water

Article The Impact of Biophysical Processes on Sediment Transport in the Wax Delta (, USA)

1, 1,2, 1, Courtney Elliton †, Kehui Xu * and Victor H. Rivera-Monroy * 1 Department of and Coastal Science, Louisiana State University, Baton Rouge, LA 70803, USA; [email protected] 2 Coastal Studies Institute, Louisiana State University, Baton Rouge, LA 70803, USA * Correspondence: [email protected] (K.X.); [email protected] (V.H.R.-M.) Present Address: Bureau of Energy Management, 45600 Woodland Road, Sterling, VA 20166, USA. †  Received: 11 June 2020; Accepted: 15 July 2020; Published: 21 July 2020 

Abstract: Sediment transport in coastal regions is regulated by the interaction of river discharge, wind, waves, and tides, yet the role of vegetation in this interaction is not well understood. Here, we evaluated these variables using multiple acoustic and optical sensors deployed for 30–60 days in spring and summer/fall 2015 at upstream and downstream stations in Mike Island, a deltaic island within the Wax Lake Delta, LA, USA. During a flooding stage, semidiurnal and diurnal tidal impact was minimal on an adjacent river channel, but significant in Mike Island where vegetation was low and wave influence was greater downstream. During summer/fall, a “vegetated channel” constricted the water flow, decreasing current speeds from ~13 cm/s upstream to nearly zero downstream. Synchrony between the upstream and downstream water levels in spring (R2 = 0.91) decreased in summer/fall (R2 = 0.84) due to dense vegetation, which also reduced the wave heights from 3–20 cm (spring) to nearly 0 cm (summer/fall). Spatial and temporal differences in total inorganic nitrogen and orthophosphate concentrations in the overlying and sediment porewater were evident as result of vegetation growth and expansion during summer/fall. This study provides key hourly/daily data and information needed to improve the parameterization of biophysical models in coastal restoration projects.

Keywords: Wax Lake Delta; coastal Louisiana; sediment deposition; vegetation; coastal restoration

1. Introduction The Mississippi plain is a complex and dynamic environment, regulated by the influx of water, sediment, nutrients and carbon from the Mississippi and Atchafalaya Rivers [1]. Several natural and anthropogenic factors affect this coastal environment, including rising relative sea level, reduced sediment supply, high subsidence rates, significant saltwater intrusion, coastal , and oil and gas extraction [2–6]. One of the major outcomes from the spatiotemporal interaction among these natural and human impacts over the last 80 years is the extensive loss of approximately 4877 km2 of productive wetland [4,7,8]. Given the wetland’s economic value, several initiatives to restore and rehabilitate have been proposed since the late 1980s, such as the use of sediment diversions and local dredging [3,9–13]. Sediment diversions in Louisiana use a combination of new channels and structures to divert sediment and freshwater from the Mississippi and Atchafalaya Rivers into adjacent basins to build new land and slow down land loss. However, the success of these projects heavily depends on both the presence of vegetation and plant–sediment interactions controlling sediment trapping efficiency to gain elevation and build land. When artificial planting is used in combination with natural wetland creation or sediment diversions, vegetation can potentially uptake nutrients, slow down velocity, trap mud,

Water 2020, 12, 2072; doi:10.3390/w12072072 www.mdpi.com/journal/water Water 2020, 12, 2072 2 of 22 and enhance mud retention to build additional land [3]. Thus, the study of plant–sediment interactions has both management and economic implications for current and future coastal wetland restoration plans in coastal Louisiana and other areas around the world. Current diversions in the plain are not only introducing freshwater and sediment, but also carbon and nutrients to both estuarine and wetland areas. These nutrient inputs into wetlands have several fates, including vegetation uptake, deposition and burial, oxidation or reduction within the sediment, and export to the Gulf of Mexico (GOM) [14,15]. Since nitrogen and phosphorus loading rates are high, the role of wetlands as sinks and transformers of inorganic nutrients is critical to avoid eutrophic conditions in the GOM where hypoxic conditions are a dominant feature, particularly during the summer [16–24]. Therefore, understanding nutrient cycling, particularly nutrient removal by wetlands, is critical to the ongoing biogeochemical modeling effort by the Coastal Protection and Restoration Authority of Louisiana to evaluate the effectiveness and ecological impacts of sediment diversions [25]. Wetland vegetation can attenuate waves, reduce current speeds, protect the shoreline from storm surge, reduce turbidity and promote sediment deposition [26–33]. Water velocity within a vegetated area is reduced through drag and frictional force that promotes sediment deposition and retention [13,26,28,30]. When a water parcel enters a vegetated bed, the velocity can be dampened by an order of magnitude and further decline with increasing vegetation density [26,27,33]. In fact, fine sediment deposition is generally associated with vegetative growth [21,31,34] and overall net accretion [30]. The Wax Lake Delta (WLD, Figure1A) is a relatively recent prograding delta controlled by the Mississippi– basin, and largely influenced by seasonal river pulses, tides, winds, and cold fronts [35,36]. This area provides a unique environmental setting to evaluate how the local hydrology, sediment transport, and vegetation density interact to impact sediment transport in an accreting delta. The main objective of this study is to evaluate the interactions between physical and biogeochemical processes that control sediment deposition in the WLD at a local scale. The WLD consists of several lobes of different ages forming well defined interdistributary bays. Mike Island (Figure1B), a deltaic island located in the middle of the WLD, is within one of the oldest lobes where the vegetation comprises complex associations of marshes and forested wetlands that are distributed along conspicuous elevation gradients. Mike Island is directly impacted by both sediment inputs from the main channel (Wax Lake Outlet, Figure1A) and episodic storm surges [ 36–38]. The northern region of Mike Island has a small secondary channel (northwest of station Mike1 on Figure1B) providing an entry point for water, sediment and nutrients from a primary channel to the interior of the island [39–41]. Approximately 23–54% of the flow from the primary channel enters the island via secondary channels and overbank flooding [39]. The tidal force also drives the sediment input and deposition [40] and is a controlling factor in the water flow direction within secondary channels in the WLD [39]. Vegetation aboveground biomass is highly seasonal with a peak at the end of summer, and as a result, surficial water flow can be greatly modified, increasing the water residence time. During winter, when vegetation density and aboveground biomass is sparse and distributed in small patches, uninterrupted water flow increases. We posed two overarching research questions of this study; first, what are the roles of wind, river discharge, waves, tides and vegetation in controlling sediment transport between an upstream and downstream location along Mike Island? How do these roles change in contrasting seasons and during river floods and cold fronts? We hypothesize that during spring, when river discharge is high and vegetation biomass is low, river discharge will be a dominant driver regulating sediment transport. Thus, the upstream location on Mike Island will be more influenced by river discharge while the downstream location will be more influenced by wave forcing due to the closer proximity to the semi-enclosed Atchafalaya Bay (Figure1A). During summer /fall, when river discharge is low and vegetation biomass is high, velocity will drop and wave impact will be minimal. Furthermore, episodic sediment accumulation on wetlands will occur during energetic events (e.g., cold fronts). Water 2020, 12, 2072 3 of 22

WaterThe second2020, 12, questionx FOR PEER is: REVIEW how does the plant–sediment interaction impact nutrient concentrations3 at of the 22 upstream and downstream locations during contrasting seasons? We hypothesize that overlying water − 3 3− waterNO3− NOand3 POand4 −POconcentrations4 concentrations will will be low be low during during the summerthe summer/fall/fall when when river river discharge discharge is low is low and + + andvegetation vegetation is dense is dense and and widespread, widespread, while while the NHthe 4NHconcentrations4 concentrations in sedimentin sediment porewater porewater will will be behigh high due due to remineralization.to remineralization.

FigureFigure 1. 1. ((AA)) Map Map of of the the National National Oceanic Oceanic and and Atmospheric Atmospheric Administration Administration (NOAA) (NOAA) Amerada Amerada Pass Pass (NOAA-8764227)(NOAA-8764227) wind wind and and the the United United States States Ge Geologicalological Survey Survey (USG (USGS)S) Calumet Calumet (USGS-07381590) (USGS-07381590) dischargedischarge stationsstations inin relation relation to to Mike Mike Island Island on theon Waxthe LakeWax Delta.Lake Delta. Black rectangleBlack rectangle displays displays the extent the of extentpanel (Bof). Thepanel circle (B). in The the Gulf circle of Mexicoin the insetGulf shows of Mexico the overall inset study shows area. the (B )overall Observational study /area.sampling (B) Observational/samplingstations Mike1 and Mike3 stations are located Mike1 ~1.5 and km Mike3 apart. are Base located maps ~1.5 in ( Akm,B) apart. are both Base from maps Google in (A Earth.) and (B) are both from Google Earth. 2. Materials and Methods 2. Materials and Methods 2.1. Study Area

2.1. StudyIf the Area Mississippi River were to naturally change its course, the next primary delta lobe would be in the Atchafalaya Bay area (Figure1A), considering its short distance to the shoreline and steep If the Mississippi River were to naturally change its course, the next primary delta lobe would gradient along that route [42,43]. In 1941, the U.S. Army Corps of Engineers constructed the Wax Lake be in the Atchafalaya Bay area (Figure 1A), considering its short distance to the shoreline and steep Outlet (WLO, Figure1A), diverting water from the Atchafalaya River to the northern Gulf of Mexico gradient along that route [42,43]. In 1941, the U.S. Army Corps of Engineers constructed the Wax to suppress flooding in Morgan City, Louisiana [42,44,45]. Although not the original purpose of the Lake Outlet (WLO, Figure 1A), diverting water from the Atchafalaya River to the northern Gulf of man-made WLO, subaqueous land began to form in 1952 as channelized sediment began to fill into Mexico to suppress flooding in Morgan City, Louisiana [42,44,45]. Although not the original purpose the Atchafalaya Bay; in 1973, this land became subaerial creating the WLD [42,44,45]. The Old River of the man-made WLO, subaqueous land began to form in 1952 as channelized sediment began to fill Control Structure, which was constructed in 1963, currently diverts 30% of the combined flow of the into the Atchafalaya Bay; in 1973, this land became subaerial creating the WLD [42,44,45]. The Old Mississippi and Red Rivers to the Atchafalaya River [35,44,46]. Although the WLO was man-made, River Control Structure, which was constructed in 1963, currently diverts 30% of the combined flow the WLD has continued to self-organize and grow naturally without the need for dredging or leveeing of the Mississippi and Red Rivers to the Atchafalaya River [35,44,46]. Although the WLO was man- since 1973 [44,45]. Previous work using radionuclides (7Be) indicates that high flooding conditions made, the WLD has continued to self-organize and grow naturally without the need for dredging or can result in up to 5 cm of flood sediment deposition (~0–2 cm/year) in some vegetated areas of the leveeing since 1973 [44,45]. Previous work using radionuclides (7Be) indicates that high flooding WLD [47]. conditions can result in up to 5 cm of flood sediment deposition (~0–2 cm/year) in some vegetated areas2.2. Sampling of the WLD Locations [47]. in Mike Island

2.2. SamplingTime series Locations of velocity, in Mike Island water level, turbidity and nutrient data were collected using six platform stations located on Mike Island and monitored by the Frontiers in Earth System Dynamics Time series of velocity, water level, turbidity and nutrient data were collected using six platform (FESD-National Science Foundation) project [40,48,49]. Two of these six platforms were used for our stations located on Mike Island and monitored by the Frontiers in Earth System Dynamics (FESD- National Science Foundation) project [40,48,49]. Two of these six platforms were used for our study. The Mike1 station is located at the north end of the island and close to a secondary channel where pulsing river discharge enters the island (Figure 1B). The other station, Mike3, is in the interior of the

Water 2020, 12, 2072 4 of 22 study.Water 2020 The, 12 Mike1, x FOR PEER station REVIEW is located at the north end of the island and close to a secondary channel4 of 22 where pulsing river discharge enters the island (Figure1B). The other station, Mike3, is in the interior ofisland, the island, about about1.5 km 1.5 south km southof Mike1 of Mike1 (Figure (Figure 1B). In1B). a normal In a normal river discharge river discharge condition, condition, the river the riverflows flowsinto Mike into Island Mike Islandthrough through a secondary a secondary channel, channel, passing passingthe upstream the upstream station (Mike1) station before (Mike1) reaching before reachingthe downstream the downstream station (Mike3). station(Mike3). This flow This directio flown, direction, however, however, can be reversed can be reversed during duringstorm events storm eventsor when or river when discharge river discharge is low and is low strong and strongflooding flooding tidal currents tidal currents come from come the from GOM the GOM[23]. [23].

2.3.2.3. Wind and Discharge DataData DataData collectedcollected fromfrom thethe nearbynearby National OceanicOceanic andand Atmospheric Administration (NOAA)(NOAA) andand UnitedUnited StatesStates GeologicalGeological SurveySurvey (USGS)(USGS) stationsstations werewere usedused to evaluate the wind speed and direction, asas wellwell asas river discharge. River discharge and gaugegauge height were obtained from the Wax LakeLake OutletOutlet stationstation inin Calumet, Calumet, located located approximately approximately 20 20 km km upstream upstream of of Mike Mike Island Island (USGS-07381590, (USGS-07381590, 29◦ 29°4141052”′52 N,″ 91N,◦ 2291°22022”′22 W)″ (FigureW) (Figure1A). Wind1A). Wind speed andspeed direction and direct dataion were data downloaded were downloaded from NOAA’s from NationalNOAA’s DataNational Buoy Data Center Buoy station, Center located station, at Amerada located at Pass Amerada on Atchafalaya Pass on Atchafalaya Delta (NOAA-8764227, Delta (NOAA-8764227, 29◦26058” N, 9129°26◦200′17”58″ N, W), 91°20 approximately′17″ W), approximately 12 km southeast 12 km of Mikesoutheast Island of (FigureMike Island1A). (Figure 1A).

2.4.2.4. Field and Laboratory Methods

2.4.1.2.4.1. Time-Series ObservationObservation AnAn arrayarray ofof acousticacoustic andand opticaloptical sensorssensors waswas deployeddeployed inin thethe springspring andand summersummer/fall/fall seasonsseasons ofof 2015.2015. TheThe objectiveobjective of of these these hourly hourly deployments deployments was was to identify to identify the spatiotemporal the spatiotemporal variations variations in twater in level,twater velocity, level, velocity, turbidity, turbidity, and waves. and The waves. spring The deployment spring deployment period was period from was 29 March from to29 2March May 2015 to 2 (hereafterMay 2015 April(hereafter 2015) April and the 2015) summer and the/fall summer/fall deployment deployment period was from period 28 Augustwas from to 2228 OctoberAugust to 2015 22 (hereafterOctober 2015 September–October (hereafter September–October 2015) to investigate 2015) seasonal to investigate differences seasonal in river discharge,differences vegetation in river biomassdischarge, and vegetation density. Inbiomass both periods, and density. an X-shaped In both platformperiods, wasan X-shaped deployed platform at the Mike1 was deployed station and at includedthe Mike1 an station acoustic and Doppler included velocimeter an acoustic (ADV) Doppler Argonaut velocimeter (SonTek, (ADV) San Diego, Argonaut CA, USA),(SonTek, optical San backscatterDiego, CA, sensorUSA), (OBS)optical 5 +backscatter(Campbell sensor Scientific, (OBS) Logan, 5+ (Campbell UT, USA), Scientific, and a wave Logan, gauge UT, (Ocean USA), Sensor and a Systems,wave gauge Inc., (Ocean Coral Springs, Sensor FL,Systems, USA) (FigureInc., Coral2A). InSpri thengs, case FL, of theUSA) Mike3 (Figure platform, 2A). aIn tripod the case was of used the toMike3 mount platform, an ADV a tripod Ocean was (SonTek), used to OBS mount 3A (Campbellan ADV Ocean Scientific), (SonTek), and OBS a wave 3A gauge(Campbell (Ocean Scientific), Sensor Systems,and a wave Inc.) gauge to compare (Ocean Sensor hydrology Systems, and sedimentInc.) to compare transport hydrology (Figure2 andB). The sediment variables transport measured (Figure in both2B). The sites variables are listed measured in Table1 .in both sites are listed in Table 1.

FigureFigure 2.2. (A). X-shapedX-shaped platformplatform deployeddeployed at Mike1Mike1 withwith anan acousticacoustic DopplerDoppler velocimetervelocimeter (ADV)(ADV) Argonaut,Argonaut, opticaloptical backscatterbackscatter sensorsensor (OBS)(OBS) 55+,+, andand aa wavewave gauge.gauge. (B) Tripod deployeddeployed atat Mike3Mike3 withwith instrumentsinstruments including including an an ADV ADV Ocean Ocean (sensor (sensor and and external external battery), battery), OBS OBS 3A, 3A, and and a wave a wave gauge. gauge. (C) Set(C) ofSet sediment of sediment traps traps used used for thefor collectionthe collection at the at sedimentthe sediment surface surface (S-S) (S-S) and and 30 cm 30 abovecm above the the bed bed (S-30); (S- the30); picture the picture was takenwas taken before before the set the was set insertedwas inserted into theinto sediment. the sediment.

Water 2020, 12, 2072 5 of 22

Table 1. Sampling specifications and placement of the instruments deployed at Mike1 and Mike3 during both field campaigns.

Distance Above Sampling Burst Sampling Station Instrument Sensor Orientation Sediment–Water Rate (Hz) Duration (s) Interval (s) Interface (cm) ADV downward looking 15 0.2 60 3600 Argonaut downward looking, Mike1 OBS 5+ optic window facing 15 1 60 3600 upstream Wave Gauge downward looking 15 10 1200 3600 ADV Ocean downward looking 15 1 1024 3600 downward looking, Mike3 OBS 3A optic window facing 15 1 60 3600 upstream Wave Gauge downward looking 15 10 1200 3600

2.4.2. Water Sampling and Analysis In situ water samples were collected near the sediment surface and in the middle of the for measurement of total suspended solid (TSS) using 2 L water bottles at Mike1 and Mike3 in March, May, August, and October of 2015. Water samples were stored in a cold room (4 ◦C) until filtration when the water was passed through a pre-weighed Whatman glass fiber filter with a 125 mm diameter and 0.7 µm pore size. The filter was then dried at 60 ◦C for 48 h and reweighed to determine suspended solid values. Overlying water approximately 10 cm above the water–sediment interface and porewater at 30 cm below the sediment surface were collected at Mike1 and Mike3 in vegetated and non-vegetated areas during March, May, August and October 2015 to measure inorganic nutrients (hereafter, referred to as the overlying and porewater values, respectively). Two 50 mL centrifuge tubes were collected at the vegetated and non-vegetated locations. The water was filtered in the field and stored in a cooler (4 ◦C) during transport to the laboratory the same day, where it was stored in a freezer until + 3 analysis of the inorganic nutrients (NO2−, NO3−, NH4 , and PO4 −) was completed within 1–3 days of collection. Nutrient concentrations were determined at the Wetland Biogeochemistry Analytical Services of Louisiana State University (LSU) via a segmented flow analysis using a Flow Solution IV AutoAnalyzer (OI Analytical, College Station, TX, USA).

2.4.3. Sediment Sampling and Analysis During the spring 2015 instrument deployment, a prototype sediment trap was tested and deployed at the Mike1 and Mike3 platforms. This trap consisted of two polyvinyl chloride (PVC) caps that were 4.45 cm in height and 10 cm in diameter (total volume ~350 cm3), and drain inserts placed on opposite sides of a 2.5 cm diameter PVC pipe (see Figure2C). One sediment trap was flushed with the sediment surface (hereafter “S-S”) and the other was located 30 cm above the sediment surface (hereafter “S-30”) (Figure2C). During the summer /fall deployment, triplicate sediment traps were deployed at Mike1 and Mike3. At the end of each deployment, the sediment traps were stored in a cold room (4 ◦C) until further analysis. In the laboratory, the sediment deposited in the trap was placed into a beaker to estimate the total volume of sediment or slurry, homogenized, and was then separated into two smaller beakers for loss-on-ignition and nutrient analysis. Another aliquot was placed in a centrifuge tube for grain size analysis. The sediment was weighed in a beaker before and after it was placed in an oven for at least 48 h to measure bulk density. The material in one beaker was placed in a muffler furnace at 550 ◦C for 2.5 h to eliminate organic matter [50] while the sediment in the other beaker was ground and packed for analysis of the total carbon (TC), nitrogen (TN) and phosphorus (TP) concentrations. TC and TN were determined on two analytical replicates with an elemental Water 2020, 12, 2072 6 of 22 combustion system (ECS) 4010 (Costech Analytical Technologies, Inc., Valencia, CA, USA). TP was extracted on duplicate core samples with 1 N HCL after combustion in a furnace at 550 ◦C[51] and determined by colorimetric analysis using a segmented flow analysis Flow Solution IV AutoAnalyzer (OI Analytical, College Station, TX, USA).

2.5. Data Analysis Data collected from the acoustic and optical sensors were plotted and analyzed using MATLAB software. Relative water levels at Mike1 and Mike3 were calculated by subtracting the means from the measured levels using wave gauges. Water level data from Calumet, Mike1, and Mike3 in spring and summer/fall 2015 were analyzed using the Fast Fourier Transform (FFT) function in MATLAB to quantify periodicities. Coefficients of determination (R2) between the water levels in Mike1 and Mike3 were also calculated. Wave data were analyzed using a toolbox developed by Karimpour and Chen [52], and the averages and standard deviations of each period were quantified. Two-factor analysis of variance (ANOVA) tests were run on all biogeochemical data to determine the significance of each group/factor and their interaction in our experimental design using JMP Pro 12 (SAS Institute, Cary, NC, USA). In the case of the sediment trap data, trap location (upstream, downstream), collection location (water column, sediment surface), and their interaction were considered fixed factors to determine the differences in TN, TC, TP, and bulk density. Nutrient concentrations in the surface and porewaters were analyzed by the following factors: location (upstream, downstream), month of collection (May, October), vegetation presence (yes, no) and water source (overlying, porewater), and their interaction. The water nutrient data were log-transformed and evaluated for normality and sample size prior to the statistical analyses [53]. The response variables for the water nutrients were + 3 total inorganic nitrogen (TIN = NO2− + NO3− + NH4 ) and PO4 −. Tukey honest significant difference tests were run on significant interactions when appropriate. All significant results were determined by an alpha value = 0.05.

3. Results

3.1. Water Column Processes Wind data collected from the NOAA buoy station in Amerada Pass recorded wind speeds primarily between 4 and 5 m/s during the spring deployment (Figure3A). During 2015, discharge from the Atchafalaya River was higher than in previous years and extended into late July. During the spring instrument deployment, the river was in a flood stage and discharging approximately 5500 m3/s at the Calumet monitoring station. The gage height at this station during the spring deployment was around 1.7–1.8 m with minimum variation during the deployment (Figure3B). Relative water level variations at both Mike1 and Mike3 during the spring deployment were between 0.3 and 0.3 m (Figure3C). − Although Mike1 and Mike3 were in phase most of the time, the tidal ranges at Mike3 were slightly larger than those recorded at Mike1 during some lower water levels in the slack water stage (Figure3C). The tides shifted between semidiurnal (two highs and two lows during a lunar day) and diurnal (one high and one low) patterns multiple times during April 2015. Water 2020, 12, 2072 7 of 22 Water 2020, 12, x FOR PEER REVIEW 7 of 22

Water 2020, 12, x FOR PEER REVIEW 7 of 22

FigureFigure 3. Wind, 3. Wind, relative relative water water level, level, and and water water levellevel difference difference measurements measurements (A– (DA)– fromD) from the April the April 2015 instrument2015 instrument deployment deployment at at Mike1 Mike1 and and Mike3. Mike3. Note the the increase increase in inwind wind speed speed andand relative relative water water levelFigurelevel towards towards3. Wind, the endtherelative end of April. ofwater April. Thelevel, The Calumet andCalumet water discharge discharge level difference station station measurements(B (B) )is is located located ~20 ( ~20A km–D km)upstream from upstream the ofApril Mike of Mike 2015Island instrument (29°41′52 deployment″ N, 91°22′22 at″ Mike1 W). Wind and Mike3.speed andNote direction the increase data in were wind downloaded speed and relative from NOAA’s water Island (29◦41052” N, 91◦22022” W). Wind speed and direction data were downloaded from NOAA’s level towards the end of April. The Calumet discharge station (B) is located ~20 km upstream of Mike NationalNational Data Data Buoy Buoy Center Center station, station, located located at at AmeradaAmerada Pass on on Atchafalaya Atchafalaya Delta Delta (see (see methods). methods). Island (29°41′52″ N, 91°22′22″ W). Wind speed and direction data were downloaded from NOAA’s Wave,NationalWave, current Datacurrent velocity, Buoy velocity, Center and station, and turbidity turbidity located parameters at parameters Amerada werePass were on measured Atchafalayameasured at Deltaat Mike1 Mike1 (see and methods).and Mike3 Mike3 duringduring both both deployments. During the spring deployment, significant wave height at Mike1 was usually < 1 deployments. During the spring deployment, significant wave height at Mike1 was usually < 1 cm, cm,Wave, with a current few small velocity, peaks inand wave turbidity height parameters up to 4.24 cm were (Figure measured 4A); average at Mike1 and and standard Mike3 deviation during with a few small peaks in wave height up to 4.24 cm (Figure4A); average and standard deviation bothof wave deployments. heights during During spring the spring at Mike1 deployment, were 0.37 si andgnificant 0.32 cm, wave respectively. height at Mike1 Wave washeights usually at Mike3 < 1 of wavecm,were with heights generally a few duringsmall higher peaks spring than in inwave at Mike1, Mike1 height with were up wave to 0.37 4.24 heights andcm (Figure 0.32primarily cm, 4A); respectively. betweenaverage and0 and standard Wave 4 cm. heightsDuring deviation some at Mike3 wereofstorm generallywave eventsheights higher in during late than April spring in 2015, Mike1, at Mike1wave with heightwere wave 0.37 reached heights and 0.32 24.67 primarily cm, cm, respectively. the highest between Wavewaves 0 and heights measured 4 cm. at During Mike3 during some stormwereall events sampling generally in late periods higher April than(Figure 2015, in Mike1, 4A); wave the heightwith average wave reached and heights standard 24.67 primarily cm, deviation the between highest of wave 0 and waves heights 4 cm. measured During during some spring during all samplingstormat Mike3 events periods were in late (Figure 0.79 April and4A); 2015,1.67 the cm,wave average respectively. height and reached standard Average 24.67 deviationcurrentcm, the speedhighest ofwave at waves Mike1 heights measured was during23 cm/s during springwith at Mike3allsignificant sampling were 0.79 fluctuationsperiods and 1.67 (Figure cm, (Figurerespectively. 4A); 4B).the averageDue Averageto instrument and st currentandard battery deviation speed failure at Mike1of (ADV wave was Ocean),heights 23 cm duringno/s current with spring significant data fluctuationsatwere Mike3 collected (Figurewere 0.79 at4B). Mike3. and Due 1.67 Using to instrumentcm, anrespectively. OBS, a battery proxy Average failureof turbidity current (ADV (in Ocean),speed nephelometric at noMike1 current turbiditywas data23 cm/s wereunit-NTU) with collected significant fluctuations (Figure 4B). Due to instrument battery failure (ADV Ocean), no current data at Mike3.was measured Using an at OBS, Mike1 a and proxy Mike3. of turbidity At Mike1, (in turbidity nephelometric remained relatively turbidity low unit-NTU) until a storm was impact measured werein late collected April (Figure at Mike3. 4C). Using At Mike3, an OBS, optical a proxy turbidity of turbidity data showed (in nephelometric a noisy response turbidity (Figure unit-NTU) 4D). at Mike1was measured and Mike3. at Mike1 At Mike1,and Mike3. turbidity At Mike1, remained turbidity relatively remained lowrelatively until low a storm until a impact storm impact in late April (Figurein late4C). April At Mike3,(Figure 4C). optical At Mike3, turbidity optical data tu showedrbidity data a noisy showed response a noisy (Figureresponse4D). (Figure 4D).

Figure 4. Hydrological variables and turbidity variations, measured in nephelometric turbidity unit- NTU, (A–D) at monitoring stations located in Mike Island (Wax Lake Delta, LA, USA) during FigureFigureinstrument 4. 4.Hydrological Hydrological deployment variables variables in April and 2015; and turbidity note turbidity the variations enhanc variations,ed, measuredwave height measured in nephelometricat Mike3 in and nephelometric turbidity turbidity at unit- Mike1 turbidity unit-NTU,NTU,during (A (–lateAD–)D Aprilat) atmonitoring monitoring(rectangle stations inset). stations See located the located me inthods Mike in section Mike Island Islandfor (Wax the instruments’ (WaxLake LakeDelta, Delta, description.LA, USA) LA, USA)during during instrument instrument deployment deployment in in April April 2015;2015; note note the the enhanc enhanceded wave wave height height at Mike3 at Mike3 and turbidity and turbidity at Mike1 at Mike1 during late April (rectangle inset). See the methods section for the instruments’ description. during late April (rectangle inset). See the methods section for the instruments’ description.

Water 2020, 12, 2072 8 of 22 Water 2020, 12, x FOR PEER REVIEW 8 of 22

During the the summer/fall summer/fall deployment deployment,, wind wind speeds speeds ranged ranged from from 3 to 34 tom/s 4 with m/s witha few alarge few peaks large 3 peaksnear 7 nearm/s (Figure 7 m/s (Figure5A), while5A), rive whiler discharge river discharge was much was lower much (1000 lower m3/s). (1000 The m water/s). level The waterat Calumet level atfluctuated Calumet between fluctuated 0.3 betweenand 1.2 m 0.3 (lower and 1.2than m 1.8 (lower m inthan April 1.8 2015) m in and April showed 2015) a and higher showed variation a higher due variationto the influence due to theof tides influence (Figure of tides 5B). (FigureMike1 5andB).Mike1 Mike3 and water Mike3 levels water were levels less were influenced less influenced by local byhydrodynamics local hydrodynamics during duringthe summer/fall the summer due/fall to due low to lowriver river discharge. discharge. Water Water level level varied varied by approximately 0.6 m throughout the deployment at Mike1 and mimicked a strong tidal signal similar to CalumetCalumet (Figure(Figure5 C).5C). At At Mike3, Mike3, water water levels levels followed followed a similar a similar tidal tidal oscillation oscillation (Figure (Figure5C). At 5C). both At stations,both stations, tides tides shifted shifted between between diurnal diurnal and and semidiurnal semidiurnal patterns patterns and and the the lowest lowest water water levellevel was observed in early October because of the passage of a cold front (Figure 55B,C).B,C). DuringDuring thisthis event,event, energetic winds of 5 mm/s/s blew from the north for more than 5 days, lowering water levels by 0.8 m at Mike1, Mike3, and Calumet stations.

Figure 5. Wind speed and relative water elevationelevation data during the instrumentinstrument deployment in Mike Island (Wax(Wax Lake Lake Delta, Delta, LA, LA, USA) USA) in September–Octoberin September–October 2015; 2015; (A) wind(A) wind direction direction and speed, and speed, (B) water (B) lever,water (lever,C) relative (C) relative water lever,water (lever,D) water (D) levelwater di levelfference difference (Mike3 (Mike3 minus minus Mike1); Mike1); note the note drop the in drop the waterin the levelwater in level early Octoberin early 2015October (rectangle 2015 (rectangle inset). See inset). methods See section methods for instruments’section for instruments’ description. Winddescription. speed andWind direction speed and data direction were downloaded data were fromdownloaded NOAA’s from National NOAA’s Data National Buoy Center Data station Buoy locatedCenter station at Amerada located Pass at Amerada on Atchafalaya Pass on Delta Atchafalaya (see methods). Delta (see methods).

Wave height at Mike1 Mike1 during during th thee summer/fall summer/fall deployme deploymentnt was was close close to to 0 m 0 mthroughout throughout most most of ofthe the sampling sampling period period (Figure (Figure 6B).6 ThereB). There were were severa severall small small peaks, peaks, but they but rarely they rarelyexceeded exceeded a few cm a few(Figure cm 6B). (Figure Wave6B). heights Wave heightsat Mike3 at were Mike3 also were minimal also minimal(Figure 6B). (Figure Average6B).Average and standard and standard deviation deviationof wave heights of wave during heights summer/fall during summer at Mike1/fall were at Mike1 0.17 were and 0.24 0.17 cm, and respectively. 0.24 cm, respectively. At Mike3, At average Mike3, averageand standard and standard deviation deviation of wave ofheights wave were heights 0.02 were and 0.020.07 andcm, respectively. 0.07 cm, respectively. Average Averagecurrent velocity current velocitycollected collected by the ADV by the Argonaut ADV Argonaut at Mike1 at was Mike1 approximately was approximately 13 cm/s 13 (Figure cm/s (Figure 6C). At6 C).Mike3, At Mike3, water watervelocities velocities were up were to up30 tocm/s 30 cmduring/s during the first the firstweek week then then rapidly rapidly decreased decreased to near to near 0 cm/s 0 cm /ons on 6 6September September 2015 2015 and and remained remained low low throughout throughout the the re restst of of the the deployment deployment (Figure (Figure 6D).6D). There There were were a afew few periods periods where where the the velocity velocity reached reached 5 5or or 10 10 cm/s cm/s,, but but overall, overall, the the first first week of the summersummer/fall/fall deployment waswas distinctly distinctly di ffdifferenterent from from the restthe ofre thest of deployment the deployment period. pe Turbidityriod. Turbidity values collected values atcollected Mike1 wereat Mike1 typically were low,typically but there low, were but there several were peaks several throughout peaks throughout the deployment the deployment (Figure6E). Many(Figure of 6E). the Many large spikesof the large in turbidity spikes datain turbidity were likely data duewere to likely acoustic due noiseto acoustic from thenoise presence from the of vegetation.presence of Thevegetation. turbidity The data turbidity collected data at Mike3 collected were at not Mike3 as variable were not as as in variable Mike1 (Figure as in Mike16F). However, (Figure there6F). However, was one sharpthere increasewas one insharp turbidity increase on 6 in September turbidity 2015on 6 thatSeptember coincided 2015 with that a velocitycoincided decrease with a atvelocity Mike3. decrease Moreover, at ourMike3. TSS valuesMoreover, collected our fromTSS bottlevalues samples collected generally from bottle decreased samples from generally March to Augustdecreased and from increased March in to October August (see and Table increased2). The in high October surface (see turbidity Table 2). value The registeredhigh surface at Mike1turbidity in value registered at Mike1 in October compared to the middle water column value is most probably a result of resuspension caused by disturbance prior to sampling.

Water 2020, 12, 2072 9 of 22

October compared to the middle water column value is most probably a result of resuspension caused byWater disturbance 2020, 12, x FOR prior PEER to REVIEW sampling. 9 of 22

Table 2.2.Total Total suspended suspended solids solids (TSS) (TSS) concentrations concentrations in the in surface the surface and middle and middle water column water sampledcolumn insampled March, in May, March, August May, and August October and 2015 Octo atber both 2015 Mike1 at both and Mike1 Mike3 and stations. Mike3 stations.

DayDay Month Month Location Location Surface Surface TSS TSS (mg/L) (mg/L) Middle Middle TSS (mg(mg/L)/L) Mike1Mike1 187.57 187.57 235.43 3030 March March Mike3Mike3 75.71 75.71 103.48 Mike1Mike1 99.57 99.57 122.67 2 2 MayMay Mike3Mike3 80.24 80.24 53.93 Mike1Mike1 41.38 41.38 101.24 2828 AugustAugust Mike3Mike3 17.76 17.76 22.29 Mike1Mike1 377.55 377.55 28.38 2222 OctoberOctober Mike3Mike3 53.07 53.07 110.43

Figure 6.6. WaterWater temperature, temperature, wave wave height, height, current current velocity, velocity, and turbidity data, measured in nephelometric turbidity unit-NTU, during the inst instrumentrument deployment in in Mike Island (Wax Lake Delta, LA, USA) in SeptemberSeptember/October/October 2015; ( A) temperature, ( B) wave height, ( C) current velocity (Mike1), (D) current velocity (Mike3), (E) turbidity (Mike1), (F) turbidity (Mike3); note the sharp water velocity reduction and increase inin turbidityturbidity atat Mike3Mike3 onon 66 SeptemberSeptember 20152015 (rectangle(rectangle inset).inset).

2 The coecoefficientfficient of of determination determination (R )(R values2) values between between Mike1 Mike1 and Mike3 and waterMike3 levels water were levels estimated were 2 usingestimated hourly using data. hourly These data. measurements These measurements were distributed were distributed near the near 1:1 line the in1:1 both line Aprilin both (R April= 0.91) (R2 2 and= 0.91) September–October and September–October (R = 0.84) (R2 = 2015 0.84) (Figure 2015 7(Figure), revealing 7), revealing that water that levels water at levels the two at stationsthe two werestations tightly were coupled tightly duecoupled to their due close to their proximity close (1.5proximity km). FFT (1.5 results km). FFT showed results that showed semidiurnal that (approximatelysemidiurnal (approximately 2 cycles/day) 2 andcycles/day) diurnal (approximatelyand diurnal (approximately 1 cycle/day) 1 tides cycle/day) dominated tides bothdominated Mike1 andboth Mike3Mike1 inand both Mike3 April in andboth September–October April and Septembe 2015r–October (Figure 20158); the (Figure semidiurnal 8); the semidiurnal tidal signal wastidal alwayssignal was stronger always than stronger the diurnal. than the Semidiurnal diurnal. Semidiurnal and diurnal and signals diurnal at the signals Calumet at the station Calumet were station visible inwere September–October visible in September–October 2015, but not 2015, detectable but not in detectable April 2015 in (Figure April8 2015). (Figure 8).

Water 2020, 12, x FOR PEER REVIEW 10 of 22 Water 2020, 12, 2072 10 of 22 Water 2020, 12, x FOR PEER REVIEW 10 of 22 0.5 0.5 A. B. 0.5 0.5 A. B. 0.25 0.25 0.25 0.25

0 0 0 R2=0.91 0 R2=0.84 2 2 -0.25 R =0.91 -0.25 R =0.84 -0.25 -0.25 1:1 line 1:1 line -0.5 -0.5 -0.51:1 -0.25 line 0 0.25 0.5 -0.51:1 -0.25 line 0 0.25 0.5 -0.5 -0.5 Water-0.5 Level(m) -0.25 at 0 Mike1 0.25 in April 0.5 Water-0.5 Level(m) -0.25 at Mike1 0 in 0.25 Sep-Oct 0.5 Figure 7. CoefficientsWater Level(m) of determination at Mike1 (R in2) Aprilbetween Mike1Water and Mike3 Level(m) water at levelsMike1 in in April Sep-Oct (A) and September–OctoberFigureFigure 7. 7.Coe Coefficientsfficients (B) of 2015.of determination determination Mike1 and (R Mike3(R2)2) between between are 1.5 Mike1 kmMike1 apart and and and Mike3 Mike3 their water water water levels levels levels in in Aprilare April generally (A (A) and) and tightlySeptember–OctoberSeptember–October coupled. (B (B) 2015.) 2015. Mike1 Mike1 and and Mike3 Mike3 are are 1.5 1.5 km km apart apart and and their their water water levels levels are are generally generally tightlytightly coupled. coupled.

FigureFigure 8. WaterWater levellevel cycles cycles/day/day at theat the Calumet Calumet (dashed (das black),hed black), Mike1 Mike1 (blue) and(blue) Mike3 and (red) Mike3 sampling (red) stations in April (A) and September–October (B) 2015. Tidal cycles at the Calumet station are barely samplingFigure 8.stations Water in level April cycles/day (A) and September–October at the Calumet (das (B)hed 2015. black), Tidal Mike1cycles at(blue) the Calumetand Mike3 station (red) detected in April due to spring river flood dominance. aresampling barely detected stations in in April April due (A) to and spring September–October river flood dominance. (B) 2015. Tidal cycles at the Calumet station Asare mentioned barely detected above, in April the presence due to spring of vegetation river flood during dominance. the September /October deployment had As mentioned above, the presence of vegetation during the September/October deployment had an impact on the water level, current velocity, and turbidity values. The increase in vegetation density an impact on the water level, current velocity, and turbidity values. The increase in vegetation density and biomassAs mentioned in Mike above, Island atthe the presence regional of scale vegetation is controlled during by the a September/October significant increase indeployment air and water had andan biomass impact on in theMike water Island level, at the current regional velocity, scale andis controlled turbidity by values. a significant The increase increase in vegetation in air and waterdensity temperature. During the spring deployment when water temperature ranged from 14 to 26 ◦C, based temperature. During the spring deployment when water temperature ranged from 14 to 26 °C, based onand the biomass OBS 3A in data, Mike vegetation Island at the was regional sparse andscale patchy is controlled across by the a studysignificant area. increase In contrast, in air during and water the on the OBS 3A data, vegetation was sparse and patchy across the study area. In contrast, during the summertemperature./fall deployment, During the spring vegetation deployment was dense when and wa widespreadter temperature due to ranged higher from water 14 temperaturesto 26 °C, based summer/fallon the OBS deployment, 3A data, vegetation vegetation was was sparse dense and and patc widespreadhy across the due study to higher area. In water contrast, temperatures during the (range: 19–31 ◦C) and nutrient availability, particularly NO3−. This high vegetation biomass and (range: 19–31 °C) and nutrient availability, particularly NO3−. This high vegetation biomass and associatedsummer/fall peak deployment, productivity vegetation is widely observedwas dense along and the widespread Louisiana due coastline to higher [5], especially water temperatures across the associated peak productivity is widely observed along the Louisiana− coastline [5], especially across delta(range: plain 19–31 [54]. The°C) physicaland nutrient impact availability, of this high vegetationparticularly density NO3 . isThis reflected high invegetation the relative biomass differences and the delta plain [54]. The physical impact of this high vegetation density is reflected in the relative andassociated fluctuations peak inproductivity the current is velocity widely betweenobserved the along April the and Louisiana September–October coastline [5], especially deployment across at differences and fluctuations in the current velocity between the April and September–October eachthe stationdelta plain (Figures [54].4 BThe and physical6C,D). This impact change of this in velocity high vegetation influences density both local is reflected hydrodynamics in the relative and deployment at each station (Figures 4B and 6C,D). This change in velocity influences both local sedimentdifferences transport and fluctuations at different levelsin the when current interacting velocity with between shifts inthe tidal April periodicity and September–October across the island. hydrodynamics and sediment transport at different levels when interacting with shifts in tidal Thedeployment seasonal diatff eacherence station in vegetation (Figures biomass4B and and6C,D). spatial This extensionchange in is velocity underscored influences by LANDSAT both local periodicityhydrodynamics across theand island. sediment The transportseasonal differen at differentce in vegetationlevels when biomass interacting and spatial with shiftsextension in tidal is periodicity across the island. The seasonal difference in vegetation biomass and spatial extension is

Water 2020, 12, 2072 11 of 22 Water 2020, 12, x FOR PEER REVIEW 11 of 22 imagery,underscored contemporaneous by LANDSAT imagery, to our instrument contemporaneou deploymentss to our datesinstrument (Figure deployments9). Indeed, evendates during(Figure periods9). Indeed, of loweven biomass, during thereperiods is stillof low vegetation biomass, present there is along still thevegetation northern present edges along of Mike the Island northern due toedges a higher of Mike elevation Island due and to species-specific a higher elevation spatial and distributionspecies-specific along spatial the ridge distribution (Figure along9A) [ the40,48 ridge,55]. This(Figure vegetation 9A) [40,48,55]. enhances This sediment vegetation retention enhances and amelioratessediment retent stormion surge and impactameliorates during storm cold frontssurge duringimpact theduring winter cold season fronts [ 55during]. the winter season [55].

Figure 9. LANDSATLANDSAT images processed using data from the USGS [[56]56] and analyzed by the Earth Scan Laboratory at Louisiana State University (LSU). Im Imagesages show the vegetation cover on Mike Island during (A)) lowlow densitydensity andand biomass biomass on on 19 19 April April 2015, 2015, and and (B ()B the) the peak peak end end of of summer summer productivity productivity on 25on August25 August 2015. 2015.

3.2. Overlying and Porewater Inorganic Nutrient Concentrations Due to logistical and sampling limitations, nutrient sampling did not occur during all months (i.e., March, May, August,August, October).October). TIN concentrat concentrationsions showed showed a a significant significant three-order three-order interaction: interaction: month of collection (May, October), location (upstream, downstream), and compartment (overlying, porewater) (p == 0.0062) (Table S1).S1). The The la largestrgest nitrogen nitrogen form form contributing to porewater TIN + concentrations is [NH + ] (78.6 9.5 µM), while [NO − ] is the main contributor to overlying water TIN concentrations is [NH44 ] (78.6 ±± 9.5 μM), while [NO3 −] is the main contributor to overlying water TIN (22.5 3.6 µM). Average TIN was significantly higher in the porewater in October at Mike1 (115.4 µM) (22.5 ±± 3.6 μM). Average TIN was significantly higher in the porewater in October at Mike1 (115.4 andμM) Mike3and Mike3 (101.5 (101.5µM) thanμM) inthan the in other the other collection collection dates dates or compartments or compartments (Figures (Figures 10 and 10 11 and). 11). Soluble reactive phosphorus (SRP, PO 3 ) showed a significant two-order statistical interaction Soluble reactive phosphorus (SRP, PO443−) showed a significant two-order statistical interaction between stationstation location location (upstream (upstream or or downstream) downstream) and and month month of collection of collection (May, (May, October) October) (p = 0.0004) (p = (Table S2). During May 2015, there was no significant difference in PO 3 concentrations in overlying 0.0004) (Table S2). During May 2015, there was no significant difference4 − in PO43− concentrations in wateroverlying between water thebetween upstream the upstream and downstream and downstre locationsam locations (Figure 10 (Figure). Additionally, 10). Additionally, there was there no 3 significant difference (p = 0.3071) (Table S4) in the PO 3concentration− between the vegetated was no significant difference (p = 0.3071) (Table S4) in the 4PO− 4 concentration between the vegetated and non-vegetated areas downstream, whereas the concentration in the non-vegetatednon-vegetated locations upstream was significantly significantly greater than in the vegetated areas areas in May 2015 ( p = 0.0067)0.0067) (Table (Table S3). S3). 3 However, during October, the upstream location had significantly higher concentrations of PO 3− ; However, during October, the upstream location had significantly higher concentrations of PO44 −; downstream concentrations at Mike3 did not varyvary significantlysignificantly betweenbetween thethe seasons.seasons. Location and 3 p vegetation presence hadhad aa significantsignificant interactioninteraction inin determiningdetermining POPO443−− concentrations ( p = 0.0188) 3 (Table S2);S2); thethe highesthighest POPO443− valuesvalues were were measured measured in in the the non-vege non-vegetatedtated area area at at the the upstream upstream location (Mike1) (Figures 10 and 1111).). Additionally, there was a significantsignificant interactioninteraction between compartment (i.e., overlyingoverlying water water and and porewater) porewater) and and vegetation vegetation presence presence (p = (0.0331)p = 0.0331) (Table (Table S2). Overall,S2). Overall, the mean the 3 PO concentration3− was higher in the overlying water (1.25 0.16 µM)) than in the sediment porewater mean4 − PO4 concentration was higher in the overlying water± (1.25 ± 0.16 μM)) than in the sediment (Figuresporewater 10 (Figures and 11). 10 and 11).

Water 2020, 12, 2072 12 of 22 Water 2020, 12, x FOR PEER REVIEW 12 of 22

3− Figure 10. Soluble reactive phosphorus (SRP, PO43−) and total inorganic nitrogen (TIN) concentrations FigureFigure 10. 10.Soluble Soluble reactive reactive phosphorus phosphorus (SRP,(SRP, POPO4 −) )and and total total inorganic inorganic nitrogen nitrogen (TIN) (TIN) concentrations concentrations (µM)(μM) in in overlying overlying water water at at the the Mike1Mike1 (square)(square) and Mike3 (cross) (cross) locations locations during during May May (blue) (blue) and and OctoberOctober (red) (red) 2015; 2015; standard standard error error bars bars areare includedincluded in both the the x x and and y y dimensions. dimensions.

3− FigureFigure 11. 11.Soluble Soluble reactive reactive phosphorus phosphorus (SRP,(SRP, POPO44 −) )and and total total inorganic inorganic nitrogen nitrogen (TIN) (TIN) concentrations concentrations (µM)(μM) in in porewater porewater at at the the Mike1 Mike1 (square) (square) andand Mike3 (cross) (cross) locations locations during during May May (blue) (blue) and and October October (red)(red) 2015; 2015; standard standard error error bars bars are are present present inin bothboth thethe x and y y dimensions. dimensions.

3.3.3.3. Sediment Sediment Trap Trap TheThe prototype prototype sediment sediment traps traps used used inin AprilApril 2015 at at Mike1 Mike1 and and Mike3 Mike3 to to capture capture sediment sediment at two at two levels,levels, i.e., i.e., 30 30 cm cm above above the the sediment–water sediment–water interface (S-30) (S-30) and and on on the the sediment sediment surface surface (S-S), (S-S), were were successfulsuccessful in in trapping trapping sediment.sediment. In In our our study, study, sand, sand, silt, silt, and and clay clay are defined are defined as >63 as μ>m63 (<4µ mphi), (< 463– phi), 63–44 μµmm (4–8 (4–8 phi) phi) and and <4< 4μµmm (>8 (> phi),8 phi), respectively. respectively. During During spring spring 2015, 2015, sediment sediment traps traps were were deployed deployed onon 28 28 March March and and retrieved retrieved on on 2 2 May May 2015. 2015. Since there was was only only one one trap trap set set (N (N = =1) 1)deployed deployed at Mike1 at Mike1

Water 2020, 12, 2072 13 of 22 Water 2020, 12, x FOR PEER REVIEW 13 of 22 and Mike3, no statistical analyses were performed to evaluate differences differences in sediment accumulation in the the traps traps between between dates; dates; only only general general trends trends are are presented. presented. Bulk Bulk density density values values estimated estimated per trap per weretrap were1.5 (S-30) 1.5 (S-30) and 1.4 and (S-S) 1.4 (S-S)g/cm g3 /atcm Mike1.3 at Mike1. However, However, at Mike3, at Mike3, bulk bulkdensity density values values were were only only0.53 (S-30)0.53 (S-30) and and0.47 0.47(S-S) (S-S) g/cm g/cm3. Similar3. Similar bulk bulk density density values values were were registered registered during during the the summer deployment. Average Average bulk density values at Mike1 were 1.25 (S-30) and 1.15 (S-S) gg/cm/cm3.. At At Mike3, Mike3, average bulk density values were much lower, with 0.23 (S-30) and 0.03 gg/cm/cm33 (S-S); the low values might be associated with the proportion of sedime sedimentnt slurry and excess water contained in the traps after sampling. The sediment collected in the traps deployed deployed at at Mike1 Mike1 and and Mike3 Mike3 was was also also analyzed analyzed for for TN, TN, TP, TP, and TC content (Table3 3)) andand graingrain size size distribution. distribution. InIn spring,spring, thethe dominantdominant graingrain sizesize trappedtrapped atat Mike1 was fine fine sand and coarse silt in both the S- S-3030 and S-S traps (Figure 12A).12A). At Mike3, the trapped sediment was more poorly sorted, and and silt silt was was the the dominant dominant grain grain size size in in both both traps traps (Figure (Figure 12A).12A). During thethe summersummer/fall/fall deployment, deployment, a a similar similar pattern pattern in in grain grain size size was was found; found; the the dominant dominant grain grain size sizein Mike1 in Mike1 was finewas sandfine sand (Figure (Figure 12B). 12B). However, However, at Mike3, at Mike3, a bimodal a bimodal distribution distribution was apparent, was apparent, with a primarywith a primary mode inmode silt and in silt a secondary and a secondary mode in mode sand in (Figure sand (Figure 12B). 12B).

(B)

Figure 12. Grain size distribution (µm) of sediment collected in the traps during (A) 28 March–2 May Figure2015 and 12. ( BGrain) 28 August–2size distribution October (μ 2015.m) of Seesediment Figure collected2C showing in the the traps trap during setup at(A bottom) 28 March–2 (sediment May 2015surface) and and (B) water28 August–2 column October (30 cm above 2015. sedimentSee Figure surface) 2C showing positions. the trap setup at bottom (sediment surface) and water column (30 cm above sediment surface) positions.

Water 2020, 12, 2072 14 of 22

Table 3. Sediment total phosphorus (TP), total nitrogen (TN) and total carbon (TC) concentrations (mg/cm3). Sediment was collected in sediment traps located at the sampling stations Mike1 and Mike 3 during the spring (n = 1) and summer/fall 2015 (n = 3) deployments. See Figure2C and methods section for trap specifications and sampling description.

SPRING SUMMER/FALL TP TN TC TP TN TC (mg/cm3) (mg/cm3) (mg/cm3) (mg/cm3) (mg/cm3) (mg/cm3) Water Column 0.5804 6.34 84.02 0.5658 10.91 123.4 Mike1 Sediment Surface 0.5758 6.68 92.98 0.5796 11.51 120.2 Water Column 0.4282 10.91 10.95 0.0919 3.35 32.2 Mike3 Sediment Surface 0.4494 11.51 13.25 0.1988 7.57 78.4

4. Discussion

4.1. Water Column Processes Mike Island is part of a dynamic system where seasonal pulsing regulates several hydrodynamic forcings throughout the WLD, including waves, tides, river discharge, and currents that in turn control elevation gradients characterized by distinct vegetation communities. High river discharge during the spring strongly influenced the hydrology of the secondary channel located at the northern end of Mike Island; this channel serves as an entry point of riverine waters into the island interior. Since the channel is narrow, the flow recorded by the ADV Argonaut instrument at Mike1 during the spring is relatively high (Figure4B). Comparatively, the Mike1 station is not influenced by waves from the GOM like Mike3, as shown by the wave height during spring 2015 (Figure4A). This pattern was expected due to the proximity of Mike3 to the extensive and semi-enclosed Atchafalaya Bay (Figure1). During a 3 day period in late April 2015, turbidity values at Mike3 were variable and characterized by several large spikes (Figure4C). It is possible that some optical noise in the OBS data from Mike3 was due to vegetation growth and/or floating organic matter (e.g., leaves and vegetation mats). Nevertheless, our data recorded the passing of a strong wind-driven storm through the Louisiana coast on 27 April 2015, which was associated with a number of distinct physical processes: high wind speed at Amerada Pass, high water level at Calumet (Figure3A,B), taller wave height in Mike3 (Figure4A), and a notable increase in water turbidity at Mike1 (Figure4C). River discharge in 2015 was generally higher than the long-term average annual records during our study. However, river discharge was lower during the summer/fall deployment, resulting in a smaller impact on Mike Island local hydrodynamics during peak plant biomass and productivity. Average current velocity at Mike1 during the summer/fall deployment was high (~16 cm/s), but comparatively lower than the spring deployment (~23 cm/s) (Figures4B and6C). Since river discharge was lower during the summer/fall, the water flow entering the island through the secondary channel was weaker, as indicated by the lower water velocity at Mike1 during this season. During the summer/fall deployment, vegetation had no measurable impact on the flow at Mike1 because the channel was not yet completely colonized by aquatic/wetland plants when compared to the remainder of the island area. The higher velocity measurements at Mike1 than Mike3 during the summer/fall support this conclusion (Figure6). However, peak biomass and productivity likely influenced the low wave heights observed at both Mike1 and Mike3 during this deployment (Figure6B). During the first week of the summer/fall deployment at Mike3, the velocity was higher (~30 cm/s) than the velocity recorded at Mike1 during the spring (~23 cm/s) (Figures4B and6D). Furthermore, there was a surprising reduction in the velocity with a concurrent increase in turbidity at Mike3 around 6 September 2015. During the entire summer/fall deployment, the quality of the ADV velocity u, v and w components at Mike3 was generally above 80%. Previous studies have suggested that vegetation presence creates a channel where the velocity is maintained between the vegetated areas but suppressed within these habitats [30]. It is likely that the seasonal vegetation Water 2020, 12, 2072 15 of 22 distribution at Mike3 during our study created a “vegetated channel” (Figure9B) where an enhanced flow passed the ADV Ocean instrument attached to the tripod before 6 September 2015. Alternatively, the turbulence and vortical structures generated near this vegetated channel can keep organic matter and fine sediments in suspension, facilitating their transport downstream from Mike1 to Mike3, i.e., [13]. After early September, the water velocity soon dropped to nearly 0 cm/s while a sharp increase in turbidity was also recorded at Mike3 (Figure6D,F). Yet, there was no increase in wave or wind values that could potentially trigger sediment resuspension. Turbidity currents can potentially cause resuspension in some areas as sediment-laden water moves down a slope [57]; however, no studies have reported turbidity currents near the study area so it is unlikely that it is the cause of this observed increase in turbidity. Water levels in the Calumet, Mike1, and Mike 3 stations are under the combined seasonal control of river and tides (Figures7 and8). For instance, our data show that a low-frequency seasonal river flood dominated over the high-frequency tides in April 2015. The coefficients of determination decrease from 0.91 to 0.84 can be explained by the presence of a dense vegetation gradient between Mike1 and Mike3. The increase in vegetation density, in conjunction with aboveground biomass, reduced the water flows leading to time lags in the water level phases between Mike1 and Mike3. Semidiurnal and diurnal tidal signals were not detectable in April 2015, but were visible in September–October 2015, indicating tidal decoupling between these stations. Additionally, during September–October 2015, the wave heights dissipated to nearly zero likely due to the presence of dense vegetation in Mike1 and Mike3, yet semidiurnal and diurnal tides penetrated through the entire Mike Island and even moved upstream 20 km reaching the Calumet station (Figures1 and8).

4.2. Water–Sediment Interface The overlying and porewater nutrient concentration showed significant interactions among the month, location, vegetation presence, and compartment (i.e., overlying water and porewater) factors. 3 The relationship between PO4 − and TIN concentrations in the overlying and sediment porewater shows a distinct nutrient gradient influencing vegetation productivity and biomass density in both 3 locations (Figures 10 and 11). In May 2015, both Mike1 and Mike3 had similar PO4 − (0.9–1.7 µM) and TIN (28–40 µM) concentrations in the overlying water. This pattern was apparent in both sampling points (replicates) within each location (Mike1, Mike3; Figure 10), indicating that the water mass over the sediment surface was the same in May at both locations and towards the end of the peak river discharge. In contrast, in October 2015, both nutrients’ concentrations in the overlying water were 3 up to 3 higher at the upstream (Mike1: TIN: 47.2 µM; PO4 −: 2.6 µM) site than the downstream × 3 (Mike3: TIN: 3.8 µM; PO4 −: 0.8 µM; Figure 10). Higher nutrient concentrations were expected at Mike1 given the direct influence of river discharge; during peak river discharge, nutrient concentrations are approximately the same [58]. Similarly, recent work shows higher NO3− concentrations in the overlying water at Mike Island during warmer months [59]. This riverine influence is underscored by the overlying water PO 3 concentration at Mike1 in October (i.e., 2.65 µM; Figure 10) which was 2 4 − × the concentration measured in May 2015, while the concentrations at Mike3 were similar during both 3 seasons. The PO4 − porewater concentrations did not vary between seasons, probably as a result of the interaction between plant uptake during the growing season and high reducing conditions, where 3 there is high potential for the microbially mediated release of iron (Fe)-bound PO4 − from sediments that are characterized by a low organic matter to Fe ratio (OM:Fe) [58]. 3 In contrast to PO4 −, the TIN porewater concentrations were high with most of the TIN comprised + of NH4 . This form of inorganic nitrogen is dominant in the sediment porewaters, probably as result of high remineralization rates occurring at the end of the growing season in the WLD, when plants begin 3 to die and belowground living biomass is high [60,61]. This major seasonal variation in TIN and PO4 − concentrations between locations and the porewater versus the overlying water indicates significant differences in nutrient transport and use (e.g., plant uptake) within the system. For instance, the lack of vegetation early in the year (spring) maintains a homogenous flow moving downstream without a large Water 2020, 12, 2072 16 of 22 reduction in water velocity. However, during October, at the end of the vegetation growing season, the river stage is lower and vegetation biomass is high. Water flow from the primary channel upstream still enters the island via the secondary channel, as indicated by the higher nutrient concentrations in this location (Figures 10 and 11). As the flow moves downstream, however, the vegetation can slow water flow [26,27,33]. Additionally, this reduction in water velocity promotes sediment deposition. It has been reported that about 90% of the inorganic phosphorus entering an estuarine/coastal system is bound to sediment particles [58,62]. As the water flow decreases downstream due to the presence of 3 dense vegetation and flow dispersion, sediment (i.e., and adsorbed PO4 − in sediment) may become 3 deposited, thus decreasing the availability of PO4 − in the overlying water downstream. TIN uptake by plants can help explain the difference in concentrations between Mike1 and Mike3 in October 2015 in our study area. When the water residence time is prolonged due to a reduction in velocity, the vegetation can utilize inorganic nutrients in the overlying water and facilitate the exchange of TIN 3 and PO4 − between the overlying water and the sediment by diffusion. During May, TIN concentrations were significantly lower in the porewater than during October 3 (p < 0.001, Figure 11). However, no significant differences were observed between PO4 − concentrations across location or month. As mentioned above, the significantly higher TIN concentrations in October 2015 can be attributed to higher remineralization and microbial activity at the end of the growing season. In addition, this higher concentration in October could be due to the net or flux of nitrate into the sediments. Because there was a significantly higher NO2− + NO3− (N + N) concentration in the overlying water than the porewater (Figures 10 and 11) it is probable that a net flux occurred from the overlying water into the sediments [59]. Additional studies assessing inorganic and organic nutrient fluxes between the sediment and overlying water using cores and flumes are needed in conjunction with water flow measurement in Mike Island. Overall, the material collected in the sediment traps show that higher bulk density, lower organic matter, higher nutrient (TP, TN) and carbon (TC) content, and coarser grain size were typical characteristics of the sediment collected at Mike1 (Table3). High bulk density and low organic matter content suggest that there is more mineral sediment deposition upstream than downstream. In addition, more nutrients and carbon were trapped at Mike1, with the exception of TN in spring. This difference between upstream and downstream locations is caused by the influx of water flow from the secondary channel directly impacting the Mike1 site. Higher sediment TN content during spring at Mike3 could be explained by the contribution of organic matter due to overbank flooding. Coarser sediment was also trapped upstream, which is expected since coarser particles settle out more quickly than finer particles. Although our sediment trap prototype was efficient in capturing sediment to determine its grain size composition, there is still the need to increase the sampling distribution to determine a water column-integrated sediment loading rate. The two depths used here were selected to evaluate the grain size differences slightly above the sediment surface (S-S) and 30 cm (S-30) above the sediment surface (Figure2C). These positions were selected at the outset of the study given the lack of information about the potential minimum and maximum water column depths at each station under different river discharge stages. Now that this range and duration was determined at least for two seasons, it is recommended to increase the number of trap positions throughout the water column to characterize the differences in the sediment composition and accumulation resulting from non-linear flow velocity and suspended inorganic profiles with more detail.

4.3. Vegetation Vegetation significantly influences current speed and wave attenuation [26–28,31]. There is evidence that during peak biomass in August 2015, wave height was greatly diminished, likely due to vegetation presence as shown by the small wave heights recorded at Mike1 and Mike3 compared to the April data, when both the vegetation biomass and density were low (Figures4 and6). Additionally, the ADV velocity data showed large decreases in velocity at Mike3. Thus, vegetation Water 2020, 12, 2072 17 of 22 density had a strong influence on the current velocity in this area, which has been similarly observed in other studies [26–28,31]. As mentioned in Section 4.1, vegetation can be effective in dissipating waves, but not tides. We acknowledge that our instrument readings might also reflect vegetation entangled in the tripod given the sporadic noisy data, or that new plant growth interfered with the acoustic and optical signals. This interference could have caused the large decrease in velocity that coincided with an increase in turbidity (Figure6). Indeed, dense mats of aquatic vegetation (e.g., Eichornia crassipes) were found and removed during retrieval of the instruments in October 2015, thus there is a potential effect of floating vegetation on data collection. Additionally, biofouling was found on some sensors deployed in summer/fall 2015 that impacted our results, such as the OBS readings (e.g., Figure6F). These field limitations highlight the challenging nature in the analysis of time-series optical and acoustic observations in dense-vegetation coastal areas like the Wax Lake Delta; these limitations are also underscored by the low number of studies in this type of system at the temporal scales we performed our study.

4.4. A Conceptual Model We summarize our results using a conceptual model to illustrate the relative impact of river discharge and wind patterns on hydrodynamic drivers (e.g., waves, current velocity, tides) interacting with vegetation presence on Mike Island in 2015 (Figure 11A). The three scenarios describe the interaction between the observed climatic conditions and field measurements to highlight the relative role and timing of events regulating sediment transport and water velocity across the island. In late April 2015, a storm event enhanced wind speeds, causing up to 0.2 m wave heights at Mike3 that increased the sediment resuspension and water turbidity (Figure 13A). This storm was associated with a tornado, as shown by our wind direction/rotation field measurements and the highest water level (Figure3). The second scenario was the velocity reduction occurring on 6 September 2015 when the largest discrepancy in the velocity values between Mike1 and Mike3 were recorded (Figure 13B). Although tides were recorded at both Mike1 and Mike3 during this event, wave heights were small at both locations. This reduction is attributed to the widespread dense vegetation across the island during this time, which has also been described in other field and laboratory studies (e.g., [30,32,63,64]). The third scenario consisted of the passage of a cold front on 1 October (Figure 13C). The average water level at Mike1 dropped by 0.8 m and the air temperature (8 ◦C) was lower than in summer (30 ◦C). A strong shift in the wind direction from southerly to northwesterly winds was also recorded. Cold fronts are common meteorological events in coastal Louisiana, and it is likely that more than one passed throughout our study area during the instrument deployment in 2015 [36,40,65]. Together, these three scenarios occurring within one year underscore the dynamic interaction between hydrological and climatic events controlling sediment deposition and plant productivity in this river-dominated deltaic system in a subtropical climate. Finally, this conceptual model invites several follow-up questions to be validated in time and space. In the future, additional study locations, in either other permanent stations (i.e., Mike Island platform network) or other locations across the delta, should be able to capture further granularity. For example, selecting a more extensive elevation gradient across the width of Mike Island might show stronger differences between the vegetations’ extension/biomass and sediment transport patterns. Thus, our results represent a baseline to advance further studies in Mike Island and other deltaic islands, including the need to expand monitoring stations to other deltaic islands and perform similar studies in other river-dominated delta systems. Water 2020, 12, 2072 18 of 22 Water 2020, 12, x FOR PEER REVIEW 18 of 22

FigureFigure 13.13. Conceptual diagram describing the climatic andand hydrologicalhydrological eventsevents controllingcontrolling sedimentsediment depositiondeposition andand transport transport in in Mike Mike Island Island (Wax (Wax Lake Lake Delta, Delta, Louisiana) Louisiana) in 2015: in 2015: (A) storm (A) storm event, event, (B) water (B) velocitywater velocity reduction reduction due to due vegetation to vegetation interference interference and (C )and cold (C front.) cold front. 5. Conclusions 5. Conclusions Our results show how several factors, including seasonal patterns in wind, wave, river, tide, Our results show how several factors, including seasonal patterns in wind, wave, river, tide, and and vegetation presence (density, productivity and biomass) interact on Mike Island to regulate vegetation presence (density, productivity and biomass) interact on Mike Island to regulate sediment sediment transport. These interactions, depending on the Atchafalaya River stage, can influence transport. These interactions, depending on the Atchafalaya River stage, can influence accretion rates accretion rates and relative elevation as determined by other studies describing lobe formation and and relative elevation as determined by other studies describing lobe formation and expansion in the expansion in the WLD region (e.g., [3,39,61]). Indeed, we documented the relative importance of WLD region (e.g., [3,39,61]). Indeed, we documented the relative importance of pulsing storm events pulsing storm events as a critical natural disturbance that trigger biological and geophysical changes as a critical natural disturbance that trigger biological and geophysical changes in short periods in short periods [65,66]. During our spring deployment, Mike Island was characterized by limited [65,66]. During our spring deployment, Mike Island was characterized by limited vegetation vegetation coverage and biomass and high river discharge; river and wind-driven waves were coverage and biomass and high river discharge; river and wind-driven waves were dominant factors dominant factors controlling sediment transport from the upstream (Mike1) station to the downstream controlling sediment transport from the upstream (Mike1) station to the downstream (Mike3). (Mike3). Additionally, the tidal impact on river discharge upstream at the Calumet gauge station Additionally, the tidal impact on river discharge upstream at the Calumet gauge station was minimal was minimal in April 2015 and the tides on Mike Island shifted between diurnal and semidiurnal in April 2015 and the tides on Mike Island shifted between diurnal and semidiurnal patterns. patterns. Regardless of the river stages and vegetation biomass, the FFT results show the combined Regardless of the river stages and vegetation biomass, the FFT results show the combined presence presence of distinct semidiurnal and diurnal tides in Mike1 and Mike3 in April and September–October of distinct semidiurnal and diurnal tides in Mike1 and Mike3 in April and September–October 2015. 2015. In summer, the vegetation growth and expansion created a “vegetated channel” that constricted In summer, the vegetation growth and expansion created a “vegetated channel” that constricted water flow to the middle of the island (Figures6D and 13;[ 30]). In addition, when river discharge water flow to the middle of the island (Figures 6D and 13; [30]). In addition, when river discharge was low and vegetation biomass high, the waves were very small, yet tidal forcing was detected. was low and vegetation biomass high, the waves were very small, yet tidal forcing was detected. Although tides can still penetrate through the dense and extensive vegetation patches, even reaching Although tides can still penetrate through the dense and extensive vegetation patches, even reaching the Calumet station upstream, this vegetation slows the current velocity and attenuates waves, the Calumet station upstream, this vegetation slows the current velocity and attenuates waves, prolonging water residence time throughout Mike Island (Figure 11). This increase in water residence prolonging water residence time throughout Mike Island (Figure 11). This increase in water residence time induced significant fine sediment deposition as registered in our sediment traps. This process time induced significant fine sediment deposition as registered in our sediment traps. This process has also been reported in other coastal and river-dominated habitats [21,26–33]. The presence of has also been reported in other coastal and river-dominated habitats [21,26–33]. The presence of vegetation, especially aboveground biomass, enhanced sediment trapping and served as a critical vegetation, especially aboveground biomass, enhanced sediment trapping and served as a critical functional attribute regulating net accretion and land formation in the WLD. Our study shows that the functional attribute regulating net accretion and land formation in the WLD. Our study shows that magnitude, extension, and spatiotemporal variation of hydrological and climate variables controlling the magnitude, extension, and spatiotemporal variation of hydrological and climate variables sediment deposition and vegetation trapping efficiency needs to be quantified at different temporal controlling sediment deposition and vegetation trapping efficiency needs to be quantified at different temporal (hours, days) and spatial scales (m, ha). Hence, our study, by design, focused on

Water 2020, 12, 2072 19 of 22

(hours, days) and spatial scales (m, ha). Hence, our study, by design, focused on measurements of critical environmental variables at this local scale that are lacking not only in the WLD, but also in other deltaic systems. This hierarchical approach can help advance engineering designs and model parametrization to successfully implement sediment river diversions to restore coastal wetlands in coastal Louisiana, as proposed in the 2012 and 2017 Louisiana’s Comprehensive Master Plan for a Sustainable Coast [67].

Supplementary Materials: The following materials are available online at http://www.mdpi.com/2073-4441/12/ 7/2072/s1, Table S1: ANOVA source table for the total inorganic nitrogen (TIN) concentrations; the following notation is used to indicate levels of significance * <0.05, ** <0.01, *** <0.001, Table S2: ANOVA source table 3 for the PO4 − concentrations; the following notation is used to indicate levels of significance * <0.05, ** <0.01, 3 *** <0.001, Table S3: ANOVA source table for PO4 − concentrations at Mike1 during May 2015; the following notation is used to indicate levels of significance * <0.05, ** <0.01, *** <0.001, Table S4: ANOVA source table for 3 PO4 − concentrations at Mike3 during May 2015; the following notation is used to indicate levels of significance * <0.05, ** <0.01, *** <0.001. Author Contributions: Conceptualization, C.E., K.X., and V.H.R.-M.; methodology, C.E., K.X., and V.H.R.-M.; software, C.E., K.X., and V.H.R.-M.; validation, C.E., K.X., and V.H.R.-M.; formal analysis, C.E., K.X., and V.H.R.-M.; investigation, C.E., K.X., and V.H.R.-M.; resources, K.X., and V.H.R.-M.; data curation, C.E., K.X., and V.H.R.-M.; writing—original draft preparation, C.E., K.X., and V.H.R.-M.; writing—review and editing, C.E., K.X., and V.H.R.-M.; visualization, C.E., K.X., and V.H.R.-M.; supervision, K.X., and V.H.R.-M.; project administration, C.E., K.X., and V.H.R.-M.; funding acquisition, K.X., V.H.R.-M. All authors have read and agreed to the published version of the manuscript. Funding: This research was funded by the Coastal Protection and Restoration Authority (CPRA) through the Coastal Science Assistantship Program (CSAP). Additional partial support was provided by a pFund through the Board of Regents and the National Science Foundation-Coupled Natural Human systems grant (No. DBCS 1212112). V.H.R.-M also received partial support from the Department of the Interior South-Central Climate Adaptation Science Center (Cooperative Agreement #G12AC00002). Acknowledgments: We are particularly grateful for the advice, guidance and help from Robert Twilley, Edward Castañeda-Moya and Gregg Snedden throughout the entire study, including the use of the established platforms on Mike Island. We are also thankful for the laboratory and field support from our colleagues in the Wetland Biogeochemistry Analytical Services, Sediment Dynamics Laboratory, and Earth Scan Laboratory at LSU. We thank four anonymous reviewers for constructive comments on earlier versions of this manuscript. We also extend our sincere appreciation to many colleagues that volunteered in the field and help in the data analysis. Conflicts of Interest: The authors declare no conflict of interest.

References

1. Blum, M.D.; Roberts, H.H. The Mississippi Delta region: Past, present, and future. Annu. Rev. Earth Planet Sci. 2012, 40, 655–683. [CrossRef] 2. Salinas, L.M.; Delaune, R.D.; Patrick, W.H. Changes occurring along a rapidly submerging coastal area—Louisiana, USA. J. Coast. Res. 1986, 2, 269–284. 3. Paola, C.; Twilley, R.R.; Edmonds, D.A.; Kim, W.; Mohrig, D.; Parker, G.; Viparelli, E.; Voller, V.R. Natural Processes in Delta Restoration: Application to the Mississippi Delta. Annu. Rev. Mar. Sci. 2011, 3, 67–91. [CrossRef] 4. Rosen, T.; Xu, Y.J. Recent decadal growth of the Atchafalaya River Delta complex: Effects of variable riverine sediment input and vegetation succession. Geomorphology 2013, 194, 108–120. [CrossRef] 5. Rivera-Monroy, V.H.; Elliton, C.E.; Narra, S.; Meselhe, E.; Zhao, X.; White, E.; Sasser, C.E.; Visser, J.M.; Meng, X.; Wang, H.; et al. Wetland Biomass and Productivity in Coastal Louisiana: Base Line Data (1976–2015) and Knowledge Gaps for the Development of Spatially Explicit Models for Ecosystem Restoration and Rehabilitation Initiatives. Water 2019, 11, 2054. [CrossRef] 6. Schleiss, A.J.; Franca, M.J.; Juez, C.; De Cesare, G. Sedimentation. J. Hydraul. Res. 2016, 54, 595–614. [CrossRef] 7. Couvillion, B.R.; Beck, H.; Schoolmaster, D.; Fischer, M. Land Area Change in coastal Louisiana 1932 to 2016; U.S. Geological Survey Reston: Reston, VA, USA, 2017; p. 16. 8. Couvillion, B.R.; Fischer, M.R.; Beck, H.J.; Sleavin, W.J. Spatial configuration trends in coastal Louisiana from 1985 to 2010. Wetlands 2016, 36, 347–359. [CrossRef] Water 2020, 12, 2072 20 of 22

9. Allison, M.A.; Meselhe, E.A. The use of large water and sediment diversions in the lower Mississippi River (Louisiana) for coastal restoration. J. Hydrol. 2010, 387, 346–360. [CrossRef] 10. Nittrouer, J.A.; Best, J.L.; Brantley, C.; Cash, R.W.; Czapiga, M.; Kumar, P.; Parker, G. Mitigating land loss in coastal Louisiana by controlled diversion of Mississippi River sand. Nat. Geosci. 2012, 5, 534–537. [CrossRef] 11. Xu, K.; Bentley, S.J., Sr.; Robichaux, P.; Sha, X.; Yang, H. Implications of texture and erodibility for sediment retention in receiving basins of coastal Louisiana diversions. Water 2016, 8, 26. [CrossRef] 12. Xu, K.H.; Bentley, S.J.; Day, J.W.; Freeman, A.M. A review of sediment diversion in the Mississippi River Deltaic Plain. Estuar. Coast. Shelf Sci. 2019, 225, 106241. [CrossRef] 13. Juez, C.; Schärer, C.; Jenny, G.; Schleiss, A.J.; Franca, M.J. Floodplain land cover and flow hydrodynamic control of overbank sedimentation in compound channel flows. Water Resour. Res. 2019, 55, 9072–9091. [CrossRef] 14. Reddy, K.R.; Kadlec, R.H.; Flaig, E.; Gale, P.M. Phosphorus Retention in Streams and Wetlands: A Review. Crit. Rev. Environ. Sci. Technol. 1999, 29, 83–146. [CrossRef] 15. Reddy, K.R.; Patrick, W.H. Nitrogen transformations and loss in flooded soils and sediments. Crit. Rev. Environ. Control 1984, 13, 273–309. [CrossRef] 16. Nichols, D.S. Capacity of natural wetlands to remove nutrients from wastewater. J. Water Pollut. Control Fed. 1983, 55, 495–505. Available online: https://www.jstor.org/stable/25041910 (accessed on 22 June 2016). 17. Day, J.W.; Ko, J.Y.; Rybczyk, J.; Sabins, D.; Bean, R.; Berthelot, G.; Brantley, C.; Cardoch, L.; Conner, W.; Day, J.N.; et al. The use of wetlands in the Mississippi Delta for wastewater assimilation: A review. Ocean Coast. Manag. 2004, 47, 671–691. [CrossRef] 18. Fisher, J.; Acreman, M.C. Wetland nutrient removal: A review of the evidence. Hydrol. Earth Syst. Sci. 2004, 8, 673–685. [CrossRef] 19. Hunter, R.; Lane, R.; Day, J.; Lindsey, J.; Day, J.; Hunter, M. Nutrient removal and loading rate analysis of Louisiana forested wetlands assimilating treated municipal effluent. Environ. Manag. 2009, 44, 865–873. [CrossRef][PubMed] 20. Twilley, R.R.; Rivera-Monroy, V.H. Sediment and nutrient trade-offs in restoring Mississippi River Delta: Restoration versus eutrophication. J. Contemp. Water Res. Educ. 2009, 141, 39–44. [CrossRef] 21. Henry, K.M.; Twilley, R.R. Nutrient biogeochemistry during the early stages of delta development in the Mississippi River Deltaic Plain. Ecosystems 2014, 17, 327–343. [CrossRef] 22. Rabalais, N.; Turner, R.E.; Wiseman, W.J. Gulf of Mexico , A.K.A. “The .”. Annu. Rev. Ecol. Syst. 2002, 33, 235–263. [CrossRef] 23. O’Connor, M.T.; Moffett, K.B. Groundwater dynamics and surface water- groundwater interactions in a prograding delta island, Louisiana, USA. J. Hydrol. 2015, 524, 15–29. [CrossRef] 24. Twilley, R.R.; Casteñeda-Moya, E.; Bentley, S.J., Sr.; Chen, Q.; Edmonds, D.A.; Hagan, S.C.; Lam, N.S.; Willson, C.S.; Xu, K.; Braud, D.; et al. Seasonal and spatial variation of surface water nitrate concentrations and water flow in delta islands of Wax Lake Delta, Louisiana. In Proceedings of the State of the Coast Meeting 2016, New Orleans, LA, USA, 2 June 2016. 25. Peyronnin, N.S.; Caffey,R.H.; Cowan, J.H.; Justic, D.; Kolker, A.S.; Laska, S.B.; McCorquodale, A.; Melancon, E.; Nyman, J.A.; Twilley,R.R.; et al. Optimizing sediment diversion operations: Working group recommendations for integrating complex ecological and social landscape interactions. Water 2017, 9, 368. [CrossRef] 26. Leonard, L.A.; Luther, M.E. Flow hydrodynamics in tidal marsh canopies. Limnol. Oceanog. 1995, 40, 1474–1484. [CrossRef] 27. Nepf, H.M.; Sullivan, J.A.; Zavitoski, R.A. A model for diffusion within emergent vegetation. Limnol. Oceanog. 1997, 42, 1735–1745. [CrossRef] 28. Nepf, H.M. Drag, turbulence, and diffusion in flow through emergent vegetation. Water Resour. Res. 1999, 35, 479–489. [CrossRef] 29. Nepf, H.M.; Vivoni, E.R. Flow structure in depth-limited, vegetated flow. J. Geophys.Res. 2000, 105, 28547–28557. [CrossRef] 30. Madsen, J.D.; Chambers, P.A.; James, W.F.; Koch, E.W.; Westlake, D.F. The interaction between water movement, sediment dynamics and submersed macrophytes. Hydrobiologia 2001, 444, 71–84. [CrossRef] 31. Cotton, J.A.; Wharton, G.; Bass, J.A.B.; Heppell, C.M.; Wotton, R.S. The effects of seasonal changes to in-stream vegetation cover on patterns of flow and accumulation of sediment. Geomorphology 2006, 77, 320–334. [CrossRef] Water 2020, 12, 2072 21 of 22

32. Augustin, L.N.; Irish, J.L.; Lynett, P. Laboratory and numerical studies of wave damping by emergent and near-emergent wetland vegetation. Coast. Eng. J. 2009, 56, 332–340. [CrossRef] 33. Corenblit, D.; Steiger, J.; Gurnell, A.M.; Tabacchi, E.; Roques, L. Control of sediment dynamics by vegetation as a key function driving biogeomorphic succession within fluvial corridors. Earth Surf. Proc. Land. 2009, 34, 1790–1810. [CrossRef] 34. Smith, B.C. The Effects of Vegetation on Island Geomorphology in the Wax Lake Delta, Louisiana. Master’s Thesis, The University of Texas at Austin, Austin, TX, USA, May 2014. 35. Mossa, J.; Roberts, H.H. Synergism of riverine and winter storm-related sediment transport processes in Louisiana’s coastal wetlands. Trans. Gulf Coast Assoc. Geol. Soc. 1990, 40, 635–642. 36. Roberts, H.H.; DeLaune, R.D.; White, J.R.; Li, C.; Sasser, C.E.; Braud, D.; Weeks, E.; Khalil, S. Floods and cold front passages: Impacts on coastal marshes in a river diversion setting (Wax Lake Delta Area, Louisiana). J. Coast. Res. 2015, 31, 1057–1068. [CrossRef] 37. Cahoon, D.R. A review of major storm impacts on coastal wetland elevations. Estuar. Coasts 2006, 29, 889–898. [CrossRef] 38. Turner, R.E.; Baustian, J.J.; Swenson, E.M.; Spicer, J.S. Wetland sedimentation from hurricanes Katrina and Rita. Science 2006, 314, 449–452. [CrossRef] 39. Hiatt, M.; Passalacqua, P. Hydrological connectivity in river deltas: The first-order importance of channel-island exchange. Water Resour. Res. 2015, 51, 2264–2282. [CrossRef] 40. Bevington, A.E.; Twilley, R.R.; Sasser, C.R.; Holm, G.O., Jr. Contribution of river floods, hurricanes, and cold fronts to elevation change in a prograding deltaic floodplain in the northern Gulf of Mexico, USA. Estuar. Coast. Shelf Sci. 2016, 191, 188–200. [CrossRef] 41. Hiatt, M.; Snedden, G.; Day, J.W.; Robli, R.V.; Nyman, J.A.; Lane, R.; Sharp, L.A. Drivers and impacts of water level fluctuations in the Mississippi River delta: Implications for delta restoration. Estuar. Coast. Shelf Sci. 2019, 224, 117–137. [CrossRef] 42. Roberts, H.H.; Coleman, J.M.; Bentley, S.J., Sr.; Walker, N.D. An embryonic major delta lobe: A new generation of delta studies in the Atchafalaya-Wax Lake Delta system. Trans. Gulf Coast Assoc. Geol. Soc. 2003, 53, 690–703. 43. Day, J.W., Jr.; Boesch, D.F.; Clairain, E.J.; Kemp, G.P.; Laska, S.B.; Mitsch, W.J.; Orth, K.; Mashriqui, H.; Reed, D.J.; Shabman, L.; et al. Restoration of the Mississippi Delta: Lessons from Hurricanes Katrina and Rita. Science 2007, 315, 1679–1684. [CrossRef] 44. Wellner, R.; Beaubouef, R.; Van Wagoner, J.; Harry, R.; Sun, T. Jet-plume depositional bodies—The primary building blocks of Wax Lake Delta. Trans. Gulf Coast Assoc. Geol. Soc. 2005, 55, 867–909. 45. Jones, C.E. Radar remote sensing of the Louisiana wetlands to study delta formation and marsh status. Natl. Wetl. Newsl. 2016, 38, 12–16. Available online: https://www.eli.org/sites/default/files/nwn/issue/38.1_ Jones.pdf (accessed on 5 January 2020). 46. Allison, M.A.; Demas, C.R.; Ebersole, B.A.; Kleiss, B.A.; Little, C.D.; Meselhe, E.A.; Powell, N.J.; Pratt, T.C.; Vosburg, B.M. A water and sediment budget for the lower Mississippi Atchafalaya River in flood years 2008–2010: Implications for sediment discharge to the and coastal restoration in Louisiana. J. Hydrol. 2012, 432, 84–97. [CrossRef] 47. Kolker, A.S.; Li, C.; Walker, N.D.; Pilley, C.; Ameen, A.D.; Boxer, G.; Ramatchandirane, C.; Ullah, M.; Williams, K.A. The impacts of the great Mississippi/Atchafalaya River flood on the oceanography of the Atchafalaya Shelf. Cont. Shelf Res. 2014, 86, 17–33. [CrossRef] 48. Bevington, A.E.; Twilley, R.R. Island edge morphodynamics along a chronosequence in a prograding deltaic floodplain wetland. J. Coast. Res. 2018, 34, 806–817. [CrossRef] 49. Twilley, R.R.; Day, J.W.; Bevington, A.E.; Castañeda-Moya, E.; Christensen, A.; Holm, G.; Heffner, L.R.; Lane, R.; McCall, A.; Aarons, A.; et al. Ecogeomorphology of coastal deltaic floodplains and in an active delta: Insights from the Atchafalaya Coastal Basin. Estuar. Coast. Shelf Sci. 2019, 227, 106341. [CrossRef] 50. Heiri, O.; Lotter, A.F.; Lemcke, G. Loss on ignition as a method for estimating organic and carbonate content in sediments: Reproducibility and comparability of results. J. Paleolimnol. 2001, 25, 101–110. [CrossRef] 51. Aspila, K.I.; Agemian, H.; Chau, A.S.Y. Semiautomated method for determination of inorganic, organic, and total phosphate in sediments. Analyst 1976, 101, 187–197. [CrossRef] Water 2020, 12, 2072 22 of 22

52. Karimpour, A.; Chen, Q. Wind wave analysis in depth limited water using OCEANLYZ, a MATLAB toolbox. Comput. Geosci. 2017, 106, 181–189. [CrossRef] 53. Tolotti, M.; Thies, H.; Nickus, U.; Psenner, R. Temperature modulated effects of nutrients on changes in a mountain lake. Hydrobiologia 2012, 221, 61–75. [CrossRef] 54. Visser, J.M.; Sasser, C.E.; Chabreck, R.H.; Linscombe, R.G. Marsh vegetation types of the Mississippi River Deltaic Plain. Estuaries 1998, 21, 818–828. [CrossRef] 55. Carle, M.V.; Sasser, C.E. Productivity and Resilience: Long-Term Trends and Storm-Driven Fluctuations in the Plant Community of the Accreting Wax Lake Delta. Estuar. Coasts 2016, 39, 406–422. [CrossRef] 56. Landsat Missions, United States Geological Survey (USGS). Available online: https://www.usgs.gov/land- resources/nli/landsat/landsat-data-access?qt-science_support_page_related_con=0#qt-science_support_ page_related_con (accessed on 5 January 2020). 57. Zordan, J.; Juez, C.; Schleiss, A.J.; Franca, M.J. Entrainment, transport and deposition of sediment by saline gravity currents. Adv. Water Resour. 2018, 115, 17–31. [CrossRef] 58. Upreti, K.; Maiti, K.; Rivera-Monroy, V.H. Microbial mediated sedimentary phosphorus mobilization in emerging and eroding wetlands of coastal Louisiana. Sci. Total Environ. 2019, 651, 122–133. [CrossRef] [PubMed] 59. Li, S.; Christensen, A.; Twilley, R.R. Benthic fluxes of dissolved oxygen and nutrients across hydrogeomorphic zones in a coastal deltaic floodplain within the Mississippi River delta plain. Biogeochemistry 2020, 149, 115–140. [CrossRef] 60. Rivery-Monroy, V.H.; Lenaker, P.; Twilley, R.R.; Delaune, R.D.; Lindau, C.W.; Nuttle, W.; Habib, E.; Fulweiler, R.W.; Casteñeda-Moya, E. Denitrification in coastal Louisiana: A spatial assessment and research needs. J. Sea Res. 2010, 63, 157–172. [CrossRef] 61. Carle, M.V.; Sasser, C.E.; Roberts, H.H. Accretion and vegetation community change in the Wax Lake Delta following the historic 2011 Mississippi River flood. J. Coast. Res. 2015, 31, 569–587. [CrossRef] 62. Froelich, P.N. Kinetic control of dissolved phosphate in natural rivers and estuaries—A primer on the phosphate buffer mechanism. Limnol. Oceanog. 1988, 33, 649–668. [CrossRef] 63. Anderson, M.E.; Smith, J.M.; McKay,S.K. Wave dissipation by vegetation. In Coastal and Hydraulics Engineering Technical Note ERDC/CHL CHETN-I-82; U.S. Army Engineer Research and Development Center: Vicksburg, MS, USA, 2011; pp. 1–22. Available online: http://chl.erdc.usace.army.mil.chetn (accessed on 5 January 2020). 64. Temmerman, S.; Bouma, T.J.; Govers, G.; Wang, Z.B.; De Vries, M.B.; Herman, P.M.J. Impact of vegetation on flow routing and sedimentation patterns: Three- dimensional modeling for a tidal marsh. J. Geophys. Res. Earth Surf. 2005, 110.[CrossRef] 65. Li, C.; Roberts, H.; Stone, G.W.; Weeks, E.; Luo, Y. Wind surge and saltwater intrusion in Atchafalaya Bay during onshore winds prior to cold front passage. Hydrobiologia 2011, 658, 27–39. [CrossRef] 66. Huang, W.; Li, C. Cold front driven flows through multiple inlets of Lake Pontchartrain . J. Geophys. Res. 2017, 122, 8627–8645. [CrossRef] 67. Coastal Protection and Restoration Authority. Available online: http://coastal.la.gov/our-plan/2017-coastal- master-plan/ (accessed on 5 January 2020).

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).