Dynamics and drivers of tidal flat morphology in China

Domain: earth_science
Published: 2025-03-04
Editorial outcome: major_revision

Abstract
Recent remote sensing analysis has revealed extensive loss of tidal flats, yet the mechanisms driving these large-scale changes remain unclear. Here we show the spatiotemporal variations of 2,538 tidal flat transects across China to elucidate how their morphological features vary with external factors, including suspended sediment concentration (SSC), tidal range, and wave height. We observe a correlation between flat width and SSC distribution, and between flat slope and tidal range. A nation-wide decline in flat width is observed together with SSC reduction between 2002 and 2016. Intriguingly, sediment-rich flats exhibit more rapid width losses if SSC reduces, but slower width gain if SSC increase compared to sediment-starved flats. These dynamics resemble stretched (sediment-rich) or compressed (sediment-starved) springs that tend to return to equilibrium, which can be explained by synthetic morphodynamic modeling. Similar patterns can be observed from Indonesia, the United States, and Australia, implying that the impact of sediment supply change is widespread and large-scale sediment allocation plan based on equilibrium concept can help preserving intertidal ecosystems.

Introduction
Tidal flats, defined as unvegetated mud or sand flats (distinct from mangroves and salt marshes) with regular tidal inundation1, are one of the most extensive coastal ecosystems worldwide, providing essential ecosystem services such as storm surge protection2,3, carbon sequestration4–6, and serving as critical habitats for large populations of waterfowls5,7. With the recent advancements in remote sensing, global-scale tidal flat dynamics have been mapped in detail1,8. Strikingly, approximately 16% of the global tidal flat area was lost during 1984–2016. 66% of the areal losses were attributed to indirect drivers, rather than direct human impact through conversion to other land uses8, although in some countries such conversion was conducted at large scales (e.g., 240–400 km2 per year during 1950–2010 in China9).

Indirect drivers include both natural coastal processes such as wave erosion, and environmental changes influenced by human activities such as altered sediment availability. They often operate at large scales and originate far from sites with emerging dynamics.

Previous studies have demonstrated that tidal range, wave height, and sediment availability can all influence tidal flat morphology at a local scale10–14, but which factors would dominate over a large spatial scale and how they lead to temporal changes remain unclear. For instance, sediment availability is widely regarded as a key factor influencing tidal flat morphology7,15, and there have been dramatic alterations in global suspended sediment flux to the coast16,17. In the global hydrologic north (north of ~20 °N), a 49% reduction in river sediment flux has been observed due to damming, while in the global hydrologic south (south of ~20 °S), river sediment flux has increased by approximately 41% since the 1980s, primarily due to mining in the upstream areas17. These global changes in sediment flux are expected to have a profound impact on large-scale tidal flat ecosystems, but their impact and the underlying mechanisms are yet to be revealed to provide guidance for management.

China possesses the 2nd largest tidal flat area in the world, with a variety of tidal ranges, wave heights, and sediment availability1,18,19. Additionally, China’s tidal flat ecosystem has experienced some of the most rapid loss globally (at 2.6% per year)1,7,8. These facts make China’s tidal flats an ideal model system to study the large-scale tidal flat morphology. In the current study, we track the spatio-temporal variation of tidal flat slope and width20, which are available from global datasets1,21. In total, we included 2538 tidal flat transects along China’s coastline for width analysis from the global tidal flat maps and 1620 transects for slope analysis from the Foreshore Assessment using Space Technology (FAST) database. These transects are selected at 1 km resolution, covering open-coast and estuaries, but those affected by direct human impact or where the width or slope information cannot be extracted were excluded from analysis (see “Methods”).

In this work, by combining tidal flat morphological data with environmental factors (i.e., hydrodynamic forcing and sediment availability), we identify the main drivers influencing spatio-temporal variation of tidal flat morphology. We further find different responses of sediment-rich and sediment-starved tidal flats to the same level of sediment availability change, driven by their tendency to restore morphological equilibrium. To assess the universality of these findings, we extended our analysis to three other countries with extensive tidal flat areas but significantly lower sediment availability compared to China, i.e., Indonesia, the USA, and Australia. Finally, the observed diverse morphological responses were explained by a model based on dynamic equilibrium theory10,11,20,22–24.

Results
Spatial variation and drivers in tidal flat morphology
Remote sensing observations show that tidal flat width ranges from 30 m to 2.6 × 104 m in 2016 (Fig. 1a). The median value of tidal flat width is 536 m. A large group of the tidal flats (34.3%) has a width of 30–300 m, whereas another large group of the tidal flats (32.4%) is wider than 1000 m (Supplementary Fig. 1). The widest tidal flats are found in Jiangsu (JS) province with a median width of 3997 m, while the smallest median width is observed in the northern Shandong Peninsula, being 65 m (Fig. 1a). To compare the tidal flats in estuaries and on open coasts, we selected 5 major estuaries in China, namely the Changjiang River Estuary, the Yellow River Estuary, the Pearl River Estuary, the Minjiang River Estuary, and the Liaohe River Estuary (Supplementary Fig. 2)25 for analysis. Notably, the median flat width in these estuaries (807 m, N=275) is greater than those on open coasts (512 m, N=2263), which is likely attributed to the higher median SSC for estuarine tidal flats (71.0 mg/L) than their open coast counterparts (44.0 mg/L).

The slope of tidal flats in China ranges from 3.6 × 10−5 to 1.2 × 10−1 (Fig. 1b), and the median slope is 7.2 × 10−3. The median slope of flats in the five major estuaries (4.1 × 10−3, N=153) is gentler than that on open coasts (7.5 × 10−3, N=1467). The tidal flats in southern Fujian have the highest median slope in the country, i.e., 1.5 × 10−2 (Fig. 1b), which is influenced by the large tidal range (3.6 m) and a low SSC level (29 mg/L). In contrast, those in southern Jiangsu show the lowest slope i.e., 6.7 × 10−4, influenced by the exceptionally high SSC (110 mg/L) and a moderate tidal range (2.93 m). Furthermore, based on the national-scale tidal flat width and slope data, it is clear that the tidal flat slope becomes gentler as the tidal flat width increases (Fig. 1c).

To identify the main drivers shaping the tidal flat morphology, we analyze the distribution of width (Fig. 2a, c, e) and slope (Fig. 2b, d, f) in conjunction with local wave height, tidal range, and suspended sediment concentration (SSC) (details in Methods). The results show that tidal flat width exhibits a positive correlation with SSC (R=0.71, P<0.01) and tidal range (R=0.44, P<0.01) but a weaker negative correlation with wave height (R=−0.20, P<0.05, Fig. 2e). A stepwise linear regression analysis indicates that the combination of SSC (80% relative importance) and tidal range (20% relative importance) best explains the distribution of tidal flat width (R2=0.61) (Fig. 2g, Eq. 3), in which the effect of spatial autocorrelation is excluded (See “Methods”). Furthermore, the width of tidal flats with flood dominance is markedly greater than that of those with ebb dominance (Supplementary Fig. 4), which is in line with previous studies20.

The tidal flat slope exhibits a positive correlation with the tidal range (R=0.34, P<0.01), but a negative correlation with SSC (R=−0.26, P<0.01). Waves are known to have an impact on tidal flat slope10,20, but it is not significant in the current dataset (R=0.13, P>0.05; Fig. 2f). The combination of tidal range (58% of relative importance) and SSC (42% of relative importance) best explains the distribution of tidal flat slope (R2=0.30) (Fig. 2h, Eq. 4).

The high SSC leads to a large sediment settling flux during each tide. Hence, there must also be more energetic hydrodynamic forcing to re-erode the additional sediment to maintain the morphological equilibrium at such high SSC. In general, wider tidal flats have higher bed shear stress from tidal current and waves (τ in Eq. (12)) compared to narrower flats10 (Supplementary Fig. 6). Thus, it explains the correlation between high SSC and larger tidal flat width in space10,20. Additionally, tidal range also plays a secondary role in tidal flat width, as naturally larger tidal ranges increase the vertical extent of intertidal area, which contribute to wider tidal flats20. Lastly, tidal flat width exhibits a weak negative correlation with wave height, which may be caused by wave-induced mobilization of sediments10. The relation between the slope of tidal flats and tidal range is related to the spatial distribution of bed shear stress11,20. On tidal flats, the representative bed shear stress from tidal currents and wind waves is generally higher at the seaward boundary and decreases towards the landward boundary, leading to an erosion trend at the lower tidal flats but a deposition trend at the higher tidal flats. Greater tidal ranges can increase such differences and lead to steeper tidal flat profiles (see also Supplementary Fig. 7).

Temporal dynamics in tidal flat width and the underlying elastic responses
Tidal flat width shows a clear trend of overall erosion (Fig. 3a, c). Alarmingly, the nation wide median tidal flat width was reduced by 10% (596 m to 536 m) from 2002 to 2016 (Fig. 3c). 30.3% of tidal flats experienced a width reduction rate greater than 1% per year. Such a trend is particularly prominent on Hainan Island and in Changjiang River Estuary, where the interannual change rate in tidal flat width was −1.89% and −1.90% per year, respectively (Fig. 3a). In contrast, there were sites (28.3%) that exhibited an expansion trend of >1% per year. Tidal flats on the southern Shandong (SD) Peninsula and the coast of Fujian Province increased their width at rates of 0.76% and 0.56% per year, respectively (Fig. 3a).

Concurrently, there was a nation wide declining trend in sediment availability at -0.4% per year as observed in interannual SSC from 2002 to 2012 (Fig. 3d). To avoid spatial autocorrelation, we conducted a K-means clustering analysis, a measure for partitioning data points into non-overlapping groups. It reveals a strong correlation between the interannual SSC reduction and tidal flat width decline (R=0.64, P<0.01) (Supplementary Fig. 8). Additionally, 56% of all observation transects exhibit concurrent declines or increases of tidal flat width with sediment availability changes (Fig. 3a, b), whereas the rest of transects do not share this pattern as 86% of them do not bear a clear SSC change trend. These statistics suggest a close linkage between altered sediment availability and changes in tidal flat morphology.

Beyond the overall connection between SSC reduction and tidal flat width loss, we further discover diverse responses of sediment-starved (SSC<50 mg/L, average SSC of China’s tidal flats) and sediment-rich (SSC>75 mg/L, average SSC in five major Chinese estuaries, Supplementary Fig. 2; the Changjiang River Estuary, the Yellow River Estuary, the Pearl River Estuary, the Minjiang River Estuary, and the Liaohe River Estuary) sites to altered sediment availability. Notably, sediment-rich sites undergo 2.1 times faster width reduction than sediment-starved sites (0.27% vs. 0.13% width loss per year) when SSC decreases between -1.2% to -4.8% per year (Fig. 4a). Conversely, sediment-starved systems exhibit 2.1 times more rapid width expansion (0.62% vs. 0.30% width gain per year) when SSC increases between 1.2% to 4.8% per year.

To elucidate these observed divergent responses, we conducted explanatory simulations of a sediment-rich and a sediment-starved tidal flat using the DET-ESTMORF model (Fig. 4b and Supplementary Fig. 9). The modeling results show similar qualitative conditional responses to sediment availability changes, but have different response rates in width change compared to observations. This difference is likely caused by the fact that these simulations are based on two exemplified sites and do not account for all the observed variations across the country. Following a previous study26, we further assess the relaxation time needed for new stable profiles. When external sediment availability decreases by 2%, the sediment-rich tidal flat reaches a new stable profile more quickly (12 years) than the sediment-starved tidal flat (24 years). However, when sediment availability increases by 2%, the sediment-starved tidal flat reaches a stable state faster (19 years) than the sediment-rich site (26 years) (Supplementary Fig. 10). These modeling results are also clearly in line with the observed pattern of tidal flat width changes.

These non-linear dynamics of tidal flat morphology depending on the current sediment input level can also be explained by an analogy to the elastic response of springs to compressional and stretching force. Thus, tidal flats in sediment-rich environments can be regarded as stretched springs due to the above-average sediment inputs (Fig. 4c). These systems have a tendency to retract to their long-term morphological equilibriums. When facing sediment input reduction, they tend to shrink quickly to restore equilibriums, but when sediment input rises, they are resistant to being stretched further from their equilibriums. By contrast, tidal flats in sediment-starved environments can be regarded as compressed springs (Fig. 4d). They have the tendency to bounce back to their equilibriums: expanding their width fast when sediment availability increases, while reducing their width slowly when sediment input is further reduced.

Finally, we conducted a synthetic modeling experiment to explore the elastic response of tidal flat morphology to sediment availability changes on a national scale (Fig. 5a). The results delineate that there are two ‘hot’ zones and a ‘neutral’ zone in tidal flat width dynamics. The two ‘hot’ zones are located at both extremes, i.e., increased sediment inputs in sediment-starved systems and decreased sediment inputs in sediment-rich systems, where the tidal flats are expected to experience rapid widening or narrowing (>0.3% per year). The ‘neutral’ zone, situated between the two hot zones, covers the space of sediment reduction in sediment-starved systems, and also sediment increase in the sediment-rich systems, where the change in tidal flat width is expected to be slow. The mechanism of tidal flat elastic responses in the ‘hot’ and ‘neutral’ zones is included in Supplementary Text. This synthetic modeling aligns with the observed data points along China’s coastline. Sites with higher rates of widening or narrowing mostly fall in the ‘hot’ zones, while sites with lower rates generally fall in the ‘neutral’ zone. It is noteworthy that there are no data points with a rapid SSC increase (>1% per year) in sediment-rich systems (Fig. 5a), reflecting the fact that China’s tidal flat ecosystem is currently experiencing a nation wide reduction in sediment availability.

In our analysis, we focus on understanding how tidal flats respond to external disturbances, since losses due to direct human interventions (such as conversion to other land use) are generally less predictable. We identified 9 transects that are converted at the beginning of our study period (e.g., 2002, see “Method”), and they are observed to generally accumulate at fast rates regardless of the SSC level (Supplementary Fig. 11). Due to the different response pattern, we excluded transects affected by direct conversion, accounting for 17% of the total transects (Supplementary Fig. 12). In addition to direct conversion, we conducted analysis excluding transects in 9 estuaries or bays, as well as those adjacent to converted transects along the open coast, where the far-field effect of conversion could be important (see “methods”). We show that the tidal flat width response to SSC changes still hold when the data of these areas are excluded (Supplementary Fig. 13).

The observed elastic response of tidal flat morphology in China also has global relevance, as similar dynamics are observed from three other countries with substantial tidal flat areas, i.e., Indonesia, Australia, and the United States. These three countries are ranked 1st, 3rd, and 4th place globally in tidal flat areas (with China being the 2nd place). Data from these four countries collectively show: 1) tidal flat width grows if SSC increases and shrinks if SSC declines; 2) tidal flats with higher SSC have lower expansion rates as SSC increases, but higher retreat rates if SSC reduces (Fig. 5b, c). Furthermore, based on the data from China’s coast, we found that in sediment-rich areas tidal flat width losses would increase rapidly once the SSC is reduced by 24% from 2002 (Supplementary Fig. 14). This finding can serve as an important rule of thumb for coastal management.

Methods
Tidal flat width and slope data
The width of the tidal flat is defined as the horizontal distance from mean high water to low water (Supplementary Fig. 15). The data of tidal flat area along China’s coastline were obtained based on the global tidal flat maps1. These maps used over 7.0×105 satellite images to record tidal flat extent, and the data explicitly exclude vegetation-dominated intertidal ecosystems (such as mangroves and vegetated marshes). The resultant global map of tidal flats exhibits a horizontal resolution of 30 m, delineating the spatiotemporal variation of tidal flats on a global scale. To obtain the width of China’s tidal flat, we measured the distance of cross-shore transects along the shoreline in OpenStreetMap (OSM)40 every 1 km. The overall accuracy of the tidal flat area map is 82.2%41. Misclassification of tidal flats (pixels) can occur in areas of highly turbid water, polluted areas, aquaculture ponds, and areas subject to strong wave action. Despite the potential errors, to our knowledge, this map is the only freely accessible tidal flat map that covers large spatial (national) and temporal (decadal) scales. The accuracy of this map is sufficient (>80%)41 to reveal the overall dynamics of tidal flat areas and to support the main findings of the current study.

The slope of the tidal flats was ascertained from the Foreshore Assessment using Space Technology (FAST) database21, which provides a high-resolution intertidal bathymetry/elevation dataset. The bed level data has a 20 m horizontal resolution and typically a 30-50 cm vertical accuracy. To obtain the tidal flat slope, we extracted the bed level data of cross-shore transects along the shoreline. The transect endpoints are based on the range of the tidal flats. The slope of the tidal flat was then calculated by the cross-shore horizontal length L of the transect and vertical height difference ΔH between the endpoints (i.e., slope=ΔH/L, Supplementary Fig. 16). Transects with discontinuous elevation were excluded from analysis (917 of 2538 transects). There are mainly two reasons that cause the discontinuous elevation: 1) gaps within the continuous elevation data (51.4%); 2) none or too few elevation data in the FAST database (48.6%).

To identify the key factors that sculpt the spatial morphology of tidal flats, we compared tidal flat width data (2014–2016) and slope data (1997–2017) with SSC (2016), tidal range (2010), and wave height (1979–2021). To reveal the temporal changes in tidal flat width, we traced the tidal flat width change data from 2002–2016 and SSC change data from 2003-2011, constrained by data availability. Changes in tidal flat width were obtained from tidal flats maps every three years (2002–2004, 2005–2007, 2008–2010, 2011–2013, and 2014–2016)1. The data on the annual variation in tidal flat width shows no significant spatial autocorrelation (Moran’s I < 0.01, p = 0.44).

Hydrodynamic data
We utilized the TPXO9-atlas dataset42 to obtain the mean tidal range for each cross-shore tidal flat transect along China’s coast. The spatial resolution of the dataset is 1/30°. The accuracy of the TPXO9 on China’s coast can be shown by an average Root Sum Squares (RSS) value of 19.92 cm43. Employing the tide model driver (TMD) tool, we processed the TPXO dataset to calculate the water levels at each transect for the year 2010. This was done by incorporating the amplitudes and phases of eight major tidal constituents: K1, K2, M2, N2, O1, P1, Q1, and S2. The average tidal range data was then interpolated from the mean high water level and the mean low water level.

Tidal asymmetry is calculated from the phase difference between the M2 and M4 tidal constituents (2θM2 − θM4). A phase difference within the range of 0–180° results in a flood-dominant tide. Conversely, a phase difference between 180° and 360° indicates an ebb-dominant tide44,45. Under the same phase difference, the amplitude ratio of M4 and M2 tidal constituents is used to indicate the magnitude of the tidal asymmetry. The tidal flats along China’s coastline exhibit a tidal range that varies from a minimum of 0.59 m near the Yellow River mouth to a maximum of 7.33 m on the southern Shandong Peninsula, with an average of 2.78 m.

We collected SLR data from 14 coastal sites in China46 and calculated the correlation between the SLR data and changes in local tidal flat width. However, the results indicate no significant correlation (p = 0.89). The annual mean sea level data of the 14 coastal sites are collected from the Permanent Service for Mean Sea Level47,48 (see Supplementary Table 1). To test the possible effect tidal range has on tidal flat width, we compared the tidal range change from the 12 UHSLC tide gauge sites49 with the tidal width changes. The results indicated no significant correlation between the tidal range changes and the nearby tidal flat width changes (p = 0.32), which is likely due to the relatively small changes in tidal range (averaged 1.1 cm per year).

The offshore wave conditions were derived from the ERA5 reanalysis database50, which encompasses comprehensive wave height and period data from 2002–2016. The database has been proven suitable for China’s coastal areas51, with data bias estimated at less than 0.1 m in deep waters. These data were firstly reprojected to align with the offshore positions of the tidal flat transects. Subsequently, the offshore wave height values were transferred to the wave height situated 3 km off the coast, equating to 78% of the offshore wave height52. In the absence of detailed nearshore bathymetry data, we assumed linear profiles from 3 km off the coast to the mean low water level53, while the intertidal bathymetry (low water to high water level) data are available from FAST21. The offshore depth is obtained from the ERA5 database. This approach allowed for the estimation of wave heights in the immediate vicinity of the tidal flats at mean low water level, accounting for wave shallowing and bottom friction54:

Dw = 3/2 π ρf e Uδ 3 (1)

Uδ = Ts / π in Hh s kh (2)

where Dw is the wave height dissipation, ρ is the water density, f e is the wave friction factor, which is assigned a value of 0.05555, Uδ is the wave orbital velocity, H s is the significant wave height, T is the wave period, k is the wave number, and h is the water depth. Wave refraction and diffraction processes are not accounted due to the lack of nearshore bathymetry data.

To assess if a change in waves might affect tidal flat width, we calculated the change rate of significant wave height at 105 sites along the coast of China (with a resolution of 0.5 degrees) from ERA5 data. It shows that 95% of tidal flat areas have experienced a minimal variation in significant wave height below 0.1 cm/year from 2002 to 2016. Thus, there is no significant correlation between the wave height change and tidal flat width dynamics (p = 0.42).

To validate the applicability of the ERA5 data, we collected wave data from tidal flats at various locations along China’s coast, including Chongming Island56,57 and Leizhou Bay58 for both wave height and period, Taiwan Longdong59 and the Yellow River mouth60 for wave height, and Jiangsu61 for wave period. The agreement between our estimated wave heights and periods with in-situ observations (Supplementary Tables 2 and 3) confirms good applicability of ERA5 wave data. In the current study, the impact of alongshore currents is not explicitly considered, since there is a lack of nationwide dataset on alongshore currents. Yet, as alongshore currents transport sediment over large scales62,63, their impact is implicitly reflected by the SSC data we analyzed.

Suspended sediment concentration (SSC) data
SSC is considered representative of the local sediment availability36–38,64, and a key external driver on tidal flat morphodynamics. The SSC data near the monitoring tidal flat transects were obtained from the GlobColour project (https://www.globcolour.info). The data product of total suspended matter concentration (TSM, mg/L) produced by the project is used to represent SSC (mg/L) because in turbid coastal waters most suspended matters are due to suspended sediments. It is estimated from satellite-derived particle back-scattering coefficient in the blue wavelength by assuming a back-scattering/scattering ratio of 0.015, and such a product has been previously used and found reliable for large scale analyzes64,65. The spatial patterns of such derived TSM are consistent with those from independent studies using other algorithms66. Although satellite-derived TSM (or SSC) represents the particle concentration in surface waters (down to an optical depth), for both well-mixed water column or highly stratified waters it can be used as a proxy for suspended particles in the water column66. This is because, for the former case it is obvious that TSM reflect the overall sediment concentration and, for the latter case, the signals from the bottom, particle-rich layer will only be attenuated slightly by the surface, particle-poor layer. The applicability of this approach has been validated in terms of both spatial distribution67 and temporal variability68, and the method has been widely applied in previous studies (e.g., sediment availability data in ref. 64 and turbidity for estuaries in ref. 69).

The SSC data product has a horizontal resolution of 1/24 degree (generally 2.2 km off the coast) and a temporal resolution of one month. To investigate the drivers behind the spatial distribution of tidal flat morphology, we analyzed the monthly average SSC data obtained through the inversion of OLCI satellite data for the year 2016, synchronized with the tidal flat width (2002 - 2016) and slope data (1997 - 2017). In the Hangzhou Bay area, the maximum SSC reaches up to 200 mg/L, which is in line with previous field observations70,71. To assign a local sediment concentration level to each tidal flat data point, the TSM data point close to the tidal flat is defined as the sediment availability for the tidal flat. We defined sediment-starved systems in China as the areas with an annual mean SSC below the national mean SSC level (50 mg/L). This value is obtained by calculating the average SSC of pixels containing tidal flats (4 km resolution). Correspondingly, areas with an annual average SSC higher than 75 mg/L are defined as sediment-rich systems, which are the annual mean SSC in 5 major estuaries (the Changjiang River estuary, the Yellow River estuary, the Pearl River estuary, the Minjiang River estuary, and the Liaohe River estuary). These thresholds can be considerably higher than other countries17,69, due to the overall higher SSC on China’s coast. Thus, sediment-starved and sediment-rich systems should be defined differently in other regions of the world.

Human impact through conversion
Conversion of tidal flats to other land use directly and indirectly influence the evolution of tidal flats. To investigate the morphological evolution of large-scale tidal flat systems with environmental factors (i.e., hydrodynamic forcing and sediment availability), we excluded transects affected by direct conversion. First, we identified tidal flat transects with direct conversion by analyzing satellite imagery (see Supplementary Fig. 12). The tidal flats are mainly converted to agriculture or aquaculture land use, and also (about 1.2%) to artificial sandy beaches in areas like Xiamen city72. 750 transects are affected by direct conversion, which are excluded from our analysis.

To compare the effects of direct conversion and external drivers, we identified nine transects that were converted at the beginning of our study period and have SSC change data, so that we can track their development. The results show that eight out of nine transects exhibited a seaward progradation trend after the conversion (Supplementary Fig. 11). The rate of tidal flat width change exceeds the rate of tidal flat evolution driven by natural drivers, highlighting the important difference imposed by direct conversion and the necessity to exclude those transects in our study.

As conversion can also affect nearby hydrodynamic conditions, thereby influencing adjacent remaining tidal flat evolution by far-field effects. Therefore, we further excluded transects adjacent to those directly impacted by conversion. We identified nine estuaries or bays where the conversion level is high (over 40% of the transects were directly converted), including Qinjiang Estuary, Yingzai River Estuary, Zhenhai Bay, Luojiang Estuary, Wenzhou Bay, Wulei Island Bay, Liaohe Estuary, the southern coast of Hangzhou Bay, and Qixing Reef. The remaining transects were identified as being influenced by far-field effects of conversion. Additionally, those adjacent to converted transects along the open coast are also deemed influenced by far-field effects. After excluding all these 156 transects, our primary conclusions regarding spatial and temporal patterns remain unchanged (See Supplementary Fig. 13).

Statistical analysis
Multiple Linear Models (MLM) were used to identify the key drivers that shape the spatial distribution of tidal flat morphology.

The statistical analysis were performed using the ‘R’ software. MLMs were created for tidal flat width and tidal flat slope, respectively. Given the low resolution of offshore wave height data (0.5°), we consolidated data points that corresponded to the same offshore wave height and computed the mean values for tidal flat width, significant wave height (Hs), suspended sediment concentration (SSC), and tidal range (TR) within each offshore wave height pixel.

First, we used stepwise linear regression to select the best combination of independent variables that explain the spatial distribution of the tidal flat morphology. This process was guided by the selection of the model yielding the lowest Akaike Information Criterion (AIC) scores, a widely accepted criterion for model selection73–75. For tidal flat width and slope, SSC and tidal range were included in the most streamlined final model. Subsequently, we established a multiple linear regression model for the selected variables (Eq. 3 and Eq. 4) and calculated their relative importance. The relative importance is calculated as the contribution to the model’s determination coefficient (R2).

width3 1(cid:3)SSC3 1+TR3 1 (3)

log(slope)(cid:3)SSC3 1+TR3 1 (4)

To obtain a normal distribution of the data for proper statistical analysis, we applied transformations to the tidal flat width, tidal range, and SSC data by taking their cube roots, and log-transformed the tidal flat slope data prior to their inclusion in the statistical models. Considering the potential impact of spatial autocorrelation, we calculated Moran’s I for the residuals in our regression models for width (0.35, p<0.01) and slope (0.11, p=0.17). We then used a spatial error model to eliminate the effects of spatial autocorrelation for the width model, achieving a better fit than the multiple linear regression (R2=0.61). P-values and R-squared values were calculated using the ‘summary’ function in the linear model, and the relative importance of each parameter was calculated using the ‘relaimpo’ package75.

DET-ESTMORF model
To explore the relationship between sediment availability variations and the corresponding temporal shifts in tidal flat width, we utilized a one-dimensional tidal flats morphological model, DET-ESTMORF (Fig. 4 and Fig. 5)11. This model is a hybrid approach that integrates morphological equilibrium20,22 with hydrodynamic and sediment transport processes, in contrast to fully process-based models12. This model has been validated previously11, and applied in intertidal biogeomorphology studies76.

Tidal flats in morphological equilibrium are characterized by a consistent distribution of bottom bed shear stress and SSC throughout their profile. When the actual local bed shear stress surpasses the equilibrium shear stress, there is a tendency of erosion, requiring a higher SSC to counteract the tendency and maintain equilibrium, i.e., a higher local equilibrium concentration than average. Hence, the magnitude of bottom bed shear stress determines the tendency of tidal flats’ geomorphic change, while the difference between actual SSC and local equilibrium SSC indicate the occurrence of geomorphic change, which is similar to the process-based models, e.g., Delft3D.

In DET-ESTMORF, we considered both the effects of wave and tidal shear stresses on the bottom bed. To obtain the tidal-induced bottom bed shear stress, we adapted the method based on mass conservation from a previous study55. Concerning the wave propagation modeling, we applied the wave energy flux conservation equation considering bottom friction54:

d/dx (Ec cg) = −Dw (5)

where E is the wave energy [kg m−2 s−2)], cg is the group velocity (s2 m−1), and g is the acceleration of gravity (ms−2). The incident H s is obtained by a random draw from the Rayleigh distribution around a given mean value54.

The attenuation of wave energy by friction is given by Eq. 1 and Eq. 2. We also considered the effect of wave breaking in the wave propagation process, where the maximum wave height H s is associated with the local water depth and the breaking height coefficient:

H s = min (H s, γ b h) (6)

where γ b is a constant value (0.5). The bed stress induced by waves τ w is quantified as77:

τ w = 1/4 ρfwUδ 2 (7)

where f w is a friction factor estimated as:

f w = 1.39 (Aδ / k b) −0.52 (8)

Where the wave orbital semi-excursion at the bed Aδ=UδT, bed roughness k b = 2πd 50 = 12, and d 50 is the median grain size of sediment particles. The mean bed shear stress under combined waves and tidal currents during a wave cycle is calculated as78

τ m = τ cur [1 + 1.2 (τ wave / (τ cur + τ wave)) 3.2] (9)

Thus, the maximum bed shear stress during a wave cycle is calculated as

τ max = (τ m 2 + τ wave 2 + 2(τ m τ wave) cosθ) 0.5 (10)

where θ is the angle between current direction and direction of wave propagation. In our study, θ = 0 as both currents and wave propagation are in the cross-shore direction. τ 90 is quantified every 30 minutes during a tidal cycle. Subsequently, τ 90 is derived as the 90th percentile of τ max over a tidal cycle, which is considered as the hydrodynamic forcing that drives morphological changes.

In morphological equilibrium, the balance between erosion and accretion in the vertical direction is achieved, which can be expressed as follows79,80:

τ m / τ cr − 1 = w s / c E (11)

Here, m represents the erosion coefficient [kg m−2 s−1)], τ cr denotes the critical shear stress (Pa), and w s represents the sedimentation rate (m/s), c E is the long-term average SSC value (mg/L) at the seaward boundary. Via this equation, τ E is the uniform bed shear stress (Pa) that can be derived from the known variables. Subsequently, the local equilibrium concentration c e based on the ratio of τ 90 to τ E can be derived as:

c e = c E (τ 90 / τ E) n (12)

The local equilibrium concentration c e can be converted to volume concentration by dividing the sediment density (ρ s = 2650 kg/m3)81. The actual spatial and temporal distributions of local SSC are obtained by solving the diffusion equation:

∂(hc) / ∂t = w s (c e − c) + ∂/∂x (D ∂c/∂x) (13)

where c is the volume sediment concentration (m3/m3), and D represents the diffusion coefficient (m2 s−1). The change in tidal flats morphology following each tidal cycle is calculated based on the difference between c and c e:

∂z / ∂t = 1 / (1 − p) w s (c − c e) (14)

where z is the bed elevation (m), and p is the bed porosity. The key parameters are detailed in supplementary Table 4, and the values of these parameters are based on previous modeling work (Supplementary Table 5)10,12,82.

To reveal the nonlinear response of tidal flat width to SSC change, we selected two sites for explanatory modeling, namely the Western Scheldt site in the Netherlands (sediment-starved)76 and Jiangsu in China (sediment-rich)63. We did not select a Chinese site for the case study of sediment-starved area, as it was not possible to find detailed field data for model validation in China, while the Western Scheldt has a unique detailed dataset available. At the Western Scheldt site (SSC=58 mg/L), the DET-ESTMORF model has been applied and validated in previous studies11,76. At the Jiangsu site, we obtained the equilibrium profile by performing a 100-year modeling from the initial linear profile based on the tide level, while wave height and offshore SSC data (134 mg/L) are based on the collected datasets in the current study. We validated the model’s accuracy by comparing the obtained equilibrium profile with the observed profile reported in a previous study (Supplementary Fig. 17)63. Building on this validation, we proceeded to calculate equilibrium profiles for both sites under varying interannual SSC change rates, including −1.2%, −0.8%, 0.8%, and 1.2%. This exercise was designed to ascertain the interannual rates of tidal flat width change over a 13-year period, in line with the observational time frame spanning from 2003 to 2015.

Analysis of temporal changes in tidal flats width
To analyze the temporal changes in tidal flat width, we integrated measured data (the bubble chart of Fig. 5a) with experimental results (colormap of Fig. 5a). We extracted tidal width change rate of tidal flats with SSC above 50 mg/L and those below 50 mg/L across different SSC change rate groups (−3% to −1.5%/year, −1.5% to 0%/year, 0% to 1.5%/year, 1.5% to 3%/year). Within each group, we chose median tidal width change (mean of the 48%–52% percentiles) as the representative value (Fig. 5a). To minimize the influence of anthropogenic factors on the geomorphology of tidal flats, data points exhibiting interannual tidal width trends exceeding 20% per year were omitted.

We then employed the DET-ESTMORF model to simulate the variation of tidal flat width under different SSC (20~120 mg/L) and varying interannual rates of change of sediment concentration (−3%~3%/year). For a consistent basis of comparison, we initialized the model with a wider profile for tidal flats with higher sediment availability, maintaining uniform parameters across all scenarios except for the initial SSC level and the SSC variation rates. For a given SSC level, we first obtained the equilibrium profile from the initial linear profile after 100 years of simulation, after which the change in the tidal flat morphology is negligible76. Based on the obtained equilibrium profile, we simulated the tidal flat morphological variations with changing SSC over 13 years (2003 to 2015, as a reflection of the observation), and finally compared the simulated flat width changes resulting from various SSC changing rates.

To test the observed elastic response of tidal flat morphology in China, we further analyzed the data from three other countries with substantial tidal flat areas, i.e., Indonesia, Australia, and the United States. There are a large number of observation transects in these countries and many of them are affected by direct human intervention. To select the representative transects, we categorized tidal flat transects from these three countries into four groups for each country, based on initial SSC levels (0-20 mg/L and >20 mg/L) and SSC change rates (-9 to -3%/year and 3 to 9%/year). Within each group, we randomly selected 50 tidal flat transects, and subsequently excluded the transects with direct human impact based on the satellite base map from Google Earth Engine. This resulted in 34 transects in Indonesia, 49 in Australia, and 33 in the USA. For China, we grouped SSC into sediment-starved and sediment-rich areas as mentioned in the previous section.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "This manuscript by Liu et al. aims to study the dynamics and drivers of tidal flat morphology in China. They give a “spring theory” to explain the response of tidal flat morphology to suspended sediment concentration (SSC). This theory is summarized based on the tidal flat morphology change during 1984-2016 in China. However, during this period, the loss of tidal flat in China was mainly due to direct reclamation or indirect human activities, such damming, nourishment, far field effect of coastal reclamation. The authors mentioned that the human induced tidal flat lost is excluded from this study. I doubt that all the direct and indirect influence can be totally removed from the data. My first concern is that is this theory universal or only applicable to China’s tidal flat? If the former, why it can be summarized from the China’s case in which the human impact should be the dominant drivers. If the latter as the authors selected the Western Scheldt site as a case study, what is the most different characteristics between China’s tidal flat and others around the world? The second one is that is it appropriate to use SSC to characterize the sediment supply as the authors ignored the dynamic factors, such as sea level rising, change of tides and wind-waves, and terrigenous sediment supply? Also, even the tidal flat change itself can drive SSC variation. So, how to analyze the nonlinear correlation between them? In my opinion, both the methodology and the results of this manuscript are not sound. The detail comments are given below:\nLine 46-47: This may be true around the world, but how is the situation in China? I believe in China during this period, tidal flat reclamation is the dominant driver for the loss or indirect by human activities, such damming, coastal engineering, far field effect of land reclamation.\nLine 58-59: Yet in this study, this is still not to be revealed.\nLine 70-71: Sites affected by direct human impact (e.g., reclamation) were excluded from the analysis. So how about the indirect human impacts?\nLine 111-113: Why is it positively correlated with tides and negatively correlated with waves? Is there any explanation on the dynamics?\nLine 113-116: The stepwise linear regressions are equation (3) and (4)? The relative importance means the weight of the two terms? How are they determined? This is pure mathematical statistics. Is there any physical explanation?\nLine 136-137: This statement seems wrong. The negative gradient should be due to the high shear force at higher tidal flat and the small shear force at lower tidal flat. Figure 5 in Supplementary does not show this characteristic. Again, if bed shear stress can be used to explain the relationship between tidal flat width and tidal currents, how about the wave-induced bed shear stress?\nLine 176-177: What do you mean the tidal flats in the estuary? Most tidal flats in China are not in the estuary. How is the distribution of sediment-rich and sediment-starving tidal flats along the China’s coast?\nLine 193: The sediment condition is defined by the SSC in the tidal flat. So, are all the tidal flats in sediment-rich area higher than the morphological equilibrium (convex) and those in sediment-starving area lower than the equilibrium (concave)?\nLine 255-256: It is curious what is the critical condition for tidal flat morphology tending to move towards the equilibrium state rather than being driven away from it if the initial morphology reached the equilibrium.\nLine 296: How to deal with the inaccurate part of tidal flat area map?\nLine 320: Compared to tidal asymmetry, tidal range is not the most accurate indicator for tidal flat morphology variation or sediment transport. As TPXO9-atlas dataset also provides the shallow water tidal constituents, have you examined the relevance of tidal asymmetry to the width and slope change of tidal flats?\nLine 330: How is the wave data coupled with tides for the calculation of τ90?\nLine 363: It is vague that the utilize of SSC data and TSM data. The TSM data is the suspended matter concentration on the surface, rather than the water column. Would it be suitable to represent the SSC in the water column, especially in the estuary where the water is highly stratified?\nLine 383-386: It is unclear that how it is defined that the annual average SSC level of China’s tidal flat coast. What is the spatial resolution for each bin to average and how far off the coast?\nLine 408-409: How are equations (3) and (4) obtained? How do they perform in China’s tidal flats? How is the time-variation of tidal range along the coast? Do the changes in width and slope also conform to these equations?\nLine 439-448: How are the key parameters determined? Like n in Equation (6), ws and D in Equation (7). The volume sediment concentration c has a unit of m3/m3, and the local equilibrium concentration (cid:1)(cid:2) has a unit of mg/L. So how can these two variables be directly subtracted in Equation (8)?\nLine 471-474: It is unclear how/whether the τw is used for the morphology change of tidal flats through Equations (1)-(2) and (5)-(12). The random waves are also excluded from the experiments. It is doubt that if the model considers the wave effects.\nLine 477: Why not chose a Chinese site? Would this site be represented for a high turbidity Chinese site?\nLine 490: This section is the model experimental results. How reliable is it compared to the measured results?\nLien 497: Why the number 20% is selected as the critical value? If chose 30%, would the conclusion be changed?\nIn the supplementary:\nLine 50-60: There is no direct function between tidal flat width and SSC.\nLine 58: C is not related to me.\nLine 62-70: The explanation is not clear, but rather difficult to understand. τ90 can be used to represent for some driving forces, and SSC can reflect τ90, but it does not mean that the SSC is changed all by τ90, such as the river input.\nLine 122: How to calculate Δce?\n(Remarks on code availability)\nThere is no README file with enough instructions for installing and running the application.", "reviewer_2": "In this manuscript the authors traced the spatial and temporal morphological changes of more than 2’500 tidal flat transects across China, unravelling the intricate controls governing their morphological evolution in response to changes in external forcing such as suspended sediment concentration (SSC), tidal range, and wave height. The objective of this study, of establishing a scientific foundation for informed management strategies is timely and relevant, considering the global decline of tidal flats in China and worldwide.\nThe authors demonstrate the correlations between tidal flat width and SSC distribution, as well as tidal flat slope and tidal range. Particularly noteworthy is the nationwide decrease in tidal flat width observed from 2002 to 2016 due to reduced SSC, underscoring the significant role of sediment supply dynamics. Furthermore, the authors' observation that sediment-rich tidal flats exhibit a swifter response to SSC reduction compared to sediment-poor tidal flats, and vice versa, highlights the nuanced interplay between sediment availability and tidal flat morphology. These responsive behaviors are underpinned by the capability of tidal flats to revert to their morphological equilibrium.\nThe research presented by the authors is well designed, scientifically sound, and is carried out in a consistent and rigorous way. I particularly appreciated the challenge of quantitatively unravelling the dependence of tidal flats from, and their response to, external forcing and changes thereof.\nThe huge dataset considered by the authors was properly analyzed and the conclusions are well supported by the results of the analyses. In particular, the finding that \"sediment-rich tidal flats respond faster to SSC reduction compared to sediment-starving areas, but the opposite is true if SSC rises\" could have important implications to tidal-flat dynamics in the face of anthropogenic pressure, which may help advance further studies in the field of coastal morphodynamics.\nThe manuscript is well-written and effectively communicates the findings to the intended audience. While the study is robust, there are critical areas for improvement that would enhance the manuscript's clarity, completeness, and overall impact.\nAs detailed in the specific comments below, my suggestions aim to:\ni) Describe the different responses to changes in SSC of sediment-rich and sediment-poor systems. While the analogy with spring dynamics is nice, it is essential to explain what morphodynamic mechanisms and feedbacks control such a response. Providing a detailed explanation grounded in morphodynamic principles would strengthen the scientific basis of the observed behaviors.\nii) Discuss the applicability of their results in diverse coastal systems, especially where sediment availability could be considerably scarcer than that along the Chinese coast. Given that 50mg/L would equate to a substantial sediment concentration for some severely sediment-starved systems globally, broadening the study's relevance is essential.\niii) Consider whether the inclusion of sea level rise (SLR) effects could potentially impact the outcomes of this study. Addressing the potential impacts of SLR on the study outcomes ensures the robustness of the study's conclusions under varying conditions.\niv) Reconcile apparently divergent findings related to concave-up and convex profiles, along with their underlying factors. This includes explaining how these factors might influence the results and ensuring consistency with previous findings.\nBased on these points, there is a clear need for substantial revisions to improve the manuscript before it can be considered for publication in Nature Communications. The issues highlighted and the suggestions provided below are aimed at enhancing the manuscript’s clarity, completeness, and scientific rigor, thereby elevating an already strong study to a higher standard of excellence.\nDetailed comments.\nLine 42. Noun as adjective. Change “tidal flats dynamics” to “tidal flat dynamics”.\nLine 46. Do you refer to worldwide decline?\nLines 47-90. In the Introduction, the authors miss to include important literature in the introduction that could provide additional context and support for their findings. Indeed, it would be worth mentioning that researchers in the field have demonstrated through both point (Fagherazzi et al., PNAS 2006; Marani et al., JGR-ES, 2010) and spatially explicit (Roberts et al., CSR 2000; Hu et al., JGR-ES 2015) models and analyses, that tidal flats can attain a dynamic equilibrium condition influenced by the external forcing considered by the authors. This suggestion is rooted in the authors' application of the equilibrium theory to support their findings and subsequent interpretations within the text.\nLines 67-70. These lines are unclear. Although the authors refer readers to the Methods section, there remains uncertainty about the meaning of \"independent and complete profiles\" and \"elevation continuous profiles.\"\nLine 86. There is an extra period in the sentence.\nLines 87-88 and 102-107. The authors state that the average width of tidal flats in estuaries is greater than that of flats on open coasts, likely due to sediment availability. However, they do not provide sufficient evidence to support this claim. Additionally, regarding tidal flat slope (lines 102-107), it is unclear what factors determine the difference between Fujian and Jiangsu.\nLines 109-116 and Figure 2. Frankly, I don't understand why the relationship between Average Width and Wave Height, or between Slope and Wave Height, is not shown. Given that the correlation between tidal flat slope and tidal range is weak (R^2 = 0.30), what would be the correlation between tidal flat slope and wave height? Furthermore, why do the authors consider average width, while examining the median slope?\nLines 135-143. What about the effect of wave heights on both tidal flat width and slope?\nLines 135-143. In certain microtidal systems like the Venice Lagoon (Italy) or the Virginia Coast Reserve (USA), where wind waves exert greater influence than tidal oscillations, tidal flats exhibit nearly negligible slopes (in fact, they are exceptionally flat!), yet the shift from tidal flats to marshes occurs through an exceptionally steep (almost vertical) scarp. How does this observation align with or challenge your findings? Please comment.\nLines 145-148. In both Figure 3 and previous figures, does it make sense to consider the average width of tidal flats, which ranges from 30 to 26,000 meters?\nLines 143-152. 28.3% of sites experienced expansion. What is the percentage of sites which experienced erosion?\nLine 174-189 Contrasting Sediment-Rich and Sediment-Starved Tidal Flats How is the threshold defined? Is the threshold based on the annual mean of the monthly mean Suspended Sediment Concentration (SSC) data? Could you kindly provide clearer clarification of this aspect either within the main text or in the section titled “Suspended Sediment Concentration (SSC) Data”?\nI am curious about the 50mg/L and 75mg/L thresholds for sediment-starved tidal flats on the open coast and on estuaries, respectively, and whether those threshold are affected by the specific SSC values of the area. A mean value of 50mg/L does not strike me as indicating low sediment availability. Moreover, the SSC on the Chinese coast, as considered by the authors, might be considerably higher than that of many other coastal systems globally. Has your detailed scrutiny of the literature identified such a threshold? How does this value compare to thresholds observed in other sediment-starved systems worldwide?\nLines 177-179. Regarding the SSC decrease, is it meaningful to highlight an average difference of 0.03% between sediment-rich and sediment-starved systems? Could such a small difference fall within the margin of error due to estimations in tidal-flat width and/or SSC concentration values? Additionally, note that the 0.27% and 0.24% rates refer to an SSC decrease between 1.2% and 4%, while for the 0-1.2% decrease scenario, the results are different. A similar consideration applies to the increase in SSC.\nLines 174-190 and Figure 4. What I observe here is that as the SSC decreases, both sediment-rich and sediment-starved tidal flats exhibit a similar response by narrowing their width at the same rate when considering actual tidal flats (Fig. 4a). However, model results suggest a more pronounced decrease in width for sediment-rich tidal flats. In this case, the model appears to overestimate the reduction in the width of the tidal flats. The opposite appears to happen when there is an increase in SSC. Could this suggest that the model is highly responsive to changes in SSC?\nMoreover, while for the observations, the reduction in width with decreasing SSC occurs at the same rate for both sediment-starved and sediment-rich systems, and the same applies to the increase in width with increasing SSC, this is not the case in the model. Additionally, the model is practically insensitive to an SSC increase of 0.8% for sediment-rich systems, whereas it is not for an increase to 2%.\nLines 182-197. Can the authors better describe the difference between actual concentration and equilibrium concentration and how they are related to SSC?\nLines 204-213. The authors describe the different responses of sediment-rich and sediment-poor systems using an analogy with the dynamics of a spring. While the analogy with spring dynamics is illustrative, it would be beneficial to explain these responses in terms of morphodynamic processes and feedbacks. Specifically, what morphodynamic mechanisms and feedbacks control such responses? How do factors like tidal range, sediment transport, deposition rates, erosion, and hydrodynamics interplay to produce these observed behaviors? Providing a detailed explanation grounded in morphodynamic principles would strengthen the understanding of these differential responses to changes in SSC between sediment-rich and sediment-poor systems.\nLines 215-230. First. Figures 4C and 4D depict concave-up versus convex tidal flat profiles and shapes. The same authors have previously explored and effectively elucidated (Hu et al., JGR-ES 2015) this difference (convex shape for tide-dominated areas; concave shape for wave-dominated areas). However, I don't recall this shape difference being previously linked to sediment availability. Interestingly, in the present study, the focus is solely on sediment availability, with no consideration given to the potential influence of tidal range and waves. Could the authors provide insights into reconciling these divergent findings?\nLines 215-230. Second. I do have a question. How do you determine the point at which new equilibrium conditions are reached? Can you quantify the timescale over which tidal flats respond to alterations in external forcing? More specifically, can you determine the time it takes for certain physical properties (like elevation, accretion rate, or progradation rate) to reach a specified percentage of their equilibrium value following a change in forcing? (e.g. D’Alpaos et al., JGR 2011)? This could be quite relevant as it would enable the estimation of the time needed for morphodynamic equilibrium conditions to be attained (referred to as relaxation time).\nLines 253-278. The authors did not demonstrate the possibility of extending their results to other coastal systems worldwide. The considered case is quite particular because, even in the case of sediment-poor systems, these systems are characterized by SSC values much larger than those found in other coastal systems globally. Moreover, there is a consensus that both sea level rise rates and sediment supply critically influence coastal dynamics, determining their persistence or disappearance (e.g., Kirwan et al., GRL 2010; Marani et al., JGR-ES 2010; Kirwan et al., Nat. Climate Change 2016; Mariotti and Carr, WRR 2014). The interplay of these factors should not be assessed in isolation. Curiously, the rates of sea level rise impacting the Chinese coast are not addressed in this study. Could this potentially impact your results? Might this also influence the anticipated response of your study sites as sea level rise accelerates?\nLines 271-278 The authors mention that “due to the time scale (2002-2016) we considered in the current study we did not include the impact of sea level rise, but over several decades to centuries, its impact can be pronounced3”. I comprehend and concur with this perspective. Nonetheless, if we aim to furnish long-term predictions, accounting for SLR becomes imperative. How might the authors reassure readers that these findings remain unaffected by varying SLR rates?\n(Remarks on code availability)", "reviewer_3": "The paper presents a data-driven analysis of tidal flat morphology from spatial datasets across China's coastline. The synthesis work utilizes various spatial datasets with disparate temporal and spatial resolutions to ascertain the effect of suspended sediment concentrations, tidal range, and wave height on tidal flat width and slope. The paper finds that SSC is a major factor in tidal flat width and recommends excess sediment be allocated to low-sediment coastal systems.\nThe noteworthy results include positive correlation of tidal flat width with suspended sediment concentrations and tidal range and the tidal slopes positive correlation with tidal range. The authors suggest a limited impact of additional sediment in sediment rich coastal regions.\nThe work does have some limitations. By ignoring the largest driver of loss i.e. direct conversion, the authors have limited the impact of the work. A brief discussion on anthropogenic loss would increase the impact of the work, as tidal flat ecosystems with partial conversion to aquaculture and other land uses are expected to have unique morphology and change trajectories. Additionally, the 917 transects with discontinuous elevation should be discussed further. Is this a FAST database issue or an indication of anthropogenic impacts?\nUncertainty and error are mentioned but need to be thoroughly discussed for each dataset. For example, tidal flat accuracy is 82.2%, and the FAST database has a vertical accuracy of 30-50 cm accuracy. No uncertainty is reported for the TPXO9-atlas atlas or the ERA-5. While error propagation would be ideal for these datasets, that is probably not feasible. However, discussing how these errors might affect the results is necessary.\nAdditionally, Figure 1 should not use error bars for quantile ranges; instead, a boxplot would be more appropriate as the current visualization suggests to a viewer that this is the error of the slope.\nThe various data transformations may appropriately handle autocorrelation, but the current paper ignores spatial autocorrelation entirely. An exploration of Moran's I is appropriate.\n37—The Introduction conflates vegetated coastal wetlands and the ecosystem services they provide with tidal flats, which have not been demonstrated to provide these same ecosystem services or at the same magnitude. I would suggest finding sources that directly discuss tidal flats.\n49 – Reclamation has a negative connotation towards the ecosystem being reclaimed and should be avoided as it suggests these ecosystems are wastelands. I suggest instead using, for example, conversion to other land use.\n59 – I suggest tidal flats be called an ecosystem, not a system.\n82 – An important context is that the spatial resolution of the underlying data is 30 m, which limits the tidal flat width.\n267 – \"Sediment starving\" should be rephrased to \"Sediment starved systems\". Additionally, a more interesting discussion is how little sediment sediment-rich tidal flats need to persist given the reduction in sediment due to dams and other coastal development.\n290—Rephrase this sentence: \" The global tidal flat maps used over 7.0 x 105 satellite images to map tidal flat extent.\"\n327 – Adding where the highest and lowest tides were would be useful for readers.\n(Remarks on code availability)\nThe code is on codeocean so it appears to have all the necessary components to run and the authors should be commended for making it available in this format. I would recommend adding a README file to the repository there which will give a greater understanding of the scripts. The run output appears correct. The scripts appear to be mostly visualization and statistical testing. While this is fine some of the most interesting code in this paper such as extracting the tidal information to calculate the slope is absent. I could be mistaken as the .mat files can not open in codeocean or on a computer without a copy of matlab.", "reviewer_4": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature Communications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career Researchers who co-review manuscripts.\n(Remarks on code availability)"}, "author_response": "“Dynamics and drivers of tidal flat morphology in China”\nShuai Liu, Zhan Hu, Tim J. Grandjean, Zheng B. Wang, Vincent T. M. van Zelst,\nLin Qi, Tianping Xu, Jun Young Seo, Tjeerd J. Bouma\nItemized List of Changes and Answers to the comments\n1. Response to Reviewer #1 (in blue):\n1.1 This manuscript by Liu et al. aims to study the dynamics and drivers of tidal flat\nmorphology in China. They give a “spring theory” to explain the response of tidal flat\nmorphology to suspended sediment concentration (SSC). This theory is summarized\nbased on the tidal flat morphology change during 1984-2016 in China. However, during\nthis period, the loss of tidal flat in China was mainly due to direct reclamation or indirect\nhuman activities, such damming, nourishment, far field effect of coastal reclamation.\nThe authors mentioned that the human induced tidal flat lost is excluded from this study.\nI doubt that all the direct and indirect influence can be totally removed from the data.\nResponse:\nWe thank the reviewer for the valuable comments. We focused on China’s tidal flat\nsystem as it has the world’s 2nd largest tidal flat area (i.e., 12049 km2 in total) that\nrepresents a great variety of tidal amplitudes, wave climates, and sediment availability\nregimes. These features make China’s tidal flats a suitable system to study the impact\nof natural processes and environmental changes on tidal flat morphology. We however\nfully agree that the loss of tidal flats in China during the study period (2002-2016) has\nindeed been strongly affected by human activities, whether directly or indirectly.\nIn the current study, we focus on understanding how tidal flats respond to indirect\nexternal disturbances from a morphodynamic perspective, while losses due to direct\nhuman interventions (reclamation) are generally less predictable. To prevent our\nanalyses from being influenced by the direct effect of human induced tidal flat loss, we\nexcluded tidal flat transects where land is reclaimed during the study period. This\nreduced our overall dataset by 26%. The exclusion was based on the identification of\nmorphological changes in the tidal flats and satellite imagery from Google Earth Engine,\nwhich allowed us to pinpoint areas that had been subject to reclamation efforts. For the\nremaining 74% of the tidal flats, indirect far field effects of reclamation cannot be\nexcluded and hence are contained in our results. To ascertain that this also did not\nsignificantly affect the main conclusion of this study, i.e., the conditional response of\ntidal flat width to SSC change, we carried out additional analyses for Indonesia, the\nUnited States, and Australia, three countries without intensive reclamation. These\nadditional analyses revealed a similar conditional response of tidal flat width to SSC\nchange, supporting the generality of the present findings. Lastly, the effect of damming\nis considered via the reduction of SSC at the coasts, which is considered as a key\nenvironmental change on tidal flat morphology in the current study.\nTo address the concern on the impact of human activities on our results, we add the\nfollowing text in the Discussion in lines 331-335:\n“In our analysis, we focus on understanding how tidal flats respond to indirect external\ndisturbances from a morphodynamic perspective, while losses due to direct human\ninterventions (reclamation) are generally less predictable. Thus, we excluded data\npoints directly impacted by human activities, such as conversion to other land uses,\naccounting for 26% of the total transects in our study (Supplementary Fig. 12).”\nTo clarify the methodology, we revised Supplementary Figure 12 as:\n[figure redacted]\nSupplementary Figure 12. Examples of tidal flat sites directly affected by human\nactivities. The red areas indicate the regions of tidal flats that have disappeared from\n2002 to 2016 due to direct reclamation.\n1.2 My first concern is that is this theory universal or only applicable to China’s tidal\nflat? If the former, why it can be summarized from the China’s case in which the human\nimpact should be the dominant drivers. If the latter as the authors selected the Western\nScheldt site as a case study, what is the most different characteristics between China’s\ntidal flat and others around the world?\nResponse:\nWe thank the reviewer for the valuable comment. It is indeed important to check if this\ntheory can be applied to other countries than China. For that reason, we checked if the\ntheory is also applicable to three other countries with extensive tidal flats (i.e.,\nIndonesia, Australia, and the United States with tidal flat areas ranked 1st, 3rd, and 4th\nglobally). The corresponding data points are included in the new Fig. 5b and Fig. 5c of\nthe revised manuscript (the associated SSC values were too low to incorporate in Fig.\n5a).\nWe chose China as the main research area because of the large tidal flat area as well as\na variety of tidal ranges, wave heights, and sediment availability. We selected the\nWestern Scheldt site as a singular case study to validate our model given the unique\npublic availability of highly detailed tidal flat bathymetry data over time (2004-2012),\nwhich is lacking for most areas around the world. To clarify the above point, we added\nlines in 255-261 and 617-627 and revised Figure 5 as:\n“The observed elastic response of tidal flat morphology in China also has global\nrelevance, as similar dynamics are observed from three other countries with substantial\ntidal flat areas, i.e., Indonesia, Australia, and the United States. These three countries\nare ranked 1st, 3rd, and 4th place globally in tidal flat areas (with China being the 2nd\nplace). Data from these four countries collectively show: 1) tidal flat width grows if\nSSC increases and shrinks if SSC declines; 2) tidal flats with higher SSC have lower\nexpansion rates as SSC increases, but higher retreat rates if SSC reduces (Fig. 5b, c).”\n“To test the observed elastic response of tidal flat morphology in China, we further\nanalyzed the data from three other countries with substantial tidal flat areas, i.e.,\nIndonesia, Australia, and the United States. There are a large number of observation\ntransects in these countries and many of them are affected by direct human intervention.\nTo select the representative transects, we categorized tidal flat transects from these\nthree countries into four groups for each country, based on initial SSC levels (0-20 mg/L\nand > 20 mg/L) and SSC change rates (-9 to -3 %/year and 3 to 9 %/year). Within each\ngroup, we randomly selected 50 tidal flat transects, and subsequently excluded the\ntransects with direct human impact based on the “satellite” base map from Google\nEarth Engine. This resulted in 34 transects in Indonesia, 49 in Australia, and 33 in the\nUSA. For China, we grouped SSC into sediment-starved and sediment-rich areas as\nmentioned in the section “Suspended Sediment Concentration (SSC) data”.”\n[panel redacted]\nFig. 5 – Modeled and observed tidal flat width response to sediment availability\nchanges. (a) The contour map represents the tidal flat width change corresponding to\ndifferent variation rates in SSC from DET-ESTMORF modeling, whereas bubbles\nindicate the representative data points for tidal flat width changes and the number\nindicates the location along China’s coast (see methods for data selection). Red bubbles\nindicate tidal flats expansions, and green bubbles indicate tidal flats retreats. The size\nof the bubbles indicates the variation rate. The upper left and lower right corners of the\ndiagram are two ‘hot’ zones, i.e., sediment-starved sites with an increase of SSC and\nsediment-rich sites with SSC drop. The area between the two solid black lines indicates\na ‘neutral’ zone where the interannual variation of tidal flat widths is within -0.1% and\n0.3%. There are no data points in the upper left corner, i.e., rapid SSC increase (> 1%\nper year) in sediment-rich systems. (b) The rate of tidal flat width changes in relation\nto the initial SSC level when SSC increases by 3 ~ 9 %/year in all four countries (p <\n0.01), indicating slower expansion of sediment-rich areas if SSC increases. (c) The rate\nof tidal flat width changes in relation to the initial SSC level when sediment decreases\nby 3 ~ 9 %/year in the four countries (p < 0.05), indicating faster retreat of sediment-\nrich areas if SSC decreases. The brown line is the linear regression line with the p-\nvalue. Data from these countries are randomly selected based on their initial SSC level\nand SSC change rate (see Methods). ‘N’ means the number of data points selected from\neach country.\n1.3 The second one is that is it appropriate to use SSC to characterize the sediment\nsupply as the authors ignored the dynamic factors, such as sea level rising, change of\ntides and wind-waves, and terrigenous sediment supply? Also, even the tidal flat change\nitself can drive SSC variation. So, how to analyze the nonlinear correlation between\nthem? In my opinion, both the methodology and the results of this manuscript are not\nsound.\nResponse:\nWe thank the reviewer for these questions and realize that a better explanation is needed\non why we use SSC to characterize the sediment availability.\nFirstly, indeed, the changes of tidal flat itself may lead to SSC variation, but such an\nimpact is considered small compared to human induced SSC variation (e.g. damming),\nas indicated by studies on global-scale SSC in coastal areas (Dethier et al., 2022; Hou\net al., 2024). Correspondingly, our data also imply that the impact of tidal flat change\non SSC is small, as the overall SSC drops with a reduction in tidal flat width (Fig. 3c,\nd). If tidal flat change would have a large impact on SSC, the reduction in tidal flat\nwidth would lead to more sediment into the water column, and would mitigate the SSC\nreduction. However, such mitigation is not observed from our dataset, which implies\nthe nonsignificant role of tidal flat width on SSC. Secondly, SSC is commonly\nconsidered to be a key external driver of intertidal morphological changes in previous\nstudies (e.g., Fagherazzi et al., 2006; Friedrichs, 2011; Kirwan et al., 2010, 2016; Maan\net al., 2015; Roberts et al., 2000), in which the impact of tidal flat change on SSC is\nrarely considered, and is beyond the scope of the current study.\nAdditionally, we agree that it is necessary to consider the potential impacts of variations\nin wind waves, tidal range, and sea-level rise.\nTo quantify the possible importance of the change of waves, we newly calculated the\nchange rate of significant wave height at 105 sites along the coast of China (with a\nresolution of 0.5 degrees) from ERA5 data. The results show that 95% of tidal flat areas\nhave experienced very limited wave height variability (below 0.1 cm/year) compared\nto tidal flat area changes from 2002 to 2016. Therefore, for the considered period, there\nis no significant correlation between the wave height change rate and the change rate\nof tidal flat width on China’s coast (p = 0.42).\nRegarding the change of tidal range, we calculated the change rates of tidal range from\nTPXO9 data, but the results indicated no significant correlation between the changes in\ntidal flat width and tidal range (p = 0.25). This may be due to the relatively small\nchanges in tidal range along China's tidal flats during the study period, with an\naverage change of 0.3% per year.\nRegarding sea-level rise (SLR), we newly included additional data on SLR from 14\ncoastal stations in China, and did a correlation analysis between SLR and tidal flat width and\nSLR. We found that there is no significant correlation between SLR and the local changes in\ntidal flat width (p=0.89). This lack of correlation is likely due to the relatively short\ntime scale of interest.\nTo demonstrate the validity of considering SSC change as arepresentative driver for\ntidal flat width change, we added text in lines 455-456 as:\n“SSC is considered representative of the local sediment availability35–37,59, and a key\nexternal driver on tidal flat morphodynamics.”\nTo indicate the impact of the wave, we included the text in lines 442-446 as:\n“To assess if a change in waves might affect tidal flat width, we calculated the change\nrate of significant wave height at 105 sites along the coast of China (with a resolution\nof 0.5 degrees) from ERA5 data. It shows that 95% of tidal flat areas have experienced\na minimal variation in significant wave height below 0.1 cm/year from 2002 to 2016.\nThus, there is no significant correlation between the wave height change and tidal flat\nwidth dynamics (p = 0.42).”\nTo indicate the impact of tidal range change, we included the text in lines 414-417 as:\n“We also calculated the change rates of tidal range from TPXO9 data between 2002\nand 2016, but the results indicated no significant correlation between the tidal flat\nwidth changes and tidal range changes (p = 0.25). This may be due to the relatively\nsmall changes in tidal range along China's tidal flats during the study period, with an\naverage change of 0.3% per year.”\nTo discuss the impact of SLR, we added analysis in lines 342-346 and 417-421 and\nSupplementary Table 1 as follows:\n“Due to the decadal time scale (2002-2016), sea-level rise does not have a clear impact\non tidal flat morphology based on data from 14 Chinese long-term water level\nobservation sites (p = 0.89, see Methods). However, over longer time scales (e.g., a\ncentury), its impact can be pronounced, especially with concurrent SSC reduction22,35–\n37, emphasizing the need to expand long-term monitoring in the future.”\n“We collected SLR data from 14 coastal sites in China44 and calculated the correlation\nbetween the SLR data and changes in local tidal flat width. However, the results indicate\nno significant correlation (p = 0.89). The tide gauge data of the 14 coastal sites are\ncollected from the Permanent Service for Mean Seal Level45,46 (see Supplementary\nTable 1).”\nSupplementary Table 1. Tidal gauge stations and trends\nStation name Latitude (deg) Longitude SLR rate\n(deg) (mm/year)\nDalian 38.89 121.68 3.50\nQinhuangdao 39.90 119.60 0.00\nZhapo 21.58 111.82 2.30\nKanmen 28.08 121.28 2.40\nLusi 32.13 121.62 5.70\nYantai 37.53 121.38 -0.20\nXiamen 24.45 118.07 1.10\nTanggu 39.00 117.72 3.74\nShijiusuo 35.38 119.55 1.68\nLianyungang 34.75 119.45 6.07\nShanwei 22.75 115.35 1.31\nDongfang 19.10 108.62 3.41\nBeihai 21.48 109.08 1.08\nHaikou 20.02 110.28 6.31\nThe detail comments are given below:\n1.4 Line 46-47: This may be true around the world, but how is the situation in China?\nI believe in China during this period, tidal flat reclamation is the dominant driver for\nthe loss or indirect by human activities, such damming, coastal engineering, far field\neffect of land reclamation.\nResponse:\nWe agree with the reviewer that further discussion about human impact is needed here.\nWe added the discussion in lines 331-335 as addressed in comment #1.1 above.\n1.5 Line 58-59: Yet in this study, this is still not to be revealed.\nResponse:\nWe thank the reviewer for the discussion. Indeed, the current study may not fully\nunravel the impact of sediment flux change on tidal flat morphology. However, we\nbelieve that the findings in the current study do advance the understanding of tidal flat\ndynamics and inform better management strategies by conveying the following novel\nkey messages that we do show for China as well as three other major countries\n(Indonesia, Australia, and the US) with tidal flats:\n- In China's tidal flat systems, SSC is a critical factor controlling the width of the\ntidal flats, while tidal range is a key factor controlling the slope of the tidal flats.\n- Sediment-rich flats exhibit more rapid area losses to SSC reduction compared to\nsediment-starved areas, and sediment-starved flats expand faster if SSC increases.\n1.6 Line 70-71: Sites affected by direct human impact (e.g., reclamation) were excluded\nfrom the analysis. So how about the indirect human impacts?\nResponse:\nWe thank the reviewer for the comment, and our responses are provided collectively in\ncomment #1.1.\n1.7 Line 111-113: Why is it positively correlated with tides and negatively correlated\nwith waves? Is there any explanation on the dynamics?\nResponse:\nWe added a morphodynamic explanation in lines 150-153 as:\n“Additionally, tidal range also plays a secondary role in tidal flat width, as naturally\nlarger tidal ranges increase the vertical extent of intertidal area, which contribute to\nwider tidal flats18. Lastly, tidal flat width exhibits a weak negative correlation with wave\nheight, which may be caused by wave-induced mobilization of sediments9.”\n1.8 Line 113-116: The stepwise linear regressions are equation (3) and (4)? The relative\nimportance means the weight of the two terms? How are they determined? This is pure\nmathematical statistics. Is there any physical explanation?\nResponse:\nWe thank the reviewer for these comments and questions, which indicate that further\nclarification and physical explanation is needed here. First, we used stepwise linear\nregression to select the best combination of independent variables that explains the\nspatial distribution of the tidal flat morphology. Subsequently, we established a multiple\nlinear regression model for the selected variables (Equation 3 and 4). The relative\nimportance of each variable denotes the contribution of each term, which is calculated\nby assessing its contribution to model's determination coefficient (R2). This method has\nbeen commonly used in previous studies (Ladd et al., 2019; Wang et al., 2020).\nTo better explain the usage of the stepwise linear regressions and multiple linear\nregression models, we revised the text on the stepwise linear regression in lines 492-\n493 and 496-499 as:\n“First, we used stepwise linear regression to select the best combination of independent\nvariables that explain the spatial distribution of the tidal flat morphology.”\n“Subsequently, we established a multiple linear regression model for the selected\nvariables (Eq. 3 and Eq. 4) and calculated their relative importance. The relative\nimportance is calculated by assessing their contribution to the model’s determination\ncoefficient (R2).”\nWe added the physical explanation in lines 145-149 and 153-158 as:\n“The high SSC leads to a large sediment settling flux during each tide. Hence, there\nmust also be more energetic hydrodynamic forcing to re-erode the additional sediment\nto maintain the morphological equilibrium at such high SSC. In general, wider tidal\nflats have higher bed shear stress from tidal current and waves ( in Eq. (6))\ncompared to narrower flats9 (Supplementary Fig. 6). Thus, it explains the correlation\nbetween high SSC and larger tidal flat width in space9,18.”\n𝜏90\n“The relation between the slope of tidal flats and tidal range is related to the spatial\ndistribution of bed shear stress10,18. On tidal flats, the representative bed shear stress\nfrom tidal currents and wind waves is generally higher at the seaward boundary and\ndecreases towards the landward boundary, leading to an erosion trend at the low tidal\nflats but a deposition trend at the higher tidal flats. Greater tidal ranges can increase\nsuch differences and lead to steeper tidal flat profiles (see also Supplementary Fig. 7).”\n1.9 Line 136-137: This statement seems wrong. The negative gradient should be due to\nthe high shear force at higher tidal flat and the small shear force at lower tidal flat.\nFigure 5 in Supplementary does not show this characteristic. Again, if bed shear stress\ncan be used to explain the relationship between tidal flat width and tidal currents, how\nabout the wave-induced bed shear stress?\nResponse:\nWe apologize for the confusion related to “negative gradient” of bed shear stress\ndistribution.\nWe compared the distribution of bed shear stress on tidal flats under different tidal\nranges. The profiles steepen when low tidal flats exhibit higher bed shear stress\ncompared to high tidal flats, and the bed shear stress has a landward negative gradient.\nThis gradient is more pronounced with larger tidal ranges. Moreover, the bed shear\nstress calculated here is indeed the result of the combined effects of waves and tidal\ncurrents. Similar spatial patterns have been reported in previous studies, (e.g.,\nFriedrichs, 2011; Hu et al., 2015).\nTo make the above points clear, we revised Supplementary Figure 7 and in lines 153-\n158 as:\n“The relation between the slope of tidal flats and tidal range is related to the spatial\ndistribution of bed shear stress10,18. On tidal flats, the representative bed shear stress\nfrom tidal currents and wind waves is generally higher at the seaward boundary and\ndecreases towards the landward boundary, leading to an erosion trend at the low tidal\nflats but a deposition trend at the higher tidal flats. Greater tidal ranges can increase\nsuch differences and lead to steeper tidal flat profiles (see also Supplementary Fig. 7).”\nSupplementary Figure 7. Schematic diagram of bed shear stress gradient ( )\ncalculation (a) and comparison of for different tidal ranges based on simulation\n∆𝝉𝟗𝟎\n(b).\n∆𝝉𝟗𝟎\n1.10 Line 176-177: What do you mean the tidal flats in the estuary? Most tidal flats in\nChina are not in the estuary. How is the distribution of sediment-rich and sediment-\nstarving tidal flats along the China’s coast?\nResponse:\nIt is not clear in the original text. Here, the tidal flats in the estuary refer to those located\nin the five major estuarine areas (Supplementary Figure 2, the Changjiang River, the\nYellow River, the Pearl River, the Minjiang River, and the Liaohe River) following a\nprevious study (Bi et al., 2017). To make this point clear, the text has been revised in\nlines 192-194 as:\n“sediment-rich (SSC > 75 mg/L, average SSC in five major Chinese estuaries,\nSupplementary Fig. 2; the Changjiang River Estuary, the Yellow River Estuary, the\nPearl River Estuary, the Minjiang River Estuary, and the Liaohe River Estuary)”\nTo show the distribution of sediment-rich and sediment-starved tidal flats along China’s\ncoast, we added the Supplementary Figure 2 as:\n[figure redacted]\nSupplementary Figure 2. Distribution of data points in five major estuaries and\nin sediment-starved and sediment-rich tidal flats on the China’s coast. Five major\nestuaries in China are the Changjiang River, the Yellow River, the Pearl River, the\nMinjiang River, and the Liaohe River, following a previous study22.\n1.11 Line 193: The sediment condition is defined by the SSC in the tidal flat. So, are\nall the tidal flats in sediment-rich area higher than the morphological equilibrium\n(convex) and those in sediment-starving area lower than the equilibrium (concave)?\nResponse:\nWe thank the reviewer for the comment. No, the tidal flats in sediment-rich areas are\nnot always higher than the morphological equilibrium and those in sediment-starved\nareas are not always lower than the equilibrium either. According to the original\nliterature on dynamic equilibrium theory (Friedrichs, 2011) and later in the subsequent\nreview (Green & Coco, 2014), sediment-rich systems typically have a convex profile\nas their morphological equilibrium, while sediment-starved systems often have a\nconcave profile. Thus, we followed these previous theoretical studies and used the\nconvex and concave profiles to represent sediment-rich and sediment-starved flats,\nrespectively.\nTo make the above point clear, we add text in the caption of Fig.4 in lines 224-226, as:\n“The convex shape of sediment-rich flats and the concave shape of the sediment-starved\nflats correspond to the ideal profiles from the dynamic equilibrium theory18,25.”\n1.12 Line 255-256: It is curious what is the critical condition for tidal flat morphology\ntending to move towards the equilibrium state rather than being driven away from it if\nthe initial morphology reached the equilibrium.\nResponse:\nWe included the following text in the Discussion (lines 301-312) to explain the\nmechanism that tidal flat morphology tending to move towards the equilibrium state\nrather than being driven away from it:\n“The conditional responses of tidal flat morphology can be explained by the balance\nbetween sediment availability and hydrodynamic forcing. Sediment-rich tidal flats\ntypically have flatter and shallower profiles, which are subject to greater wave and\ncurrent induced bed shear stresses9. On these flats, surplus sediment is less likely to\nsettle, hindering tidal flat expansion, but a sediment availability deficit can easily lead\nto rapid erosion due to the primitive high level of bed shear stress. Conversely,\nsediment-starved flats have relatively lower bed shear stresses due to the steeper and\ndeeper profiles9, making them able to accommodate surplus sediment and resistant to\nfurther erosion during sediment deficit. These conditional responses lead to the\nobserved spring-like behaviors of tidal flat morphodynamics that tend to move towards\nthe equilibrium state rather than being driven further away from it (Fig. 4). This\nmechanism can be well explained from a modeling perspective, provided in\nSupplementary Text.”\n1.13 Line 296: How to deal with the inaccurate part of tidal flat area map?\nResponse:\nWe acknowledge the inaccuracies in the tidal flat area map, which primarily stem from\nthe limitations of remote sensing methods (Murray et al., 2019, 2022). The inaccuracy\ncan be observed in areas of highly turbid water, polluted areas, aquaculture ponds, and\nareas subject to strong wave action.\nHowever, to our knowledge, this tidal flat area map is the only freely accessible tidal\nflat dataset that enables doing large-scale analysis such as needed for the current study.\nBased on the accuracy of the original data (>80%), we believe that the inaccuracy in\nthe datasets is not so large that it would affect the main findings of the current study.\nTo elucidate the sources of possible errors, we have added text in lines 368-374:\n“The overall accuracy of the tidal flat area map is 82.2%39. Misclassification of tidal\nflats (pixels) can occur in areas of highly turbid water, polluted areas, aquaculture\nponds, and areas subject to strong wave action. Despite the potential errors, to our\nknowledge, this map is the only freely accessible tidal flat map that covers large spatial\n(national) and temporal (decadal) scales. The accuracy of this map is sufficient\n(>80%)39 to reveal the overall dynamics of tidal flat areas and to support the main\nfindings of the current study.”\n1.14 Line 320: Compared to tidal asymmetry, tidal range is not the most accurate\nindicator for tidal flat morphology variation or sediment transport. As TPXO9-atlas\ndataset also provides the shallow water tidal constituents, have you examined the\nrelevance of tidal asymmetry to the width and slope change of tidal flats?\nResponse:\nWe can calculate the tidal asymmetry using the tidal constituents provided by the\nTPXO9-atlas dataset. By integrating the analysis with tidal flat width and slope data,\nthe results indicated that the width of tidal flats with flood dominance is significantly\ngreater than that of flats with ebb dominance (p < 0.05). However, the magnitude of\ntidal asymmetry shows no significant correlation with the spatial distribution of tidal\nflat width (p = 0.42). Therefore, tidal asymmetry cannot explain the spatial distribution\nof tidal flat width in the same way that tidal range does.\nWe included these results in the manuscript by adding text in lines 126-127, 405-409\nand Supplementary Figure 4 as:\n“Furthermore, the width of tidal flats with flood dominance is markedly greater than\nthat of those with ebb dominance (Supplementary Fig. 4), which is in line with previous\nstudies18.”\n“Tidal asymmetry is calculated from the phase difference between the M2 and M4 tidal\nconstituents (2θ -θ ). A phase difference within the range of 0° to 180° results in a\nM2 M4\nflood-dominant tide. Conversely, a phase difference between 180° and 360° indicates\nan ebb-dominant tide42,43. Under the same phase difference, the amplitude ratio of M4\nand M2 tidal constituents is used to indicate the magnitude of the tidal asymmetry.”\nSupplementary Figure 4. Comparison of tidal flat widths between flood-dominant\nand ebb-dominant systems\n1.15 Line 330: How is the wave data coupled with tides for the calculation of τ90?\nThe mean bed shear stress under combined waves and tidal currents during a wave cycle\nis calculated as (Soulsby et al., 1995)\n\n  [1( wave )3.2]\nm cur  \ncur wave\nThus, the maximum bed shear stress during a wave cycle is calculated as\n [(  cos)2 ( sin)2]0.5\nmax m wave wave\nwhere θ is the angle between the current direction and the direction of wave propagation.\nIn our study, as both the currents and wave propagation are in the cross-shore\ndirection following previous studies (Hu et al., 2014; Maan et al., 2015). is\n𝜃 = 0\nquantified every 30 minutes during a tidal cycle. Subsequently, is derived as the\n𝜏max\n90th percentile of τ\nmax\nover a tidal cycle, which is considered a\n𝜏\ns9 0the hydrodynamic\nforcing that drives morphological changes (Friedrichs, 2011). To show this point clearly,\nwe have added the text in lines 548-557.\n1.16 Line 363: It is vague that the utilize of SSC data and TSM data. The TSM data is\nthe suspended matter concentration on the surface, rather than the water column. Would\nit be suitable to represent the SSC in the water column, especially in the estuary where\nthe water is highly stratified?\nResponse:\nActually, we used the total suspended matter (TSM) data to represent suspended\nsediment concentration (SSC) in the water column. The TSM data are from the\nGlobColour project. The data represent total suspended matter in the water column and\nhave been developed, validated, and distributed by ACRI-ST, France (Barrot et al.,\n2007). The applicability of the data for large-scale studies and the reliability of this\nmethod have also been substantiated in previous studies (e.g., Schuerch et al. 2018).\nTo make these points clear, we revised the text in lines 456-459 as:\n“The SSC data near monitoring tidal flat transects were obtained from the GlobColour\nproject (https://www.globcolour.info). We used the total suspended matter (TSM) in the\nwater column to represent SSC. This method has been previously used and found\nreliable for large scale analyses59,60.\n1.17 Line 383-386: It is unclear that how it is defined that the annual average SSC level\nof China’s tidal flat coast. What is the spatial resolution for each bin to average and how\nfar off the coast?\nResponse:\nTo improve clarity on the spatial resolution of the SSC data and the distance from the\ncoast, we have revised the expression in lines 475-476 and 464-465 as:\n“This value is obtained by calculating the average SSC of pixels containing tidal flats\n(4 km resolution).”\n“The SSC data product has a horizontal resolution of 1/24 degree (generally 2.2 km off\nthe coast)…”\n1.18 Line 408-409: How are equations (3) and (4) obtained? How do they perform in\nChina’s tidal flats? How is the time-variation of tidal range along the coast? Do the\nchanges in width and slope also conform to these equations?\nResponse:\nWe obtained equations (3) and (4) from multiple linear regression and they are only\napplied to analyzing the spatial distribution of tidal flat width and slope in China.\nDetails of these equations are addressed in response # 1.8. They perform well for\nChina’s tidal flats, indicating that the spatial difference in flat width is mostly influenced\nby suspended sediment concentration (SSC, R2 = 0.6, p < 0.05) while the spatial\ndifference of flat slope is mostly influenced by tidal range (TR, R2 = 0.30, p < 0.05).\nThus, the spatial changes in width and slope are confirmed with these equations.\nTemporal variation of slope cannot be obtained as there is only one large-scale tidal flat\nbathymetry dataset over time. Temporal variation of width (via global tidal flat maps\ndata) with SSC is revealed and discussed in Fig. 3, 4, and 5 of the manuscript. The\ntemporal variation of tidal range along the coast is small, which is by average\n0.3 %/year on China’s coast.\nTo make the above points clear, we added detailed explanations and performances of\nequations (3) and (4) as indicated in response # 1.8.\nThe time-variation of tidal range along the coast is included in line 414-417, as:\n“We also calculated the change rates of tidal range from TPXO9 data between 2002\nand 2016, but the results indicated no significant correlation between the tidal flat\nwidth changes and tidal range changes (p = 0.25). This may be due to the relatively\nsmall changes in tidal range along China's tidal flats during the study period, with an\naverage change of 0.3% per year.”\n1.19 Line 439-448: How are the key parameters determined? Like n in Equation (6),\nws and D in Equation (7). The volume sediment concentration c has a unit of m3/m3,\nand the local equilibrium concentration ; has a unit of mg/L. So how can these two\nvariables be directly subtracted in Equation (8)?\n𝑐𝑒\nResponse:\nThe key parameters and the corresponding references are detailed in the supplementary\nTables 4 and 5. Moreover, the local equilibrium concentration can be converted to\nvolume concentration by dividing the sediment density ( ) (Rijn & C,\n𝑐𝑒\n2007). 3\n𝜌𝑠 = 2650 𝑘𝑔/𝑚\nTo make these points clear, we added the text in lines 576-578 and 568-569 as:\n“The key parameters are detailed in supplementary Table 4, and the values of these\nparameters are based on previous modeling work (Supplementary Table 5)9,11,75.”\n“The local equilibrium concentration can be converted to volume concentration by\ndividing the sediment density ( )74.”\n𝑐𝑒\n3\n𝜌𝑠 = 2650 𝑘𝑔/𝑚\n1.20 Line 471-474: It is unclear how/whether the τw is used for the morphology change\nof tidal flats through Equations (1)-(2) and (5)-(12). The random waves are also\nexcluded from the experiments. It is doubt that if the model considers the wave effects.\nResponse:\nThe calculation of is provided collectively in response #1.15. We agree with the\nreviewer that more details should be provided here. The wave height at the model\n𝜏𝑤\nboundary is set for each tidal cycle by a random draw from the Rayleigh distribution\naround a constant mean value (Maan et al., 2015). Subsequently, the model calculates\nthe corresponding wave height at each grid cell, taking into account wave shoaling and\ndissipation due to bed friction, by the continuity equation for the wave energy flux\n(Christoffersen & Jonsson, 1985): To clarify this point, we have added the text in lines\n536-537 as:\n“The incident is obtained by a random draw from the Rayleigh distribution around\na given mean value51.”\n𝐻𝑠\n1.21 Line 477: Why not chose a Chinese site? Would this site be represented for a high\nturbidity Chinese site?\nResponse:\nWe did not select a Chinese site for the case study of sediment-starved areas because it\nis challenging to find field data for model validation. Most field observations in China\nare conducted in sediment-rich regions, such as Jiangsu and the Yangtze River Estuary.\nInstead, we chose the Western Scheldt site as a case study site due to the availability of\ndetailed tidal flat bathymetry data over time (2004-2012). Additionally, our model has\nbeen tested and verified for its applicability at this site in previous studies. Although\nthis site is not located in China, the principle of the model is universal, and the\nconsistency of these simulation results supports the global applicability of our\nconclusions.\nTo clarify the reason for choosing this site, we added the following text in lines 582-\n584:\n“We did not select a Chinese site for the case study of sediment-starved area, as it was\nnot possible to find detailed field data for model validation in China, while the Western\nScheldt has a unique detailed dataset available.”\n1.22 Line 490: This section is the model experimental results. How reliable is it\ncompared to the measured results?\nResponse:\nThis section encompasses both the measured results and model data, providing an\nexplanation of the data for Figure 5a. The first paragraph indicates the selection criteria\nfor the bubble plot, which are derived from the measured results. The second paragraph\ndetails the method for the color map in the background, based on model experimental\nresults. From the comparison between the bubble plot and the background, we believe\nour model results are well in line with data on the conditional changes of sediment-rich\nand sediment-starved tidal flat to sediment availability variations.\nTo make this point clear, we add the text in lines 597-598 and 248-250 as:\n“To analyze the temporal changes in tidal flat width, we integrated measured data (the\nbubble chart of Figure 5a) with experimental results (colormap of Figure 5a).”\n“This synthetic modeling aligns with the observed data points along China’s coastline.\nSites with higher rates of widening or narrowing mostly fall in the ‘hot’ zones, while\nsites with lower rates generally fall in the ‘neutral’ zone.”\n1.23 Line 497: Why the number 20% is selected as the critical value? If chose 30%,\nwould the conclusion be changed?\nResponse:\nThe critical value here is applied in the selection of representative points for the\nbubble chart in Figure 5, as 98% of the points are within this range, and points with a\nhigher change rate are likely related to direct human impacts. We agree with the\nreviewer that conducting a sensitivity analysis with alternative threshold values is a\nreasonable approach. If we chose 30%, the conclusion would not be changed.\nTo make this point clear, we include this figure in the Supplementary Fig. 16.\n[figure redacted]\nSupplementary Figure 16. Sensitivity experiment for Figure 5a site selection\nexcluding points with annual variation exceeding 30%.\n1.24 In the supplementary:\nLine 50-60: There is no direct function between tidal flat width and SSC.\nLine 58: C is not related to me.\nLine 62-70: The explanation is not clear, but rather difficult to understand. τ90 can be\nused to represent for some driving forces, and SSC can reflect τ90, but it does not mean\nthat the SSC is changed all by τ90, such as the river input.\nLine 122: How to calculate Δce?\nResponse:\nWe thank the reviewer for these comments regarding the section in the Supplementary\nInformation on the explanation of the spring-like dynamics of tidal flat morphology to\nSSC change. We have revised the whole section in order to clearly explain the\nmechanism of the observed responses.\nIn the model, tidal flat morphodynamic changes are directly determined by the\ndifference between the actual sediment concentration (SSC) and the equilibrium\nconcentration (i.e., c and c in Eq. 8 in the main text). As a result, tidal flat width is a\ne\nfunction of SSC.\nThe equation S3 and S4 is to quantify the factors influencing c , in which C is the square\ne\nof .\n𝜏𝑐𝑟\nWe used the model to calculate the of tidal flats under various SSC, as well as the\nafter sediment change, and determined the changes in equilibrium concentrations\n𝑐𝑒\n( .\n𝑐𝑒\n∆𝑐𝑒)\nTo explain the relationship between tidal flat width and SSC, we revised lines in 158-\n160 in the supplementary file as:\n“In the model, tidal flat morphodynamic changes are directly determined by the\ndifference between the actual sediment concentration and the equilibrium\nconcentration (i.e., c and c in Eq. 8 in the main text).”\ne\nTo clarify the equation, we revised the text in lines 172-173 as:\n“where A and B are constants related to erosion coefficient ( ), sedimentation rate\n( ), and critical shear stress for resuspension ( ). C is the square of .”\n𝑚𝑒\n𝑤𝑠 𝜏𝑐𝑟 𝜏𝑐𝑟\nTo explain the mechanism for the responses we observed, we added text in lines 181-\n201 and Supplementary Figure 19 as:\n“When the external SSC ( ) increases, the change in is higher in the sediment-\nrich site than the sediment-starved site (Supplementary F2ig. 19), while the change in\n𝑐𝐸 𝜏90\nis lower in sediment-rich site than the sediment-starved site (Supplementary Fig.\n𝑓\n19\n(𝑐\n).𝐸 T\n)\nhe overall effect is that the change in equilibrium concentration (△ ) is higher\ntowards the sediment-rich site (Supplementary Fig. 19). Thus, facing the sa𝑐m𝑒e increase\nin actual sediment concentration ( ), the difference between change in actual\nconcentration and equilibrium concentration is larger in the sediment-starved site than\n△ 𝑐\nthe sediment-rich site (Supplementary Fig. 19). This difference gives the momentum for\nsediment accretion and subsequent tidal flat width growth. Thus, the sediment-starved\nsite responds faster than the sediment-rich site in case of sediment availability increases.\nWhen the external SSC ( ) drops, the changes in are negligible (< 0.01)\n(Supplementary Fig. 19). Therefore, shifts in equilibrium2 concentration are mainly\n𝑐𝐸 𝜏90\ndriven by the , which is negative and lower in the sediment-starved site than the\nsediment-rich site (Supplementary Fig. 19). This leads to an increase towards the\n△ 𝑓(𝑐𝐸)\nsediment-rich site (Supplementary Fig. 19), and the difference between the change in\nactual concentration and equilibrium concentration is larger in the sediment-rich site\nthan the sediment- starved site (Supplementary Fig. 19), leading to a faster response in\nthe sediment-rich site in case of sediment availability reductions.”\nSupplementary Figure 19. Simulated responses of , , and in\ntidal flats with varying SSC under sediment increase (a,𝟐 c, d) and decrease (b, d,\n∆𝝉𝟗𝟎 ∆𝒇(𝒄𝑬) ∆𝒄𝒆\nf).\nReviewer #1 (Remarks on code availability):\nThere is no README file with enough instructions for installing and running the\napplication.\nResponse:\nWe thank the reviewer for the reminder. We have added a README file with\ninstructions on the code.\n2. Response to Reviewer #2 (in blue):\n2.1 In this manuscript the authors traced the spatial and temporal morphological\nchanges of more than 2’500 tidal flat transects across China, unravelling the intricate\ncontrols governing their morphological evolution in response to changes in external\nforcing such as suspended sediment concentration (SSC), tidal range, and wave height.\nThe objective of this study, of establishing a scientific foundation for informed\nmanagement strategies is timely and relevant, considering the global decline of tidal\nflats in China and worldwide.\nThe authors demonstrate the correlations between tidal flat width and SSC distribution,\nas well as tidal flat slope and tidal range. Particularly noteworthy is the nationwide\ndecrease in tidal flat width observed from 2002 to 2016 due to reduced SSC,\nunderscoring the significant role of sediment supply dynamics. Furthermore, the\nauthors' observation that sediment-rich tidal flats exhibit a swifter response to SSC\nreduction compared to sediment-poor tidal flats, and vice versa, highlights the nuanced\ninterplay between sediment availability and tidal flat morphology. These responsive\nbehaviors are underpinned by the capability of tidal flats to revert to their morphological\nequilibrium.\nThe research presented by the authors is well designed, scientifically sound, and is\ncarried out in a consistent and rigorous way. I particularly appreciated the challenge of\nquantitatively unravelling the dependence of tidal flats from, and their response to,\nexternal forcing and changes thereof.\nThe huge dataset considered by the authors was properly analyzed and the conclusions\nare well supported by the results of the analyses. In particular, the finding that\n\"sediment-rich tidal flats respond faster to SSC reduction compared to sediment-\nstarving areas, but the opposite is true if SSC rises\" could have important implications\nto tidal-flat dynamics in the face of anthropogenic pressure, which may help advance\nfurther studies in the field of coastal morphodynamics.\nThe manuscript is well-written and effectively communicates the findings to the\nintended audience. While the study is robust, there are critical areas for improvement\nthat would enhance the manuscript's clarity, completeness, and overall impact.\nResponse:\nWe are very grateful for the reviewer’s positive evaluation of our paper, and for\nrecognizing it being timely and relevant for management. Below, we provide a point-\nby-point response to the reviewer’s comments and show how they are incorporated into\nthe revised manuscript.\n2.2 i) Describe the different responses to changes in SSC of sediment-rich and\nsediment-poor systems. While the analogy with spring dynamics is nice, it is essential\nto explain what morphodynamic mechanisms and feedbacks control such a response.\nProviding a detailed explanation grounded in morphodynamic principles would\nstrengthen the scientific basis of the observed behaviors.\nResponse:\nWe thank the reviewer for this comment. Indeed, it is essential to explain what\nmorphodynamic mechanisms and feedback control such a response. Thus, we revised\nlines 301-312 in the main text for a concise explanation, which illustrates the\nmechanism of the spring-like change of tidal flat width to SSC from a modeling\nperspective.\n“The conditional responses of tidal flat morphology can be explained by the balance\nbetween sediment availability and hydrodynamic forcing. Sediment-rich tidal flats\ntypically have flatter and shallower profiles, which are subject to greater wave and\ncurrent induced bed shear stresses9. On these flats, surplus sediment is less likely to\nsettle, hindering tidal flat expansion, but a sediment availability deficit can easily lead\nto rapid erosion due to the primitive high level of bed shear stress. Conversely,\nsediment-starved flats have relatively lower bed shear stresses due to the steeper and\ndeeper profiles9, making them able to accommodate surplus sediment and resistant to\nfurther erosion during sediment deficit. These conditional responses lead to the\nobserved spring-like behaviors of tidal flat morphodynamics that tend to move towards\nthe equilibrium state rather than being driven further away from it (Fig. 4). This\nmechanism can be well explained from a modeling perspective, provided in\nSupplementary Text.”\nAdditionally, we also rewrite the supplementary section (Supplementary Fig. 19 and\nSupplementary Text) to explain the mechanism from a modeling perspective.\n2.3 ii) Discuss the applicability of their results in diverse coastal systems, especially\nwhere sediment availability could be considerably scarcer than that along the Chinese\ncoast. Given that 50mg/L would equate to a substantial sediment concentration for some\nseverely sediment-starved systems globally, broadening the study's relevance is\nessential.\nResponse:\nWe thank the reviewer for the suggestion. In the revised manuscript, our theory has\nbeen confirmed in countries with lower sediment availability, including Indonesia,\nAustralia, and the United States, three countries with extensive tidal flat areas (ranked\n1st, 3rd, and 4th globally). The relevant results are included in the new Fig. 5 in the\nrevised manuscript.\n[panel redacted]\nFig. 5 – Modeled and observed tidal flat width response to sediment availability\nchanges. (a) The contour map represents the tidal flat width change corresponding to\ndifferent variation rates in SSC from DET-ESTMORF modeling, whereas bubbles\nindicate the representative data points for tidal flat width changes and the number\nindicates the location along China’s coast (see methods for data selection). Red bubbles\nindicate tidal flats expansions, and green bubbles indicate tidal flat retreats. The size\nof the bubbles indicates the variation rate. The upper left and lower right corners of the\ndiagram are two ‘hot’ zones, i.e., sediment-starved sites with an increase of SSC and\nsediment-rich sites with SSC drop. The area between the two solid black lines indicates\na ‘neutral’ zone where the interannual variation of tidal flat widths is within -0.1% and\n0.3%. There are no data points in the upper left corner, i.e., rapid SSC increase (> 1%\nper year) in sediment-rich systems. (b) The rate of tidal flat width changes in relation\nto the initial SSC level when SSC increases by 3 ~ 9 %/year in all four countries (p <\n0.01), indicating slower expansion of sediment-rich areas if SSC increases. (c) The rate\nof tidal flat width changes in relation to the initial SSC level when sediment decreases\nby 3 ~ 9 %/year in the four countries (p < 0.05), indicating faster retreat of sediment-\nrich areas if SSC decreases. The brown line is the linear regression line with the p-\nvalue. Data from these countries are randomly selected based on their initial SSC level\nand SSC change rate (see Methods). ‘N’ means the number of data points selected from\neach country.\nTo illustrate the methodology for selecting representative points, we added text in lines\n617-627 as:\n“To test the observed elastic response of tidal flat morphology in China, we further\nanalyzed the data from three other countries with substantial tidal flat areas, i.e.,\nIndonesia, Australia, and the United States. There are a large number of observation\ntransects in these countries and many of them are affected by direct human intervention.\nTo select the representative transects, we categorized tidal flat transects from these\nthree countries into four groups for each country, based on initial SSC levels (0-20 mg/L\nand > 20 mg/L) and SSC change rates (-9 to -3 %/year and 3 to 9 %/year). Within each\ngroup, we randomly selected 50 tidal flat transects, and subsequently excluded the\ntransects with direct human impact based on the “satellite” base map from Google\nEarth Engine. This resulted in 34 transects in Indonesia, 49 in Australia, and 33 in the\nUSA. For China, we grouped SSC into sediment-starved and sediment-rich areas as\nmentioned in the section “Suspended Sediment Concentration (SSC) data”.”\nTo discuss the applicability of the theory in other countries, we revised the text in lines\n479-481 and 255-261 as:\n“These thresholds can be considerably higher than other countries15,65, due to the\noverall higher SSC on China’s coast. Thus, sediment-starved and sediment-rich systems\nshould be defined differently in other regions of the world.”\n“The observed elastic response of tidal flat morphology in China also has global\nrelevance, as similar dynamics are observed from three other countries with substantial\ntidal flat areas, i.e., Indonesia, Australia, and the United States. These three countries\nare ranked 1st, 3rd, and 4th place globally in tidal flat areas (with China being the 2nd\nplace). Data from these four countries collectively show: 1) tidal flat width grows if\nSSC increases and shrinks if SSC declines; 2) tidal flats with higher SSC have lower\nexpansion rates as SSC increases, but higher retreat rates if SSC reduces (Fig. 5b, c).”\n2.4 iii) Consider whether the inclusion of sea level rise (SLR) effects could potentially\nimpact the outcomes of this study. Addressing the potential impacts of SLR on the study\noutcomes ensures the robustness of the study's conclusions under varying conditions.\nResponse:\nWe thank the reviewer for the comment. The supplementary data indicate that there is\nno significant correlation between the changes in tidal flat width and SLR during the\nstudy period.\nWe fully understand the reviewer’s concern on the impact of historical sea-level rise\nand have included relevant discussion and references in the manuscript in Lines 342-\n346 as:\n“Due to the decadal time scale (2002-2016), sea-level rise does not have a clear impact\non tidal flat morphology based on data from 14 Chinese long-term water level\nobservation sites (p = 0.89, see Methods). However, over longer time scales (e.g., a\ncentury), its impact can be pronounced, especially with concurrent SSC reduction22,35–\n37, emphasizing the need to expand long-term monitoring in the future.”\nLastly, the reviewer also mentioned in comment 2.26 that he/she agrees that due to the\nshort time scale of the current study (14 years), it is acceptable not to consider sea level\nrise as a factor.\n2.5 iv) Reconcile apparently divergent findings related to concave-up and convex\nprofiles, along with their underlying factors. This includes explaining how these factors\nmight influence the results and ensuring consistency with previous findings.\nResponse:\nWe thank the reviewer for the comment. From the original literature on dynamic\nequilibrium theory (Friedrichs, 2011), indeed sediment-rich systems often have convex\nprofile shapes while sediment-starved systems often have concave shapes. Thus, we\ndepicted the concave versus convex tidal flat profiles to correspond with sediment-\nstarved and sediment-rich systems in Fig 4. To make the above point clear, we added\nthe text in the caption of Figure 4 as:\n“The convex shape of sediment-rich flats and the concave shape of the sediment-starved\nflats correspond to the ideal profiles from the dynamic equilibrium theory18,25.”\n2.6 Based on these points, there is a clear need for substantial revisions to improve the\nmanuscript before it can be considered for publication in Nature Communications. The\nissues highlighted and the suggestions provided below are aimed at enhancing the\nmanuscript’s clarity, completeness, and scientific rigor, thereby elevating an already\nstrong study to a higher standard of excellence.\nResponse:\nWe appreciate the reviewer’s kind evaluation of our work as an ‘already strong study’\nand the constructive suggestions. Detailed responses are listed below.\nDetailed comments.\n2.7 Line 42. Noun as adjective. Change “tidal flats dynamics” to “tidal flat dynamics”.\nResponse:\nWe thank the reviewer for this comment. The text has been revised.\n2.8 Line 46. Do you refer to worldwide decline?\nResponse:\nHere we refer to the loss of tidal flat areas worldwide. The text has been revised in line\n43 as:\n“Strikingly, approximately 16% of the global tidal flat area was lost during 1984-2016”\n2.9 Lines 47-90. In the Introduction, the authors miss to include important literature in\nthe introduction that could provide additional context and support for their findings.\nIndeed, it would be worth mentioning that researchers in the field have demonstrated\nthrough both point (Fagherazzi et al., PNAS 2006; Marani et al., JGR-ES, 2010) and\nspatially explicit (Roberts et al., CSR 2000; Hu et al., JGR-ES 2015) models and\nanalyses, that tidal flats can attain a dynamic equilibrium condition influenced by the\nexternal forcing considered by the authors. This suggestion is rooted in the authors'\napplication of the equilibrium theory to support their findings and subsequent\ninterpretations within the text.\nResponse:\nWe agree with the reviewer that it is important to provide a context of dynamic\nequilibrium theory for the subsequent application of the theory. Thus, we included the\nsuggested references in lines 79-80 in the new paper as:\n“Finally, the observed diverse morphological responses were explained by a model\nbased on dynamic equilibrium theory9,10,18,20–22.”\n2.10 Lines 67-70. These lines are unclear. Although the authors refer readers to the\nMethods section, there remains uncertainty about the meaning of \"independent and\ncomplete profiles\" and \"elevation continuous profiles.\"\nResponse:\nThe text has been revised in lines 69-72 and 383-386 as:\n“These transects are selected at 1 km resolution, covering open-coast and estuaries,\nbut those affected by direct human impact or where the width or slope information\ncannot be extracted were excluded from the analysis (see Methods).”\n“Transects with discontinuous elevation were excluded from analysis (917 of 2538\ntransects). There are mainly two reasons that cause the discontinuous elevation: 1) gaps\nwithin the continuous elevation data (51.4%); 2) none or too few elevation data in the\nFAST database (48.6%).”\n2.11 Line 86. There is an extra period in the sentence.\nResponse:\nWe thank the reviewer for the comment. The text has been revised accordingly.\n2.12 Lines 87-88 and 102-107. The authors state that the average width of tidal flats in\nestuaries is greater than that of flats on open coasts, likely due to sediment availability.\nHowever, they do not provide sufficient evidence to support this claim. Additionally,\nregarding tidal flat slope (lines 102-107), it is unclear what factors determine the\ndifference between Fujian and Jiangsu.\nResponse:\nWe calculated the average SSC for both estuarine and open coastal areas of tidal flats.\nThe SSC in estuaries is significantly higher than that on the open coast (74.0 mg/L vs.\n47.4 mg/L), which may serve as supporting evidence. Additionally, the high slope of\ntidal flats in Fujian is a characteristic of its relatively large mean tidal range of 3.6 m\nand low SSC level of 29 mg/L, whereas the lower slope of tidal flats in Jiangsu is\ninfluenced by high SSC (110.0 mg/L) and the moderately high tidal range (2.93 m).\nTo make this point clear, we revised the text in lines 89-95 and 111-115 as follows:\n“To compare the tidal flats in estuaries and on open coasts, we selected 5 major\nestuaries in China, namely the Changjiang River Estuary, the Yellow River Estuary, the\nPearl River Estuary, the Minjiang River Estuary, and the Liaohe River Estuary\n(Supplementary Fig. 2)23 for analysis. Notably, the median flat width in these estuaries\n(807 m, N = 275) is greater than those on open coasts (512 m, N = 2263), which is\nlikely attributed to the higher median SSC for estuarine tidal flats (71.0 mg/L) than\ntheir open coast counterparts (44.0 mg/L).”\n“The tidal flats in southern Fujian have the highest median slope in the country, i.e.,\n1.5×10-2 (Fig. 1b), which is influenced by the large tidal range (3.6 m) and a low SSC\nlevel (29 mg/L). In contrast, those in southern Jiangsu show the lowest slope i.e.,\n6.7×10-4, influenced by the exceptionally high SSC (110 mg/L) and a moderate tidal\nrange (2.93 m).”\n2.13 Lines 109-116 and Figure 2. Frankly, I don't understand why the relationship\nbetween Average Width and Wave Height, or between Slope and Wave Height, is not\nshown. Given that the correlation between tidal flat slope and tidal range is weak (R^2\n= 0.30), what would be the correlation between tidal flat slope and wave height?\nFurthermore, why do the authors consider average width, while examining the median\nslope?\nResponse:\nWe are grateful for the reviewer's comments and concur that it is necessary to include\na plot indicating the relationship between wave height and the width and slope in Figure\n2. Additionally, we calculated the correlation coefficient between the tidal flat slope and\nwave height to be 0.13 (p > 0.05), and the correlation coefficient between tidal range\nand slope to be 0.34 (p < 0.01). The correlation coefficient for tidal flat width and wave\nheight is -0.20 (p < 0.05).\nAdditionally, considering the large distribution range of the tidal flat width (30-26000\nm) and slope (3.6×10-5-1.2×10-1), we agree that it is better to consider the median value\nfor both width and slope, instead of the average width. To make these points clear, we\nrevised the lines in 120-122, 140-141 and Figure 2 as:\n“The results show that tidal flat width exhibits a positive correlation with SSC (R =\n0.71, P < 0.01) and tidal range (R = 0.44, P < 0.01) but a weaker negative correlation\nwith wave height (R = -0.20, P < 0.05, Fig. 2e).”\n“Waves are known to have an impact on tidal flat slope9,18, but it is not significant in\nthe current dataset (R = 0.13, P > 0.05; Fig. 2f).”\nFig. 2 - Relations between the spatial distribution of tidal flat width and slope with SSC\n(a, b), tidal range (c, d), and wave height (e, f). The number displayed at the base of\neach bar represents the number of data points of tidal flat width (average of 2014-2016)\nand slope (average of 1997-2017). (g, h) Linear regression models (solid lines) that\nbest explain the distribution of width and slope with 95% confidence intervals (shaded\nareas), in which data are transformed to ensure normal distribution. The effect of\nspatial autocorrelation is excluded through the application of a spatial error model\n(details of data processing are included in Methods).\n2.14 Lines 135-143. What about the effect of wave heights on both tidal flat width and\nslope?\nResponse:\nIn our data analysis, tidal flat width is inversely correlated with wave height, with a\ncorrelation coefficient of -0.20 that is statistically significant (P < 0.05). The tidal flat\nslope correlates positively with wave height, but this correlation is not statistically\nsignificant (R = 0.13, P > 0.05).\nThe mechanism is that higher waves would create higher peaks in bed shear stress\nduring wave breaking, which can easily erode the tidal flat profile, resulting in steeper\nprofile slopes and narrower widths. To make these points clear, we added the text in\nlines 120-122 and 140-141 as:\n“The results show that tidal flat width exhibits a positive correlation with SSC (R =\n0.71, P < 0.01) and tidal range (R = 0.44, P < 0.01) but a weaker negative correlation\nwith wave height (R = -0.20, P < 0.05, Fig. 2e).”\n“Waves are known to have an impact on tidal flat slope9,18, but it is not significant in\nthe current dataset (R = 0.13, P > 0.05; Fig. 2f).”\n2.15 Lines 135-143. In certain microtidal systems like the Venice Lagoon (Italy) or the\nVirginia Coast Reserve (USA), where wind waves exert greater influence than tidal\noscillations, tidal flats exhibit nearly negligible slopes (in fact, they are exceptionally\nflat!), yet the shift from tidal flats to marshes occurs through an exceptionally steep\n(almost vertical) scarp. How does this observation align with or challenge your findings?\nPlease comment.\nResponse:\nIndeed, it is known from previous studies (Friedrichs, 2011; Roberts et al., 2000) that\ntidal flats in micro-tidal systems have a very low slope. This is complementary to our\nresults as shown in Figure 2. In such cases, the effect of waves is more important. To\nmake this point clear, we added the following text in the Discussion section in lines\n287-292 as:\n“In this study, we use China’s tidal flat ecosystem as an example and elucidate that\ntidal range predominantly influences the slope of tidal flats, compared to incident waves\nor SSC. In our system, a higher tidal range typically leads to a steeper slope. This is\ncomplementary to the observations from microtidal systems like the Venice Lagoon\n(Italy) or the Virginia Coast Reserve (USA), where the tidal flats are exceptionally level\ndue to the low tidal ranges9,26.”\n2.16 Lines 145-148. In both Figure 3 and previous figures, does it make sense to\nconsider the average width of tidal flats, which ranges from 30 to 26,000 meters?\nResponse:\nWe agree with the reviewer on this comment that considering the average width of the\ntidal flats is not meaningful when there is a large variation in tidal flat widths.\nAccordingly, we revised the figures to calculate the median width in Figures 1-3.\n2.17 Lines 143-152. 28.3% of sites experienced expansion. What is the percentage of\nsites which experienced erosion?\nResponse:\n30.3% of the tidal flat sites showed an erosion trend > 1% per year. To make this point\nclear, we added the text in line 163 as:\n“30.3% of tidal flats experienced a width reduction rate greater than 1% per year.”\n2.18 Line 174-189 Contrasting Sediment-Rich and Sediment-Starved Tidal Flats How\nis the threshold defined? Is the threshold based on the annual mean of the monthly mean\nSuspended Sediment Concentration (SSC) data? Could you kindly provide clearer\nclarification of this aspect either within the main text or in the section titled “Suspended\nSediment Concentration (SSC) Data”?\nI am curious about the 50mg/L and 75mg/L thresholds for sediment-starved tidal flats\non the open coast and on estuaries, respectively, and whether those threshold are\naffected by the specific SSC values of the area. A mean value of 50mg/L does not strike\nme as indicating low sediment availability. Moreover, the SSC on the Chinese coast, as\nconsidered by the authors, might be considerably higher than that of many other coastal\nsystems globally. Has your detailed scrutiny of the literature identified such a threshold?\nHow does this value compare to thresholds observed in other sediment-starved systems\nworldwide?\nResponse:\nThe threshold for sediment-starved systems is determined based on the multi-year\naverage suspended sediment concentration (SSC) on the tidal flats in China, including\nboth open coast and estuaries (50 mg/L), and we consider areas below the average to\nbe sediment-starved systems. The threshold for sediment-rich systems (75 mg/L) is\ndetermined from the multi-year average SSC in estuaries with typically high sediment\navailability.\nAdditionally, our theory has been confirmed in countries with lower sediment\navailability, and the detailed responses for the global applicability are provided\ncollectively in comment #2.3.\nTo clarify the rationale behind the selection of the threshold, we revised the text in lines\n190-195 as:\n“Beyond the overall connection between SSC reduction and tidal flat width loss, we\nfurther discover diverse responses of sediment-starved (SSC < 50 mg/L, average SSC\nof China’s tidal flats) and sediment-rich (SSC > 75 mg/L, average SSC in five major\nChinese estuaries, Supplementary Fig. 2; the Changjiang River Estuary, the Yellow\nRiver Estuary, the Pearl River Estuary, the Minjiang River Estuary, and the Liaohe\nRiver Estuary) sites to altered sediment availability.”\nTo make clear that these values may be different in other areas, we also added the\nfollowing text in Lines 479-481 as:\n“These thresholds can be considerably higher than other countries15,65, due to the\noverall higher SSC on China’s coast. Thus, sediment-starved and sediment-rich systems\nshould be defined differently in other regions of the world.”\n2.19 Lines 177-179. Regarding the SSC decrease, is it meaningful to highlight an\naverage difference of 0.03% between sediment-rich and sediment-starved systems?\nCould such a small difference fall within the margin of error due to estimations in tidal-\nflat width and/or SSC concentration values? Additionally, note that the 0.27% and 0.24%\nrates refer to an SSC decrease between 1.2% and 4%, while for the 0-1.2% decrease\nscenario, the results are different. A similar consideration applies to the increase in SSC.\nResponse:\nWe agree that an average difference of 0.03% may not be significant. Therefore, we\nexamined a wider range of SSC variations from 1.2% to 4.8%, at which point the\ndifference in tidal flat erosion between the sediment-rich and sediment-starved systems\nis 0.17% (0.27% vs 0.10% per year). For cases where the SSC increases, we also\nprovide more detailed results, similarly.\nAccordingly, we revised the text in lines 195-199 and Figure 4 as:\n“Notably, sediment-rich sites undergo 2.7 times faster width reduction than sediment-\nstarved sites (0.27% vs. 0.10% width loss per year) when SSC decreases between -1.2%\nto -4.8% per year (Fig. 4a). Conversely, sediment-starved systems exhibit 2.1 times\nmore rapid width expansion (0.64% vs. 0.30% width gain per year) when SSC increases\nbetween 1.2% to 4.8% per year.”\nFig. 4 - Elastic response of tidal flats width changes to altered sediment availability.\nFlat width changes with sediment concentration change in sediment-rich and sediment-\nstarved areas based on observation (a) and explanatory modeling (b). The numbers at\nthe base of each bar represent the number of observations. Model results are based on\nan exemplified sediment-rich site and a sediment-starved site (see Methods). (c)\nDiagram showing a sediment-rich tidal flat is similar to a stretched spring that tends\nto return to its morphological equilibrium (dashed line) and is resistant to being\nstretched further. (d) Diagram showing a sediment-starved tidal flat is similar to a\ncompressed spring that tends to restore its morphological equilibrium (dashed line) and\nresists being compressed further. The convex shape of sediment-rich flats and the\nconcave shape of the sediment-starved flats correspond to the ideal profiles from the\ndynamic equilibrium theory18,25.\n2.20 Lines 174-190 and Figure 4. What I observe here is that as the SSC decreases, both\nsediment-rich and sediment-starved tidal flats exhibit a similar response by narrowing\ntheir width at the same rate when considering actual tidal flats (Fig. 4a). However,\nmodel results suggest a more pronounced decrease in width for sediment-rich tidal flats.\nIn this case, the model appears to overestimate the reduction in the width of the tidal\nflats. The opposite appears to happen when there is an increase in SSC. Could this\nsuggest that the model is highly responsive to changes in SSC?\nMoreover, while for the observations, the reduction in width with decreasing SSC\noccurs at the same rate for both sediment-starved and sediment-rich systems, and the\nsame applies to the increase in width with increasing SSC, this is not the case in the\nmodel. Additionally, the model is practically insensitive to an SSC increase of 0.8%\nfor sediment-rich systems, whereas it is not for an increase to 2%.\nResponse:\nWe thank the reviewer for these questions. As our responses for comment #2.19,\nsediment-rich and sediment-starved tidal flats exhibit significant differences in their\nresponses to changes in SSC.\nIn contrast to Fig. 4a, which contains data from many different sites, the model results\nin Fig. 4b are from two tidal flats as two exemplified sites to show the observed general\npattern (Fig 4a) in the data can be reproduced and explained by modeling. Thus, it is\nmeant for a qualitative comparison and explanatory modeling test with the observed\npattern.\nWe have included this information in the revised manuscript in lines 201-206.\n“To elucidate these observed divergent responses, we conducted explanatory\nsimulations of a sediment-rich and a sediment-starved tidal flat using the DET-\nESTMORF model (Fig. 4b and Supplementary Fig. 9). The modeling results show\nsimilar qualitative conditional responses to sediment availability changes, but have\ndifferent response rates in width change compared to observations. The latter is likely\ncaused by the fact that the simulations are based on two exemplified sites while not\naccount for all the observed variations across the country.”\n2.21 Lines 182-197. Can the authors better describe the difference between actual\nconcentration and equilibrium concentration and how they are related to SSC?\nResponse:\nDue to length limitations, we think it is better to include this detailed explanation in the\nsupplementary section, where the difference between actual concentration and\nequilibrium concentration and how their interplay results in the conditional response of\ntidal flat morphology are included. In relation to this comment, the explanation of the\ntidal flat conditional response has been addressed in response #2.2.\n2.22 Lines 204-213. The authors describe the different responses of sediment-rich and\nsediment-poor systems using an analogy with the dynamics of a spring. While the\nanalogy with spring dynamics is illustrative, it would be beneficial to explain these\nresponses in terms of morphodynamic processes and feedbacks. Specifically, what\nmorphodynamic mechanisms and feedbacks control such responses? How do factors\nlike tidal range, sediment transport, deposition rates, erosion, and hydrodynamics\ninterplay to produce these observed behaviors? Providing a detailed explanation\ngrounded in morphodynamic principles would strengthen the understanding of these\ndifferential responses to changes in SSC between sediment-rich and sediment-poor\nsystems.\nResponse:\nWe thank the reviewer for the comment, which would improve our manuscript. We\nadded the morphodynamic explanations in lines 301-312, as addressed in detail in\ncomment #2.2 above.\n2.23 Lines 215-230. First. Figures 4C and 4D depict concave-up versus convex tidal\nflat profiles and shapes. The same authors have previously explored and effectively\nelucidated (Hu et al., JGR-ES 2015) this difference (convex shape for tide-dominated\nareas; concave shape for wave-dominated areas). However, I don't recall this shape\ndifference being previously linked to sediment availability. Interestingly, in the present\nstudy, the focus is solely on sediment availability, with no consideration given to the\npotential influence of tidal range and waves. Could the authors provide insights into\nreconciling these divergent findings?\nResponse:\nOur response regarding the relationship between profile concavity and sediment\navailability are provided in comment #2.5.\nAs for our focus in this paper, we investigate the influence of tidal range and waves in\nthe spatial tidal flat morphology. However, we did not study their effect on temporal\nchanges, since temporal changes in tidal range and wave climate were small given the\nrelatively short time frame that we considered (2002-2016).\nTo indicate the impact of wave, we included the text in lines 442-446 as:\n“To assess if a change in waves might affect tidal flat width, we calculated the change\nrate of significant wave height at 105 sites along the coast of China (with a resolution\nof 0.5 degrees) from ERA5 data. It shows that 95% of tidal flat areas have experienced\na minimal variation in significant wave height below 0.1 cm/year from 2002 to 2016.\nThus, there is no significant correlation between the wave height change and tidal flat\nwidth dynamics (p = 0.42).”\nTo indicate the impact of tidal range change, we included the text in lines 414-417 as:\n“We also calculated the change rates of tidal range from TPXO9 data between 2002\nand 2016, but the results indicated no significant correlation between the tidal flat\nwidth changes and tidal range changes (p = 0.25). This may be due to the relatively\nsmall changes in tidal range along China's tidal flats during the study period, with an\naverage change of 0.3% per year.”\n2.24 Lines 215-230. Second. I do have a question. How do you determine the point at\nwhich new equilibrium conditions are reached? Can you quantify the timescale over\nwhich tidal flats respond to alterations in external forcing? More specifically, can you\ndetermine the time it takes for certain physical properties (like elevation, accretion rate,\nor progradation rate) to reach a specified percentage of their equilibrium value\nfollowing a change in forcing? (e.g. D’Alpaos et al., JGR 2011)? This could be quite\nrelevant as it would enable the estimation of the time needed for morphodynamic\nequilibrium conditions to be attained (referred to as relaxation time).\nResponse:\nWe can quantify the timescale of relaxation time by calculating the elevation rate. To\ndo this, we added explanatory modeling and calculated the time to reach a new\nequilibrium (elevation rate <1 mm/year) under a 2% increase and decrease in sediment\navailability. Our modeling results indicate that sediment-rich systems reach equilibrium\n\nmore rapidly as sediment levels decrease (12 years < 24 years), whereas sediment-\nstarved systems reach equilibrium more quickly when sediment levels increase (19\nyears < 26 years). This result also confirms the phenomenon that sediment-rich systems\nare more sensitive to sediment decrease. To make this point clear, we added the text in\nlines 206-212 and Supplementary Figure 10:\n“Following a previous study24, we further assess the relaxation time needed for new\nstable profiles. When external sediment availability decreases by 2%, the sediment-rich\ntidal flat reaches a new stable profile more quickly (12 years) than the sediment-starved\ntidal flat (24 years). However, when sediment availability increases by 2%, the\nsediment-starved tidal flat reaches a stable state more quickly (19 years) than the\nsediment-rich site (26 years) (Supplementary Fig. 10). These results of relaxation time\nare also clearly in line with the observed pattern of tidal flat width changes.”\nSupplementary Figure 10. Modeled spatial-average elevation change rate of Jiangsu\nand Western Scheldt tidal flat profile under a 2% decrease (a) and increase (b) in\nsediment availability. Equilibrium points (the period when tidal flat morphological\nequilibrium is reached) are defined as the spatial-average elevation change rate below\n0.1 mm/year.\n2.25 Lines 253-278. The authors did not demonstrate the possibility of extending their\nresults to other coastal systems worldwide. The considered case is quite particular\nbecause, even in the case of sediment-poor systems, these systems are characterized by\nSSC values much larger than those found in other coastal systems globally. Moreover,\nthere is a consensus that both sea level rise rates and sediment supply critically\ninfluence coastal dynamics, determining their persistence or disappearance (e.g.,\nKirwan et al., GRL 2010; Marani et al., JGR-ES 2010; Kirwan et al., Nat. Climate\nChange 2016; Mariotti and Carr, WRR 2014). The interplay of these factors should not\nbe assessed in isolation. Curiously, the rates of sea level rise impacting the Chinese\ncoast are not addressed in this study. Could this potentially impact your results? Might\nthis also influence the anticipated response of your study sites as sea level rise\naccelerates?\nResponse:\nWe thank the reviewer for this comment and the suggested references. We have added\nthe analysis of three other countries with extensive tidal flat areas, which show the same\npattern (Fig. 5b and 5c). The responses for the global applicability are provided\ncollectively in comments #1.2 and #2.3.\nAs our response for the comment #2.4, there is no significant correlation between the\nchanges in tidal flat width and SLR during the study period. We fully understand\nreviewer’s concern about the impact of sea-level rise and have included relevant\ndiscussion and references in the manuscript in lines 342-346 as:\n“Due to the decadal time scale (2002-2016), sea-level rise does not have a clear impact\non tidal flat morphology based on data from 14 Chinese long-term water level\nobservation sites (p = 0.89, see Methods). However, over longer time scales (e.g., a\ncentury), its impact can be pronounced, especially with concurrent SSC reduction22,35–\n37, emphasizing the need to expand long-term monitoring in the future.”\n2.26 Lines 271-278 The authors mention that “due to the time scale (2002-2016) we\nconsidered in the current study we did not include the impact of sea level rise, but over\nseveral decades to centuries, its impact can be pronounced3”. I comprehend and concur\nwith this perspective. Nonetheless, if we aim to furnish long-term predictions,\naccounting for SLR becomes imperative. How might the authors reassure readers that\nthese findings remain unaffected by varying SLR rates?\nResponse:\nWe thank the reviewer for this comment, and our responses are provided collectively in\ncomment #2.4 and #2.25.\n3. Response to Reviewer #3 (in blue):\nThe paper presents a data-driven analysis of tidal flat morphology from spatial datasets\nacross China's coastline. The synthesis work utilizes various spatial datasets with\ndisparate temporal and spatial resolutions to ascertain the effect of suspended sediment\nconcentrations, tidal range, and wave height on tidal flat width and slope. The paper\nfinds that SSC is a major factor in tidal flat width and recommends excess sediment be\nallocated to low-sediment coastal systems.\nThe noteworthy results include positive correlation of tidal flat width with suspended\nsediment concentrations and tidal range and the tidal slopes positive correlation with\ntidal range. The authors suggest a limited impact of additional sediment in sediment\nrich coastal regions.\nResponse:\nWe thank the reviewer for the insightful summary of our paper. Below, we provide a\npoint-by-point response to the reviewer’s comments and show how they are\nincorporated to improve the revised paper.\nThe work does have some limitations.\n3.1 By ignoring the largest driver of loss i.e. direct conversion, the authors have limited\nthe impact of the work. A brief discussion on anthropogenic loss would increase the\nimpact of the work, as tidal flat ecosystems with partial conversion to aquaculture and\nother land uses are expected to have unique morphology and change trajectories.\nResponse:\nWe thank the reviewer for the insightful suggestions. Regarding the direct effect of\nhuman induced tidal flat loss, we excluded tidal flat transects directly affected by human\nactivities (e.g., conversion to other land use), which account for 26% of our dataset.\nAdditionally, the effect of damming is considered via the reduction of SSC at the coasts,\nwhich is considered as a key environmental change on tidal flat morphology in the\ncurrent study. To make the above points clear, we added a discussion on human impact\nin lines 331-335 and added Supplementary Figure 12 as:\n“In our analysis, we focus on understanding how tidal flats respond to indirect external\ndisturbances from a morphodynamic perspective, while losses due to direct human\ninterventions (reclamation) are generally less predictable. Thus, we excluded data\npoints directly impacted by human activities, such as conversion to other land uses,\naccounting for 26% of the total transects in our study (Supplementary Fig. 12).”\n[figure redacted]\nSupplementary Figure 12. Examples of tidal flat sites directly affected by human\nactivities. The red areas indicate the regions of tidal flats that have disappeared from\n2002 to 2016 due to reclamation.\n3.2 Additionally, the 917 transects with discontinuous elevation should be discussed\nfurther. Is this a FAST database issue or an indication of anthropogenic impacts?\nResponse:\nTo provide the cause of the discontinuity, we added the text in lines 383-386 as:\n“Transects with discontinuous elevation were excluded from analysis (917 of 2538\ntransects). There are mainly two reasons that cause the discontinuous elevation: 1) gaps\nwithin the continuous elevation data (51.4%); 2) none or too few elevation data in the\nFAST database (48.6%).”\n3.3 Uncertainty and error are mentioned but need to be thoroughly discussed for each\ndataset. For example, tidal flat accuracy is 82.2%, and the FAST database has a vertical\naccuracy of 30-50 cm accuracy. No uncertainty is reported for the TPXO9-atlas atlas or\nthe ERA-5. While error propagation would be ideal for these datasets, that is probably\nnot feasible. However, discussing how these errors might affect the results is necessary.\nResponse:\nIn the revised manuscript, we clarify the errors in each database and their possible\nimpact on the results.\nTo explain the accuracy of the ERA-5 and TPXO9-atlas datasets, we include lines 424-\n426 and 399-401 as:\n“The database has been proven suitable for China's coastal areas48, with data bias\nestimated at less than 0.1 m in deep waters.”\n“The accuracy of the TPXO9 on China’s coast can be shown by an average Root Sum\nSquares (RSS) value of 19.92 cm41.”\nTo discuss the influence of these errors on the results, we include the text in lines 335-\n338 and 340-342 as:\n“Additionally, cumulative errors from various data sources (e.g., FAST, ERA-5, tidal\nflat map) in large-scale spatiotemporal studies could influence the accuracy of the\nfindings. For example, the tidal flat map data may misidentify highly turbid waters1,\nwhich may lead to an overestimation of the tidal flat widths.”\n“Despite these potential errors, our analysis aligns with dynamic equilibrium modeling\nand is consistent with numerous previous studies9,10,18.”\n3.4 Additionally, Figure 1 should not use error bars for quantile ranges; instead, a\nboxplot would be more appropriate as the current visualization suggests to a viewer that\nthis is the error of the slope.\nResponse:\nWe thank the reviewer for this kind comment. We have changed Figure 1 to show the\nerror of the slope as follows:\n[panels redacted]\nFig. 1 - Distribution of tidal flats width (a) and slope (b) along the coast of China.\nCoastal provinces of China are listed in the maps, namely Liaoning (LN), Hebei (HB),\nShandong (SD), Jiangsu (JS), Zhejiang (ZJ), Fujian (FJ), Guangdong (GD), Guangxi\n(GX), Hainan (HN) and Taiwan (TW). Red boxes indicate regions with large widths or\nslopes, and blue boxes indicate regions with minimal values. The values in the figure\nrepresent the median values of data in the box. The variation of tidal flat width and\nslope along latitude is displayed on their right panel. The shaded areas represent the\n25th and the 75th percentile values. (c) The relationship between tidal flat width and\nmedian slope in each group. The number N represents the number of data points. The\nupper whisker extends to the 75th percentile plus 1.5 times the interquartile range, and\nthe lower whisker extends to the 25th percentile minus 1.5 times the interquartile range.\n3.5 The various data transformations may appropriately handle autocorrelation, but the\ncurrent paper ignores spatial autocorrelation entirely. An exploration of Moran's I is\nappropriate.\nResponse:\nWe conducted an additional analysis by calculating Moran's I values for both the\nresiduals of our linear regression model for spatial distribution analysis and the data on\nthe rate of change in tidal flat width. This method enables us to consider the effects of\nspatial autocorrelation in our methodology. To make the above points clear, we added\ntext in lines 122-126, 505-509 and 392-395 as:\n“A stepwise linear regression analysis indicates that the combination of SSC (80%\nrelative importance) and tidal range (20% relative importance) best explains the\ndistribution of tidal flat width (R2 = 0.61) (Fig. 2g, Eq. 3), in which the effect of spatial\nautocorrelation is excluded (See Methods).”\n“Considering the potential impact of spatial autocorrelation, we calculated Moran's I\nfor the residuals in our regression models for width (0.35, p < 0.01) and slope (0.11, p\n= 0.17). We then used a spatial error model to eliminate the effects of spatial\nautocorrelation for the width model, achieving a better fit than the multiple linear\nregression (R2 = 0.61).”\n“Changes in tidal flat width were obtained from tidal flats maps every three years\n(2002-2004, 2005-2007, 2008-2010, 2011-2013, and 2014-2016)1. The data on the\nannual variation in tidal flat width shows no significant spatial autocorrelation\n(Moran's I < 0.01, p = 0.44).”\n3.6 37—The Introduction conflates vegetated coastal wetlands and the ecosystem\nservices they provide with tidal flats, which have not been demonstrated to provide\nthese same ecosystem services or at the same magnitude. I would suggest finding\nsources that directly discuss tidal flats.\nResponse:\nWe agree with the reviewer and have revised the text to clarify the distinct roles and\necosystem services of tidal flats, as follows:\n“Tidal flats, defined as unvegetated mud or sand flats (distinct from mangroves and salt\nmarshes) with regular tidal inundation1, are one of the most extensive coastal\necosystems worldwide, providing essential ecosystem services such as storm surge\nprotection2,3, carbon sequestration4–6, and serving as critical habitats for large\npopulations of waterfowls5,7. With the recent advancements in remote sensing,\nglobal-scale tidal flat dynamics have been mapped in detail1,8.”\n1. Murray, N. J. et al. The global distribution and trajectory of tidal flats. Nature 565,\n222–225 (2019).\n2. Zhang, M. et al. Tidal-flat reclamation aggravates potential risk from storm impacts.\nCoastal Engineering 166, 103868 (2021).\n3. Murray, N. J., Clemens, R. S., Phinn, S. R., Possingham, H. P. & Fuller, R. A.\nTracking the rapid loss of tidal wetlands in the Yellow Sea. Frontiers in Ecology and\nthe Environment 12, 267–272 (2014).\n4. Jia, M. et al. Rapid, robust, and automated mapping of tidal flats in China using\ntime series Sentinel-2 images and Google Earth Engine. Remote Sensing of\nEnvironment 255, 112285 (2021).\n5. Barbier, E. B. et al. Coastal Ecosystem-Based Management with Nonlinear\nEcological Functions and Values. Science 319, 321–323 (2008).\n6. Mazarrasa, I. et al. Drivers of variability in Blue Carbon stocks and burial rates\nacross European estuarine habitats. Science of The Total Environment 886, 163957\n(2023).\n7. Wang, X. et al. Tracking annual changes of coastal tidal flats in China during 1986–\n2016 through analyses of Landsat images with Google Earth Engine. Remote Sensing\nof Environment 238, 110987 (2020).\n8. Murray, N. J. et al. High-resolution mapping of losses and gains of Earth’s tidal\nwetlands. Science 376, 744–749 (2022).\n3.7 49 – Reclamation has a negative connotation towards the ecosystem being\nreclaimed and should be avoided as it suggests these ecosystems are wastelands. I\nsuggest instead using, for example, conversion to other land use.\nResponse:\nWe thank the reviewer for the feedback on the use of the term \"reclamation\" in our\nmanuscript, and we replaced it with ‘conversion to other land uses’ in lines 43-45 as:\n“Strikingly, approximately 16% of the global tidal flat area was lost during 1984-2016,\nin which 66% of the area losses were attributed to indirect drivers, rather than direct\nhuman impact through conversion to other land uses8.”\n3.8 59 – I suggest tidal flats be called an ecosystem, not a system.\nResponse:\nWe thank the reviewer for this comment. We have revised “systems” to “ecosystems”.\n3.9 82 – An important context is that the spatial resolution of the underlying data is 30\nm, which limits the tidal flat width.\nResponse:\nIt is indeed correct that the 30 m resolution imposes a limitation on the detection of\nnarrower tidal flats, but it is the best resolution that can be obtained from the freely\naccessible dataset.\nTo make the above point clear, we add the text in lines 338-340 as:\n“Furthermore, the 30 m spatial resolution of the tidal flat map affects the accuracy of\nrelatively narrow tidal flat widths, however, the overall impact is limited given the\nmedian flat width being 536 m in China.”\n3.10 267 – \"Sediment starving\" should be rephrased to \"Sediment starved systems\".\nAdditionally, a more interesting discussion is how little sediment sediment-rich tidal\nflats need to persist given the reduction in sediment due to dams and other coastal\ndevelopment.\nResponse:\nWe thank the reviewer for the valuable suggestions. We revised “sediment starving” to\n“sediment starved” throughout the manuscript. More importantly, the review provides\na valuable suggestion that can be very important for coastal management in sediment-\nrich areas. We conducted an additional analysis based on the data from China’s coast.\nIt shows that for sediment-rich tidal flats, the tidal flat width loss increases dramatically\nwhen the external SSC is reduced by more than 24% from 2002.\nTherefore, to maintain the stability of these tidal flats, it is essential to preserve at least\nthree-quarters of the sediment availability.\nTo make the above point clear, we add the text and supplementary Figure 11 in lines\n261-264 and 322-324 as follows:\n“Furthermore, based on the data from China’s coast, we found that in sediment-rich\nareas tidal flat width losses would increase rapidly once the SSC is reduced by 24%\nfrom 2002 (Supplementary Fig. 11). This finding can serve as an important rule of\nthumb for coastal management.”\n“Moreover, considering the widespread SSC reduction due to river damming, it is\nessential to preserve at least 76% of the long-term stable SSC to prevent severe tidal\nflat area loss (Supplementary Fig. 11).”\nSupplementary Figure 11. Relationship between change of tidal flat width and change\nof SSC for sediment-rich tidal flats based on data from China’s Coast.\n3.11 290—Rephrase this sentence: \" The global tidal flat maps used over 7.0 x 105\nsatellite images to map tidal flat extent.\"\nResponse:\nWe thank the reviewer for the comment. The text is revised accordingly in lines 363-\n364.\n3.12 327 – Adding where the highest and lowest tides were would be useful for readers.\nResponse:\nWe thank the reviewer for the suggestion. We added the text in lines 409-412 as:\n“The tidal flats along China's coastline exhibit a tidal range that varies from a\nminimum of 0.59 m near the Yellow River mouth to a maximum of 7.33 m on the\nsouthern Shandong Peninsula, with an average of 2.78 m.”\nReviewer #3 (Remarks on code availability):\nThe code is on codeocean so it appears to have all the necessary components to run and\nthe authors should be commended for making it available in this format. I would\nrecommend adding a README file to the repository there which will give a greater\nunderstanding of the scripts. The run output appears correct. The scripts appear to be\nmostly visualization and statistical testing. While this is fine some of the most\ninteresting code in this paper such as extracting the tidal information to calculate the\nslope is absent. I could be mistaken as the .mat files can not open in codeocean or on a\ncomputer without a copy of matlab.\nResponse:\nWe have included a README file in the repository. The data processing code of\nextracting the tidal information to calculate the slope and other variables is now also\nincluded.\n4. Response to Reviewer #4 (in blue):\nI co-reviewed this manuscript with one of the reviewers who provided the listed reports.\nThis is part of the Nature Communications initiative to facilitate training in peer review\nand to provide appropriate recognition for Early Career Researchers who co-review\nmanuscripts.\nResponse:\nWe appreciate the co-review initiative and thank the Early Career Researchers for\nhis/her contribution.\nReferences:\nBarrot, G., Mangin, A., & Pinnock, S. (2007). Global Ocean Colour for Carbon Cycle\nResearch, Product User Guide. ACRI-ST, Sophia-Antipolis.\nBi, S., Yang, Y., Xu, C., Zhang, Y., Zhang, X., & Zhang, X. (2017). Distribution of\nheavy metals and environmental assessment of surface sediment of typical\nestuaries in eastern China. Marine Pollution Bulletin, 121(1), 357–366.\nhttps://doi.org/10.1016/j.marpolbul.2017.06.013\nChristoffersen, J. B., & Jonsson, I. G. (1985). Bed friction and dissipation in a combined\ncurrent and wave motion. Ocean Engineering, 12(5), 387–423.\nhttps://doi.org/10.1016/0029-8018(85)90002-2\nDethier, E. N., Renshaw, C. E., & Magilligan, F. J. (2022). Rapid changes to global\nriver suspended sediment flux by humans. Science, 376(6600), 1447–1452.\nhttps://doi.org/10.1126/science.abn7980\nFagherazzi, S., Carniello, L., D’Alpaos, L., & Defina, A. (2006). Critical bifurcation of\nshallow microtidal landforms in tidal flats and salt marshes. Proceedings of the\nNational Academy of Sciences, 103(22), 8337–8341.\nhttps://doi.org/10.1073/pnas.0508379103\nFriedrichs, C. T. (2011). 3.06 - Tidal Flat Morphodynamics: A Synthesis. In E. Wolanski\n& D. 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Investigation using simple\nmathematical models of the effect of tidal currents and waves on the profile\nshape of intertidal mudflats. Continental Shelf Research, 20(10), 1079–1097.\nhttps://doi.org/10.1016/S0278-4343(00)00013-3\nSoulsby, R., Stive, M., de Vriend, H., Fredsoe, J., Hamm, L., Teisson, C., & Winterwerp,\nJ. (1995). Advances in coastal morphodynamics.\nWang, F., Sanders, C. J., Santos, I. R., Tang, J., Schuerch, M., Kirwan, M. L., et al.\n(2020). Global blue carbon accumulation in tidal wetlands increases with\nclimate change. National Science Review, 8(9), nwaa296.\nhttps://doi.org/10.1093/nsr/nwaa296\n“Dynamics and drivers of tidal flat morphology in China”\nShuai Liu, Zhan Hu, Tim J. Grandjean, Zheng B. Wang, Vincent T. M. van Zelst,\nLin Qi, Tianping Xu, Jun Young Seo, Tjeerd J. Bouma\nItemized List of Changes and Answers to the comments\n1. Response to Reviewer #1 (in blue):\n1.1 I appreciate the authors’ clarification and supplementation, but it also exposes more\nflaws in the manuscript especially in terms of data usage. Moreover, the revised\nmanuscript only provided explanations and did not find out new insights based on the\nreviewer's comments.\nResponse:\nWe appreciate the reviewer’s feedback. In response to the concerns raised, we have\ncarefully revisited our analysis to ensure the validity. A few new insights have been\nfound based on reviewer’s comments, which are listed below:\n1. We found that tidal flats in three other countries with extensive tidal flat areas share\nthe same dynamic response to SSC in China. This is supported by our additional\ndata analysis in the previous revision following reviewer’s suggestions. See also\nresponse # 1.7.\n2. The morphological evolution patterns of tidal flats subject to direct human\nconversion differ significantly from those of tidal flats evolving under natural\nconditions, highlighting the specific influence of human conversion and the\nnecessity to exclude transects affected by such activities. See also response #1.6 and\n#3.2\n3. Based on tide gauge data along China's coast, the relatively small changes in tidal\nrange (averaging 1.1 cm per year) and sea level rise have limited impacts on tidal\nflat morphology over the timescale of our study.\n1.2 For the hydrodynamics, the tides and waves were mentioned in this study. How\nabout the alongshore current, which is also important for the open coast tidal flat.\nI noticed that in Supplementary Figure 2, most of the sediment-rich tidal flats locate\nright in or adjacent to the estuaries. For those sediment-rich tidal flats a little bit far\nfrom the estuaries such as in the Jiangsu and Zhejiang coasts, the sediment is also\nsupplied by the Changjiang River, but carried by the alongshore current, rather than\ntides or waves.\nResponse:\nWe thank the reviewer for the comment. We agree with that the alongshore current is\nalso an important aspect of hydrodynamics. In the current study, we did not explicitly\nconsider the impact of alongshore currents for the following 3 reasons: 1) there is a lack\nof nationwide dataset or fine-scaled modelling results on alongshore current that can\nsupport our analysis. 2) As the reviewer mentioned that alongshore currents transport\nsediment over large scales, their impact is to some extent reflected by the SSC data we\nanalyzed. Thus, the role of alongshore currents is implicitly accounted for in the current\nstudy. 3) In our analysis, the considered environmental factors (i.e., SSC and tidal range)\nhave statistically significant impact on tidal flat morphology (p < 0.05, see Fig. 2 and\n3). Thus, we think that inclusion of alongshore currents as another environmental\nfactors would not affect the main results.\nIn the Method section of the revised manuscript, we acknowledge the exclusion of\nalongshore currents and explain the main reasons of it in lines 467-470 as:\n“In the current study, the impact of alongshore currents is not explicitly considered,\nsince there is a lack of nationwide dataset on alongshore currents. Yet, as alongshore\ncurrents transport sediment over large scales62,63, their impact is implicitly reflected by\nthe SSC data we analyzed.”\n1.3. Line 414-416: It is mentioned that the change rates of tidal range was calculated\nfrom TPXO9 data between 2002 and 2016. TPXO dataset only provides the harmonic\nconstants for 15 constituents. The calculated tidal range change rates are actually the\nlong-term variation of tidal forcing, such as the 18.61-year lunar nodal period. It is not\na response of the tidal flat morphological change.\nResponse:\nWe thank the reviewer for the constructive comment. We include tide level data from\n12 coastal stations in China in the current version. However, the results still indicated\nno significant correlation between the tidal range change and the width dynamics of the\nnearby tidal flats (p = 0.32). This is likely due to the relatively small changes in tidal\nrange, with an average change of 1.1 cm/year.\nTo make this point clear, we include text in lines 431-435 and the data are included in\nSupplementary Table 1 as:\n“To test the possible effect tidal range on tidal flat width, we compared the tidal range\nchange from the 12 UHSLC tide gauge sites49 with the tidal width changes. The results\nindicated no significant correlation between the tidal range changes and the nearby\ntidal flat width changes (p = 0.32), which is likely due to the relatively small changes\nin tidal range (averaged 1.1 cm per year).”\n1.4. Line 423-426: Reference 48 was used to evident that the ERA5 wave reanalysis\ndata suitable for China's coastal areas. However, the conclusion of this reference is “The\ndifference between the significant wave height (SWH) of ERA 5 and that of the buoy\nvaries from −0.35 m to 0.30 m for the three shallow locations; for the three deep\nlocations, the variation ranges from −0.09 m to 0.09 m. ... Hence, the ERA5 SWH data\ncannot be used for design applications without site-specific validation”. As shown in\nSupplementary Figure 3b, the wave heights in most coasts along China mainland are\nbelow 0.30 m, which are smaller than the errors estimated by reference 48.\nResponse:\nActually, in the abstract of Ref. 48 (Ref. 51 in the new version), the authors indicate\n\"Inter-comparisons suggest that the ERA5 dataset is consistent with the annual mean\nSWH\". As mentioned by the reviewer and in the main text of Ref. 48, ERA5 SWH data\ncannot be used for “design applications without site-specific validation”. Thus, we think\nthe authors of the Ref. 48 mean that the ERA5 SWH data may not be applied directly\nin engineering projects, such as design a harbor, but it is good to provide annual mean\nwave height, which is exactly what we need in our analysis.\nFurthermore, in the previous version, we actually tested the applicability of the ERA5\nSWH data. We compared the ERA5 dataset with field wave height data at four locations,\nand wave period data at three locations, respectively. The results confirm good\napplicability of ERA5 wave data on the coast of China.\nTo make this point clear, we add text in lines 462-467 and Supplementary Table 2 and\n3 as follows:\n“To validate the applicability of the ERA5 data, we collected wave data from tidal flats\nat various locations along China's coast, including Chongming Island56,57 and Leizhou\nBay58 for both wave height and period, Taiwan Longdong59 and the Yellow River\nmouth60 for wave height, and Jiangsu61 for wave period. The agreement between our\nestimated wave heights and periods with in-situ observations (Supplementary Tables 2\nand 3) confirms good applicability of ERA5 wave data.\n1.5. Line 455-459: As I mentioned in the previous review, the satellite remoted\nsurface SSC is not representative for coastal waters, especially the highly-stratified\nestuarine waters. But the authors explained that they used the TSM in the water\ncolumn to represent SSC. So, I checked the product manual of the GlobColour\nproject. It is given that “The MERIS/OLCI TSM product is computed from the back-\nscattering coefficient at 444 nm using the following assumptions: BP = BBP/0.015,\nTSM = 1.73*BP. BBP is an output of the GSM merging algorithm applied to L3\nsingle-sensors reflectances NRRS”. It is very clear that the TSM is the surface total\nsuspended matters, not in the water column. Furthermore, as shown in Supplementary\nFigure 3c, the SSC in the Yellow River mouth is much less than that in the Hangzhou\nBay. Do you believe that?\nResponse:\nWe thank the reviewer for the comment. We double checked our method and further\nreviewed the existing main literatures on this matter (Curran & Novo, 1988; Feng et\nal., 2014; Dorji et al., 2016; Shi & Wang, 2017; Schuerch et al., 2018; Zhao et al.,\n2022; Grandjean et al., 2024). We believe that this method is suitable for the current\nanalysis. The reasons are listed below:\nFirstly, our results show that the SSC in Yellow River mouth is indeed less than that in\nHangzhou Bay. We believe it is correct as the similar pattern can be found in other\nindependent studies based on different algorithms (see Fig. 6 in Feng et al., 2014; Fig.\n10 in Shi and Wang, 2017 and Fig. 4 in Zhao et al., 2022).\nSecondly, TSM or SSC. We totally agree that all satellite-derived water properties are\nfor “surface” waters down to one optical depth, whose corresponding physical depth\ndepends on the water column properties, ranging from tens of meters in clear waters\nto a few meters (or even centimeters) in turbid waters. Furthermore, similar to SSC,\nTSM is also a measure of concentration (note the units of mg L-1, equivalent to g m-3)\nas opposed to the integrated “total” water-column suspended matter (g m-2). In turbid\ncoastal waters, nearly all solid matters are suspended sediment particles, and therefore\nTSM and SSC are often used interchangeably. On whether the satellite-derived TSM\n(i.e., SSC used in this study) is an accurate representation of the water column, this\nreally depends on the vertical profiles of water properties. If the water is well mixed,\nthe answer is yes. For a two layer-system (i.e., highly stratified water) where the\nsurface layer is clear and most suspended matters are in the bottom layer, the satellite-\nderived TSM is still a good index because the contribution of the bottom layer to the\nsatellite signal is only attenuated slightly by the surface layer. A reversed two layer-\nsystem (i.e., the bottom layer is clear but surface layer contains most of the suspended\nmaterials) is instable because of particle sinking and therefore rare.\nThirdly, on the accuracy of satellite-derived TSM (mg/L). As with any other\nalgorithms, the TSM algorithm is not error free but contains uncertainties, largely\nfrom the assumption that particle backscattering (bbp) is only 1.5% (i.e., 0.015) of\ntotal particle scattering (bp). This assumption is based on the average value of a large\ndataset, but it can vary from place to place depending on the particle refraction index\nand size. However, such uncertainties are not expected to change the overall spatial\npatterns of temporal changes, especially when data are grouped to represent different\nclasses (e.g., 0-20, 20-50, 50-75, 75-280, Fig. 2). There is a lack of in situ data across\nthe whole China’s coast to validate the satellite data, yet results from independent\nstudies and other algorithms (Fig. 10 of Shi and Wang, 2017, Fig. 4 of Zhao et al.,\n2022 and Fig. 6 of Feng et al., 2014) are consistent with what we used here.\nTherefore, we believe that the uncertainties in the satellite-derived TSM used in this\nstudy would not alter our findings and conclusions.\nTo make the above points clear, we revised the text in the method section in lines 474-\n489 as:\n“The SSC data near the monitoring tidal flat transects were obtained from the\nGlobColour project (https://www.globcolour.info). The data product of total\nsuspended matter concentration (TSM, mg/L) produced by the project is used to\nrepresent SSC (mg/L) because in turbid coastal waters most suspended matters are\ndue to suspended sediments. It is estimated from satellite-derived particle\nbackscattering coefficient in the blue wavelength by assuming a\nbackscattering/scattering ratio of 0.015, and such a product has been previously used\nand found reliable for large scale analyses64,65. The spatial patterns of such derived\nTSM are consistent with those from independent studies using other algorithms66.\nAlthough satellite-derived TSM (or SSC) represents the particle concentration in\nsurface waters (down to an optical depth), for both well-mixed water column or\nhighly stratified waters it can be used as a proxy for suspended particles in the water\ncolumn66. This is because, for the former case it is obvious that TSM reflect the\noverall sediment concentration and, for the latter case, the signals from the bottom,\nparticle-rich layer will only be attenuated slightly by the surface, particle-poor layer.\nThe applicability of this approach has been validated in terms of both spatial\ndistribution67 and temporal variability68, and the method has been widely applied in\nprevious studies (e.g., ‘sediment availability data’ in ref64 and ‘turbidity for estuaries’\nin ref69).”\n1.6. The authors give some good examples of tidal flat sites directly affected by human\nactivities. However, these reclamations can not only converse the tidal flat to others,\nbut also affect the tidal flat nearby, like in the same bay/estuary or close to each other\nin the open coast, as these projects can alter the alongshore current or tidal range in the\nentire bay or estuary. I believe this is one of the main reasons for the morphological\nchange of tidal flats during this period. This is different from the increase/decrease\nsediment supply mentioned in this study. And do not forget those beach restoration\ncaused by artificial sand replenishment, such as in Xiamen. These activities all should\nbe separated in this study.\nResponse:\nWe thank the reviewer for the comment. In addition to excluding transects directly\ninfluenced by reclamations (conversion), we performed analyses by further removing\ntransects indirectly affected by the far-field effect of conversion. In total, 156 transects\nwere identified.\nWe first identified nine estuaries or bays that are heavily affected by conversion (over\n40% of the transects were directly converted), including Qinjiang River, Yingzai River,\nZhenhai Bay, Luojiang Estuary, Wenzhou Bay, Wulei Island Bay, Liaohe Estuary, the\nsouthern coast of Hangzhou Bay, and Qixing Reef. Then, the remaining transects in\nthese estuaries or bays are regarded as transects being affected by the far-field effect of\nconversion. Additionally, those adjacent to converted transects along the open coast are\nalso deemed influenced by far-field effects.\nSecondly, regarding beach restoration projects, the scale of beach restoration projects\nin China is limited compared to the national tidal flat coastline, only accounting for 1.2%\n(120 km / 10,196 km, Liu et al., 2020; Sun et al., 2024). A total of 6 transects were\ninfluenced by such activity.\nAfter excluding these transects that are indirectly or directly affected by reclamations\n(conversion), the response pattern of tidal flat width with SSC remains unchanged (even\nbecome more apparent) as shown in Supplementary figure 13.\nTo make this point clear, we add text in lines 266-269, 511-518 and 528-537as:\n“In addition to direct conversion, we conducted analysis excluding transects in 9\nestuaries or bays, as well as those adjacent to converted transects along the open coast,\nwhere the far-field effect of conversion could be important (see methods). We show that\nthe tidal flat width response to SSC change still hold when the data of these areas\nexcluded (Supplementary Fig. 13).”\n“Conversion of tidal flats to other land use directly and indirectly influence the\nevolution of tidal flats. To investigate the morphological evolution of large-scale tidal\nflat systems with environmental factors (i.e., hydrodynamic forcing and sediment\navailability), we excluded transects affected by direct conversion. First, we identified\ntidal flat transects with direct conversion by analyzing satellite imagery (see\nSupplementary Fig. 12). The tidal flats are mainly converted to agriculture or\naquaculture land use, and also (about 1.2%) to artificial sandy beaches in areas like\nXiamen city72. 750 transects are affected by direct conversion, which are excluded from\nour analysis.”\n“As conversion can also affect nearby hydrodynamic conditions, thereby influencing\nadjacent remaining tidal flat evolution by far-field effects. Therefore, we further\nexcluded transects adjacent to those directly impacted by conversion. We identified nine\nestuaries or bays where the conversion level is high (over 40% of the transects were\ndirectly converted), including Qinjiang Estuary, Yingzai River Estuary, Zhenhai Bay,\nLuojiang Estuary, Wenzhou Bay, Wulei Island Bay, Liaohe Estuary, the southern coast\nof Hangzhou Bay, and Qixing Reef. The remaining transects were identified as being\ninfluenced by far-field effects of conversion. Additionally, those adjacent to converted\ntransects along the open coast are also deemed influenced by far-field effects After\nexcluding all these 156 transects, our primary conclusions regarding spatial and\ntemporal patterns remain unchanged (See Supplementary Fig. 13).”\nWe also added the Supplementary Figure 13 as:\n[panels redacted]\nSupplementary Figure 13. Spatial (a) and temporal (b) results after excluding far-field\nimpacts of conversion. (c) An example of estuaries heavily impacted by human\nconversion (Liaohe Estuary). (d) An example of beach restoration caused by artificial\nsand replenishment (Xiamen).\n1.7. As the authors mentioned their theory also applied to tidal flats in Indonesia,\nAustralia, and the United States. But I do not see any figures or tables to support their\nconclusion.\nResponse:\nActually, in the previous revision, figures related to our theory applied to Indonesia,\nAustralia, and the United States are included in the Fig. 5b and Fig. 5c. A detailed\nexplanation of these results is provided in line 271-277.\n2. Response to Reviewer #2 (in blue):\n2.1. I have read in detail and with great interest the revised version of the paper\n\"Dynamics and drivers of tidal flat morphology in China\" by Liu et al.\nI consider that the Authors have quite satisfactorily covered, both by correcting or\nanswering correctly, all the questions and comments that were posed by myself in the\nreview of the first version. I have also read the response to the comments and requests\nfor change of the other reviewers and I think the paper greatly benefited from those\nsuggestions and from the detailed answers to those reviewers. I am quite pleased to note\nthat the authors have very seriously addressed all of the comments: they have done a\nthorough job in revising this manuscript.\nIn particular, the authors have:\n1) Provided more detailed explanations on the morphodynamic mechanisms and\nfeedbacks that control the contrasting responses of sediment-rich and sediment-starved\nareas to changes in sediment availability. This strengthens the understanding of the\nresults.\n2) Included an analysis of data from three other countries (Indonesia, Australia, United\nStates, countries with extensive tidal flat areas) to show the global applicability of their\ntheory. This expands the relevance of the study. I appreciated this effort.\n3) Discussed the potential impact of sea-level rise, recalling appropriate references and\nexplaining why it was not considered in this short-term study.\n4) Clarified the thresholds used to define sediment-rich and sediment-starved areas and\nacknowledged that these thresholds may vary in other regions.\n5) Provided further details on how they quantified the relaxation times to reach a new\nmorphodynamic equilibrium.\nThe paper was already in good shape in its first version, nonetheless it has been further\nimproved and has advanced notably in clarity. I think this new version of the manuscript\nis scientifically stronger. I think this paper will be of great interest to Nature\nCommunications readership and I therefore recommend publication.\nResponse:\nWe thank the reviewer for the constructive feedback and positive evaluation of our\nmanuscript.\nHowever, I have one remaining minor point that the authors could address:\n2.2 While the authors have discussed the lack of impact from historical sea-level rise\nover the 2002-2016 period, they should also consider how increasing future rates of\nrelative sea-level rise could potentially impact tidal flat dynamics and the applicability\nof their results over longer timescales.\nResponse:\nWe thank the reviewer for the comment. We agree with that the impact of sea-level rise\nshould be considered over longer timescales. In the context of the current study and\nprevious literatures, sediment-starved tidal flats face greater threats under accelerated\nsea-level rise. Additionally, sediment-rich tidal flats must maintain their sediment\navailability to mitigate the risks posed by rising sea levels. To make the above point\nclear, we added the text in lines 350-353 as:\n“However, over longer time scales (e.g., a few decades), its impact can be pronounced,\nespecially with concurrent SSC reduction23,36–38. Sediment-starved tidal flats face\ngreater threats under accelerated sea-level rise scenarios39, whereas sediment-rich\ntidal flats must also maintain their sediment availability to mitigate these risks36.”\n3. Response to Reviewer #3 (in blue):\n3.1. The authors have addressed our major points in the review. A new issue with the\npaper does arise with the inclusion of Australia, Indonesia, and the USA. These\ntransects are poorly integrated into the larger manuscript narrative and are potentially\nconfusing. They do not read like an answer to the generalizability of the finding.\nResponse:\nWe thank the reviewer for the comment. To better integrate the results from Australia,\nIndonesia, and the USA into the manuscript, we added text in the abstract (lines 32-35),\nas\n“Similar patterns can be observed from Indonesia, the United States, and Australia,\nimplying that the impact of sediment supply change is wide-spread and large-scale\nsediment allocation plan based on equilibrium concept can help preserving intertidal\necosystems.”\nIn the introduction (lines 80-82) as:\n“To assess the universality of these findings, we extended our analysis to three other\ncountries with extensive tidal flat areas but significantly lower sediment availability\ncompared to China, i.e., Indonesia, the USA, and Australia.”\nLastly, in discussion sections (lines 315-318) as:\n“Interestingly, our observation, combined with synthetic modeling, unveils a non-linear\nresponse of sediment-rich and sediment-starved tidal flats to altered sediment\navailability across four major countries with extensive tidal flat areas and diverse\nsediment supply levels (i.e., China, Indonesia, Australia, and the United States).”\n3.2 Additionally, the lack of discussion around direct conversion is unfortunate. While\nmentioned as a source of uncertainty the scope of direct change vs indirect drivers can\nnot be analyzed with the current study. If similar patterns are not observed in the directly\nimpacted mudflats, it only strengthens the general conclusions of the research. I would\nsuggested including that analyzing at least in a supplemental.\nResponse:\nWe thank the reviewer for the insightful suggestions, and we agree that it strengthens\nour general conclusion if different patterns are observed on transects that are directly\nimpacted by conversion. Since most tidal flats with the direct conversion are completely\nlost, their changing pattern with the environmental (indirect) factors cannot be revealed.\nThus, in the current revision, we identified nine tidal flat transects where a part of the\ntidal flats was converted, and compared these transects to those without the impact of\ndirect conversion.\nThis additional analysis reveals that:\n1. The morphology evolution patterns of tidal flats with direct human impact differ\nfrom those of tidal flats without human impact.\n2. Tidal flats exhibit a tendency to recover through fast sedimentation after direct\nconversion by human activity.\n3. The rate of tidal flat recovery exceeds the rate of tidal flat evolution driven by\nnatural drivers.\nThese results underscore the important difference imposed by direct human conversion.\nTo make the above points clear, we added the following text in the Results (lines 260-264)\nand Methods section (lines 520-526), as:\n“In our analysis, we focus on understanding how tidal flats respond to external\ndisturbances, since losses due to direct human interventions (such as conversion to\nother land use) are generally less predictable. We identified 9 transects that are\nconverted at the beginning of our study period (e.g., 2002, see Method), and they are\nobserved to generally accumulate at fast rates regardless of the SSC level\n(Supplementary Fig. 11).”\n“To compare the effects of direct conversion and external drivers, we identified nine\ntransects that were converted at the beginning of our study period and have SSC change\ndata, so that we can track their development. The results show that eight out of nine\ntransects exhibited a seaward progradation trend after the conversion (Supplementary\nFig. 11). The rate of tidal flat width change exceeds the rate of tidal flat evolution driven\nby natural drivers, highlighting the important difference imposed by direct conversion\nand the necessity to exclude those transects in our study.”\nSupplementary Figure 11. Comparison between the impact of direct human conversion\nand SSC change. The contour map represents the tidal flat width change corresponding\nto different variation rates in SSC from DET-ESTMORF modeling. Bubbles represent\nthe observed data points for tidal flat width changes, with those exceeding the axis\nrange plotted on the boundary (denoted by asterisks). Red bubbles indicate tidal flat\nexpansion, while green bubbles represent tidal flat retreat. Bubbles with black outlines\ndenote sites that are partly converted to other land use. The size of the bubbles reflects\nthe variation rate, scaled proportionally smaller compared to Fig. 5a.\n3.3 Line 44. Framing with the global number but also mention what the rate of direct\nconversion is in China.\nResponse:\nWe find that direct human conversion along China's coast ranged from 240 to 400 km²\nannually between 1950 and 2010 (Ma et al., 2014). To make the above point clear, we\nadded text in line 44-47 as:\n“66% of the area losses were attributed to indirect drivers, rather than direct human\nimpact through conversion to other land uses8, although in some countries such\nconversion was conducted at large scales (e.g., 240 to 400 km² per year during 1950-2010 in China9).”\n3.4 Line 333. I suggest changing “reclamation” to “conversion.” reclamation suggests\nmudflats need to be reclaimed from the ocean and implies they are wastelands which is\ndirectly opposed to the narrative of the paper.\nResponse:\nWe thank the reviewer for the comment. We have changed “reclamation” to “conversion”\nin the revised manuscript.\nReferences:\nBarrot, G., Mangin, A., & Pinnock, S. (2007). Global Ocean Colour for Carbon Cycle\nResearch, Product User Guide. ACRI-ST, Sophia-Antipolis.\nBi, S., Yang, Y., Xu, C., Zhang, Y., Zhang, X., & Zhang, X. (2017). 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Investigation using simple\nmathematical models of the effect of tidal currents and waves on the profile\nshape of intertidal mudflats. Continental Shelf Research, 20(10), 1079–1097.\nhttps://doi.org/10.1016/S0278-4343(00)00013-3\nSoulsby, R., Stive, M., de Vriend, H., Fredsoe, J., Hamm, L., Teisson, C., & Winterwerp,\nJ. (1995). Advances in coastal morphodynamics.\nWang, F., Sanders, C. J., Santos, I. R., Tang, J., Schuerch, M., Kirwan, M. L., et al.\n(2020). Global blue carbon accumulation in tidal wetlands increases with\nclimate change. National Science Review, 8(9), nwaa296.\nhttps://doi.org/10.1093/nsr/nwaa296\n“Dynamics and drivers of tidal flat morphology in China”\nShuai Liu, Zhan Hu, Tim J. Grandjean, Zheng B. Wang, Vincent T. M. van Zelst,\nLin Qi, Tianping Xu, Jun Young Seo, Tjeerd J. Bouma\nItemized List of Changes and Answers to the comments\n1. Response to Reviewer #1 (in blue):\n1.1 I appreciate the authors’ clarification and supplementation, but it also exposes more\nflaws in the manuscript especially in terms of data usage. Moreover, the revised\nmanuscript only provided explanations and did not find out new insights based on the\nreviewer's comments.\nResponse:\nWe appreciate the reviewer’s feedback. In response to the concerns raised, we have\ncarefully revisited our analysis to ensure the validity. A few new insights have been\nfound based on reviewer’s comments, which are listed below:\n1. We found that tidal flats in three other countries with extensive tidal flat areas share\nthe same dynamic response to SSC in China. This is supported by our additional\ndata analysis in the previous revision following reviewer’s suggestions. See also\nresponse # 1.7.\n2. The morphological evolution patterns of tidal flats subject to direct human\nconversion differ significantly from those of tidal flats evolving under natural\nconditions, highlighting the specific influence of human conversion and the\nnecessity to exclude transects affected by such activities. See also response #1.6 and\n#3.2\n3. Based on tide gauge data along China's coast, the relatively small changes in tidal\nrange (averaging 1.1 cm per year) and sea level rise have limited impacts on tidal\nflat morphology over the timescale of our study.\n1.2 For the hydrodynamics, the tides and waves were mentioned in this study. How\nabout the alongshore current, which is also important for the open coast tidal flat.\nI noticed that in Supplementary Figure 2, most of the sediment-rich tidal flats locate\nright in or adjacent to the estuaries. For those sediment-rich tidal flats a little bit far\nfrom the estuaries such as in the Jiangsu and Zhejiang coasts, the sediment is also\nsupplied by the Changjiang River, but carried by the alongshore current, rather than\ntides or waves.\nResponse:\nWe thank the reviewer for the comment. We agree with that the alongshore current is\nalso an important aspect of hydrodynamics. In the current study, we did not explicitly\nconsider the impact of alongshore currents for the following 3 reasons: 1) there is a lack\nof nationwide dataset or fine-scaled modelling results on alongshore current that can\nsupport our analysis. 2) As the reviewer mentioned that alongshore currents transport\nsediment over large scales, their impact is to some extent reflected by the SSC data we\nanalyzed. Thus, the role of alongshore currents is implicitly accounted for in the current\nstudy. 3) In our analysis, the considered environmental factors (i.e., SSC and tidal range)\nhave statistically significant impact on tidal flat morphology (p < 0.05, see Fig. 2 and\n3). Thus, we think that inclusion of alongshore currents as another environmental\nfactors would not affect the main results.\nIn the Method section of the revised manuscript, we acknowledge the exclusion of\nalongshore currents and explain the main reasons of it in lines 467-470 as:\n“In the current study, the impact of alongshore currents is not explicitly considered,\nsince there is a lack of nationwide dataset on alongshore currents. Yet, as alongshore\ncurrents transport sediment over large scales62,63, their impact is implicitly reflected by\nthe SSC data we analyzed.”\n1.3. Line 414-416: It is mentioned that the change rates of tidal range was calculated\nfrom TPXO9 data between 2002 and 2016. TPXO dataset only provides the harmonic\nconstants for 15 constituents. The calculated tidal range change rates are actually the\nlong-term variation of tidal forcing, such as the 18.61-year lunar nodal period. It is not\na response of the tidal flat morphological change.\nResponse:\nWe thank the reviewer for the constructive comment. We include tide level data from\n12 coastal stations in China in the current version. However, the results still indicated\nno significant correlation between the tidal range change and the width dynamics of the\nnearby tidal flats (p = 0.32). This is likely due to the relatively small changes in tidal\nrange, with an average change of 1.1 cm/year.\nTo make this point clear, we include text in lines 431-435 and the data are included in\nSupplementary Table 1 as:\n“To test the possible effect tidal range on tidal flat width, we compared the tidal range\nchange from the 12 UHSLC tide gauge sites49 with the tidal width changes. The results\nindicated no significant correlation between the tidal range changes and the nearby\ntidal flat width changes (p = 0.32), which is likely due to the relatively small changes\nin tidal range (averaged 1.1 cm per year).”\n1.4. Line 423-426: Reference 48 was used to evident that the ERA5 wave reanalysis\ndata suitable for China's coastal areas. However, the conclusion of this reference is “The\ndifference between the significant wave height (SWH) of ERA 5 and that of the buoy\nvaries from −0.35 m to 0.30 m for the three shallow locations; for the three deep\nlocations, the variation ranges from −0.09 m to 0.09 m. ... Hence, the ERA5 SWH data\ncannot be used for design applications without site-specific validation”. As shown in\nSupplementary Figure 3b, the wave heights in most coasts along China mainland are\nbelow 0.30 m, which are smaller than the errors estimated by reference 48.\nResponse:\nActually, in the abstract of Ref. 48 (Ref. 51 in the new version), the authors indicate\n\"Inter-comparisons suggest that the ERA5 dataset is consistent with the annual mean\nSWH\". As mentioned by the reviewer and in the main text of Ref. 48, ERA5 SWH data\ncannot be used for “design applications without site-specific validation”. Thus, we think\nthe authors of the Ref. 48 mean that the ERA5 SWH data may not be applied directly\nin engineering projects, such as design a harbor, but it is good to provide annual mean\nwave height, which is exactly what we need in our analysis.\nFurthermore, in the previous version, we actually tested the applicability of the ERA5\nSWH data. We compared the ERA5 dataset with field wave height data at four locations,\nand wave period data at three locations, respectively. The results confirm good\napplicability of ERA5 wave data on the coast of China.\nTo make this point clear, we add text in lines 462-467 and Supplementary Table 2 and\n3 as follows:\n“To validate the applicability of the ERA5 data, we collected wave data from tidal flats\nat various locations along China's coast, including Chongming Island56,57 and Leizhou\nBay58 for both wave height and period, Taiwan Longdong59 and the Yellow River\nmouth60 for wave height, and Jiangsu61 for wave period. The agreement between our\nestimated wave heights and periods with in-situ observations (Supplementary Tables 2\nand 3) confirms good applicability of ERA5 wave data.\n1.5. Line 455-459: As I mentioned in the previous review, the satellite remoted\nsurface SSC is not representative for coastal waters, especially the highly-stratified\nestuarine waters. But the authors explained that they used the TSM in the water\ncolumn to represent SSC. So, I checked the product manual of the GlobColour\nproject. It is given that “The MERIS/OLCI TSM product is computed from the back-\nscattering coefficient at 444 nm using the following assumptions: BP = BBP/0.015,\nTSM = 1.73*BP. BBP is an output of the GSM merging algorithm applied to L3\nsingle-sensors reflectances NRRS”. It is very clear that the TSM is the surface total\nsuspended matters, not in the water column. Furthermore, as shown in Supplementary\nFigure 3c, the SSC in the Yellow River mouth is much less than that in the Hangzhou\nBay. Do you believe that?\nResponse:\nWe thank the reviewer for the comment. We double checked our method and further\nreviewed the existing main literatures on this matter (Curran & Novo, 1988; Feng et\nal., 2014; Dorji et al., 2016; Shi & Wang, 2017; Schuerch et al., 2018; Zhao et al.,\n2022; Grandjean et al., 2024). We believe that this method is suitable for the current\nanalysis. The reasons are listed below:\nFirstly, our results show that the SSC in Yellow River mouth is indeed less than that in\nHangzhou Bay. We believe it is correct as the similar pattern can be found in other\nindependent studies based on different algorithms (see Fig. 6 in Feng et al., 2014; Fig.\n10 in Shi and Wang, 2017 and Fig. 4 in Zhao et al., 2022).\nSecondly, TSM or SSC. We totally agree that all satellite-derived water properties are\nfor “surface” waters down to one optical depth, whose corresponding physical depth\ndepends on the water column properties, ranging from tens of meters in clear waters\nto a few meters (or even centimeters) in turbid waters. Furthermore, similar to SSC,\nTSM is also a measure of concentration (note the units of mg L-1, equivalent to g m-3)\nas opposed to the integrated “total” water-column suspended matter (g m-2). In turbid\ncoastal waters, nearly all solid matters are suspended sediment particles, and therefore\nTSM and SSC are often used interchangeably. On whether the satellite-derived TSM\n(i.e., SSC used in this study) is an accurate representation of the water column, this\nreally depends on the vertical profiles of water properties. If the water is well mixed,\nthe answer is yes. For a two layer-system (i.e., highly stratified water) where the\nsurface layer is clear and most suspended matters are in the bottom layer, the satellite-\nderived TSM is still a good index because the contribution of the bottom layer to the\nsatellite signal is only attenuated slightly by the surface layer. A reversed two layer-\nsystem (i.e., the bottom layer is clear but surface layer contains most of the suspended\nmaterials) is instable because of particle sinking and therefore rare.\nThirdly, on the accuracy of satellite-derived TSM (mg/L). As with any other\nalgorithms, the TSM algorithm is not error free but contains uncertainties, largely\nfrom the assumption that particle backscattering (bbp) is only 1.5% (i.e., 0.015) of\ntotal particle scattering (bp). This assumption is based on the average value of a large\ndataset, but it can vary from place to place depending on the particle refraction index\nand size. However, such uncertainties are not expected to change the overall spatial\npatterns of temporal changes, especially when data are grouped to represent different\nclasses (e.g., 0-20, 20-50, 50-75, 75-280, Fig. 2). There is a lack of in situ data across\nthe whole China’s coast to validate the satellite data, yet results from independent\nstudies and other algorithms (Fig. 10 of Shi and Wang, 2017, Fig. 4 of Zhao et al.,\n2022 and Fig. 6 of Feng et al., 2014) are consistent with what we used here.\nTherefore, we believe that the uncertainties in the satellite-derived TSM used in this\nstudy would not alter our findings and conclusions.\nTo make the above points clear, we revised the text in the method section in lines 474-\n489 as:\n“The SSC data near the monitoring tidal flat transects were obtained from the\nGlobColour project (https://www.globcolour.info). The data product of total\nsuspended matter concentration (TSM, mg/L) produced by the project is used to\nrepresent SSC (mg/L) because in turbid coastal waters most suspended matters are\ndue to suspended sediments. It is estimated from satellite-derived particle\nbackscattering coefficient in the blue wavelength by assuming a\nbackscattering/scattering ratio of 0.015, and such a product has been previously used\nand found reliable for large scale analyses64,65. The spatial patterns of such derived\nTSM are consistent with those from independent studies using other algorithms66.\nAlthough satellite-derived TSM (or SSC) represents the particle concentration in\nsurface waters (down to an optical depth), for both well-mixed water column or\nhighly stratified waters it can be used as a proxy for suspended particles in the water\ncolumn66. This is because, for the former case it is obvious that TSM reflect the\noverall sediment concentration and, for the latter case, the signals from the bottom,\nparticle-rich layer will only be attenuated slightly by the surface, particle-poor layer.\nThe applicability of this approach has been validated in terms of both spatial\ndistribution67 and temporal variability68, and the method has been widely applied in\nprevious studies (e.g., ‘sediment availability data’ in ref64 and ‘turbidity for estuaries’\nin ref69).”\n1.6. The authors give some good examples of tidal flat sites directly affected by human\nactivities. However, these reclamations can not only converse the tidal flat to others,\nbut also affect the tidal flat nearby, like in the same bay/estuary or close to each other\nin the open coast, as these projects can alter the alongshore current or tidal range in the\nentire bay or estuary. I believe this is one of the main reasons for the morphological\nchange of tidal flats during this period. This is different from the increase/decrease\nsediment supply mentioned in this study. And do not forget those beach restoration\ncaused by artificial sand replenishment, such as in Xiamen. These activities all should\nbe separated in this study.\nResponse:\nWe thank the reviewer for the comment. In addition to excluding transects directly\ninfluenced by reclamations (conversion), we performed analyses by further removing\ntransects indirectly affected by the far-field effect of conversion. In total, 156 transects\nwere identified.\nWe first identified nine estuaries or bays that are heavily affected by conversion (over\n40% of the transects were directly converted), including Qinjiang River, Yingzai River,\nZhenhai Bay, Luojiang Estuary, Wenzhou Bay, Wulei Island Bay, Liaohe Estuary, the\nsouthern coast of Hangzhou Bay, and Qixing Reef. Then, the remaining transects in\nthese estuaries or bays are regarded as transects being affected by the far-field effect of\nconversion. Additionally, those adjacent to converted transects along the open coast are\nalso deemed influenced by far-field effects.\nSecondly, regarding beach restoration projects, the scale of beach restoration projects\nin China is limited compared to the national tidal flat coastline, only accounting for 1.2%\n(120 km / 10,196 km, Liu et al., 2020; Sun et al., 2024). A total of 6 transects were\ninfluenced by such activity.\nAfter excluding these transects that are indirectly or directly affected by reclamations\n(conversion), the response pattern of tidal flat width with SSC remains unchanged (even\nbecome more apparent) as shown in Supplementary figure 13.\nTo make this point clear, we add text in lines 266-269, 511-518 and 528-537as:\n“In addition to direct conversion, we conducted analysis excluding transects in 9\nestuaries or bays, as well as those adjacent to converted transects along the open coast,\nwhere the far-field effect of conversion could be important (see methods). We show that\nthe tidal flat width response to SSC change still hold when the data of these areas\nexcluded (Supplementary Fig. 13).”\n“Conversion of tidal flats to other land use directly and indirectly influence the\nevolution of tidal flats. To investigate the morphological evolution of large-scale tidal\nflat systems with environmental factors (i.e., hydrodynamic forcing and sediment\navailability), we excluded transects affected by direct conversion. First, we identified\ntidal flat transects with direct conversion by analyzing satellite imagery (see\nSupplementary Fig. 12). The tidal flats are mainly converted to agriculture or\naquaculture land use, and also (about 1.2%) to artificial sandy beaches in areas like\nXiamen city72. 750 transects are affected by direct conversion, which are excluded from\nour analysis.”\n“As conversion can also affect nearby hydrodynamic conditions, thereby influencing\nadjacent remaining tidal flat evolution by far-field effects. Therefore, we further\nexcluded transects adjacent to those directly impacted by conversion. We identified nine\nestuaries or bays where the conversion level is high (over 40% of the transects were\ndirectly converted), including Qinjiang Estuary, Yingzai River Estuary, Zhenhai Bay,\nLuojiang Estuary, Wenzhou Bay, Wulei Island Bay, Liaohe Estuary, the southern coast\nof Hangzhou Bay, and Qixing Reef. The remaining transects were identified as being\ninfluenced by far-field effects of conversion. Additionally, those adjacent to converted\ntransects along the open coast are also deemed influenced by far-field effects After\nexcluding all these 156 transects, our primary conclusions regarding spatial and\ntemporal patterns remain unchanged (See Supplementary Fig. 13).”\nWe also added the Supplementary Figure 13 as:\n[panels redacted]\nSupplementary Figure 13. Spatial (a) and temporal (b) results after excluding far-field\nimpacts of conversion. (c) An example of estuaries heavily impacted by human\nconversion (Liaohe Estuary). (d) An example of beach restoration caused by artificial\nsand replenishment (Xiamen).\n1.7. As the authors mentioned their theory also applied to tidal flats in Indonesia,\nAustralia, and the United States. But I do not see any figures or tables to support their\nconclusion.\nResponse:\nActually, in the previous revision, figures related to our theory applied to Indonesia,\nAustralia, and the United States are included in the Fig. 5b and Fig. 5c. A detailed\nexplanation of these results is provided in line 271-277.\n2. Response to Reviewer #2 (in blue):\n2.1. I have read in detail and with great interest the revised version of the paper\n\"Dynamics and drivers of tidal flat morphology in China\" by Liu et al.\nI consider that the Authors have quite satisfactorily covered, both by correcting or\nanswering correctly, all the questions and comments that were posed by myself in the\nreview of the first version. I have also read the response to the comments and requests\nfor change of the other reviewers and I think the paper greatly benefited from those\nsuggestions and from the detailed answers to those reviewers. I am quite pleased to note\nthat the authors have very seriously addressed all of the comments: they have done a\nthorough job in revising this manuscript.\nIn particular, the authors have:\n1) Provided more detailed explanations on the morphodynamic mechanisms and\nfeedbacks that control the contrasting responses of sediment-rich and sediment-starved\nareas to changes in sediment availability. This strengthens the understanding of the\nresults.\n2) Included an analysis of data from three other countries (Indonesia, Australia, United\nStates, countries with extensive tidal flat areas) to show the global applicability of their\ntheory. This expands the relevance of the study. I appreciated this effort.\n3) Discussed the potential impact of sea-level rise, recalling appropriate references and\nexplaining why it was not considered in this short-term study.\n4) Clarified the thresholds used to define sediment-rich and sediment-starved areas and\nacknowledged that these thresholds may vary in other regions.\n5) Provided further details on how they quantified the relaxation times to reach a new\nmorphodynamic equilibrium.\nThe paper was already in good shape in its first version, nonetheless it has been further\nimproved and has advanced notably in clarity. I think this new version of the manuscript\nis scientifically stronger. I think this paper will be of great interest to Nature\nCommunications readership and I therefore recommend publication.\nResponse:\nWe thank the reviewer for the constructive feedback and positive evaluation of our\nmanuscript.\nHowever, I have one remaining minor point that the authors could address:\n2.2 While the authors have discussed the lack of impact from historical sea-level rise\nover the 2002-2016 period, they should also consider how increasing future rates of\nrelative sea-level rise could potentially impact tidal flat dynamics and the applicability\nof their results over longer timescales.\nResponse:\nWe thank the reviewer for the comment. We agree with that the impact of sea-level rise\nshould be considered over longer timescales. In the context of the current study and\nprevious literatures, sediment-starved tidal flats face greater threats under accelerated\nsea-level rise. Additionally, sediment-rich tidal flats must maintain their sediment\navailability to mitigate the risks posed by rising sea levels. To make the above point\nclear, we added the text in lines 350-353 as:\n“However, over longer time scales (e.g., a few decades), its impact can be pronounced,\nespecially with concurrent SSC reduction23,36–38. Sediment-starved tidal flats face\ngreater threats under accelerated sea-level rise scenarios39, whereas sediment-rich\ntidal flats must also maintain their sediment availability to mitigate these risks36.”\n3. Response to Reviewer #3 (in blue):\n3.1. The authors have addressed our major points in the review. A new issue with the\npaper does arise with the inclusion of Australia, Indonesia, and the USA. These\ntransects are poorly integrated into the larger manuscript narrative and are potentially\nconfusing. They do not read like an answer to the generalizability of the finding.\nResponse:\nWe thank the reviewer for the comment. To better integrate the results from Australia,\nIndonesia, and the USA into the manuscript, we added text in the abstract (lines 32-35),\nas\n“Similar patterns can be observed from Indonesia, the United States, and Australia,\nimplying that the impact of sediment supply change is wide-spread and large-scale\nsediment allocation plan based on equilibrium concept can help preserving intertidal\necosystems.”\nIn the introduction (lines 80-82) as:\n“To assess the universality of these findings, we extended our analysis to three other\ncountries with extensive tidal flat areas but significantly lower sediment availability\ncompared to China, i.e., Indonesia, the USA, and Australia.”\nLastly, in discussion sections (lines 315-318) as:\n“Interestingly, our observation, combined with synthetic modeling, unveils a non-linear\nresponse of sediment-rich and sediment-starved tidal flats to altered sediment\navailability across four major countries with extensive tidal flat areas and diverse\nsediment supply levels (i.e., China, Indonesia, Australia, and the United States).”\n3.2 Additionally, the lack of discussion around direct conversion is unfortunate. While\nmentioned as a source of uncertainty the scope of direct change vs indirect drivers can\nnot be analyzed with the current study. If similar patterns are not observed in the directly\nimpacted mudflats, it only strengthens the general conclusions of the research. I would\nsuggested including that analyzing at least in a supplemental.\nResponse:\nWe thank the reviewer for the insightful suggestions, and we agree that it strengthens\nour general conclusion if different patterns are observed on transects that are directly\nimpacted by conversion. Since most tidal flats with the direct conversion are completely\nlost, their changing pattern with the environmental (indirect) factors cannot be revealed.\nThus, in the current revision, we identified nine tidal flat transects where a part of the\ntidal flats was converted, and compared these transects to those without the impact of\ndirect conversion.\nThis additional analysis reveals that:\n1. The morphology evolution patterns of tidal flats with direct human impact differ\nfrom those of tidal flats without human impact.\n2. Tidal flats exhibit a tendency to recover through fast sedimentation after direct\nconversion by human activity.\n3. The rate of tidal flat recovery exceeds the rate of tidal flat evolution driven by\nnatural drivers.\nThese results underscore the important difference imposed by direct human conversion.\nTo make the above points clear, we added the following text in the Results (lines 260-264)\nand Methods section (lines 520-526), as:\n“In our analysis, we focus on understanding how tidal flats respond to external\ndisturbances, since losses due to direct human interventions (such as conversion to\nother land use) are generally less predictable. We identified 9 transects that are\nconverted at the beginning of our study period (e.g., 2002, see Method), and they are\nobserved to generally accumulate at fast rates regardless of the SSC level\n(Supplementary Fig. 11).”\n“To compare the effects of direct conversion and external drivers, we identified nine\ntransects that were converted at the beginning of our study period and have SSC change\ndata, so that we can track their development. The results show that eight out of nine\ntransects exhibited a seaward progradation trend after the conversion (Supplementary\nFig. 11). The rate of tidal flat width change exceeds the rate of tidal flat evolution driven\nby natural drivers, highlighting the important difference imposed by direct conversion\nand the necessity to exclude those transects in our study.”\nSupplementary Figure 11. Comparison between the impact of direct human conversion\nand SSC change. The contour map represents the tidal flat width change corresponding\nto different variation rates in SSC from DET-ESTMORF modeling. Bubbles represent\nthe observed data points for tidal flat width changes, with those exceeding the axis\nrange plotted on the boundary (denoted by asterisks). Red bubbles indicate tidal flat\nexpansion, while green bubbles represent tidal flat retreat. Bubbles with black outlines\ndenote sites that are partly converted to other land use. The size of the bubbles reflects\nthe variation rate, scaled proportionally smaller compared to Fig. 5a.\n3.3 Line 44. Framing with the global number but also mention what the rate of direct\nconversion is in China.\nResponse:\nWe find that direct human conversion along China's coast ranged from 240 to 400 km²\nannually between 1950 and 2010 (Ma et al., 2014). To make the above point clear, we\nadded text in line 44-47 as:\n“66% of the area losses were attributed to indirect drivers, rather than direct human\nimpact through conversion to other land uses8, although in some countries such\nconversion was conducted at large scales (e.g., 240 to 400 km² per year during 1950-2010 in China9).”\n3.4 Line 333. I suggest changing “reclamation” to “conversion.” reclamation suggests\nmudflats need to be reclaimed from the ocean and implies they are wastelands which is\ndirectly opposed to the narrative of the paper.\nResponse:\nWe thank the reviewer for the comment. We have changed “reclamation” to “conversion”\nin the revised manuscript.\nReferences:\nBarrot, G., Mangin, A., & Pinnock, S. (2007). Global Ocean Colour for Carbon Cycle\nResearch, Product User Guide. ACRI-ST, Sophia-Antipolis.\nBi, S., Yang, Y., Xu, C., Zhang, Y., Zhang, X., & Zhang, X. (2017). 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Investigation using simple\nmathematical models of the effect of tidal currents and waves on the profile\nshape of intertidal mudflats. Continental Shelf Research, 20(10), 1079–1097.\nhttps://doi.org/10.1016/S0278-4343(00)00013-3\nSoulsby, R., Stive, M., de Vriend, H., Fredsoe, J., Hamm, L., Teisson, C., & Winterwerp,\nJ. (1995). Advances in coastal morphodynamics.\nWang, F., Sanders, C. J., Santos, I. R., Tang, J., Schuerch, M., Kirwan, M. L., et al.\n(2020). Global blue carbon accumulation in tidal wetlands increases with\nclimate change. National Science Review, 8(9), nwaa296.\nhttps://doi.org/10.1093/nsr/nwaa296"}, {"round": 2, "reviewer_comments": {"reviewer_1": "I appreciate the authors’ clarification and supplementation, but it also exposes more flaws in the manuscript especially in terms of data usage. Moreover, the revised manuscript only provided explanations and did not find out new insights based on the reviewer's comments.\n1. For the hydrodynamics, the tides and waves were mentioned in this study. How about the alongshore current, which is also important for the open coast tidal flat. I noticed that in Supplementary Figure 2, most of the sediment-rich tidal flats locate right in or adjacent to the estuaries. For those sediment-rich tidal flats a little bit far from the estuaries such as in the Jiangsu and Zhejiang coasts, the sediment is also supplied by the Changjiang River, but carried by the alongshore current, rather than tides or waves.\n2. Line 414-416: It is mentioned that the change rates of tidal range was calculated from TPXO9 data between 2002 and 2016. TPXO dataset only provides the harmonic constants for 15 constituents. The calculated tidal range change rates are actually the long-term variation of tidal forcing, such as the 18.61-year lunar nodal period. It is not a response of the tidal flat morphological change.\n3. Line 423-426: Reference 48 was used to evident that the ERA5 wave reanalysis data suitable for China's coastal areas. However, the conclusion of this reference is “The difference between the significant wave height (SWH) of ERA 5 and that of the buoy varies from −0.35 m to 0.30 m for the three shallow locations; for the three deep locations, the variation ranges from −0.09 m to 0.09 m. ... Hence, the ERA5 SWH data cannot be used for design applications without site-specific validation”. As shown in Supplementary Figure 3b, the wave heights in most coasts along China mainland are below 0.30 m, which are smaller than the errors estimated by reference 48.\n4. Line 455-459: As I mentioned in the previous review, the satellite remoted surface SSC is not representative for coastal waters, especially the highly-stratified estuarine waters. But the authors explained that they used the TSM in the water column to represent SSC. So, I checked the product manual of the GlobColour project. It is given that “The MERIS/OLCI TSM product is computed from the back-scattering coefficient at 444 nm using the following assumptions: BP = BBP/0.015, TSM = 1.73*BP. BBP is an output of the GSM merging algorithm applied to L3 single-sensors reflectances NRRS”. It is very clear that the TSM is the surface total suspended matters, not in the water column. Furthermore, as shown in Supplementary Figure 3c, the SSC in the Yellow River mouth is much less than that in the Hangzhou Bay. Do you believe that?\n5. The authors give some good examples of tidal flat sites directly affected by human activities. However, these reclamations can not only converse the tidal flat to others, but also affect the tidal flat nearby, like in the same bay/estuary or close to each other in the open coast, as these projects can alter the alongshore current or tidal range in the entire bay or estuary. I believe this is one of the main reasons for the morphological change of tidal flats during this period. This is different from the increase/decrease sediment supply mentioned in this study. And do not forget those beach restoration caused by artificial sand replenishment, such as in Xiamen. These activities all should be separated in this study.\n6. As the authors mentioned their theory also applied to tidal flats in Indonesia, Australia, and the United States. But I do not see any figures or tables to support their conclusion.\n(Remarks on code availability)", "reviewer_2": "I have read in detail and with great interest the revised version of the paper \"Dynamics and drivers of tidal flat morphology in China\" by Liu et al.\nI consider that the Authors have quite satisfactorily covered, both by correcting or answering correctly, all the questions and comments that were posed by myself in the review of the first version. I have also read the response to the comments and requests for change of the other reviewers and I think the paper greatly benefited from those suggestions and from the detailed answers to those reviewers. I am quite pleased to note that the authors have very seriously addressed all of the comments: they have done a thorough job in revising this manuscript.\nIn particular, the authors have:\n1) Provided more detailed explanations on the morphodynamic mechanisms and feedbacks that control the contrasting responses of sediment-rich and sediment-starved areas to changes in sediment availability. This strengthens the understanding of the results.\n2) Included an analysis of data from three other countries (Indonesia, Australia, United States, countries with extensive tidal flat areas ) to show the global applicability of their theory. This expands the relevance of the study. I appreciated this effort.\n3) Discussed the potential impact of sea-level rise, recalling appropriate references and explaining why it was not considered in this short-term study.\n4) Clarified the thresholds used to define sediment-rich and sediment-starved areas and acknowledged that these thresholds may vary in other regions.\n5) Provided further details on how they quantified the relaxation times to reach a new morphodynamic equilibrium.\nThe paper was already in good shape in its first version, nonetheless it has been further improved and has advanced notably in clarity. I think this new version of the manuscript is scientifically stronger. I think this paper will be of great interest to Nature Communications readership and I therefore recommend publication.\nHowever, I have one remaining minor point that the authors could address:\nWhile the authors have discussed the lack of impact from historical sea-level rise over the 2002-2016 period, they should also consider how increasing future rates of relative sea-level rise could potentially impact tidal flat dynamics and the applicability of their results over longer timescales.\n(Remarks on code availability)", "reviewer_3": "The authors have addressed our major points in the review. A new issue with the paper does arise with the inclusion of Australia, Indonesia, and the USA. These transects are poorly integrated into the larger manuscript narrative and are potentially confusing. They do not read like an answer to the generalizability of the finding. Additionally, the lack of discussion around direct conversion is unfortunate. While mentioned as a source of uncertainty the scope of direct change vs indirect drivers can not be analyzed with the current study. If similar patterns are not observed in the directly impacted mudflats, it only strengthens the general conclusions of the research. I would suggested including that analyzing at least in a supplemental.\nLine 44. Framing with the global number but also mention what the rate of direct conversion is in China.\nLine 333. I suggest changing “reclamation” to “conversion.” reclamation suggests mudflats need to be reclaimed from the ocean and implies they are wastelands which is directly opposed to the narrative of the paper.\n(Remarks on code availability)"}, "author_response": "“Dynamics and drivers of tidal flat morphology in China”\nShuai Liu, Zhan Hu, Tim J. Grandjean, Zheng B. Wang, Vincent T. M. van Zelst,\nLin Qi, Tianping Xu, Jun Young Seo, Tjeerd J. Bouma\nItemized List of Changes and Answers to the comments\n1. Response to Reviewer #1 (in blue):\n1.1 I appreciate the authors’ clarification and supplementation, but it also exposes more\nflaws in the manuscript especially in terms of data usage. Moreover, the revised\nmanuscript only provided explanations and did not find out new insights based on the\nreviewer's comments.\nResponse:\nWe appreciate the reviewer’s feedback. In response to the concerns raised, we have\ncarefully revisited our analysis to ensure the validity. A few new insights have been\nfound based on reviewer’s comments, which are listed below:\n1. We found that tidal flats in three other countries with extensive tidal flat areas share\nthe same dynamic response to SSC in China. This is supported by our additional\ndata analysis in the previous revision following reviewer’s suggestions. See also\nresponse # 1.7.\n2. The morphological evolution patterns of tidal flats subject to direct human\nconversion differ significantly from those of tidal flats evolving under natural\nconditions, highlighting the specific influence of human conversion and the\nnecessity to exclude transects affected by such activities. See also response #1.6 and\n#3.2\n3. Based on tide gauge data along China's coast, the relatively small changes in tidal\nrange (averaging 1.1 cm per year) and sea level rise have limited impacts on tidal\nflat morphology over the timescale of our study.\n1.2 For the hydrodynamics, the tides and waves were mentioned in this study. How\nabout the alongshore current, which is also important for the open coast tidal flat.\nI noticed that in Supplementary Figure 2, most of the sediment-rich tidal flats locate\nright in or adjacent to the estuaries. For those sediment-rich tidal flats a little bit far\nfrom the estuaries such as in the Jiangsu and Zhejiang coasts, the sediment is also\nsupplied by the Changjiang River, but carried by the alongshore current, rather than\ntides or waves.\nResponse:\nWe thank the reviewer for the comment. We agree with that the alongshore current is\nalso an important aspect of hydrodynamics. In the current study, we did not explicitly\nconsider the impact of alongshore currents for the following 3 reasons: 1) there is a lack\nof nationwide dataset or fine-scaled modelling results on alongshore current that can\nsupport our analysis. 2) As the reviewer mentioned that alongshore currents transport\nsediment over large scales, their impact is to some extent reflected by the SSC data we\nanalyzed. Thus, the role of alongshore currents is implicitly accounted for in the current\nstudy. 3) In our analysis, the considered environmental factors (i.e., SSC and tidal range)\nhave statistically significant impact on tidal flat morphology (p < 0.05, see Fig. 2 and\n3). Thus, we think that inclusion of alongshore currents as another environmental\nfactors would not affect the main results.\nIn the Method section of the revised manuscript, we acknowledge the exclusion of\nalongshore currents and explain the main reasons of it in lines 467-470 as:\n“In the current study, the impact of alongshore currents is not explicitly considered,\nsince there is a lack of nationwide dataset on alongshore currents. Yet, as alongshore\ncurrents transport sediment over large scales62,63, their impact is implicitly reflected by\nthe SSC data we analyzed.”\n1.3. Line 414-416: It is mentioned that the change rates of tidal range was calculated\nfrom TPXO9 data between 2002 and 2016. TPXO dataset only provides the harmonic\nconstants for 15 constituents. The calculated tidal range change rates are actually the\nlong-term variation of tidal forcing, such as the 18.61-year lunar nodal period. It is not\na response of the tidal flat morphological change.\nResponse:\nWe thank the reviewer for the constructive comment. We include tide level data from\n12 coastal stations in China in the current version. However, the results still indicated\nno significant correlation between the tidal range change and the width dynamics of the\nnearby tidal flats (p = 0.32). This is likely due to the relatively small changes in tidal\nrange, with an average change of 1.1 cm/year.\nTo make this point clear, we include text in lines 431-435 and the data are included in\nSupplementary Table 1 as:\n“To test the possible effect tidal range on tidal flat width, we compared the tidal range\nchange from the 12 UHSLC tide gauge sites49 with the tidal width changes. The results\nindicated no significant correlation between the tidal range changes and the nearby\ntidal flat width changes (p = 0.32), which is likely due to the relatively small changes\nin tidal range (averaged 1.1 cm per year).”\n1.4. Line 423-426: Reference 48 was used to evident that the ERA5 wave reanalysis\ndata suitable for China's coastal areas. However, the conclusion of this reference is “The\ndifference between the significant wave height (SWH) of ERA 5 and that of the buoy\nvaries from −0.35 m to 0.30 m for the three shallow locations; for the three deep\nlocations, the variation ranges from −0.09 m to 0.09 m. ... Hence, the ERA5 SWH data\ncannot be used for design applications without site-specific validation”. As shown in\nSupplementary Figure 3b, the wave heights in most coasts along China mainland are\nbelow 0.30 m, which are smaller than the errors estimated by reference 48.\nResponse:\nActually, in the abstract of Ref. 48 (Ref. 51 in the new version), the authors indicate\n\"Inter-comparisons suggest that the ERA5 dataset is consistent with the annual mean\nSWH\". As mentioned by the reviewer and in the main text of Ref. 48, ERA5 SWH data\ncannot be used for “design applications without site-specific validation”. Thus, we think\nthe authors of the Ref. 48 mean that the ERA5 SWH data may not be applied directly\nin engineering projects, such as design a harbor, but it is good to provide annual mean\nwave height, which is exactly what we need in our analysis.\nFurthermore, in the previous version, we actually tested the applicability of the ERA5\nSWH data. We compared the ERA5 dataset with field wave height data at four locations,\nand wave period data at three locations, respectively. The results confirm good\napplicability of ERA5 wave data on the coast of China.\nTo make this point clear, we add text in lines 462-467 and Supplementary Table 2 and\n3 as follows:\n“To validate the applicability of the ERA5 data, we collected wave data from tidal flats\nat various locations along China's coast, including Chongming Island56,57 and Leizhou\nBay58 for both wave height and period, Taiwan Longdong59 and the Yellow River\nmouth60 for wave height, and Jiangsu61 for wave period. The agreement between our\nestimated wave heights and periods with in-situ observations (Supplementary Tables 2\nand 3) confirms good applicability of ERA5 wave data.\n1.5. Line 455-459: As I mentioned in the previous review, the satellite remoted\nsurface SSC is not representative for coastal waters, especially the highly-stratified\nestuarine waters. But the authors explained that they used the TSM in the water\ncolumn to represent SSC. So, I checked the product manual of the GlobColour\nproject. It is given that “The MERIS/OLCI TSM product is computed from the back-\nscattering coefficient at 444 nm using the following assumptions: BP = BBP/0.015,\nTSM = 1.73*BP. BBP is an output of the GSM merging algorithm applied to L3\nsingle-sensors reflectances NRRS”. It is very clear that the TSM is the surface total\nsuspended matters, not in the water column. Furthermore, as shown in Supplementary\nFigure 3c, the SSC in the Yellow River mouth is much less than that in the Hangzhou\nBay. Do you believe that?\nResponse:\nWe thank the reviewer for the comment. We double checked our method and further\nreviewed the existing main literatures on this matter (Curran & Novo, 1988; Feng et\nal., 2014; Dorji et al., 2016; Shi & Wang, 2017; Schuerch et al., 2018; Zhao et al.,\n2022; Grandjean et al., 2024). We believe that this method is suitable for the current\nanalysis. The reasons are listed below:\nFirstly, our results show that the SSC in Yellow River mouth is indeed less than that in\nHangzhou Bay. We believe it is correct as the similar pattern can be found in other\nindependent studies based on different algorithms (see Fig. 6 in Feng et al., 2014; Fig.\n10 in Shi and Wang, 2017 and Fig. 4 in Zhao et al., 2022).\nSecondly, TSM or SSC. We totally agree that all satellite-derived water properties are\nfor “surface” waters down to one optical depth, whose corresponding physical depth\ndepends on the water column properties, ranging from tens of meters in clear waters\nto a few meters (or even centimeters) in turbid waters. Furthermore, similar to SSC,\nTSM is also a measure of concentration (note the units of mg L-1, equivalent to g m-3)\nas opposed to the integrated “total” water-column suspended matter (g m-2). In turbid\ncoastal waters, nearly all solid matters are suspended sediment particles, and therefore\nTSM and SSC are often used interchangeably. On whether the satellite-derived TSM\n(i.e., SSC used in this study) is an accurate representation of the water column, this\nreally depends on the vertical profiles of water properties. If the water is well mixed,\nthe answer is yes. For a two layer-system (i.e., highly stratified water) where the\nsurface layer is clear and most suspended matters are in the bottom layer, the satellite-\nderived TSM is still a good index because the contribution of the bottom layer to the\nsatellite signal is only attenuated slightly by the surface layer. A reversed two layer-\nsystem (i.e., the bottom layer is clear but surface layer contains most of the suspended\nmaterials) is instable because of particle sinking and therefore rare.\nThirdly, on the accuracy of satellite-derived TSM (mg/L). As with any other\nalgorithms, the TSM algorithm is not error free but contains uncertainties, largely\nfrom the assumption that particle backscattering (bbp) is only 1.5% (i.e., 0.015) of\ntotal particle scattering (bp). This assumption is based on the average value of a large\ndataset, but it can vary from place to place depending on the particle refraction index\nand size. However, such uncertainties are not expected to change the overall spatial\npatterns of temporal changes, especially when data are grouped to represent different\nclasses (e.g., 0-20, 20-50, 50-75, 75-280, Fig. 2). There is a lack of in situ data across\nthe whole China’s coast to validate the satellite data, yet results from independent\nstudies and other algorithms (Fig. 10 of Shi and Wang, 2017, Fig. 4 of Zhao et al.,\n2022 and Fig. 6 of Feng et al., 2014) are consistent with what we used here.\nTherefore, we believe that the uncertainties in the satellite-derived TSM used in this\nstudy would not alter our findings and conclusions.\nTo make the above points clear, we revised the text in the method section in lines 474-\n489 as:\n“The SSC data near the monitoring tidal flat transects were obtained from the\nGlobColour project (https://www.globcolour.info). The data product of total\nsuspended matter concentration (TSM, mg/L) produced by the project is used to\nrepresent SSC (mg/L) because in turbid coastal waters most suspended matters are\ndue to suspended sediments. It is estimated from satellite-derived particle\nbackscattering coefficient in the blue wavelength by assuming a\nbackscattering/scattering ratio of 0.015, and such a product has been previously used\nand found reliable for large scale analyses64,65. The spatial patterns of such derived\nTSM are consistent with those from independent studies using other algorithms66.\nAlthough satellite-derived TSM (or SSC) represents the particle concentration in\nsurface waters (down to an optical depth), for both well-mixed water column or\nhighly stratified waters it can be used as a proxy for suspended particles in the water\ncolumn66. This is because, for the former case it is obvious that TSM reflect the\noverall sediment concentration and, for the latter case, the signals from the bottom,\nparticle-rich layer will only be attenuated slightly by the surface, particle-poor layer.\nThe applicability of this approach has been validated in terms of both spatial\ndistribution67 and temporal variability68, and the method has been widely applied in\nprevious studies (e.g., ‘sediment availability data’ in ref64 and ‘turbidity for estuaries’\nin ref69).”\n1.6. The authors give some good examples of tidal flat sites directly affected by human\nactivities. However, these reclamations can not only converse the tidal flat to others,\nbut also affect the tidal flat nearby, like in the same bay/estuary or close to each other\nin the open coast, as these projects can alter the alongshore current or tidal range in the\nentire bay or estuary. I believe this is one of the main reasons for the morphological\nchange of tidal flats during this period. This is different from the increase/decrease\nsediment supply mentioned in this study. And do not forget those beach restoration\ncaused by artificial sand replenishment, such as in Xiamen. These activities all should\nbe separated in this study.\nResponse:\nWe thank the reviewer for the comment. In addition to excluding transects directly\ninfluenced by reclamations (conversion), we performed analyses by further removing\ntransects indirectly affected by the far-field effect of conversion. In total, 156 transects\nwere identified.\nWe first identified nine estuaries or bays that are heavily affected by conversion (over\n40% of the transects were directly converted), including Qinjiang River, Yingzai River,\nZhenhai Bay, Luojiang Estuary, Wenzhou Bay, Wulei Island Bay, Liaohe Estuary, the\nsouthern coast of Hangzhou Bay, and Qixing Reef. Then, the remaining transects in\nthese estuaries or bays are regarded as transects being affected by the far-field effect of\nconversion. Additionally, those adjacent to converted transects along the open coast are\nalso deemed influenced by far-field effects.\nSecondly, regarding beach restoration projects, the scale of beach restoration projects\nin China is limited compared to the national tidal flat coastline, only accounting for 1.2%\n(120 km / 10,196 km, Liu et al., 2020; Sun et al., 2024). A total of 6 transects were\ninfluenced by such activity.\nAfter excluding these transects that are indirectly or directly affected by reclamations\n(conversion), the response pattern of tidal flat width with SSC remains unchanged (even\nbecome more apparent) as shown in Supplementary figure 13.\nTo make this point clear, we add text in lines 266-269, 511-518 and 528-537as:\n“In addition to direct conversion, we conducted analysis excluding transects in 9\nestuaries or bays, as well as those adjacent to converted transects along the open coast,\nwhere the far-field effect of conversion could be important (see methods). We show that\nthe tidal flat width response to SSC change still hold when the data of these areas\nexcluded (Supplementary Fig. 13).”\n“Conversion of tidal flats to other land use directly and indirectly influence the\nevolution of tidal flats. To investigate the morphological evolution of large-scale tidal\nflat systems with environmental factors (i.e., hydrodynamic forcing and sediment\navailability), we excluded transects affected by direct conversion. First, we identified\ntidal flat transects with direct conversion by analyzing satellite imagery (see\nSupplementary Fig. 12). The tidal flats are mainly converted to agriculture or\naquaculture land use, and also (about 1.2%) to artificial sandy beaches in areas like\nXiamen city72. 750 transects are affected by direct conversion, which are excluded from\nour analysis.”\n“As conversion can also affect nearby hydrodynamic conditions, thereby influencing\nadjacent remaining tidal flat evolution by far-field effects. Therefore, we further\nexcluded transects adjacent to those directly impacted by conversion. We identified nine\nestuaries or bays where the conversion level is high (over 40% of the transects were\ndirectly converted), including Qinjiang Estuary, Yingzai River Estuary, Zhenhai Bay,\nLuojiang Estuary, Wenzhou Bay, Wulei Island Bay, Liaohe Estuary, the southern coast\nof Hangzhou Bay, and Qixing Reef. The remaining transects were identified as being\ninfluenced by far-field effects of conversion. Additionally, those adjacent to converted\ntransects along the open coast are also deemed influenced by far-field effects After\nexcluding all these 156 transects, our primary conclusions regarding spatial and\ntemporal patterns remain unchanged (See Supplementary Fig. 13).”\nWe also added the Supplementary Figure 13 as:\n[panels redacted]\nSupplementary Figure 13. Spatial (a) and temporal (b) results after excluding far-field\nimpacts of conversion. (c) An example of estuaries heavily impacted by human\nconversion (Liaohe Estuary). (d) An example of beach restoration caused by artificial\nsand replenishment (Xiamen).\n1.7. As the authors mentioned their theory also applied to tidal flats in Indonesia,\nAustralia, and the United States. But I do not see any figures or tables to support their\nconclusion.\nResponse:\nActually, in the previous revision, figures related to our theory applied to Indonesia,\nAustralia, and the United States are included in the Fig. 5b and Fig. 5c. A detailed\nexplanation of these results is provided in line 271-277.\n2. Response to Reviewer #2 (in blue):\n2.1. I have read in detail and with great interest the revised version of the paper\n\"Dynamics and drivers of tidal flat morphology in China\" by Liu et al.\nI consider that the Authors have quite satisfactorily covered, both by correcting or\nanswering correctly, all the questions and comments that were posed by myself in the\nreview of the first version. I have also read the response to the comments and requests\nfor change of the other reviewers and I think the paper greatly benefited from those\nsuggestions and from the detailed answers to those reviewers. I am quite pleased to note\nthat the authors have very seriously addressed all of the comments: they have done a\nthorough job in revising this manuscript.\nIn particular, the authors have:\n1) Provided more detailed explanations on the morphodynamic mechanisms and\nfeedbacks that control the contrasting responses of sediment-rich and sediment-starved\nareas to changes in sediment availability. This strengthens the understanding of the\nresults.\n2) Included an analysis of data from three other countries (Indonesia, Australia, United\nStates, countries with extensive tidal flat areas) to show the global applicability of their\ntheory. This expands the relevance of the study. I appreciated this effort.\n3) Discussed the potential impact of sea-level rise, recalling appropriate references and\nexplaining why it was not considered in this short-term study.\n4) Clarified the thresholds used to define sediment-rich and sediment-starved areas and\nacknowledged that these thresholds may vary in other regions.\n5) Provided further details on how they quantified the relaxation times to reach a new\nmorphodynamic equilibrium.\nThe paper was already in good shape in its first version, nonetheless it has been further\nimproved and has advanced notably in clarity. I think this new version of the manuscript\nis scientifically stronger. I think this paper will be of great interest to Nature\nCommunications readership and I therefore recommend publication.\nResponse:\nWe thank the reviewer for the constructive feedback and positive evaluation of our\nmanuscript.\nHowever, I have one remaining minor point that the authors could address:\n2.2 While the authors have discussed the lack of impact from historical sea-level rise\nover the 2002-2016 period, they should also consider how increasing future rates of\nrelative sea-level rise could potentially impact tidal flat dynamics and the applicability\nof their results over longer timescales.\nResponse:\nWe thank the reviewer for the comment. We agree with that the impact of sea-level rise\nshould be considered over longer timescales. In the context of the current study and\nprevious literatures, sediment-starved tidal flats face greater threats under accelerated\nsea-level rise. Additionally, sediment-rich tidal flats must maintain their sediment\navailability to mitigate the risks posed by rising sea levels. To make the above point\nclear, we added the text in lines 350-353 as:\n“However, over longer time scales (e.g., a few decades), its impact can be pronounced,\nespecially with concurrent SSC reduction23,36–38. Sediment-starved tidal flats face\ngreater threats under accelerated sea-level rise scenarios39, whereas sediment-rich\ntidal flats must also maintain their sediment availability to mitigate these risks36.”\n3. Response to Reviewer #3 (in blue):\n3.1. The authors have addressed our major points in the review. A new issue with the\npaper does arise with the inclusion of Australia, Indonesia, and the USA. These\ntransects are poorly integrated into the larger manuscript narrative and are potentially\nconfusing. They do not read like an answer to the generalizability of the finding.\nResponse:\nWe thank the reviewer for the comment. To better integrate the results from Australia,\nIndonesia, and the USA into the manuscript, we added text in the abstract (lines 32-35),\nas\n“Similar patterns can be observed from Indonesia, the United States, and Australia,\nimplying that the impact of sediment supply change is wide-spread and large-scale\nsediment allocation plan based on equilibrium concept can help preserving intertidal\necosystems.”\nIn the introduction (lines 80-82) as:\n“To assess the universality of these findings, we extended our analysis to three other\ncountries with extensive tidal flat areas but significantly lower sediment availability\ncompared to China, i.e., Indonesia, the USA, and Australia.”\nLastly, in discussion sections (lines 315-318) as:\n“Interestingly, our observation, combined with synthetic modeling, unveils a non-linear\nresponse of sediment-rich and sediment-starved tidal flats to altered sediment\navailability across four major countries with extensive tidal flat areas and diverse\nsediment supply levels (i.e., China, Indonesia, Australia, and the United States).”\n3.2 Additionally, the lack of discussion around direct conversion is unfortunate. While\nmentioned as a source of uncertainty the scope of direct change vs indirect drivers can\nnot be analyzed with the current study. If similar patterns are not observed in the directly\nimpacted mudflats, it only strengthens the general conclusions of the research. I would\nsuggested including that analyzing at least in a supplemental.\nResponse:\nWe thank the reviewer for the insightful suggestions, and we agree that it strengthens\nour general conclusion if different patterns are observed on transects that are directly\nimpacted by conversion. Since most tidal flats with the direct conversion are completely\nlost, their changing pattern with the environmental (indirect) factors cannot be revealed.\nThus, in the current revision, we identified nine tidal flat transects where a part of the\ntidal flats was converted, and compared these transects to those without the impact of\ndirect conversion.\nThis additional analysis reveals that:\n1. The morphology evolution patterns of tidal flats with direct human impact differ\nfrom those of tidal flats without human impact.\n2. Tidal flats exhibit a tendency to recover through fast sedimentation after direct\nconversion by human activity.\n3. The rate of tidal flat recovery exceeds the rate of tidal flat evolution driven by\nnatural drivers.\nThese results underscore the important difference imposed by direct human conversion.\nTo make the above points clear, we added the following text in the Results (lines 260-264)\nand Methods section (lines 520-526), as:\n“In our analysis, we focus on understanding how tidal flats respond to external\ndisturbances, since losses due to direct human interventions (such as conversion to\nother land use) are generally less predictable. We identified 9 transects that are\nconverted at the beginning of our study period (e.g., 2002, see Method), and they are\nobserved to generally accumulate at fast rates regardless of the SSC level\n(Supplementary Fig. 11).”\n“To compare the effects of direct conversion and external drivers, we identified nine\ntransects that were converted at the beginning of our study period and have SSC change\ndata, so that we can track their development. The results show that eight out of nine\ntransects exhibited a seaward progradation trend after the conversion (Supplementary\nFig. 11). The rate of tidal flat width change exceeds the rate of tidal flat evolution driven\nby natural drivers, highlighting the important difference imposed by direct conversion\nand the necessity to exclude those transects in our study.”\nSupplementary Figure 11. Comparison between the impact of direct human conversion\nand SSC change. The contour map represents the tidal flat width change corresponding\nto different variation rates in SSC from DET-ESTMORF modeling. Bubbles represent\nthe observed data points for tidal flat width changes, with those exceeding the axis\nrange plotted on the boundary (denoted by asterisks). Red bubbles indicate tidal flat\nexpansion, while green bubbles represent tidal flat retreat. Bubbles with black outlines\ndenote sites that are partly converted to other land use. The size of the bubbles reflects\nthe variation rate, scaled proportionally smaller compared to Fig. 5a.\n3.3 Line 44. Framing with the global number but also mention what the rate of direct\nconversion is in China.\nResponse:\nWe find that direct human conversion along China's coast ranged from 240 to 400 km²\nannually between 1950 and 2010 (Ma et al., 2014). To make the above point clear, we\nadded text in line 44-47 as:\n“66% of the area losses were attributed to indirect drivers, rather than direct human\nimpact through conversion to other land uses8, although in some countries such\nconversion was conducted at large scales (e.g., 240 to 400 km² per year during 1950-2010 in China9).”\n3.4 Line 333. I suggest changing “reclamation” to “conversion.” reclamation suggests\nmudflats need to be reclaimed from the ocean and implies they are wastelands which is\ndirectly opposed to the narrative of the paper.\nResponse:\nWe thank the reviewer for the comment. We have changed “reclamation” to “conversion”\nin the revised manuscript.\nReferences:\nBarrot, G., Mangin, A., & Pinnock, S. (2007). Global Ocean Colour for Carbon Cycle\nResearch, Product User Guide. ACRI-ST, Sophia-Antipolis.\nBi, S., Yang, Y., Xu, C., Zhang, Y., Zhang, X., & Zhang, X. (2017). Distribution of\nheavy metals and environmental assessment of surface sediment of typical\nestuaries in eastern China. Marine Pollution Bulletin, 121(1), 357–366.\nhttps://doi.org/10.1016/j.marpolbul.2017.06.013\nChristoffersen, J. B., & Jonsson, I. G. (1985). Bed friction and dissipation in a combined\ncurrent and wave motion. Ocean Engineering, 12(5), 387–423.\nhttps://doi.org/10.1016/0029-8018(85)90002-2\nDethier, E. N., Renshaw, C. E., & Magilligan, F. J. (2022). Rapid changes to global\nriver suspended sediment flux by humans. Science, 376(6600), 1447–1452.\nhttps://doi.org/10.1126/science.abn7980\nFagherazzi, S., Carniello, L., D’Alpaos, L., & Defina, A. (2006). Critical bifurcation of\nshallow microtidal landforms in tidal flats and salt marshes. Proceedings of the\nNational Academy of Sciences, 103(22), 8337–8341.\nhttps://doi.org/10.1073/pnas.0508379103\nFriedrichs, C. T. (2011). 3.06 - Tidal Flat Morphodynamics: A Synthesis. In E. Wolanski\n& D. McLusky (Eds.), Treatise on Estuarine and Coastal Science (pp. 137–170).\nWaltham: Academic Press. https://doi.org/10.1016/B978-0-12-374711-\n2.00307-7\nGreen, M. O., & Coco, G. (2014). Review of wave-driven sediment resuspension and\ntransport in estuaries. Reviews of Geophysics, 52(1), 77–117.\nhttps://doi.org/10.1002/2013RG000437\nHou, X., Xie, D., Feng, L., Shen, F., & Nienhuis, J. H. (2024). Sustained increase in\nsuspended sediments near global river deltas over the past two decades. Nature\nCommunications, 15(1), 3319. https://doi.org/10.1038/s41467-024-47598-6\nHu, Z., Suzuki, T., Zitman, T., Uittewaal, W., & Stive, M. (2014). Laboratory study on\nwave dissipation by vegetation in combined current–wave flow. Coastal\nEngineering, 88, 131–142. https://doi.org/10.1016/j.coastaleng.2014.02.009\nHu, Z., Wang, Z. B., Zitman, T. J., Stive, M. J. F., & Bouma, T. J. (2015). Predicting\nlong-term and short-term tidal flat morphodynamics using a dynamic\nequilibrium theory. Journal of Geophysical Research: Earth Surface, 120(9),\n1803–1823. https://doi.org/10.1002/2015JF003486\nKirwan, M. L., Guntenspergen, G. R., D’Alpaos, A., Morris, J. T., Mudd, S. M., &\nTemmerman, S. (2010). Limits on the adaptability of coastal marshes to rising\nsea level. Geophysical Research Letters, 37(23).\nhttps://doi.org/10.1029/2010GL045489\nKirwan, M. L., Temmerman, S., Skeehan, E. E., Guntenspergen, G. R., & Fagherazzi,\nS. (2016). Overestimation of marsh vulnerability to sea level rise. Nature\nClimate Change, 6(3), 253–260. https://doi.org/10.1038/nclimate2909\nLadd, C. J. T., Duggan‐Edwards, M. F., Bouma, T. J., Pagès, J. F., & Skov, M. W. (2019).\nSediment Supply Explains Long‐Term and Large‐Scale Patterns in Salt Marsh\nLateral Expansion and Erosion. Geophysical Research Letters, 46(20), 11178–\n11187. https://doi.org/10.1029/2019GL083315\nMaan, D. C., van Prooijen, B. C., Wang, Z. B., & De Vriend, H. J. (2015). Do intertidal\nflats ever reach equilibrium? Journal of Geophysical Research: Earth Surface,\n120(11), 2406–2436. https://doi.org/10.1002/2014JF003311\nMurray, N. J., Phinn, S. R., DeWitt, M., Ferrari, R., Johnston, R., Lyons, M. B., et al.\n(2019). The global distribution and trajectory of tidal flats. Nature, 565(7738),\n222–225. https://doi.org/10.1038/s41586-018-0805-8\nMurray, N. J., Worthington, T. A., Bunting, P., Duce, S., Hagger, V., Lovelock, C. E., et\nal. (2022). High-resolution mapping of losses and gains of Earth’s tidal wetlands.\nScience, 376(6594), 744–749. https://doi.org/10.1126/science.abm9583\nRijn, V., & C, L. (2007). Unified View of Sediment Transport by Currents and Waves.\nI: Initiation of Motion, Bed Roughness, and Bed-Load Transport. Journal of\nHydraulic Engineering, 133(6), 649–667. https://doi.org/10.1061/(ASCE)0733-\n9429(2007)133:6(649)\nRoberts, W., Le Hir, P., & Whitehouse, R. J. S. (2000). Investigation using simple\nmathematical models of the effect of tidal currents and waves on the profile\nshape of intertidal mudflats. Continental Shelf Research, 20(10), 1079–1097.\nhttps://doi.org/10.1016/S0278-4343(00)00013-3\nSoulsby, R., Stive, M., de Vriend, H., Fredsoe, J., Hamm, L., Teisson, C., & Winterwerp,\nJ. (1995). Advances in coastal morphodynamics.\nWang, F., Sanders, C. J., Santos, I. R., Tang, J., Schuerch, M., Kirwan, M. L., et al.\n(2020). Global blue carbon accumulation in tidal wetlands increases with\nclimate change. National Science Review, 8(9), nwaa296.\nhttps://doi.org/10.1093/nsr/nwaa296"}, {"round": 3, "reviewer_comments": {"reviewer_1": "The study on the dynamics and drivers of tidal flat morphology is of great importance for understanding the evolution of coastal ecosystems and addressing environmental changes globally. This study by Liu et al. fills a significant knowledge gap regarding the large-scale morphological changes of tidal flats and provides valuable insights for coastal management. The findings on the non-linear responses of sediment-rich and sediment-starved tidal flats to sediment availability changes are novel and can contribute to the development of more effective management strategies. It also has practical implications for sediment allocation strategies, which can help in the conservation and restoration of tidal flat ecosystems. This is particularly relevant considering the global changes in sediment flux and the importance of tidal flats for various ecosystem services. I am satisfied with the authors’ response to my comments. Therefore, I recommend accepting this manuscript.\n(Remarks on code availability)", "reviewer_3": "The authors have addressed all of my questions and comments from previous rounds of review. There are a few minor grammatical errors in the new sections that should be addressed.\nMinor comment:\nLine 269 \"...these areas excluded...\" should be \"...these areas are excluded...\"\nLine 432 \"...possible effect tidal range on...\" should be \"...possible effect tidal range has on\"\n(Remarks on code availability)\nThe code appears complete and reproducible."}, "author_response": "“Dynamics and drivers of tidal flat morphology in China”\nShuai Liu, Zhan Hu, Tim J. Grandjean, Zheng B. Wang, Vincent T. M. van Zelst,\nLin Qi, Tianping Xu, Jun Young Seo, Tjeerd J. Bouma\nItemized List of Changes and Answers to the comments\n1. Response to Reviewer #1 (in blue):\n1.1. The study on the dynamics and drivers of tidal flat morphology is of great\nimportance for understanding the evolution of coastal ecosystems and addressing\nenvironmental changes globally. This study by Liu et al. fills a significant knowledge\ngap regarding the large-scale morphological changes of tidal flats and provides valuable\ninsights for coastal management. The findings on the non-linear responses of sediment-\nrich and sediment-starved tidal flats to sediment availability changes are novel and can\ncontribute to the development of more effective management strategies. It also has\npractical implications for sediment allocation strategies, which can help in the\nconservation and restoration of tidal flat ecosystems. This is particularly relevant\nconsidering the global changes in sediment flux and the importance of tidal flats for\nvarious ecosystem services. I am satisfied with the authors’ response to my comments.\nTherefore, I recommend accepting this manuscript.\nResponse:\nWe thank the reviewer for the constructive feedback and positive evaluation of our\nmanuscript.\n2. Response to Reviewer #3 (in blue):\n2.1. The authors have addressed all of my questions and comments from previous\nrounds of review. There are a few minor grammatical errors in the new sections that\nshould be addressed.\nResponse:\nWe thank the reviewer for the positive feedback. We have carefully proofread the\nmanuscript to correct the minor grammar errors. The revised version has been updated\naccordingly.\nMinor comment:\n2.2. Line 269 \"...these areas excluded...\" should be \"...these areas are excluded...\"\nResponse:\nWe thank the reviewer for the comment. We have made the corresponding revision as\nsuggested.\n2.3. Line 432 \"...possible effect tidal range on...\" should be \"...possible effect tidal range\nhas on\"\nResponse:\nWe thank the reviewer for the comment. We have made the corresponding revision as\nsuggested.\n2.4 The code appears complete and reproducible.\nResponse:\nWe appreciate the reviewer's confirmation that the code is complete and reproducible."}]

Decision letter