Study of the efflux velocity induced by two propellers

Present analysis is related with seabed erosion caused during docking and undocking maneuvering. Twin propellers without rudder were studied using a physical model with a fixed clearance distance and three different rotating velocities. Experimental results were compared to theoretical expressions of the efflux velocity, axial velocity and finally maximum bed velocity. Efflux velocity equations overestimate the experimental results, whereas axial velocity computed using the Dutch method fits reasonably well the experimental data. However, when maximum bed velocity expressions are compared to experimental results, German method behaves better with an over estimation if a quadratic superposition of the single jets is used.Postprint (published version

O cambio climático

Os cambios no clima sucedéronse ao longo da historia do noso planeta debido a mecanismos naturais. Sen embargo, o cambio climático actual ten a singularidade de estar tamén afectado polo ser humano. Este efecto antropoxénico potencia o quecemento global, incrementando a velocidade dos cambios e limitando a capacidade de adaptación das especies ás novas condicións. Así, incluso variacións pequenas, como décimas de grao na temperatura, poden ser desfavorables para moitas especies, levando á extinción dalgunhas delas. O coñecemento dos cambios climáticos, tanto os pasados coma o actual, permite desenvolver ferramentas de mitigación e adaptación para enfrontarse aos cambios futuros do mellor xeito posible

Multiscale flood risk assessment under climate change: the case of the Miño river in the city of Ourense, Spain

[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.Xunta de Galicia; ED431C 2021/44FEDER; 0034_RISC_ML_6_EXunta de Galicia; ED481B-2021-10

IberWQ: A GPU Accelerated Tool for 2D Water Quality Modeling in Rivers and Estuaries

Este artigo inclúese no número especial "Modelling Flow, Water Quality, and Sediment Transport Processes in Coastal, Estuarine, and Inland Waters"[Abstract] Numerical models are useful tools to analyze water quality by computing the concentration of physical, chemical and biological parameters. The present work introduces a two-dimensional depth-averaged model that computes the most relevant and frequent parameters used to evaluate water quality. High performance computing (HPC) techniques based on graphic processing unit (GPU) parallelization have been applied to improve the efficiency of the package, providing speed-ups of two orders of magnitude in a standard PC. Several test cases were analyzed to show the capabilities and efficiency of the model to evaluate the environmental status of rivers and non-stratified estuaries. IberWQ will be freely available through the package Iber.European Commission; INTERREG-POCTEP; 0034_RISC_ML_6_EXunta de Galicia; ED431C 2017/64-GRCXunta de Galicia; ED481A-2017/31

Comparison of machine learning techniques for reservoir outflow forecasting

Número especial: Advances in machine learning for natural hazards risk assessment[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.FEDER; 0034_RISC_ML_6_EXunta de Galicia; ED431C 2021/44Xunta de Galicia; ED481B-2021-108Universidade de Vigo; 0000 131H TAL 64

Analysis of two sources of variability of basin outflow hydrographs computed with the 2D shallow water model Iber: Digital Terrain Model and unstructured mesh size

Financiado para publicación en acceso aberto: Universidade da Coruña/CISUG[Abstract:] Modelling hydrological processes with fully distributed models based on the shallow water equations implies a high computational cost, which often limits the resolution of the computational mesh. Therefore, in practice, modellers need to find a compromise between spatial resolution, numerical accuracy and computational cost. Moreover, this balance is probably related to the accuracy and resolution of the underlying Digital Terrain Model (DTM). In this work, it is studied the effect of the DTM resolution and the size of the computational mesh on the results and on the runtime of a hydrological model based on the 2D shallow water equations. Seven rainfall events in four different basins have been modelled using 3 DTMs and 3 different mesh resolutions. The results obtained highlight the relevance of the vertical accuracy versus the horizontal resolution of the DTMs. Furthermore, it has been observed that mesh resolutions greater than 25 m, together with LiDAR-based DTMs with horizontal resolution greater than 25 m, provide comparable outflow hydrographs.Xunta de Galicia; ED481B-2021-108Xunta de Galicia; ED431C 2021/44Xunta de Galicia; ED431C 2018/56Fondo Europeo de Desarrollo Regional (FEDER); 0034_RISC_ML_6_

An accelerated tool for flood modelling based on Iber

Este artigo inclúese no número especial "Selected Papers from the 1st International Electronic Conference on the Hydrological Cycle (ChyCle-2017)"[Abstract:] This paper presents Iber+, a new parallel code based on the numerical model Iber for two-dimensional (2D) flood inundation modelling. The new implementation, which is coded in C++ and takes advantage of the parallelization functionalities both on CPUs (central processing units) and GPUs (graphics processing units), was validated using different benchmark cases and compared, in terms of numerical output and computational efficiency, with other well-known hydraulic software packages. Depending on the complexity of the specific test case, the new parallel implementation can achieve speedups up to two orders of magnitude when compared with the standard version. The speedup is especially remarkable for the GPU parallelization that uses Nvidia CUDA (compute unified device architecture). The efficiency is as good as the one provided by some of the most popular hydraulic models. We also present the application of Iber+ to model an extreme flash flood that took place in the Spanish Pyrenees in October 2012. The new implementation was used to simulate 24 h of real time in roughly eight minutes of computing time, while the standard version needed more than 15 h. This huge improvement in computational efficiency opens up the possibility of using the code for real-time forecasting of flood events in early-warning systems, in order to help decision making under hazardous events that need a fast intervention to deploy countermeasures.Water JPI—WaterWorks Programme, project Improving Drought and Flood Early Warning, Forecasting and Mitigation, IMDROFLOOD; PCIN-2015-243European Commission; project RISC_ML 034_RISC_ML_6_EXunta de Galicia; ED431C 2017/64-GRCXunta de Galicia; ED481A-2017/314Xunta de Galicia; ED481B-2018/020European Commission; IMDROFLOOD PCIN-2015-24

Assessment of Hybrid Wind-Wave Energy Resource for the NW Coast of Iberian Peninsula in a Climate Change Context

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 coastThe 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 Renewable Energy” (CA17105), which received funding from the HORIZON2020 Framework Programme by COST (European Cooperation in Science and Technology), a funding agency for research and innovation networksS

Economic Feasibility of Floating Offshore Wind Farms Considering Near Future Wind Resources: Case Study of Iberian Coast and Bay of Biscay

[Abstract] Wind energy resources are subject to changes in climate, so the use of wind energy density projections in the near future is essential to determine the viability and profitability of wind farms at particular locations. Thus, a step forward in determining the economic assessment of floating offshore wind farms was taken by considering current and near-future wind energy resources in assessing the main parameters that determine the economic viability (net present value, internal rate of return, and levelized cost of energy) of wind farms. This study was carried out along the Atlantic coast from Brest to Cape St. Vincent. Results show that the future reduction in wind energy density (2%–6%) mainly affects the net present value (NPV) of the farm and has little influence on the levelized cost of energy (LCOE). This study provides a good estimate of the economic viability of OWFs (Offshore Wind Farms) by taking into account how wind resources can vary due to climate change over the lifetime of the farm.Ministerio de Ciencia e Innovación; 10.13039/501100011033.Xunta de Galicia; ED431C 2017/6