Seasonal variability of cohesive sediment aggregation in the ... - LEGOS

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Geo-Mar Lett (2012) 32:103–121 DOI 10.1007/s00367-011-0273-8

ORIGINAL

Seasonal variability of cohesive sediment aggregation in the Bach Dang–Cam Estuary, Haiphong (Vietnam) Jean-Pierre Lefebvre & Sylvain Ouillon & Vu Duy Vinh & Robert Arfi & Jean-Yves Panché & Xavier Mari & Chu Van Thuoc & Jean-Pascal Torréton

Received: 6 April 2011 / Accepted: 19 December 2011 / Published online: 15 January 2012 # Springer-Verlag 2012

Abstract In the Bach Dang–Cam Estuary, northern Vietnam, mechanisms governing cohesive sediment aggregation were investigated in situ in 2008–2009. As part of the Red River delta, this estuary exhibits a marked contrast in hydrological conditions between the monsoon and dry seasons. The impact on flocculation processes was assessed by means of surveys of water discharge, suspended particulate matter concentration and floc size distributions (FSDs) conducted during a tidal cycle at three selected sites along the estuary. A method was developed for calculating the relative volume concentration for the modes of various size classes from FSDs provided by the LISST 100X (Sequoia Scientific Inc.). It was found that all FSDs comprised four modes identified as particles/flocculi, fine and coarse microflocs, and macroflocs. Under the influence of the instantaneous turbulent kinetic energy, their proportions varied but without significant modification of their median diameters. In particular, when the turbulence level corresponded to a Kolmogorov microscale of less than

∼235 μm, a major breakup of flocs resulted in the formation of particles/flocculi and fine microflocs. Fluctuations in turbulence level were governed by seasonal variations in freshwater discharge and by the tidal cycle. During the wet season, strong freshwater input induced a high turbulent energy level that tended to generate sediment transfer from the coarser size classes (macroflocs, coarse microflocs) to finer ones (particles/flocculi and fine microflocs), and to promote a transport of sediment seawards. During the dry season, the influence of tides predominated. The turbulent energy level was then only episodically sufficiently high to generate transfer of sediment between floc size classes. At low turbulent energy, modifications in the proportions of floc size classes were due to differential settling. Tidal pumping produced a net upstream transport of sediment. Associated with the settling of sediment trapped in a near-bed layer at low turbulent energy, this causes the silting up of the waterways leading to the harbour of Haiphong.

Responsible guest editor: D. Doxaran J.-P. Lefebvre (*) : S. Ouillon IRD, Université de Toulouse, UPS (OMP), UMR 5566 LEGOS, 14 av. Edouard Belin, 31400 Toulouse, France e-mail: [email protected] V. D. Vinh : C. Van Thuoc Institute of Marine Environment and Resources (IMER), Vietnam Academy of Science and Technology (VAST), 246 Danang Street, Haiphong City, Vietnam R. Arfi IRD, Université Aix-Marseille 2, UMR 6535 LOPB, Centre d’Océanologie de Marseille, Luminy, 13288 Marseille cedex 09, France

J.-Y. Panché IRD, US 191 IMAGO, BP A5, 98848 Nouméa cedex, New Caledonia X. Mari : J.-P. Torréton IRD, Université Montpellier II, UMR 5119 ECOSYM, cc 093, Place Bataillon, 34095 Montpellier, France Present Address: X. Mari Institute of Biotechnology, Environmental Biotechnology Laboratory, 18 Hoang Quoc Viet Street, Cau Giay, Hanoi, Vietnam

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Introduction In Vietnam, the silting up of the Red River delta constitutes a main concern for the authorities due to its particularly negative impact on traffic in the country’s second biggest harbour, Haiphong. During the 1980s, the construction of two dams across the Red River induced a reduction of sediment inputs to the coast, which caused fast and locally intense erosion in the bay of Haiphong. Although the impact of dam constructions has long been investigated worldwide in terms of total suspended particulate matter concentration (SPMC; e.g. Uncles et al. 1988; Vörösmarty et al. 2003; Mantovanelli et al. 2004; Wolanski et al. 2006; Scully and Friedrichs 2007; Winterwerp 2011), less is known about interrelations with floc size distributions (FSDs). Flocculation processes depend on various factors including the electric charge on particles (ζ potential), organic matter content, suspended matter availability, and turbulent shear rate (e.g. Lunven and Gentien 2000; Lunau et al. 2006; Mietta et al. 2009). In estuaries, the high variability in forcing (Verney et al. 2009) and the impact of biological factors make the behaviour of cohesive sediments even more complex and still not well understood (Winterwerp 2011). Organic bindings such as those due to transparent exopolymeric particles (TEPs; e.g. Passow et al. 2001; Wetz et al. 2009; Mari et al. 2011) or dissolved exopolymeric substances (e.g. Bhaskar et al. 2005) can generate macroflocs of various sizes and strengths. The abundance of mineral particles can affect the process of aggregation, except for SPMC in the range 50–250 mg L−1 (cf. Milligan and Hill 1998). Turbulence affects flocculation processes by increasing the collision frequency between aggregates, and also by generating a shear stress at the surface of aggregates that limits their size increase in the same order of magnitude as the smallest turbulent eddies (van Leussen 1997; Jarvis et al. 2005). Sudden disaggregation of flocs beyond a threshold of turbulent intensity was found by Chen et al. (2005) in the Scheldt Estuary. Turbulence level and differential settling of aggregates of various sizes and densities are usually thought to dominate the aggregation and breakup processes (e.g. van Leussen 1994; Winterwerp 2006; Kumar et al. 2010). Lick et al. (1993) proposed a model where the median apparent diameter of aggregates Dv is related to the product of the turbulence-induced shear rate (G) and SPMC through a power law Dv 0 α (G·SPMC)β, where α and β are constants. Manning and Dyer (1999) compared this equation to a more sophisticated formula and proved that it was reasonably accurate. The governing action of tides on flocculation and differential settling has been identified in numerous estuaries of temperate regions. In the Tamar Estuary (UK), for example, the balancing of re-suspension and differential settling at

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high tide slack water is revealed by a close relationship between SPMC and Dv (Uncles et al. 2010). In this estuary, moderate levels of turbulence promote collisions between flocs, and transfers from microflocs to macroflocs enhanced by organic bindings. During spring tide, a highly concentrated benthic suspension layer is generated near the bed that contributes to dampening the turbulence within that layer. The generation of coarser macroflocs results in a marked bimodality in floc size distribution (Manning 2004). In shallow estuaries, an asymmetry between ebb tide and flood tide caused by nonlinear tidal interaction and by astronomic tides can be observed. Since the celerity of the tidal wave increases with increasing water depth, the tide propagates faster at high water than at low water. This causes the shape of the tidal wave to distort as it moves landwards; the rise of the tide becomes faster than its fall and, consequently, the peak current is faster at flood tide than at ebb tide. An increase in tidal level counterbalances the liquid budget, so that the overall balance of the tidal flow is essentially nil. This asymmetry results in a larger sediment transport upstream at flood tide than downstream at ebb tide (Dronkers 1986). This landward transport of sediment caused by ‘tidal pumping’ has been described by Geyer et al. (2001) for the Hudson River Estuary during spring tides. At the site of the present study near Haiphong, the Bach Dang–Cam Estuary is under the influence of a diurnal tidal regime; therefore, this mechanism is likely to be enhanced (Hoitink et al. 2003). In monsoon-dominated rivers, the freshwater discharge exhibits a marked seasonality that affects turbulence, salt stratification in the water column and tidal wave propagation in the estuary. SPMC can be related to turbulence through bed erosion, and to inputs from the catchment basins. The balance between tidal propagation and freshwater discharge determines the amplitude and direction of the current flow, and the level and advection of turbulence in the water column, both impacting on the transport and settling of sediment (Dyer 1995). Water column stratification can constitute an impediment to the vertical advection of turbulence (Geyer 1993; Uncles and Stephens 1993; Jay and Musiak 1994; Peters 1997; Scully and Friedrichs 2003), and can prevent the advection of sediment across the freshwater–saltwater interface, resulting in the trapping of sediment in the upper freshwater or lower saltwater layers. As an example, the Mekong and Red River estuaries experience similar seasonal forcing. Solid discharge by the Mekong River (170×106 metric tons year−1) is similar to that of the Red River (Milliman and Meade 1983), both being characterized by silt-dominated material. In the southern branch of the Mekong delta, the salt wedge is observed near the mouth of the estuary during the wet season. During the dry season, the tidal asymmetry increases and the salt wedge propagates further into the estuary. The sediment load budget indicates

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a tidally averaged flux to the sea of at least 95% during the wet season (Wolanski et al. 1996), and tidal pumping from the coastal area to the estuary during the dry season, coupled with a balancing of settling out at slack tide and reentrainment at higher current speeds. In the Mekong River delta, non-biological flocs are found only in brackish water and remain non-flocculated in the freshwater layer. This results in a seaward transport of particles as ‘wash load’ in the near-surface freshwater layer, and a tidally varying transport of near-bed flocculated sediments. No significant difference in floc size was observed between the wet and dry seasons, and examination of the aggregates confirmed their non-biological origins (Wolanski et al. 1998). In the silt-dominated Fly River Estuary, Papua New Guinea, smaller flocs have been found in the near-surface layer and larger flocs in the near-bed saltwater layer. Nevertheless, the impact of turbulence on floc size was identical in the freshwater and saltwater layers (Wolanski and Gibbs 1995). In the Yangtze River Estuary, flocculation triggered by biological processes has been observed in freshwater and brackish water (Guo and He 2011). The varying hydrodynamics in the estuary generated strong spatiotemporal fluctuations in FSDs, associated with strong variations in macroflocs (defined as D≥D75 in Guo and He 2011, where D is diameter), moderate variations in coarse microflocs (D50 ¼< uðz; t Þ >  < SPMCðz; t Þ > , and the tidally driven component of the tidally averaged flux < qp ðzÞ >¼< u0 ðz; t Þ  SPMC0 ðz; t Þ > in the vicinity of the deepest location of the channel. The discharge and sediment transport per unit area S at the sampling station, q(t) (m3 s−1) and qs(t) (g s−1) respectively, were calculated as: qðtÞ ¼

qs ðtÞ ¼

Suspended particulate matter discharge In each case, the velocity profile corresponding to the location of the turbidity profile was extracted from the crosssectional set. It was assumed that the CTD profile was representative of the same location, i.e. any drift of the ship was considered negligible, and the two scale depths were matched between the surface and the bottom. The velocity profiles achieved with a bin width of 0.5 m were interpolated at the depths of CTD profiling. Sediment flux fs(z,t) (g m−2 s−1) was calculated as: fs ðz; t Þ ¼ uðz; t Þ  SPMCðz; t Þ

ð7Þ

This comprises the advective sediment flux and the tidal pumping of sediment. By expressing both SPMC(z,t) and u (z,t) as the sum of their tidally averaged components and the deviation from the tidally averaged values, the tidally averaged sediment flux becomes: < fs >¼< ð< u > þu0 Þ  ð< SPMC > þSPMC0 Þ >

ð8Þ

where the brackets < > indicate time-averaging over one tidal cycle, and the prime indicates the deviation from the tidally averaged value. Since SPMC0 > ¼ < u >  < SPMC0 > ¼ 0 a n d < u0  < SPMC >>¼< u0 >  < SPMC >¼ 0 , E q . (8) becomes: < fs >¼< u >  < SPMC > þ < u0  SPMC0 >

ð9Þ

ð10Þ

and

ð6Þ

where m is a proportionality factor. At each station and separately for each campaign, second-order linear regression analyses were conducted on datasets for near-surface and near-bottom layers. Pooling these data per station and season revealed coefficients of determination that were sufficiently high to justify using one average conversion factor per station and campaign.

h S X uðz; tÞΔz h z¼0

h S X uðz; tÞSPMCðz; tÞΔz h z¼0

ð11Þ

The total sediment load over the whole cross section of the river, Qs(t), was obtained by assuming that the ratio qs(t)/q(t) did not vary significantly across the whole cross section: Qs ðtÞ qs ðtÞ ¼ QðtÞ qðtÞ

ð12Þ

The sediment load averaged over one tidal cycle was computed according to: hQs i ¼

N 1 X QsðiÞ þ Qsðiþ1Þ 1 ðtiþ1  ti Þ tN  t1 i¼1 2

ð13Þ

Floc size distribution Immediately after each CTD profile, a depth profile of FSD and concentration was conducted using an in situ laser scattering and transmissometry instrument (LISST 100X, Sequoia Scientific Inc.; e.g. Traykovski et al. 1999; Agrawal and Pottsmith 2000; Mikkelsen and Pejrup 2000; Jouon et al. 2008). The LISST of type C enables measurement of volumetric particulate concentration in 32 logarithmically spaced size classes ranging from 2.5 to 500 μm, with attenuation at l0660 nm. In view of the high turbidity in the study area, an optical path reduction module of 90% was employed, and the measurements corrected accordingly. The mean apparent diameter Dv was calculated for every FSD. D v was determined as the apparent diameter corresponding to 50% of the cumulative volume concentration of aggregates. Expressed on a log normal scale for the apparent diameter, each FSD was decomposed into a mixture of 25 irregularly spaced Gaussian curves, using the expectationmaximization (EM) algorithm of Tsui (2009) based on a maximum likelihood criterion. A non-supervised spectrum analysis was applied: the Gaussian curves were sorted by

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increasing modal diameter, and they were then progressively merged as partial components until the mid-height position met the boundary condition for a given component: individual clay/silt particles and flocculi (