A Bayesian Network model to identify suitable areas for offshore wave energy farms, in the framework of ecosystem approach to marine spatial planning.

The production of energy from waves is gaining attention. In its expansion strategy, technical, environmental and socioeconomic aspects should be taken into account to identify suitable areas for development of wave energy projects. In this research we provide a novel approach for suitable site identification for wave energy farms.

Climate regime shifts and biodiversity redistribution in the Bay of Biscay.

Global ocean warming, wave extreme events, and accelerating sea-level rise are challenges that coastal communities must address to anticipate damages in coming decades. The objective of this study is to undertake a time-series analysis of climate change (CC) indicators within the Bay of Biscay, including the Basque coast. We used an integrated and flexible methodology, based on Generalized Additive Mixed Models, to detect trends on 19 indicators (including marine physics, chemistry, atmosphere, hydrology, geomorphology, biodiversity, and commercial species).

Beach carrying capacity management under Covid-19 era on the Basque Coast by means of automated coastal videometry.

This paper describes the methodology followed to implement social distancing recommendations in the COVID-19 context along the beaches of the coast of Gipuzkoa (Basque Country, Northern Spain) by means of automated coastal videometry. The coastal videometry network of Gipuzkoa, based on the KostaSystem technology, covers 14 beaches, with 12 stations, along 50 km of coastline. A beach user detection algorithm based on a machine learning approach has been developed allowing for automatic assessment of beach attendance in real time at regional scale.