Variations in Channel Centerline Migration Rate and Intensity of a Braided Reach in the Lower Yellow River

remote sensing

Article Variations in Channel Centerline Migration Rate and Intensity of a Braided Reach in the Lower Yellow River

Junqiang Xia 1,*, Yingzhen Wang 1, Meirong Zhou 1, Shanshan Deng 1, Zhiwei Li 1 and Zenghui Wang 1,2

1 State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan 430072, China; [email protected] (Y.W.); [email protected] (M.Z.); [email protected] (S.D.); [email protected] (Z.L.); [email protected] (Z.W.) 2 College of Water Resources and Architectural Engineering, Northwest A & F University, Yangling 712100, China * Correspondence: [email protected]

Abstract: The Yellow River (YR) covers three climatic zones including arid region, semi-arid region and temperate monsoon region, with frequent appearance of flow intermittence in the Lower Yellow River (LYR) before 1999. Channel migration occurs frequently in braided rivers, which is a major focus of study in geomorphology and river dynamics. The braided reach in the LYR is featured by a complexly spatio-temporal variation in channel migration parameters owing to the varying condition of flow and sediment. It is crucial to investigate the migration characteristics of channel centerline for the sake of fully understanding channel evolution. A detailed calculation procedure is proposed to quantify migration rates and intensities of channel centerline at section- and reach-scales, using the measurements of remote sensing images and cross-sectional topography. Migration rates and intensities of channel centerline at section- and reach-scales from 1986 to 2016 were calculated, with the characteristics and key factors to control the migration intensity of channel centerline being Citation: Xia, J.; Wang, Y.; Zhou, M.; identified quantitatively. Calculated results indicate that: (i) the mean probability of centerline Deng, S.; Li, Z.; Wang, Z. Variations in migrating toward the left side was approximately equal to the probability of rightward migration Channel Centerline Migration Rate and Intensity of a Braided Reach in from a long-term sequence; (ii) the mean reach-scale migration rate of channel centerline was reduced the Lower Yellow River. Remote Sens. from 410 m/yr in 1986–1999 to 185 m/yr in 1999–2016, with a reduction of 55% owing to the 2021, 13, 1680. https://doi.org/ Xiaolangdi Reservoir operation in 1999, and the mean reach-scale migration intensity of channel 10.3390/rs13091680 centerline was decreased from 0.28 to 0.16 m/(yr·m), with a reduction of 43%; (iii) the incoming flow-sediment regime was a dominant factor affecting the degree of channel migration, although the Academic Editors: channel boundary conditions could influence the intensity of channel migration; and (iv) the reach- Angelica Tarpanelli and Jiaguang Li scale migration intensity of channel centerline can be written as a power function of the previous two-year average incoming sediment coefficient or fluvial erosion intensity, and the reach-scale Received: 19 March 2021 migration intensities of channel centerline calculated using the proposed relations are generally in Accepted: 22 April 2021 close agreement with the measurements over the period of 30 years. Published: 27 April 2021

Keywords: channel centerline; migration rate; migration intensity; braided reach; Lower Yellow River Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affil- iations. 1. Introduction Braided channel pattern is one of the common river patterns of natural rivers, which is widely distributed throughout the world. The Mengjin–Gaocun reach of the Lower Yellow River (LYR) in China and the Jamuna River in Bangladesh belong to typical braided Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland. rivers [1,2]. These rivers have a number of central bars or islands, which lead to multiple This article is an open access article channels at low flows, and such a planform geometry usually results in frequent lateral distributed under the terms and channel shifting. For example, the main-channel near the Liuyuankou section of the conditions of the Creative Commons braided reach in the LYR shifted to and fro along the north-south direction during the 1954 Attribution (CC BY) license (https:// flood season, with the migration amplitude greater than 6 km within 24 h [3]. The Jamuna creativecommons.org/licenses/by/ River is quite active, and the channel shifts frequently, with lateral migration rates greater 4.0/). than 500 m/yr [4]. These fluvial processes of braided rivers can cause unfavorable effects

Remote Sens. 2021, 13, 1680. https://doi.org/10.3390/rs13091680 https://www.mdpi.com/journal/remotesensing Remote Sens. 2021, 13, 1680 2 of 21

such as inducing the collapse of floodplain banks and threatening the safety of levees. Therefore, channel migration processes in braided rivers have aroused major concern in the study of river dynamics and geomorphology [5–7]. However, previous studies on channel evolution of braided rivers usually focused on investigations into the variation in incoming flow-sediment regime, channel aggradation and degradation, and adjustments in cross-sectional geometry [8–12], and seldom conducted a quantitative analysis of channel migration in braided rivers [13]. Channel migration plays a vital role in morphological changes of braided rivers, and usually includes various lateral shiftings of bankline, thalweg, main streamline and channel centerline [2,5,14]. A number of data sources derived from historical maps, cross-sectional topography and remote sensing images can be used to determine these changes [10,11,13,15–17]. Leys and Werritty [18] reported that an image processing software (ER Mapper) was applied to handle aerial photographs and scanned maps, in order to conduct a detailed analysis of planform changes of historical river channels, and the lateral shifting of channel centerline was estimated in the selected river reach of the Cleekhimin Burn. Richard et al. [16] adopted a geographic information system (GIS) from digitized aerial photographs of the active river channel without vegetation, and quantified the reach-scale lateral migration in the Cochiti reach of the Rio Grande over the period 1918–2001. Furthermore, many previous studies were conducted in the braided reach of the LYR. Wu et al. [19] examined the influence of artificial river regulation projects on lateral migration intensity of main- flow path, and it was found that the mean shifting rate of main-flow path was reduced from 425 m/yr in 1949–1960 to 160 m/yr in 1975–1990 owing to the implementation of river training works. Chen et al. [14] pointed out that lateral shifting of main streamline was dominant in channel planform adjustments of the braided reach, and an analysis of historical river regime maps indicated that the mean shifting rate of main streamline was reduced by 16–34% in response to the operation of the Xiaolangdi Reservoir (2000–2008), as compared with the value during the operation of the Sanmenxia Reservoir (1960–1964). A reach-averaged method proposed by Xia et al. [10] was used to determine the bankfull channel dimensions in the braided reach, with the reach-scale bankfull width increasing by about 400 m in 1999–2012, which approximately represented the magnitude of bankline retreat at reach-scale over the past 13 years. Furthermore, Li et al. [13] calculated the migration widths and intensities of channel thalweg at both section- and reach-scales in the braided reach in 1986–2015, and it was found that thalweg-migration width and intensity at reach-scale were reduced, respectively, by 47% and 35% after the initial operation of the reservoir in 1999. However, these traditional methods using a limited number of historical maps or cross-sectional topography are generally localized in extent, and hence cannot accurately investigate the detailed channel migration processes of alluvial rivers [20–22]. As a multi-temporal, multi-spectral, cost-effective and high-resolution information source, the technology of remote sensing has been widely used to investigate changes of channel morphology in alluvial rivers, with specified methodologies or software being developed to quantify channel properties [17,21,23–26]. Rowland et al. [16] presented the methodologies of a set of analysis algorithms to determine riverbank erosion and accretion, which can be used to analyze the planform variations of various river morpholo- gies. Remote sensing technology can be used to quantify planform changes in alluvial rivers, covering channel centerline migration and riverbank shifting [7,20,21,27–30]. The spatio-temporal changes of riverbanks and channel centerlines in the active Yellow River Delta were systematically quantified, using the technologies of satellite remote sensing and GIS [20]. Peixoto et al. [6] used Landsat TM imagery to investigate spatial and temporal migration of three reaches in western Brazilian Amazonia over a 21-year period, and found that the rates of annual lateral erosion and vegetated land accretion were well-balanced along these three reaches. Using eight dry-season satellite images of the Ganges River in Bangladesh, morphological changes in this reach were assessed, and the bankline shifting rates of the river were also quantified under four different periods in 1973–2009, with the results indicating that both the left and right riverbanks underwent significant migration Remote Sens. 2021, 13, 1680 3 of 21

processes in response to varying rates of bank erosion and accretion [31]. Various satellite imageries were employed to quantify the planform migration of the Lower Jingjiang Reach of the Middle Yangtze River, and the mean channel centerline migration rate decreased from 31.1 m/yr in 1983–1988 to 11.6 m/yr in 2009–2013 [21]. Kong et al. [17] investigated planform changes in the LYR in 1987–2017 using multi-temporal remotely sensed images, and it was found that the mean migration rate of channel centerline in the braided reach varied around 30–100 m/yr after the Xiaolangdi Reservoir operation. Therefore, an inte- gration of remote sensing and GIS can be used to quantify channel migration processes in alluvial rivers, covering the lateral shifting rates of channel centerline and bankline. However, these studies are seldom integrated with the results obtained from traditional approaches based on the discipline of river dynamics, and therefore they cannot present the quantitative relationships between channel morphometric parameters and incoming flow-sediment factors. The regime of flow and sediment was altered dramatically in the braided reach owing to the operation of the Xiaolangdi Reservoir [8,10,11,14,32]. In consequence, significant channel evolution occurred, including continuous channel degradation and remarkable migration of channel centerline. Therefore, it is appropriate to determine the spatio- temporal variations in migration rate and intensity of channel centerline in the braided reach, for the sake of fully understanding the characteristics of fluvial processes. In this study, a fusion approach of data from multiple sources at various scales has been adopted to investigate the spatio-temporal variations in migration rate and intensity of channel centerline in the braided reach over the period from 1986 to 2016. These multiple- source data cover satellite images, cross-sectional topography, discharges and sediment concentrations at different hydrometric sections. The major aims of the current study are: (i) to develop an integrated procedure to determine the migration rate and intensity of channel centerline at reach-scale; (ii) to estimate the morphometric parameters at reach- scale to depict the channel morphology; and (iii) to analyze the key factors that influence the migration intensity of channel centerline and establish empirical relationships between migration intensity and different flow-sediment factors based on investigations of their varying characteristics.

2. Study Area The 5464 km long Yellow River originates from the Bayankala Mountains and flows from west to east through nine administrative regions, and finally extends eastward to the Bohai Sea [33–35], which covers three climatic zones including arid region, semi-arid region and temperate monsoon region. Before emptying into the Bohai Sea in Shandong Province, the 786-km long Lower Yellow River flows from Mengjin (abbreviated to MJ) in Henan Province of central China to the northeast across the North China Plain, with a basin area of only 23,000 km2 accounting for a mere 3% of the total area (Figure1a). The total drop in elevation of the LYR is 93.6 m, with an average channel slope of 0.012%. The LYR receives water and sediment from the mainstream of the Middle Yellow River and two tributaries of the Yiluo River and the Qin River. Excessive sediment deposition in the LYR caused the riverbed level in Kaifeng, Henan Province to be 10 m higher than the level around the surrounding zone. There are three distinct reaches in the LYR according to their different geomorphological characteristics, including a braided reach from Mengjin to Gaocun, a transitional reach from Gaocun to Taochengpu and a meandering reach from Taochengpu to Lijin in proper sequence. There is a narrow main-channel zone with the width ranging between 0.5 and 4.5 km in the LYR, with the area of main-channel zone accounting for about 20% of the total channel area; however, the widths of two floodplains on both sides vary from 5 to 20 km. The braided reach is relatively straight, with the average curvature coefficient of 1.15 and the planform geometry characterised by alternated wide and narrow sub-reaches, with rapid morphological changes often occurring in this reach. Three hydrometric stations have been set up in the braided reach, including Huayuankou, Jiahetan and Gaocun, which can be, respectively, abbreviated to HYK, JHT and GC. Based Remote Sens. 2021, 13, x FOR PEER REVIEW 4 of 23

on both sides vary from 5 to 20 km. The braided reach is relatively straight, with the average curvature coefficient of 1.15 and the planform geometry characterised by alternated wide and narrow sub-reaches, with rapid morphological changes often occurring in this reach. Three hydrometric stations have been set up in the braided reach, including Huayuankou, Jiahetan and Gaocun, which can be, respectively, abbreviated to HYK, JHT and GC. Based on the difference in geographical positions and boundary conditions, the braided reach is commonly divided into three sub-reaches, including the upper sub-reach from MJ to HYK, the middle sub-reach from HYK to JHT, and the lower sub-reach from JHT to GC (Figure 1b). In general, the braided reach is characterised by a wide and shallow cross-sectional geometry, a frequently shifting main-channel, and a rapid changing chan- Remote Sens. 2021, 13, 1680 4 of 21 nel planform [19,33]. In the late 1990s, a large-scale comprehensive water conservancy project, the Xiaolangdi Reservoir, was constructed, which also has the other functions of water sup- onply, the irrigation difference and in power geographical generation, positions in order and to boundary control extreme conditions, floods the and braided reduce reach the issedimentation commonly divided rate in into the threeLYR. sub-reaches, Due to a large including quantity the upperof sediment sub-reach trapped from in MJ the to HYK,Xiaolangdi the middle Reservoir sub-reach since fromOctober HYK 1999, to JHT, the andflows the with lower low sub-reach sediment from concentrations JHT to GC (Figurewere released1b). In general,into the LYR. the braided The LYR reach therefore is characterised underwent by continuous a wide and channel shallow degrada- cross- sectionaltion [10,11]. geometry, Furthermore, a frequently the degree shifting of channel main-channel, migration and adjusted a rapid due changing to the channelvarying planformregime of [water19,33]. discharge and sediment concentration.

FigureFigure 1.1. Maps of the Lower Yellow River: ( (aa)) Planview Planview of of the the YR; YR; and and ( (bb) )Remote Remote sensing sensing image image showingshowing thethe braidedbraided reachreach inin thethe LYR.LYR.

InFlow the intermittence late 1990s, a refers large-scale to the comprehensivephenomenon of waterwater conservancyshortages at some project, sections the Xi- of aolangdia large river Reservoir, during wascertain constructed, time periods, which with also the has specific the other performance functions of of low water water supply, dis- irrigationcharge and and dry power river generation,bed. Precipitation in order has to been control low extreme in most floods areas andof the reduce Yellow the River sedi- mentationbasin since rate the in1970s, the LYR. and Duethe tosituation a large has quantity deteriorated of sediment even trapped further insince the Xiaolangdi1990. Since Reservoirthere is a substantial since October increase 1999, in the agricultural flows with irrigation low sediment water, concentrations the downstream were runoff released has intodropped the LYR. sharply, The LYRwhich therefore has caused underwent the occurrence continuous of flow channel intermittence degradation with [10 extremely,11]. Fur- thermore,low discharges the degree in the ofLYR. channel Relevant migration data show adjusted that since due to the the 1960s, varying the regimeannual ofrunoff water of dischargethe LYR into and the sediment sea has concentration. gradually decreased from 57.5 billion m3 in the 1960s to 18.7 billion Flowm3 in the intermittence 1990s, with refers a reduction to the phenomenonof 67%. Frequent of waterseasonal shortages flow intermittence at some sections in the ofLYR a large began river in the during early certain1970s, especially time periods, in the with late the1990s. specific In 1997, performance the period ofof lowflow water inter- dischargemittence reached and dry 226 river days bed. at Precipitationthe section of has Lijin been in the low LYR, in most andareas the phenomenon of the Yellow of River flow basinintermittence since the occurred 1970s, and at the the section situation of JHT, has wi deterioratedth the period even of very further low sincedischarges 1990. lasting Since there18 days. is a After substantial 1999, the increase phenomenon in agricultural of flow irrigation intermittence water, did the not downstream occur in the runoff LYR, hasow- droppeding to various sharply, measures which hassuch caused as the theoperatio occurrencen of the of Xiaolangdi flow intermittence Reservoir, with and extremely the estab- lowlishment discharges of water in regulation the LYR. Relevant rules. data show that since the 1960s, the annual runoff 3 of the LYR into the sea has gradually decreased from 57.5 billion m in the 1960s to 18.7 billion m3 in the 1990s, with a reduction of 67%. Frequent seasonal flow intermittence in the LYR began in the early 1970s, especially in the late 1990s. In 1997, the period of flow intermittence reached 226 days at the section of Lijin in the LYR, and the phenomenon of flow intermittence occurred at the section of JHT, with the period of very low discharges lasting 18 days. After 1999, the phenomenon of flow intermittence did not occur in the LYR, owing to various measures such as the operation of the Xiaolangdi Reservoir, and the

establishment of water regulation rules.

3. Materials and Methods 3.1. Data Sources 3.1.1. Hydrological Data Hydrological data at three hydrometric stations over the period 1986–2016 were collected, covering daily mean discharges and sediment concentrations, and ﬂood-season and hydrological-year average discharges and sediment concentrations were calculated. In general, the regime of ﬂow and sediment entering the braided reach can be described Remote Sens. 2021, 13, x FOR PEER REVIEW 5 of 23

3. Materials and Methods 3.1. Data Sources 3.1.1. Hydrological Data Hydrological data at three hydrometric stations over the period 1986–2016 were collected, covering daily mean discharges and sediment concentrations, and flood-season and hydrological-year average discharges and sediment concentrations were calculated. In general, the regime of flow and sediment entering the braided reach can be described approximately by the water discharge and sediment concentration at the Huayuankou station (Figure 2). During the reservoir operation period (1999–2016), the annual mean water volume at HYK was 25.4 × 109 m3/yr, with the mean value in flood seasons comprising 36%, which was only 6.5% lower than the value of 27.7 × 109 m3/yr in 1986–1999. However, the sediment amount entering the LYR decreased dramatically because a large quantity of sediment was detained by the Xiaolangdi Reservoir, with the accumulated deposition volume of 3.90 × 109 t. The average annual sediment discharge at HYK declined from 0.74 × 109 t/yr (1986–1999) to 0.06 × 109 t/yr (1999–2016), with the mean value in flood seasons accounting, respectively, for 96% and 95% during these two periods. Before the Xiaolangdi Reservoir operation, the variation in water volume was not totally consistent with the variation in sediment discharge. For example, the annual water volume in 1988 (34.9 × 109 m3) was smaller than that in 1989 (40.3 × 109 m3), and contrarily the annual sediment discharge in 1988 was significantly greater than that in 1989. After the reservoir operation, the annual water volume entering the LYR changed slightly with a reduction of 8%, whereas there was a huge reduction of 92% in annual sediment discharge. Furthermore, Remote Sens. 2021 13 , , 1680 it should be noted that the non-equilibrium suspended load transport had an overwhelm-5 of 21 ing domination over the bed load, mainly because the mean ratio of suspended load to total load was greater than 99.5%, according to the observed data presented in the previ- ousapproximately analysis [36]. by Therefore, the water the discharge effect of andbed load sediment transport concentration was neglected at the in Huayuankouthe following analysis.station (Figure 2).

FigureFigure 2. 2. VariationVariation in the in condition the condition of flow ofand ﬂow sediment and at sediment HYK: (a) atwater HYK: volume; (a) water (b) sediment volume; discharge.(b) sediment discharge.

3.1.2.During Cross-Sectional the reservoir Topography operation period (1999–2016), the annual mean water volume 9 3 at HYKProfiles was at 25.4 28× sedimentation10 m /yr, with sections the mean measured value after in ﬂood the seasonsflood seasons comprising along 36%, the × 9 3 braidedwhich was reach only were 6.5% obtained, lower than as well the as value the amounts of 27.7 of10 cumulativem /yr in 1986–1999.bed deformation However, vol- umethe sediment in the braided amount reach entering and the the whole LYR decreasedLYR from 1986 dramatically to 2016. because a large quantity of sediment was detained by the Xiaolangdi Reservoir, with the accumulated deposition volume of 3.90 × 109 t. The average annual sediment discharge at HYK declined from 0.74 × 109 t/yr (1986–1999) to 0.06 × 109 t/yr (1999–2016), with the mean value in ﬂood seasons accounting, respectively, for 96% and 95% during these two periods. Before the

Xiaolangdi Reservoir operation, the variation in water volume was not totally consistent with the variation in sediment discharge. For example, the annual water volume in 1988 (34.9 × 109 m3) was smaller than that in 1989 (40.3 × 109 m3), and contrarily the annual sediment discharge in 1988 was signiﬁcantly greater than that in 1989. After the reservoir operation, the annual water volume entering the LYR changed slightly with a reduction of 8%, whereas there was a huge reduction of 92% in annual sediment discharge. Furthermore, it should be noted that the non-equilibrium suspended load transport had an overwhelming domination over the bed load, mainly because the mean ratio of suspended load to total load was greater than 99.5%, according to the observed data presented in the previous analysis [36]. Therefore, the effect of bed load transport was neglected in the following analysis.

3.1.2. Cross-Sectional Topography Profiles at 28 sedimentation sections measured after the flood seasons along the braided reach were obtained, as well as the amounts of cumulative bed deformation volume in the braided reach and the whole LYR from 1986 to 2016. In order to better monitor channel deformation, sedimentation sections have been set up along the LYR, with the topographic surveys at cross-sections being conducted prior and post to each flood season [10]. As shown in Figure3a, the mean bed elevation at the Liuyuankou section of the braided reach was risen, caused by the continuous channel aggradation during the period 1986–1999, with the main-channel shrinking remarkably and the corresponding mean bed level elevated by 1.28 m. However, both bank erosion and bed incision occurred at Liuyuankou during the period 1999–2016, with the corresponding bankfull depth increasing from 1.40 to 3.45 m because of the recent continuous bed incision Remote Sens. 2021, 13, x FOR PEER REVIEW 6 of 23

In order to better monitor channel deformation, sedimentation sections have been set up along the LYR, with the topographic surveys at cross-sections being conducted prior and post to each flood season [10]. As shown in Figure 3a, the mean bed elevation at the Liuyuankou section of the braided reach was risen, caused by the continuous channel aggradation during the period 1986–1999, with the main-channel shrinking remarkably and Remote Sens. 2021, 13, 1680 the corresponding mean bed level elevated by 1.28 m. However, both bank erosion6 of 21 and bed incision occurred at Liuyuankou during the period 1999–2016, with the corresponding bankfull depth increasing from 1.40 to 3.45 m because of the recent continuous bed (Figureincision3b). (Figure The number 3b). The of number sedimentation of sedimentation sections displayed sections a graduallydisplayed increasing a gradually trend increas- aftering 1999,trend which after greatly1999, which improved greatly the monitor improved accuracy the ofmonitor channel accuracy deformation. of channel Before the defor- implementationmation. Before ofthe the implementation Xiaolangdi Reservoir, of the there Xiaolangdi were initially Reservoir, 28 sedimentation there were sections, initially 28 withsedimentation an average sections, distance with between an average two consecutive distance sections between of two about consecutive 10 km. After sections the of reservoirabout 10 operation km. After in Octoberthe reservoir 1999, the operation sedimentation-section in October 1999, number the increased sedimentation-section gradually, andnumber it was increased finally equal gradually, to 145 after and the it was year finally of 2005, equal with ato mean 145 after spacing the of year approximately of 2005, with a 2mean km. Usingspacing these of approximately cross-sectional 2 profiles km. Using surveyed these repeatedly, cross-sectional it is easy profiles to obtain surveyed the re- volumepeatedly, of bedit is deformationeasy to obtain over the a volume specified of period. bed deformation over a specified period.

(a) 84 Wbf2 82 Wbf1

80 Hbf1

78 Hbf2 Wbf1= 1986.2 m 1986.10

Bed (m) Bed elevation 76 W = 828.0 m bf2 1999.10 74 (b) 841500 2500 3500Wbf3 4500 5500 Distance from the left bank (m) Wbf2 80 Hbf3 Hbf2 76 Hbf2= 1.40 m 1999.10 Hbf3= 3.45 m 2016.10 Bed elevation (m) Bed elevation 72 1500 2000 2500 3000 3500 4000 4500 5000 5500 Distance from the left bank (m)

FigureFigure 3. 3.Temporal Temporal variations variations in thein the cross-sectional cross-sectiona proﬁlel profile at the at Liuyuankou the Liuyuankou section: section: (a) during (a) during the periodthe period 1986–1999; 1986–1999; and ( band) during (b) during the period the period 1999–2016. 1999–2016.

TheThe braided braided reach reach in in the the LYR LYR underwent underwent two tw contrastingo contrasting stages stages of bed of depositionbed deposition and erosion in 1986–2016, leading to significant variations in lateral shifting of bankline, and erosion in 1986–2016, leading to significant variations in lateral shifting of bankline, thalweg, main streamline and channel centerline. The continuous process of channel thalweg, main streamline and channel centerline. The continuous process of channel ag- aggradation in 1986–1999 was caused by the unfavourable matching relationship between watergradation discharge in 1986–1999 and the corresponding was caused sedimentby the un concentration,favourable matching and the cumulative relationship volume between ofwater sediment discharge deposition and the was corresponding 1.51 × 109 m3 during sedime thisnt period,concentration, which comprised and the 71.9%cumulative of the vol- totalume value of sediment in the LYR deposition (Figure4). was However, 1.51 × 10 significant9 m3 during channel this degradationperiod, which occurred comprised in this 71.9% reachof the after total the value onset in of the reservoirLYR (Figure in 1999, 4). withHowever, the cumulative significant channel channel scour degradation volume of oc- 1.38curred× 10 in9 mthis3 comprising reach after 72.2% the onset of the of total the value reservoir in the in LYR. 1999, The with flood-season the cumulative cumulative channel volumescour volume of channel of 1.38 scour × 10 was9 m 0.653 comprising× 109 m3, 72.2% which wasof the approximately total value in equivalent the LYR. The to the flood- valueseason of cumulative 0.72 × 109 m volume3 in non-flood of channel seasons. scour Since was the 0.65 degree × 109 ofm3 channel, which deformationwas approximately in 9 3 Remote Sens. 2021, 13, x FOR PEER REVIEWfloodequivalent seasons to was the ofvalue equal of importance 0.72 × 10 m as thatin non-flood in non-flood seasons. seasons, Since the hydrological-yearthe degree of channel7 of 23 averagedeformation parameters in flood of seasons flow and was sediment of equal over importance the period as 1986–2016 that in non-flood were used seasons, in the the followinghydrological-year analysis. average parameters of flow and sediment over the period 1986–2016 were used in the following analysis. 2.5 )

3 LYR Reservoir operation m

9 2 Braided reach 1.91 1.5 2.10 (1986-1999) (1999-2016) 1 1.38 0.5 1.51 (1986-1999) (1999-2016) Cumulative channel Cumulative 0 evolution volume (10 evolution 1986 1991 1996 2001 2006 2011 2016 Year FigureFigure 4. Cumulative volume volume of of bed bed deformation deformation in thein the braided braided reach reach and theand LYR the during LYR during the period the period1986–2016. 1986–2016.

3.1.3. Remote Sensing Images Remote sensing images are characterized by real-time, accurate, and intuitive information, which are often used to recognize land-water boundaries to depict the process of channel migration [21]. Combined with the GIS technique, remote sensing images in different periods can be compared, with the characteristics of channel migration being determined for a long time series, which can greatly improve the calculation accuracy of channel migration. Therefore, Thematic Mapper (TM), Enhanced Thematic Mapper (ETM+) and Operational Land Imager (OLI) Landsat scenes with a spatial resolution of 30 m over the period from 1986 to 2016 were collected in this study. Figure 5 shows the local satellite images near the sections of HYK, JHT and GC at different times. These satellite images are archived by the EROS Center of USGS (https://glovis.usgs.gov/) (20 June 2020).

Figure 5. Remote sensing images in different years near the sections of: (a) HYK; (b) JHT; and (c) GC.

Since there are many remote sensing images in a hydrological year for a specified satellite sensor, it is necessary to select the most representative images. It is difficult to distinguish the main-channel and floodplain zones during flood seasons owing to large water discharges and high-water levels. However, the post-flood main-channel zone can be detected easily from the remote sensing images, based on the fact that the flow returns to the main-channel zone due to the decreased water discharges. Therefore, the post-flood remote sensing images were selected to extract the banklines of the braided reach. Due to a large area of the study reach, one remote sensing image could not cover the whole study

Remote Sens. 2021, 13, x FOR PEER REVIEW 7 of 23

2.5 )

3 LYR Reservoir operation m

9 2 Braided reach 1.91 1.5 2.10 (1986-1999) (1999-2016) 1 1.38 0.5 1.51 (1986-1999) (1999-2016) Cumulative channel Cumulative 0 evolution volume (10 evolution 1986 1991 1996 2001 2006 2011 2016 Year Figure 4. Cumulative volume of bed deformation in the braided reach and the LYR during the period 1986–2016.

Remote Sens. 2021, 13, 1680 7 of 21 3.1.3. Remote Sensing Images Remote sensing images are characterized by real-time, accurate, and intuitive information, which are often3.1.3. Remote used to Sensing recognize Images land-water boundaries to depict the process of channel migration [21].Remote Combined sensing with images the are GIS characterized technique, by real-time, remote accurate, sensing and images intuitive in infor- dif- mation, which are often used to recognize land-water boundaries to depict the process ferent periods can beof channelcompared, migration with [21 the]. Combined characteristics with the GISof channel technique, migration remote sensing being images deter- in mined for a long timedifferent series, periods which can can be compared, greatly improve with the characteristics the calculation of channel accuracy migration of beingchan- nel migration. Therefore,determined Thematic for a long Mapper time series, (TM), which Enhanced can greatly improve Thematic the calculation Mapper accuracy(ETM+) of channel migration. Therefore, Thematic Mapper (TM), Enhanced Thematic Mapper and Operational Land(ETM+) Imager and Operational (OLI) Landsat Land Imager scen (OLI)es with Landsat a spatial scenes with resolution a spatial resolution of 30 m ofover 30 the period from 1986m overto 2016 the period were from collected 1986 to 2016in this were study. collected Figure in this study.5 shows Figure the5 shows local the satellite local images near the sectionssatellite of images HYK, near JHT the and sections GC of at HYK, different JHT and times. GC at These different satellite times. These images satellite are images are archived by the EROS Center of USGS (https://glovis.usgs.gov/) (accessed on archived by the EROS20 June Center 2020). of USGS (https://glovis.usgs.gov/) (20 June 2020).

Figure 5.Figure Remote 5. Remote sensing sensing images images in differentdifferent years years near thenear sections the sections of: (a) HYK; of: (b ()a JHT;) HYK; and ( c()b GC.) JHT; and (c) GC. Since there are many remote sensing images in a hydrological year for a specified satellite sensor, it is necessary to select the most representative images. It is difficult to Since there aredistinguish many remote the main-channel sensing andimages floodplain in a zones hydrological during flood year seasons for owing a specified to large satellite sensor, it iswater necessary discharges to and select high-water the most levels. representative However, the post-flood images. main-channel It is difficult zone can to be detected easily from the remote sensing images, based on the fact that the flow returns distinguish the main-channelto the main-channel and zonefloodplain due to the zones decreased during water discharges.flood seasons Therefore, owing the post-flood to large water discharges andremote high-water sensing images levels. were However, selected to extractthe post-flood the banklines main-channel of the braided reach. zone Due can be detected easily fromto a large the arearemote of the sensing study reach, images, one remote based sensing on the image fact could that not the cover flow the returns whole study area, and two satellite images were combined to study the characteristics of channel to the main-channelmigration zone due in the to braidedthe decreased reach. The water detailed discharges. information of Therefore, the selected satellite the post-flood images is remote sensing imagesshown were in Table selected1. to extract the banklines of the braided reach. Due to a large area of the study reach, one remote sensing image could not cover the whole study

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Table 1. (a) Characteristics of the selected satellite images (Path Row is 123). (b). Characteristics of the selected satellite images (Path Row is 124).

No Acquisition Water Level Water Level Water Level Image Type Spatial Date at HYK (m) at JHT (m) at GC (m) Resolution (m) Path Row 1 19861203 91.54 72.96 60.54 Landsat5-TM 30 123 2 19871222 91.45 73.03 60.72 Landsat5-TM 30 123 3 19881122 92.05 73.1 60.62 Landsat5-TM 30 123 4 19891125 92.32 73.47 61.03 Landsat5-TM 30 123 5 19900824 92.41 73.73 61.48 Landsat5-TM 30 123 6 19911030 92.37 73.05 60.28 Landsat5-TM 30 123 7 19921016 92.64 73.8 61.45 Landsat5-TM 30 123 8 19931019 92.66 74.04 61.43 Landsat5-TM 30 123 9 19941022 92.72 75.92 61.1 Landsat5-TM 30 123 10 19951110 92.84 75.83 61.45 Landsat5-TM 30 123 11 19961027 92.47 75.83 61.25 Landsat5-TM 30 123 12 19971030 92.27 75.22 60.59 Landsat5-TM 30 123 13 19981017 92.69 75.19 61.7 Landsat5-TM 30 123 14 19991129 92.42 75.78 62.15 Landsat7-ETM+ 30 123 15 20001030 92.64 76.2 62.56 Landsat7-ETM+ 30 123 16 20011017 92.46 76.04 62.27 Landsat7-ETM+ 30 123 17 20021004 92.02 76.17 62.12 Landsat7-ETM+ 30 123 18 20031226 91.57 75.08 61.58 Landsat7-ETM+ 30 123 19 20041025 90.98 74.62 60.69 Landsat7-ETM+ 30 123 20 20051215 91.04 75.05 60.74 Landsat7-ETM+ 30 123 21 20061015 91.20 74.41 60.35 Landsat7-ETM+ 30 123 22 20071103 91.04 74.39 60.75 Landsat7-ETM+ 30 123 23 20081121 90.61 73.89 59.92 Landsat7-ETM+ 30 123 24 20091023 90.73 73.63 60 Landsat7-ETM+ 30 123 25 20101229 90.48 73.69 59.7 Landsat7-ETM+ 30 123 26 20111114 90.92 73.96 60.29 Landsat7-ETM+ 30 123 27 20121031 89.96 73.25 59.68 Landsat7-ETM+ 30 123 28 20131010 90.12 73.36 59.62 Landsat8-OLI 30 123 29 20141114 89.58 72.89 59.48 Landsat8-OLI 30 123 30 20151016 88.87 72.34 58.92 Landsat8-OLI 30 123 31 20161103 89.19 72.86 59.11 Landsat8-OLI 30 123 b

No Acquisition Water Level Water Level Water Level Image Type Spatial Date at HYK (m) at JHT (m) at GC (m) Resolution (m) Path Row 1 19861110 91.44 72.69 60.39 Landsat5-TM 30 124 2 19871113 91.6 73.15 60.91 Landsat5-TM 30 124 3 19881115 92.04 73.2 60.61 Landsat5-TM 30 124 4 19891204 92.34 73.75 61.35 Landsat5-TM 30 124 5 19901121 92.36 73.76 61.49 Landsat5-TM 30 124 6 19911007 92.34 73.3 60.94 Landsat5-TM 30 124 7 19921025 92.46 73.46 61.16 Landsat5-TM 30 124 8 19931231 92.47 73.5 61.2 Landsat5-TM 30 124 9 19941031 92.83 75.87 61.16 Landsat5-TM 30 124 10 19951103 92.74 75.78 61.36 Landsat5-TM 30 124 11 19961004 92.6 76.01 61.43 Landsat5-TM 30 124 12 19971007 92.62 75.77 61.71 Landsat5-TM 30 124 13 19981127 92.59 75.2 61.71 Landsat5-TM 30 124 14 19991122 92.46 75.89 62.22 Landsat7-ETM+ 30 124 15 20001226 92.5 76.12 62.49 Landsat7-ETM+ 30 124 16 20011111 91.87 75.36 61.88 Landsat7-ETM+ 30 124 17 20021013 92.01 76.07 62.03 Landsat7-ETM+ 30 124 18 20031101 92.36 75.65 61.69 Landsat7-ETM+ 30 124 19 20041002 90.91 74.83 60.87 Landsat7-ETM+ 30 124 20 20051208 91.15 75.06 60.77 Landsat7-ETM+ 30 124 21 20061008 91.29 74.44 60.48 Landsat7-ETM+ 30 124 22 20071128 91.15 74.18 60.43 Landsat7-ETM+ 30 124 23 20081130 90.5 73.82 59.9 Landsat7-ETM+ 30 124 24 20091016 90.66 73.82 60.06 Landsat7-ETM+ 30 124 25 20101104 90.51 73.77 59.84 Landsat7-ETM+ 30 124 26 20111006 91.24 74.18 60.61 Landsat7-ETM+ 30 124 27 20121008 90.59 73.77 60.22 Landsat7-ETM+ 30 124 28 20131019 90.48 73.77 59.97 Landsat8-OLI 30 124 29 20141006 89.63 73.05 59.52 Landsat8-OLI 30 124 30 20151009 88.9 72.42 58.85 Landsat8-OLI 30 124 31 20161214 88.84 72.2 58.77 Landsat8-OLI 30 124 Remote Sens. 2021, 13, 1680 9 of 21

3.2. Methods A detailed calculation procedure is proposed herein to quantify migration rates and intensities of channel centerline at section- and reach-scales, using a fusion approach of data from multiple sources at various scales, obtained from the measurements of hydrological data, cross-sectional topography and remote sensing images. This proposed procedure is illustrated in Figure6, which covers the calculations of characteristic parameters repre- Remote Sens. 2021, 13, x FOR PEER REVIEWsenting the ﬂow-sediment condition, bankfull channel dimensions (width and depth)10 of 23 at

reach-scale, section-scale channel migration rate, and reach-scale channel migration rate and intensity.

Figure 6. Flow chart of calculating the migration rate and intensity of channel centerline. Figure 6. Flow chart of calculating the migration rate and intensity of channel centerline. 3.2.1. Hydrological Data 3.2.1. HydrologicalPrevious studies Data show that channel evolution is closely associated with the altered regimesPrevious of flow studies and show sediment that inchannel alluvial evolution rivers [10 is, 11closely,37]. Theassociated incoming with flow-sediment the altered regimescondition of flow in a study and sediment reach is generally in alluvial expressed rivers [10,11,37]. by a specified The functionincoming of flow-sediment the mean water conditiondischarge in anda study the reach corresponding is generally sediment expressed concentration. by a specified In function this study, of the a characteristicmean water dischargeparameter and termed the corresponding as fluvial erosion sediment intensity concen (Fi) istration. used to In depict this study, the incoming a characteristic condition

parameterof ﬂow and termed sediment, as fluvial which erosion can be intensity written ( inFi this) is used form: to depict the incoming condition

of flow and sediment, which can be written in2 this form:4 Fi = Qi /Si /10 (1) = 24 FQSiii()//10 (1) where Qi is the annual mean water discharge over the ith hydrological year; and Si is the wherecorresponding Qi is the concentrationannual mean water of suspended discharge load. over the ith hydrological year; and Si is the correspondingIt is known concentration to us that sediment of suspended transport load. is mainly composed of suspended load insteadIt is known of bed to load us inthat an sediment alluvial rivertranspor sucht is as mainly the LYR. composed The relationship of suspended between load in- sed- steadiment of dischargebed load in (Q ans) alluvial and water river discharge such as the (Q )LYR. has beenThe relationship developed inbetween previous sediment studies. dischargeSuch a relation (Qs) and is water usually discharge deﬁned (Q as) sedimenthas been developed rating curve in (SRC).previous It commonlystudies. Such takes a relationthe form is usually of a power defined function, as sediment and the rating general curve relationship (SRC). It commonly between themtakes the is expressed form of b a powerby Qs = function, aQ [38– and43]. Syvitskithe general et al.relationship [39] have statedbetween that them the is SRC expressed is the statistical by Qs = aQ relation-b [38– 43].ship Syvitski between et al. suspended [39] have sediment stated that discharge the SRC and is the water statistical discharge relationship and, therefore, between the SRCsus- is pendednot only sediment for sediment discharge that doesand notwater participate discharge in and, morphological therefore, the processes. SRC is Previousnot only stud-for sedimenties also regardedthat does the not parameter participatea asin anmorpho indexlogical of erosion processes. severity Previous in a river studies channel also [44 re-,45], garded the parameter a as an index of erosion severity in a river channel [44,45], and the exponent b is used to depict the erosion power of a river, both of which reveal that the SRC is related to morphological processes. In the study, the hydrological data measured under a quasi-equilibrium state in the LYR were collected to calibrate the parameters of the SRC. In this state, the channel geometry generally keeps unchanged and the value of sediment concentration can be approximately equivalent to the magnitude of sediment transport capacity. The calibrated exponent b in SRC was roughly equal to 2.0 under a quasi-equilibrium state at sections of HYK and JHT in the LYR (Qs = aQ2 in Figure 7), with the determination coefficient (R2) between them of 0.66 and 0.70, respectively. It can be seen that the correlations are not very high

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and the exponent b is used to depict the erosion power of a river, both of which reveal that the SRC is related to morphological processes. In the study, the hydrological data measured under a quasi-equilibrium state in the LYR were collected to calibrate the parameters of the SRC. In this state, the channel Remote Sens. 2021, 13, x FOR PEER REVIEWgeometry generally keeps unchanged and the value of sediment concentration can be 11 of 23

approximately equivalent to the magnitude of sediment transport capacity. The calibrated exponent b in SRC was roughly equal to 2.0 under a quasi-equilibrium state at sections of 2 2 HYK and JHT in the LYR (Qs = aQ in Figure7), with the determination coefficient ( R ) becausebetween themthe sediment of 0.66 and transport 0.70, respectively. capacity It canis al beso seen affected that the by correlations other factors, are not but very the water dischargehigh because is thea dominant sediment transportfactor. Therefore, capacity is the also sediment affected by transport other factors, capacity but the can water be written asdischarge S* ≈ Qs is/Q a = dominant aQ1, and factor. then the Therefore, base of the the sediment fluvial er transportosion intensity capacity canis in be the written form of S*/S 1 =as aQS*/≈S. QIns/ orderQ = aQ to, andaccount then thefor base the ofeffect the fluvialof wa erosionter discharge intensity on is channel in the form deformation, of S*/S the fluvial= aQ/S .erosion In order intensity to account is for defined the effect by of multiplying water discharge the water on channel discharge deformation, (Q) on the this basis, fluvial erosion intensity is defined by multiplying the water discharge (Q) on this basis, that that is, Fi = Qi2/S, with the coefficient being reduced greatly after the reservoir operation, is, F = Q 2/S, with the coefficient being reduced greatly after the reservoir operation, which whichi cani be determined in the subsequent relation fitting. This parameter of fluvial ero- can be determined in the subsequent relation fitting. This parameter of fluvial erosion sionintensity intensity has been has widely been usedwidely in previous used in studies previous on channel studies adjustments on channel in theadjustments LYR and in the LYRthe Middle and the Yangtze Middle River Yangtze [46–48 ].River [46–48].

(a) 360 (b) 300

1.926 300 2.056 = = 240 QQs 0.1982( /100) QQs 0.1365( /100) 240 (R2 =0.700) (R2 =0.661) 180 180 (t/s) (t/s) 120 s 120 s Q Q 60 60

0 0 0 1020304050 0 1020304050 Q (102m3/s) Q (102m3/s)

Figure 7.7.Sediment Sediment rating rating curves curves at sectionsat sections of: ( aof:) HYK; (a) HYK; (b) JHT. (b) JHT. There is a relaxation or recovery time for the channel to adjust itself under the altered regimeThere of flow is a andrelaxation sediment, or whichrecovery is called time for delayed the channel response to [ 37adjust]. Therefore, itself under channel the altered regimemigration of occurs, flow and owing sediment, to an accumulative which is consequencecalled delayed of the response earlier conditions [37]. Therefore, of water channel migrationdischarge and occurs, sediment owing concentration, to an accumulative and the mean consequence fluvial erosion of the intensity earlier conditions (Fn) during of water the previous n-year is written as the following form: discharge and sediment concentration, and the mean fluvial erosion intensity ( Fn ) during the previous n-year is written as the following1 n form: Fn = Fi (2) n ∑ n i==1 1 FFni (2) Previous studies show that channel morphologyn i=1 adjusts along with the variation in the incoming sediment coefficient. Thus, the mean incoming sediment coefficient (ξ ) Previous studies show that channel morphology adjusts along with the variationn in during the previous n-year can also be used to represent the cumulative condition of flow ξ theand incoming sediment, whichsediment can be coefficient. written as: Thus, the mean incoming sediment coefficient ( n ) during the previous n-year can also be used to represent the cumulative condition of flow 1 n and sediment, which can be writtenξ nas:= ∑ ξi (3) n i=1 n ξξ= 1 ni (3) where the incoming sediment coefficient (ξi) refers to the ratio of Si to Qi during the ith n i=1 hydrological year. ξ S Q where3.2.2. Calculation the incoming of Reach-Scale sediment Bankfull coefficient Channel ( i ) Dimensionsrefers to the ratio of i to i during the ith hydrologicalOwing to the year. fact that remote sensing images cannot quantify the accurate banklines at bankfull level, 28 post-flood profiles of sedimentation cross-sections in 1986–2016 were 3.2.2. Calculation of Reach-Scale Bankfull Channel Dimensions Owing to the fact that remote sensing images cannot quantify the accurate banklines at bankfull level, 28 post-flood profiles of sedimentation cross-sections in 1986–2016 were adopted to calculate the section-scale bankfull channel widths. Xia et al. [10,11] proposed a suitable identification method to determine the bankfull channel widths at such sections with complex geometry. Furthermore, an integrated approach was utilized in this study

to determine the reach-scale bankfull channel width (Wbf ), which combines the geometric average based on the log transformation and the weighted mean based on the distance

between two consecutive sections [10]. The specific representation of Wbf is written in this form:

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adopted to calculate the section-scale bankfull channel widths. Xia et al. [10,11] proposed a suitable identiﬁcation method to determine the bankfull channel widths at such sections with complex geometry. Furthermore, an integrated approach was utilized in this study to determine the reach-scale bankfull channel width (Wb f ), which combines the geometric average based on the log transformation and the weighted mean based on the distance between two consecutive sections [10]. The speciﬁc representation of Wb f is written in this form: N1−1 ! 1 i+1 i W = exp ln W + ln W ∆x (4) b f ∑ b f b f i 2L1 i=1 i where Wb f is the bankfull channel width at the ith section; ∆xi is the distance between the ith and (i + 1)th sections; and L1 is the total channel length in the study reach. It is assumed that the study reach covered N1 cross-sections, and N1 = 28 was used in this analysis. This method can guarantee the continuity of bankfull channel dimensions, as well as avoid the effect on the calculation of bankfull channel dimensions at reach-scale caused by the varied i spacing between two sections. In addition, the bankfull channel depths (Hb f and Hb f ) at section- and reach-scales can also be determined using a similar approach. Using the above calculation approach, Figure3 indicates the section-scale bankfull channel depths and widths at Liuyuankou in three years.

3.2.3. Calculation of Section-Scale Channel Migration Rate Section-scale bankfull discharges vary significantly along the braided reach owing to the difference in cross-sectional geometry [10,11], and it is difficult to identify accurately the river bankline and the main-channel zone at bankfull level from a specified satellite image. Therefore, channel migration can usually be represented by the migration of channel centerline, which can be determined from the channels at low water levels extracted from the post-flood satellite images. It should be noted that remote sensing images obtained from the Landsat scenes were all Level 1T terrain-correction images, with topography, systematic radiation and geometric correction being conducted. The following steps were used to process the selected remote sensing images [7,21]. Firstly, the NDWI approach developed by McFeeters [49] was used to identify the water body area; secondly, the banklines are defined as the boundary of the extracted water body, with the water surface being regarded as the river channel zone (Figure5); thirdly, Software Envi was used to draw the left and right banklines of the braided reach, with the corresponding positions of 145 cross-sections being marked according to their latitude and longitude, and then the extracted banklines and the positions of cross-sections were imported into Software ArcMap to determine their coordinates; finally, two intersection points of (XLk,YLk) and (XRk,YRk) between two banklines and the kth section were determined using the corresponding Fortran code, with the middle site of these two points being defined as the center of the section (XCk,YCk). The connection line for the middle point of each section is defined as the channel centerline (Figure8). The ratio of the width (∆Wk: m) between the middle points of a section to the specified period k (∆t: yr) is termed as the section-scale migration rate (Rm: m/yr), which can be written in this form: k Rm = ∆Wk/∆t (5)

where ∆t is the time interval between two different dates (t1 and t2) of interest, and ∆t = t2 − t1. The middle point at a section is considered to migrate toward the left side if this point is located on the left side after a period of ∆t. For example, the migration width of channel center at JHT was 739 m during the period 1986–1999, with the mean migration rate of 57 m/yr calculated by Equation (5), as shown in Figure5(b2). The migration width of channel center at JHT was 1256 m in 1999–2016, with the corresponding mean migration rate of 74 m/yr, as shown in Figure5(b3). Remote Sens. 2021, 13, 1680 12 of 21 Remote Sens. 2021, 13, x FOR PEER REVIEW 13 of 23

FigureFigure 8.8. SketchSketch mapmap forfor determinationdetermination ofof thethe centerlinecenterline migrationmigration raterate atat section-scale.section-scale.

3.2.4.3.2.4. CalculationCalculation ofof Reach-ScaleReach-Scale ChannelChannel MigrationMigration raterate andand IntensityIntensity The reach-scale migration rate of channel centerline (Rm: m/yr) over the speciﬁed The reach-scale migration rate of channel centerline ( R : m/yr) over the specified period ∆t can be determined by the similar reach-averaged approach.m Since the migration rateperiod of channel Δt can be centerline determined at section-scale by the similar over reach-averaged a speciﬁed period approach. may be Since zero, the the migration equation forrate calculating of channel the centerline reach-scale at section-scale migration rate over can a specified be written period as: may be zero, the equation for calculating the reach-scale migration rate can be written as: N2−1 − k 1 N2 1 k+1 R = 1 R k+ R + ∆l (6) m RRRl2=+ΔL ∑ ()m mk 1 k mk2 i=1 mm (6) 2L2 i=1

where N2 is the number of the refined cross-sections; ∆lk is the distance between the kth and where N2 is the number of the refined cross-sections; Δlk is the distance between the kth (k + 1)th sections; L2 is the total length of channel centerline in the study reach determined and (k + 1)th sections; L2 is the total length of channel centerline in the study reach deter- based on the remote sensing images. It should be pointed out that the calculation accuracy mined based on the remote sensing images. It should be pointed out that the calculation of the reach-scale migration rate depends on the number of sections adopted in the reach, accuracy of the reach-scale migration rate depends on the number of sections adopted in and a larger number of cross-sections can produce a higher calculation accuracy [50]. As the reach, and a larger number of cross-sections can produce a higher calculation accuracy mentioned above, the number of the measured sedimentation sections after 2004 was equal [50]. As mentioned above, the number of the measured sedimentation sections after 2004 to 145 in the braided reach. Therefore, N2 = 145 was used in Equation (6). was equal to 145 in the braided reach. Therefore, N2 = 145 was used in Equation (6). It is unreasonable to assess the channel stability only using the variation in migration It is unreasonable to assess the channel stability only using the variation in migration rate of channel centerline, because the adjustment in the bankfull channel width at reach- rate of channel centerline, because the adjustment in the bankfull channel width at reach- scale can influence the rate of centerline migration. Thus, a ratio of the reach-scale migration ratescale of can channel influence centerline the rate to of the centerline mean bankfull migration. channel Thus, width a ratio at of reach-scale the reach-scale in a periodmigra- oftion∆t ratecan of be channel calculated centerline as a relative to the migrationmean bankfull rate. channel This ratio width can at represent reach-scale the in lateral a pe- mobilityriod of Δ degreet can be of calculated main-channel as a relative [2], and migration it is defined rate. as theThis reach-scale ratio can represent migration the intensity lateral mobility degree of main-channel [2], and it is defined as the reach-scale migration inten- of channel centerline (RWm: m/(yr·m)), which can be written as: sity of channel centerline (RWm: m/(yr·m)), which can be written as: R RW = mR (7) mRW = m m Wb f 1 ++Wb f 2 /2 (7) ()WWbf12 bf /2

W W t t wherewhere Wbbf f 11 andand Wbbf f 22 are are the the reach-scale reach-scale bankfull bankfull widths widths at at dates dates of of1 t1and and 2t.2.

4.4. ResultsResults andand DiscussionDiscussion InIn thisthis study,study, thethe aboveabove methodsmethods werewere employedemployed toto quantifyquantify thethe section-section- andand reach-reach- scale morphometric parameters, covering the migration direction, rate and intensity of scale morphometric parameters, covering the migration direction, rate and intensity of channel centerline in the braided reach in 1986–2016. channel centerline in the braided reach in 1986–2016. 4.1. Migration Direction of Channel Centerline 4.1. Migration Direction of Channel Centerline Migration directions at the typical sections of HYK, JHT and GC were determined duringMigration the period directions 1986–2016. at the The typical total numberssections of HYK, leftward JHT migration and GC were at three determined sections wereduring 17, the 16, period and 13, 1986–2016. respectively, The while total the numbers numbers of ofleftward rightward migration migration at three were sections 13, 14, andwere 16 17, (Figure 16, and9a). 13, These respectively, results indicatewhile the that numbers the probability of rightward of the migration channel were centerline 13, 14, and 16 (Figure 9a). These results indicate that the probability of the channel centerline

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migrating toward the left bank was approximately equal to the probability of rightward migrating toward the left bank was approximately equal to the probability of rightward migration from from a long-term a long-term sequence. sequence.

Figure 9. 9.Variations Variations in the in section- the section- and reach-scale and reach-scale centerline migrationcenterline direction: migration (a) the direction: number of (a) the number eachof each migration migration direction direction at typical at sections; typical ( bsections;) reach-scale (b) migration reach-scale probability migration (PLR). probability (PLR). Furthermore, the migration directions at 145 sections in the braided reach of the LYR were alsoFurthermore, determined annuallythe migration from 1986 directions to 2016. The at number145 sections of cross-sections in the braided at which reach of the LYR thewere channel also centerlinedetermined migrated annually toward from the left1986 or rightto 201 bank6. The over number a specified of period cross-sections was at which defined,the channel respectively, centerline as N migratedL or NR, and toward the ratio the (P leftLR) wasor right calculated bank byover the a value specified of period was NL/NR. At these sections, the values of NL and NR were, respectively, 73 CSs/yr and defined, respectively, as NL or NR, and the ratio (PLR) was calculated by the value of NL/NR. 72 CSs/yr during the period 1986–2016, with the ratio (PLR) equaling 1.01 (Figure9b). Therefore,At these itsections, can be concluded the values that of the probabilityN L and N ofR channel were, migration respectively, toward 73 the CSs/yr left or and 72 CSs/yr right side was generally equivalent at both section- and reach-scales. It is mainly attributed during the period 1986–2016, with the ratio (PLR) equaling 1.01 (Figure 9b). Therefore, it to this fact that a number of central bars were widely distributed and the riverbed consisted can be concluded that the probability of channel migration toward the left or right side of fine sand, which caused remarkable channel adjustments in the braided reach [3]. This findingwas generally reveals that equivalent the migration at directionboth section- of channel and centerline reach-scales. in the braided It is mainly reach was attributed to this reciprocating,fact that a number which fully of reflectedcentral thebars self-adjustment were widely characteristics distributed of and this reachthe riverbed [1]. consisted of fine sand, which caused remarkable channel adjustments in the braided reach [3]. This 4.2. Migration Rate of Channel Centerline finding reveals that the migration direction of channel centerline in the braided reach was In 1986–1999, the braided reach underwent a remarkable aggradation process, which ledreciprocating, to the centerline which of the fully channel reflected shifting the significantly. self-adjustment In 1999–2016, characteristics there was aof sig- this reach [1]. nificant channel degradation process in this reach, with the degree of channel migration decreasing4.2. Migration gradually Rate [51 of]. Channel Figure 10 Centerlinea shows the migration rates of channel centerline at the sections of HYK, JHT and GC during the period from 1986 to 2016. These results indicate In 1986–1999, the braided reach underwent a remarkable aggradation process, which that: (i) the migration rates of channel centerline were a little higher in the years of 1988, 1992led to and the 1996 centerline due to the of occurrence the channel of hyperconcentrated shifting significantly. flood events In before 1999–2016, the reservoir there was a signif- operation,icant channel and the degradation corresponding process rates at threein this sections reach, were with 973, the 190 degree and 50 m/yr of channel in 1988, migration de- 1224,creasing 1284 gradually and 6 m/yr [51]. in 1992, Figure and 1011, 10a shows 49 and 51the m/yr migration in 1996, respectively,rates of channel and the centerline at the averagesections migration of HYK, rates JHT of and channel GC centerlineduring the in 1986–1999period from were 1986 540, to 341 2016. and 92 These m/yr; results indicate (ii) after the Xiaolangdi Reservoir operation (1999–2016), the maximum migration rate at HYKthat: reached(i) the migration 1049 m/yr inrates 2000 of owing channel to the centerline recession of were a sharply a little curved higher bend in near the years of 1988, the1992 HYK and section; 1996 due similarly, to the the occurrence migration rate of athype JHTrconcentrated increased gradually flood from events 1999 tobefore the reser- 2002,voir operation, with the maximum and the value corresponding approximating rates 961 m/yr at three in 2002, sections and the were migration 973, 190 rate and 50 m/yr in decreased1988, 1224, gradually 1284 and after 6 am/yr sharply in curved1992, and bend 1011, was regenerated; 49 and 51 them/yr average in 1996, annual respectively, and migration rates of channel centerline at HYK, JHT and GC were 244, 296 and 48 m/yr over the average migration rates of channel centerline in 1986–1999 were 540, 341 and 92 m/yr; (ii) after the Xiaolangdi Reservoir operation (1999–2016), the maximum migration rate at HYK reached 1049 m/yr in 2000 owing to the recession of a sharply curved bend near the HYK section; similarly, the migration rate at JHT increased gradually from 1999 to 2002, with the maximum value approximating 961 m/yr in 2002, and the migration rate decreased gradually after a sharply curved bend was regenerated; the average annual migration rates of channel centerline at HYK, JHT and GC were 244, 296 and 48 m/yr over the period 1999–2016, with the corresponding reduction degrees of 55%, 13% and 48%; and (iii) moreover, the migration rates at the sections of HYK and JHT were much larger

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the period 1999–2016, with the corresponding reduction degrees of 55%, 13% and 48%; and (iii) moreover, the migration rates at the sections of HYK and JHT were much larger thanthan thethe valuesvalues atat the the section section of of GC GC during during the the period period 1986–2016. 1986–2016. The The GC GC section section had had a anarrower narrower and and deeper deeper geometry geometry and the local riverriver trainingtraining works works reduced reduced the the degree degree of ofchannel channel migration, migration, as as compared compared with with the the cr cross-sectionsoss-sections of of HYK HYK and and JHT JHT without without the pro- protectiontection of ofeffective effective rive riverr training training engineering. engineering.

(a) 1400 Max=1224 1284 HYK 1049 JHT 1100 961 GC 800 698 (m/yr) m

R 500 Mean=540 341 296 207 200 244 92 48 Min=32 49 -100 6 10 20 2 1986-1999 1986-19991986-1999 1986-1999 1999-2016 1999-2016 1999-2016 Period (b)1500 HYK JHT GC 1986-1999 Maoan 1200 1999-2016

900 Sanyizhai

(m/yr) 600 m R 300

0 Mazhai 0 50 100 150 200 250 300 Distance from the Xiaolangdi Reservoir (km) FigureFigure 10.10.Temporal Temporal variations variations in thein the section-scale section-scale migration migration rate ofrate channel of channel centerline: centerline: (a) at sections (a) at sec- oftions HYK, of JHTHYK, and JHT GC; and (b )GC; at all (b the) at sections all the sections in the braided in the reach.braided reach.

InIn general,general, the the migration migration rates rates of of channel channel centerline centerline varied varied greatly greatly along along the braidedthe braided reach,reach, andand were were influenced influenced by by various various factors factor suchs such as theas the conditions conditions of water of water discharge discharge andand sedimentsediment concentration, concentration, and and channel channel boundary boun conditionsdary conditions [3]. During [3]. theDuring period the 1986– period 1999,1986–1999, the largest the migrationlargest migration rate of channel rate of centerline channel centerline occurred at occurred the Maoan at section the Maoan situated section 66.2situated km upstream66.2 km upstream of JHT, with of JHT, the value with the of 1225 value m/yr. of 1225 After m/yr. the After Xiaolangdi the Xiaolangdi Reservoir Res- operation, the maximum migration rate (exceeding 590 m/yr) in 1999–2016 occurred at the ervoir operation, the maximum migration rate (exceeding 590 m/yr) in 1999–2016 oc- Sanyizhai section located 2.9 km downstream of JHT, while the minimum value was about curred at the Sanyizhai section located 2.9 km downstream of JHT, while the minimum 20 m/yr occurring at the Mazhai section located 37.6 km downstream of JHT. In addition, value was about 20 m/yr occurring at the Mazhai section located 37.6 km downstream of only 19 of the 145 cross-sections after the reservoir operation had a larger migration rate thanJHT. theIn addition, value before only the 19 reservoir of the 145 operation, cross-sections which after indicates the reservoir that the migration operation degree had a of larger channelmigration centerline rate than was the reduced value remarkably,before the reservoir with the channel operation, braiding which property indicates weakening, that the mi- causedgration bydegree the water of channel impoundment centerline and was sediment reduced retention remarkably, of the with Xiaolangdi the channel Reservoir. braiding Figureproperty 10b weakening, also reveals caused that the by rate the of water channel impoundment migration was and the sediment most dramatic retention in the of the HYK–JHTXiaolangdi sub-reach. Reservoir. One Figure of the 10b most also important reveals reasonsthat the can rate be of explained channel asmigration follows. Thewas the criticalmost dramatic shear stress in the of the HYK–JHT river bank sub-reach. soil is generally One of much the most lower important than the near-bank reasons can shear be ex- stressplained of theas follows. flow because The critical of its weak shear erosion-resistance stress of the river and bank lower soil clayis generally content, much and the lower shearthan the strength near-bank of bank shear soil can stress bedetermined of the flow by because the internal of its friction weak angleerosion-resistance and cohesion, and withlower their clay values content, decreasing and the greatly shear strength with anincrease of bank insoil water can contentbe determined [52]. Therefore, by the internal the riverbanksfriction angle in thisand sub-reach cohesion, were with pronetheir values to being decreasing scoured and greatly collapsing, with an which increase made in itwater possiblecontent for[52]. the Therefore, channel centerline the riverbanks to shift in from this one sub-reach branch towere another. prone Figure to being 10 indicates scoured and that the characteristics of channel migration at a specified section or in a local sub-reach collapsing, which made it possible for the channel centerline to shift from one branch to made it difficult to represent the migration trend of a whole study reach, and that the another. Figure 10 indicates that the characteristics of channel migration at a specified reach-scale migration rate needs to be investigated. section or in a local sub-reach made it difficult to represent the migration trend of a whole Subsequently, the reach-scale migration rates of channel centerline in the braided reachstudy from reach, 1986 and to that 2016 the were reach-scale calculated usingmigration Equation rate (6),needs as shownto be investigated. in Figure 11a. During the continuousSubsequently, channel the aggradationreach-scale migration period 1986–1999, rates of thechannel largest centerline reach-scale in channelthe braided migrationreach from rate 1986 was to 6592016 m/yr, were whichcalculated occurred using in Equation 1988 mainly (6), as due shown to the in occurrence Figure 11a. of Dur- aing hyperconcentrated the continuous channel flood event, aggradation and the period average 1986–1999, annual channel the largest migration reach-scale ratewas channel 410migration m/yr in rate 1986–1999. was 659 After m/yr, the which reservoir occurred operation, in 1988 the maximummainly due reach-scale to the occurrence migration of a hyperconcentrated flood event, and the average annual channel migration rate was 410 m/yr in 1986–1999. After the reservoir operation, the maximum reach-scale migration rate (303 m/yr) occurred in 2003, and it was mainly related to strong flood processes. Five flood events with low sediment concentrations and large water discharges occurred in the 2003

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rate (303 m/yr) occurred in 2003, and it was mainly related to strong flood processes. Five floodflood events season, with which low sediment caused concentrations intensive andscour large and water migration discharges processes. occurred in the The average annual 2003migration flood season, rate at which reach-scale caused intensive was 185 scour m/yr and in migration 1999–2016, processes. with The a reduction average of 55%, as com- annual migration rate at reach-scale was 185 m/yr in 1999–2016, with a reduction of 55%, aspared compared with with the the pre-dam pre-dam value in in 1986–1999. 1986–1999.

FigureFigure 11. 11.Temporal Temporal variations variations in the in reach-scale the reach-scale channel channel migration migration parameters parameters of: (a) rate; of: (a) rate; (b) (b) intensity. intensity. In order to further explore the temporal and spatial characteristics of channel migration in the braidedIn order reach, to thefurther average explore migration the rates temporal of three sub-reaches and spatial were characteristics calculated using of channel migra- thetion above-mentioned in the braided reach-averaged reach, the average method, as migration shown in Figure rates 12 a.of In three terms sub-reaches of temporal were calculated variation, the results show that the migration rate of each sub-reach was relatively large beforeusing the the reservoir above-mentioned operation, and it reach-averaged tended to have a gradually method, decreasing as shown trend thereafter.in Figure 12a. In terms of Ittemporal was mainly variation, related to the a significant results variationshow that in the the flow migration and sediment rate regimeof each after sub-reach was rela- thetively reservoir large operation. before the In terms reservoir of spatial operation, variation, theand mean it tended migration to rateshave in a three gradually decreasing sub-reaches were 403, 522 and 274 m/yr before the reservoir operation; over the period 1999–2016,trend thereafter. the mean migrationIt was mainly rate was related the most to significant a significant in the HYK–JHTvariation sub-reach in the flow and sediment (regimeRm = 252 after m/yr), the while reservoir the mean operation. rates in the MJ–HYKIn terms and of JHT–GCspatial sub-reachesvariation, were the mean 160 migration rates andin three 129 m/yr, sub-reaches respectively. were On the403, whole, 522 statisticaland 274 resultsm/yr ofbefore migration the ratesreservoir in these operation; over the threeperiod sub-reaches 1999–2016, were the consistent mean with migration the calculated rate was results the at section-scale.most significant Therefore, in the HYK–JHT sub- the migration rate of channel centerline in the braided reach was characterized spatially byreach the fact ( R thatm = the252 values m/yr), in the while middle the sub-reach meanwere rates generally in the larger MJ–HYK than those and in JHT–GC the sub-reaches upperwere and160 lower and sub-reaches.129 m/yr, respectively. On the whole, statistical results of migration rates in these three sub-reaches were consistent with the calculated results at section-scale. There- fore, the migration rate of channel centerline in the braided reach was characterized spatially by the fact that the values in the middle sub-reach were generally larger than those in the upper and lower sub-reaches.

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(a) 1000 907 Sub-reaches MJ-HYK 800 Max=724 HYK-JHT 600 533 JHT-GC Mean=403 522 469 (m/yr)

m 400 R 278 274 252 188 200 301 Min=250 160 129 90 87 0 77 52 1234561986-1999 1999-2016 Period (b) 0.5 0.44 0.42 0.4 0.34 0.33 0.30

m 0.3 0.27 0.27 0.26 RW 0.2 0.20 0.18 0.21 0.17 0.17 0.13 0.1 0.12 0.06 0.06 0.08 0 1234561986-1999 1999-2016 Period FigureFigure 12. 12. TemporalTemporal variations in thethe reach-scalereach-scale migrationmigration parameters parameters of of channel channel centerline centerline in in three threesub-reaches: sub-reaches: (a) rate; (a) (rate;b) intensity. (b) intensity.

4.3.4.3. Migration Migration Intensity Intensity of of Channel Channel Centerline Centerline TheThe reach-scale reach-scale migration migration intensities of ch channelannel centerline over the period 1986–2016 were also calculated using Equation (7). It It can can be be seen seen in Figure 11b11b that the variation trendtrend in in migration migration intensity intensity was was consistent consistent with with the themigration migration rate ratein 1986–2016. in 1986–2016. The max- The imummaximum reach-scale reach-scale migration migration intensity intensity of channel of channel centerline centerline was 0.34 was m/(yr·m) 0.34 m/(yr in· m)1998, in which1998, whichwas higher was higherthan the than average the averageannual migration annual migration intensity of intensity 0.28 m/(yr·m) of 0.28 during m/(yr ·them) periodduring 1986–1999. the period 1986–1999.After the reservoir After the operation, reservoir operation,the maximum the maximummigration migrationintensity reachedintensity 0.28 reached m/(yr·m),0.28 m/(yroccurring·m), in occurring 2003; subsequently, in 2003; subsequently, the migration the migrationintensity gradually intensity decreased,gradually decreased,ranging between ranging 0.07 between and 0.21 0.07 m/ and(yr·m). 0.21 In m/(yr 1999–2016,·m). In the 1999–2016, average theannual average mi- grationannual migrationintensity of intensity channel ofcenterline channel centerlinewas 0.16 m/(yr·m), was 0.16 m/(yrwith a· m),corresponding with a corresponding reduction ofreduction 43%, as compared of 43%, as comparedwith the average with the annual average value annual in 1986–1999. value in 1986–1999. This variation This trend variation was mainlytrend was related mainly to the related reduced to thesediment reduced conc sedimententration concentration and the subsequent and the channel subsequent incision.channel incision. InIn addition, addition, the the average average annual annual channel channel migration migration intensities intensities in 1986–1999 in 1986–1999 were, were, re- respectively, 0.27, 0.33 and 0.20 m/(yr·m) in the sub-reaches of MJ–HYK, HYK–JHT, and spectively, 0.27, 0.33 and 0.20 m/(yr·m) in the sub-reaches of MJ–HYK, HYK–JHT, and JHT–GC, as shown in Figure 12b. In 1999–2016, the average annual migration intensities JHT–GC, as shown in Figure 12b. In 1999–2016, the average annual migration intensities in three sub-reaches were reduced, respectively, to 0.13, 0.17 and 0.17 m/(yr·m), with the in three sub-reaches were reduced, respectively, to 0.13, 0.17 and 0.17 m/(yr·m), with the corresponding reduction degrees of 52%, 48% and 15%. The JHT–GC sub-reach had the corresponding reduction degrees of 52%, 48% and 15%. The JHT–GC sub-reach had the smallest channel migration rate, but the mean migration intensity was relatively large, smallest channel migration rate, but the mean migration intensity was relatively large, because the bankfull channel width in this sub-reach was only half of the other two sub- because the bankfull channel width in this sub-reach was only half of the other two sub- reaches, resulting in a higher channel migration intensity. reaches, resulting in a higher channel migration intensity. 4.4. Influencing Factors of Channel Migration Intensity 4.4. Influencing Factors of Channel Migration Intensity Channel evolution covers various deformation components such as adjustments in planformChannel and evolution cross-sectional covers geometries, various deformat and channelion components migration such is a critical as adjustments component in planformof channel and planform cross-sectional adjustments geometries, in alluvial and riverschannel [3 ,migration13]. Factors is a influencing critical component channel ofmigration channel mainlyplanform include adjustments the variations in alluvial in channel rivers boundary[3,13]. Factors and incominginfluencing flow-sediment channel migration mainly include the variations in channel boundary and incoming flow-sediment

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regime [1,53,54]. These influencing factors are presented herein to investigate the variation regimecharacteristics [1,53,54 ].in Thesemigration influencing intensity factors of channel are presented centerline herein in the to braided investigate reach. the variation characteristics in migration intensity of channel centerline in the braided reach. 4.4.1. Effect of Channel Boundary Conditions 4.4.1. Effect of Channel Boundary Conditions Channel boundary conditions generally refer to different geomorphological factors, includingChannel bed-material boundary composition, conditions generally geomorphic refer coefficient, to different the geomorphological level difference between factors, includingmain-channel bed-material and floodplain, composition, as well geomorphic as the longitudinal coefficient, channel the level slope difference [1,3]. In addition, between main-channelthe construction and of floodplain,river training as wellworks as woul the longitudinald also have an channel impact slope on the [1, 3channel]. In addition, evolu- thetion construction of a local reach. of river training works would also have an impact on the channel evolution of a localThe river reach. training works implemented in the Lower Yellow River are mainly divided into threeThe river types, training including works shoal-protection implemented inworks, the Lower flow guide Yellow works River and are levee mainly protection divided intoworks three [1,19,55]. types, includingHu et al. shoal-protection[55] found that works,the migration flow guide rate works of main-channel and levee protection at HYK works [1,19,55]. Hu et al. [55] found that the migration rate of main-channel at HYK reached 7.5 km/yr under natural conditions; however, the migration rate was reduced to reached 7.5 km/yr under natural conditions; however, the migration rate was reduced 3 km/yr after the implementation of river training works in the early 1990s. Further inves- to 3 km/yr after the implementation of river training works in the early 1990s. Further tigations reveal that only 7 of a total of 110 river regulation projects still had a certain effect investigations reveal that only 7 of a total of 110 river regulation projects still had a certain on the mainstream migration in the braided reach [13], which indicates that it was impos- effect on the mainstream migration in the braided reach [13], which indicates that it was sible to achieve long-term channel stability merely controlled by river training works. It impossible to achieve long-term channel stability merely controlled by river training works. is confirmed that both incoming flow-sediment regime and channel boundary conditions It is confirmed that both incoming flow-sediment regime and channel boundary conditions are two main factors to control the channel migration rate in the braided reach, and it is are two main factors to control the channel migration rate in the braided reach, and it is difficult to completely change the inherent adjustment characteristics of rivers through difficult to completely change the inherent adjustment characteristics of rivers through limited artificial projects which only play an auxiliary role [19]. limited artificial projects which only play an auxiliary role [19]. With the purpose of investigating the relationship between migration intensity of With the purpose of investigating the relationship between migration intensity of channel centerlinecenterline andand composition composition of of bed bed material, material, the the mean mean post-flood post-flood median median diameters diameters of bed material (D50) at HYK, JHT and GC were calculated annually as the representa- of bed material (D50) at HYK, JHT and GC were calculated annually as the representative diametertive diameter of bed of material.bed material. Before Before the reservoir the reservoir operation, operation, channel channel aggradation aggradation occurred oc- incurred the downstreamin the downstream reach, withreach, the with bed-material the bed-material composition compositio graduallyn gradually becoming becoming fine, andfine, thenand anthen intensive an intensive process process of channel of channel degradation degradation occurred, occurred, characterized characterized by evident by ev- coarseningident coarsening of the of bed-material. the bed-material. The The outcomes outcomes presented presented in in Figure Figure 13 13aa show show that that thethe migration intensityintensity of of channel channel centerline centerline decreased decreased as theas medianthe median diameter diameter increased, increased, with thewith determination the determination coefficient coefficient between between them them of R2 of= R 0.66,2 = 0.66, which which qualitatively qualitatively reflected reflected the restrictivethe restrictive effect effect of bed-material of bed-material composition composition on channel on channel migration migration in the in braided the braided reach. Itreach. is also It is one also of one the of reasons the reasons explaining explaining a decrease a decrease in the in migrationthe migration intensity intensity of channelof chan- centerlinenel centerline since since 1999. 1999.

=−0.5 2 + 0.5 − (a) (b) RWmbfbfbfbf0.001( Wh / ) 0.044( Wh / ) 0.239 0.4 0.4 (R2 =0.83) 0.3 0.3 m m 0.2 0.2 RW RW

-0.95 0.1 RWm = 0.02 (D50) 0.1 (R² = 0.66) 0 0 0.05 0.1 0.15 0.2 0 10203040 − Whm0.50.5/(-0.5 0.5 ) D50 (mm) Bbf/h (m bf ) Figure 13. Relationships between migration intensity and various channel boundary conditions of: 0.50.5 ((aa)) medianmedian diametersdiameters ofof bedbed materialmaterial ((DD5050); ( b) geomorphic coefficient coefficient (WWhbbf f //hb bf f ).). q In addition, geomorphic coefficient ( Wb f /hb f ) was used to represent the cross- sectionalIn addition, geometry geomorphic [10]. A polynomial coefficient function ( Whbf/ relationship bf ) was used can to berepresent established the cross-sec- between q m RWtionalm and geometry geomorphic [10]. A coefficientpolynomial ( functionWb f /h brelationship f ), as shown can in be Figure established 13b. The between migration RW

intensityand geomorphic of channel coefficient centerline ( Wh firstbf/ generally bf ), as shown increased in Figure with 13b. the The increasing migration geomorphic intensity coefficient,of channel centerline whereas it first reached generally the maximum increased valuewith the when increasing the magnitude geomorphic of geomorphic coefficient, −0.5 coefficientwhereas it wasreached equal the to aboutmaximum 25 m value, and when then the it decreasedmagnitude with of geomorphic the increasing coefficient geomorphic coefficient, with R2 = 0.83. It can be seen that the migration degree was stronger in a wider and shallower channel geometry when geomorphic coefficient ranged within a

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was equal to about 25 m−0.5, and then it decreased with the increasing geomorphic coefficient, with R2 = 0.83. It can be seen that the migration degree was stronger in a wider and shallower channel geometry when geomorphic coefficient ranged within a certain limitation; however, the channel showed a narrower and deeper geometry owing to the recent channel degradation in 1999–2016, which decreased the migration degree of channel centerline.

4.4.2. Effect of the Altered Flow and Sediment Regime Remote Sens. 2021, 13, 1680 After the Xiaolangdi Reservoir operation, the flow and sediment regime entering18 of the 21 braided reach was altered significantly, leading to a great reduction in the amount of sediment discharge at HYK. Consequently, the downstream channel adjusted from the con- certaintinuous limitation; deposition however, state to the the recent channel degradation showed a narrowerstate, and andthe volume deeper geometryof channel owing scour toaccounted the recent for channel more than degradation half of the in total 1999–2016, volume whichof the whole decreased LYR. the Therefore, migration the degree varying of channelregime of centerline. flow and sediment was the primary factor causing adjustments in cross-sectional geometry. In the current study, Equations (1)–(3) were used to analyze the effect of 4.4.2.the incoming Effect of flow the Alteredand sediment Flow and regime Sediment on the Regime migration intensity. AfterIn order the to Xiaolangdi study the relationship Reservoir operation, between the the intensity flow and of sedimentchannel migration regime entering and the theincoming braided regime reach of was flow altered and sediment, significantly, these leading annual to mean a great parameters reduction of in flow the amount and sedi- of sedimentment at HYK discharge from 1986 at HYK. to 2016 Consequently, were calculated, the covering downstream the discharge, channel adjusted sediment from concen- the continuoustration, incoming deposition sediment state coefficient, to the recent and degradation fluvial erosion state, intensity. and the Various volume relationships of channel scourwere then accounted presented for morebetween than these half flow-sediment of the total volume parameters of the wholeand the LYR. reach-scale Therefore, migra- the varyingtion intensity regime of of channel flow and centerline sediment (RW wasm), the which primary displayed factor both causing single adjustments and combined in cross- ef- sectionalfects of flow geometry. and sediment In the current conditions study, on Equations the reach-scale (1)–(3) weremigration used tointensity analyze of the channel effect ofcenterline, the incoming as shown flow in and Figure sediment 14. These regime relations on the in migration Figure 14a,b intensity. can be written as: In order to study the relationship between= theξ intensity0.34 of channel migration and the RWm 0.92(2 ) (8a) incoming regime of flow and sediment, these annual mean parameters of flow and sediment

at HYK from 1986 to 2016 were calculated, covering the− discharge, sediment concentration, RW= 0.39( F ) 0.31 incoming sediment coefﬁcient, and ﬂuvialm erosion2 intensity. Various relationships were(8b)

thenIt presented indicates between that: the thesevalue ﬂow-sediment of RWm increased parameters with a larger and the previous reach-scale two-year migration mean intensity of channel centerline (RWξ m), which2 displayed both single and combined effects of incoming sediment coefficient ( 2 ), with R = 0.90 (Figure 14a), and decreased as the pre- ﬂow and sediment conditions on the reach-scale migration intensity of channel centerline, vious two-year mean fluvial erosion intensity ( F ) increased, with R2 = 0.85 (Figure 14b). as shown in Figure 14. These relations in Figure 142 a,b can be written as: It comes to a conclusion from Figure 14 that the incoming sediment coefficient or fluvial erosion intensity is an important factor that remarkably0.34 influenced the migration intensity RWm = 0.92(ξ ) (8a) of channel centerline in the braided reach over the2 period 1986–2016. −0.31 RWm = 0.39(F ) (8b) 2

(a) (b) 0.4 0.4

0.3 0.3 m -0.31 m RWm = 0.39 (F2) RW 0.2 0.2 ξ 0.34 RW (R² = 0.85) RWm = 0.92 ( 2) 0.1 (R² = 0.90) 0.1

0 0 0 0.010.020.030.040.05 050100150 ξ (kg⸳s/m6) F (m9/kg⸳s2) 2 2

Figure 14. RelationshipsRelationships between between the the channel channel migration migration intensity intensity and andvarious various incoming incoming flow-sedi- flow- ment factors of: (a) the previous two-year average incoming sediment coefficient (ξ ); (b) the pre- sediment factors of: (a) the previous two-year average incoming sediment coefficient2 (ξ2); (b) the previousvious two-year two-year average average fluvial fluvial erosion erosion intensity intensity ( F2 (F).2 ).

ItBased indicates on the that: results the valuecalculated of RW usingm increased Equation with (8a,b), a larger the variation previous in two-year the migration mean 2 incomingintensity of sediment channel coefficientcenterline in (ξ 2the), withbraidedR =reach 0.90 was (Figure reproduced. 14a), and Figure decreased 15 indicates as the 2 previous two-year mean fluvial erosion intensity (F2) increased, with R = 0.85 (Figure 14b). It comes to a conclusion from Figure 14 that the incoming sediment coefficient or fluvial erosion intensity is an important factor that remarkably influenced the migration intensity of channel centerline in the braided reach over the period 1986–2016. Based on the results calculated using Equation (8a,b), the variation in the migration intensity of channel centerline in the braided reach was reproduced. Figure 15 indicates that the migration intensities of channel centerline at reach-scale, estimated using Equation (8a,b), can generally agree with the measured process in 1986–2016. Moreover, measured migration intensities of channel centerline in 2017 and 2018 were used to verify two empirical relations, as shown in red dots. It shows that the migration intensities of channel centerline at reach-scale, estimated using Equation (8a,b), can generally agree with the measured data in 2017 and 2018, with the relative errors of 1.5% (in 2017) and 21% (in 2018) of Equation (8a), and 20% (in 2017) and 37% (in 2018) of Equation (8b). Therefore, these Remote Sens. 2021, 13, x FOR PEER REVIEW 20 of 23

that the migration intensities of channel centerline at reach-scale, estimated using Equa- tion (8a,b), can generally agree with the measured process in 1986–2016. Moreover, measured migration intensities of channel centerline in 2017 and 2018 were used to verify two empirical relations, as shown in red dots. It shows that the migration intensities of channel Remote Sens. 2021, 13, 1680 centerline at reach-scale, estimated using Equation (8a,b), can generally agree with19 ofthe 21 measured data in 2017 and 2018, with the relative errors of 1.5% (in 2017) and 21% (in 2018) of Equation (8a), and 20% (in 2017) and 37% (in 2018) of Equation (8b). Therefore, twothese empirical two empirical relations relations can be usedcan be to predictused to the predict migration the migration intensity ofintensity channel of centerline channel incenterline the braided in the reach. braided reach.

Figure 15. Comparisons betweenbetween thethe measurementsmeasurements and and the the reach-scale reach-scale channel channel centerline centerline migration migra- intensitiestion intensities calculated calculated using: using: (a) Equation (a) Equation (8a); (8a); (b) Equation (b) Equation (8b). (8b).

5. Conclusions Channel migrationmigration plays plays a vitala vital role role in adjustments in adjustments of channel of channel planform planform in the braided in the reach.braided In reach. this study, In this a detailedstudy, a calculationdetailed ca procedurelculation procedure was proposed was toproposed determine to determine migration ratemigration and intensity rate and of intensity channel of centerline, channel centerline, using remote using sensing remote images sensing and images cross-sectional and cross- topography.sectional topography. Migration Migration rates and rates intensities and intensities of channel of channel centerline centerline at section- at section- and reach- and scalesreach-scales in the in braided the braided reach reach in 1986–2016 in 1986–201 were6 were calculated calculated using using the proposed the proposed procedure. proce- Thedure. conclusions The conclusions are presented are presented as follows: as follows: (i) The probabilityprobability ofof channelchannel migrationmigration towards the leftleft oror rightright sideside waswas almostalmost equivalent over over the the period period 1986–2016, 1986–2016, and and section-scale section-scale migration migration rates rates in the in middle the middle sub- sub-reach were generally higher than the values in the upper and lower sub-reaches. reach were generally higher than the values in the upper and lower sub-reaches. (ii) The average annual reach-scale migration rate of channel centerline was 410 m/yr (ii) The average annual reach-scale migration rate of channel centerline was 410 m/yr over the period 1986–1999, and it was reduced to 185 m/yr over the period 1999–2016 due over the period 1986–1999, and it was reduced to 185 m/yr over the period 1999–2016 due to the recent channel scour caused by the implementation of the reservoir. The reach-scale to the recent channel scour caused by the implementation of the reservoir. The reach-scale migration intensity of channel centerline underwent a similar adjustment, with the average migration intensity of channel centerline underwent a similar adjustment, with the aver- annual migration intensity decreasing from 0.28 m/(yr·m) in 1986–1999 to 0.16 m/(yr·m) age annual migration intensity decreasing from 0.28 m/(yr·m) in 1986–1999 to 0.16 in 1999–2016. m/(yr·m) in 1999–2016. (iii) The incoming flow and sediment regime was a dominant factor influencing the (iii) The incoming flow and sediment regime was a dominant factor influencing the migration intensity of channel centerline, although channel boundary conditions could also migration intensity of channel centerline, although channel boundary conditions could influence the migration intensity. The reach-scale migration intensity of channel centerline also influence the migration intensity. The reach-scale migration intensity of channel cen- was written as a function of the previous two-year mean incoming sediment coefficient orterline fluvial was erosion written intensity as a function at HYK, of andthe prev correspondingious two-year parameters mean incoming were calibrated sediment by coef- the measurementsficient or fluvial in erosion 1986–2016, intensity with theat HYK, corresponding and corresponding determination parameters coefficients were of calibrated 0.90 and 0.85.by the Furthermore, measurements the in proposed 1986–2016, relations with the were corresponding also verified againstdetermination the measurements coefficients inof 20170.90 and and 0.85. 2018. Furthermore, Therefore, reach-scale the proposed centerline relations migration were also intensities verified calculated against the using meas- the proposedurements relationsin 2017 and are 2018. generally Therefore, in close reach- agreementscale centerline with the measurements. migration intensities calculated using the proposed relations are generally in close agreement with the measure- Authorments. Contributions: Methodology, J.X. and Y.W.; formal analysis, Y.W.; writing—original draft preparation, J.X.; conceptualization, M.Z.; writing—review and editing, Y.W., S.D., Z.L. and Z.W. All authorsAuthor Contributions: have read and agreed Methodology, to the published J.X. and versionY.W.; formal of the an manuscript.alysis, Y.W.; writing—original draft preparation, J.X.; conceptualization, M.Z.; writing—review and editing, Y.W., S.D., Z.L. and Z.W. Funding:All authorsThis have research read and was agreed funded to by th thee published National Naturalversion Scienceof the manuscript. Foundation of China, grant numbers (51725902, 51579186, 51809196) and the Program of the National Key Research and Development Plan,Funding: grant This number research 2017YFC0405501. was funded by the National Natural Science Foundation of China, grant numbers (51725902, 51579186, 51809196) and the Program of the National Key Research and Devel- Institutionalopment Plan, Reviewgrant number Board 2017YFC0405501. Statement: Not applicable. InformedInstitutional Consent Review Statement: Board Statement:Not applicable. Not applicable. Data Availability Statement: Not applicable. Acknowledgments: The study reported herein was supported by the National Natural Science

Foundation of China (Grant Nos. 51725902; 51579186; 51809196), and it was also supported partly by the Program of the National Key Research and Development Plan (Grant No. 2017YFC0405501). The constructive suggestions of the anonymous reviewers are gratefully acknowledged. Conﬂicts of Interest: The authors declare no conﬂict of interest. Remote Sens. 2021, 13, 1680 20 of 21

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