In recent years, Spain, in an effort to meet European Union (E.U.) targets, has been developing different strategies to promote the installation of renewable energy plants. In this regard, evaluating territories to assess their potential and thus identify optimum sites for the installation of energy-generating facilities is a crucial task. This paper presents a comprehensive geographic information system (GIS)-based site-selection methodology for wind-power plants in the province of Córdoba, which has hitherto been regarded as unsuitable for this sort of facility owing to the lack of wind resources. Three scenarios have been set out, each of which presents a different set of restrictions. Scenario 2 applies the most stringent restrictions in the specialized literature, and finds no suitable areas for the installation of wind-energy plants. However, Scenario 1, which applies the least stringent restrictions, and Scenario 3, which applies the same restrictions currently in force for other wind turbines already in operation in Andalusia, have led to the identification of several areas that could a priori be considered suitable and now need more detailed analysis. The results illustrate the convenience of undertaking multiscenario analyses.
Saltmarshes provide high-value ecological services and play an important role in coastal ecosystems and populations. As the rate of sea level rise accelerates in response to climate change, saltmarshes and tidal environments and the ecosystem services that they provide could be lost in those areas that lack sediment supply for vertical accretion or space for landward migration. Predictive models could play an important role in foreseeing those impacts, and to guide the implementation of suitable management plans that increase the adaptive capacity of these valuable ecosystems. The SLAMM (sea-level affecting marshes model) has been extensively used to evaluate coastal wetland habitat response to sea-level rise. However, uncertainties in predicted response will also reflect the accuracy and quality of primary inputs such as elevation and habitat coverage. Here, we assessed the potential of SLAMM for investigating the response of Atlantic-Mediterranean saltmarshes to future sea-level rise and its application in managerial schemes. Our findings show that SLAMM is sensitive to elevation and habitat maps resolution and that historical sea-level trend and saltmarsh accretion rates are the predominant input parameters that influence uncertainty in predictions of change in saltmarsh habitats. The understanding of the past evolution of the system, as well as the contemporary situation, is crucial to providing accurate uncertainty distributions and thus to set a robust baseline for future predictions.
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