This study presents a 3D process-based morphodynamic model that uses orthogonal unstructured grids. It is designed for coastal applications involving complex bathymetry and varying spatial scales. The model extends the Delft3D-FM framework by incorporating full 3D representation of wave, wind, and density-driven effects in the short-wave-averaged, non-linear shallow water equations. The framework includes expressions for wave and roller effects on flow forcing, turbulence, and bed shear stress, and integrates sediment transport and morphodynamic feedback. Multi-fraction sediment transport is supported, and the model tracks stratigraphy through a layered bed composition framework. Features such as infragravity wave dynamics, sediment mass slumping, swash zone slope nudging and morphological acceleration techniques are incorporated to better capture long-term morphological trends as well as storm erosion. The framework supports in-memory model coupling and is fully parallelized, enabling efficient, large-scale simulations. Model verifications presented here include analytical benchmarks and comparisons with laboratory and field observations, demonstrating reliable reproduction of wave–current interaction, sediment transport rates, and bed level changes. The model has the potential to bridge the gap between high-resolution event-scale modelling and long-term morphodynamic prediction, offering a flexible framework to study coastal sedimentary dynamics.

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 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.

Robust predictions of shoreline change are critical for sustainable coastal management. Despite advancements in shoreline models, objective benchmarking remains limited. Here we present results from ShoreShop2.0, an international collaborative benchmarking workshop, where 34 groups submitted shoreline change predictions in a blind competition. Subsets of shoreline observations at an undisclosed site (BeachX) over short (5-year) and medium (50-year) periods were withheld from modelers and used for model benchmarking. Using satellite-derived shoreline datasets for calibration and evaluation, the best performing models achieved prediction accuracies on the order of 10 m, comparable to the accuracy of the satellite shoreline data, indicating that certain beaches can be modelled nearly as well as they can be remotely observed. The outcomes from this collaborative benchmarking competition critically review the present state-of-the-art in shoreline change prediction as well as reveal model limitations, facilitate improvements, and offer insights for advancing shoreline-prediction capabilities.

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.

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.

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.

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.