture prediction, where empirical dead moisture content models fitted from atmospheric variables were analysed for: Pinus halepensis in Greece, Pinus sylvestris in Poland, and Pinus pinea, P. pinaster and P. radiata in Spain. Several types of fuels were considered: litter, duff and suspended needles. Moreover, an evaluation of the capability of different existing models to predict dead fuel moisture content in the above pine species and Eucalyptus globulus in Spain, and Nothofagus antarctica and Astrocedrus chilensis in Argentina was carried out. In general terms, FWI codes and the Sneeuwjagt and Peet values, adequately reflected the pattern of variation of fuel moisture of litter and duff. Still, the estimates of these models did not show sufficient accuracy to be used directly as predictors of the dead fuel moisture content. In periods not affected by precipitation, simpler vapour exchange models appeared to be suitable for dead fuel moisture content predictions.
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Title: D3.1-1 Review of existing databases for fuel moisture and fuel bed characteristics /
Language: English
Description: Fuel moisture, that is "the moisture percentage of fuel, usually measured by oven-drying a sample and calculating the ratio of dry and moist samples" (according to the EUFireLab Glossary, D-02-01 "Methods for wildland fuel description and modelling: A state of the art") is a critical parameter that affects fire ignition, fire behaviour as well as the impacts of fire. Fuel moisture content is a necessary input for all existing physical, semi-physical and empirical fire behaviour prediction models. In addition, fuel moisture content is a main component of most fire danger rating systems. From the operational point of view, fuel moisture content estimates are also required for prescribed burning (planning and use) and for suppression activities. On the other hand, the characterization of fuel beds, defined as "individual fuel particles organized in defined proportions and structural configurations" (EUFireLab Glossary, D-02-01), has also been pointed out as one of the keys for the assessment of potential fire behaviour and effects, related with both wildland fire prevention and fighting. Therefore, fire scientists as well as fire managers require specific information concerning fuel moisture content and fuel bed characteristics, as it has also been pointed out in Fire Paradox D3.3-1. In this frame, the aim of this deliverable (3.1-1) is to give an overview on existing databases for fuel moisture and fuel bed characterization. To achieve this goal, a search was conducted through Internet, EuFireLab documentation and other literature, and a questionnaire requesting information on the databases for fuel moisture or fuel bed characterization was sent to all members of the Fire Paradox Module 3. A total of five positive answers (XG-CIFAL, Cemagref, University of Thessaloniki, Forest Research Institute of Warsaw and University of Edinburgh) was received.
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