This work defines a national flood susceptibility index for the Portuguese continental territory, by proposing the aggregation of different variables which represent natural conditions for permeability, runoff and accumulation. This index is part of the national vulnerability index developed in the scope of Flood Maps in Climate Change Scenarios (CIRAC) project, supported by the Portuguese Association of Insurers (APS). This approach expands on previous works by trying to bridge the gap between different flood mechanisms (e.g. progressive and flash floods) occurring at different spatial scales in the Portuguese territory through (a) selecting homogeneously processed data sets and (b) aggregating their values to better translate the spatially continuous and cumulative influence in floods at multiple spatial scales. Results show a good ability to capture, in the higher susceptibility classes, different flood types: fluvial floods and flash floods. Lower values are usually related to mountainous areas, low water accumulation potential and more permeable soils. Validation with independent flood data sets confirmed these index characteristics, although some overestimation can be seen in the southern region of Alentejo where, due to a dense hydrographic network and an overall low slope, floods are not as frequent as a result of lower precipitation mean values. Future work will focus on (i) including extreme precipitation data sets to represent the triggering factor, (ii) improving representation of smaller and stepper basins, (iii) optimizing variable weight definition process and (iii) developing more robust independent flood validation data sets.

The north-central region of Portugal has undergone significant land cover change since the early 1900s, with large-scale replacement of natural vegetation types with plantation forests. This transition consisted of an initial conversion primarily to Pinus pinaster, followed by a secondary transition to Eucalyptus globulus. This land cover change is likely to have altered the hydrologic functioning of this region; however, these potential impacts are not fully understood. To contribute to a better understanding of the potential hydrologic impacts of this land cover change, this study examines the temporal trends in 75 years of data from the Águeda watershed (part of the Vouga Basin) over the period of 1936–2010. A number of hydrometeorological variables were analyzed using a combined Thiel–Sen/Mann–Kendall trend-testing approach, to assess the magnitude and significance of patterns in the observed data. These trend tests indicated that there have been no significant reductions in streamflow over either the entire test period, or during sub-record periods, despite the large-scale afforestation which has occurred. This lack of change in streamflow is attributed to the specific characteristics of the watershed and land cover change. By contrast, a number of significant trends were found for baseflow index, with positive trends in the early data record (primarily during Pinus pinaster afforestation), followed by negative trends later in the data record (primarily during Eucalyptus globulus afforestation). These trends are attributed to land use and vegetation impacts on streamflow generating processes, both due to species differences and to alterations in soil properties (i.e., infiltration capacity, soil water repellency). These results highlight the importance of considering both vegetation types/dynamics and watershed characteristic when assessing hydrologic impacts, in particular with respect to soil properties.

The project ADAPTACLIMA, promoted by EPAL, the largest Portuguese Water Supply Utility, aims to provide the company with an adaptation strategy in the medium and long term to reduce the vulnerability of its activities to climate change. We used the four scenarios (A1, A2, B1, B2) adopted in the Special Report Emissions Scenarios (SRES) of the IPCC (Intergovernmental Panel on Climate Change) to produce local scenarios of water use. Available population SRES for Portugal were downscaled to the study area using a linear approach. Local land use scenarios were produced using the following steps: (1) characterization of the present land use for each municipality of the study area using Corine Land Cover and adaptation of the CLC classes to those used in the SRES; (2) identification of recent tendencies in land use change for the study area; (3) identification of SRES tendencies for land use change in Europe; and (4) production of local scenarios of land use. Water use scenarios were derived considering both population and land use scenarios as well as scenarios of change in other parameters (technological developments, increases in efficiency, climate changes, or political and behavioural changes). The A2 scenario forecasts an increase in population (+16%) in the study area while the other scenarios show a reduction in the resident population (−6 to 8%). All scenarios, but especially A1, show a reduction in agricultural area and an increase in urban area. Regardless of the scenario, water use will progressively be reduced until 2100. These reductions are mainly due to increased water use efficiency and the reduction of irrigated land. The results accord with several projects modelling water use at regional and global level.

Decades of academic discussion on social resilience have led to the development of indicators, indexes, and different approaches to assessing it at national and local levels. The need to show real-world applications of such assessments is evident since resilience became a political and disaster risk reduction governance component. This article gives a full description of the methodology used to develop SoResilere, a new social resilience index applied to flood disaster-affected Portuguese municipalities. Study cases were selected according to historical databases, academic sources and governmental entities. Statistical methods for data dimension reduction, such as Factor Analysis (through Principal Component Analysis), were applied to the quantitative data and Optimal Scaling to the categorical data. SoResilere results were analyzed. Since SoResilere is a new tool, component weighting was applied to compare results with no weighting, although it did not affect the SoResilere status in 55.5% of the study cases. There is a tendency to look at the improvement of SoResilere results with component weighting due mainly to the quantitative subindex. There is no evidence of the benefits of component weighting, as no logical association or spatial pattern was found to support SoResilere status improvement in 22.22% of the study cases.