Global climate changes have accelerated sea-level rise (SLR), which exacerbates the risks of coastal flooding and erosion. It is of practical interest to understand the long-term hydro-morphodynamic adaptation of coastal systems to SLR at a century time scale. In this work we use a numerical model to explore morphodynamic evolution of a schematized tidal basin in response to SLR of 0.25–2.0 m over 100 years with special emphasis on the impact of lateral basin expansion. Starting from a sloped initial bed, morphodynamic development of the system leads to the formation of alternating bars and meandering channels inside the tidal basin and an ebb-tidal delta extending seaward from the basin. Imposing rising sea level causes progressive inundation of the low-lying floodplains, found along the basin margins, inducing an increase in basin plain area and tidal prism, as well as intertidal area and storage volume. Although the overall channel-shoal structure persists under SLR, lateral shoreline expansion alters the basin hypsometry, leading to enhanced sediment export. The newly-submerged floodplains partly erode, supplying sediment to the system for spatial redistribution, hence buffering the impact of SLR. The vertical accretion rate of the tidal flats inside the tidal basin lags behind the rate of SLR. However, lateral shoreline migration under SLR creates new intertidal flats, compensating intertidal flat loss in the original basin. In contrast, a constrained tidal basin without low-lying floodplains is subject to profound drowning and tidal flat losses under SLR. Overall, the model results suggest that an unconstrained tidal system allowing lateral shoreline migration has buffering capacity for alleviating the drowning impact of SLR by evolving new intertidal areas, sediment redistribution and morphodynamic adjustment. These findings suggest that preserving tidal flats located along the margins of tidal basins (instead of reclaiming them) sustains the system's resilience to SLR.@en

Many large rivers in the world delivers decreasing sediment loads to coastal oceans owing to reductions in sediment yield and disrupted sediment deliver. Understanding the sediment load regime is a prerequisite of sediment management and fluvial and deltaic ecosystem restoration. This work examines sediment load changes across the Changjiang River basin based on a long time series (1950–2017) of sediment load data stretching from the headwater to the delta. We find that the sediment loads have decreased progressively throughout the basin at multiple time scales. The sediment loads have decreased by ~96% and ~74% at the outlets of the upper basin and entire basin, respectively, in 2006–2017 compared to 1950–1985. The hydropower dams in the mainstem have become a dominant cause of the reduction, although downstream channel erosion causes moderate sediment load recovery. The basin-scale sediment connectivity has declined as the upper river is progressively dammed, the middle-lower river is leveed and river-lake interplay weakens. The middle-lower river has changed from a slight depositional to a severe erosional environment, from a sediment transport conduit to a new sediment source zone, and from a transport-limited to a supply-limited condition. These low-level sediment loads will likely persist in the future considering the cumulative dam trapping and depleted channel erosion. As a result, substantial hydro-morphological changes have occurred that affect the water supply, flood mitigation, and the aquatic ecosystem. The findings and lessons in this work can shed light on other large river systems subject to intensified human interference.@en

River discharge is known to enhance tidal damping and tidal wave deformation in estuaries. While the damping effect on astronomical tides has been well documented, river impact on tidal wave deformation and associated overtide generation (shallow water harmonics of one or more astronomical constituents, such as M4) remains insufficiently understood. Overtides affect tidal asymmetry, extreme water levels, and subsequent sediment transport and flooding management, thus meriting in-depth examination. Being inspired by unusual overtide changes in the landward and seaward parts of the Changjiang Estuary under low and high river discharges, in this work, we use a schematized tidal estuary model to systematically explore overtide variations under different river discharges. Model results show enhanced overtide generation in the case with river discharge compared with that without river impact. The M4 amplitude decreases in the landward parts of the estuary, but increases in the seaward parts under increasing river discharges. The potential energy of M4 integrated throughout the estuary shows nonlinear variations and reaches a transitional maximum when the river discharge to tidal mean discharge (R2T) ratio at the mouth is close to unity. Similar nonlinear behaviors are observed for compound tides like MS4 when more astronomical constituents are prescribed and triad tidal interactions are enabled. The space-dependent overtide variability is more profound in large estuaries with high river discharges like the Amazon and Changjiang estuaries. It is ascribed to the inherently nonlinear river-tide interactions, specifically the twofold effects of river discharge in enhancing bottom stress, which simultaneously enhances dissipation of astronomical constituents and reinforces the energy transfer to overtides. These findings highlight the profound nonlinear impact of river discharge on overtides, and inform the study of tidal asymmetry and compound flood risk in large estuaries and deltas.@en

A better understanding of how tidal-flat reclamation changes the flood hazard is critical for climate-proofing coastal flood defense design of heavily urbanized areas. Since the 1950s, large-scale reclamation has been performed along the Shanghai coast, China, to fulfill the land demands of city expansion. We now show that the loss of tidal flats may have resulted in harmful impacts of coastal storm flooding. Using the foreshore profiles measured before and after reclamation (i.e., wide vs. narrow tidal flat), we determined the long-term changes in flood risk using a numerical model that combines extreme tidal level and wave overtopping analysis. Results show that wide tidal flats in front of a seawall provide efficient wave damping even during extreme water levels. Reclamation of these tidal flats substantially increased wave heights and correspondingly reduced the return period of a specific storm. As a result, estimates of overtopping are aggravated by more than 80% for the varying return periods examined. It is concluded that the disasters of coastal flooding after the 1997 tidal-flat reclamation in Hangzhou Bay, China are a consequence of both anthropogenic and natural activities. Moreover, our model calculations provide an equation describing the equivalent dike height needed to compensate for the loss of every km tidal flat of a certain elevation, and vice versa. For example, for every km of tidal flat ranging from high marsh to bare tidal flat that is being regained, the dike can be lowered by 0.84 m–0.67 m, when designing for a 1 in 200 years storm event. Overall, we suggest that wide tidal flats are ideally restored in front of dikes, and that when tidal areas are reclaimed, the seawall height is raised as part of the intertidal reclamation procedure. Using such an equivalent protection standard is relevant to designing hybrid flood defense system worldwide.@en

Reclamation of low-lying tidal flats and floodplains adjacent to present shorelines has been implemented worldwide for both coastal defense and development. While it is technically feasible to monitor the short-term impact of tidal flat embankments, it is challenging to identify long-term and cumulative morphodynamic impact, particularly considering centennial sea-level rise (SLR). In this study, we construct a process-based hydro-morphodynamic model for a schematized tidal basin and examine its morphodynamic evolution under the combined influence of SLR and tidal flat embankments. We see that rising sea levels lead to inundation of low-lying floodplains just above high water, creating new intertidal flats that mitigate the drowning impact of SLR. This mitigation effect is lost if the low-lying floodplains and tidal flats are reclaimed, preventing any shoreline migration under SLR. Removing a large portion of intertidal flats within the tidal basin induces significant changes in basin hypsometry and potentially, a reversal of flood/ebb dominance. The resulting hydro-morphodynamic impact of large-scale tidal flat embankment is more significant than SLR at a centennial time scale. This suggests a need for much greater management awareness regarding the cumulative impact of human activities. These findings imply that allowing lateral shoreline migration under SLR sustains tidal basin's inherent morphodynamic buffering capacity, whereas reclaiming tidal flats significantly alters hydro-morphodynamic adaptation at the decadal to centennial time scales. It highlights the importance of conserving low-lying floodplains and tidal flats in tide-dominated systems to counteract the drowning impact of SLR.@en

Simple stability relationships are practically useful to provide a rapid assessment of coastal and estuarine landforms in response to human interventions and long‐term climate change. In this contribution, we review a variety of simple stability relationships which are based on the analysis of tidal asymmetry (shortened to “TA”). Most of the existing TA‐based stability relationships are derived using the one‐dimensional tidal flow equations assuming a certain regular shape of the tidal channel cross‐sections. To facilitate analytical solutions, specific assumptions inevitably need to be made e.g. by linearising the friction term and dropping some negligible terms in the tidal flow equations. We find that three major types of TA‐based stability relationships have been proposed between three non‐dimensional channel geometric ratios (represented by the ratio of channel widths, ratio of wet surface areas and ratio of storage volumes) and the tide‐related parameter a/h (i.e. the ratio between tidal amplitude and mean water depth). Based on established geometric relations, we use these non‐dimensional ratios to re‐state the existing relationships so that they are directly comparable. Available datasets are further extended to examine theutility of these TA‐based relationships. Although a certain agreement is shown for these relationships, we also observe a large scatter of data points which are collected in different types of landscape, hydrodynamic and sedimentologic settings over the world. We discuss in detail the potential reasons for this large scatter and subsequently elaborate on the limited applicability of the various TA‐based stability relationships for practical use. We highlight the need to delve further into what constitutes equilibrium and what is needed to develop more robust measures to determine the morphological state of these systems.@en

Tidal wave deformation and tidal asymmetry widely occur in tidal estuaries and lagoons. Tidal asymmetry has been intensively studied because of its controlling role on residual sediment transport and large‐scale morphological evolution. There are several methods available to characterize tidal asymmetry prompting the need for an overview of their applicability and shortcomings. In this work we provide a brief review and evaluation of two methods, namely, the harmonic method and the statistical method. The latter comprises several statistical measures that estimate the probability density function and various forms of skewness. We find that both the harmonic and statistical methods are effective and have complementary advantages. The harmonic method is applicable to predominantly semidiurnal or diurnal regimes, while the statistical methods can be used in mixed tidal regimes. Assisted by harmonic data, a modified skewness measure can isolate the contribution of different tidal interactions on net tidal asymmetry and also reveal its subtidal variations. The application of the skewness measure to nonstationary river tides reveals stronger tidal asymmetry during spring tides than neap tides, and the nonlinear effects of river discharges on tidal asymmetry in the upper and lower regions of long estuaries.@en

Climate change, and especially the associated acceleration of sea-level rise, forms a serious threat to the Wadden Sea. The Wadden Sea contains the world’s largest coherent intertidal flat area and it is known that these flats can drown when the rate of sea-level rise exceeds a critical limit. As a result, the intertidal flats would then be permanently inundated, seriously affecting the ecological functioning of the system. The determination of this critical limit and the modelling of the transient process of how a tidal basin responds to accelerated sea-level rise is of critical importance. In this contribution we revisit the modelling of the response of the Wadden Sea tidal basins to sea-level rise using a basin scale morphological model (aggregated scale morphological interaction between tidal basin and adjacent coast, ASMITA). Analysis using this aggregated scale model shows that the critical rate of sea-level rise is not merely influenced by the morphological equilibrium and the morphological time scale, but also depends on the grain size distribution of sediment in the tidal inlet system. As sea-level rises, there is a lag in the morphological response, which means that the basin will be deeper than the systems morphological equilibrium. However, so long as the rate of sea-level rise is constant and below a critical limit, this offset becomes constant and a dynamic equilibrium is established. This equilibrium deviation as well as the time needed to achieve the dynamic equilibrium increase non-linearly with increasing rates of sea-level rise. As a result, the response of a tidal basin to relatively fast sea-level rise is similar, no matter if the sea-level rise rate is just below, equal or above the critical limit. A tidal basin will experience a long process of ‘drowning’ when sea-level rise rate exceeds about 80% of the critical limit. The insights from the present study can be used to improve morphodynamic modelling of tidal basin response to accelerating sea-level rise and are useful for sustainable management of tidal inlet systems.@en

Aggregation is used to represent the real world in a model at an appropriate level of abstraction. We used the convection-diffusion equation to examine the implications of aggregation progressing from a three-dimensional (3D) spatial description to a model representing a system as a single box that exchanges sediment with the adjacent environment. We highlight how all models depend on some forms of parametric closure, which need to be chosen to suit the scale of aggregation adopted in the model. All such models are therefore aggregated and make use of some empirical relationships to deal with sub-scale processes. One such appropriately aggregated model, the model for the aggregated scale morphological interaction between tidal basin and adjacent coast (ASMITA), is examined in more detail and used to illustrate the insight that this level of aggregation can bring to a problem by considering how tidal inlets and estuaries are impacted by sea level rise.@en

Tidal waves traveling into estuaries are modified by channel geometry and river flow. The damping effect of river flow on incident astronomical tides is well documented, whereas its impact on low‐frequency tides like MSf and Mm is poorly understood. In this contribution, we employ a numerical model to explore low‐frequency tidal behavior under varying river flow. MSf and Mm are locally generated by frictional mechanisms inside an estuary, and they are larger in amplitude far upstream in tidal rivers and persist landward of the point of tidal extinction. Increasing river flow nonlinearly modulates the longitudinal variations of MSf and Mm amplitudes. This is dynamically explained by flow‐enhanced asymmetry in subtidal friction over the spring‐neap (MSf) and perigee‐apogee (Mm) cycles, respectively. Estuaries act as frequency filters, where low‐frequency waves decay at a smaller rate and propagate more inland than high‐frequency waves. Strong inland penetration of low‐frequency tides informs compound flood management.@en

The geomorphology of the Yangtze Estuary in the Changjiang River Delta in Eastern China has been the subject of extensive research. This study extends previous work to examine the influence of wind-waves on the mouth-bar, where about half of the river-borne material settles to the bed. The site is located just outside of Changjiang River mouth, which is meso-tidal and subject to seasonally varying river flows and wind-wave conditions. Modeling was performed with a coupled wave-current hydrodynamic model using TELEMAC and TOMAWAC and validated against observed data. Bottom Shear Stress (BSS) from river, tide and waves based on the numerical model output was used to infer the respective contribution to the evolution of the subaqueous delta. Our examination did not however extend to modeling the sediment transport or the morphological bed changes. The results suggest that (i) the dominance of river discharge is limited to an area inside the mouth, while outside, the mouth-bar is tide-wave dominant; (ii) considering just the tide, the currents on the shallow shoals are flood dominant and deep channels are ebb dominant, which induces continued accretion over the shallows and erodes the deeper parts of the mouth-bar until the tidal currents become too weak to transport sediment; (iii) whereas waves are very efficient at reshaping the shallow shoals, with the effect being subtly dependent on the depth distribution over the mouth-bar; (iv) the stability of shallow shoal morphology is highly dependent on the presence of seasonal wind-waves and characterized as “summer storing and winter erosion” while deep channels perform like corridors of water and sediment, exporting sediment all year round. The nature of the mouth-bar response has important implications for coastal management, such as the ongoing deep water channel maintenance, reclamations and coastal defense measures.@en

The geomorphology of the Yangtze Estuary in the Changjiang River Delta in Eastern China has been the subject of extensive research. This study extends previous work to examine the influence of wind-waves on the mouth-bar, where about half of the river-borne material settles to the bed. The site is located just outside of Changjiang River mouth, which is meso-tidal and subject to seasonally varying river flows and wind-wave conditions. Modeling was performed with a coupled wave-current hydrodynamic model using TELEMAC and TOMAWAC and validated against observed data. Bottom Shear Stress (BSS) from river, tide and waves based on the numerical model output was used to infer the respective contribution to the evolution of the subaqueous delta. Our examination did not however extend to modeling the sediment transport or the morphological bed changes. The results suggest that (i) the dominance of river discharge is limited to an area inside the mouth, while outside, the mouth-bar is tide-wave dominant; (ii) considering just the tide, the currents on the shallow shoals are flood dominant and deep channels are ebb dominant, which induces continued accretion over the shallows and erodes the deeper parts of the mouth-bar until the tidal currents become too weak to transport sediment; (iii) whereas waves are very efficient at reshaping the shallow shoals, with the effect being subtly dependent on the depth distribution over the mouth-bar; (iv) the stability of shallow shoal morphology is highly dependent on the presence of seasonal wind-waves and characterized as “summer storing and winter erosion” while deep channels perform like corridors of water and sediment, exporting sediment all year round. The nature of the mouth-bar response has important implications for coastal management, such as the ongoing deep water channel maintenance, reclamations and coastal defense measures.@en

Beaches around the world continuously adjust to daily and seasonal changes in wave and tide conditions, which are themselves changing over longer time-scales. Different approaches to predict multi-year shoreline evolution have been implemented; however, robust and reliable predictions of shoreline evolution are still problematic even in short-term scenarios (shorter than decadal). Here we show results of a modelling competition, where 19 numerical models (a mix of established shoreline models and machine learning techniques) were tested using data collected for Tairua beach, New Zealand with 18 years of daily averaged alongshore shoreline position and beach rotation (orientation) data obtained from a camera system. In general, traditional shoreline models and machine learning techniques were able to reproduce shoreline changes during the calibration period (1999–2014) for normal conditions but some of the model struggled to predict extreme and fast oscillations. During the forecast period (unseen data, 2014–2017), both approaches showed a decrease in models’ capability to predict the shoreline position. This was more evident for some of the machine learning algorithms. A model ensemble performed better than individual models and enables assessment of uncertainties in model architecture. Research-coordinated approaches (e.g., modelling competitions) can fuel advances in predictive capabilities and provide a forum for the discussion about the advantages/disadvantages of available models.@en

Beaches around the world continuously adjust to daily and seasonal changes in wave and tide conditions, which are themselves changing over longer time-scales. Different approaches to predict multi-year shoreline evolution have been implemented; however, robust and reliable predictions of shoreline evolution are still problematic even in short-term scenarios (shorter than decadal). Here we show results of a modelling competition, where 19 numerical models (a mix of established shoreline models and machine learning techniques) were tested using data collected for Tairua beach, New Zealand with 18 years of daily averaged alongshore shoreline position and beach rotation (orientation) data obtained from a camera system. In general, traditional shoreline models and machine learning techniques were able to reproduce shoreline changes during the calibration period (1999–2014) for normal conditions but some of the model struggled to predict extreme and fast oscillations. During the forecast period (unseen data, 2014–2017), both approaches showed a decrease in models’ capability to predict the shoreline position. This was more evident for some of the machine learning algorithms. A model ensemble performed better than individual models and enables assessment of uncertainties in model architecture. Research-coordinated approaches (e.g., modelling competitions) can fuel advances in predictive capabilities and provide a forum for the discussion about the advantages/disadvantages of available models.@en

Beaches around the world continuously adjust to daily and seasonal changes in wave and tide conditions, which are themselves changing over longer time-scales. Different approaches to predict multi-year shoreline evolution have been implemented; however, robust and reliable predictions of shoreline evolution are still problematic even in short-term scenarios (shorter than decadal). Here we show results of a modelling competition, where 19 numerical models (a mix of established shoreline models and machine learning techniques) were tested using data collected for Tairua beach, New Zealand with 18 years of daily averaged alongshore shoreline position and beach rotation (orientation) data obtained from a camera system. In general, traditional shoreline models and machine learning techniques were able to reproduce shoreline changes during the calibration period (1999–2014) for normal conditions but some of the model struggled to predict extreme and fast oscillations. During the forecast period (unseen data, 2014–2017), both approaches showed a decrease in models’ capability to predict the shoreline position. This was more evident for some of the machine learning algorithms. A model ensemble performed better than individual models and enables assessment of uncertainties in model architecture. Research-coordinated approaches (e.g., modelling competitions) can fuel advances in predictive capabilities and provide a forum for the discussion about the advantages/disadvantages of available models.@en

Beaches around the world continuously adjust to daily and seasonal changes in wave and tide conditions, which are themselves changing over longer time-scales. Different approaches to predict multi-year shoreline evolution have been implemented; however, robust and reliable predictions of shoreline evolution are still problematic even in short-term scenarios (shorter than decadal). Here we show results of a modelling competition, where 19 numerical models (a mix of established shoreline models and machine learning techniques) were tested using data collected for Tairua beach, New Zealand with 18 years of daily averaged alongshore shoreline position and beach rotation (orientation) data obtained from a camera system. In general, traditional shoreline models and machine learning techniques were able to reproduce shoreline changes during the calibration period (1999–2014) for normal conditions but some of the model struggled to predict extreme and fast oscillations. During the forecast period (unseen data, 2014–2017), both approaches showed a decrease in models’ capability to predict the shoreline position. This was more evident for some of the machine learning algorithms. A model ensemble performed better than individual models and enables assessment of uncertainties in model architecture. Research-coordinated approaches (e.g., modelling competitions) can fuel advances in predictive capabilities and provide a forum for the discussion about the advantages/disadvantages of available models.@en

Beaches around the world continuously adjust to daily and seasonal changes in wave and tide conditions, which are themselves changing over longer time-scales. Different approaches to predict multi-year shoreline evolution have been implemented; however, robust and reliable predictions of shoreline evolution are still problematic even in short-term scenarios (shorter than decadal). Here we show results of a modelling competition, where 19 numerical models (a mix of established shoreline models and machine learning techniques) were tested using data collected for Tairua beach, New Zealand with 18 years of daily averaged alongshore shoreline position and beach rotation (orientation) data obtained from a camera system. In general, traditional shoreline models and machine learning techniques were able to reproduce shoreline changes during the calibration period (1999–2014) for normal conditions but some of the model struggled to predict extreme and fast oscillations. During the forecast period (unseen data, 2014–2017), both approaches showed a decrease in models’ capability to predict the shoreline position. This was more evident for some of the machine learning algorithms. A model ensemble performed better than individual models and enables assessment of uncertainties in model architecture. Research-coordinated approaches (e.g., modelling competitions) can fuel advances in predictive capabilities and provide a forum for the discussion about the advantages/disadvantages of available models.@en