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Abstract. River floods, which are one of the most dangerous natural hazards
worldwide, have increased in intensity and frequency in recent decades as a
result of climate change, and the future scenario is expected to be even
worse. Therefore, their knowledge, predictability, and mitigation represent
a key challenge for the scientific community in the coming decades,
especially in those local areas that are most vulnerable to these extreme
events. In this sense, a multiscale analysis is essential to obtain detailed
maps of the future evolution of floods. In the multiscale analysis, the
historical and future precipitation data from the CORDEX (Coordinated Regional Downscaling Experiment) project are used as
input in a hydrological model (HEC-HMS) which, in turn, feeds a 2D hydraulic
model (Iber+). This integration allows knowing the projected future
changes in the flow pattern of the river, as well as analyzing the impact of
floods in vulnerable areas through the flood hazard maps obtained with
hydraulic simulations. The multiscale analysis is applied to the case of the
Miño-Sil basin (NW Spain), specifically to the city of Ourense. The
results show a delay in the flood season and an increase in the frequency
and intensity of extreme river flows in the Miño-Sil basin, which will
cause more situations of flooding in many areas frequented by pedestrians
and in important infrastructure of the city of Ourense. In addition, an
increase in water depths associated with future floods was also detected,
confirming the trend for future floods to be not only more frequent but also
more intense. Detailed maps of the future evolution of floods also provide
key information to decision-makers to take effective measures in advance in
those areas most vulnerable to flooding in the coming decades. Although the
methodology presented is applied to a particular area, its strength lies in
the fact that its implementation in other basins and cities is simple, also
taking into account that all the models used are freely accessible.

Abstract. Reservoirs play a key role in many human societies due to their capability to manage water resources. In addition to their role in water supply and hydropower production, their ability to retain water and control the flow makes them a valuable asset for flood mitigation. This is a key function, since extreme events have increased in the last few decades as a result of climate change, and therefore, the application of mechanisms capable of mitigating flood damage will be key in the coming decades. Having a good estimation of the outflow of a reservoir can be an advantage for water management or early warning systems. When historical data are available, data-driven models have been proven a useful tool for different hydrological applications. In this sense, this study analyzes the efficiency of different machine learning techniques to predict reservoir outflow, namely multivariate linear regression (MLR) and three artificial neural networks: multilayer perceptron (MLP), nonlinear autoregressive exogenous (NARX) and long short-term memory (LSTM). These techniques were applied to forecast the outflow of eight water reservoirs of different characteristics located in the Miño River (northwest of Spain). In general, the results obtained showed that the proposed models provided a good estimation of the outflow of the reservoirs, improving the results obtained with classical approaches such as to consider reservoir outflow equal to that of the previous day. Among the different machine learning techniques analyzed, the NARX approach was the option that provided the best estimations on average.

Abstract. An early warning system for flood prediction based on
precipitation forecast is presented. The system uses rainfall forecast
provided by MeteoGalicia in combination with a hydrologic (Hydrologic Modeling System, HEC-HMS) and a
hydraulic (Iber+) model. The upper reach of the Miño River and the
city of Lugo (NW Spain) are used as a study area. Starting from rainfall
forecast, HEC-HMS calculates the streamflow and Iber+ is automatically
executed for some previously defined risk areas when a certain threshold is
exceeded. The analysis based on historical extreme events shows that the
system can provide accurate results in less than 1 h for a forecast
horizon of 3 d and report an alert situation to decision makers.

Smoothed Particle Hydrodynamics (SPH) method is used here to simulate a heaving point-absorber with a Power Take-Off system (PTO). The SPH-based code DualSPHysics is first validated with experimental data of regular waves interacting with the point-absorber. Comparison between the numerical and experimental heave displacement and velocity of the device show a good agreement for a given regular wave condition and different configurations of the PTO system. The validated numerical tool is then employed to investigate the efficiency of the proposed system. The efficiency, which is defined here as the ratio between the power absorbed by the point-absorber and its theoretical maximum, is obtained for different wave conditions and several arrangements of the PTO. Finally, the effects of highly energetic sea states on the buoy are examined through alternative configurations of the initial system. A survivability study is performed by computing the horizontal and vertical forces exerted by focused waves on the wave energy converter (WEC). The yield criterion is used to determine that submerging the heaving buoy at a certain depth is the most effective strategy to reduce the loads acting on the WEC and its structure, while keeping the WEC floating at still water level is the worst-case scenario. ; This work was partially financed by the Ministry of Economy and Competitiveness of the Government of Spain under project "WELCOME ENE2016-75074-C2-1-R″ and financed by Xunta de Galicia (Spain) under project ED431C 2017/64 ″Programa de Consolidación e Estructuración de Unidades de Investigación Competitivas (Grupos de Referencia Competitiva)" cofunded by European Regional Development Fund (ERDF). Dr. C. Altomare acknowledges funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No.: 792370. Dr J. M. Domínguez acknowledges funding from Spanish government under the program "Juan de la Cierva-incorporación 2017" (IJCI-2017-32592). ; Peer Reviewed ; Postprint (author's final draft)

Offshore renewable energy has a high potential for ensuring the successful implementation of the European decarbonization agenda planned for the near future. Hybrid wind-wave farms can reduce installation and maintenance costs, and increase the renewable energy availability of a location by compensating for the wind's intermittent nature with good wave conditions. In addition, wave farms can provide protection to wind farms, and the combined wind/wave farm can provide coastal protection. This work aims to assess the future hybrid wind-wave energy resource for the northwest coast of Iberian Peninsula for the near future (2026–2045), under the RCP 8.5 greenhouse gas emission scenario. This assessment was accomplished by applying a Delphi classification method to define four categories, aiming to evaluate the richness (wind and wave energy availability, downtime), the variability (temporal variation), the environmental risk (extreme events), and cost parameters (water depth and distance to coast) of the wind and wave resources. The combined index (CI), which classifies the hybrid wind-wave resource, shows that most of the NW Iberian Peninsula presents good conditions (CI > 0.6) for exploiting energy from wind and wave resources simultaneously. Additionally, there are some particularly optimal areas (CI > 0.7), such as the region near Cape Roca, and the Galician coast ; The first author of this work has been supported by the Portuguese Science Foundation (FCT) through a doctoral grant (SFRH/BD/114919/2016). Thanks are also due to FCT/MCTES for the financial support to CESAM (UIDB/50017/2020+UIDP/50017/2020), through national funds. This work was partially supported by Xunta de Galicia under project ED431C 2017/64-GRC (Grupos de Referencia Competitiva) and by Ministry of Economy and Competitiveness of the Government of Spain under the project "WELCOME ENE2016-75074-C2-1-R" funded by European Regional Development Fund (ERDF). This study is also part of the project "WECAnet: A pan-European network for Marine ...

The expansion of marine renewable power is a major alternative for the reduction of greenhouse gases emissions. In Europe, however, the high penetration of offshore wind brings intermittency and power variability into the existing power grid. Offshore solar photovoltaic power is another technological alternative under consideration in the plans for decarbonization. However, future variations in wind, air temperature or solar radiation due to climate change will have a great impact on both renewable energy resources. In this context, this study focusses on the offshore energy assessment off the coast of Western Iberia, a European region encompassing Portugal and the Northwestern part of Spain. Making use of a vast source of data from 35 simulations of a research project called CORDEX, this study investigates the complementarity of offshore wind and solar energy sources with the aim of improving the energy supply stability of this region up to 2040. Although the offshore wind energy resource has proven to be higher than solar photovoltaic resource at annual scale, both renewable resources showed significant spatiotemporal energy variability throughout the western Iberian Peninsula. When both renewable resources are combined, the stability of the energy resource increased considerably throughout the year. The proposed wind and solar combination scheme is assessed by a performance classification method called Delphi, considering stability, resource, risk, and economic factors. The total index classification increases when resource stability is improved by considering hybrid offshore wind-photovoltaic solar energy production, especially along the nearshore water ; X. Costoya is supported by the Spanish Government through a Juan de la Cierva Postdoctoral Fellowship (FJCI-2017-32577). This work was partially supported by Xunta de Galicia under project ED431C 2021/44 (Grupos de Referencia Competitiva) and Ministry of Science and Innovation of the Government of Spain under the project SURVIWEC PID2020-113245RB-I00. D. ...

Abstract. The floods that struck the lower Tagus valley in February 1979 correspond to the most intense floods in this river and affected the largest number of people in a river flow event in Portugal during the last 150 years. In fact, the vast area affected significantly impacted circa 10 000 people in the lower Tagus sector (and an additional 7000 in other regions of Portugal), including thousands of people evacuated or made homeless. In this context, the present study focuses on an in-depth analysis of this event from a hydrodynamic perspective by means of the Iber+ numerical model and on developing strategies to mitigate the flood episodes that occur in the lower section of the Tagus River using the exceptional floods of February 1979 as a benchmark. In this sense, dam operating strategies were developed and analyzed for the most important dam along the Tagus River basin in order to propose effective procedures to take advantage of these infrastructures to minimize the effect of floods. Overall, the numerical results indicate a good agreement with watermarks and some descriptions of the 1979 flood event, which demonstrates the model capability to evaluate floods in the area under study. Regarding flood mitigation, results obtained indicate that the frequency of floods can be reduced with the proposed strategies, which were focused on providing optimal dam operating rules to mitigate flooding in the lower Tagus valley. In addition, hydraulic simulations corroborated an important decrease in water depth and velocity for the most extreme flood events, and also a certain reduction in the flood extension was detected. This confirms the effectiveness of the proposed strategies to help in reducing the flood impact in the lower Tagus valley through the efficient functioning of dams.

The final publication is available at Springer via http://dx.doi.org/10.1007/s40571-021-00404-2 ; DualSPHysics is a weakly compressible smoothed particle hydrodynamics (SPH) Navier–Stokes solver initially conceived to deal with coastal engineering problems, especially those related to wave impact with coastal structures. Since the first release back in 2011, DualSPHysics has shown to be robust and accurate for simulating extreme wave events along with a continuous improvement in efficiency thanks to the exploitation of hardware such as graphics processing units for scientific computing or the coupling with wave propagating models such as SWASH and OceanWave3D. Numerous additional functionalities have also been included in the DualSPHysics package over the last few years which allow the simulation of fluid-driven objects. The use of the discrete element method has allowed the solver to simulate the interaction among different bodies (sliding rocks, for example), which provides a unique tool to analyse debris flows. In addition, the recent coupling with other solvers like Project Chrono or MoorDyn has been a milestone in the development of the solver. Project Chrono allows the simulation of articulated structures with joints, hinges, sliders and springs and MoorDyn allows simulating moored structures. Both functionalities make DualSPHysics especially suited for the simulation of offshore energy harvesting devices. Lately, the present state of maturity of the solver goes beyond single-phase simulations, allowing multi-phase simulations with gas–liquid and a combination of Newtonian and non-Newtonian models expanding further the capabilities and range of applications for the DualSPHysics solver. These advances and functionalities make DualSPHysics an advanced meshless solver with emphasis on free-surface flow modelling. ; This work was partially financed by the Ministry of Economy and Competitiveness of the Government of Spain under project "WELCOME ENE2016-75074-C2-1-R" and financed by Xunta de Galicia (Spain) under project ED431C 2017/64 ″Programa de Consolidación e Estructuración de Unidades de Investigación Competitivas (Grupos de Referencia Competitiva)" co-funded by European Regional Development Fund (ERDF). We are grateful for funding from the European Union Horizon 2020 programme under the ENERXICO Project, Grant Agreement No. 828947 and the Mexican CONACYT- SENER Hidrocarburos Grant Agreement No. B-S-69926. Dr. J. M. Domínguez acknowledges funding from Spanish government under the program "Juan de la Cierva-incorporación 2017" (IJCI-2017-32592). Dr. C. Altomare acknowledges funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No.: 792370. ; Peer Reviewed ; Postprint (author's final draft)