Browsing by Author "Pinto, Renata"
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- Deciphering the impact of uncertainty on the accuracy of large wildfire spread simulationsPublication . Benali, Akli Ait; Ervilha, Ana R.; Sá, Ana C.L.; Fernandes, Paulo M.; Pinto, Renata; Trigo, Ricardo M.; Cardoso Pereira, José MiguelPredicting wildfire spread is a challenging task fraught with uncertainties. ‘Perfect’ predictions are unfeasible since uncertainties will always be present. Improving fire spread predictions is important to reduce its negative environmental impacts. Here, we propose to understand, characterize, and quantify the impact of uncertainty in the accuracy of fire spread predictions for very large wildfires. We frame this work from the perspective of the major problems commonly faced by fire model users, namely the necessity of accounting for uncertainty in input data to produce reliable and useful fire spread predictions. Uncertainty in input variables was propagated throughout the modeling framework and its impact was evaluated by estimating the spatial discrepancy between simulated and satellite-observed fire progression data, for eight very large wildfires in Portugal. Results showed that uncertainties in wind speed and direction, fuel model assignment and typology, location and timing of ignitions, had a major impact on prediction accuracy.We argue that uncertainties in these variables should be integrated in future fire spread simulation approaches, and provide the necessary data for any firemodel user to do so
- Effects of dry-wet cycles on nitrous oxide emissions in freshwater sediments: a synthesisPublication . Pinto, Renata; Weigelhofer, Gabriele; Brito, Antonio Guerreiro De; Hein, ThomasBackground. Sediments frequently exposed to dry-wet cycles are potential biogeochemical hotspots for greenhouse gas (GHG) emissions during dry, wet and transitional phases. While the effects of drying and rewetting on carbon fluxes have been studied extensively in terrestrial and aquatic systems, less is known about the effects of dry-wet cycles on N2O emissions from aquatic systems. As a notable part of lotic systems are temporary, and small lentic systems can substantially contribute to GHG emissions, dry-wet cycles in these ecosystems can play a major role on N2O emissions. Methodology. This study compiles literature focusing on the effects of drying, rewetting, flooding, and water level fluctuations on N2O emissions and related biogeochemical processes in sediments of lentic and lotic ecosystems. Results. N2O pulses were observed following sediment drying and rewetting events. Moreover, exposed sediments during dry phases can be active spots for N2O emissions. The general mechanisms behind N2O emissions during dry-wet cycles are comparable to those of soils and are mainly related to physical mechanisms and enhanced microbial processing in lotic and lentic systems. Physical processes driving N2O emissions are mainly regulated by water fluctuations in the sediment. The period of enhanced microbial activity is driven by increased nutrient availability. Higher processing rates and N2O fluxes have been mainly observed when nitrification and denitrification are coupled, under conditions largely determined by O2 availability. Conclusions. The studies evidence the driving role of dry-wet cycles leading to temporarily high N2O emissions in sediments from a wide array of aquatic habitats. Peak fluxes appear to be of short duration, however, their relevance for global emission estimates as well as N2O emissions from dry inland waters has not been quantified. Future research should address the temporal development during drying-rewetting phases in more detail, capturing rapid flux changes at early stages, and further explore the functional impacts of the frequency and intensity of dry-wet cycles
- Nitrogen in water-Portugal and Denmark: two contrasting realitiesPublication . Cruz, Soraia; Cordovil, Cláudia; Pinto, Renata; Brito, Antonio Guerreiro De; Cameira, Maria; Gonçalves, Guilherme; Poulsen, Jane R.; Thodsen, Hans; Kronvang, Brian; May, LindaAgricultural activities are responsible for most of the nitrogen (N) inputs that degrade water quality. To elucidate the drivers leading to N pressures on water, we examined the resulting state of surface waters in terms of N concentrations, the impact of this on water quality status and policy responses to these constraints across different climatic and management conditions. Portugal and Denmark were chosen as contrasting case studies for the Driver-Pressure-State-Impact-Response (DPSIR) analysis. Our results showed reductions of 39% and 25% in the use of mineral fertilizer in Portugal and Denmark, respectively, between 2000 and 2010. The N surplus in Portugal varied between 15 and 30 kg N ha -1 between 1995 and 2015. In Denmark, in 2015, this amount was 70 kg N ha -1, representing a 53% decrease from the 1990 value. The average amount of total N discharged to surface waters was 7 kg ha -1 for mainland Portugal in 2015 and 14.6 kg ha -1 for Denmark in 2014. These reductions in the N surplus were attributed to historical policies aimed at N pressure abatement. In Denmark, N losses are expected to decline further through the continuation or improvement of existing national action plans. In Portugal, they are expected to decline further due to the expansion of Nitrate Vulnerable Zones and the introduction of targeted policies aimed at improving N use effciency and reducing losses to water
- Probabilistic fire spread forecast as a management tool in an operational settingPublication . Pinto, Renata; Benali, Akli; Sá, Ana C.L.; Fernandes, Paulo M.; Soares, Pedro M.M.; Cardoso, Rita M.; Trigo, Ricardo M.; Cardoso Pereira, José MiguelBackground: An approach to predict fire growth in an operational setting, with the potential to be used as a decision-support tool for fire management, is described and evaluated. The operational use of fire behaviour models has mostly followed a deterministic approach, however, the uncertainty associated with model predictions needs to be quantified and included in wildfire planning and decision-making process during fire suppression activities. We use FARSITE to simulate the growth of a large wildfire. Probabilistic simulations of fire spread are performed, accounting for the uncertainty of some model inputs and parameters. Deterministic simulations were performed for comparison. We also assess the degree to which fire spread modelling and satellite active fire data can be combined, to forecast fire spread during large wildfires events. Results: Uncertainty was propagated through the FARSITE fire spread modelling system by randomly defining 100 different combinations of the independent input variables and parameters, and running the correspondent fire spread simulations in order to produce fire spread probability maps. Simulations were initialized with the reported ignition location and with satellite active fires. The probabilistic fire spread predictions show great potential to be used as a fire management tool in an operational setting, providing valuable information regarding the spatial–temporal distribution of burn probabilities. The advantage of probabilistic over deterministic simulations is clear when both are compared. Re-initializing simulations with satellite active fires did not improve simulations as expected. Conclusion: This information can be useful to anticipate the growth of wildfires through the landscape with an associated probability of occurrence. The additional information regarding when, where and with what probability the fire might be in the next few hours can ultimately help minimize the negative environmental, social and economic impacts of these fires