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Article

Quantitative Assessment of the Impact of Port Construction on the Surrounding Mudflat Topography Based on Remote Sensing—A Case Study of Binhai Port in Jiangsu Province

by
Binbin Chen
1,
Zhengdong Chen
1,
Chuping Song
1,
Xiaodong Pang
1,
Peixun Liu
2 and
Yanyan Kang
3,*
1
College of Information Engineering, Nanjing Polytechnic Institute, Nanjing 210048, China
2
Jiangxi Academy of Emergency Management Science, Nanchang 330199, China
3
College of Oceanography, Hohai University, Nanjing 210098, China
*
Author to whom correspondence should be addressed.
J. Mar. Sci. Eng. 2024, 12(12), 2290; https://doi.org/10.3390/jmse12122290
Submission received: 29 October 2024 / Revised: 26 November 2024 / Accepted: 10 December 2024 / Published: 12 December 2024
(This article belongs to the Special Issue Coastal Hydrodynamic and Morphodynamic Processes)
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Abstract

:
Activities, particularly harbor construction, often exert significant and non-negligible impacts on coastal environments. Therefore, it is of great practical importance to quantitatively assess the effects of such construction on the surrounding topography, such as tidal flats. This study focuses on the coast of Jiangsu Binhai Harbor. Using multi-source and multi-temporal remote sensing images, digital elevation models of tidal flats surrounding Binhai Harbor were generated for the years 2013, 2015, and 2017 through the waterline method. A quantitative analysis was conducted utilizing GIS spatial analysis techniques to examine erosion–deposition patterns, contour changes, and typical cross-sectional comparisons. The findings reveal that, although the overall coastline is in a state of erosion, the localized impacts of harbor construction are evident. Between 2013 and 2017, the northern tidal flats experienced overall erosion, whereas deposition occurred near the harbor’s root areas. Compared to 2013–2015, there was a significant decrease in erosion between 2015 and 2017, indicating that the construction of the project had a significant impact on the northern tidal flats. Throughout the five-year study period, the tidal flats within the breakwater underwent continuous adjustment, shifting from being close to the shoreline to being concentrated on both sides of the breakwater. Significant siltation was observed on the inner side of the breakwater at Binhai Harbor between 2015 and 2017, with an increase of 0.86 km2 in the area above −2 m. This study demonstrates that remote sensing technology is highly effective in monitoring changes in coastal topography, especially under the influence of human activities.

1. Introduction

The coastal zone, with its abundant natural resources and advantageous geographical location, has become a key area for international competition and development. It also represents the frontier of sea–land interaction, and its geomorphological evolution has attracted significant attention in light of global warming, sea-level rise, and intensified human activities [1,2,3]. The positive impact of the port economy on the development of coastal cities is very great, which can promote the development of the local economy, improve the competitiveness of the city, drive employment and population mobility, and improve the level of local infrastructure, etc., such as in the Shanghai Port, Chattogram Port [4], and so on. The rapid urbanization of coastal areas and the continued depletion of natural resources mean that ports can no longer be developed without considering environmental issues [5]. Iwasaki (2022) focused on changes in coastal topography due to harbor construction in Ishikari Bay, Japan, and the effects on coastal forest growth [6]. Foti (2023) analyzed shoreline changes due to port construction in Calabria, Italy, and showed that strong anthropogenic (port construction) pressures altered not only the geomorphology but also the coastal dynamics, and that severe shoreline erosion processes are often observed even at considerable distances from the port [7]. Rodríguez (2021) analyzed the coastal changes between the harbors of Castellón and Sagunto from 1956 until the present day and noted that harbors and troughs can cause significant changes in littoral depositional patterns, which can result in a significant accumulation of material upstream of the barrier and a significant loss of material downstream of the trough [8]. Qu (2024) focused on the geomorphological processes around the artificial island of Yangkou Harbor, Jiangsu, China, and noted that, at present, the sandbanks around the island are still in the process of dynamic evolution after the construction of the project and the local scouring around the island has not yet reached equilibrium. Meanwhile, the lack of long-term continuous monitoring during the harbor construction process has hindered the systematic study of these geomorphic processes [9]. Human activities, especially the construction of flood control facilities or reclamation projects, not only directly alter the local marine hydrodynamic environment but also may affect the long-term evolution of the tidal flat system by altering sediment holding space and migration patterns [10]. In the case of Binhai Harbor, Jiangsu, China, the continuous construction of yards and wharves has led to constant changes in coastal topography. Such geomorphological evolution also impacts harbor operations, including the siltation of channels and the scouring and erosion of piers [11]. Monitoring topographic changes in the surrounding tidal flats, particularly before and after construction activities, is crucial for the scientific management and ecological restoration of coastal zones [12].
Field surveys are the most direct and accurate means of studying coastal evolution; however, field conditions are often harsh, and the costs in terms of manpower and material resources are extremely high, particularly in tidal flat areas. These surveys are typically used to obtain short-term, accessible, and small-scale localized coastal geomorphological information [13], which is insufficient to fully capture the spatial and temporal variability of macro-geomorphological evolution [14]. Remote sensing monitoring of tidal flat topography has been well established. Conventional techniques such as ground-based and airborne (e.g., Light Laser Detection and Ranging (LiDAR)) surveys can provide accurate elevation measurements [15], but they are relatively expensive to produce and costly for long-term, continuous monitoring. The satellite-based InSAR technique generates a digital elevation model (DEM) in the intertidal region based on acquired images at low tide, but for multi-channel interferometric measurements, the time lag between two acquisitions at different angles is still the limiting issue [16]. Satellite LiDAR altimetry (e.g., ICESat-2) can be used to derive topographic profiles along the altimeter ground track [17], but its ground track coverage is not dense enough to generate a gridded DEM. Element-based inversion methods mostly utilize the optical image reflectivity or SAR image backscattered cross-sections to model the relationship with the beach surface elevation, then realize the inversion of tidal flat topography [18], but this type of method is susceptible to the influence of the surrounding hydrodynamic environment, and it is difficult to promote. The basic principle of the waterline method is to use the “waterline” as an altimeter to measure the tidal flats [19] and combine it with the instantaneous sea surface height to obtain the tidal flat elevation information. Currently, the waterline method is the most operable method for tidal flat topographic monitoring, with the advantages of rich image resources, high monitoring frequency, strong environmental adaptability, low cost, and support for historical topographic construction, and is widely used around the world [20,21,22,23,24,25,26]. However, the monitoring of tidal flats changes at the engineering scale puts higher demands on both timeliness and accuracy [12]. Most previous studies have primarily focused on the construction of high-precision DEMs for mudflats, while the analysis of mudflat topographic evolution has been insufficient [23].
The quantitative assessment of changes in the topography of mudflats, which exhibit a faceted distribution, is an important component of the environmental impacts of port development. However, due to the lack of large-area measured topographic data, systematic geomorphologic evolution research on the need for deep excavation is limited [27,28]. The purpose of this study is to analyze the topographic evolution of tidal flats under the influence of harbor construction, using remote sensing techniques. Tidal flats surrounding Binhai Harbor have been selected as the study area, and DEMs for different time periods will be constructed based on multi-source and multi-temporal remote sensing images using the waterline method. Sequential DEMs will be used to analyze erosion and deposition patterns, contour changes, and typical section changes through GIS spatial analysis tools. The results will provide a detailed account of the timing and extent of the impact of harbor construction activities on the mudflats. This study will offer valuable insights into the sustainable management and conservation of mudflats in the future.

2. Study Area and Dataset

2.1. Study Area

Binhai Harbor is located on the western coast of the Yellow Sea, in the most prominent section of Jiangsu’s eastern shoreline, at geographic coordinates 34°18′ N latitude and 120°16′37″ E longitude, across the sea from Japan and South Korea. Deep water approaches close to the shore, with the −15 m isobath located only 3.95 km offshore. Binhai Harbor offers ideal conditions for 10–15 million ton-class wharfs, making it the best-invested deep-water port in the province.
Tidal flats extend along both the northern and southern sides of Binhai Harbor, with those on the north side (between Binhai Harbor and Zhongshan Estuary) spanning 1–2 km in width. Fewer tidal flats are found on the southern side, with only remnants in areas such as Eran and Moon Bay. The construction of the harbor breakwaters was completed in 2011, resulting in the development of tidal flats inside the harbor. The construction of facilities, including internal and external yards at Binhai Harbor, continued from 2013 to 2017. The engineering activities, when superimposed onto the macro-hydrodynamic environment, have collectively impacted the surrounding mudflats and shoreline [29].
The study area is situated in the Abandoned Yellow River delta, which formed due to the accumulation of large quantities of sediment carried by the Yellow River from 1128 to 1855, when it flowed into the Yellow Sea (Figure 1). Since the Yellow River’s diversion in 1855, the Yellow River delta has lost a total of 1400 km2 of land, with the eroded sediments predominantly transported southward along the shoreline [30]. The study area is primarily influenced by rotating tidal waves in the South Yellow Sea, with a no-tide point located at 34°30′ N, 121°10′ E, 80 km east of the mouth of the Abandoned Yellow River [31], and along the coast of northern Jiangsu, most tides are irregular semidiurnal, except for irregular diurnal tides near the no-tide point. The tidal range is generally around 3 m [32]. The duration of the rising tide in the nearshore area is shorter than that of the falling tide, forming a generally reciprocal flow, with the rising tide flowing in the SSE direction and the falling tide in the NNW direction [33]. The surface sediments are fine, with an average grain size of 5–10 μm. Coastal mudflats in Jiangsu Province are mainly influenced by sediment recharge from the Yangtze River and the abandoned Yellow River. Sediment core samples [34] showed that on a century scale, 73.91% of the sediments in Sheyang (south side of the study area) were from the abandoned Yellow River source, and 26.09% were from the Yangtze River source and part of these minor rivers.

2.2. Dataset

With the development of remote sensing satellites and technology, data availability has surged since the 2010s, providing a sufficient number of images under different tidal conditions for the waterline method [23]. To construct the tidal flats topography in the study area, optical images (Figure 2) with medium spatial resolutions of 10–30 m were selected after comprehensive consideration of factors such as single-scene coverage area, temporal and spatial resolution coordination, and cost. These include Landsat-8 from the USGS, USA, and the Chinese High-resolution Earth Observation Satellite series (GF-1). In addition, we selected a small number of images from other sources, such as the Chinese Earth observation satellite for environment and disaster monitoring (HJ-1) and the China–Brazil Earth Resources Satellite (CBERS). Taking 2013, 2015, and 2017 as time nodes, remote sensing images within those years were collected. To ensure comparability of the DEMs, we selected six remotely sensed images each year, evenly distributed across different tidal conditions. The remote sensing images were pre-processed through band composition, stripe removal, image enhancement, and geometric correction. The accuracy of geometric correction was controlled within one pixel. The datum WGS_1984_UTM_Zone_51N was selected for all image coordinate systems. Tide level data were obtained from the Binhai Harbor tide level station using the China National Elevation Datum 1985 (CNHD 1985), as shown in Table 1.

3. Methods

3.1. The Waterline Method

As an intertidal area with frequent interaction between land and sea, tidal flats are subject to the influence of tides, experiencing periodic inundation and exposure. With the rise and fall of the tide, the land–sea boundary changes constantly, and the land–sea intersection line traverses the entire tidal flat during each tidal cycle [24]. The waterline records the tide-related attributes of the tidal flats at the synchronized moment, i.e., the tide level at each point on the waterline matches the elevation of the tidal flat at that moment [25]. Thus, the waterline can be considered as a natural altimeter for measuring tidal flat elevations [11]. Remote sensing images at different moments in multiple periods provide a collection of waterlines at different tidal conditions, which, when synchronized with corresponding tide levels, are used to construct a digital elevation model of the tidal flats.
Referring to the literature [10], the waterline method is divided into three main steps: (1) extraction of waterlines: pre-processed remote sensing images are used, and the sea–land boundary is extracted through automated image processing techniques; (2) waterline assignment: interpolating tide level data to match the time of waterline extraction, and assigning elevations to the different waterlines; and (3) DEM construction: utilizing the pre-assigned waterline data, an appropriate spatial interpolation technique is employed to construct a digital elevation model of the tidal flat area.

3.1.1. Waterline Extraction from Remote Sensing Images

In this study, the remote sensing waterline extraction method is adopted, which involves automatic extraction as the first step, followed by manual post-processing. The object-oriented spatial feature extraction module—Feature Extraction (FX) of ENVI 5.3 software—is used for automatic waterline extraction [35]. FX segments the image based on adjacent pixel brightness, texture, and color. It utilizes an edge-based segmentation algorithm, which efficiently generates multi-scale segmentation results with a single input parameter. Controlling boundary differences across scales produces a multi-scale segmentation, ranging from fine to coarse. A high-scale image segmentation produces fewer patches, while a low-scale segmentation results in more patches. The segmentation effect determines the accuracy of classification, and the segmentation can be previewed to select an ideal threshold for optimal edge feature extraction. The specific parameters are set as follows: the segmentation algorithm selects “Edge,” with a threshold of 40; the merging algorithm selects the “Full Lambda Schedule” module to merge large block regions with strong texture, with a threshold of 90. The Texture Kernel Size is set to 10. Since the features in the tidal flats are simple, we skipped the subsequent refinement classification and directly outputted the vector, which yielded satisfactory results. Additionally, due to the presence of numerous narrow tidal channels on the tidal flats, line breakages often occur during the extraction process. Therefore, appropriate post-processing manual editing is required to minimize this issue. The final extraction results are shown in Figure 3.

3.1.2. Elevation Assignment and DEM Construction

In this study, elevation assignment of the waterline was achieved through time interpolation using tide data from nearby stations. Since the measured tide level data are provided at hourly intervals, while remote sensing image acquisition is accurate to the minute, a simple linear interpolation method was employed to calculate the tide level at the moment of image acquisition (which corresponds to the moment of waterline acquisition). Because of the limited extent of the study area, the tide level value was assumed to represent the elevation of the corresponding waterline.
The ANUDEM (Thin Plate Spline Interpolation) algorithm calculates the interpolation by identifying topographic features (depressions, saddles) in the elevation data and topographic features (ridges, gullies) implicit in the elevation points and contours and by applying streams (gradient turning lines), adding a set of ordered topographic features to the algorithm (Simple Ordered Chain Constraints) constraints. Calculating the interpolation means that surface geomorphic features (especially those subject to erosion by flowing water) can be accurately and realistically represented on the fitted surface. The tidal flats are mostly flat, but there are eroded tidal creeks present, and the DEM must adequately capture these geomorphological features. Therefore, in this study, the series of waterlines were first converted into point sets, and the ANUDEM (thin-plate spline interpolation) algorithm was used to perform spatial interpolation [36]. The waterline point sets were input into the Topo to Raster module (the ANUDEM algorithm in ArcGIS 10.5 software) as point elevation data. Through extensive testing, the following parameters were chosen: the maximum number of superpositions was set to 45, the roughness coefficient to 0.5, and the raster size to 50 m.

3.2. Quantitative Analysis of Geomorphologic Evolution

Based on the sequence DEMs obtained through the waterline method, three aspects were analyzed using the ArcGIS spatial analysis tool: the distribution of erosion–deposition, contour changes, and the comparison of typical cross sections.
The erosion–deposition distribution map illustrates the magnitude of topographic changes across different patches over various periods and is a crucial element in geo-morphic evolution analysis. In this study, the raster calculator tool in ArcGIS 10.5 software [37] was used to obtain the erosion–deposition distribution map by subtracting corresponding image elements from DEMs across different periods.
The comparison of the planimetric position of contour lines serves as the primary indicator for characterizing elevation changes in the area. The magnitude of contour shifts indicates the extent of geomorphic changes across different tidal flat zones (high, medium, and low tide flats). In this study, different contours were extracted using the contour extraction tool within the ArcGIS surface analysis module.
Delineating typical sections for areas of special interest and examining elevation change curves over time are essential for understanding geomorphic evolution. The 3D analysis module in ArcGIS was used to generate elevation change curves for the profiles.

4. Results

4.1. DEMs of Tidal Flats

Based on the waterline method, these digital elevation models of tidal flats around Binhai Harbor were constructed for the years 2013, 2015, and 2017, and the results are shown in Figure 4. To facilitate comparison, the elevation range selected for this study was between −1 m and 2 m. Overall, the coast exhibits a gradual decrease in elevation from land to sea, with the high beach being steeper than the low beach.
Based on regional differences, the northern, internal, and southern parts of the coastal harbor were analyzed in detail. Three aspects were examined: surface erosion–deposition distribution, contour changes, and the comparison of typical sections. Coastal harbor construction progressed from 2013 to 2017, with breakwaters built within the harbor from 2013 to 2015, and a new yard constructed north of the existing harbor from 2015 to 2017.

4.2. Geomorphologic Evolution of Exposed Tidal Flat

4.2.1. Erosion–Deposition Distribution

According to the three-phase digital elevation model (2013, 2015, 2017), erosion and deposition distribution maps were obtained by subtracting the corresponding image elements (Figure 5). (1) Tidal flats north of Binhai Harbor: In 2015, compared to 2013 (Figure 5a), the northern shoreline experienced overall erosion, with a mean value of −0.2 m. However, siltation occurred near the shoreline’s root, close to the coastal harbor (indicated by the arrow). By 2017 (Figure 5b), the northern terminal yard was established, which significantly impacted the overall shoreline. The northern shore erosion was mitigated by the project, and compared to the macro erosion trend observed in previous years, there was a balance between erosion and deposition, with the mean value reduced to −0.05 m. Meanwhile, siltation occurred at the root of the northern shore in the newly constructed yard area (indicated by arrows). (2) Tidal flats inside the two breakwaters: Significant deposition occurred within both breakwaters between 2013 and 2017. The maximum depositional thickness exceeded 0.5 m, and the tidal flats underwent significant changes in extent due to the internal construction. (3) Tidal flats south of Binhai Harbor: The tidal flats in this region covered a smaller area. The Eran area experienced significant erosion between 2013 and 2015, with the offshore tidal flats in this region eroding away entirely by 2017. The southern portion was not significantly affected by the project. The Moon Bay area exhibited minimal overall change, and the tidal flat area remained small.

4.2.2. Changes in the North Coast

(1) Contour changes
The 0 m, −1 m, and −2 m contours were extracted from the three-phase digital elevation model (DEM), and their planar changes were analyzed through overlay. The results are shown in Figure 6. Overall, the contour lines tend to move toward the shore, indicating that the bank is generally undergoing erosion.
Between 2013 and 2017, the 0 m contour showed an overall landward movement, particularly in zones a and b, which were in an erosive state. By 2015, relative to 2013, the 0 m contour shifted seaward near the root of the yard in zone c, where siltation occurred. By 2017, relative to 2015, the 0 m contour continued to gradually move toward the shore, with minimal changes in magnitude compared to the preceding two years. Nonetheless, siltation was observed in zone c, near the root of the new yard. Similar to the 0 m contour, the −1 m contour also showed an overall shoreward movement, with the northern coastline experiencing erosion. Greater changes were observed between zones a and b, while little change occurred between zones b and c. Zone c showed slight siltation around the yard. Compared to 2013–2015, the shoreward movement of the −1 m contour decreased between 2015 and 2017, with seaward movement observed in some areas (between zones a and b, and on both sides of the breakwaters in zone c), indicating that the construction of the project (indicated by the arrows) significantly impacted the northern shoreline. The trends of the −2 m and −1 m contours were more consistent, with zones a, b, and c generally moving closer to shore. The rate of shoreward movement varied across different periods, and after the completion of the yard and landfill construction in 2017, the extent of landward movement of the −2 m contour significantly decreased, and erosion slowed. For example, in area c, shoreward movement was approximately 150 m from 2013 to 2015, and about 80 m from 2015 to 2017, reflecting a decrease in the erosion rate.
(2) Elevation changes in typical cross-sections
Four typical sections were set up on the tidal flats in the northern part of Binhai Harbor, where elevation changes from 2013 to 2017 were analyzed (Figure 7).
Section 1 is located outside the mouth of the Zhongshan River, where the tidal flats experienced erosion, showing significant scouring in 2015 compared to 2013, with a maximum scouring depth of 0.58 m. Little change was observed between 2017 and 2015, with both erosion and deposition occurring, and a maximum deposition of 0.22 m on the seaward side.
Section 2 is located in the central area, where erosion occurred between 2013 and 2015. The following two years (2015–2017) showed no significant elevation changes.
Sections 3 and 4 are located near Binhai Harbor. Section 3, like Sections 1 and 2, remained in an erosive state. However, the overall erosion was interrupted by the completion of the dam at the landfill, with minimal elevation changes observed between 2015 and 2017, accompanied by both erosion and deposition. Section 4 was affected by the polder works on both sides, with a maximum deposition of 0.3 m in 2017 compared to 2015, and the deposition was primarily concentrated near the root of the dyke.

4.2.3. Changes in Tidal Flats Inside These Breakwaters

The north and south breakwaters of Binhai Harbor were completed in 2011, and this study examines the changes in the internal beach during the periods of 2013, 2015, and 2017. Since the internal mudflats exhibited different distribution ranges at various times, a comprehensive point-to-point erosion and deposition analysis was not conducted. Instead, the focus was on analyzing the distribution and changes of the 0 m, −1 m, and −2 m contour lines. The results of the three-period DEMs and the distribution of mudflats under different contours are shown in the following figure.
As shown in Figure 8 and Table 2, the range of mudflat deposition within the breakwater has continuously shifted over the past five years, shifting from a distribution close to the shore in 2013 to a concentration on both sides of the breakwater in 2015 and 2017. Compared to 2013, the total beach area (above −2 m) showed minimal change in 2015, except for significant alteration of the beach area, which was related to engineering dredging and channel dredging activities during this period. In 2017, compared to 2015, the mudflat distribution remained stable on both sides of the breakwater, but significant siltation occurred, increasing the area of mudflats within each contour. The overall area above −2 m increased by 0.86 km2, which warrants further attention.

4.2.4. Changes in the South Coast

The entire area south of Binhai Harbor to the mouth of the abandoned Yellow River is in an eroded state. Based on the three-phase DEMs (Figure 9a), the tidal flats on the south side of Marina Harbor are primarily distributed in two regions: Eran and Moon Bay.
The area of tidal flats at Eran gradually decreased over the years 2013, 2015, and 2017. Only the area above −2 m is considered, which measured approximately 0.6 km2 in 2013, 0.4 km2 in 2015, and 0.1 km2 in 2017. As shown in Figure 9b, with respect to the movement of the −2 m contour line, between 2013 and 2015, the −2 m contour shifted shoreward by up to 150 m. From 2015 to 2017, it shifted shoreward by a maximum of 110 m, with the rate of erosion decreasing; however, by the post-2017 period, the tidal flats were nearly eroded.
The tidal flats at Moon Bay are mainly influenced by the outer seaward guiding dyke. As shown in Figure 9c, the area above −2 m remained at approximately 0.3 km2 over the past five years, with little change. Inside the circular guiding dyke, internal sediment accumulation led to the gradual exposure of tidal flats, resulting in 0.3 km2 of exposed area above −2 m by 2017 compared to previous years.

5. Discussion

5.1. Causes and Future Trends in Tidal Flat Geomorphology

The causes of coastal erosion in the study area are quite complex, ranging from macroscopic historical backgrounds to mesoscale changes in sediment dynamics and small-scale engineering influences.
Regarding the macro-historical context, in 1128, the ancient Yellow River diverted into the Huaihe River and discharged into the sea, bringing a large amount of sediment and causing the coastline to advance seaward [38]. In 1855, the Yellow River shifted back to its northern course, reducing the sediment supply, leading to coastline retreat, and placing the coast in an erosional state. The retreating shoreline at the apex of the delta has receded by more than 20 km (Figure 10), and large portions of the underwater deltas, such as Wujisha and Dasha, were eroded, flattened, and eventually transformed into deep-water areas with depths of 12 to 14 m [39]. For the Jiangsu coast, these two significant shifts in sediment conditions, occurring in completely opposite directions, represent important macro-historical factors affecting both sides of the Yellow River’s mouth (the study area). The overall sediment transport trend has remained unchanged for over 160 years and is expected to persist for the foreseeable future [33]. Therefore, seabed erosion off the Abandoned Yellow River Estuary is likely to continue. In addition, the sharp decrease in sediment in the southern Yangtze River estuary has left the Jiangsu coast with even less sediment recharge, thus increasing erosion [40].
On the mesoscale, the converging tidal wave system off the Jiangsu shoreline is an inevitable result of oceanic tidal wave propagation under the unique boundary formed by the Korean Peninsula, Shandong Peninsula, and Jiangsu shoreline [41]. Coupled with the large-scale reclamation of the Yancheng section of the Jiangsu coast and the gradual flattening of the shoreline, significant changes in the shoreline and submerged topography have substantial local effects on tidal wave propagation [42]. Several modeling studies [43,44] have demonstrated that hydrodynamic forces have intensified as the shoreline has receded and the underwater delta has flattened, resulting in an inevitable increase in erosion. At the same time, wave dissipation and coastal protection projects, including compliant sea ponds, pile-type offshore submerged dykes, and ding dams, have been constructed along the abandoned Yellow River delta to mitigate further shoreline retreat [45]. According to model predictions, the mudflat system along the central coast of Jiangsu is expected to reach its growth limit around 2065 [46]. Current investigations indicate that the offshore tidal flats have already been lost within nearly 50 years along the line from Binhai Harbor to the mouth of the Biandan River, as shown in Figure 10b. Erosion in the study area is extending from the north to the south, which is consistent with changes in sediment supply patterns. Therefore, the area is expected to face extensive erosion soon.
On the microscopic scale, the continuous construction of coastal ports has altered the local shoreline and water depth of the wharf channel, resulting in changes in current fields, sediment transport, and submarine topography near the project area. The impact increases in proximity to the project area. According to previous numerical modeling results, the harbor breakwater project does not alter the direction of sediment transport but significantly affects net suspended sediment transport [47,48]. Breakwaters and landfills intercept sediment transport from north to south, resulting in reduced net sediment transport on the south side of the breakwater. This phenomenon is common in protruding ports around the world, such as the three major breakwaters in Thailand (Cha Am jetty, Krai jetty, and Na Saton jetty) [49], which protrude into the surf zone and completely intercept sediment transport along the coast, resulting in siltation of sediments on one side. In the case of Binhai port, the sediment content increased in the sea area close to the northern side of the breakwater and decreased in the southern sea area away from the breakwater.
In the shore section north of the project, the breakwater and landfill intercept sediment transport from north to south, resulting in decreased net sediment transport on the south side of the breakwater. Meanwhile, sediment content increases in the sea area close to the north side of the breakwater, while sediment content decreases in the southern sea area farther from the breakwater. The area of exposed tidal flats increases on both sides of the breakwater due to reduced flow velocities, siltation, and increasing topography inside the embracing breakwater. The topographic changes in the tidal flats of Binhai Harbor from 2013 to 2017 were influenced by the broader erosional background, while localized sediment deposition was primarily driven by engineering construction. Notably, the topography gradually adapts to the influence of engineering over time and eventually stabilizes. As shown in Figure 10b, the rate of tidal flats reduction on the north side of the coastal harbor is significantly smaller than on the south side, and there is still a 1–2 km wide tidal flats distribution, which is correlated with the construction of the coastal harbor.

5.2. Limitations for the Geomorphic Evolutionary Analysis of the Tidal Flats

The limitations of this study are mainly reflected in two aspects. First, the reliance on data from only three periods, 2013, 2015, and 2017, for analyzing terrain evolution means that the study covers only a targeted five-year period without accounting for subsequent changes. This limitation could be addressed by extending the time span and increasing the frequency of data collection in future studies. Secondly, the waterline method in our study still has some room for improvement. Short-term morphological changes in intertidal mudflats are not always negligible. In this study, we assumed that topographic changes were negligible during the acquisition of a series of remote sensing data. However, in the intertidal area, field measurements during the tidal cycle revealed that the mean sediment concentration in the flood tide was greater than that in the ebb tide: in fact, the mean sediment volume per unit width in either the flood or ebb tide exceeded 1 kg [50]. This difference between flood and ebb tides can cause changes in morphodynamics over a month period. This will have important implications for the construction of DEMs. Therefore, methods for acquiring instantaneous (true) tidal flat elevation should be an important topic of discussion for future research, such as SWOT (InSAR) [51] and UAV + LiDAR [52] techniques. UAV photogrammetry can produce orthophotos and digital models with the highest spatial resolution (1.25 cm/pixel), but at the cost of large file sizes and long processing times, and is, therefore, only applicable to small areas. On the other hand, UAV-LiDAR has proved to be a promising tool for coastal studies, providing high-resolution orthophoto maps (2.7 cm/pixel) and high-precision digital elevation models from lighter datasets with a shorter processing time, which is advantageous for elevation monitoring in small areas [53]. Similar to this study, the harbor area is large in scope and requires multiple flights to complete. In addition, the use of UAVs during the construction of the harbor is small and not yet on a large scale; therefore, in support of the historical terrain construction of this method, the advantage of the waterline method is obvious.
The remote sensing images for the waterline should ideally be captured within a shorter time frame (e.g., three months). However, the one-year time span in this study is primarily due to the limited availability of clear remote sensing images of the sea area, which was influenced by weather conditions. In addition, this study did not conduct a quantitative prediction of future tidal flat topographic evolution trends. A hydrodynamic model will be introduced in future research to address this aspect and provide deeper insights.

6. Conclusions

The remote sensing waterline method provides powerful technical support for studying tidal flat evolution due to its high efficiency, speed, large coverage, and ability to reconstruct historical terrain. In this study, Binhai Harbor and the surrounding tidal flats were selected as the study area, and the DEMs of different years (2013, 2015, and 2017) were obtained using the waterline method. By comparing the DEMs from various years, it is possible to clearly observe the topographic changes, resource distribution, and siltation patterns of the tidal flats. The results show that the northern coast of Binhai Harbor has experienced reduced topographic erosion following the construction of the project, with sediment deposition occurring at the root of the project. The tidal flats inside the two breakwaters of Binhai Harbor show significant deposition, with the deposited areas concentrated in the inner strips of the breakwaters. Meanwhile, the tidal flats in the southern part of Binhai Harbor have nearly disappeared in recent years, and the other coastlines are approaching the dykes, except for the sediment accumulation inside Moon Bay. The findings of this study enhance understanding of the impacts of the Binhai Harbor project on the surrounding tidal flats and provide a scientific basis for local environmental protection, resource utilization, and planning. The waterline method has the advantages of a large measuring area, low cost, support for historical terrain construction, and the ability to monitor inter-annual changes, making it suitable for long-term coastal evolution analysis and engineering impact assessment. This study also serves as a valuable reference for understanding beach evolution in other coastal areas, contributing to the promotion of sustainable coastal development.

Author Contributions

Conceptualization, B.C. and Y.K.; methodology, B.C.; software, C.S. and X.P.; validation, B.C. and P.L.; formal analysis, Z.C.; investigation, B.C. and Z.C.; resources, Y.K.; data curation, B.C.; writing—original draft preparation, B.C. and Z.C.; writing—review and editing, X.P. and P.L. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by ‘Accurate Extraction Research and Product Realization of Water Information About Impervious Surface from High-resolution Images’ (Grant No. NJPI-RC-2023-06) and ‘Jiangsu Province Vocational Education Teaching Reform Key Project Funding’ (Grant No. ZZZ18) and ‘Jiangsu Province Vocational Education Teaching; the Jiangsu Transportation Technology Project’ (Grant No. 2017ZX01).

Data Availability Statement

The data presented in this research are available upon request from the corresponding authors.

Acknowledgments

The authors are grateful to the China Center for Resource Satellite Data and Applications (CRESDA) for supplying all the HJ-1 CCD and GF-1 images. Thanks to the United States Geological Survey (USGS) for providing Landsat images.

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. Study area and distribution of tidal flats around the Binhai harbor.
Figure 1. Study area and distribution of tidal flats around the Binhai harbor.
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Figure 2. Remote sensing images in this study (false color composite image).
Figure 2. Remote sensing images in this study (false color composite image).
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Figure 3. Waterlines in different tide conditions (a) in low tide; (b) in middle tide; (c) in high tide.
Figure 3. Waterlines in different tide conditions (a) in low tide; (b) in middle tide; (c) in high tide.
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Figure 4. (a) waterlines and DEM in 2013; (b) waterlines and DEM in 2015; (c) waterlines and DEM in 2017.
Figure 4. (a) waterlines and DEM in 2013; (b) waterlines and DEM in 2015; (c) waterlines and DEM in 2017.
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Figure 5. Maps of erosion−deposition distribution at different periods of time (a) 2015−2013; (b) 2017–2015.
Figure 5. Maps of erosion−deposition distribution at different periods of time (a) 2015−2013; (b) 2017–2015.
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Figure 6. Comparison of different contour lines (a) 0 m; (b) −1 m; (c) −2 m.
Figure 6. Comparison of different contour lines (a) 0 m; (b) −1 m; (c) −2 m.
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Figure 7. Elevation comparison curves for different sections.
Figure 7. Elevation comparison curves for different sections.
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Figure 8. Comparison of different DEM and tidal flats area; (a) 2013DEM; (b) 2015DEM; (c) 2017DEM; (d) tidal flats area in 2013; (e) tidal flats area in 2015; (f) tidal flats area in 2017.
Figure 8. Comparison of different DEM and tidal flats area; (a) 2013DEM; (b) 2015DEM; (c) 2017DEM; (d) tidal flats area in 2013; (e) tidal flats area in 2015; (f) tidal flats area in 2017.
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Figure 9. Comparison of different DEM and contour lines (a) 2013, 2015, and 2017 DEM; (b) −2 m contours in Eran; (c) −2 m contours in Moon Bay.
Figure 9. Comparison of different DEM and contour lines (a) 2013, 2015, and 2017 DEM; (b) −2 m contours in Eran; (c) −2 m contours in Moon Bay.
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Figure 10. Remote sensing images and historical shoreline conditions on both sides of the abandoned Yellow River estuary: (a) historical shorelines and underwater delta; (b) comparison of the distribution of mudflats (at maximum low tide).
Figure 10. Remote sensing images and historical shoreline conditions on both sides of the abandoned Yellow River estuary: (a) historical shorelines and underwater delta; (b) comparison of the distribution of mudflats (at maximum low tide).
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Table 1. Satellite images of Binhai Harbor under different tidal conditions.
Table 1. Satellite images of Binhai Harbor under different tidal conditions.
YearSatellitesDateTimeTide Level/m
(Tide Station)
2017Landsat82017/11/2610:361.11
CB2017/04/2810:53−0.02
GF-12017/04/1211:15−0.59
Landsat82017/02/1110:36−1.29
CB2018/01/1310:47−1.64
Landsat82018/01/2910:36−1.91
2015Landsat82015/03/2610:361.15
Landsat82015/03/1010:360.16
Landsat82015/10/1210:36−0.77
Landsat82015/06/1410:35−1.2
Landsat82015/05/1310:35−1.65
GF-12015/01/1711:02−2.07
2013Landsat82013/11/0710:321.13
Landsat82013/07/1010:380.31
GF-12013/09/0311:15−0.51
Landsat82013/05/2310:38−1.02
Landsat82013/12/0110:38−1.48
HJ-12013/04/0710:21−2.00
Table 2. Tidal flats distribution area in different contours.
Table 2. Tidal flats distribution area in different contours.
YearTotal Above −2 m−2 m~−1 m−1 m~0 mTotal Above 0 m
20131.721.030.540.15
20151.691.310.310.07
20172.551.700.640.21
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Chen, B.; Chen, Z.; Song, C.; Pang, X.; Liu, P.; Kang, Y. Quantitative Assessment of the Impact of Port Construction on the Surrounding Mudflat Topography Based on Remote Sensing—A Case Study of Binhai Port in Jiangsu Province. J. Mar. Sci. Eng. 2024, 12, 2290. https://doi.org/10.3390/jmse12122290

AMA Style

Chen B, Chen Z, Song C, Pang X, Liu P, Kang Y. Quantitative Assessment of the Impact of Port Construction on the Surrounding Mudflat Topography Based on Remote Sensing—A Case Study of Binhai Port in Jiangsu Province. Journal of Marine Science and Engineering. 2024; 12(12):2290. https://doi.org/10.3390/jmse12122290

Chicago/Turabian Style

Chen, Binbin, Zhengdong Chen, Chuping Song, Xiaodong Pang, Peixun Liu, and Yanyan Kang. 2024. "Quantitative Assessment of the Impact of Port Construction on the Surrounding Mudflat Topography Based on Remote Sensing—A Case Study of Binhai Port in Jiangsu Province" Journal of Marine Science and Engineering 12, no. 12: 2290. https://doi.org/10.3390/jmse12122290

APA Style

Chen, B., Chen, Z., Song, C., Pang, X., Liu, P., & Kang, Y. (2024). Quantitative Assessment of the Impact of Port Construction on the Surrounding Mudflat Topography Based on Remote Sensing—A Case Study of Binhai Port in Jiangsu Province. Journal of Marine Science and Engineering, 12(12), 2290. https://doi.org/10.3390/jmse12122290

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