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Quantifying effects of water and sediment regulation scheme on the sand bar in the yellow river estuary in 2014
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Quantifying effects of water and sediment regulation scheme on the sand bar in the yellow river estuary in 2014 Yunzhe Wang a, Yunbao Fan a, Fei Bu a,b, Demin Zhou a,∗
Q1
a
College of Resource Environment and Tourism, Capital Normal University, 105 West Third Ring Road, Haidian District, Beijing 100048, China b Beijing Information Technology Project Evaluation Center, China
a r t i c l e
i n f o
Article history: Received 23 July 2019 Revised 8 September 2019 Accepted 26 October 2019 Available online xxx Keywords: Water and sediment regulation scheme Coastal wetlands Sand bar Reclamation land Yellow River tail channel
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a b s t r a c t Water and sediment regulation scheme (WSRS) is an annual water conservancy project which aims to alleviate sand depositions and reduce flood risks in the Yellow River of China since 2002. There are few researches on the sand bar within Yellow River tail channel and its estuary from each WSRS effect, though these relative researches are important to be carried out for a better understanding of WSRS. By interpreting two GF-1 satellite images in the end of 2013 and the start of 2015 after carefully controlling some potential bias factors from the change of water level, precipitation or tidal, we compared and analyzed the change of sand bars by one WSRS implemented in 2014 in this paper. Our results indicated this WSRS changed obviously the area/shape of sand bars. It made the area of the river sand bar decreased totally by 5.55 km2 , while the estuarine sand bar increased by 2.08 km2 . And it achieved the highest scour efficiency (90.11%) in the straight channel, but it achieved the lowest scour efficiency (44.71%) in the more bends channel. From the prospect in the change of estuarine sand bar, the west side area increased, while the east side area shrank. There were some broken small sand bars on the north side and they were forming a large sand bar. © 2019 European Regional Centre for Ecohydrology of the Polish Academy of Sciences. Published by Elsevier B.V. All rights reserved.
1. Introduction Water and sediment regulation scheme (WSRS) is the application of water conservancy project to regulate the water and sediment flux of rivers in order to alleviate deposition in the channel and reduce the risk of the huge flood event further. The Yellow River is the second-most sediment-laden river. Due to the highly suspended sediment concentration (SSC) from the Yellow River and the serious deposition in its middle and downstream river channel (Milliman and Meade, 1983; Yao, 2014), the ∗
Corresponding author. E-mail addresses: [email protected] (Y. Wang), [email protected] (Y. Fan), [email protected] (F. Bu), [email protected], zhoudemin@ neigae.ac.cn (D. Zhou).
Yellow River becomes the so-called “suspended” river. Therefore, Chinese engineers have constructed some of dams and reservoirs such as the Xiaolangdi Reservoir to raise the water level of the Yellow River channel artificially. After reaching a reasonable water level, then reservoir administrators can discharge a large amount of water to scour the deposition in the river channel. Thereby, it can effectively reduce the deposition and sediment in the river channel. At the same time, WSRS directly promotes the land reclamation in the estuarine area (Wang, 2005). Except for some occasionally stopped WSRS due to the water shortage such as 2016 and 2017, WSRS has regularly implemented in the Yellow River every year and has been executed 16 times by 2018 (Li, 2002; Wu et al., 2015). WSRS scours the riverbed simultaneously every time by changing the shape of the sand bar in the river channel.
https://doi.org/10.1016/j.ecohyd.2019.10.004 1642-3593/© 2019 European Regional Centre for Ecohydrology of the Polish Academy of Sciences. Published by Elsevier B.V. All rights reserved.
Please cite this article as: Y. Wang, Y. Fan and F. Bu et al., Quantifying effects of water and sediment regulation scheme on the sand bar in the yellow river estuary in 2014, Ecohydrology & Hydrobiology, https://doi.org/10.1016/j.ecohyd.2019.10.004
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It has regulated the hydrology-ecological connectivity of the wetland in the Yellow River Estuary (YRE). WSRS has reshaped the landscape pattern of the coastal wetland, and also largely affected the habitats of various rivers and wetlands in delta. As a special water conservancy project through the North China, WSRS was focused by both national and international society. Therefore, many researchers have carried out researches on the issue of WSRS. Most of the researchers mainly focused on the simulation of sediment transport process (Song et al., 2018), the retrieval of SSC in the estuary (Yu et al., 2018), and the analysis of measured cross-section change (Zheng et al., 2018). The long period of suspended particulate matter (SPM) concentration in the Yellow River estuary and adjacent sea can explain the correlation between SPM and land area, and it’s a valid approach to dynamically analyze SPM temporal variations in the near bay (Li et al., 2019). However, it’s difficult to explore SPM variation in the river channel and YRM, due to the slight difference in the most of the time. But it can effectively analyze the situation of the river channel and YRM with sand bar properties (e.g. position, shape, area) which have correlation with SPM from the high spatial resolution image. Most of previous researches rarely explored the correlation analysis between Yellow River tail channel and its estuary and linked with WSRS. Some scholars carried out researches on river channel sand bars landscape change in the Changjiang river (Wang et al., 2018a). However, their study did not involve ocean dynamics. the YRE is affected by not only the human influence of the Lijin Hydrological station but also the ocean dynamics. So the situation of YRE is more complicated to be studied. The Yellow River Delta (YRD) has been changing quickly, because of less runoff, heavy sediment and complicated ocean dynamics. So most researchers investigated the changed coastline of the YRD by carrying out analyzing the effects of land reclamation and channel diversion. The Yellow River Conservancy Commission (YRCC) believes that the study on the coastline must be based in the same month with the same tide level, but very few remote sensing images can match the YRCC standard for such a study. Therefore, some scholars adopted the average high-tide line method (Li et al., 2012) and the general high-tide line method to conduct related researches (Wang et al., 2018b). Because the tidal level data and the effective image were jointly limited, the researchers were difficult to accurately control the tidal level data. However, the tidal level data is actually an important factor in the change of the YRD, and the medium spatial resolution remote sensing image such as Landsat TM/ETM series was difficult to capture the small area in the YRE. But those small changes in the sand bar can deliver more accurate information about the changing characteristics and the future trend of the delta. The objectives of this study are: (1) According to the GF-1 remote sensing images which has a high spatial resolution, we integrated them with multiple factors of monitoring data such as water level, tidal level and precipitation data to eliminate the uncertainty existed in the remote sensing analysis. From which authors extracted quantitatively the landscape information of the tail channel and
the Yellow River Mouth (YRM) before and after the WSRS in 2014; (2) The sand bar change was compared and analyzed quantitatively by exploring it within the tail channel and YRM before and after the WSRS in 2014. And authors explored the landscape reshaping effect of WSRS on the tail channel and the YRM. This study can assist in a better understanding the scientific basis of the wetland habitat change in the YRE. It is significant for this study to reveal the evolution mechanism of the wetland in the YRD and to develop a reasonable scientific strategy for wetland conservation in this area. 2. Study area and data sources 2.1. Study area The Yellow River Delta Wetland Reserve is listed as a hot spot for coastal wetland study from the global scope (Xiao and Zhao, 2016; Zhang et al., 2016). The reserve is located in the eastern part of Shandong Province, China where from 118°42 E to 119°22 E and from 37°33 N to 37°56 N. It is the largest estuary delta nature reserve in China due to its typical wetland biodiversity and its important role in rare birds. Meanwhile, it is a very representative example of the estuarine wetland ecosystem in the world. The annual precipitation varies greatly in this nature reserve, and the seasonal precipitation is also unevenly distributed, which is mainly concentrated from June to August. According to the monitoring data from 2002 to 2013, the annual average water level is 11.24 m at Lijin Hydrological Station, while the annual water level reaches 12.6 m during the period of WSRS. The sea area around the YRE is half-closed, and the tides are irregular half-day tides in most of the shores (Shandong Yellow River Delta National Nature Reserve Administration, 2016). The study area is divided into four parts of A, B, C, and D, according to the detailed description from the planning report of the Yellow River Delta National Nature Reserve in Shandong Province, and the survey information on the Yellow River tail channel, and the sand bar distribution. The total study area is of about 55.03 km2, which keeps 50 km away from Lijin Hydrological Station, and 23 km from Dongying Port (Fig. 1).
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2.2. Data source and preprocessing
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In order to present the detailed changes in sand bar, we selected GF-1 remote sensing images which had the high spatial resolution, and integrated them with the hydrological data: tidal level simulation data, channel water level data, precipitation data and storm surge data. The tide level simulation data was sourced from the National Ocean Information Center at the Dongying Port in 2014, while the daily water level data was derived by YRCC at the Lijin Site in 2014 (http://61.163.88.227:8006/hwsq.aspx). The monitoring data of storm surge was from the Gudong Oilfield (near the northern part of the Yellow River Delta Wetland Reserve) in 2014, and the precipitation data was derived from the daily weather forecast of Kenli County, which covers the study area.
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Fig. 1. The location map of the study area (the more bends upper channel (A); the straight middle channel (B); the less sand bar lower channel (C) and the YRM (D)).
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The GF-1 satellite is the first satellite for generating the high spatial resolution imagery as one of the Earth Observation System of China (Bai, 2013). It has a 2 m spatial resolution for the panchromatic band, and an 8 m spatial resolution for the multi-spectral band. The GF-1 remote sensing images were difficult to be acquired for fully covering the study area at the same time due to the very long shape study area. Hence, we tried to select remote sensing images in the similar dates. Finally, December 9th, 2013 was fixed as the date of the image for reflecting sand bar information before WSRS, while January 18th, 2015 and January 22th, 2015 were fixed as the dates for that after WSRS. ENVI 5.3 was applied to implement image preprocessing including radiation correction, atmospheric correction, geometric correction and registration. The PAN Sharpening fusion method was used to fuse the panchromatic image and the multi-spectral image before we clip remote sensing images.
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3. Methods
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3.1. Selection of remote sensing image acquisition dates
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The remote sensing image reflects the instantaneous information of the sand bar in the estuary and tail channel. We used the different acquisition dates and times remote sensing images to compare and analyze the sand bar change before and after 2014. The key point is making the water level and tidal level elements normalized to a unique standard, therefore the inter-annual variation of the sand bar can be comparable. It is necessary to analyze the hydrological, meteorological and tidal level data of the study area for further fixing the reasonable images. We
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comprehensively analyzed for determining the date and time points of remote sensing image acquisition. Firstly, we selected the date with a small amount of precipitation in winter by analyzing the hydrological and meteorological data. Meanwhile, the exposed area of sand bar is steady and clear, therefore it is the best time for comparative analysis of sand bar changes in the Yellow River tail channel. Furthermore, we need to fix the reasonable date and time for remote sensing images according to the Dongying Port tidal level data. The tides level data were divided into the five periods according to the regularity of the high and low daily tide level data. The overall tide level was high from the end of May to the end of September, and the difference on tidal level was relatively large between the highest and lowest tide level value in the same day. So it was easier to achieve the same standard from the period between December to March. Because the fluctuation of the tide level was small on the dates within this period (Fig. 2(a)). We preliminary determined the best dates for extracting remote sensing image data (red points as the selection dates) on December 9th, 2013 before WSRS and on January 22th, 2015 after WSRS. We focused on the hourly tidal data of the 5 days before and after the remote sensing image acquisition day for further analysis of the potential selection time point. According to the calculated hourly tide level data (Fig. 2(b)), the tidal level data before WSRS was 116.64 cm, while the tidal level data after WSRS was 118.47 cm. The difference between the two tides level was 1.83 cm, a very tiny gap. Hence it didn’t exist a significant error that can bias the comparing of the estuarine sand bar change. Furthermore, there was no precipitation and storm surge in the week before the remote sensing image acquisition time by
Please cite this article as: Y. Wang, Y. Fan and F. Bu et al., Quantifying effects of water and sediment regulation scheme on the sand bar in the yellow river estuary in 2014, Ecohydrology & Hydrobiology, https://doi.org/10.1016/j.ecohyd.2019.10.004
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1 from Dec.6th,2013 to Mar.14th,2014; 2 from Fig. 2. Tide level simulation data ((a) daily tide level (highest tidal level and lowest tidal level), 3 from May.27th,2014 to Sept.24th,2014; 4 from Sept.25th,2014 to Dec.7th,2014; 5 from Dec.8th,2014 to Jan.25th,2015; Mar.15th,2014 to May.26th,2014; (b) hourly tide level, data source: China Oceanic Information Network).
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checking other relevant data. The water level data in channel was also analyzed, and it showed that measured water level (above the mean sea-level) was 10.45 m on December 9th, 2013 while it was 10.47 m on January 18th, 2015 according to the water level data from the Lijin Hydrological station where is no tributary until to the estuary. Therefore, the water level in channel was similar, and there was not obvious error in the comparison of the river sand bar landscape. Therefore, we finally selected December 9th, 2013 and January 18th and 22th, 2015 for the remote sensing images acquisition for comparing the sand bar changes in the tail channel and the YRM. Finally, Fig. 2(b) showed
the red points as the remote sensing image acquisition times.
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3.2. Interpretation of river sand bars
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The river sand bar in the study area were scoured by WSRS, and its shape frequently became irregular and small which was different from the other natural rivers sand bar and difficult to monitor by low spatial resolution remote sensing image. But the high spatial resolution image can facilitate the observation by monitoring the slight sand bar change. So combing the visual judgment by the
Please cite this article as: Y. Wang, Y. Fan and F. Bu et al., Quantifying effects of water and sediment regulation scheme on the sand bar in the yellow river estuary in 2014, Ecohydrology & Hydrobiology, https://doi.org/10.1016/j.ecohyd.2019.10.004
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Table 1 Visual interpretation of river sand bars. Sand bar types
Ellipse
Bamboo-leaf
Sickle
Bank
Interpretation symbols
228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 Q2 248 249 250
GF-1, the field investigation and relevant research (Li., 2013), the river sand bars were divided into ellipse sand bar, bamboo-leaf sand bar, sickle-shaped sand bar, other shape sand bar and bank. Table 1 presented the classification criteria which is used to distinguish the five types of river sand bar from images. The elliptical sand bar which is the sand bar early development form generally with a small area. And it always locates at the straight channel with little changes on its width. The bamboo-leaf sand bar is the sand bar stable development form generally with a larger area/circumference and locates at the “bow-shaped” channel. The sickle-shaped sand bar develops in the natural river bay and bends to the convex bank. We referenced the similar image segmentation research method (Yu et al., al.,2017; Yuan et al., 2015). And the multi-resolution segmentation method was used to segment GF-1 preprocessing data at the eCognition 8.9 platform. After many attempts to analyze and contrast, we assigned with image segmentation threshold of 120, the shape parameter of 0.5, the compactness of 0.5, and the weight of each band of 1. The water and the non-water were separated, according to the threshold of the NDWI (Eq. (1)).
NDW I = (( p(Green ) − p(NIR ))/( p(Green ) + p(NIR ))) (1) 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276
After the initial classification results, we achieved the overall accuracy over‘ 85% and the kappa coefficient around 0.72. In order to make interpretation more accurate, we carried out further post-processing. The classification result was manually re-corrected by processing the GF-1 on the ArcGIS 10.2 platform. After further manual modification and visual interpretation, we classified the study area into the various landscapes including water, bank, ellipse sand bar, bamboo-leaf sand bar, sickle-shaped sand bar, other shape sand bar, estuarine sand bar and artificial facility. It’s easy to classified out the water and artificial facility, but it’s difficult to classified the sand bar without expertise. So we classified the sand bar with some field study which could better distinguish each sand bar type. And we carried out stepwise classification with expertise in the character of each sand bar type. First step, the sand bar which is joined to the land could be classified as the bank. Second step, the sand bar whose shape is sickle in the curved channel could be classified as the sickle-shaped sand bar. Third step, the sand bar whose shape is ellipse and area is small could be classified as the ellipse sand bar. Final step, the other sand bar could be distinguish from their shape and image acquisition date, because most of sand bar are bamboo-leaf sand bars before WSRS and most of sand bar are other shape sand bars after WSRS.
3.3. Landscape change analysis
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In order to explore further impact of WSRS, the sand bar structure information was analyzed from the perspective of landscape. We referenced other studies in the application of landscape index (He and Zhang, 2009; Kong, 2017), and finally selected the patch density (PD) in the class metrics, the aggregation index (AI) in the class metrics, and the contagion (CONTAG) in the landscape metrics for sand bar landscape analysis. All these landscape index were analyzed on the sand bars by running the Fragstats 4.2 software. PD (Eq. (2)) can describe the fragmentation and is fundamental aspect of landscape pattern. PD has the same basic utility as number of patches as an index, except that it expresses number of patches on a per unit area basis that facilitates comparisons among landscapes of varying size. AI (Eq. (3)) can reflect the connectivity between the patches of each landscape type. The smaller the value, the more dispersed the landscape type. CONTAG (Eq. (4)) can describe the agglomeration and extension of the patches of each landscape type.
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ni PD = A
AI =
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(2)
ni = number of patches in the landscape of patch type i. A = total landscape area (m2 ).
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gii (100 ) max → gii
50 = 100 +
m m i=1
k=1
(P i )
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(3)
gii = number of like adjacencies between pixels of patch type i based on the single-count method. Max→gii = maximum number of like adjacencies between pixels of patch type i based on the single-count method.
CONT AG
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gik m k=1
gik
ln(P i )
gik m k=1
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gik
ln(m ) (4)
Pi = proportion of the landscape occupied by patch type i. gik = number of adjacencies between pixels of patch types i and k based on the double-count method. m = number of patch types present in the landscape, including the landscape border if present.
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4. Results
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4.1. Effects on the change of sand bar types by 2014 WSRS
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The Fig. 3 showed the results of landscape map from the remote sensing images before and after WSRS and
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Fig. 3. (a) Interpretation results (2013) before WSRS; (b) interpretation results (2015) after WSRS.
Table 2 Transition matrix (km2 ).
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Types
Water
Bank
Estuary sand bar
Ellipse sand bar
Bamboo-leaf sand bar
Other shape sand bar
Artificial facility
Water Bank Estuary sand bar Ellipse sand bar Bamboo-leaf sand bar Sickle-shaped sand bar Other shape sand bar Artificial facility 2015 area total:
34.26 4.91 0.85 0.02 0.89 0.47 0.53 0.00 41.93
0.63 2.63
2.93
0.03 0.02
0.20 0.09
0.41 0.12
0.01 0.00
5.84 0.00 0.01 0.01 0.01 0.00 3.28
8.78
0.00 0.01
0.00 0.00 0.00
0.00
0.02 0.01 0.08
0.05
0.30
0.64
Table 2 showed the transition matrix results between various types of landscapes. From which, the total variation area of the sand bars was 11.20 km2 , including 2.08 km2 as the totally increased area of the estuarine sand bar (the accumulated 2.93 km2 minus by the eroded 0.85 km2 ). The totally decreased area of the river sand bars was 5.55 km2 (the erosion of 6.82 km2 minus the accumulation of 1.27 km2 ). With the this influence statistics of sand bars, we concluded that sand bars were mainly existed in the upper and lower channel. As for assessing the WSRS scouring efficiency (from the aspect of the sand bar erosion area), the middle river channel had the highest efficiency (90.11%), while the upper channel had the lowest efficiency (44.71%). The upper channel low efficiency indicated that the river bend was scoured, but the very curved river hindered the transport of eroded sediment to the estuary. And the new sand bar would be regenerated again near the scouring place a period later of past scoring. The lower river channel received the medial efficiency of scouring by WSRS, which meant that the closer to the estuary,
0.00 0.01
2013 area total 38.46 7.76 6.69 0.03 0.93 0.49 0.62 0.01 54.98
the lower WSRS scouring efficiency. It is reasonable if considering of the role of ocean power near the estuarine area. The Table 2 showed the result of transition matrix between classified types in the variation of this WSRS. In general, the total area of river sand bars was decreased while the estuarine sand bar area was increased due to the 2014 WSRS according to Table 2. The areas of different types have obviously transited as following: the river channel banks was eroded into bamboo-leaf sand bar, elliptical sand bar and other shape sand bars; the bambooleaf sand bars was eroded into other shape sand bars. So it led to an increase in the area of the elliptical sand bar and other shapes sand bars, and an decrease in the other river sand bar types area. According to the landscape matrix, the result of converting water into various types of sand bars indicated that WSRS not only generated new types of sand bars but also changed the positions of them. And some estuarine sand bars were transformed into water at the same time, indicating an obvious role of marine erosion.
Please cite this article as: Y. Wang, Y. Fan and F. Bu et al., Quantifying effects of water and sediment regulation scheme on the sand bar in the yellow river estuary in 2014, Ecohydrology & Hydrobiology, https://doi.org/10.1016/j.ecohyd.2019.10.004
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Fig. 4. Upper channel (A) around Q2 section: (a1 ) the interpretation result before WSRS; (a2 ) the interpretation result after WSRS; middle channel (B) around Q4 section: (b1 ) the interpretation result before WSRS; (b2 ) the interpretation result after WSRS; lower channel (C) around Q7 section: (c1 ) the interpretation result before WSRS; (c2 ) the interpretation result after WSRS; (d) the variation area of YRM below WSRS.
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4.2. Effects on the different parts of the study area by 2014 WSRS Since the tail channel was too long and narrow to be analyzed, YRM was also divided into three parts and each part of A, B, C, and D was selected for a detailed analysis on its spatial change (Fig. 4). And the different directions of YRM area had significant difference in increase and decrease: the western YRM was increased by 2.82 km2 and decreased by 0.12 km2 ; the northern YRM was increased by 0.06 km2 and decreased by 0.36 km2 ; the eastern YRM was increased by 0.06 km2 and decreased by 0.37 km2 . The western YRM area had a huge variation by extending to the north and the west. But the east side of the northern YRM was eroded and shrunk, and the area where was the two blocks in northern YRM was increased and trended to the whole block. And the area on the north and east side of the eastern YRM was decreased. Both shape and location of sand bar had changed, and most of the sand bar had been “stretched” to the estuary by comparing the results of interpretations from before and after 2014 WSRS. Since there were many bends in the upper channel, hence the large bank had been eroded into many small area sand bars including small banks, bamboo-leaf sand bars and some other shapes of small sand bars. The existed large bamboo-leaf sand bars were eroded into an irregular shape, being more fragmented and complicated. The middle channel was relatively straightforward, hence its both sides sand bars were eroded smoothly, though most of them were scattered. This scouring made the bamboo-
leaf sand bar and the different small shape sand bars into the main sand bar types. This scouring achieved an obvious effect by eliminating large sand bars in the lower channel. Therefore the larger sand bars were eroded into broken small sand bars such as bamboo-leaf sand bars, elliptical sand bars and other shaped sand bars in the entire tail channel after 2014 WSRS.
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4.3. The landscape variations of sand bars due to 2014 WSRS
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The landscape indices were presented in the Table 3, according to the classified interpretation. The CONTAG in 2013 was 76.26, while it was 79.77 in 2015. The variation value was 3.51 and the change rate was 4.60%. The PD of estuarine sand bar was reduced, which indicating that the patches decreased and gradually became larger patches. The AI and the CONTAG of the river sand bars (except for the disappeared sickle-shaped sand bar) showed that WSRS may cause the sand bar distribution to be dispersed spatially, but the deposition location did not change very quickly. The river channel became smoother after this WSRS according to the results of the CONTAG.
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5. Discussions
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The channel sand bars have been constantly reshaped by irregular WSRSs. The sand bar is defined as a formed deposition which is exposed above the water surface (Li, 2013). It has a close correlation with the riverbed which could be reflected by the channel section, so it could be
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Bank Estuary sand bar Ellipse sand bar Bamboo-leaf sand bar Sickle-shaped sand bar Water Other shape sand bar Artificial facility
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Patch density (PD)
Aggregation index (AI)
2013
2015
Change rate (%)
2013
2015
Change rate (%)
3.14 0.76 0.16 0.44 0.11 0.89 0.15 0.04
5.00 0.56 1.09 1.24 0.00 2.83 0.89 0.04
59.01 −26.17 566.85 183.42 −100.00 218.49 512.80 0.00
98.06 99.57 96.56 98.60 98.99 99.58 98.76 90.42
97.41 99.65 92.31 95.00 0.00 99.62 96.96 94.56
−0.67 0.08 −4.41 −3.65 −100.00 0.05 −1.82 4.59
an useful indicator to further explore the influence by WSRS. Based on the monitoring data from the Q2, Q4, and Q7 sections in the study area, the changes of each section incised were obviously after the flood season, especially those from the Q4 were very significantly, meanwhile the channel where Q2 section erosion located happened mainly in the north bank and continuously been broadened (Cui, 2015). The main scouring were performed in the both sides of the channel and depositing in the middle of the channel. The similar results were presented if comparing Fig. 4(a1 ) with Fig. 4(a2 ). The major erosion happened in the bank of the north channel, while the sand bar mainly existed in the center of the channel due to this WSRS. Therefore, the remote sensing interpretation results of this study were further verified by the measured data from the channel sections. WSRSs promote the land reclamation effect in the YRM by increasing the probability of the hyperpycnal flow which is one of the transport pattern of suspended sediment off the river mouth (Song et al., 2018). During the transporting of suspended sediments off the river mouth, different transport patterns which depend on the SSC and salinity have unique accumulation methods. The hyperpycnal plume will form if the river density is less than the surrounding density when the river enters the sea, unless the hyperpycnal flow will form. Each WSRS carries a lot of suspended sediment into the sea, then it effectively increases the probability of the hyperpycnal flow, which form sand bars at the esturarine area (Xu et al., 2014). Each WSRS plays a key role in a direct effect to form and change the variation area of sand bars in YRM. And it can further explain the mechanism of such a form or change by analyzing the suspended sediment particle sizes and the corresponding changes within the near shore sections. The suspended sediment particle size was smaller and more difficult to deposit, due to the gradually implementation of WSRS which caused the downstream riverbed to be coarser, therefore it resulted in reducing the channel sand bar erosion efficiency and worsening the delta erosion resistance (Miao et al., 2016; Long et al., 2017). So these results explained that the YRM area existed erosion and the deposition concentration location in channel was stable in our study. Furthermore, the sediment was accumulated at 25–35 km (within the current estuary), and the estuary delta was gradually expanding to the sea areas on both sides of the YRM, but the deposition was in a dynamic change at the near shore (Wang et al.,
2015). And the small bay locates between YRM and the Gudong seawall is easy to deposit (Yu et al., 2015). According to our study result, the YRM was spread on both river banks, and mainly deposited on the west side (near the Gudong seawall). Although the average increase of the YRD area (which is larger than our study result) was 8.57 km2 in many years (2002–2015) according to the study from Li (2016), so the YRM variation area would be smaller than 8.57 km2 according to this study. And it can also indicated that the YRM variation area was smaller than before, because the extending length of Yellow River tail channel was slow during 1999–2010 (Zhang et al., 2019). The YRM variation area due to 2014 WSRS is similar with those data from other researchers. On the other hand, our study showed that the YRM area was still large, although WSRS implement interval was longer. So it indicated other sediment factors (expect WSRS factor) continued to offset some parts of the sea erosion. At the same time, the Yellow River estuary were modified by many dam projects that can further consolidate the deposition then enhance land reclamation effects. Therefore, our study conclusions been further confirmed by some previous study cases. The YRM accumulation position depended on the type of shear front which was influenced by the flood and ebb tide phases during WSRS period (Wang et al., 2006). The tides near YRD basically parallel to the shoreline and have back-and-force movements which the flood tide direction is southeast and the ebb tide direction is northwest (Yu et al., 2018). During the WSRS period, the sediment will be deposited in the southeastern YRM along the flood tide, and in the northwestern YRM along the ebb tide after the shear front. Then we inferred the variation area of sand bars in YRM was influenced by the ebb tide during 2014 WSRS period. However, it is difficult to accurately describe the shape and location of the YRM sand bars, and analyze the formation mechanism with the current data sets (Xu et al., 2014). High spatial resolution images could reflect more details on the sand bar shape after our result and analysis, and it is possible to present dynamic information by a series of long period high spatial resolution images. Each WSRS obviously changed the sand bar area and further profoundly affected the ecological environment in the YRD. A WSRS can directly affect the plant habitat of reeds on tidal flats or river channel. The patches, areas and numbers of both phragmites australis habitats and tidal flats are partly controlled by the fluxes of stream
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flow or sediment from Yellow River. And the heavy metals and arsenic (As) were carried to the YRD by WSRS (due to rapid agricultural development upstream of the YRD and heavy applications of agrochemicals and fertilizers), then the wetland habitat was seriously polluted (Bai et al., 2012). So WSRS obviously changed the morphological characteristics of the sand bar, and also affected the soil properties in the wetland (Bai et al., 2014). From which the breeding of red-crowned cranes can be influenced since their habitat types can be changed largely due to the annual or inter-annual variation caused by each WSRS (Bai et al., 2015; Wang, 2017; Cao et al., 2011). In addition, each WSRS also affects the growth and reproduction of marine life. The invertebrate assemblage was affected by the fluxes of stream flow and sediment from Yellow River at the section of 20 km from the estuary (Zhang et al., 2014). Each WSRS changes the sand bar dynamic balance by depositing or eroding, then changes the shape/area of each sand bar annually (Li, 2013), however the influence factors of each WSRS were complicated. These factors include runoff, sediment discharge, suspended sediment particle size and the boundary condition of the riverbed in the Yellow River (Yao, 2014; Wang, 2005). Furthermore, each WSRS implementation time issue is also crucial if comparing with the high-speed water flow experiment in the Colorado River of United States (Grams et al., 2010), which would also leads to change the sand bar largely. On the first day of the experiment, the sediment deposit was the largest, but the erosion exceeded the deposition after three days according to Grams’ study. Due to the high suspended solids concentration before the experiment, some researches indicated that it would result to form a larger sand bar, otherwise high-speed water flow may erode the sand bar and would not form sand bars (Wu et al., 2004; Yuan et al., 2012). These previous studies could help us improve the WSRS erosion efficiency in the river channel, furthermore better control the YRM area. The wetland conservation could guide a reasonable scientific strategy with a new cognition in the channel sand bars. It’s a scientific approach to discover the situation of channel deposition by the analysis of water level and sand bar interpretation result in channel. During the flooding, the administrators could monitor potential dangerous location which exists large area of sand bar in high water level. Meanwhile, the location of the diversion dam could be further optimized by the channel deposition. The better controlling of dams could improve the water diversion efficiency to solve the water shortage problem in the wetland during the WSRS period.
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6. Conclusions
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The sand bar landscape change were explored both in the Yellow River tail channel and its estuary before and after a WSRS in 2014. The high spatial resolution images were applied to quantitative extract and conduct comparative analysis on the change based on the comprehensive analysis of key influence factors such as tide level, water level, rainfall, and storm surge. From which, we carried out a further analysis of the potential impact from this WSRS on the land reclamation in The Yellow River Delta Wetland
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Reserve. The following conclusions can be drew from this study:
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(1) In general, the 2014 WSRS eroded the banks of the Yellow River tail channel and change into some small, broken sand bars. It caused the sand bar to be fragmented, though there was not a significant change in the location. The sand bar area within the tail river channel totally decreased 5.55 km2 due to this WSRS, and been scoured mainly in the straight channel (middle channel). The curved channel sand bar was vulnerably scoured, but the overall erosion efficiency was low from this WSRS which was prefer to form the new sand bars. (2) The estuarine sand bar in YRM had a large area deposition in west side and a small erosion area in east side after this WSRS, and with a tendency to union some small sand bars on the north side. The overall effect from this WSRS showed a movement to the sea from the channel sediment. Based on the area/shape change of the estuarine sand bars, the YRM area was increased by 2.08 km2 due to this WSRS, indicating an obvious effect on land reclamation in the estuarine area.
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At present, few study were carried out to evaluate and analyze the change in tail channel and YRM caused by the single WSRS or multiple WSRSs with the support of the remote sensing technology. But it is obvious that each WSRS plays a key role in alleviating deposition and land reclamation, and it changes the sand bars by activating with many other natural and artificial factors. We in this study carefully evaluated the WSRS effects by focusing especially on the land reclamation and the landscape change of the sand bar within the Yellow River tail channel and its estuary. It provided also a new perspective for the protection of coastal wetland resources and delta hydrological ecology.
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Declaration of Competing Interest
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The authors declare no conflict of interest. Ethical Statement The research was done according to ethical standards.
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Acknowledgement
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Thanks for the support of the National Key R&D Program (2017YFC0505903). Thanks for the help of GONG, Z., KE, Y., BAI, J.
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Quantifying effects of water and sediment regulation scheme on the sand bar in the yellow river estuary in 2014 Yunzhe Wang a, Yunbao Fan a, Fei Bu a,b, Demin Zhou a,∗
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a
College of Resource Environment and Tourism, Capital Normal University, 105 West Third Ring Road, Haidian District, Beijing 100048, China b Beijing Information Technology Project Evaluation Center, China
a r t i c l e
i n f o
Article history: Received 23 July 2019 Revised 8 September 2019 Accepted 26 October 2019 Available online xxx Keywords: Water and sediment regulation scheme Coastal wetlands Sand bar Reclamation land Yellow River tail channel
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a b s t r a c t Water and sediment regulation scheme (WSRS) is an annual water conservancy project which aims to alleviate sand depositions and reduce flood risks in the Yellow River of China since 2002. There are few researches on the sand bar within Yellow River tail channel and its estuary from each WSRS effect, though these relative researches are important to be carried out for a better understanding of WSRS. By interpreting two GF-1 satellite images in the end of 2013 and the start of 2015 after carefully controlling some potential bias factors from the change of water level, precipitation or tidal, we compared and analyzed the change of sand bars by one WSRS implemented in 2014 in this paper. Our results indicated this WSRS changed obviously the area/shape of sand bars. It made the area of the river sand bar decreased totally by 5.55 km2 , while the estuarine sand bar increased by 2.08 km2 . And it achieved the highest scour efficiency (90.11%) in the straight channel, but it achieved the lowest scour efficiency (44.71%) in the more bends channel. From the prospect in the change of estuarine sand bar, the west side area increased, while the east side area shrank. There were some broken small sand bars on the north side and they were forming a large sand bar. © 2019 European Regional Centre for Ecohydrology of the Polish Academy of Sciences. Published by Elsevier B.V. All rights reserved.
1. Introduction Water and sediment regulation scheme (WSRS) is the application of water conservancy project to regulate the water and sediment flux of rivers in order to alleviate deposition in the channel and reduce the risk of the huge flood event further. The Yellow River is the second-most sediment-laden river. Due to the highly suspended sediment concentration (SSC) from the Yellow River and the serious deposition in its middle and downstream river channel (Milliman and Meade, 1983; Yao, 2014), the ∗
Corresponding author. E-mail addresses: [email protected] (Y. Wang), [email protected] (Y. Fan), [email protected] (F. Bu), [email protected], zhoudemin@ neigae.ac.cn (D. Zhou).
Yellow River becomes the so-called “suspended” river. Therefore, Chinese engineers have constructed some of dams and reservoirs such as the Xiaolangdi Reservoir to raise the water level of the Yellow River channel artificially. After reaching a reasonable water level, then reservoir administrators can discharge a large amount of water to scour the deposition in the river channel. Thereby, it can effectively reduce the deposition and sediment in the river channel. At the same time, WSRS directly promotes the land reclamation in the estuarine area (Wang, 2005). Except for some occasionally stopped WSRS due to the water shortage such as 2016 and 2017, WSRS has regularly implemented in the Yellow River every year and has been executed 16 times by 2018 (Li, 2002; Wu et al., 2015). WSRS scours the riverbed simultaneously every time by changing the shape of the sand bar in the river channel.
https://doi.org/10.1016/j.ecohyd.2019.10.004 1642-3593/© 2019 European Regional Centre for Ecohydrology of the Polish Academy of Sciences. Published by Elsevier B.V. All rights reserved.
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It has regulated the hydrology-ecological connectivity of the wetland in the Yellow River Estuary (YRE). WSRS has reshaped the landscape pattern of the coastal wetland, and also largely affected the habitats of various rivers and wetlands in delta. As a special water conservancy project through the North China, WSRS was focused by both national and international society. Therefore, many researchers have carried out researches on the issue of WSRS. Most of the researchers mainly focused on the simulation of sediment transport process (Song et al., 2018), the retrieval of SSC in the estuary (Yu et al., 2018), and the analysis of measured cross-section change (Zheng et al., 2018). The long period of suspended particulate matter (SPM) concentration in the Yellow River estuary and adjacent sea can explain the correlation between SPM and land area, and it’s a valid approach to dynamically analyze SPM temporal variations in the near bay (Li et al., 2019). However, it’s difficult to explore SPM variation in the river channel and YRM, due to the slight difference in the most of the time. But it can effectively analyze the situation of the river channel and YRM with sand bar properties (e.g. position, shape, area) which have correlation with SPM from the high spatial resolution image. Most of previous researches rarely explored the correlation analysis between Yellow River tail channel and its estuary and linked with WSRS. Some scholars carried out researches on river channel sand bars landscape change in the Changjiang river (Wang et al., 2018a). However, their study did not involve ocean dynamics. the YRE is affected by not only the human influence of the Lijin Hydrological station but also the ocean dynamics. So the situation of YRE is more complicated to be studied. The Yellow River Delta (YRD) has been changing quickly, because of less runoff, heavy sediment and complicated ocean dynamics. So most researchers investigated the changed coastline of the YRD by carrying out analyzing the effects of land reclamation and channel diversion. The Yellow River Conservancy Commission (YRCC) believes that the study on the coastline must be based in the same month with the same tide level, but very few remote sensing images can match the YRCC standard for such a study. Therefore, some scholars adopted the average high-tide line method (Li et al., 2012) and the general high-tide line method to conduct related researches (Wang et al., 2018b). Because the tidal level data and the effective image were jointly limited, the researchers were difficult to accurately control the tidal level data. However, the tidal level data is actually an important factor in the change of the YRD, and the medium spatial resolution remote sensing image such as Landsat TM/ETM series was difficult to capture the small area in the YRE. But those small changes in the sand bar can deliver more accurate information about the changing characteristics and the future trend of the delta. The objectives of this study are: (1) According to the GF-1 remote sensing images which has a high spatial resolution, we integrated them with multiple factors of monitoring data such as water level, tidal level and precipitation data to eliminate the uncertainty existed in the remote sensing analysis. From which authors extracted quantitatively the landscape information of the tail channel and
the Yellow River Mouth (YRM) before and after the WSRS in 2014; (2) The sand bar change was compared and analyzed quantitatively by exploring it within the tail channel and YRM before and after the WSRS in 2014. And authors explored the landscape reshaping effect of WSRS on the tail channel and the YRM. This study can assist in a better understanding the scientific basis of the wetland habitat change in the YRE. It is significant for this study to reveal the evolution mechanism of the wetland in the YRD and to develop a reasonable scientific strategy for wetland conservation in this area. 2. Study area and data sources 2.1. Study area The Yellow River Delta Wetland Reserve is listed as a hot spot for coastal wetland study from the global scope (Xiao and Zhao, 2016; Zhang et al., 2016). The reserve is located in the eastern part of Shandong Province, China where from 118°42 E to 119°22 E and from 37°33 N to 37°56 N. It is the largest estuary delta nature reserve in China due to its typical wetland biodiversity and its important role in rare birds. Meanwhile, it is a very representative example of the estuarine wetland ecosystem in the world. The annual precipitation varies greatly in this nature reserve, and the seasonal precipitation is also unevenly distributed, which is mainly concentrated from June to August. According to the monitoring data from 2002 to 2013, the annual average water level is 11.24 m at Lijin Hydrological Station, while the annual water level reaches 12.6 m during the period of WSRS. The sea area around the YRE is half-closed, and the tides are irregular half-day tides in most of the shores (Shandong Yellow River Delta National Nature Reserve Administration, 2016). The study area is divided into four parts of A, B, C, and D, according to the detailed description from the planning report of the Yellow River Delta National Nature Reserve in Shandong Province, and the survey information on the Yellow River tail channel, and the sand bar distribution. The total study area is of about 55.03 km2, which keeps 50 km away from Lijin Hydrological Station, and 23 km from Dongying Port (Fig. 1).
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2.2. Data source and preprocessing
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In order to present the detailed changes in sand bar, we selected GF-1 remote sensing images which had the high spatial resolution, and integrated them with the hydrological data: tidal level simulation data, channel water level data, precipitation data and storm surge data. The tide level simulation data was sourced from the National Ocean Information Center at the Dongying Port in 2014, while the daily water level data was derived by YRCC at the Lijin Site in 2014 (http://61.163.88.227:8006/hwsq.aspx). The monitoring data of storm surge was from the Gudong Oilfield (near the northern part of the Yellow River Delta Wetland Reserve) in 2014, and the precipitation data was derived from the daily weather forecast of Kenli County, which covers the study area.
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Fig. 1. The location map of the study area (the more bends upper channel (A); the straight middle channel (B); the less sand bar lower channel (C) and the YRM (D)).
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The GF-1 satellite is the first satellite for generating the high spatial resolution imagery as one of the Earth Observation System of China (Bai, 2013). It has a 2 m spatial resolution for the panchromatic band, and an 8 m spatial resolution for the multi-spectral band. The GF-1 remote sensing images were difficult to be acquired for fully covering the study area at the same time due to the very long shape study area. Hence, we tried to select remote sensing images in the similar dates. Finally, December 9th, 2013 was fixed as the date of the image for reflecting sand bar information before WSRS, while January 18th, 2015 and January 22th, 2015 were fixed as the dates for that after WSRS. ENVI 5.3 was applied to implement image preprocessing including radiation correction, atmospheric correction, geometric correction and registration. The PAN Sharpening fusion method was used to fuse the panchromatic image and the multi-spectral image before we clip remote sensing images.
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3. Methods
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3.1. Selection of remote sensing image acquisition dates
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The remote sensing image reflects the instantaneous information of the sand bar in the estuary and tail channel. We used the different acquisition dates and times remote sensing images to compare and analyze the sand bar change before and after 2014. The key point is making the water level and tidal level elements normalized to a unique standard, therefore the inter-annual variation of the sand bar can be comparable. It is necessary to analyze the hydrological, meteorological and tidal level data of the study area for further fixing the reasonable images. We
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comprehensively analyzed for determining the date and time points of remote sensing image acquisition. Firstly, we selected the date with a small amount of precipitation in winter by analyzing the hydrological and meteorological data. Meanwhile, the exposed area of sand bar is steady and clear, therefore it is the best time for comparative analysis of sand bar changes in the Yellow River tail channel. Furthermore, we need to fix the reasonable date and time for remote sensing images according to the Dongying Port tidal level data. The tides level data were divided into the five periods according to the regularity of the high and low daily tide level data. The overall tide level was high from the end of May to the end of September, and the difference on tidal level was relatively large between the highest and lowest tide level value in the same day. So it was easier to achieve the same standard from the period between December to March. Because the fluctuation of the tide level was small on the dates within this period (Fig. 2(a)). We preliminary determined the best dates for extracting remote sensing image data (red points as the selection dates) on December 9th, 2013 before WSRS and on January 22th, 2015 after WSRS. We focused on the hourly tidal data of the 5 days before and after the remote sensing image acquisition day for further analysis of the potential selection time point. According to the calculated hourly tide level data (Fig. 2(b)), the tidal level data before WSRS was 116.64 cm, while the tidal level data after WSRS was 118.47 cm. The difference between the two tides level was 1.83 cm, a very tiny gap. Hence it didn’t exist a significant error that can bias the comparing of the estuarine sand bar change. Furthermore, there was no precipitation and storm surge in the week before the remote sensing image acquisition time by
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1 from Dec.6th,2013 to Mar.14th,2014; 2 from Fig. 2. Tide level simulation data ((a) daily tide level (highest tidal level and lowest tidal level), 3 from May.27th,2014 to Sept.24th,2014; 4 from Sept.25th,2014 to Dec.7th,2014; 5 from Dec.8th,2014 to Jan.25th,2015; Mar.15th,2014 to May.26th,2014; (b) hourly tide level, data source: China Oceanic Information Network).
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checking other relevant data. The water level data in channel was also analyzed, and it showed that measured water level (above the mean sea-level) was 10.45 m on December 9th, 2013 while it was 10.47 m on January 18th, 2015 according to the water level data from the Lijin Hydrological station where is no tributary until to the estuary. Therefore, the water level in channel was similar, and there was not obvious error in the comparison of the river sand bar landscape. Therefore, we finally selected December 9th, 2013 and January 18th and 22th, 2015 for the remote sensing images acquisition for comparing the sand bar changes in the tail channel and the YRM. Finally, Fig. 2(b) showed
the red points as the remote sensing image acquisition times.
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3.2. Interpretation of river sand bars
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The river sand bar in the study area were scoured by WSRS, and its shape frequently became irregular and small which was different from the other natural rivers sand bar and difficult to monitor by low spatial resolution remote sensing image. But the high spatial resolution image can facilitate the observation by monitoring the slight sand bar change. So combing the visual judgment by the
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Table 1 Visual interpretation of river sand bars. Sand bar types
Ellipse
Bamboo-leaf
Sickle
Bank
Interpretation symbols
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GF-1, the field investigation and relevant research (Li., 2013), the river sand bars were divided into ellipse sand bar, bamboo-leaf sand bar, sickle-shaped sand bar, other shape sand bar and bank. Table 1 presented the classification criteria which is used to distinguish the five types of river sand bar from images. The elliptical sand bar which is the sand bar early development form generally with a small area. And it always locates at the straight channel with little changes on its width. The bamboo-leaf sand bar is the sand bar stable development form generally with a larger area/circumference and locates at the “bow-shaped” channel. The sickle-shaped sand bar develops in the natural river bay and bends to the convex bank. We referenced the similar image segmentation research method (Yu et al., al.,2017; Yuan et al., 2015). And the multi-resolution segmentation method was used to segment GF-1 preprocessing data at the eCognition 8.9 platform. After many attempts to analyze and contrast, we assigned with image segmentation threshold of 120, the shape parameter of 0.5, the compactness of 0.5, and the weight of each band of 1. The water and the non-water were separated, according to the threshold of the NDWI (Eq. (1)).
NDW I = (( p(Green ) − p(NIR ))/( p(Green ) + p(NIR ))) (1) 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276
After the initial classification results, we achieved the overall accuracy over‘ 85% and the kappa coefficient around 0.72. In order to make interpretation more accurate, we carried out further post-processing. The classification result was manually re-corrected by processing the GF-1 on the ArcGIS 10.2 platform. After further manual modification and visual interpretation, we classified the study area into the various landscapes including water, bank, ellipse sand bar, bamboo-leaf sand bar, sickle-shaped sand bar, other shape sand bar, estuarine sand bar and artificial facility. It’s easy to classified out the water and artificial facility, but it’s difficult to classified the sand bar without expertise. So we classified the sand bar with some field study which could better distinguish each sand bar type. And we carried out stepwise classification with expertise in the character of each sand bar type. First step, the sand bar which is joined to the land could be classified as the bank. Second step, the sand bar whose shape is sickle in the curved channel could be classified as the sickle-shaped sand bar. Third step, the sand bar whose shape is ellipse and area is small could be classified as the ellipse sand bar. Final step, the other sand bar could be distinguish from their shape and image acquisition date, because most of sand bar are bamboo-leaf sand bars before WSRS and most of sand bar are other shape sand bars after WSRS.
3.3. Landscape change analysis
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In order to explore further impact of WSRS, the sand bar structure information was analyzed from the perspective of landscape. We referenced other studies in the application of landscape index (He and Zhang, 2009; Kong, 2017), and finally selected the patch density (PD) in the class metrics, the aggregation index (AI) in the class metrics, and the contagion (CONTAG) in the landscape metrics for sand bar landscape analysis. All these landscape index were analyzed on the sand bars by running the Fragstats 4.2 software. PD (Eq. (2)) can describe the fragmentation and is fundamental aspect of landscape pattern. PD has the same basic utility as number of patches as an index, except that it expresses number of patches on a per unit area basis that facilitates comparisons among landscapes of varying size. AI (Eq. (3)) can reflect the connectivity between the patches of each landscape type. The smaller the value, the more dispersed the landscape type. CONTAG (Eq. (4)) can describe the agglomeration and extension of the patches of each landscape type.
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ni PD = A
AI =
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(2)
ni = number of patches in the landscape of patch type i. A = total landscape area (m2 ).
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gii (100 ) max → gii
50 = 100 +
m m i=1
k=1
(P i )
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(3)
gii = number of like adjacencies between pixels of patch type i based on the single-count method. Max→gii = maximum number of like adjacencies between pixels of patch type i based on the single-count method.
CONT AG
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gik m k=1
gik
ln(P i )
gik m k=1
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gik
ln(m ) (4)
Pi = proportion of the landscape occupied by patch type i. gik = number of adjacencies between pixels of patch types i and k based on the double-count method. m = number of patch types present in the landscape, including the landscape border if present.
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4. Results
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4.1. Effects on the change of sand bar types by 2014 WSRS
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The Fig. 3 showed the results of landscape map from the remote sensing images before and after WSRS and
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Fig. 3. (a) Interpretation results (2013) before WSRS; (b) interpretation results (2015) after WSRS.
Table 2 Transition matrix (km2 ).
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Types
Water
Bank
Estuary sand bar
Ellipse sand bar
Bamboo-leaf sand bar
Other shape sand bar
Artificial facility
Water Bank Estuary sand bar Ellipse sand bar Bamboo-leaf sand bar Sickle-shaped sand bar Other shape sand bar Artificial facility 2015 area total:
34.26 4.91 0.85 0.02 0.89 0.47 0.53 0.00 41.93
0.63 2.63
2.93
0.03 0.02
0.20 0.09
0.41 0.12
0.01 0.00
5.84 0.00 0.01 0.01 0.01 0.00 3.28
8.78
0.00 0.01
0.00 0.00 0.00
0.00
0.02 0.01 0.08
0.05
0.30
0.64
Table 2 showed the transition matrix results between various types of landscapes. From which, the total variation area of the sand bars was 11.20 km2 , including 2.08 km2 as the totally increased area of the estuarine sand bar (the accumulated 2.93 km2 minus by the eroded 0.85 km2 ). The totally decreased area of the river sand bars was 5.55 km2 (the erosion of 6.82 km2 minus the accumulation of 1.27 km2 ). With the this influence statistics of sand bars, we concluded that sand bars were mainly existed in the upper and lower channel. As for assessing the WSRS scouring efficiency (from the aspect of the sand bar erosion area), the middle river channel had the highest efficiency (90.11%), while the upper channel had the lowest efficiency (44.71%). The upper channel low efficiency indicated that the river bend was scoured, but the very curved river hindered the transport of eroded sediment to the estuary. And the new sand bar would be regenerated again near the scouring place a period later of past scoring. The lower river channel received the medial efficiency of scouring by WSRS, which meant that the closer to the estuary,
0.00 0.01
2013 area total 38.46 7.76 6.69 0.03 0.93 0.49 0.62 0.01 54.98
the lower WSRS scouring efficiency. It is reasonable if considering of the role of ocean power near the estuarine area. The Table 2 showed the result of transition matrix between classified types in the variation of this WSRS. In general, the total area of river sand bars was decreased while the estuarine sand bar area was increased due to the 2014 WSRS according to Table 2. The areas of different types have obviously transited as following: the river channel banks was eroded into bamboo-leaf sand bar, elliptical sand bar and other shape sand bars; the bambooleaf sand bars was eroded into other shape sand bars. So it led to an increase in the area of the elliptical sand bar and other shapes sand bars, and an decrease in the other river sand bar types area. According to the landscape matrix, the result of converting water into various types of sand bars indicated that WSRS not only generated new types of sand bars but also changed the positions of them. And some estuarine sand bars were transformed into water at the same time, indicating an obvious role of marine erosion.
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Fig. 4. Upper channel (A) around Q2 section: (a1 ) the interpretation result before WSRS; (a2 ) the interpretation result after WSRS; middle channel (B) around Q4 section: (b1 ) the interpretation result before WSRS; (b2 ) the interpretation result after WSRS; lower channel (C) around Q7 section: (c1 ) the interpretation result before WSRS; (c2 ) the interpretation result after WSRS; (d) the variation area of YRM below WSRS.
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4.2. Effects on the different parts of the study area by 2014 WSRS Since the tail channel was too long and narrow to be analyzed, YRM was also divided into three parts and each part of A, B, C, and D was selected for a detailed analysis on its spatial change (Fig. 4). And the different directions of YRM area had significant difference in increase and decrease: the western YRM was increased by 2.82 km2 and decreased by 0.12 km2 ; the northern YRM was increased by 0.06 km2 and decreased by 0.36 km2 ; the eastern YRM was increased by 0.06 km2 and decreased by 0.37 km2 . The western YRM area had a huge variation by extending to the north and the west. But the east side of the northern YRM was eroded and shrunk, and the area where was the two blocks in northern YRM was increased and trended to the whole block. And the area on the north and east side of the eastern YRM was decreased. Both shape and location of sand bar had changed, and most of the sand bar had been “stretched” to the estuary by comparing the results of interpretations from before and after 2014 WSRS. Since there were many bends in the upper channel, hence the large bank had been eroded into many small area sand bars including small banks, bamboo-leaf sand bars and some other shapes of small sand bars. The existed large bamboo-leaf sand bars were eroded into an irregular shape, being more fragmented and complicated. The middle channel was relatively straightforward, hence its both sides sand bars were eroded smoothly, though most of them were scattered. This scouring made the bamboo-
leaf sand bar and the different small shape sand bars into the main sand bar types. This scouring achieved an obvious effect by eliminating large sand bars in the lower channel. Therefore the larger sand bars were eroded into broken small sand bars such as bamboo-leaf sand bars, elliptical sand bars and other shaped sand bars in the entire tail channel after 2014 WSRS.
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4.3. The landscape variations of sand bars due to 2014 WSRS
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The landscape indices were presented in the Table 3, according to the classified interpretation. The CONTAG in 2013 was 76.26, while it was 79.77 in 2015. The variation value was 3.51 and the change rate was 4.60%. The PD of estuarine sand bar was reduced, which indicating that the patches decreased and gradually became larger patches. The AI and the CONTAG of the river sand bars (except for the disappeared sickle-shaped sand bar) showed that WSRS may cause the sand bar distribution to be dispersed spatially, but the deposition location did not change very quickly. The river channel became smoother after this WSRS according to the results of the CONTAG.
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5. Discussions
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The channel sand bars have been constantly reshaped by irregular WSRSs. The sand bar is defined as a formed deposition which is exposed above the water surface (Li, 2013). It has a close correlation with the riverbed which could be reflected by the channel section, so it could be
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Bank Estuary sand bar Ellipse sand bar Bamboo-leaf sand bar Sickle-shaped sand bar Water Other shape sand bar Artificial facility
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Patch density (PD)
Aggregation index (AI)
2013
2015
Change rate (%)
2013
2015
Change rate (%)
3.14 0.76 0.16 0.44 0.11 0.89 0.15 0.04
5.00 0.56 1.09 1.24 0.00 2.83 0.89 0.04
59.01 −26.17 566.85 183.42 −100.00 218.49 512.80 0.00
98.06 99.57 96.56 98.60 98.99 99.58 98.76 90.42
97.41 99.65 92.31 95.00 0.00 99.62 96.96 94.56
−0.67 0.08 −4.41 −3.65 −100.00 0.05 −1.82 4.59
an useful indicator to further explore the influence by WSRS. Based on the monitoring data from the Q2, Q4, and Q7 sections in the study area, the changes of each section incised were obviously after the flood season, especially those from the Q4 were very significantly, meanwhile the channel where Q2 section erosion located happened mainly in the north bank and continuously been broadened (Cui, 2015). The main scouring were performed in the both sides of the channel and depositing in the middle of the channel. The similar results were presented if comparing Fig. 4(a1 ) with Fig. 4(a2 ). The major erosion happened in the bank of the north channel, while the sand bar mainly existed in the center of the channel due to this WSRS. Therefore, the remote sensing interpretation results of this study were further verified by the measured data from the channel sections. WSRSs promote the land reclamation effect in the YRM by increasing the probability of the hyperpycnal flow which is one of the transport pattern of suspended sediment off the river mouth (Song et al., 2018). During the transporting of suspended sediments off the river mouth, different transport patterns which depend on the SSC and salinity have unique accumulation methods. The hyperpycnal plume will form if the river density is less than the surrounding density when the river enters the sea, unless the hyperpycnal flow will form. Each WSRS carries a lot of suspended sediment into the sea, then it effectively increases the probability of the hyperpycnal flow, which form sand bars at the esturarine area (Xu et al., 2014). Each WSRS plays a key role in a direct effect to form and change the variation area of sand bars in YRM. And it can further explain the mechanism of such a form or change by analyzing the suspended sediment particle sizes and the corresponding changes within the near shore sections. The suspended sediment particle size was smaller and more difficult to deposit, due to the gradually implementation of WSRS which caused the downstream riverbed to be coarser, therefore it resulted in reducing the channel sand bar erosion efficiency and worsening the delta erosion resistance (Miao et al., 2016; Long et al., 2017). So these results explained that the YRM area existed erosion and the deposition concentration location in channel was stable in our study. Furthermore, the sediment was accumulated at 25–35 km (within the current estuary), and the estuary delta was gradually expanding to the sea areas on both sides of the YRM, but the deposition was in a dynamic change at the near shore (Wang et al.,
2015). And the small bay locates between YRM and the Gudong seawall is easy to deposit (Yu et al., 2015). According to our study result, the YRM was spread on both river banks, and mainly deposited on the west side (near the Gudong seawall). Although the average increase of the YRD area (which is larger than our study result) was 8.57 km2 in many years (2002–2015) according to the study from Li (2016), so the YRM variation area would be smaller than 8.57 km2 according to this study. And it can also indicated that the YRM variation area was smaller than before, because the extending length of Yellow River tail channel was slow during 1999–2010 (Zhang et al., 2019). The YRM variation area due to 2014 WSRS is similar with those data from other researchers. On the other hand, our study showed that the YRM area was still large, although WSRS implement interval was longer. So it indicated other sediment factors (expect WSRS factor) continued to offset some parts of the sea erosion. At the same time, the Yellow River estuary were modified by many dam projects that can further consolidate the deposition then enhance land reclamation effects. Therefore, our study conclusions been further confirmed by some previous study cases. The YRM accumulation position depended on the type of shear front which was influenced by the flood and ebb tide phases during WSRS period (Wang et al., 2006). The tides near YRD basically parallel to the shoreline and have back-and-force movements which the flood tide direction is southeast and the ebb tide direction is northwest (Yu et al., 2018). During the WSRS period, the sediment will be deposited in the southeastern YRM along the flood tide, and in the northwestern YRM along the ebb tide after the shear front. Then we inferred the variation area of sand bars in YRM was influenced by the ebb tide during 2014 WSRS period. However, it is difficult to accurately describe the shape and location of the YRM sand bars, and analyze the formation mechanism with the current data sets (Xu et al., 2014). High spatial resolution images could reflect more details on the sand bar shape after our result and analysis, and it is possible to present dynamic information by a series of long period high spatial resolution images. Each WSRS obviously changed the sand bar area and further profoundly affected the ecological environment in the YRD. A WSRS can directly affect the plant habitat of reeds on tidal flats or river channel. The patches, areas and numbers of both phragmites australis habitats and tidal flats are partly controlled by the fluxes of stream
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flow or sediment from Yellow River. And the heavy metals and arsenic (As) were carried to the YRD by WSRS (due to rapid agricultural development upstream of the YRD and heavy applications of agrochemicals and fertilizers), then the wetland habitat was seriously polluted (Bai et al., 2012). So WSRS obviously changed the morphological characteristics of the sand bar, and also affected the soil properties in the wetland (Bai et al., 2014). From which the breeding of red-crowned cranes can be influenced since their habitat types can be changed largely due to the annual or inter-annual variation caused by each WSRS (Bai et al., 2015; Wang, 2017; Cao et al., 2011). In addition, each WSRS also affects the growth and reproduction of marine life. The invertebrate assemblage was affected by the fluxes of stream flow and sediment from Yellow River at the section of 20 km from the estuary (Zhang et al., 2014). Each WSRS changes the sand bar dynamic balance by depositing or eroding, then changes the shape/area of each sand bar annually (Li, 2013), however the influence factors of each WSRS were complicated. These factors include runoff, sediment discharge, suspended sediment particle size and the boundary condition of the riverbed in the Yellow River (Yao, 2014; Wang, 2005). Furthermore, each WSRS implementation time issue is also crucial if comparing with the high-speed water flow experiment in the Colorado River of United States (Grams et al., 2010), which would also leads to change the sand bar largely. On the first day of the experiment, the sediment deposit was the largest, but the erosion exceeded the deposition after three days according to Grams’ study. Due to the high suspended solids concentration before the experiment, some researches indicated that it would result to form a larger sand bar, otherwise high-speed water flow may erode the sand bar and would not form sand bars (Wu et al., 2004; Yuan et al., 2012). These previous studies could help us improve the WSRS erosion efficiency in the river channel, furthermore better control the YRM area. The wetland conservation could guide a reasonable scientific strategy with a new cognition in the channel sand bars. It’s a scientific approach to discover the situation of channel deposition by the analysis of water level and sand bar interpretation result in channel. During the flooding, the administrators could monitor potential dangerous location which exists large area of sand bar in high water level. Meanwhile, the location of the diversion dam could be further optimized by the channel deposition. The better controlling of dams could improve the water diversion efficiency to solve the water shortage problem in the wetland during the WSRS period.
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6. Conclusions
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The sand bar landscape change were explored both in the Yellow River tail channel and its estuary before and after a WSRS in 2014. The high spatial resolution images were applied to quantitative extract and conduct comparative analysis on the change based on the comprehensive analysis of key influence factors such as tide level, water level, rainfall, and storm surge. From which, we carried out a further analysis of the potential impact from this WSRS on the land reclamation in The Yellow River Delta Wetland
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9
Reserve. The following conclusions can be drew from this study:
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(1) In general, the 2014 WSRS eroded the banks of the Yellow River tail channel and change into some small, broken sand bars. It caused the sand bar to be fragmented, though there was not a significant change in the location. The sand bar area within the tail river channel totally decreased 5.55 km2 due to this WSRS, and been scoured mainly in the straight channel (middle channel). The curved channel sand bar was vulnerably scoured, but the overall erosion efficiency was low from this WSRS which was prefer to form the new sand bars. (2) The estuarine sand bar in YRM had a large area deposition in west side and a small erosion area in east side after this WSRS, and with a tendency to union some small sand bars on the north side. The overall effect from this WSRS showed a movement to the sea from the channel sediment. Based on the area/shape change of the estuarine sand bars, the YRM area was increased by 2.08 km2 due to this WSRS, indicating an obvious effect on land reclamation in the estuarine area.
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At present, few study were carried out to evaluate and analyze the change in tail channel and YRM caused by the single WSRS or multiple WSRSs with the support of the remote sensing technology. But it is obvious that each WSRS plays a key role in alleviating deposition and land reclamation, and it changes the sand bars by activating with many other natural and artificial factors. We in this study carefully evaluated the WSRS effects by focusing especially on the land reclamation and the landscape change of the sand bar within the Yellow River tail channel and its estuary. It provided also a new perspective for the protection of coastal wetland resources and delta hydrological ecology.
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Declaration of Competing Interest
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The authors declare no conflict of interest. Ethical Statement The research was done according to ethical standards.
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Acknowledgement
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Thanks for the support of the National Key R&D Program (2017YFC0505903). Thanks for the help of GONG, Z., KE, Y., BAI, J.
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Please cite this article as: Y. Wang, Y. Fan and F. Bu et al., Quantifying effects of water and sediment regulation scheme on the sand bar in the yellow river estuary in 2014, Ecohydrology & Hydrobiology, https://doi.org/10.1016/j.ecohyd.2019.10.004
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