Mangrove forests’ restoration has gained traction as a sustainable solution to mitigate the effects of greenhouse gas emissions and to provide ecosystem services, such as coastal protection. Restoration projects are often informed by expert judgment rather than a quantitative understanding and have a high failure rate. Monitoring mangrove restoration performance may take decades and has a strong case study dependency. To optimise restoration strategies, we developed an individual-based mangrove and process-based hydro-morphodynamic model to simulate multi-species mangrove forest trajectories, including the physical environment’s feedback. We find a significant impact of planting zonation on the mudflat behaviour, with seaward erosion and in-forest-landward deposition. Planting mangroves close to mean sea level decreases carbon storage potential due to increased mudflat erosion. Configuring planting in multiple patches proves beneficial to mangrove biomass development, expansion, and sediment accumulation. Combined with sound monitoring, the developed tool can potentially optimize planned mangrove restoration strategies.

Coastal zones are experiencing notable changes attributed to natural and anthropogenic effects. This study investigates the potential of machine learning (ML) in predicting shoreline changes, a developing field still in its early exploration phase. Traditional methods, while insightful, have faced challenges in terms of adaptability, accuracy, and computational demands. ML, as a data-driven approach, potentially offers flexibility, computational efficiency, and can avoid the constraints associated with physics-based models. This study aims to evaluate various machine learning models’ efficacy in predicting shoreline changes using synthetic data. Through comprehensive testing across one complex shoreline evolution scenario, this research identifies the ConvLSTM model—trained on 2D gridded data— as the optimal machine learning approach suited for addressing specific shoreline complexities and evolution patterns. This approach can learn shoreline evolution, predict it, and serve as a foundational component of a proposed method for probabilistic shoreline position prediction. Additionally, the study shows that the choice of ML model depends on the complexity of shoreline evolution and the desired level of accuracy.

Due to the increase in ship sizes and traffic, the effect of passing ships on the mooring forces of moored ships is becoming an increasingly more important aspect in restricted waterways, channels, and ports. The objective of the presented work is to investigate the effects of the presence of an ambient current on the hydrodynamic forces on moored ships when another vessel passes through the waterway.

In this research, XBeach-NH in (nonhq3d) mode is used to simulate passing ship effects, corresponding to test conditions as measured in physical model tests carried out at Deltares as a part of the JIP Ropes (Joint Industry Project, Research on Passing Effects on Ships) project (van der Hout and de Jong, 2014). Even though various layouts were tested in the Ropes project; the current paper focuses on the straight channel layout with different combinations of ship velocity and ambient current speed. Results show that XBeach slightly overestimates the draw down effects (water level depression) due to the primary waves, as well as the surge forces. And, the differences in surge forces between XBeach and measurement increases with increasing Froude number. However, sway forces and yaw moments are in better agreement with the measured data, even for higher Froude numbers, though slightly underestimated. This variation in results is consistent in almost all XBeach simulations. Results also indicate that ship velocities relative through water are more important than ship speed over ground in the presence of uniform current. However, in modelling exercises, it is advisable to run simulations implementing actual currents rather than simply adding or subtracting the current velocity to/from ship speed over ground to obtain a representative relative vessel through water, since in the latter case the duration of hydrodynamic force excitation on the moored vessel will not be realistic. Furthermore, simulations show that by only representing the correct relative speed through water in the simulations (and not the correct speed over ground), the surge force & yaw moment magnitude are underestimated in case of counter currents and sway forces are underestimated in case of following currents.

Fluvial sediment supply towards the coast has been the subject of extensive research. Important aspects relate to the impact of sediment retaining hydropower dams, potential delta progradation, coastal sediment supply and delta vulnerability to sea level rise. Once validated, process-based models provide a valuable tool to address these aspects and offer detailed information on sediment pathways, distribution and budget in specific systems. This study aims to advance the understanding of the sediment dynamics and sediment budget in the Mekong Delta system. We developed a process-based model (Delft3D FM) that allows for coupling 2D area grids to 1D network grids. The flexible mesh describes both wide river sections and channel irrigation and drainage networks present in the Mekong Delta. We calibrated the model against observed discharge, salinity, suspended sediment concentration (SSC) and sediment flux. The model was able to skillfully describe seasonal variations of SSC and hysteresis of SSC and water discharge caused by the Tonle Sap Lake induced flow patterns and seasonally varying bed sediment availability in the channels. Model results suggest that the Mekong River delivers an amount of sediment, towards the delta which is much lower than the common estimate of 160 Mt/year. About 23% of the modeled total sediment load at Kratie reaches the sea. Our modeling approach is a useful tool to assess sediment dynamics under strategic anthropogenic interventions or climate change scenarios.

Mangrove ecosystems are widely recognized for having highly valued multiple ecosystem services. These services, however, are often overlooked because of the lack of understanding of mangrove's species-specific and associated eco-geomorphological dynamics. Therefore, it will lead to a limited quantification and valuation of mangrove's functional and structural attributes. A mangrove ecosystem model capable of mechanistically simulating the feedback loop between mangrove stands and physical–environmental drivers is essentially important, specifically in the strategy of integrating mangroves as nature-based solutions for climate change adaptation and mitigation. The main objectives of this chapter are to gain a better insight into complex mangrove ecosystem and eco-geomorphic interactions to predict their trajectories, the possibility of modelling those utilizing a process-based model, and explore the interactions of mangrove, mudflat, and physical–environmental drivers. Following that, this chapter introduces a new hybrid model, so-called DFMFON, achieved by coupling mangrove individual-based and landscape-scale hydro-morphodynamic models which is capable of reproducing mangrove forest dynamics and morphodynamic delta features. To conclude, the application, limitations, and future development of process-based mangrove modelling for nature-based solutions are discussed.

Tropical-cyclone impacts can have devastating effects on the population, infrastructure, and natural habitats. However, predicting these impacts is difficult due to the inherent uncertainties in the storm track and intensity. In addition, due to computational constraints, both the relevant ocean physics and the uncertainties in meteorological forcing are only partly accounted for. This paper presents a new method, called the Tropical Cyclone Forecasting Framework (TC-FF), to probabilistically forecast compound flooding induced by tropical cyclones, considering uncertainties in track, forward speed, and wind speed and/or intensity. The open-source method accounts for all major relevant physical drivers, including tide, surge, and rainfall, and considers TC uncertainties through Gaussian error distributions and autoregressive techniques. The tool creates temporally and spatially varying wind fields to force a computationally efficient compound-flood model, allowing for the computation of probabilistic wind and flood hazard maps for any oceanic basin in the world as it does not require detailed information on the distribution of historical errors. A comparison of TC-FF and JTWC operational ensembles, both based on DeMaria et al. (2009), revealed minor differences of <10 %, suggesting that TC-FF can be employed as an alternative, for example, in data-scarce environments. The method was applied to Cyclone Idai in Mozambique. The underlying physical model showed reliable skill in terms of tidal propagation, reproducing the storm surge generation during landfall and flooding near the city of Beira (success index of 0.59). The method was successfully applied to forecasting the impact of Idai with different lead times. The case study analyzed needed at least 200 ensemble members to get reliable water levels and flood results 3 d before landfall (<1 % flood probability error and <20 cm sampling errors). Results showed the sensitivity of forecasting, especially with increasing lead times, highlighting the importance of accounting for cyclone variability in decision-making and risk management.

An unstructured hydrodynamic model is presented that is able to simulate 2D nearshore hydrodynamics on the wave group scale. A non-stationary wave driver with directional spreading, with physics similar to XBeach (Roelvink et al., 2009) is linked to an improved and extended version of the existing unstructured flow solver Delft3D–FM (Kernkamp et al., 2011; Martyr-Koller et al., 2017). The model equations are discretised on meshes consisting of triangular and rectangular elements. The model allows for coverage of the model domain with locally optimised resolution to accurately resolve the dominant processes, yet with a smaller total number of grid cells. The model also allows a larger explicit time step, compared to structured models with similar functionality. The model reliably reproduces measured datasets of water levels, sea/swell and low frequency wave heights in laboratory and field conditions, and is as such widely deployable in a variety of simple and complex coastal settings to study nearshore hydrodynamics.

As climate-change-driven extremes potentially make coastal areas more vulnerable, mangroves can help sustainably protect the coasts. There is a substantial understanding of both mangrove dynamics and hydro-morphodynamic processes. However, the knowledge of complex eco-geomorphic interactions with physical-environmental stressors remains lacking. We introduce a novel coupled modelling approach consisting of an individual-based mangrove (mesoFON) and a process-based hydromorphodynamic model (Delft3D-FM). This coupled model is unique because it resolves spatiotemporal processes, including tidal, seasonal, and decadal environmental changes (water level, flow, sediment availability, and salinity) with full life-stages (propagule, seedling, sapling, mature) mangrove interaction. It allows us to mechanistically simulate forest expansion, retreat, and colonisation influenced by and with feedback on physical-environmental drivers. The model is applied in a schematized mixed fluvial-tidal deltaic mangrove forest in dominantly muddy sediment inspired by the prograding delta of Porong, Indonesia. Model results successfully reproduce observed mangrove extent development, age-height relationship, and morphodynamic delta features.

Intertidal shoals are key features of estuarine environments worldwide. Climate change poses questions regarding the sustainability of intertidal areas under sea-level rise (SLR). Our work investigates the SLR impact on the long-term morphological evolution of unvegetated intertidal sandy shoals in a constrained channel-shoal system. Utilizing a process-based model (Delft3D), we schematize a short tidal system in a rectangular (2.5 × 20 km) basin with a high-resolution grid. An initial, mildly sloping, bathymetry is subjected to constant semidiurnal tidal forcing, sediment supply, and small wind-generated waves modeled by SWAN. A positive morphodynamic feedback between hydrodynamics, sediment transport, and morphology causes the emergence of large-scale channel-shoal patterns. Over centuries, tide-residual sediment transport gradually decreases leading to a state of low morphological activity balanced by tides, waves, and sediment supply. Tidal currents are the main driver of the SLR morphodynamic adaptation. Wave action leads to wider and lower shoals but does not fundamentally change the long-term morphological evolution. SLR causes increased flood dominance which triggers sediment import into the system. Shoals accrete in response to SLR with a lag that increases as SLR accelerates, eventually causing intertidal shoals to drown. Seaward shoals near the open boundary sediment source have higher accretion rates compared to landward shoals. Similarly, on a shoal-scale, the highest accretion rates occur at the shoal edges bounding the sediment suppling channels. A larger sediment supply enhances the SLR adaptation. Waves help distribute sediment supplied from channels across shoals. Adding mud fractions leads to faster, more uniform, accretion and muddier shoals under SLR.

Understanding directional spectra of infragravity (IG) waves composed of free and bound components is required due to their impacts on various coastal processes (e.g., coastal inundation and morphological change). However, conventional reconstruction methods of directional spectra relying on linear wave theory are not applicable to IG waves in intermediate water depths (20–30 m) due to the presence of bound waves. Herein, a novel method is proposed to reconstruct directional spectra of IG waves in intermediate depth based on weakly nonlinear wave theory. This method corrects cross-spectra among observed wave signals by taking account of the nonlinearity of bound waves in order to reconstruct directional spectra of free IG waves. Numerical experiments using synthetic data representing various directional distributions show that the proposed method reconstructs free IG wave directional spectra more accurately than the conventional method. The method is subsequently applied to observations of severe sea-states at two field sites. At these sites, free IG waves are not isotropic and have clear peak directions. Numerical modeling of the wave fields shows that these peak directions correspond to the reflection of IG waves from the shore and/or coastal structures. Additionally, the validity of the underlying weakly nonlinear wave theory of the present method is assessed by a newly proposed method employing bispectral analysis. The bound wave response generally agrees with the theory at the field sites but deviates slightly for energetic sea states. The applicability of the present method on a sloping bottom is further discussed by an analytical solution.

This review focuses on recent advances in process-based numerical models of the impact of extreme storms on sandy coasts. Driven by larger-scale models of meteorology and hydrodynamics, these models simulate morphodynamics across the Sallenger storm-impact scale, including swash,collision, overwash, and inundation. Models are becoming both wider (as more processes are added) and deeper (as detailed physics replaces earlier parameterizations). Algorithms for wave-induced flows and sediment transport under shoaling waves are among the recent developments. Community and open-source models have become the norm. Observations of initial conditions (topography, land cover, and sediment characteristics) have become more detailed, and improvements in tropical cyclone and wave models provide forcing (winds, waves, surge, and upland flow) that is better resolved and more accurate, yielding commensurate improvements in model skill. We foresee that future storm-impact models will increasingly resolve individual waves, apply data assimilation, and be used in ensemble modeling modes to predict uncertainties.

Coastal mangroves, thriving at the interface between land and sea, provide robust flood risk reduction. Projected increases in the frequency and magnitude of climate impact drivers such as sea level rise and wind and wave climatology reinforce the need to optimize the design and functionality of coastal protection works to increase resilience. Doing so effectively requires a sound understanding of the local coastal system. However, data availability particularly at muddy coasts remains a pronounced problem. As such, this paper captures a unique dataset for the Guyana coastline and focuses on relations between vegetation (mangrove) density, wave attenuation rates and sediment characteristics. These processes were studied along a cross-shore transect with mangroves fringing the coastline of Guyana. The data are publicly available at the 4TU Centre for Research Data (4TU.ResearchData) via https://doi.org/10.4121/c.5715269 (Best et al., 2022) where the collection Advancing Resilience Measures for Vegetated Coastline (ARM4VEG), Guyana, comprises of six key datasets.

Suspended sediment concentrations typically exceeded 1 g L−1 with a maximum of 60 g L−1, implying that we measured merely fluid-mud conditions across a 1 m depth. Time series of wind waves and fluid-mud density variations, recorded simultaneously with tide elevation and suspended sediment data, indicate that wave–fluid-mud interactions in the nearshore may be largely responsible for the accumulation of fine, muddy sediment along the coast. Sediment properties reveal a consolidated underlying bed layer. Vegetation coverage densities in the Avicennia-dominated forest were determined across the vertical with maximum values over the first 20 cm from the bed due to the roots and pneumatophores.

Generalized total wave attenuation rates in the forest and along the mudflat were between 0.002–0.0032 m−1 and 0.0003–0.0004 m−1 respectively. Both the mangroves and the mudflats have a high wave-damping capacity. The wave attenuation in the mangroves is presumably dominated by energy losses due to vegetation drag, since wave attenuation due to bottom friction and viscous dissipation on the bare mudflats is significantly lower than wave dissipation inside the mangrove vegetation. Data collected corroborate the coastal defence function of mangroves by quantifying their contribution to wave attenuation and sediment trapping. The explicit linking of these properties to vegetation structure facilitates modelling studies investigating the mechanisms determining the coastal defence capacities of mangroves.

Fluvial, tidal, and combined hydro-morphodynamics interaction in a complex, seasonal, sediment transport regime has been the subject of extensive research. It becomes particularly challenging when there is limited data. The Ganges-Brahmaputra-Meghna (GBM) Delta is one example of a huge system lacking data. Bathymetric data simultaneously covering the rivers and estuaries is hardly present, let alone sequences of bathymetries or a system-wide sediment budget. Hence it is difficult to understand and predict future developments. This research aims to make a sediment budget for the GBM delta with a process-based model. It is a first-ever sediment budget simulation for the GBM system. A process-based morphological model, Delft3D, has been used to reproduce the bathymetric evolution over time and the associated sediment budget. This chapter demonstrates the possibilities for the application of a robust modeling system to assess the morphodynamic evolution and sediment budget and pathways. The Ganges and Jamuna rivers carry sediment load in the ranges of 216–1038 million tonnes/yr and 80–228 million tonnes/yr respectively. The total accumulation in the estuary system is 1150 million tonnes/yr, out of which more than eighty percent of sediment is in suspension. The model results show that about 22% of the total sediment coming into the system is deposited in the floodplains and tidal plains and causes river morphology changes. The rest of the sediment is lost to the pro-delta, to the deep ocean bed, or leaves the domain. The results also indicate that Padma, Gorai, Pussur-Sibsa, Bishkhali, Shahbajpur channel, Lower Meghna, Tentulia Channel, and Arial Khan rivers are mainly in the aggrading phase, whereas, the Ganges, Jamuna, and Baleshwar are in the degrading phase. This particular delta model offers many opportunities to compare with sediment data, where it deals with a poorly surveyed area.

This study aims at developing a new set of equations of mean motion in the presence of surface waves, which is practically applicable from deep water to the coastal zone, estuaries, and outflow areas. The generalized Lagrangian mean (GLM) method is employed to derive a set of quasi-Eulerian mean three-dimensional equations of motion, where effects of the waves are included through source terms. The obtained equations are expressed to the second-order of wave amplitude. Whereas the classical Eulerian-mean equations of motion are only applicable below the wave trough, the new equations are valid until the mean water surface even in the presence of finite-amplitude surface waves. A two-dimensional numerical model (2DV model) is developed to validate the new set of equations of motion. The 2DV model passes the test of steady monochromatic waves propagating over a slope without dissipation (adiabatic condition). This is a primary test for equations of mean motion with a known analytical solution. In addition to this, experimental data for the interaction between random waves and a mean current in both non-breaking and breaking waves are employed to validate the 2DV model. As shown by this successful implementation and validation, the implementation of these equations in any 3D model code is straightforward and may be expected to provide consistent results from deep water to the surf zone, under both weak and strong ambient currents.

This article presents a novel approach to explore mangrove dynamics on a prograding delta by integrating unmanned aerial vehicle (UAV) and satellite imagery. The Porong Delta in Indonesia has a unique geographical setting with rapid delta development and expansion of the mangrove belt. This is due to an unprecedented mud load from the LUSI mud volcanic eruption. The mangrove dynamics analysis combines UAV-based Structure from Motion (SfM) photogrammetry and 11 years (2009–2019) satellite imagery cloud computing analysis by Google Earth Engine (GEE). Our analysis shows unique, high-spatiotemporal-resolution mangrove extent maps. The SfM pho-togrammetry analysis leads to a 3D representation of the mangrove canopy and an estimate of mangrove biophysical properties with accurate height and individual position of the mangroves stand. GEE derived vegetation indices resulted in high (three-monthly) resolution mangrove coverage dynamics over 11 years (2009–2019), yielding a value of more than 98% for the overall, producer and consumer accuracy. Combining the satellite-derived age maps and the UAV-derived spatial tree structure allowed us to monitor the mangrove dynamics on a rapidly prograding delta along with its structural attributes. This analysis is of essential value to ecologists, coastal managers, and poli-cymakers.

In numerical ocean models, the effect of waves on currents is usually expressed by either vortex-force or radiation stress representations. In this paper, the differences and similarities between those two representations are investigated in detail in conditions of both conservative and nonconservative waves. In addition, comparisons between different sets of equations of mean motion that apply different representations of wave-induced forcing terms are included. The comparisons are useful for selecting a suitable numerical ocean model to simulate the mean current in conditions of waves combined with currents.

Building high dykes is a common measure of coping with floods and plays an important role in agricultural management in the Vietnamese Mekong Delta. However, the construction of high dykes causes considerable changes in hydrodynamics of the Mekong River. This paper aims to assess the impact of the high-dyke system on water level fluctuations and tidal propagation in the Mekong River branches. We developed a coupled 1-D to 2-D unstructured grid using Delft3D Flexible Mesh software. The model domain covered the Mekong Delta extending to the East (South China Sea) and West (Gulf of Thailand) seas, while the scenarios included the presence of high dykes in the Long Xuyen Quadrangle (LXQ), the Plain of Reeds (PoR) and the Trans-Bassac regions. The model was calibrated for the year 2000 high-flow season. Results show that the inclusion of high dykes changes the percentages of seaward outflow through the different Mekong branches and slightly redistributes flow over the low-flow and high-flow seasons. The LXQ and PoR high dykes result in an increase in the daily mean water levels and a decrease in the tidal amplitudes in their adjacent river branches. Moreover, the different high-dyke systems not only have an influence on the hydrodynamics in their own branch, but also influence other branches due to the Vam Nao connecting channel. These conclusions also hold for the extreme flood scenarios of 1981 and 1991 that had larger peak flows but smaller flood volumes. Peak flood water levels in the Mekong Delta in 1981 and 1991 are comparable to the 2000 flood as peak floods decrease and elongate due to upstream flooding in Cambodia. Future studies will focus on sediment pathways and distribution as well as climate change impact assessment.

With large-scale human interventions and climate change unfolding as they are now, coastal changes at decadal timescales are not limited to incremental modifications of systems that are fixed in their general geometry, but often show significant changes in layout that may be catastrophic for populations living in previously safe areas. This poses severe challenges that are difficult to meet for existing models. A new free-form coastline model, ShorelineS, is presented that is able to describe large coastal transformations based on relatively simple principles of alongshore transport gradient driven changes as a result of coastline curvature, including under highly obliquely incident waves, and consideration of splitting and merging of coastlines, and longshore transport disturbance by hard structures. An arbitrary number of coast sections is supported, which can be open or closed and can interact with each other through relatively straightforward merging and splitting mechanisms. Rocky parts or structures may block wave energy and/or longshore sediment transport. These features allow for a rich behavior including shoreline undulations and formation of spits, migrating islands, merging of coastal shapes, salients and tombolos. The main formulations of the (open-source) model, which is freely available at www.shorelines.nl, are presented. Test cases show the capabilities of the flexible, vector-based model approach, while field validation cases for a large-scale sand nourishment (the Sand Engine; 21 million m3) and an accreting groin scheme at Al-Gamil (Egypt) show the model’s capability of computing realistic rates of coastline change as well as a good representation of the shoreline shape for real situations.

Prediction of the shoreline response behind offshore breakwaters is essential for coastal protection projects. Due to the complexity of the processes behind the breakwaters (e.g., wave diffraction, currents, longshore transport), detailed modelling needs high computational efforts. Therefore, simplifying the process effect in a simpler coastline model could be efficient. In this study, the coastline evolution model ShorelineS is used. A new routine was implemented in the model to adjust the wave heights and angles behind the offshore breakwaters. Two approaches from the literature and a newly introduced one were tested in this study. The model free grid system was used to simply track the breaker line; such an advantage also helped to form tombolo, which is not common for these types of models. The tests showed promising results for single and multi breakwaters systems; however, the newly introduced approach still needs further testing and refinement for better performance and less computational cost.

Bathymetric data plays a major role in obtaining accurate results in hydrodynamic modeling of rivers, estuaries, and coasts. Bathymetries are commonly generated by spatial interpolation methods of data on a model grid. Sparse and limited data will impact the quality of the interpolated bathymetry. This study proposes an efficient spatial interpolation framework for producing a channel bathymetry from sparse, cross-sectional data. The proposed approach consists of three steps: (1) anisotropic bed topography data locations transformed to an orthogonal and smooth grid coordinate system that is aligned with its riverbanks and thalweg; (2) sample data are linearly interpolated to generate river bathymetry; and (3) the generated river bathymetry is converted into its original coordinates. The proposed approach was validated with a high spatial resolution topography of the Tieu estuarine branch. In addition, the proposed approach is compared with other spatial interpolation methods such as ordinary kriging, inverse distance weighting, and kriging with external drift. The proposed approach gives a nearly unbiased topography and a strongly reduced RMSE compared with the other methods. In addition, it accurately reproduces the thalweg. The proposed approach appears to be efficiently applicable for regions with sparse cross-sections. Moreover, river topography generated by the proposed approach is smooth including important morphologic features, making it suitable for two- and three-dimensional hydrodynamic modeling.