Improving our understanding of individual wildfires by combining satellite data with fire spread modelling

Doutoramento em Engenharia Florestal e dos Recursos Naturais - Instituto Superior de AgronomiaWildfires pose real threats to life and property. In Portugal, the recent year of 2017 had the largest burnt area extent and number of casualties. A knowledge gap still exists in wildfire research related with better understanding individual wildfires, which has important implications for fire suppression, management, and policies. Wildfire spread models have been used to study individual wildfires, however, associated uncertainties and the lack of systematic evaluation methods hamper their capability for accurately predicting their spread. Understanding how fire spread predictions can be improved is a critical research task, as they will only be deemed useful if they can provide accurate and reliable information to fire managers. The present Thesis proposes to contribute to improve fire spread predictions by: i) Developing a methodology to systematically evaluate fire spread predictions ii) Thoroughly characterizing input data uncertainty and its impact on predictions; iii) Improving predictions using data-driven model calibration. The spread of large historical wildfires were studied by combining satellite data and models. The major findings of the present Thesis were: i) Satellite data accurately contributed to provide accurate fire dates and ignition information for large wildfires. ii) The evaluation metrics were very useful in identifying areas and periods of low/high spatio-temporal agreement, highlighting the strong underprediction bias and poor accuracy of the predictions. iii) Uncertainties in wind speed and direction, fuel model assignment and typology, location and timing of ignitions, had a major impact on prediction accuracy. iv) Predictions iii) Uncertainties in wind speed and direction, fuel model assignment and typology, location and timing of ignitions, had a major impact on prediction accuracy. iv) Predictions were improved by ‘learning’ from past wildfires, significantly reducing the impact of data uncertainty on the accuracy of fire spread predictions Overall, the work contributed to advance the body of knowledge regarding individual wildfires and identified future research steps towards a reliable operational fire system capable of supporting more effective and safer fire management decisions with the aim of reducing the dramatic impacts of wildfiresN/

Monitoring chlorophyll-a with remote sensing techniques in the Tagus Estuary

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Gestão e Sistemas AmbientaisEstuaries are transitional ecosystems with high temporal and spatial variability and suffer high anthropogenic pressures. At the present there is a major challenge to monitor these systems in a robust, frequent, systematic and accurate fashion. With the implementation of the Water Framework Directive (WFD), the EU Member States must monitor regularly the most relevant physical and biological parameters. Estuarine information is attained using in-situ samples, model analysis and/or remote sensing data. This work assessed the applicability and accuracy of chlorophyll-a products from the MODIS sensor in the Tagus estuary, comparing them (2000-2002) with simulations of an ecological model, the EcoWin2000. The latter was previously calibrated (1998 & 1999) and validated(2000). It is proposed a conceptual and methodological framework for future monitoring of the estuary using remote sensing data. In a first stage, in the year 2000, typical Case 1 algorithms were pre-assessed and Case 2 algorithms were regionally calibrated. The GSM and Clark algorithms had the best performances, with errors of approximately of 1.1 μg chl-a l-1 (or 20%) and correlations ranging 0.4-0.5. During calibration, the ratio R678/R551 had a good correlation (r = 0.83) and low errors (~1μg chl-a l-1). Its evaluation in 2002, showed low and sometimes negative correlations, with errors of about 2 μg chl-a l-1. In agreement with the preliminary assessment,in 2002, the GSM algorithm had the best correlation (r~0.50) and errors of approximately 0.8μg chl-a l-1. The reliability of remote sensing is higher in the Spring and Summer, and spatially, in the wider mid estuary sections. Although remote sensing needs extensive further development, it was proven to be a reliable tool with several advantages for systematic chl-a monitoring in the Tagus estuary. Specifically, it is a tool with high to assist the EU Member States to accomplish the WFD objectives

How do large wildfires impact sediment redistribution over multiple decades?

Wildfires have become an increasing threat for Mediterranean ecosystems, due to increasing climate change-induced wildfire activity and changing land management practices. In addition to the initial risk, wildfires can alter the soil in various ways—depending on fire severity—and cause enhanced post-fire erosion. Usually, post-fire erosion studies focus on a short time window and lack the attention for sediment dynamics at larger spatial scales. Yet, these large spatial and temporal scales are fundamental for a better understanding of long-term destructive effects of multiple recurring wildfires on post-fire erosion processes and catchment sediment dynamics. In this study the landscape evolution model LAPSUS was used to simulate erosion and deposition in the 404 km2 Águeda catchment in north-central Portugal over a 41-year (1979–2020) timespan, including eight wildfires each burning >1000 ha. To include variation in fire severity and its impact on the soil, four burn severity classes, represented by the difference normalized burn ratio (dNBR), were parameterized. Although model calibration was difficult due to lack of spatial and temporal measured data, the results show that long-term post-fire net erosion rates were significantly higher in the wildfire scenarios (5.95 ton ha−1 yr−1) compared to those of a non-wildfire scenario (0.58 ton ha−1 yr−1). Furthermore, erosion values increased with burn severity and multiple wildfires increased the overall catchment sediment build-up. Simulated erosion patterns showed great spatial variability, with large deposition and erosion rates inside streams. This variability made it difficult to identify land uses that were most sensitive for post-fire erosion, because some land uses were located in more erosion-sensitive areas (e.g. streams, gullies) or were more affected by high burn severity levels than others. Despite these limitations, LAPSUS performed well on addressing spatial sediment processes and can contribute to pre-fire management strategies, by identifying locations at risk of post-fire erosion.info:eu-repo/semantics/publishedVersio

Drivers of extreme burnt area in Portugal: fire weather and vegetation

Fire weather indices are used to assess the effect of weather on wildfire behaviour and to support fire management. Previous studies identified the high daily severity rating percentile (DSRp) as being strongly related to the total burnt area (BA) in Portugal, but it is still poorly understood how this knowledge can support fire management at a smaller spatial scale. The aims of this study were to (1) assess whether the 90th DSRp (DSR90p) threshold is adequate for estimating most of the BA in mainland Portugal; (2) analyse the spatial variability of the DSRp threshold that explains a large part of BA, at higher resolution; and, (3) analyse whether vegetation cover can justify the DSRp spatial variability. We used weather reanalysis data from ERA5-Land, wildfire and land use data from Portuguese land management departments for an extended summer period (15 May to 31 October) from 2001 to 2019. We computed and related DSRp to large wildfires (BA &gt; 100 ha) and land use to clarify the effectiveness of the DSRp for estimating BA in Portugal and assess how vegetation influences it. Results revealed that the DSR90p is an adequate indicator of extreme fire weather days and BA in Portugal. In addition, the spatial pattern of the DSRp associated with most of the total BA shows variability at the municipality scale. Municipalities where large wildfires occur with more extreme weather conditions have most of the BAs in forests and are in coastal areas. By contrast, municipalities where large wildfires occur with less extreme weather conditions are predominantly covered by shrublands and are situated in eastern and inland regions. These findings are a novelty for fire science in Portugal and should be considered by fire managers and fire risk assessors.</p

Assessing risk and prioritizing safety interventions in human settlements affected by large wildfires

The large wildfires of June 2017 disturbed many communities in central Portugal. The civil parish of Alvares was severely affected, with about 60% of its area burnt. Assessing the risk of large wildfires affecting local communities is becoming increasingly important, to reduce potential losses in the future. In this study, we assessed wildfire risk for the 36 villages of Alvares parish, by combining hazard, exposure and vulnerability analysis at the settlement scale. Hazard was obtained from fire spread simulations, which integrated exposure together with population and building density within each village. Vulnerability was based on the sociodemographic characteristics of the population, ranked with a hierarchical cluster analysis. Coping capacity was also integrated, considering the distance of each village to the fire station and the time needed for residents to reach a shelter. We simulated 12 different land management scenarios, regarding the implementation of a fuel-break network and the level of forest management activities. The potential effects of each scenario in the exposure and risk levels of the settlements were evaluated. The results show that, for a business-as-usual scenario, 36% of the villages are at high or very high risk of wildfires. Examining each risk component, 28% of the villages are highly exposed, 44% are highly vulnerable, and 22% do not have a potential shelter on-site, calling for different intervention strategies in each specific risk dimension. All the land management scenarios, even if designed for other purposes than the protection of settlements, could decrease the proportion of highly exposed villages at different levels, up to a maximum of 61%. These findings can contribute to adjust prevention and mitigation strategies to the risk levels and the characteristics of the population and the territory, and to prioritize the protection and emergency actions at the local scale.info:eu-repo/semantics/publishedVersio

A simple water balance model adapted for soil water repellency: application on Portuguese burned and unburned eucalypt stands

Soil water repellency can impact soil hydrology, overland flow generation and associated soil losses. However, current hydrological models do not take it into account, which creates a challenge in repellency-prone regions. This work focused on the adaptation for soil water repellency of a daily water balance model. Repellency is estimated from soil moisture content using site-specific empirical relations, and used to limit maximum soil moisture. This model was developed and tested using c. 2 years of data from one long-unburned and two recently burned eucalypt plantations in northern Portugal, all of which showed strong seasonal soil water repellency cycles. Results indicated important improvements for the burned plantations, with the Nash-Sutcliffe efficiency increasing from -0.55 and -0.49 to 0.55 and 0.65. For the unburned site, model performance was already good without the modification and efficiency only improved slightly from 0.71 to 0.74, mostly due to the better simulation of delayed soil wetting after dry periods. Results suggested that even a simple approach to simulate soil water repellency can markedly improve the performance of hydrological models in eucalypt forests, especially after fire.info:eu-repo/semantics/publishedVersio

Drivers of extreme burnt area in Portugal: fire weather and vegetation

Fire weather indices are used to assess the effect of weather on wildfire behaviour and to support fire management. Previous studies identified the high daily severity rating percentile (DSRp) as being strongly related to the total burnt area (BA) in Portugal, but it is still poorly understood how this knowledge can support fire management at a smaller spatial scale. The aims of this study were to (1) assess whether the 90th DSRp (DSR90p) threshold is adequate for estimating most of the BA in mainland Portugal; (2) analyse the spatial variability of the DSRp threshold that explains a large part of BA, at higher resolution; and, (3) analyse whether vegetation cover can justify the DSRp spatial variability. We used weather reanalysis data from ERA5-Land, wildfire and land use data from Portuguese land management departments for an extended summer period (15 May to 31 October) from 2001 to 2019. We computed and related DSRp to large wildfires (BA > 100 ha) and land use to clarify the effectiveness of the DSRp for estimating BA in Portugal and assess how vegetation influences it. Results revealed that the DSR90p is an adequate indicator of extreme fire weather days and BA in Portugal. In addition, the spatial pattern of the DSRp associated with most of the total BA shows variability at the municipality scale. Municipalities where large wildfires occur with more extreme weather conditions have most of the BAs in forests and are in coastal areas. By contrast, municipalities where large wild fires occur with less extreme weather conditions are predominantly covered by shrublands and are situated in eastern and inland regions. These findings are a novelty for fire science in Portugal and should be considered by fire managers and fire risk assessors.info:eu-repo/semantics/publishedVersio

Defining priorities for wildfire mitigation actions at the local scale: insights from a novel risk analysis method applied in Portugal

IntroductionIn Portugal, the 2017 fire season was particularly extreme, leading to an unprecedented large number of fatalities, injured people, destruction of houses and infrastructures. These dramatic outcomes have contributed to raise awareness regarding the importance of ensuring the safety of people and assets from high intensity uncontrollable wildfires. It is crucial to identify the settlements at higher risk and the most suitable mitigation actions that can maximize the protection of people and assets.MethodsWe developed a simple methodology that combines exposure and vulnerability to estimate wildfire risk at the local level. Exposure was estimated using a fire spread simulation approach that was used to determine the probability of (i) a wildfire generating firebrands that could affect a settlement and (ii) a high intensity wildfire occurring adjacent to a settlement. Exposure was estimated using two fuel scenarios created to represent the current year of 2023 (short-term scenario) and 2030, assuming that no fuel management nor large fires occur in the meantime (medium-term worst-case scenario). Vulnerability was determined by the (i) Index of Total Dependence (IDT), and (ii) evacuation difficulty. Exposure and vulnerability metrics were normalized in percentiles, distributed into quadrants and combined to provide six levels of wildfire risk. For each vulnerability\exposure combination, we proposed a set of priority mitigation actions. The methodology was applied to three areas in Portugal where the risk estimates were analyzed and compared with the implementation rate of two risk mitigation programs already in place.ResultsResults showed that 8.7% of the settlements had “very high” wildfire risk and about 19.5% had “high” wildfire risk, potentially affecting 8,403 and 34,762 inhabitants, respectively. The spatial distribution of settlements at higher risk was very heterogeneous across the study areas and the total fraction ranged between 14% in Coimbra to 36% in Barlavento Algarvio. The overall implementation of mitigation programs in the study areas is very low, with only around 1% of the settlements in “very high” risk having any of the mitigation programs implemented. Conversely, our results also suggest that the implementation rate in settlements classified in lower risk classes is disproportionately high.DiscussionThe application of this risk analysis methodology can be used to assess the implementation status of mitigation actions, and contribute to tailor the actions that maximize the protection of people and assets according to the specific conditions found in each targeted area

Combining landscape fire simulations with stand-level growth simulations to assist landowners in building wildfire-resilient landscapes

The wildfire regime in Portugal has been responsible for millions of hectares of burnt area, and Alvares parish is no exception. In 2017, a severe wildfire burnt 60% of its area. Land abandonment has been increasing since the mid 20th century, and a large fraction of the forest area belongs to quasi-absent landowners. This has given rise to large, almost unbroken expanses of undermanaged forests that, in combination with rugged topography, originates a landscape prone to large, intense wildfires. Thus, a change in landscape composition and structure capable of reducing flammability and promoting fuel discontinuity is urgently needed. A fire spread simulator and a forest growth simulator were combined to show the impact of improving management at landscape level. It was assumed that the probability of large wildfires may be reduced by setting aside forest area for the implementation of a fuel break network (FBN) and increasing the area under sustainable forest management. Three levels of management intensity were simulated by restricting the area of Quasi-absent non-industrial owners to 34.5%, 20.1%, and 8.5% of the Alvares forest area, in favor of increasing the area of active and semi-active non-industrial owners (current, moderate, and high management scenarios). Different FBN extents, representing four levels of network implementation priority were combined with the management levels, resulting in 12 scenarios. To evaluate the impact of fire, simulations assuming no-fire, no-FBN, and current management intensity were performed, whereas the impact of operation costs was assessed assuming reduced costs for silvicultural operations. Per hectare simulations were then scaled up to the parish level and volume harvested and net present values were used to compare the management improvement scenarios. Results showed that fire has major repercussions on forest income, but these impacts can be minimized. Intensifying forest management and implementing the first priority FBN segments originated substantial improvements in financial outcome from timber production, close to those obtained for the full FBN implementation. Results also evidenced contrasting contributions from industrial and non-industrial owners with the later evidencing unbalanced cash-flows derailing the possibility for interesting forest incomes. The coupling of fire and forest growth simulations can be an interesting approach to assess the impact of different management and policy scenarios and inform policiesinfo:eu-repo/semantics/publishedVersio

The potential of satellite data to study individual wildfire events

Geophysical Research Abstract of EGU General Assembly 2014, held 27 April - 2 May, 2014 in Vienna, Austria