Wildfire is known to create the pre-conditions leading to accelerated soil erosion. Unfortunately, its occurrence is expected to increase with climate change. The objective of this study was to assess the impacts of fire on runoff and soil erosion in a context of global change, and to evaluate the effectiveness of mulching as a post-fire erosion mitigation measure. For this, the long-term soil erosion model LandSoil was calibrated for a Mediterranean catchment in north-central Portugal that burnt in 2011. LandSoil was then applied for a 20-year period to quantify the separate and combined hydrological and erosion impacts of fire frequency and of post-fire mulching using four plausible site-specific land use and management scenarios (S1. business-as-usual, S2. market-oriented, S3. environmental protection and S4. sustainable trade-off) and an intermediate climate change scenario Representative Concentration Pathway (RCP) 4.5 by 2050. The obtained results showed that: (i) fire had a reduced impact on runoff generation in the studied catchment (<5%) but a marked impact on sediment yield (SY) by about 30%; (ii) eucalypt intensification combined with climate change and fires can increase SY by threefold and (iii) post-fire mulching, combined with riparian vegetation maintenance/restoration and reduced tillage at the landscape level, was highly effective to mitigate soil erosion under global change and associated, increased fire frequency (up to 50% reduction). This study shows how field monitoring data can be combined with numerical erosion modeling to segregate the prominent processes occurring in post forest fire conditions and find the best management pathways to meet international goals on achieving land degradation neutrality (LDN).

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 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.

The world is facing a global sustainability crisis affecting environmental systems and society. Addressing these issues requires a multi-dimensional approach that can integrate energy, water, and environment Systems, as well as provide scientific policy advice. In this study, an updated version of an Integrated Assessment Model (IAM) was used, together with new data compatible with Shared Socioeconomic Pathways (SSPs) projections, to significantly improve the work developed before. SSP climate data (temperature, precipitation, and total radiative forcing) and socioeconomic data (population and GDP) were loaded into the IAM, together with different scenario parameters. By analyzing varying socioeconomic scenarios, mitigation efforts, and adaptation strategies, this study assesses their impact on primary energy demand and, consequently, their impact on hydropower potential production. Our results show diverse energy paths, strongly dependent on the future scenario. Energy demand could increase up to 160%; however, several projections foresee a decline in hydropower production to minus 46% due to both climate change and socioeconomic transformation. Our findings highlight the importance of considering a range of potential future scenarios in energy planning and policy development. The varied outcomes across the considered scenarios emphasize the need for flexibility in strategies to accommodate for uncertainties and address the challenges posed by divergent trajectories in hydropower use and renewable energy shares.