Wetland Ecological Restoration and Geomorphological Evolution: A Hydrodynamic-Sediment-Vegetation Coupled Modeling Study

Abstract

This study developed a coupled hydrodynamic-sediment-vegetation model to investigate the effects of Spartina alterniflora management and Suaeda salsa restoration on coastal wetland geomorphological evolution and vegetation distribution. Special attention is paid to the regulatory roles of tidal dynamics, sea-level rise, sediment supply, and sediment characteristics. The study shows that the management of Spartina alterniflora significantly alters the sediment deposition patterns in salt marsh wetlands, leading to intensified local erosion and a decline in the overall stability of the wetland system; meanwhile, the geomorphology of wetlands restored with Suaeda salsa is influenced by tidal range, sediment settling velocity, and suspended sediment concentration, exhibiting different deposition and erosion patterns. Under the scenario of sea-level rise, when sedimentation rates fail to offset the rate of sea-level increase, the wetland ecosystem faces the risk of collapse. This study provides scientific evidence for the ecological restoration and management of coastal wetlands and offers theoretical support for future wetland conservation and restoration policies.

1. Introduction

Wetland resources in China are widely distributed and diverse in type, with significant regional differences. The Yellow River Delta wetland is the most intact and expansive important wetland in China’s warm temperate zone. Its unique hydrodynamic-sediment-vegetation coupling process and geomorphological evolution mechanism have long been an important frontier in international coastal wetland ecology and geomorphology research.

Coastal salt marshes are typical coastal wetland ecosystems, mainly distributed in the upper intertidal zone, periodically inundated by tides, and inhabited by salt-tolerant plants such as Suaeda salsa, Spartina alterniflora, Tamarix, and Phragmites [1,2]. Recent studies highlight that marsh loss manifests through diverse pathways (drowning, edge erosion, pond expansion), yet integrated models capturing these multi-mechanism feedbacks remain limited [3]. Salt marshes not only provide ecological functions such as water purification, blue carbon sequestration, and biodiversity maintenance [4,5] but also effectively mitigate extreme marine disasters like storm surges, forming natural coastal protection [6,7].

Salt marsh plants play a key role in capturing sediment and maintaining geomorphological stability, earning them the title of “ecosystem engineers” [8]. They exhibit strong adaptability to sea-level changes and environmental disturbances [1]. However, when the rate of sea-level rise exceeds the sedimentation rate and the sediment budget is in negative balance, the salt marsh system faces degradation risks, manifested as subsidence of marsh surfaces, increased edge erosion, and reduced vegetation cover [9,10,11]. Their resilience is highly contingent on sediment supply and relative sea-level rise (RSLR) rates, with salt marshes particularly vulnerable to drowning under high RSLR [3]. In recent years, the area of coastal wetlands worldwide has continued to decrease under the dual impact of climate change and human activities [12,13].

A particular concern is the disturbance caused by invasive species to local ecosystems. Spartina alterniflora was introduced to China in the 1990s as a plant for stabilizing tidal flats. Initially, its distribution was sporadic, but since 2010, it has expanded explosively, with an average annual expansion rate of 25% [14]. By 2020, its distribution area had exceeded 6000 hectares. This expansion has significantly compressed native vegetation habitats, leading to a decline in biodiversity and seriously threatening the stability of salt marsh ecosystems [15,16]. Critically, simplistic eradication strategies may overlook functional trade-offs, as Spartina alterniflora can provide significant wave attenuation and carbon storage services depending on its spatial position [17]. Furthermore, large-scale removal efforts face significant challenges in monitoring effectiveness and predicting resultant sediment dynamics [18,19].

Changes in salt marsh vegetation not only affect ecological stability but also significantly regulate hydrodynamics and sediment processes. Vegetation cover increases water flow resistance, accelerates wave energy dissipation [20], and effectively promotes the settling of suspended sediments, which is a crucial mechanism for maintaining wetland elevation and mitigating sea-level rise. However, the removal of invasive species or vegetation degradation will alter sediment dynamics. Simulations suggest that when wetland area is reduced by 25%, its sediment capture capacity decreases by 50% [21]. A study based on the Delft3D model also shows that after vegetation removal, wetlands exhibit reduced sedimentation rates and localized erosion under the influence of storm surges [22]. Current predictive capabilities are hampered by insufficient integration of key processes and high-resolution observational data [23,24]. This gap limits our ability to forecast geomorphological consequences of management interventions under changing climates [3,23].

In this context, focusing on intertidal saltmarsh ecosystems, it is essential to systematically investigate the impacts of vegetation changes on coastal wetland disaster prevention and geomorphological evolution, given the critical regulatory role of saltmarsh vegetation in hydrodynamics and sediment transport. To this end, this study developed a numerical simulation model coupling hydrodynamics, sediment, and vegetation, through quantitatively simulating the hydrodynamic responses and geomorphological changes before and after the management of Spartina alterniflora, in conjunction with local vegetation restoration engineering practices, aiming to reveal the ecological-geographical synergistic evolution patterns of salt marshes.

2. Methods

2.1. Delft3D Model Setup

This study is based on field-measured topographic data from the northern shore tidal flat salt marsh wetland of the Qing Shui Gou River course in the Yellow River Delta, including typical features such as a shore slope of 0.001, the distribution patterns of dominant vegetation communities, and sediment composition parameters, to construct an idealized numerical model experiment. The initial topography of the model is set as a uniformly sloped plane, with the tidal flat elevation gradually decreasing from 1 m above mean sea level to 1 m below mean sea level. The slope increases below 1 m of mean sea level and connects to a deeper offshore basin, with a maximum water depth set at 5 m. A 1 cm random disturbance is introduced to the bed surface. The model’s computational domain is set as a rectangular area, extending 2.5 km in the cross-shore direction and 0.5 km in the along-shore direction. The shoreline boundary condition uses a fixed seawall boundary to simulate real engineering constraints. The computational grid uses a structured orthogonal grid with a spatial resolution of 10 m × 10 m to ensure fine representation of topographic changes and dynamic processes. The main model parameters are listed in

Table 1. Summary of model parameters.

Parameters	Values	Unit
Tidal Range	0.4–2.4	m
Tidal Period	12.5	h
Wave Height	0.4	m
Dry Bed Density	500	kg/m3
Fall/Settling Velocity	0.1–2.0	mm/s
Critical Bed Shear Stress for Erosion	0.1–0.7	N/m2
Critical Bed Shear Stress for Sedimentation	1000	N/m2
Open Boundary Suspended Sediment Concentration	0.01–0.1	kg/m3

. In this study, the vegetation morphology and biomechanical parameters were primarily derived from field measurements of dominant species in the Yellow River Delta, namely Spartina alterniflora and Suaeda salsa [25], and were parameterized with reference to the theory of vegetation-hydrodynamic interactions in tidal flats [26]. Detailed parameters are listed in

Table 2. Summary of plant parameters.

Parameters	Spartina alterniflora	Suaeda salsa	Unit
Seed, Chance of Establishment, Seed	0.01	0.01	/
Initial Plant Density, P0	50	50	stems/m2
Intrinsic Growth Rate, r	1	1	yr−1
Max. Carrying Capacity for the plant density, K	600	400	stems/m2
Plant Diffusion Coefficient, D	0.2	0.2	m−2·yr−1
Plant Erosion Coefficient due to Bed Shear Stress, Cτ	30	30	stems·m−2·(N·m−2)−1
Critical Bed Shear Stress for Plant Erosion, τcr	0.26	0.26	N/m2
Plant Erosion Coefficient due to Inundation Stress, Cinund	3000	3000	stems/m3
Critical Inundation Height at High Tide, Hcrp	1.4	0.8	m
Plant Canopy Drag Coefficient	2	1	/

. This study employs a tide-driven open boundary condition. The western boundary is driven by the M2 tidal constituent’s harmonic constant, with a tidal range set at 0.4–2.4 m (period: 12.5 h), combined with wave conditions, where significant wave height (Hs) is set at 0.4 m. The hydrodynamic parameters of the model (particularly the tidal range and wave characteristics) are based on the actual dynamic background of the study area [27]. The sediment boundary condition uses a constant suspended sediment concentration (0.01–0.1 kg/m³).

2.2. Dynamic Vegetation Model Approach

The vegetation growth module adopts a research method based on population dynamics theory [28,29]. However, for the micro-topography extension model of Delft3D-FLOW, this study improved the coupling technique of vegetation and its representation over different time scales, enabling it to simultaneously simulate vegetation dynamics in salt marshes and tidal flats. The net growth of vegetation can be expressed by the following equation: Equation (1): Net Vegetation Growth [26,29]

$$dP=d{P}_{est}+d{P}_{growth}+d{P}_{diffx}+d{P}_{diffy}-(d{P}_{inund}+d{P}_{flow})$$

(1)

In this model, $dP$ represents the rate of change in total stem density of salt marsh vegetation over time (in years) (unit: stems/m²), while $dPx$ represents the rate of change in stem density (unit: stems/m²) under the influence of different factors, with x representing establishment, growth, diffusion, inundation, and water flow shear stress. This bio-geomorphic coupling model was specifically developed to address the impact mechanisms of two vegetation types in the Yellow River Delta: Spartina alterniflora and Suaeda salsa. At the end of each vegetation time step, the model synchronously records the changes in parameters such as elevation, vegetation density, drag coefficient, bed roughness, and vegetation relative coverage within the computational grid. The vegetation roughness extension module of Delft3D (trachytope extension) is used to define the spatial distribution characteristics of vegetation within the computational domain. After each geomorphological dynamics time step, the results output by Delft3D (including bed elevation, shear stress, water level, and flow velocity) will be converted into input parameters for the vegetation growth model, primarily including inundation duration and shear stress. Subsequently, at the end of each vegetation growth time step, the updated roughness and flow resistance parameters will be rewritten into the trachytope input file. The roughness effect exerted by vegetation on water flow is quantified using a parameterized relationship established in previous studies [30], where a larger parameter value indicates a smoother surface and a smaller corresponding drag force. Subsequently, the Delft3D-FLOW model will restart the simulation based on the updated vegetation spatial distribution and bed elevation (Figure 1). The seasonal and diurnal variations in water level not only affect the spatiotemporal distribution pattern of vegetation but also influence the setting of hydrodynamic and geomorphological dynamics time steps. If bed elevation changes and vegetation growth are calculated at each hydrodynamic time step, it will significantly increase the computational load. Therefore, this study adopts a 100-fold acceleration factor (MF) to make a single tidal cycle represent three months of geomorphological evolution. The coupling of the vegetation growth model with Delft3D is executed every three months (i.e., every tidal cycle), and this coupling strategy effectively captures the seasonal dynamic characteristics of vegetation growth.

3. Results

3.1. Effects of Wetland Restoration on Tidal Flat Hydrodynamics and Vegetation-Topography Feedbacks

To clarify the regulatory mechanism of wetland ecological restoration projects on the hydrodynamic processes of tidal flats in the Yellow River Delta, this study developed three idealized scenario models: Scenario a represents the Original Spartina alterniflora-Invaded State, Scenario b represents the Secondary Bare Tidal Flat Degradation after the failure of Suaeda salsa restoration (the intertidal zone degraded into a barren landscape with no vegetation cover), Scenario c represents the Suaeda salsa Ecological Restoration Success (with the complete removal of Spartina alterniflora and Suaeda salsa gradually beginning to cover the intertidal zone). By systematically configuring key parameters such as vegetation height, initial density, and diffusion rate, this study quantitatively analyzes the impact of bio-geomorphological succession at different restoration stages on sediment and water transport patterns.

Figure 2 illustrates the characteristics of salt marsh wetland geomorphological evolution under different simulation scenarios. Simulation results indicate that during the early stages of salt marsh system development, geomorphological evolution significantly influences the spatial expansion pattern of the salt marsh. This phenomenon is related to the dual environmental stressors of tidal inundation frequency and erosion stress, which limit the extent of plant colonization. At this stage, vegetation distribution is in discrete patch patterns, located on the surface of the sediment platform. As vegetation modifies local hydrodynamic conditions and flow paths, the tidal creek network gradually forms and converges at the vegetation edge. With the continuous incision and lateral erosion of the tidal creeks, sediment transported to both sides gradually accumulates, ultimately forming raised landform structures at the creek edges.

The sediment deposition and erosion analysis results in Figure 3 show that Spartina alterniflora, due to its taller plant height and stronger flood tolerance, significantly enhanced the sediment accumulation process in the central region of the intertidal zone. The erosion ratio in the intertidal zone was 56%, effectively suppressing the erosion of tidal flats (Scenario a). However, in the secondary barren land state after the failure of Suaeda salsa restoration, due to the absence of vegetation, the erosion ratio in the intertidal zone increased to 79%, while the sediment deposition ratio decreased to 20%, leading to the degradation of tidal flats into barren landscapes with no vegetation cover (Scenario b). In contrast, in the scenario of successful Suaeda salsa restoration, although the vegetation density is low and the individuals are low-growing, it still helps reduce tidal flat erosion to some extent, with an erosion ratio of 60% in the intertidal zone (Scenario c).

3.2. Macro-Geomorphological Characteristics of Wetlands

To systematically assess the impact of key environmental driving factors on the geomorphology and ecological dynamics of salt marsh wetlands, this chapter designs and implements multiple parameter sensitivity experiments. The experiments focus on four core parameters: tidal range (A, m), sediment settling velocity (ω_s, mm/s), open boundary suspended sediment concentration (Suspended Sediment Concentration, SSC, kg/m³), and relative sea level rise rate (Relative Sea Level Rise Rate, RSLR, mm/a). These parameters are systematically adjusted within reasonable ranges based on the literature (Table 1). The experimental design uses the method of controlling variables to construct four idealized scenarios: (a) Vary the tidal range (A) to analyze the influence of tidal dynamics. (b) Vary the sediment settling velocity (ω_s) to reflect changes in sediment characteristics. (c) Vary the open boundary suspended sediment concentration to simulate changes in external sediment supply flux. (d) Vary the relative sea level rise rate to explore the potential effects of future sea level rise scenarios. The simulation period for the first three scenarios is set to 10 years, while scenario (d) considers the long-term cumulative effects of sea level rise, with the simulation period extended to 30 years. The specific parameter settings and conditions for each scenario are as follows: Scenario (a) includes 10 conditions with evenly spaced tidal ranges; Scenario (b) sets 12 conditions, with 10 evenly spaced conditions within the range of ω_s < 1.0 mm/s, and adds two high-value conditions for ω_s = 1.5 mm/s and 2.0 mm/s; Scenario (c) includes 10 conditions with evenly spaced SSC values; Scenario (d) sets five conditions, with evenly spaced intervals based on the RSLR range, plus an additional condition for RSLR = 4 mm/a.

3.2.1. Impact of Different Parameters on Elevation Changes in Wetland Systems

Figure 4 illustrates the simulated mean elevation profiles of the wetland system along the offshore-to-onshore transect under varying controlling factors. The simulations reveal that tidal range variations significantly influence the elevation distribution patterns of tidal flats (Figure 4a): A smaller tidal range corresponds to lower inundation of the salt marsh platform and relatively lower elevations in the upper intertidal zone, resulting in a steep transitional zone; as the tidal range increases, elevations in the upper intertidal zones generally rise, whereas those in the lower intertidal zone exhibit a declining trend. Variations in sediment settling velocity (Figure 4b) lead to notable differences in the lower intertidal zone elevation and the width of the salt marsh platform: when the settling velocity increases from 0.1 mm/s to 0.9 mm/s, the average elevation of the lower intertidal zone rises markedly from −1.12 m to −0.43 m, accompanied by a widening of the salt marsh platform, whereas the elevation change in the upper intertidal zone remains relatively minor. An increase in external suspended sediment concentration (Figure 4c) results in a general rise in wetland surface elevation and a trend toward a gentler slope, with the elevation increase being most pronounced in the lower intertidal zone: when the open-boundary suspended sediment concentration increases from 0.00 kg/m³ to 0.08 kg/m³, the average elevation of the lower intertidal zone rises from −1.07 m to −0.39 m, while the upper zone elevation increases from 0.44 m to 0.58 m. Under a constant sediment supply rate, sea level rise (Figure 4d) causes a uniform decline in wetland surface elevation and an expansion of the inundated area.

3.2.2. Impact of Different Parameters on the Evolution of Wetland Geomorphological Features

Figure 5 presents the simulated geomorphological patterns of coastal salt marshes under varying controlling factors. The simulations indicate that tidal range variations markedly influence salt marsh morphology: Under smaller tidal range conditions, tidal creek networks are well-defined, marginal zones are distinctly developed, and the terrain exhibits pronounced elevation undulations with complex branching structures; under larger tidal ranges, tidal creek morphology becomes indistinct, and the overall elevation of the salt marsh tends to flatten. Variations in sediment settling velocity result in pronounced differences in salt marsh morphology: Under lower settling velocities, the salt marsh exhibits generally lower elevation and a well-developed tidal creek system; under higher settling velocities, the lower intertidal zone experiences rapid elevation increase and partial enclosure, with a reduction or complete disappearance of tidal channels. Changes in external suspended sediment concentration influence the degree of geomorphic development: at lower concentrations, the overall salt marsh elevation remains low, while at higher concentrations, the salt marsh exhibits a general increase in elevation and a trend toward tidal creek siltation. Variations in sea-level rise rate result in changes in geomorphic structure: with no or low rates of sea-level rise, the tidal creek system remains well-developed, and geomorphological forms are diverse; as the rise rate increases, the salt marsh becomes gradually inundated, with a decrease in overall elevation and a progressive loss of spatial structural features.

3.3. Plant Growth Characteristics and Biomass

Figure 6 illustrates the effects of four key physical factors on salt marsh vegetation coverage, with distinctions made between areas above and below sea level. As the tidal range increases (from 0.4 m to 2.2 m), vegetation coverage in the area above sea level decreases from 100% to 40%, while coverage below sea level declines markedly, with overall vegetation coverage dropping from 67% to 17%. With increasing sediment settling velocity, vegetation coverage below sea level rises, while coverage above sea level remains relatively stable at approximately 95%; when the settling velocity approaches 0.7, coverage below sea level peaks at 18%, and total coverage reaches a maximum of 48%, followed by a declining trend. With increasing external suspended sediment concentration (from 0.01 kg/m³ to 0.1 kg/m³), vegetation coverage below sea level rises from 5% to 27%, while the above-sea-level region maintains a stable coverage of approximately 97%, with overall coverage increasing from 41% to 55%. As the relative rate of sea-level rise increases (from 0 mm/a to 30 mm/a), vegetation coverage above sea level declines from 95% to 62%, while coverage below sea level drops to 0%, and overall vegetation coverage decreases from 43% to 24%.

3.4. SLR

3.4.1. Effects of Sea-Level Rise Rate on Saltmarsh Vegetation Abundance

This study adopts an idealized scenario of constant-rate sea-level rise, aiming to isolate and explore the mechanisms of the impact of sea-level rise on the system itself, rather than predicting future scenarios under specific pathways. According to the data shown in Figure 7, there are significant differences in the impact of different sea-level rise rates on plant quantity. In scenarios with lower sea-level rise rates, the plant quantity steadily increases over time and eventually stabilizes. However, in scenarios with faster sea-level rise rates, the growth of plant quantity significantly slows down, especially in the 30 mm/a scenario, where the plant population begins to decline after about 25 years, and vegetation growth exhibits significant nonlinear changes. After 30 years, the total plant quantity is 53% of that in the scenario with no sea-level rise.

3.4.2. Dynamics of Saltmarsh Vegetation and Tidal Flat Elevation Under Relative Sea-Level Rise Scenarios

In the Yellow River Delta region, due to factors such as sediment compaction and groundwater extraction, local ground subsidence rates can reach 10 mm/a or higher, particularly in certain areas of Dongying. Therefore, in five independent relative sea-level rise (RSLR) scenarios, this study selects the RSLR of 30 mm/a for detailed analysis. Figure 8 shows the spatial distribution changes of bed shear stress and wave height at different time points within a complete tidal cycle. The data indicate that over time, seawater first invades along tidal channels, accompanied by an increase in bed shear stress on the inner side of the tidal channel. During the rising tide, the wave coverage expands with the rise in tide level, significantly increasing bed shear stress in the upper intertidal zone. The high-value regions of bed shear stress gradually extend from the lower intertidal zone to the middle-upper zone. The tidal channel topography was observed to be associated with the propagation of waves to higher regions. At the maximum tidal level, the upper intertidal zone becomes the area with the highest concentration of bed shear stress. During the ebb tide phase, the flow of residual water in the tidal channel leads to an increase in shear forces along the channel. Additionally, during the process of water level decrease, a transient peak in bed shear stress is observed near the tidal channel mouth.

Figure 9 shows the dynamic changes in vegetation biomass and the evolution of tidal flat elevation under the RSLR scenario of 30 mm/a in the salt marsh region. In the early stages of simulation, the salt marsh vegetation has extensive coverage and is in good condition. Over time, the vegetation coverage gradually decreases, particularly in the middle-lower intertidal zone. Areas that were originally able to sustain plant growth gradually show signs of degradation, with a decrease in the vegetation biomass growth rate, and some regions even experience vegetation loss and tidal flat exposure. The changes in tidal flat elevation show that the incision effect in the middle-lower intertidal zone strengthens over time. By the later stages of the simulation (such as years 25 and 30), although some higher-elevation areas still maintain vegetation coverage, the overall vegetation coverage has significantly decreased. The tidal channel system shows signs of degradation.

As shown in Figure 10, driven by sea-level rise, the lower intertidal zone is significantly eroded in the early stages. The effects of waves and tides lead to the resuspension and transport of sediment, causing bed erosion. However, as the simulation progresses and external sediment supply gradually becomes sufficient, the bed elevation rises, and the elevation in the salt marsh region begins to recover. However, as sea-level rise continues, surpassing the sediment deposition rate, the inundated area gradually expands, and the salt marsh region begins to degrade.

4. Discussion

The study of coastal wetland ecological-geomorphological coupling processes has deepened, with various numerical models being applied to systems such as salt marshes and mangroves [31,32,33,34]. Among them, the equilibrium model based on relative elevation-vegetation biomass [35] has made significant progress in describing the static relationship between vegetation and topography, but it struggles to capture vegetation dynamics (establishment, growth, expansion, degradation) and its real-time feedback with hydrodynamic-sediment processes. The two-dimensional hydrodynamic-sediment-vegetation coupling model developed in this study, based on the Delft3D-FLOW wave-tidal dynamics coupling, sediment transport, and topographic evolution processes, interacts with the biomass accumulation and vegetation growth dynamics simulated in MATLAB (version 2013 or higher), aiming to more dynamically simulate the response of the Yellow River Delta salt marsh system to multiple stresses (such as sea-level rise, sediment reduction, and invasive species management). The following discussion focuses on the key findings of the model results, comparisons with existing knowledge, model limitations, and their implications for management.

4.1. Simulation Verification, Comparative Assessment, and Feedback Mechanisms of Hydro-Sedimentary Processes and Geomorphic Changes

4.1.1. Simulation Validation and Comparison

The model successfully reproduces the characteristic of fine-grained sediments being transported to farther land areas due to their low settling rate [36], showing quantitative consistency in sediment spatial distribution patterns with simulations from the salt marsh of Plum Island Sound, USA [37]. The sensitivity analysis of sediment settling velocity (Figure 4b) indicates that an increase in settling rate (e.g., from 0.1 mm/s to 0.9 mm/s) significantly enhances the sedimentation intensity in the lower intertidal zone, with an average elevation increase of approximately 0.7 m. This result is consistent with the findings of Best et al., indicating that an increase in sediment settling rate promotes sediment accumulation in lower tidal areas while inhibiting further accumulation in higher tidal areas [9]. The simulation results further confirm that, under the background of a sharp reduction in sediment flux from the Yellow River [38] and coarsening of sediment particle size, the resistance of the delta salt marsh wetland to sea-level rise and wave erosion significantly decreases. For example, the simulation shows that when the suspended sediment concentration at the open boundary is extremely low, the average elevation of the lower intertidal zone is only −1.07 m, significantly lower than −0.39 m when sediment supply is abundant. This strongly supports the critical role of sufficient sediment supply in maintaining salt marsh stability [39].

4.1.2. Response Mechanisms of Morphodynamic Evolution in Tidal Flat-Saltmarsh Systems to Driving Factors

Based on the simulation results from Figure 4 and Figure 5, the morphological evolution of the tidal-flat-saltmarsh system in response to different driving factors is primarily controlled by the dynamic interplay between hydrodynamics and sediment transport. In terms of tidal range, a smaller tidal range limits the inundation of the saltmarsh platform and water exchange, causing wave energy to dissipate primarily in the lower intertidal zone, intensifying erosion. Simultaneously, it promotes sediment accumulation at the tidal limit, forming a steep transitional zone that helps maintain a clear tidal channel network and local microtopographic variations. A higher tidal range increases tidal current velocity and extends the inundation time in the middle and upper zones, promoting sediment deposition in this area and contributing to the formation of a gentle transitional zone. However, the lower intertidal zone may experience stronger scouring erosion. At the same time, the strong tidal energy associated with a higher tidal range can destabilize tidal channels, leading to the blurring of saltmarsh morphology, overall flattening, and driving the landward migration of the saltmarsh. In terms of settling velocity, a lower settling velocity allows sediment to be easily transported landward by water flow, leading to increased erosion in the lower intertidal zone and the landward movement of sediments. This limits the overall sedimentation rate of the saltmarsh but helps maintain the hydrodynamic activity and erosive power of tidal channels, promoting channel development. A higher settling velocity, on the other hand, promotes rapid sedimentation in the lower intertidal zone, increasing its stability. However, this rapid sedimentation quickly raises the intertidal flat and blocks tidal channel passages, reducing the number of channels or even causing them to become infilled. In terms of external suspended sediment concentration, low concentrations limit the sediment supply to the entire wetland system, slowing down the morphological development process. High concentrations, on the other hand, provide abundant sediment sources, leading to increased sedimentation across the system, flattening the slope, intensifying internal deposition in tidal channels, and limiting the complexity and connectivity of the channel morphology. Regarding sea-level rise, in the absence of sufficient sediment compensation, it increases relative water depth, enhances hydrodynamic forces, and extends inundation time, making it difficult for the sedimentation rate to counteract the combined effects of erosion and rising sedimentation baselines. This not only causes the entire tidal flat to uniformly lower and the wetland inundation area to expand but also increases the erosive power of hydrodynamics on the saltmarsh platform while inhibiting vegetation colonization. Ultimately, this leads to a decline in the overall elevation of the saltmarsh and degradation and disappearance of tidal channel networks and other spatial structural features, and, in extreme cases, it may cause the structural collapse of the saltmarsh platform. These response mechanisms collectively reveal the vulnerability and adaptability of the tidal-flat-saltmarsh system when facing environmental changes.

4.2. Biogeomorphic Feedbacks in Saltmarsh Systems: Drivers, Responses, and Restoration Challenges

4.2.1. Tidal Creek-Vegetation Feedbacks and Vegetation Patterning

The model reveals the feedback relationship between the development of the tidal channel network and the spatial pattern of vegetation: the expansion of tidal channels limits the lateral spread of vegetation, leading to the fragmentation of continuous vegetation patches [40]. As shown in Figure 3, the distribution range of Spartina alterniflora in the lower intertidal zone is significantly greater than that of Suaeda salsa, but due to the expansion of tidal channels, the vegetation patches become fragmented, resulting in a significant reduction in its coastal protection function.

4.2.2. Response Mechanisms of Vegetation Coverage to Driving Factors

The response pattern of vegetation coverage to driving factors revealed in Figure 6 reflects the complex interplay between geomorphological processes, hydrological stress, and the vegetation niche in the saltmarsh ecosystem. The tidal range has been confirmed as the core factor controlling the distribution of saltmarsh vegetation [41] and the system’s resilience. The simulation results of this study (Figure 6a) clearly show that as the tidal range increases (from 0.4 m to 2.2 m), the overall vegetation coverage in the saltmarsh decreases dramatically (from 67% to 17%), particularly in the areas above sea level, where coverage drops sharply from nearly complete to 40%. This is primarily due to the dual stress effects associated with a large tidal range: enhanced hydrodynamic conditions intensify the scouring of the upper intertidal vegetation roots, significantly increasing the likelihood of physical damage. The intensified inundation process significantly extends the immersion time in the lower intertidal zone and raises the water level beyond the critical inundation height for vegetation, triggering hypoxic stress that exceeds its physiological tolerance threshold, thereby disrupting normal physiological functions and ecological adaptability. This indicates that a larger tidal range significantly inhibits vegetation establishment and maintenance in the intertidal zone by increasing inundation frequency and hydrodynamic disturbances. The increase in settling velocity exhibits a nonlinear effect: its enhancement promotes rapid sediment deposition and elevation of the intertidal zone’s lower part, creating new ecological niches for vegetation to expand seaward, thereby increasing coverage below sea level. While the above-sea-level areas remain stable due to lower stress, excessively high settling velocity may cause the intertidal flat to rise too quickly or result in drastic morphological changes, destroying habitats or hindering colonization, leading to a decrease in coverage. This suggests the existence of an optimal balance between settling velocity and local hydrological conditions. The increase in external suspended sediment concentration significantly enhances vegetation coverage in the lower intertidal zone by promoting sediment accumulation, while having little impact on the above-sea-level areas with lower stress. An increase in the relative sea-level rise rate has an overwhelming negative effect: it directly leads to the continuous reduction in the area of intertidal flats suitable for vegetation growth and causes the inundation depth and duration of the previously sub-sea-level areas to rapidly exceed the survival threshold, leading to complete vegetation degradation. The accompanying increase in erosion further destabilizes habitat stability. In summary, saltmarsh vegetation is highly sensitive to changes in geomorphological and hydrodynamic driving factors, which shape vegetation patterns by regulating intertidal flat elevation, inundation time and height, and the intensity of hydrodynamic stress.

4.2.3. Core Dilemmas and Geomorphic Risks in Spartina Alterniflora Control

In recent years, the rapid expansion of Spartina alterniflora has garnered widespread attention due to its impacts on wetland ecosystems. A large body of research has shown that this invasive species significantly reduces biodiversity in coastal wetlands and poses a serious threat to ecosystem health [42,43]. This study quantitatively evaluates the geomorphological risks associated with different removal strategies. Simulation results clearly indicate that, in the absence of effective alternative protective measures, the strategy of rapidly removing Spartina alterniflora carries high risks. The rapid removal strategy leads to significant erosion of the leading edge of the mudflat, a phenomenon consistent with the sudden elevation drop in vegetation loss areas observed in long-term monitoring records [44]. In contrast, the strategy of using native Suaeda salsa for restoration significantly slows down the erosion rate in the saltmarsh area. Therefore, management decisions should be based on the specific conditions of the area, assessing the hydrodynamic disturbance intensity that may result from removal, and implementing corresponding engineering interventions to maintain shoreline stability, thus avoiding new ecological disasters caused by the management measures. At the same time, it is important to recognize the limitations of the native dominant species Suaeda salsa in terms of its protective efficacy and sediment-promoting capabilities. Its ecological function restoration and enhancement require time and the support of supplementary measures.

4.3. Eco-Geomorphic Response and Degradation Mechanisms Under Extreme Sea-Level Rise Scenarios

4.3.1. Hydrodynamic Impacts and Eco-Geomorphic Responses

Under the context of high relative sea level rise rates, the observed spatiotemporal variation pattern of bed shear stress (Figure 8) reveals the key processes of tidal-wave-topography interactions. Seawater preferentially invades along tidal channels due to the natural flow path created by the low-lying topography of the tidal channels, explaining the early stress increase observed on the inner side of the tidal channel. The rising tide extends the range of wave action to higher tidal flats, directly causing a significant increase in stress at the upper intertidal zone. The upward expansion of high bed shear stress zones reflects the process of wave energy input advancing landward with increasing water depth. Tidal channels, acting as deep troughs, effectively guide wave energy into the saltmarsh, allowing it to affect more landward areas. At maximum tide, the upper intertidal zone becomes the main stress zone, indicating that this area is subject to the strongest hydrodynamic forces at this time. During ebb tide, the enhanced along-channel shear force in the tidal channel is caused by concentrated drainage in the channel, which facilitates the transport of sediment seaward. Stress peaks observed near the tidal channel mouth during ebb tide may be related to wave breaking or the concentration of energy release caused by the falling water level. The results from Figure 8 and Figure 9 collectively indicate that waves are the primary physical driver that initiates and exacerbates scouring degradation in the saltmarsh region. Waves are not only the direct source of bed shear stress, but more importantly, their propagation through tidal channel topography and energy release on the saltmarsh platform significantly increases stress levels in the saltmarsh area, directly triggering and sustaining the scouring erosion process. Tides primarily regulate this degradation process indirectly by controlling water level changes and tidal channel flow.

4.3.2. Coupled Ecosystem-Geomorphic Degradation Under Sea-Level Rise Forcing

The three-phase elevation evolution model of the saltmarsh shown in Figure 10 reveals the competitive relationship between sea level rise rate and sedimentation rate. Early erosion: In the early stages of sea level rise, the increase in relative water depth and enhanced hydrodynamics surpass the sedimentation rate in the saltmarsh area, causing erosion in the lower intertidal zone. Mid-term recovery: Under conditions with external sediment supply, the increased suspended sediment concentration and prolonged inundation time may promote some degree of sedimentation, leading to an overall elevation of the bed and recovery of the saltmarsh elevation. Late-stage degradation: However, when relative sea level rise (RSLR) continues to exceed the sedimentation rate, sediment deposition cannot compensate for the combined effect of subsidence and enhanced hydrodynamics, leading to a significant increase in inundation frequency and duration, causing overall degradation of the saltmarsh area. The observed retreat in the distribution of Suaeda salsa in Figure 11 is its direct response to inundation stress. Although Figure 10 shows some elevation of the tidal flat, the rate of elevation is much lower than RSLR, meaning that the relative water depth and inundation duration faced by the vegetation continue to increase. This “ insufficient elevation gain” is the core environmental pressure driving continuous vegetation loss. The loss of vegetation further weakens the functional integrity of the saltmarsh ecosystem. On one hand, the reduction in vegetation leads to a significant decline in its wave attenuation and sediment-trapping ability, allowing wave energy to more easily penetrate the saltmarsh, which not only exacerbates erosion in the upper intertidal zone but also hinders the capture and deposition of new sediments. On the other hand, the weakening of root-binding stability significantly reduces sediment stability, making the tidal flat more susceptible to erosion, thus forming a vicious cycle of “erosion leading to vegetation loss, and vegetation loss triggering further erosion.” Under the combined effects of continuous inundation pressure from sea level rise, the increasingly enhanced hydrodynamic environment, and the ecological functional decline due to vegetation loss, the saltmarsh geomorphic structure is disrupted, and the ecosystem falls into continuous degradation. Ultimately, if there is insufficient sediment input or effective mitigation measures, the saltmarsh ecosystem will struggle to maintain its original structure and function, facing the risk of collapse.

4.4. Model Limitations

The construction and application of this model have limitations, which must be carefully considered when interpreting results and guiding management. Firstly, while the generalized topography used can capture the overall behavior of the system, it is difficult to accurately reflect the complex micro-topography of the real tidal flats. This may lead to biases in predicting feedback intensity between tidal channels and vegetation at the local scale, erosion hotspots, and sedimentation patterns and may underestimate the potential impact of spatial heterogeneity on the overall system stability. Secondly, the simplification of the vegetation module is a key limitation, as the model does not account for inter-species competition and the lag effects of biomass accumulation. This limits the accuracy of long-term vegetation succession dynamics and final community structure predictions. Furthermore, the model primarily focuses on mid-term dynamic time scales, which imposes significant constraints and makes it difficult to fully capture the cumulative effects of accelerated sea-level rise, increased frequency of extreme weather events, and long-term slow feedback from the ecosystem. At the same time, while the use of the time acceleration factor (MF) can effectively reveal macro trends, it may smooth out the instantaneous effects of high-frequency dynamic events and their impacts on landforms and ecosystems. Future research should explore more refined time coupling strategies to address this limitation. Overall, this model is more suitable for evaluating the relative effectiveness and risks of different management strategies in the near to medium term.

4.5. Management Implications

Based on the quantitative simulations and discussions in this study, the following specific management recommendations are proposed for the protection of the Yellow River Delta salt marsh wetland and the management of Spartina alterniflora. The primary task is to optimize the Spartina alterniflora removal strategy: strictly avoid implementing rapid large-scale removal in key protective shoreline sections, prioritize progressive, zonal rotation removal or integrate simultaneous ecological engineering, and use models to pre-assess local hydrodynamics and sediment environment change risks. Secondly, efforts should be focused on improving sediment utilization efficiency: actively explore the resource utilization of dredged sediment from estuarine channels to alleviate the pressure of insufficient sediment entering the sea. Strengthening the monitoring network and implementing adaptive management are crucial: establish a long-term high-resolution monitoring network in key areas and dynamically adjust management strategies based on real-time data and model updates. In management decision-making, a systematic trade-off between short-term ecological benefits and long-term protective risks must be made: discuss the short-term ecological recovery benefits of removal and the potential long-term risks of weakened coastal protection functionality. In areas with sediment scarcity and insufficient alternative protection, it may be practical to retain some Spartina alterniflora as a transitional protection strategy while accelerating research to cultivate locally adapted communities with stronger protective functions. Finally, the long-term threat of sea-level rise must be given high priority, given the enormous risk of salt marsh ecosystem collapse under high relative sea-level rise rates. Management strategies should be forward-looking. Continuous monitoring of sea-level rise and regional subsidence rates, evaluating the long-term sustainability of sediment supply, and actively implementing adaptive measures to enhance system resilience and promote natural or artificial sediment accumulation are essential.

5. Conclusions

This study developed a coupled hydrodynamic-sediment-vegetation model to systematically explore the impact of Spartina alterniflora management and Suaeda salsa restoration on the geomorphological evolution and vegetation distribution of coastal wetlands. It also analyzed the regulatory mechanisms of various dynamic environmental factors (including tidal range, sea level, sediment supply, and sediment characteristics) on geomorphological patterns and vegetation spatial distribution. The study shows that the management of Spartina alterniflora significantly altered the sediment deposition patterns in saltmarsh wetlands, leading to increased local erosion and weakening the overall stability of the wetland system. Further analysis of the wetland morphology after Suaeda salsa restoration revealed that tidal range variation significantly influences the erosion-deposition patterns of the intertidal zone by adjusting the spatial distribution of wave energy. Under low tidal range conditions, wave energy concentrates in the lower intertidal zone, inducing erosion and forming a steep slope transition zone; in contrast, under high tidal range conditions, the tidal current’s sediment transport capacity increases, promoting sediment accumulation in the middle and upper intertidal zone. Sediment settling velocity determines the distribution of sediment deposition: low settling velocity drives sediment landward, maintaining the development of tidal creek systems, while high settling velocity promotes rapid sedimentation in the lower intertidal zone and accelerates the closure of tidal creek channels. Changes in suspended sediment concentration regulate the rate of geomorphological evolution: under low concentration conditions, elevation growth is limited; under high concentration conditions, it promotes saltmarsh expansion and tidal creek sedimentation. Coastal wetland vegetation exhibits high sensitivity to tidal range, sediment dynamics, and sea-level rise, particularly in submergence-prone areas. Sediment settling velocity nonlinearly influences vegetation expansion, with the system reaching an optimal state under moderate settling conditions. The study also revealed the potential threat of sea level rise to saltmarsh wetlands, particularly when sedimentation rates are insufficient to offset relative sea level rise, posing a risk of ecosystem collapse.

It is important to emphasize that the model used in this study has certain limitations, which may affect the accuracy of predictions regarding local complex landform-vegetation feedback and long-term succession dynamics. This uncertainty must be considered when interpreting the results and guiding management practices. Therefore, future research should focus on more detailed field observations, quantitatively verifying the key processes predicted by this model, conducting sensitivity analysis of uncertainties in key parameters such as vegetation and sediment, and quantitatively assessing the long-term ecological and geomorphological effects of different Spartina alterniflora removal schemes and sediment resource management strategies. At the same time, the model’s capabilities need to be expanded to include interspecies competition mechanisms and long-term ecological accumulation feedback, in order to enhance the prediction capabilities for wetland restoration pathways and final states.

In conclusion, future coastal wetland protection and restoration strategies, particularly those targeting Spartina alterniflora management, must carefully balance ecological restoration goals with coastal protection functions. Under the dual pressures of insufficient sediment supply and sea level rise, prioritizing the stability of critical coastal sections is crucial. The risks revealed by the model should be fully considered, avoiding rapid large-scale removal in vulnerable areas and actively exploring and optimizing proactive interventions such as engineering-based sediment supplementation to enhance the resilience and sustainability of wetland ecosystems.