Integrating complex numerical approaches into a user-friendly application for the management of coastal environments

Estuarine environmental flow assessment based on the flow-ecological health index relation model: a case study in Yangtze River Estuary, China

Environmental flow (e-flow) is the water demand of one given ecosystem, which can become the flow regulation target for protection and restoration of river or estuarine ecosystems. In this study, an e-flow assessment based on the flow-ecological health index (EHI) relation model was conducted to improve ecosystem health of the Yangtze River Estuary (YRE). Monitoring data of hydrology, biology, and water environment in the last decades were used for the model establishment. For the description of the YRE ecosystem, an EHI system was developed by cumulative frequency distribution curves and adaption of national standards. After preprocessing original flow values into proportional flow values, the generalized additive model and Monte Carlo random sampling were used for the establishment of the flow-EHI relation model. From the model calculation, the e-flow assessment results were that, in proportional flow values, the suitable flow range was 1.05-1.35, and the optimum flow range was 1.15-1.25 (flows in Yangtze River Datong Station). For flow regulation in two crucial periods, flows of 42,630-65,545 m3/s or over 14,675 m3/s are needed for the suitable flow of YRE in summer (June-August) or January, respectively. An adaptive management framework of ecological health-based estuarine e-flow assessment for YRE was contrived due to the limitation of current established model when facing the extreme drought in summer, 2022. The methodology and framework in this study are expected to provide valuable management and data support for the sustainable development of estuarine ecosystems and to bring inspiration for further studies at even continental or global levels.

Wave energy assessment under climate change through artificial intelligence

The implementation of renewable energies is among the main challenges that we are confronting in the present situation of climate change. In this work, an artificial neural network (ANN) is optimized and used to assess the wave energy resource available to a wave farm over its service life. We select as case study a stretch of coastline in southern Spain. Different ANN architectures and training algorithms are tested for a dataset in deep water composed by: three values of significant wave height, four values of peak period, two values of incoming wave direction, three astronomical tide values, three storm surge values and three values of sea level rise induced by climate change. These deep-water sea states were propagated using a numerical model (Delft3D-Wave) and results were obtained at 176 locations. Thus, more than 114,000 data were used to train and test the ANNs. Once validated, the ANN was used to assess the cumulative wave energy at 704 locations during a 25-year period for three scenarios of rise in sea level according to the Intergovernmental Panel on Climate Change (IPCC) reports: present situation, pessimistic IPCC projection and optimistic IPCC projection. According to the results, the cumulative wave energy in the case study increases with increasing water depths. The greatest values of cumulative wave energy are reached at great depths off a shoreline horn and a port. Importantly, the rise in sea level will induce an increase in the wave energy resource. The ANN developed in this work allows the quantification of wave energy over long-term periods, reducing the computational cost, as well as the choice of the best locations for wave farms considering the effects of climate change.

Multi-criteria characterization and mapping of coastal cliff environments: A case study in NW Spain

This paper presents a novel approach to characterize cliff exposure to marine action that combines wave power and biology. This multidisciplinary approach is illustrated through a case study on a coastal stretch in NW Spain - the Catedrales Natural Monument. The engineering perspective is based on quantifying the wave power acting on the cliff. To this end, a statistical characterization of the wave climate in deep water is carried out, and relevant sea states are propagated numerically from deep water to the cliff. Four levels of cliff exposure, from sheltered to exposed, are defined based on wave power and mapped onto the study area. As for the biological perspective, ecological factors, bioindicated variables and biological indicators characterized through field observations are considered and, on this basis, also four levels of cliff exposure are established and mapped. In general, there is good agreement between the exposure patterns obtained through the engineering and biological perspectives; however, there are some differences in certain areas. The upshot is that the engineering and biological points of view should be regarded as complementary. The multi-criteria characterization performed in this paper may be used as a management tool to establish different degrees of exposure to marine action on cliff coasts elsewhere.

Coastal infrastructure operativity against flooding - A methodology

The operativity of the transport infrastructures and urban developments protected by coastal structures is conditioned by flooding events and the resulting wave overtopping. This work presents a methodology to assess the operational conditions of infrastructures located in coastal areas based on the combination of advanced statistical techniques, laboratory experiments and state-of-the-art numerical models properly validated. It is applied to a case study in the SW coast of England, the railway seawall at Dawlish, which was subjected to recurrent wave overtopping until its dramatic collapse in February 2014. To quantify the increase in overtopping discharges with wave height and water level, we define an ad hoc variable, the effective overtopping forcing, which explains 98% of the variability of the overtopping discharge. The return periods associated to the operational thresholds for coastal structures protecting people and railways are also obtained. The proposed methodology enables the assessment of the overtopping discharge induced by a given sea state and, thus, check if a coastal infrastructure will be or not operational under any expected marine condition. This innovative methodology can also be used to analyse the flooding event consequences on urban areas protected by coastal infrastructures.

Approaching Software Engineering for Marine Sciences: A Single Development Process for Multiple End-User Applications

Research software is currently used by a large number of scientists on a daily basis, and everything indicates that this trend will continue to increase in the future. Most of this scientific software is very often developed by the researchers themselves, who usually make it available to the rest of the scientific community. Although the relationship between science and software is unquestionably useful, it is not always successful. Some of the critical problems that scientists face include a lack of training in software development, a shortage of time and resources, or difficulty in effectively cooperating with other colleagues. Additional challenges arise in the context of increasingly common cross-cutting and multidisciplinary research. This often results in the developed software and code being slow, not reusable, lacks visibility and dissemination, and in the worst cases it is defective and unreliable. Therefore, a multidisciplinary framework is needed to meet the demands of both scientists and software engineers and handle the situation successfully. However, a multidisciplinary team is not always sufficient to solve this problem, and it is necessary to have links between scientists and developers: software engineers with a solid scientific background. This paper presents the approach used in the framework of the PROTOCOL project, and more particularly in the development of its applied software, in which a tool for the characterization of climate agents has been developed. The main guidelines of the development process include, among others, modularity, distributed control version, unit testing, profiling, inline documentation and the use of best practices and tools.

Wave farm effects on the coast: The alongshore position

For wave energy to become a fully-fledged renewable and thus contribute to the much-needed decarbonisation of the energy mix, the effects of wave farms (arrays of wave energy converters) on coastal systems must be addressed. The objective of this work is to investigate the effects of wave farms on the longshore sediment transport and shoreline evolution of a gravel-dominated beach and, in particular, its sensitivity to the longshore position of the farm based on eight scenarios. Nearshore wave propagation patterns are computed by means of a spectral wave propagation model (SWAN), variations in sediment transport rates induced by the farm are calculated, and a one-line model is applied to determine the shoreline position and dry beach area. The significant wave height at breaking is reduced in the lee of the wave farm, dampening sediment transport. We find that changes in the dry beach area induced by the wave farm are highly sensitive to its alongshore position, and may result in: (i) erosion relative to the baseline scenario (without wave farm) in three of the eight scenarios, (ii) accretion in three other scenarios, and (iii) negligible effects in the remaining two. These results prove that the alongshore position of the wave farm controls the response of the beach to the extent that it may shift from accretionary to erosionary, and provide evidence of its effectiveness in countering erosion if appropriately positioned. This effectiveness opens up the possibility of using wave farms not only to generate carbon-free energy but also to manage coastal erosion, thus strengthening the case for the development of wave energy.

Protection of gravel-dominated coasts through wave farms: Layout and shoreline evolution

The impacts of wave farms (arrays of wave energy converters, or WECs) on the nearshore must be fully understood for wave technology to develop and thus contribute to a sustainable, carbon-free energy mix in the near future. The objective of this work is to investigate the role played by the farm layout on the wave propagation patterns leewards and the implications for longshore sediment transport (LST) and shoreline evolution on a gravel-dominated deltaic coast. Changes in wave propagation in four scenarios, corresponding to as many wave farm layouts, are computed by means of a spectral numerical model (Delft3D-WAVE) under (i) low-energy and storm conditions, and (ii) westerly and easterly waves - the two prevailing wave directions. On this basis, sediment transport rates are computed and changes in the shoreline position assessed using a one-line model. To quantify the impact of the wave farm on the nearshore wave conditions, sediment transport and shoreline, we define three ad hoc indicators: the non-dimensional wave height reduction, the non-dimensional LST rate reduction and the non-dimensional shoreline advance. Significant wave heights decrease in the lee of the wave farm, with the consequent reduction in LST rates. As a result, the dry beach area increases in every scenario under both westerly and easterly waves. We find that case studies with the WECs arranged on fewer rows but covering a greater stretch of coastline provide better coastal protection. These results confirm that wave farms can be used not only to generate carbon-free energy but also to protect gravel-dominated coasts.