Coastal morphodynamic emulator for early warning short-term forecasts

- Name of the Software: XBeach version 1.23. Developers: Deltares/XBeach Open-Source Community; First year available: 2009; Cost: Free; Software availability:https://download.deltares.nl/en/download/xbeach-open-source/; Program size: 330.97 MB. - The deep learning-based emulator used for surrogating the XBeach morphodynamic module was implemented in Python language (version 3.9) based on TensorFlow library. The authors used a Windows 11 Home OS environment, CPU Intel(R) Core (TM) i7-8750H 2.20 GHz, RAM 16 GB, GPU Nvidia GeForce GTX 1060. The architecture of the model is available at: http://www.hydroshare.org/resource/b4ae97df748842a1800816b32a3d640 b.Data will be made available on request. Deep learning model for XBeach morphodynamic emulation (Original data) (HydroShare): https://www.hydroshare.org/resource/b4ae97df748842a1800816b32a3d640b/The use of numerical models to anticipate the effects of floods and storms in coastal regions is essential to mitigate the damages of these natural disasters. However, local studies require high spatial and temporal resolution numerical models, limiting their use due to the involved high computational costs. This constraint becomes even more critical when these models are used for real-time monitoring and warning systems. Therefore, the objective of this paper was to reduce the computational time of coastal morphodynamic models simulations by implementing a deep learning emulator. The emulator performance was evaluated using different scenarios run with the XBeach software, which considered different grid resolutions and the effects of a storm event in the morphodynamic patterns around a breakwater and a groin. The morphodynamic simulation time was reduced by 23%, and it was identified that the major restriction to reducing the computational cost was the hydrodynamic numerical model simulation.This research was supported by the Doctoral Grant SFRH/BD/151383/2021 financed by the Portuguese Foundation for Science and Technology (FCT), and with funds from the Ministry of Science, Technology and Higher Education, under the MIT Portugal Program. I. Iglesias also acknowledge the FCT financing through the CEEC program (2022.07420. CEECIND)

Simulation of saltwater intrusion in the Minho river estuary under sea level rise scenarios

Estuaries are areas that are vulnerable to the impacts of climate change. Understanding how these impacts affect these complex environments and their uses is essential. This paper presents a work based on an analytical solution and 2DH and 3D versions of the Delft3D numerical model to simulate the Minho River estuary and its saline wedge length under climate change projections. Temperature observations at several locations in the estuary region were selected to determine which model better simulated the temperature patterns. Specific simulations were performed for the observation periods. Sixteen numerical model scenarios were proposed, considering a varying tide, different river flows, and several SLR projections based on the RCP4.5 and RCP8.5 for 2050 and 2100. The analytical solution was also calibrated using the numerical model solutions. The results show that although there is no relevant stratification, there was a difference in both models in which in the worst climate change scenario, the length of the saline intrusion increased up to 28 km in the 2DH model and 30 km in the 3D model. It was concluded that the 3D model results were more precise, but both configurations can provide insights into how the saline intrusion will be affected. Additionally, the excellent agreement between the analytical solution and the results of the numerical models allowed us to consider the analytical solution a helpful tool for practical applications. It was demonstrated that freshwater discharges and bed slopes are the most critical drivers for the saline intrusion length in the Minho River estuary as they have more impact than the increase in sea level. Therefore, flow regulation can be an excellent way to control saline intrusion in the future.NNI -Nortel Networks Inc(2022.07420

Emulating the estuarine morphology evolution using a deep convolutional neural network emulator based on hydrodynamic results of a numerical model

Coastal and estuarine areas present remarkable environmental values, being key zones for the development of many human activities such as tourism, industry, fishing, and other ecosystem services. To promote the sustainable use of these services, effectively managing these areas and their water and sediment resources for present and future conditions is of utmost importance to implement operational forecast platforms using real-time data and numerical models. These platforms are commonly based on numerical modelling suites, which can simulate hydro-morphodynamic patterns with considerable accuracy. However, in many cases, considering the high spatial resolution models that are necessary to develop operational forecast platforms, a high computing capacity is also required, namely for data processing and storage. This work proposes the use of artificial intelligence (AI) models to emulate morphodynamic numerical model results, allowing us to optimize the use of computational resources. A convolutional neural network was implemented, demonstrating its capacity in reproducing the erosion and sedimentation patterns, resembling the numerical model results. The obtained root mean squared error was 0.59 cm, and 74.5 years of morphological evolution was emulated in less than 5 s. The viability of surrogating numerical models by AI techniques to forecast the morphological evolution of estuarine regions was clearly demonstrated. HIGHLIGHTS The application of convolutional neural network (CNN) for the development of an estuarine morphodynamic emulator is still rare.; Delft3D hydrodynamic results processed in MATLAB for generating AI model inputs datasets.; Python framework for hybrid use of Delft3D and TensorFlow is selected for hydro-morphodynamic models.; The assessment of CNN hyperparameter for a morphodynamic problem is an area of focus for future research.; A comparison between an emulator and a numerical model can be observed in sedimentation and erosion results.