# Coastal Plumes Contribution to the Suspended Sediment Transport in the Southwest Atlantic Inner Continental Shelf

Paulo Victor Lisboa<sup>a,b,*</sup>, Elisa H. Fernandes<sup>a</sup>, Aldo Sottolichio<sup>b</sup>, Nicolas Huybrecht<sup>c</sup>, Raylton Bendô<sup>d</sup>.

## Abstract

Global coastal zones are constantly changing due to the actions of various physical forces. Recent studies show that the supply of suspended sediment of continental origin plays an important role in these changes. Once in the coastal region, this sediment significantly influences the sedimentation process on the internal platform. Knowing this, understanding the transport and destination of these sediments is crucial to interpreting the morphodynamic evolution of the seabed and biogeochemical processes in the ocean. The Southwest Atlantic Shelf is the largest continental shelf in the Southern Hemisphere and one of the most important in biological production, because of the great continental contribution exercised by both the Río de la Plata and the Patos Lagoon. Studies in the region show that these effluents are significantly affected by the El Niño-Southern Oscillation (ENSO) effect, which can significantly interfere with the availability of suspended material inserted into the coastal region. Despite the great efforts of several authors to understand these changes and their interactions with the environment, some questions remain unanswered. Thus, this work aims to fill this gap by answering questions related to the contribution of sediment of continental origin and its behaviour on the Southwest Atlantic Inner Shelf. The behaviour of suspended sediment was investigated in two distinct periods using the hydromorphodynamic model TELEMAC-3D: one representing normal years, that is, without the effect of ENSO (2005-2006) and the other experiencing the effect of ENSO (2008-2009). The model was calibrated and validated using field data for both studied periods and for other periods. The results were based on statistical analyses, such as wavelet and empirical orthogonal function (EOF) analyses, in addition to time series. The results show that the Southwest Atlantic Inner Shelf is mainly influenced by the fluvial discharge of the Río de la Plata and the Patos Lagoon, and by

<footnote><sup>a</sup> Laboratócio de Oceanografia Costeira e Estuarina - LOCOSTE, Instituto de Oceanografia - PPGO, Universidade Federal do Rio Grande, Rio Grande, RS, 96203-900, Brazil</footnote>

<footnote><sup>b</sup> Environnements et Paléo-Environnements Océaniques et Continentaux – EPOC Laboratory, University of Bordeaux, 33615 Pessac, France.</footnote>

<footnote><sup>c</sup> Cerema, Direction Technique Eau, Mer et Fleuves, 134 rue de Beauvais - CS 60039-60280 Margny-lès-Compiègne - France.</footnote>

<footnote><sup>d</sup> Escola de Engenharia - PPGE, Universidade Federal do Rio Grande, Rio Grande, RS, 96203-900, Brazil.</footnote>

<footnote>* Corresponding author</footnote>

<footnote>E-mail address: paulovictor_fjv@hotmail.com</footnote>
the local wind. The Río de la Plata being the largest exporter of suspended sediment in the region, with an approximate rate of $1.2 \times 10^8$ tons/year in neutral (normal) years and $3.0 \times 10^8$ tons/year in years under the influence of ENSO. The Patos Lagoon, on the other hand, exports approximately $1.25 \times 10^7$ tons/year in the period without the ENSO effect and $1.35 \times 10^7$ tons/year in the period influenced by ENSO. The results also show that the fluvial discharge interacts with the suspended sediment in seasonal to interannual scales, while the wind contributes to the concentration of suspended sediment on synoptic scales. Still on the local wind regime, the results show that the local wind regime gains importance particularly when the suspended sediment reaches the coastal region.

Keywords: Suspended Sediment Concentration; Southwest Atlantic Inner Continental Shelf; Numerical Modelling; La Plata River; Patos Lagoon; ENSO.

# 1. Introduction

Coastal zones are constantly changing due to the continuous action of winds, waves, currents, tides, and river discharges (Wright and Friedrichs, 2006; Rosa et. al., 2013). Although their study started decades ago (Helder and Ruardij, 1982; Blanton, 1988; Zavialov et. al., 1998), current studies still aim to understand these changes and interactions between different coastal environments, with different physical forcings, particularly in relation to the importance of suspended sediment transport in the sediment supply and the dispersion processes on the adjacent coastal shelf (Rodrigues et. al., 2006; Rosa et. al., 2013; He et. al., 2018).

The global sedimentary budget of the world's rivers indicates that approximately 15-20 billion tons of suspended sediment are annually transported towards the ocean (Milliman and Syvitski, 1992). This riverine suspended sediment is transported seawards mainly by coastal plumes (Wright and Nittrouer, 1995). Among various estuaries and rivers, some have a fluvial contribution sufficiently large to perpetuate a coastal plume during significant periods (on a weekly scale) and over large distances in the continental shelf (Menandro et. al., 2015). According to Simpson and Sharples (2012), the influence of freshwater on the continental shelf depends on several widely complex physical processes, inducing significant buoyancy in the coastal region. Horizontal density gradients tend to generate a circulation in the coastal region analogous to an estuarine setting, with the difference being that this flow can be modified by the action of the Coriolis effect when generating currents parallel to the coastline. According to the authors, the combined action of the tide with the wind is also responsible for the vertical stratification and the displacement of the plume across the coastal region.

Once in the coastal seas, this fluvial contribution can influence sedimentation in the inner shelf due its interaction with coastland shelf dynamics (Mestres et. al., 2007), and can be trapped in deltas, deposited on the adjacent nearshores, distributed in the continental shelf, or delivered to the deep sea over the shelf break or via submarine canyons (Meade, 1996). Only the four world's largest rivers in terms of suspended
sediment load (Amazon, Ganges-Brahmaputra, Yangtze and Yellow before damming) contribute together about 4 billion tons of suspended sediment into the oceans, accounting for 20% of the total global discharge (Milliman and Syvitski, 1992). These rivers are extensively studied in terms of river processes, sediment characteristics, river plume dynamics, sedimentary properties, and shelf sediment transport (Montanher et. al., 2018; Haque et. al., 2016; He et. al., 2018; Ye et. al., 2019).

Understanding the transport and fate of riverine suspended sediment is crucial for interpreting seabed morphodynamic evolution and biogeochemical processes in the ocean. This is because continental waters carry high amounts of organic matter and nutrients, which help in the intensification of biogeochemical processes and support coastal primary productivity and fishing stocks. They can also promote hypoxia in the inner continental shelf due to their proximity to coastal processes such as an intensification of biological activities (Mann and Lazier, 1991; Geyer et. al., 2004).

Several authors have investigated the interaction between continental suspended sediment contributions and their adjacent coastal regions throughout the world. The fate and behaviour of suspended sediments in the continental shelf are controlled by linear and non-linear processes that can be studied through field data analyses, remote sensing, and analytical and numerical models (e.g., Milliman et. al., 1985; Kourafalou et. al., 1996; Foster and Carter, 1997; Rodrigues et. al., 2006; Warrick et. al., 2013; Brodie et. al., 2010). In Asia, Milliman et. al. (1985) studied the contribution of suspended material from the Chengjiang estuary to the Chinese Continental Shelf and its interaction with the Taiwan Current and the Jiangsu Current in the Yellow Sea. The authors showed that sediment transport is directly related to the riverine ebb and flood regime, but the tidal phase (spring or neap) also plays an important role; it was estimated that 40% of the riverine suspended sediment load is deposited inside the estuary. The remaining suspended sediment is deposited directly in the adjacent continental shelf during flood seasons, being resuspended and carried southwards by the coastal current. Still in Asia, Haque et. al. (2016) studied the mechanism of sediment transport in the Ganges - Brahmaputra Delta region using 1D and 2D dynamic models (HEC RAS and Delft 3D) to analyse the volumetric flow distribution in estuarine systems. Their results show that the distribution patterns of the freshwater inlet and water storage are much higher than those of the saltwater inlet and storage flow. This results in a clockwise estuarine residual circulation pattern causing the sediments to return from the sea to the central estuarine system and leading to significant local sedimentation. In the North Atlantic Bay of Biscay, Diaz et. al. (2020) used the realistic 3D hydrodynamic and sediment transport model MARS3D to evaluate the influence of the model's empirical parameterizations on residual sediment fluxes and to estimate the uncertainties in the transfer of mud and sand at the macrotidal Gironde estuary mouth. The results revealed that simulated residual fluxes are not only sensitive to sedimentation and erosion parameters, but also to the spin-up period and the sliding process of sediments. The model also highlighted the strong seasonal variability in sediment fluxes, importing suspended sediment during high river flow and slowly exporting it during a low river flow.
Kineke and Stemberg (1995) studied the Amazon River suspended-sediment exportation and its contribution to the Amazon Shelf to understand the link between physical processes and the fate of Amazon River suspended sediment at different time scales. Results based on field data showed that the vertical structure of benthic fluid mud varies through space and time, with fortnightly variability close to the river mouth. The authors also concluded that the total suspended sediment inventory on the shelf during the high discharge season is approximately equal to the annual suspended sediment discharge from the river (1.2x10⁹ tons/year) and more than 90% of that inventory is fluid mud. Gabioux et. al. (2005) presented a study with a 2D numerical model of the effects of suspended sediments on the Amazon shelf. The results showed that the presence of suspended sediment close to the bottom of the shelf represents an important factor in the dynamics of the continental shelf in the Amazon, reducing the bottom shear stress to the point of generating energy dissipation, which in turn affects the amplitude of the wave tide on the spot.

The Southwest Atlantic Shelf is the largest continental shelf in the Southern Hemisphere and one of the most biologically productive areas in the oceans globally, (Castello and Möller, 1977; Bisbal, 1995; Acha et. al., 2004) because of the high phytoplankton biomass sustained by the Patos Lagoon and the Río de la Plata runoffs and shelf-break upwelling (Ciotti et. al., 1995; Bauer et. al., 2017). Particularly in the Southern Brazilian Continental Shelf, the impact of the la Plata's waters on the shelf has been recognised since the first oceanographic studies in the region (Emilson, 1961; Guerrero et. al., 1997; Depetris and Pasquini, 2007b). Möller et. al. (2008) showed that the intrusion of la Plata water into the continental shelf forms a saline plume, that extends along a coastal strip of 1300 km (Piola et. al., 2005). This plume affects the circulation, stratification, and the distributions of nutrients and biological species over a broad extension of the adjacent continental shelf. The presence of this large amount of freshwater in the coastal zone generates a salinity gradient in the region, strongly modulated by the synoptic action of the wind (Pereira, 1989; Zavialov et. al., 1998; Pimenta et. al., 2005). Piola et. al. (2005), combined hydrographic and wind historical data with numerical simulations to determine the seasonal and interannual variability of the Río de la Plata dynamics, in addition to its relationship with the magnitude of the river discharge and the intensity and direction of the wind. Their results indicated that the seasonal variability of the river plume is controlled by the alongshore component of the wind. Soares et. al. (2007b) then analysed the importance of turbulent mixing for the evolution of the la Plata plume and its spreading on the platform towards the Patos Lagoon using 3D numerical modelling results. It was shown that the la Plata plume tends to expand along the northern margin in the presence of local winds during autumn and is more restricted to the mouth of the river during spring, when winds are weaker and the tidal regime prevails in the region.

The influence of the Patos Lagoon waters in the continental shelf has also been widely studied (Marques et. al., 2009; 2010a; Monteiro et. al., 2011). Marques et. al. (2009) studied the physical forcings controlling the dynamics of the Patos Lagoon coastal plume. They concluded that the coastal plume behaves as a small spatial scale plume, and the dominant mode of variability is associated with a transport towards
the south, controlled by the combination of dominant north quadrant winds and the seasonal variability of river discharge in the region. Marques et. al. (2010a) investigated the importance of straining and advection processes of the water column along the region that is influenced by the Patos Lagoon, in the Southern Brazilian inner shelf. The study was carried out through 3D numerical modelling experiments. Results showed that the freshwater discharge intensity controls the straining and advection, which in turn were the most important mechanisms for the bed evolution in the adjacent coastal region. The different forcings that control the dynamics of the plume of the Patos Lagoon were studied by Monteiro et. al. (2011). The authors analysed the influence of the Earth's rotation, the flow of the river, the tide, and the winds in the dynamics of the plume. The results showed that the Earth's rotation plays an important role in the asymmetry of the plume flow; the tides control the mixing process, reducing the penetration of the plume on the inner shelf. The results also showed that the balance between fluvial discharge and the wind is responsible for the internal and external displacement of the plume in the Patos Lagoon estuary.

The effects of three distinct west contour currents can be added to these continental contributions in the South Atlantic Inner Shelf: the Malvinas Current (MC), the Brazilian Current (BC) and the Coastal Currents (CC), as well as the effects of tides and winds (Souza and Robinson, 2004). The interaction between the Coastal Currents and the coastal plumes can have several effects on the coastal dynamics (Soares et. al., 2007a). The Coastal Current is a dynamic help in plume transport along the continental shelf, depending only on the wind patterns that control the direction of plume propagation (Soares et. al., 2007b).

The region is also subject to ENSO cycles, although their magnitude is greater in the north of Southwest Atlantic Inner Continental Shelf in comparison with the southern part. In South America, ENSO cycles are a periodic climate pattern characterized by two modes: warm (El Niño) and cool (La Niña) phases, with recurring cycles taking place between every two to seven years (Grimm et. al., 1998). Particularly in the southern region of Brazil, strong and consistent anomalies in precipitation can be associated with these events (Grimm et. al., 1998; 2000). Little is known, however, about how ENSO cycles affect the Southwest Atlantic Shelf. García-Rodríguez et. al. (2014) analyzed changes in geochemical variables in the middle section of the Río de la Plata estuary during the 2009-2010 ENSO event. The authors realized that during the warm phase of the ENSO event, the flow of the river was 5 times greater than the average historical levels. Meanwhile, Berbery and Barros (2002) found that the historical maxima of the river flow during the year following the start of El Niño can triple the typical average flow of the river. However, according to Piola et. al. (2005), the effects of wind and precipitation anomalies tend to compensate for the increased flow, preventing anomalous extensions of northeast plumes associated with large flow events. Therefore, the discharge from the Río de la Plata spreads into the sea. Still on the effect of ENSO on the flow of the la Plata River, Dogliotti et. al. (2016) analysed the spatio-temporal variability of turbidity in the region from 15 years of MODIS satellite data. The authors found a strong seasonal variability in the upper and middle estuaries, with high flow occurring from March to May and low turbidity from June to January. The influence of ENSO
occurs at interannual time scales, showing an increase in turbidity when negative fluvial discharge anomalies occur, but this is not always related to La Niña events since these events are not the only drought predictions in the region. Ciotti et. al. (1995) stated that the amount of chlorophyll in the coastal region is directly related to the nutrients provided by the fluvial discharge. Therefore, extreme precipitation rates and different wind patterns suggest that ENSO events have an important impact on the variability of phytoplankton production, thus affecting biogeochemical cycles in the region of the Southwest Atlantic Inner Shelf.

Távora et. al. (2020) used a 17-year assessment of MODIS-aqua surface suspended sediments in the Patos Lagoon, in southern Brazil, and observed strong suspended particulate matter (SPM) interannual variability correlated with ENSO events. From TELEMAC-3D model simulations over five years, Bitencourt et. al. (2020) also observed the ENSO influence on high suspended sediment concentration (SSC) values throughout the Patos Lagoon on an interannual variability scale.

Although many studies have been conducted on the coastal plumes of the Río de la Plata and the Patos Lagoon, little is known about how these continental contributions actually affect the sediment dynamics and morphological features on the Southwest Atlantic Inner Continental Shelf. Thus, this paper aims to fulfill this gap by answering two scientific questions: how big is the contribution of continental suspended sediment to the Southwest Atlantic Inner Continental Shelf? And how does this suspended sediment behave when it reaches the inner shelf?

## 2. Study Region

The study region is comprised between the latitude of 28° S (Santa Marta Cape) and 38°S (Mar Del Plata), corresponding to the central region of the Southwest Atlantic Shelf (Figure 1), which extends from Tierra del Fuego (55°S), to Cabo Frio (22°S) (Palma et. al., 2008).

<caption>FIGURE 1</caption>

The Southwest Atlantic Inner Shelf (SAIS) is located inside the Southwest Atlantic Shelf (SAS) and it is the most important fishing area of the Brazilian coast (Haimovici et. al., 1989; Castello et. al., 1990). The region receives more than 95% of its discharge from the Paraná and Uruguay Rivers (Depetris and Paolini, 1991), and other tributaries reaching the southern coast of Brazil, such as the Patos-Mirim System, the estuarine complex of Laguna, and the Itajaí-Açu River.

The Río de la Plata is the second largest watershed in South America (3,170,000 km²), extending from the subequatorial zone through to the tropics. The La Plata freshwater discharge is around 22,000 m³/s on annual average and peaks of discharge as high as 90,000 m³/s and as low as 8,000 m³/s can be observed during extreme conditions related to ENSO cycles (Berbery and Barros, 2002). It has an approximately 300 km long northwest to southeast-oriented funnel shape that narrows from 220 km at its mouth to 40 km at the upper end (Moreira et al., 2016), resulting in an estuarine area of 35,000 km².
The Río de la Plata estuary displays a variable geometry and bathymetry, resulting in highly complex river-estuary-ocean dynamics. Therefore, the estuarine region is classically divided into two parts, according to its geomorphology: inner-intermediate and outer regions (Framiñan et. al., 1996). These parts are separated by a topographical feature known as the Barra del Indio shoal (Fossati et. al., 2014), a shallow area that crosses the estuary between Punta Piedras and Montevideo, marking the seaward limit of which both the river cross-sectional area and depth increase and where the salinity front is located (Sepúlveda et. al., 2004). The region is characterised by a fluvial regime with tidal influence and no stratification. The outer region is formed by brackish waters of variable salinity influenced by tides, winds, and the contribution of freshwater from the river basin (Santoro et. al., 2016). Density in the outer estuary is controlled by salinity, whereas temperature exhibits a small horizontal gradient, even though interannual variability may be high (Guerrero et. al., 1997; Simionato et. al., 2010). Water stratification is controlled by the confluence of highly buoyant continental discharge advecting offshore, lying on denser shelf water that intrudes into the estuary as a topographically controlled salt wedge. This salt wedge is typically between 100 and 250 km long and defines a bottom salinity front over the Barra del Indio shoal following approximately the 10 m isobath (Guerreiro et. al., 1997). Forced by the prevailing winds (Simionato et. al., 2001) both surface and bottom salinity fronts show a seasonal cycle that largely modifies the salt wedge structure from spring-summer to autumn-winter (Guerreiro et. al., 1997). The high wind variability that characterises the region (Simionato et. al., 2005) also forces significant variability on synoptic time scales in the estuarine variables (Meccia et. al., 2009).

The tidal regime is microtidal and dominated by the M2 component, followed by O1 component which is responsible for diurnal inequality (Fossati et. al., 2014; Santoro et. al., 2016). The tidal amplitude is greater along the Argentinean coast (order of 1 m), while is about 0.4 m along the Uruguayan coast. The meteorological tides are mainly generated in the Argentinean continental shelf and then propagate northward as trapped coastal waves until they reach the estuary (Santoro et. al., 2013). Currents at the estuary are controlled by the oceanic tide, reaching values close to 0.3 m/s at the bottom and 0.5 m/s at the surface, near Montevideo city (Fossati and Piedra-Cueva, 2013).

Río de la Plata discharges more than 160 million tons/year of suspended sediment into the South Atlantic Ocean, mainly carried by the Paraná River. The outer estuary and the adjacent continental shelf are covered with sand, while silty clays, clayey silts, and silts, are confined to the upper and middle portions of the estuary. The La Plata plume is advected alongshore towards the north, covering long distances and spreading along the coasts of Argentina, Uruguay and Brazil (Piola et. al., 2000; 2005).

The Patos Lagoon, located on the southernmost part of Brazil (between 30 °S and 32 °S), is the largest choked coastal lagoon in the world (Kjerfve, 1986), being 250 km long and 40 km wide and covering an area of 10.360 km². The lagoon is considered as a shallow system with a mean depth of 5 m and higher
depths occurring in the estuarine channel. The latter is narrow (less than 1 km wide at the mouth) and deep (about 16 m) and connects the lagoon to the South Atlantic Ocean.

The Lagoon drains a drainage basin of approximately 201,626 km², consisting of the Guaíba, Camaquã Rivers and the São Gonçalo Channel as the main tributaries in the north, central and south part of the lagoon, respectively. The rivers have a midlatitude pattern with high discharge in late winter and early spring followed by low to moderate discharge through summer and autumn (Möller et. al., 2001). The mean annual freshwater contribution in the north of the Patos Lagoon is 2,000 m³/s; seasonal variations are observed from 700 m³/s during summer (late December–March) up to 3,000 m³/s during spring (September–early December). Moller et. al. (1996) reported river discharge peaks of 12,000 and 25,000 m³/s during El Niño years and which impact the lagoon residence time (Fernandes et al., 2002). Meanwhile, the flow of the São Gonçalo Channel is controlled by gates that are only closed when the levels are above 1 m. Consequently, the discharge of freshwater from the upper part of the lagoon to the estuary is variable (700 to 3000 m³/s), generally being more intense during winter and spring (Hartmann et. al., 1990).

Circulation in the Patos Lagoon is controlled by various mechanisms depending on the considered area: a combination of a local wind-driven set-up and set-down mechanism in the main lagoon, the non-local wind action in the estuarine and coastal regions and the river discharge in the north of the lagoon (Fernandes et. al., 2002; 2005; Moller et. al., 1996). The wind action dominates during periods of low to moderate river discharge (< 2,000 m³/s) (Möller and Castaing, 1999). Möller et. al. (2001) demonstrated that the northeast wind causes a barotropic pressure gradient towards the ocean because of the Ekman Transport acting at 90° to the wind direction, resulting in freshwater discharge into the continental shelf. In contrast, the southwest wind causes an increase in the water level at the coast, promoting a barotropic pressure gradient towards the continent and inhibiting the fluvial discharge from the Patos Lagoon estuary. This pattern does not occur during high river discharge periods (> 2,000 m³/s) because the southwest wind effect is overcome by the river discharge. In this situation, the estuarine zone occurs in the adjacent coastal region (Möller & Castaing, 1999).

The tidal signal in the region is mixed (mainly diurnal), having a mean amplitude of 0.23 m (Moller et. al., 2001) and characterising a microtidal system. The tidal effect is of secondary importance for the dynamics of the system, being restricted to the coastal region and to the estuarine portion of the Patos Lagoon. Fernandes et. al. (2004) demonstrated that the Patos Lagoon access channel acts like a filter damping the tidal signal as it moves up the estuary.

The morphological characteristics of the Patos Lagoon show a dominance of coarse sediment in the shallow areas and fine grains in the deeper ones, especially in the estuarine zone. The west margin of the Patos Lagoon is covered by medium to coarse sand (Martins et. al., 1987; Toldo, 1991), carried out mainly by the Camaquã River. At the east and north margins, sediment is composed of fine sand from the coastal-marine depositional system. Hartmann et. al. (1986) indicated that the average suspended sediment
concentration (SSC) varies from 43 to 196 mg/L based on three years of sampling along the lagoon's main axis and at the mouth of the main tributaries. In a qualitative analysis of the suspended sediment, Hartmann et. al. (1986), reported that the region has a predominance of silt (>80%), followed by clay, and little sand (5%), indicating that the lagoon is a source of silt and clay for the adjacent coastal region. Calliari and Fachin (1993) mapped silty clay and clayey silt in the southern region of the Patos Lagoon mouth, between 15 and 17 m isobaths, but fine sediments can be found at up to 22 m depths. Calliari et. al. (2009) found a sediment accumulation rate of around 25 mm/year based on the ²¹⁰Pb dating method.

Toldo et. al. (2006) estimated the short-term sedimentation rate for the Patos Lagoon based on data of ²¹⁰Pb of surface deposits, defining the sedimentation rate as ranging from 3.5 to 8.3 mm/year. These values corroborate those presented by Ivanoff et. al. (2020) in the same study region. The authors estimated a sedimentation rate ranging from 7 mm/year, in the northern region of the lagoon, passing values around 4.4 to 5.5 mm/year in the central portion, up to values close to 4.8 mm/year in the southern region of the lagoon. As for the impact of ENSO cycles on the region, Ivanoff et. al. (2020) estimated that the sedimentation rate in the north cell of the Patos Lagoon increases by 135% during El Niño years, while in the central and south regions it increases by 164% and 170%, respectively. In the estuarine region, this increase is around 262%.

The estuarine region occupies about 10% of the Patos Lagoon area and is characterised by an increase in cross section with distance from the mouth (Möller et. al., 2001). The lagoon and the estuary are separated by a morphological step formed by sandbanks situated around the region called Ponta da Feitoria (Figure 1). In addition to the contribution from the main lagoon, the São Gonçalo Channel is an important source of sediment to the Patos Lagoon estuary (Hartmann et. al., 1990; Oliveira et. al., 2015; 2019). The sedimentology of the estuarine area is more diverse than in the lagoon, presenting sand in the shallow banks and a combination of silt and clay in the deeper areas (Calliari et. al., 2009).

### 3. Materials and methods

The behaviour and variability of the suspended sediment in the Southwest Atlantic Inner Continental Shelf was investigated using numerical simulations. Two hydrodynamic simulations with a duration of 730 days were carried out, with one simulation performed for the years 2005-2006, and another for 2008-2009 (Appendix A, Table A1). The choice of the analysed periods is related to the ENSO influence over the region, where 2005-2006 is a neutral period (without the ENSO effect) and 2008-2009 is a period affected by La Niña (2008) and El Niño (2009). Details about the model set-up and the methodological steps developed in this work are presented in Appendix A.
## 3.1. The Numerical Models

Hydrodynamic simulations were performed using the 3D model TELEMAC-3D, (www.opentelemac.org), developed by the "Laboratoire National d'Hydraulique et Environnement of the Electricité de France Company (EDF)". The model solves the Navier-Stokes equations considering the local variations in the free surface of the fluid, disregarding density variations in the mass conservation equation, and considering the Boussinesq and hydrostatic approximations for solving momentum equations (Hervouet, 2007).

The transport of suspended sediments is calculated with the TELEMAC-3D system using the SED-3D (V7P0) module, where equations are solved based on the finite element method, with fractional decomposition being performed in steps (Janin and Marcos, 1997). The suspended sediment is treated as an active tracer, but together with salinity and temperature, it can promote fluctuations in the density field. To represent the cohesive effects on suspended sediment transportation, the settling velocity was calculated as a function of the sediment concentration, temperature, salinity and velocity gradient according to the Van Leussen formulation (Van Leussen, 1994), which was applied to this region by Marques et. al. (2010a; 2010b).

Cohesive suspended sediment transport occurs through the combination of advection and diffusion. In SEDI-3D, a 3D advection-diffusion equation is solved by considering the cohesive sediment particles moving at the same velocity as the fluid:

$$ \frac{\partial c}{\partial t} + U_j \frac{\partial c}{\partial x_j} = \frac{\partial}{\partial x_j} \left( \frac{v_t}{\sigma_t} \frac{\partial c}{\partial x_j} + w_s C \delta_{ij} \right) \quad (1) $$

In this equation $U$ is the mean flow velocity (m/s), $t$ is the time (s), $x_j$ represents the components of the coordinate vector (m), $v_t$ is the eddy viscosity (m²/s), $\sigma_t$ is the turbulent Prandtl-Schmidt number (i.e. the radio of $v_t$ to the eddy diffusivity of the sediment particles), $C$ is the sediment concentration (g.l⁻¹) or (kg.m⁻³), $w_s$ is the representative mean settling velocity (m/s) and $\delta_{ij}$ is the Kronecker delta.

At the interface between the water column and the bed layer, erosion processes take place because of the bottom shear stress induced by the flow. The erosion flux is computed with the Partheniades formula – Equation 2 – (Partheniades, 1965). The erosion flux is the product of an erosion rate multiplied with a probability factor as a function of the shear stress in excess of a critical erosion shear stress.

$$ E = \begin{cases} M \left( \frac{\tau_b}{\tau_{ce}} - 1 \right) & \text{if } \tau_b > \tau_{ce} \\ 0 & \text{otherwise} \end{cases} \quad (2) $$
Here, $M$ is the Krone-Partheniades erosion constant (kg.m$^{-2}$.s$^{-1}$), $\tau_b$ is the bed shear stress and $\tau_{ce}$ the critical bed shear stress for erosion. So, erosion only occurs when the bed shear stress is higher than the critical bed shear stress for erosion set by the user. The erosion constant $M$ determines the intensity of the erosion. A larger value will mean more erosion, if erosion occurs. The bed shear stress is given by:

$$ \tau_b = \rho_w u_* |u_*| \qquad (3) $$

Where $\rho_w$ is the density of the water and $u_*$ is the friction velocity. In SEDI-3D, a quadratic friction law is used with a drag coefficient $C_D$ to computed $\tau_b$ in a rough regime. When a Nikuradse formula is used, the equation looks as follows:

$$ \tau_b = \frac{1}{2} \rho_w C_D \bar{U} |\bar{U}| \qquad (4) $$

With:

$$ C_D = 7.831 \ln \left( 12 \frac{h}{k_s} \right) \qquad (5) $$

Here, $\bar{U}$ is the depth-averaged velocity (which also calculated is SEDI-3D), $k_s$ is the roughness size and $h$ is the water depth. After determining the shear stress, the shear velocity is calculated and is then imposed at the bottom as a boundary condition for solving the momentum conservation equations of the flows. The empirical depositional law from Krone is implemented in SEDI-3D to estimate sediment deposition. Here the deposition flux is approximated by the product of local sediment concentration with the settling velocity, multiplied with a deposition probability:

$$ D = \begin{cases} w_s C \left(1 - \frac{\tau_b}{\tau_{cd}}\right) & \text{if } \tau_b > \tau_{cd} \\ 0 & \text{otherwise} \end{cases} \qquad (6) $$

Where, $\tau_{cd}$ is the critical shear stress for mud deposition, $w_s$ is the settling velocity (m/s), and $C$ is SSC (g.l$^{-1}$) or (kg.m$^{-3}$). If the bottom shear stress is smaller than the critical bottom shear for deposition, the sediment is settling.

The bed evolution in SEDI-3D is calculated with the Exner equation (Exner, 1925):

$$ (1 - \lambda) \frac{\partial z_b}{\partial t} + (E - D) = 0 \qquad (7) $$
Where, $\lambda$ is the bed porosity and $z_b$ is the bed level.

In this version of SEDI-3D only one fraction of cohesive sediment can be modelled. Based on the main suspended sediment grain size observed by Toldo et. al. (2006), Fossati and Cuevas (2013), and Moreira and Simionato (2019) for the study region, a characteristic silt particle diameter of 50 µm was chosen. The constant settling velocity of 0.5 mm/s was chosen according to the grain size and based on Van Leussen et. al. (1994), Winterwerp et. al. (2002) and Lee et. al. (2011). The sediment density was set to 2650 kg/m³. Flocculation and hindered settling were not considered. Two initially empty bed layers were chosen. If mud was deposited in these layers, the mud layer density was set to 1500 kg.m⁻³. The critical shear stress for erosion was set to 0.15 Pa, the critical shear stress for deposition was 0.05 Pa, and the Partheniades coefficient was 2.0E-6 kg.m⁻².s⁻¹. These three parameters are calibration parameters regarding suspended sediment transport.

## 3.2. Domain and Numerical Mesh

The domain defined for this work (Figure 2) extends from latitudes 28° S (Cabo de Santa Marta - SC) to 38° S (Mar del Plata) and longitudes of 49° W to 52° W, reaching depths of approximately 300 m. Data from different sources was combined to acquire for the best representation of the bathymetric characteristics of the La Plata River, the Patos Lagoon and its estuary and the adjacent coastal region.

For the estuarine region, the lagoon and the northern coast, bathymetric data extracted from the nautical charts of the *Diretoria de Hidrografia e Navegação (DHN)* of the Brazilian Navy. In order to improve the quality of bathymetric information in the main access channel to the Port of Rio Grande, data from a survey carried out in 2006 and 2010 by the port authorities and complementary data from a bathymetric survey carried out by the Brazilian Navy as part of the Brazilian Continental Shelf Survey Project (LEPLAC) were used. The bathymetry of the Rio de la Plata and its adjacent coastal region was interpolated with data from the Argentinean Navy, and complemented with data from Smith and Sandwell (1997) for depths greater than 200 m (Palmas et. al., 2008).

FIGURE 2

The numerical domain was initially discretised with triangles measuring 10 km at the oceanic edge, 6 km in the Inner Platform, 3 km in the coastal region and 1.5 km at the mouth of the La Plata River; near the mouth of the Patos Lagoon the triangle edges varied between 130 m to 20 m. The resulting 2D unstructured mesh (Figure 2) has 18275 nodes and 33296 triangular elements, discretised vertically with 11 sigma levels, for which the equations were solved.
### 3.3. Initial and Boundary Conditions

Together with initial conditions, the model needs boundary conditions to better represent the dynamics of the region. The numerical mesh (Figure 2A) has 7 open boundaries: the continental boundaries in the north of the Rio de La Plata and the Patos Lagoon, the oceanic boundary, the coastal north and south boundaries, and the surface boundary. Details about the data used as initial and boundary conditions are presented in Appendix B.

Initial salinity conditions (Appendix B, Figure B1), a constant water level of 0.4 m and an initial current velocity of 0.5 m/s were initially prescribed throughout the domain in the hydrodynamic module (TELEMAC3D).

In the oceanic boundary, tide and constant mean water level (eastern boundary), current velocity (north and south boundaries) and salinity data were prescribed (Figure 2A and Appendix B, Figure B1). The tide was calculated by the inverse solution of Laplace's equations (Edgbert et. al., 1994), and 33 harmonic components of the tide were used to generate a reliable estimate of the sea level behaviour (Appendix B, Figure B1). Current velocity was estimated using regional tidal current velocity fields, obtained with the OSU Tidal Inversion Software-OTIS (Edgbert and Erofeeva, 2002), internally coupled in TELEMAC. Salinity fields were obtained from HYCOM + NCODA Global (Hybrid Coordinate Ocean Model, https://hycom.org/), with temporal and spatial resolutions of 3 h and 0.08°, respectively.

The continental boundary conditions for the Patos Lagoon correspond to daily river discharge data (Appendix B, Figure B3) from the Guaíba and Camaquã Rivers, provided by the Brazilian National Water Agency (ANA – www.hidroweb.ana.gov.br). For the third tributary (Canal São Gonçalo), there is no systematic discharge time series and the water level data obtained from the Mirim Lagoon Agency (ALM, https://wp.ufpel.edu.br/alm/) was converted into daily freshwater discharges by Oliveira et. al. (2015) using a rating curve method. For the La Plata River, daily river discharge data were provided by the Argentine Naval Hydrography Service (https://argentina.gob.ar/armada). For the suspended sediment fluxes from the rivers, there are no available measurements to build realistic time series. Riverine SSC was therefore considered constant in the model, so sediment fluxes are only dependent on the river flow. Values assigned for SSC were 200 mg.l⁻¹, 100 mg.l⁻¹, 150 mg.l⁻¹ for the Guaíba River, Camaquã River and São Gonçalo Channel, respectively (Marques et. al., 2010), and 230 mg.l⁻¹ for the Río de la Plata (Moreira and Simionato, 2019). The suspended sediment class used in this study was fine silt (Marques et. al., 2010b).

Wind data from the European Centre for Medium-Range Weather Forecasts' (ECMWF), ERA Interim (http://www.ecmwf.int) was prescribed at the surface boundary, with a 6 h temporal scale and 0.75° spatial resolution, interpolated in time and space for every point of the numerical mesh (Appendix B, Figures B4 and B5).
### 3.4. Model Calibration and Validation

The TELEMAC-3D model has been extensively calibrated and validated for the Patos Lagoon (Fernandes et. al., 2001; 2002; 2005; 2007; Marques et. al., 2009; 2010a; 2010b; Silva et. al., 2015, Oliveira et. al., 2019). In this study, the model domain has been significantly extended (Figures 1 and 2) and complementary calibration and validation exercises were carried out. The model's ability to reproduce measured data was evaluated based on statistical parameters such as those presented by Fernandes et. al. (2001), Marques et. al., (2009) and Lisboa et. al., (2015) (Appendix C).

In the hydrodynamic calibration exercises, current velocity, direction and salinity data, from the 22nd of October to the 30th of November of 2006 and from the 15th of October to the 19th of November of 2011 were collected at the coast using an ADPC (Acoustic Doppler Current Profiler) model Sontek Argonalta 1000 kHz and a CTD (Conductivity Temperature Depth) installed in the access channel of the Port of Rio Grande, respectively. Free surface elevation data from the 16th of May to the 24th of October of 2005, and from the 19th of March to the 31st of August of 2010 obtained in the Rio de La Plata navigation channel as part of the FREPLATA-IFREMER project were also used.

In the first stage of the calibration exercises, different values of specific physical parameters were tested. Because the dynamics of the region are strongly affected by the wind, the first parameter investigated was the Wind Influence Coefficient, with values varying from $10^{-4}$ to $10^{-6}$ (the higher the Wind Influence Coefficient, the strongest the wind influence). Other important physical parameters applied in the calibration exercises were a time step of 60 s, a Coriolis coefficient of -7.70735 x $10^{-5}$ s⁻¹, a Smagorinsky in the horizontal turbulence model (30 for salinity and $1 \cdot 10^{-4}$ for sediment), a mixing length (Prandlt) in the vertical turbulence model ($1 \cdot 10^{-6}$) and Manning as the law of bottom friction (0.02 s/m¹/³). The best model results were obtained with the Wind Influence Coefficient equal to $3 \cdot 10^{-6}$ when comparing measured and calculated current velocity at the surface (Figure 3A) and at the bottom (Figure 3B) in the access channel to the Port of Rio Grande. In this calibration exercise, the values found were considered excellent (RMAE = 0.16 and 0.18) according to the statistical classification Waltra et. al. (2001) and Sutherland et. al. (2004a; 2004b).

#### FIGURE 3

After defining the adequate Wind Influence Coefficient ($3 \cdot 10^{-6}$) for the region, further calibrations were carried out varying the horizontal (Smagorinsky, K-Epsilon) and vertical (Tsanis, Prandlt and K-Epsilon) turbulence models, as well as the bottom friction laws (Manning and Nikuradse), as shown in the calibration exercises for the free surface elevation at Cassino Beach and Rio de La Plata, in Appendix D. The best results were achieved for Test 10, with RMAE of 0.15 and 0.18 for Cassino Beach (Figure 4A) and Rio de La Plata (Figure 4B), respectively; these values are classified as excellent according to Waltra et. al. (2001). Thus, the best set of physical parameters was defined as a combination of the Manning law of bottom friction
(friction coefficient= 0.02 s/m¹/³), the Smagorinsky horizontal turbulence model (30 for salinity and 1.E10⁻⁴ for Sediment) and the mixture length (Prandlt) vertical turbulence model (1.E10⁻⁶).

FIGURE 4

After defining the best set of physical parameters for the hydrodynamic model, further validation exercises were carried out for the period between the 22nd of October to the 30th of November of 2006, and the model's performance for reproducing salinity and current velocity was evaluated (Figures 5A and 5B). The model's performance for simulating salinity at the surface and near the bottom of the Patos Lagoon estuary was classified as good according to Walstra et. al. (2001), with RMAE of 0.24 and 0.40, respectively. The RMSE values ranged from 5.68 to 9.06 psu. Considering the measured and calculated current velocity time series, the model's capacity was also classified as excellent according to Walstra et. al. (2001), with RMAE of 0.16 and 0.18 at the surface (Figure 5A) and bottom (Figure 5B), respectively. RMSE values ranged from 0.16 to 0.37 m/s. An overall analysis of the calibration and validation exercises indicates that the TELEMAC Model is an adequate tool for simulating the hydrodynamics of the domain.

FIGURE 5

For the validation of calculated SSC, data from Rio de La Plata between the 26th of November of 2009 and the 16th of December of 2010 (FREPLATA-IFREMER Project) were used. Details about data acquisition procedures were described by Fossati et. al. (2014). Figure 6 shows the temporal evolution of the calculated and measured SSC in the lower, middle and upper Rio de La Plata estuary, resulting in RMSE values ranging from 14.05 to 15.53 mg.l⁻¹ and a RMAE = 0.21, at the limit between the classification of an excellent and a good reproduction (Walstra et. al., 2001).

FIGURE 6

Due to the lack of observational SSC data for the calibration of the numerical model in southern Brazil, an alternative methodology based on remote sensing products for the region were used. Three LandSat 5 images from the American Space Agency (https://earthexplorer.usgs.gov/) were used (6th of February, 2008; 3rd of October, 2008; 17th of September, 2008), and processed according to Peixoto et. al. (2018) to obtain products with a 30 m spatial resolution for further comparison with calculated maps of surface SSC in two profiles (Figure 7).
Longitudinal and transversal profiles were used for a quantitative comparison.

FIGURE 7

A comparison between the SSC calculated by the numerical model and information from remote sensing indicates that the model can reproduce some features of the Patos Lagoon coastal plume such as its orientation and spreading. Furthermore, the profiles selected for comparison (Figures 7C and 7F) indicate that numerical and remote sensing information is as similar, with RMSE values of 3.96 and 2.85 mg.l⁻¹ for the alongshore, and 3.16 and 3.86 mg.l⁻¹ for cross shore profiles (Figure 7C and 7F).

3.5. Time series analysis

Results from the numerical experiments indicate the contribution of the Patos Lagoon and Rio de Plata coastal plumes to the South Atlantic Inner Shelf. The analysis of their spatial and temporal variability in distinct regions of the domain, however, is not straightforward and depends on the scale of the SSC. This regional variability can be accessed using the empirical orthogonal function (EOF) analysis, which provides a compact description of the spatial and temporal variability of simulated data series in terms of statistic modes, where most of the variance of the spatially distributed series can be observed in the first few orthogonal functions (Emery and Thomson, 1998). Knowing the regions that the coastal plumes are located in during the majority of the time is essential for identifying potential regions where the fine sediments transported via river discharge could be initially deposited after reaching the coastal region.

The spatial and temporal variability of SSC calculated for the domain with the numerical model was analysed based on the first three EOF analyses for the neutral period (2005-2006) and for the period affected by an ENSO cycle (2008-2009). Three spatial representations were considered: 1) a horizontal plan; 2) longitudinal and transversal vertical transects at the mouth of the Rio de La Plata; and 3) longitudinal and transversal vertical transects at the mouth of the Patos Lagoon.

A wavelet analysis (continuous wavelet transform), regarded as a better option for dynamic analysis (Farge, 1992), was applied to this study to evaluate the spatial and temporal variability of SSC. This wavelet spectrum (or local energy cross-spectrum) provides energy variations along a frequency-time axis, which enables the determination of the dominant modes of variability and how those modes vary in time (Torrence & Compo, 1998). The contour line (dashed lines) enclosing regions is indicated to a 95% confidence level to the correlation between the time series varying in both space and time. For the global spectrum, the influence of the analyzed variable is only representative if power values are greater than the 95% confidence level (dashed line). The choice of mother-wavelets (or wavelets function) is essential for adequate results (Jalón-Rojas et. al., 2016). Thus, for the present study the Mexican hat (for higher frequencies – seasonal, annual, and interannual time scales) mother-wavelets were selected to analyse river discharge relations with SSC,
while the Morlet wavelet was applied to analyse wind relations with SSC, as mentioned by Marques et. al. (2014), Oliveira et. al. (2015) and Costi et. al. (2018).

# 4. Results

## 4.1. Distribution of the Patos Lagoon and Río de la Plata Plumes in the South Atlantic Inner Shelf

The results of SIM1 (Appendix A – Table A1) show the simultaneous behaviour of the Patos Lagoon and Río de la Plata plumes in winter and summer (Figure 8). During the winter of the neutral period (Figure 8A), both plumes are spread on the inner shelf, with the plume of the Patos Lagoon moving south and that of the Río de la Plata to the north, reaching a latitude of 30° S. In this case, SSC values are continuously high (> 10 mg/l) along the coast between the two outlets. Due to the large difference in fluvial discharge values between the two estuaries, it was noted that the plume of the Río de la Plata penetrates the Patos Lagoon estuary, near the entrance. The results still show that the La Plata plume is dense enough to merge with or even dominate over the Patos Lagoon plume during the southern winter. In summer (Figure 8C), the predominance of northeast winds and the lower continental discharge associated with the drier season produce less spreading of the two plumes on the inner shelf, and their meeting does not seem to happen, since a SSC minimum (1 mg/l) is observed close to the coast, between two more concentrated areas close to the two outlets. During the period of influence of the ENSO cycle (Figures 8B and 8D), the SSC values did not change much. The differences were more due to the displacement of the plume, which reached shorter distances, both along the coast and along the ocean, characterising a more coastal plume when compared to the previous (neutral) period.

FIGURE 8

Figure 9 shows the average SSC and the normal and transverse velocities calculated by the model along the water column for transverse transects across the Río de la Plata (T2) and the Patos Lagoon (T4) mouths during the simulated periods (SIM1 and SIM2). The results indicate that the coastal plumes of the Río de la Plata and the Patos Lagoon exhibit different behaviours. Under neutral conditions, the Río de la Plata (Figures 9A and 9B) assumes a homopycnal flow pattern, with uniform SSC over the entire water column, longitudinal velocities indicating residual outflow (red tones) and higher SSC close to the margins towards the coastal region (reaching up to 200 mg/l). The Patos Lagoon (Figures 9C and 9D) shows a larger SSC vertical gradient, where the highest values are concentrated in the centre of the transect and near the surface, assuming a characteristic of hypopycnal plume with positive buoyancy (Figure 9C). The residual flow chart (Figure 9D) shows residual outflow over the water column in the centre of the transect, in line with
the lagoon outlet, while inflow is observed at the north and the south of the transect, with higher valuer in the south. During the period affected by the ENSO cycle, these patterns are maintained in both transects (Figures 9E to 9H), with small differences with the neutral period. In both outlets, weaker residual flows are observed, the difference was due to the SSC. While in Patos Lagoon it was observed that there was a decrease in SSC, in Río de la Plata this value increased both on the north coast and on the south coast due to the effect of La Niña.

FIGURE 9

As a way of quantifying how much suspended sediment the Río de la Plata and the Patos Lagoon export to the adjacent inner shelf, the section-averaged suspended matter flux was calculated along the transects T2 and T4 (Figure 10), based on the average SSC and the normal velocity component in the cross-section (Figure 9).

The results of Figure 10A indicate the predominance of a negative mass flux in the Patos Lagoon during the neutral period, showing that the region exports suspended sediment to the coastal region during most of the analysed period. The highest peaks are observed between July and December of 2005 when the Patos Lagoon exports $3.0 \times 10^4$ tons/day of suspended sediment to the inner shelf. The time series of the cumulative mass flux of suspended sediment in the cross-section indicates that the Patos Lagoon exported $2.5 \times 10^7$ tons of suspended sediment during the years 2005-2006 and presented an average annual flow of $1.25 \times 10^7$ tons/year. In the period under the influence of the ENSO cycle (Figure 10B), predominantly La Niña, the export pattern of suspended sediment from the Patos Lagoon remained the same, but with less accumulative mass flux during the period ($1.0 \times 10^7$ tons/year) and, consequently, less annual flow ($2.2 \times 10^4$ tons/day). However, a strong ebbing event at the end of 2009 due to an El Niño event raised the suspended sediment flux into the platform to $4.5 \times 10^4$ tons/day, generating an accumulative mass flux of $2.7 \times 10^7$ tons of suspended sediment exported in that period, which results in an annual rate of $1.35 \times 10^7$ tons/year.

FIGURE 10

Figures 10C and 10D present the same analysis for the cross-section at the Río de la Plata mouth (Figure 1), where a synoptic-scale modulation can be observed promoting the alternation between suspended sediment export and import. The largest exports of suspended sediment occurred at the end of 2005 and the beginning of 2006 (summer in the Southern Hemisphere). During this period, the Río de la Plata exported a maximum flux of $2 \times 10^5$ tons/day of suspended sediment to the inner shelf. In contrast to what happened in the Patos Lagoon, in the La Plata River, periods of positive mass flux are significant for the region, with a suspended sediment import flux of $2.5 \times 10^5$ tons/day at the end of 2005 and early 2006
(summer in the Southern Hemisphere), approximately ten times greater than the flux found for the Patos Lagoon. The accumulative mass flux of suspended sediment suggests that the Río de la Plata exported 2.3x10⁸ tons of suspended sediment during the years 2005-2006, with an annual average flux of 1.2x10⁸ tons/year. The results for the period subjected to the ENSO cycle (Figure 10D) show that similarly to the Patos Lagoon, the Río de la Plata maintained the pattern of mass flux behaviour during this period and maintained lower concentrations of suspended sediment until the moment that the El Niño event began (October 2009). As of this moment, the mass flux underwent a significant increase reaching 5.8x10⁸ tons/day at the end of 2009. As a result, the accumulative mass flux reached 6.0x10⁵ tons/day, and the annual integrated mass flux was 3.0x10⁸ tons/year.

## 4.2. Spatial Variability of Coastal Plums

The EOF analyses of the entire studied domain presented in this article resulted in a map depicting the spatial variability of the coastal plumes of the Río de la Plata and the Patos Lagoon on the South Atlantic Inner Shelf (Figure 11). Under neutral conditions, the first EOF represents 61% of the variance (Figure 11A) and indicates a high SSC amplitude in the north of the Patos Lagoon and on the south coast of the La Plata River, mainly in the regions near Punta Piedras, where tributaries contribute the highest SSC. The second EOF represents 22% of the variance and is located near Montevideo (Figure 11C), while the third EOF represents only 8% of the variance (Figure 11E). During the period influenced by the ENSO cycle, the first EOF mode represents 51% of the variance, while the third EOF mode remained unchanged (Figures 11B and 11F). However, due to the lower discharge values observed, the modes of variability underwent changes in the second EOF, which explain 14% of the observed variability (Figure 11D).

FIGURE 11

Similar EOF analyses are presented for SSC along the longitudinal transect of the Río de la Plata (T1, Figure 12). During the neutral period, the first EOF represents 49% of the variance and higher SSC close to the continental inflow, mainly at the estuary bottom (Figure 12A). The second EOF represents 28% of the variance (Figure 12C) and the third 4% (Figure 13E) indicating the presence of high SSC moving towards the inner shelf. During the period under the influence of the ENSO cycle, the first EOF represented 67% (Figure 12B), the second 22% (Figure 12D) and the third 4% (Figure 12F) of the variance, presenting lower SSC that spread more across the adjacent coastal region. The occurrence of higher SSC near the bottom is evident in the three modes of variability of the EOF.

FIGURE 12
In the transversal profile of the Río de la Plata mouth (T2, Figure 1) during the neutral period (Figures 13A, 13C, 13E), the first EOF represents 48% of the variability of SSC located near the south margin of the river mouth. The second mode (32%) corroborates that the highest SSC occurs in the north margin of the river mouth, as can also be seen in the normal velocity component of the cross-section of the mouth (Figures 9B and 9F); the third mode (9%) indicates the occurrence of high SSC in both margins and low SSC in the centre of the profile. Again, the occurrence of the highest SSC near the bottom is evident.

When we consider the period under the influence of the ENSO cycle (Figures 13B, 13D, and 13F), the first EOF presents 77% of the variability very close to the south margin of the Río de la Plata mouth (Figure 13B), and this pattern spreads slightly to the north margin of the mouth in the second EOF (12%; Figure 13D). The first two EOF analyses corroborate the intensification of ebb currents observed in this region in Figure 9F. The third EOF (9%, Figure 13F) behaves similarly to the previous period, indicating the occurrence of high SSC in both margins of the estuary and low SSC in the centre of the profile.

FIGURE 13

Along the longitudinal transect of the Patos Lagoon mouth (T4, Figure 1), the first EOF represents 93% of the variance and higher SSC towards the south of the Rio Grande jetties bar (dotted line, Figure 14A). The second EOF represents only 3% of the variance (Figure 14C) and the third 2% (Figure 14E), always remaining concentrated south of the bar jetties. The EOF represents the residual outflow of the suspended sediment shown in Figures 8A and 8C, showing the hypopycnal flow characteristics of the plume when leaving the Patos Lagoon estuary (Figures 9C and 9G), through the bar jetties. During the period under the influence of the ENSO cycle, the same pattern was observed, with the first EOF representing 92% of the variance (Figure 14B), the second 4% (Figure 14D) and the third 2% (Figure 14F), indicating that the hypopycnal flow characteristics of the plume persist in extreme events.

FIGURE 14

In the transversal profile to the Patos Lagoon mouth during the neutral period (figure 15A, 15C, 15E), in the first EOF, which represents 73% of the SSC variability, a core of maximum pattern towards the ocean can be identified, corroborating the results presented in figures 9C and 9G which show the superficial position of the sediment plume at the mouth. The second EOF (12%) shows a well-marked pattern in the behaviour of the plume with a preference in transgressing towards the south of the mouth, while the third EOF (6%) shows the slightly tendency of the plume to migrate to the north of the mouth.

When we consider the period under the influence of the ENSO cycle (Figure 15B, 15D and 15F), the first EOF shows 70% of the variability maintaining the pattern (spatial distribution) found in neutral years, but
more intensified. This behaviour is repeated both for the second EOF (11%) and for the third (6%), showing
a pattern in the displacement of the plume to the south and to the north of the Patos Lagoon mouth,
respectively.

FIGURE 15

**4.3. Temporal Variability of Coastal Plumes**

In order to better evaluate the temporal variability of SSC in the Río de la Plata and Patos Lagoon estuaries, a cross-wave analysis was performed on the calculated time series of SSC, correlating its behaviour with fluvial discharge from the river (Figures 16 and 17). The relationship of SSC with the wind was also assessed (Figures 18 and 19)

FIGURE 16

The results show that during the neutral period (Figure 16A) the relationship between SSC and fluvial discharge from the Río de la Plata occurs in time intervals between 32 and 256 days during 2005, and part of 2006, as can be observed by the occurrence of regions delimited by black contour lines that occur within the area of significance (dashed line) of Figure 16B. This result is in line with the global power spectrum (Figure 16C), which indicates that the power (solid line) is greater than the 95% confidence interval (dotted line), for periods longer than 32 days.

When analysing the results during the period under the influence of the ENSO cycle (Figure 16D), the cross-analysis between the SSC and the river discharge in the Río de la Plata region extends the interval to between 32 and 512 days, during the two years, as delimited by the black line in the figure, within the significance range (dashed line) of Figure 16E. The global power spectrum (Figure 16F) corroborates this result, indicating that the power (solid line) is greater than the 95% confidence interval (dotted line) for periods longer than 32 days.

FIGURE 17

For the Patos Lagoon region, the results show that during the neutral period (Figure 17A) the cross-
analysis between the SSC and the fluvial discharge occurs in time intervals between 32 and 512 days during
2005 and 2006, as can be observed by the occurrence of regions bounded by black contour lines that occur
within the area of significance (dashed line) of Figure 17B. This result is in line with the global power spectrum
(Figure 17C), which indicates that the power (solid line) is greater than the 95% confidence interval (dotted
line), for periods longer than 32 days.
When analysing the results during the period under the influence of the ENSO cycle (Figure 17D), the cross-analysis between the SSC and the Patos Lagoon fluvial discharge reduces the interval to between 32 and 256 days, during the two years, as delimited by the black line in the figure, within the significance range (dashed line) of Figure 17E. The global power spectrum (Figure 17F) corroborates this result, indicating that the power (solid line) is greater than the 95% confidence interval (dotted line) for periods longer than 32 days.

FIGURE 18

The relationship between the wind and the SSC of the Río de la Plata for the simulated periods is shown in Figure 18. During the neutral period (Figure 18A and 18B), the relationship of the wind with the suspended sediment occurs on a synoptic time scale between 2 and 16 days, as can be seen by the occurrence of regions bounded by black contour lines that occur within the area of significance (dashed line) of Figure 18B. This result is in accordance with the global power spectrum (Figure 18C), which indicates that the power (solid line) is greater than the 95% confidence interval (dotted line), for periods shorter than 16 days. The same behaviour was observed for the period under the influence of an ENSO cycle (Figures 18D-18F), but only in the summer of 2008 and spring and summer of 2009 (Southern Hemisphere).

FIGURE 19

A similar analysis made for the Patos Lagoon shows that SSC (Figure 19) is also correlated with the wind on a synoptic time scale between 2 and 16 days both in the neutral period (Figures 19B and 19C) and in the period under the influence of the ENSO cycle (Figures 19E and 19F).

4.4. Behaviour of Sediment in Suspension on the Inner Shelf

In order to understand the behaviour of suspended sediment on the South Atlantic Inner Shelf, daily time series of SSC were extracted from a cross-section established along the inner shelf (T6, Figure 1) for the simulated periods, and its spatial and temporal distribution were analysed in the Hovmöller diagram (Figures 20 top panel – A, B and C – and bottom panel – D, E and F). This diagram shows the time on the ordinate axis and the geographic coordinate on the abscissa axis, with the southwest being the limit of the closest transect to the Río de la Plata and the northeast the closest limit to the Patos Lagoon.

FIGURE 20
The spatial and temporal distribution of the SSC along T6 (Figure 1) on the inner shelf appears to have a direct relationship with the SSC from the continental discharge of the Río de la Plata and the Patos Lagoon (Figures 20A and 20C) most of the time during the neutral period, because following the continental discharge peaks of these contributors, high SSC are observed distributed along the adjacent coast. This behavior is especially evident for the Patos Lagoon during the winter and spring of 2005 (Southern Hemisphere) (Figure 20C), although it does not always apply to the La Plata River, as seen in the summer of 2005-2006 (Southern Hemisphere), when high SSC are observed on the inner shelf (Figure 20B), but discharge peaks in the Río de la Plata are not evident (Figure 20A).

In bottom panel, a similar analysis is made for the period affected by the ENSO cycle. The results indicate that the direct relationship between continental discharge and SSC is maintained in the Patos Lagoon (Figure 20F) both during the La Niña period (2008 and the 1st semester of 2009) and during the El Niño period (the 2nd semester of 2009 for the La Plata River; Figure 20D); the continental discharge peaks observed at the end of 2008 (La Niña) and at the end of 2009 (El Niño) were reflected in peaks of SSC in the inner shelf.

FIGURE 21

The preferred regions of occurrence of the highest SSC in the inner shelf were determined through an EOF analysis of the region during the two simulated periods (Figure 21). Both during the neutral period and during the period influenced by the ENSO cycle, the first EOF represented 60% (Figures 21A and 21D) and the second EOF 15% (Figures 21B and 21E) of the variance, indicating higher SSC in the region of inner shelf between the mouths of the Río de la Plata and the Patos Lagoon; this suggests an interaction between the contributions from the two environments. The third EOF (5% variance, Figures 21C and 21F) is related to the high SSC exactly in front of the mouth of the tributaries.

## 5. Discussion

Since the calibration and validation exercises resulted in statistic parameters considered adequate, the model's ability to reproduce the realistic behaviour of the system was considered effective (Appendix E). Thus, our results show that the model reproduced the variability of the SSC over a neutral period (2005-2006) and over a period under the effect of ENSO, predominantly La Niña (2008–September of 2009), with the appearance of an El Niño event from October of 2009 for the Southwest Atlantic Inner Shelf.

### 5.1. Distribution of Patos Lagoon and Río de la Plata Plumes in the South Atlantic Inner Shelf

The SSC distributions in the Southwest Atlantic Inner Shelf (Figure 8) show a relationship with the seasonality of the Patos Lagoon and the Río de la Plata plumes for both periods analysed. The southern
winter (Figures 8A and 8B), is when the higher SSC values associated with the regions being most influenced by the Río de la Plata occurred, and when the seasonal cycle had a robust signal, as also observed by Guerrero et. al. (1997). As analysed by Campos et. al., 1999, Piola et. al. (2004), Pimenta et. al. (2005), Soares et. al. (2007a) and Simionato and Moreira (2018), among others, during the southern winter the Río de la Plata estuarine plume expands widely as a coastal strip in a northeast direction along the coast of Uruguay and southern Brazil (Moreira et. al., 2013), reaching latitudes close to 26°S; this shows the plume can reach more than 1,000 km of distance from the mouth of the La Plata River. During the southern summer (figures 8C and 8D) the influence of SSC on the inner platform occurs through a relatively thin coastal strip that migrates to the north, reaching latitudes close to 30°S and through another portion that is concentrated in the region of the mouth of the Río de la Plata (Piola et. al., 2004).

Like for the La Plata River, the Patos Lagoon SSC contribution to the adjacent coastal region is influenced by the seasonal character of the suspended sediment coastal plume (Marques et. al., 2010a; 2010b). Higher SSC values occur during the southern winter (Figures 8A and 8B) when the river discharge is stronger in the region. Additionally, during the southern summer (Figures 8C and 8D) the region has lower SCC values, when the observed values of fluvial discharge are below average (Marques et. al., 2009). Still on the importance of fluvial discharge, Burrage et. al. (2008) stated that due to the contrast between fluvial discharge regimes from the two estuaries (22,000 m³/s for the Río de la Plata compared to 2,000 m³/s for the Patos Lagoon), the Río de la Plata plume normally penetrates beyond the entrance to the Patos Lagoon estuary, fully incorporating it by merging or even dominating the plume of the Patos Lagoon, corroborating the results in this work.

It is worth noting that the region studied during the years influenced by the ENSO phenomenon may present precipitation anomalies (Grimm et. al., 1998; Grimm et. al., 2000). Thus, the years under the influence of El Niño tend to be more humid with a high rate of precipitation, and the opposite is observed in La Niña years, when a drought period is expected.

During the period influenced by the ENSO phenomena – predominantly La Niña – (Figures 8B and 8D) the SSC patterns showed high interannual variability. According to Dogliotti et. al. (2016), low turbidity values were observed during El Niño years and high turbidity values during some La Niña years. However, the La Niña (El Niño) effect is not always the only dry (flood) forecast in the region. This is due to the fact that the main contributor of suspended sediment to the Río de la Plata and the Bermejo River (approximately 70% of the total sediment), is not greatly affected by ENSO phenomena (Pasquini and Depedris, 2007; Dogliotti et. al., 2016). However, the main effluents that supply more than 97% of the La Plata's freshwater are highly influenced by the rainfall anomaly caused by the ENSO effect (Dogliotti et. al., 2016), which may increase the average of river discharge by 3-5 times (Berbery and Barros, 2002; García-Rodríguez et. al., 2014). Therefore, the influence of the ENSO phenomena on SSC acts essentially by diluting the concentration of the sediment due to the increased flow of the main effluents.
For the Patos Lagoon, the interannual variability and its contribution to local dynamics has been investigated by several authors (Möller et. al., 2001; Fernandes et. al., 2002; Vaz et. al., 2006; Marques et. al., 2010a; 2010b, Távola et. al., 2020; Bitencourt et. al., 2020). It has been shown that there is an anomalous pattern in fluvial discharge, with values that exceed the average during the El Niño years and values that vary from the average to below average during La Niña years, significantly changing the SSC, as shown in figures 8B and 8D. Marques et. al. (2010b) reported a direct relationship between the fluvial discharge and the SSC, which intensifies towards the Atlantic Ocean during strong El Niño events.

Regarding the influence of wind in the region, Piola et. al. (2004) and Moreira et. al. (2013) confirmed that there is strong seasonal variability in wind stress along the coast. During the summer (Figures 8C and 8D), winds of moderate speed from the north and northeast directions dominate, being responsible for the minimum displacement of the coastal plume (Piola et. al., 2004; Soares et. al., 2007a). During the winter (Figures 8A and 8B), the wind exhibits the opposite behaviour: strong southwest winds become frequent and important in the maximum insertions of coastal plumes to the north during the austral winter (Piola et. al., 2004; Soares et. al., 2007a).

Regarding the hydrodynamics of the Río de la Plata estuary, Fossati and Cuevas (2013) qualified the wind action, together with the river discharge and meteorological tide, as the main forces of local estuarine circulation, in addition to the strong participation of the local bathymetry in local hydrodynamics. Figure 9B and 9F show that flood and ebb flows are highly influenced by local bathymetry, as confirmed by Fossati and Cuevas (2013). This is because in the high estuary, near the river mouth, ebb flows are commonly observed in shallow areas, such as coastal or shoal zones (Figures 9B and 9F). On the other hand, flood flows are found in the deeper areas, mainly in those closest to the Uruguayan coast (Figures 9B and 9F). These results corroborate those found by Fossati and Cuevas (2013) when observing an inflow of salt water through the deepest regions near the northern coast of the estuary. The ENSO effect in the region (Figure 9F) was noticeable in the results when de-intensifying the flood and ebb currents, as was observed by Guerrero et. al. (1997) in the Río de la Plata estuary. When analyzing the hydrodynamics of the Patos Lagoon through the cross section (Figures 9D and 9H), a unidirectional circulation pattern is observed in the channel region, with the results indicating a dominance (mean) of the ebb flow. During the La Niña years studied, the Patos Lagoon, like the La Plata River, suffered a slight weakening of the current speed (Figure 9H), as a result of the predicted drought period (Grimm et. al., 2000).

Local hydrodynamics control the distribution of suspended sediment across the Río de la Plata estuary (Moreira et. al., 2019). Results in figures 9A and 9E show a homopycnal profile in the plume of the Río de la Plata (occupying the entire water column), with a preference for high SSC, in the upper estuary, along the northern coast (Uruguay) and the southern coast (Argentina). According to Monteiro et. al. (2013), the relatively higher SSC observed along the southern coast of the upper estuary (Figures 9A and 9E) may be linked, at least in part, to the higher suspended solid flow of the Paraná River compared to the Uruguay
River (two of the main effluents in the La Plata River). As a result, waters from the Paraná River tend to occupy the southern coast in the upper portion of the estuary, whereas waters from the Uruguay River are limited to the northern coast. The influence of the ENSO phenomenon (Figure 9E) becomes explicit by reducing the value of SSC both on the south coast and on the north coast, as has also been observed by Dogliotti et. al., (2016) when analysing SSC during La Niña years. For the Patos Lagoon the local hydrodynamics suggest the formation of a hypopycnal plume (positive buoyancy), with a high SSC at its core (Figure 9C), where the maximum occur associated with the maximum discharge events, which most of the time migrate southwards in the coastal region (as a result of northeast winds); during the occurrence of winds from the south quadrant, previously exported materials can be reinserted into the estuarine region, as observed by Marques et. al. (2010b). When considering the years controlled by the ENSO effect (Figure 9G), we find a more weakly concentrated plume compared to normal years. This result found in the present article for the La Niña event, corroborating the results presented by Marques et. al. (2010b), in which the authors show that the freshwater discharge from the Patos Lagoon has a high interannual variability and directly influences the export of suspended material to the adjacent coastal zone. According to the authors, the events El Niño and La Niña can also intensify and considerably reduce the normal seasonal flow pattern, respectively.

Regarding the average behaviours of the suspended sediment and the current at the mouth of the Río de la Plata and the Patos Lagoon, we observed that both systems export waters and suspended sediments of continental origin to the Southwest Atlantic Inner Shelf. The total mass flux estimated through its integration along the cross section at the mouth of the Río de la Plata (Figures 10A and 10B) resulted in time series with very similar inflow and outflow patterns and intensities, where the maxima occur associated with the maximum events of fluvial discharge (Figure B3 - Appendix B), with a delay of approximately one month between the maximum flow and the peak of suspended sediment, was as has also observed by Simionato et. al. (2009), Moreira et. al. (2013) and Dogliotti et. al. (2016). These authors state that this time lag may be the result of the travel time of the sediment from downstream to the mouth. Marques et. al. (2010a) made a similar analysis for the Patos Lagoon in the years 1998-1999. As in the present work, the authors integrated the mass flow (Figures 10A and 10B) along a cross section of the access channel resulting in a time series with a profile similar to that of the river discharge (Figure B3 - Appendix B), where the maximum peaks show some correlation with the maximum flow. The ebb and flow periods are directly related to the north/northeast and south quadrant winds, respectively.

Weather conditions can influence the behaviour of suspended sediment in some coastal regions, as seen by Marques et. al. (2010a) for the south of Brazil and Talke and Stacey (2008) for the San Francisco bay. Thus, when analysing the years under the influence of ENSO, it is clear that when the ENSO index is above 1 (Figures 10E and 10F), there is an evident response in river discharge, significantly influencing the mass flux. It can be seen that at the beginning of 2008 the region is under the effect of a moderate La Niña
event which is already sufficient to alter the values of the mass flux both in the Río de la Plata and in the Patos Lagoon. At the end of 2009 however, an El Niño with an index above 1.5 was enough to increase the amount of suspended sediment exported by the Río de la Plata and the Patos Lagoon.

As for the cumulative value of the transported mass, Menéndez and Sarubbi (2007) stated that the Río de la Plata exports $1.6 \times 10^8$ tons/year of sediment. In the current work, cumulative mass transport for the neutral years (2005–2006) reached an export rate around $1.2 \times 10^8$ tons/year (in the same order of magnitude as the values cited by Menéndez and Sarubbi, 2007), while for the years affected by the ENSO phenomenon, the rates were around $3.0 \times 10^8$ tons/year. For the Patos Lagoon, Marques et. al. (2010b) found a suspended sediment export rate equal to $1.4 \times 10^7$ tons/year, whereas in the present work this rate was slightly lower, hovering around $1.3 \times 10^7$ tons/year. For the years affected by ENSO, this value increased to $1.35 \times 10^7$ tons/year, which is closer to the rate reported by Marques et. al. (2010b).

## 5.2. Spatial Variability of Coastal Plumes

EOF analyses are widely used for oceanographic parameters such as salinity, temperature and chlorophyll, among others, to detect the influence of environmental and oceanographic processes on the spatial variability of the analysed parameters. In the present work, this analysis was used on the SSC exported by the Río de la Plata and the Patos Lagoon to the Southwest Atlantic Inner Shelf, in order to understand how the suspended sediment is distributed in suspension in the studied region.

Our results point to the dominance of two main modes controlling the spatial variability of the SSC in the Río de la Plata and the Patos Lagoon. The first horizontal mode (Figure 11A) explains the spatial distribution of the plumes in 61% of the simulated period, with persistent features in the north of the Patos Lagoon and east and west coasts of the La Plata River. These dominant patterns result from the combination of available waters of continental origin towards the coastal zone due to the formation of coastal plumes, with the action of the wind from the north quadrant in both systems (Möller et. al., 2001; Fernandes et. al., 2002; Marques et. al., 2010a) aligned with the Coriolis effect and the tide acting in the Río de la Plata (Moreira et. al., 2013; Simionato and Moreira, 2018). When studying the period influenced by ENSO (Figure 11B), the first horizontal mode explains the suspended sediment variability 51% of the time. This may be a result of the influence that ENSO has on the river discharge of the Paraná and Uruguay Rivers, as stated by Moreira et. al. (2013) and Dogliotti et. al. (2016).

For the Patos Lagoon, Toldo et. al. (2006) stated that there is a high correlation between the SSC and the fluvial discharge from the Guaíba River. The pattern defined by the first EOF mode (Figures 11A and 11B) for the Patos Lagoon shows this correlation not only for the Guaíba River but also for the other two main effluents in the lagoon, the Camaquã River and the São Gonçalo Channel, as has also been mentioned by Hartmann et. al. (1991) and Oliveira et. al. (2015). The Patos Lagoon access channel also plays a role in the trapping of suspended sediment (Figure 11A). Marques et. al. (2010a) analysed the plume formation in
the Patos Lagoon and showed the importance of the navigation channel in this process, since the presence of this channel intensifies the vertical circulation, favouring the formation of the coastal plume. For the La Plata River, the water supply of the Paraná River takes place mainly along the south coast of the Río de la Plata estuary, showing its importance on local sedimentary dynamics (in red - Figure 11A). On the north coast, where the Uruguay River is mainly responsible for the river contribution, the suspended sediment variability has a negative character (blue - Figure 11A), showing the high variability of this effluent on the dynamics of the estuary. These results agree with those of Guerrero et al. (1997), Moreira et al. (2013) and Moreira et al. (2019).

The second mode of variability (Figures 11C and 11D) represents about 22% of the behaviour of SSC for the period considered neutral period (Figure 11C) and 14% for the period under the ENSO influence (Figure 11D), with an evident attenuation of the Guaíba River plume during the neutral period (Figure 11C) and its intensification during the ENSO period (Figure 11D). For the Río de la Plata this second mode of variability in SSC for the neutral period suggests a preference of the coastal plume in concentrating on the northern coast of the La Plata estuary. In the ENSO period (Figure 11D), however, the opposite happens (the plume is closer to the southern coast) and there is a negative pattern in the region of the low estuary of the Río de la Plata (blue region), showing the high variability of sediment concentration in the region. When analysing the seasonal and interannual behaviour of the suspended material, Dogliotti et al. (2016) also showed a high temporal variability in the lower Río de la Plata estuary.

For the third mode (Figures 11E and 11F), the SSC in the neutral period and the period under the ENSO effect represent only 8% of the variability. A well-defined pattern in practically the entire south and north coast of the Río de la Plata can be identified for the two analysed periods (Figures 11E and 11F). For the Patos Lagoon this third mode shows a negative pattern (great variability) for the main effluents, both in the neutral period and in the period under the ENSO effect; this is a sporadic event for the region, since the region is characterised by the exportation of suspended sediment to the inner Patos Lagoon (Toldo et al., 2006).

To investigate the behaviour of the suspended sediment in the water column, similar EOF analyses were carried out for longitudinal and transversal sections at the mouth of both systems (Figures 12, 13, 14, and 15). For the longitudinal section of the Río de la Plata (Figure 12), the first three EFOs (49%, 28%, and 4%) account for 87% of the variability of the SSC during the neutral period (Figures 12A, 12C, and 12E), while during the ENSO period the first three modes account for approximately 93% of the variability (Figures 12B, 12D, and 12F). Results indicate the presence of suspended sediments throughout the intermediate region (mainly near Punta Piedras; Figure 1), and this was already stated by Moreira et al. (2013) and Dogliotti et al. (2016), who related this spatial distribution pattern to the fluvial discharge of the main tributaries of the Río de la Plata and the resuspension of sediment caused by the tides. On the other hand, in the region of the upper estuary, it is possible to perceive a high variability in the SSC (blue region), due to
the influence of the main effluents of the Río de la Plata (the Paraná River and Uruguay River) (Guerreiro et. al., 1997; Moreira et. al., 2010; Dogliotti et. al., 2016).

At the mouth of the Río de la Plata (Figure 13), the first EOF analysis along the transversal profile during the neutral period suggests that the suspended sediment is exported to the coastal zone through to the southern side of the estuary 48% of the time coming from the Paraná River (Figure 13A), and through the northern margin 32% of the time coming from the Uruguay River (Figure 13C). During the ENSO period the contribution from the Paraná River represents the suspended sediment variability 77% of the time, while the Uruguay River accounts for only 12% of the variability, evidencing the influence of ENSO in the two main effluents of the La Plata River, as stated by Berbery and Barros (2002), García-Rodríguez et. al. (2014), and Dogliotti et. al. (2016).

Although the Uruguay and Paraguay rivers contribute approximately 97% of the continental discharge reaching the Río de la Plata and are subjected to ENSO effects, it is worth mentioning that the Bermejo River is responsible for 70% of the suspended sediment exported to the Río de la Plata estuary, and it is not significantly affected by ENSO cycles. Thus, considering that the amount of suspended sediment arriving in the Río de la Plata estuary does not change significantly due to the La Niña effect present during the 2008-2009 ENSO period, the main factor responsible for the calculated concentration of suspended sediment is the availability of continental water. As a result, the large amount of suspended sediment exported to the adjacent coastal region is the result of low continental discharge during this period.

When analysing the transversal profiles at the mouth of the Patos Lagoon (Figure 14), a floating plume which turns to the SE end of the profile (leaving the estuary) can be observed. This dominant pattern, represented by the first EOF mode (Figures 14A, 14B) during the neutral and ENSO periods (representing 93 and 92% of the suspended sediment variability, respectively), can be generated by the combination of fluvial discharges and the action of the north quadrant wind during most of the simulated period, and was also observed by Marques et. al. (2009; 2010b). The second and the third EOF modes (Figures 14C, 14D, 14E, and 14F) presented small variability for both periods.

The longitudinal profiles at the mouth of the Patos Lagoon (Figure 15), on the other hand, indicate a feature similar to a floating plume (hypopycnal) as a result of the bathymetry constraining the low-density waters closer to the surface. This dominant pattern is represented by the first EOF mode (Figures 15A and 15B) during the neutral and ENSO periods (representing 73 and 70% of the suspended sediment variability, respectively). The second EOF mode highlights the presence of higher SSC in the main channel (southwest limit of the profile), representing 12 and 13% of the variability during the neutral (Figure 15C) and the ENSO periods (Figure 15D), respectively. The third EOF mode represents only 6% of the variability observed in the simulated period (Figures 15E and 15F), where negative values (blue areas) indicate low SSC inside the Patos Lagoon access channel as a result of south quadrant winds (Möller et. al., 2001; Castelão and Möller, 2006; Marques et. al., 2009; 2010a).
## 5.3. Temporal Variability of Coastal Plumes

The temporal variability of the suspended sediment coastal plumes during both studied periods (Figures 16-19) showed temporal scales from days to years for both the Río de la Plata mouth and the Patos Lagoon mouth when related to wind and freshwater discharge. The action of the wind is observed in cycles shorter than 15 days, which is related to the passage of weather fronts over the areas and is in accordance with the synoptic time scales observed by Möller et. al. (1996; 2001), Guerrero et. al. (1997), Simionato et. al. (2005) and Simionato et. al. (2007). The discharge however is related to the SSC on time scales from one month to one year covering intraseasonal, seasonal and interannual cycles associated with the precipitation patterns over the regions, which is in agreement with Acha et. al. (2008) and Marques et. al. (2010a).

## 5.4. Behavior of suspended sediment on the Inner Shelf

The SSC throughout the inner shelf (Figures 20) show a well-defined pattern between fluvial discharge and SSC in the Patos Lagoon, with the higher SSC occurring during the winter, when the discharge is higher (Marques et. al., 2009). In the Río de la Plata this relation presents a time-lag between the flow and SSC (Möller et. al., 1998; Marques et. al., 2010; Dogliotti et. al., 2016). As mentioned earlier, this delay is related to the distance between the effluents of the Río de la Plata and the location chosen to generate the diagram (transect T6 - Figure 1), as observed by Guerrero et. al. (1997) and Dogliotti et. al. (2016).

As for the interannual variations, there is a difference between the neutral years and the years affected by the ENSO phenomena. The effects on the suspended sediment distribution on the inner shelf of La Niña during 2008 and those of El Niño occurring at the end of 2009 were evident (Figure 20B), but not sufficient to affect the SSC observed on the inner shelf during the neutral period (Figure 20A). These results contradict the findings made by Dogliotti et. al. (2016), where the authors observed that during the La Niña years there was an increase in the concentration of suspended material compared to the El Niño years. This difference may be due to the location of the T6 profile (Figure 1).

When looking at the variability associated with the SSC on the inner shelf, the first two modes of the EOF analyses (Figure 21) represent approximately 75-76% of the sediment distribution observed during the simulated periods, respectively. The first EOF modes (Figures 21A and 21B), indicate a very similar distribution of suspended sediment on the inner shelf, with a well-defined pattern located in a small coastal strip, responding to the seasonal variation of SSC in the region (Figure 8). For the second EOF mode the suspended sediment variability indicates the influence of the north quadrant winds in the dynamics of the Patos Lagoon and the Río de la Plata plumes towards the south, as was also observed by Marques et. al. (2010b) and Simionato et. al. (2005). Thus, the wind becomes an important force on the internal platform, since the sediment moves away from the dynamic influence of the flow, both from the Río de la Plata and from the Patos Lagoon (Soares et. al., 2007a).
## 6. Conclusion

The Southwest Atlantic Inner Shelf is a region influenced by continental discharge and local wind. This influence is dominant in the suspended sediment transport process of the region, which is affected significantly from seasonal and interannual variations promoted by the ENSO cycles, mainly in its fluvial discharge regime. The Río de la Plata is the major exporter of suspended sediment in the region, with an approximate rate of $1.2 \times 10^8$ tons/year in a neutral period. For years under the ENSO influence, this rate rises to $3.0 \times 10^8$ tons/year. The Patos Lagoon also contributes to the increase in SSC in the coastal region ($1.25 \times 10^7$ tons/years without ENSO effect and $1.35 \times 10^7$ tons/years with ENSO), but on a smaller scale compared to the La Plata River.

Regarding spatial variability in neutral years, there is a strongly defined SSC pattern in the Punta Piedras region, as well as on the south coast of the La Plata estuary, while on the north coast the sediment behaviour presents greater variability due to the influence of the Uruguay River on the Uruguayan coast. In the periods affected by ENSO, the SSC shows low variability in practically all sectors of the estuary, evidencing the strong impact of the flow of the river on the distribution of sediments in the estuary. For the Patos Lagoon, there was no great difference in the spatial variability of sediments in the region. A well-defined pattern is observed in the region influenced by the Guaíba River, one of the principal suppliers of sediment to the Patos Lagoon.

Regarding spatial variability, results at the mouth of the rivers confirmed that in the Río de la Plata the plume behaves with homopycnal characteristics (affecting the whole water column), and the sediment is preferentially distributed toward the southern coast of the estuary, as a result of the Paraná River contribution. In the Patos Lagoon, the plume is classified as hypopycnal and tends to migrate southwards mainly due to the action of the predominant northeast wind.

As for temporal variability, the fluvial discharge interacts with the SSC on a seasonal up to an interannual scale, while the wind contributes to the SSC's variability on a synoptic time scale. Upon arriving at the inner shelf, the suspended sediment preferentially occupies a narrow coastal strip close to the shore. The wind, in turn, gains importance on the platform, as the sediment moves away from the influence of the flow, both from the Río de la Plata and the Patos Lagoon.

## 7. Work limitations and future projection

Because the present study does not consider the effect of waves in the region, it would be very relevant to use a wave model to analyse their contribution to this process. According to the literature (Santoro et. al., 2015), the waves are responsible for the remobilization of the bottom sediments back toward the water column, thus being important for the SSC distribution and behaviour on the internal platform.
Another point to be highlighted is the period we chose to analyse the ENSO effects. During 2008 and 2009, the influence of La Niña was noticed most of the time, and El Niño only toward the end of the period. However, the presence of the two distinct effects within a short period of time made the analysis of the results very difficult. The most appropriate thing would be to analyse a period completely influenced by only one of the effects, either El Niño or La Niña.

Finally, due to the lack of a long SSC time series in the analysed periods, the values used as SSC in the effluents were annual averages used by other authors who had previously studied the same region. Despite the calibration exercises, which presents statistically satisfactorily results, the estimated values may be slightly different from true values.

**Funding:** This research was partially funded by the SUNSET project from CAPES nº 88881.192857/2018-01, edict COFECUB 382/2019.

**Acknowledgments:** The authors would like to thank CAPES (Coordination for Personal Improvement of Personnel) for sponsoring the doctoral scholarship of the first author (P.V.L.) through the Graduate Program in Oceanography (PPGO). We are also grateful to Team LOCOSTE (Laboratory of Coastal and Estuarine Oceanography) and team METHIS (Modélisation Expérimentale et Télédétection en Hydrodynamique Sédimentaire) for their support during this research, to Osmar Möller and to the FREPLATA project for providing the in situ data used for calibration and validation of the TELEMAC-3D model.

**Conflicts of interest:** The authors declare that there are no conflicts of interest.

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<figure><img src="image_1.png" /><figcaption>Figure 1 - The study region defined between the latitudes of 28°S (Santa Marta Cape) and 38°S (Mar Del Plata). Blue dots represent the main effluents from the Patos Lagoon (Guaíba River, Camaquã River, and São Gonçalo Channel), green dots show important regions in the study area and black dots represent the points from where model results were extracted for the wavelet analysis (P1 and P2). T shows the transects where model results were extracted from (T1, T2, T3, T4, and T5) for empirical orthogonal function (EOF) analyses. The white lines represent the main effluents of the Río de la Plata (River Bermejo, River Paraná, and River Uruguay)</figcaption></figure>
<figure><img src="image_2.png" /><figcaption>Figure 2 – Computational domain and numerical mesh used for the simulations. (A) Initial and boundary conditions prescribed in the model. The points where the time series of salinity (S1 and S2), current velocity (V1 and V2), and water level (L1 and L2) prescribed as boundary conditions were extracted are also shown. (B) Zoom view of the Patos Lagoon mesh and (C) that of the Río de la Plata mesh.</figcaption></figure>
<figure><img src="image_3.png" /></figure>

Figure 3 - Comparison between measured and calculated time series of current velocity (A) at the surface and (B) at the bottom of the access channel to the Port of Rio Grande (see Figure 2B for location).

<figure><img src="image_4.png" /></figure>

Figure 42 - Comparison between the measured and calculated time series of free surface elevation at (A) Cassino Beach and (B) Rio La Plata.
<figure><img src="image_5.png" /></figure>

<figure><img src="image_6.png" /></figure>

<figure><img src="image_7.png" /></figure>

<figure><img src="image_8.png" /></figure>

Figure 5 - Comparison between the measured (red line) and calculated (blue line) salinity and current velocity time series at (A) the surface and (B) the bottom.

<figure><img src="image_9.png" /></figure>

Figure 6 - Comparison between the calculated suspended sediment concentration (blue line) and the measured data (red line) in (A) the lower, (B) middle and (C) upper estuary in Rio de La Plata River, between the 24th of June to the 16th of December, 2010.
<figure><img src="image_10.png" /></figure>

Figure 7 – Left panels: Suspended sediment concentrations (SSC) at the surface obtained with the numerical model (A, D) and from remote sensing (B, D) on the 6th of February, 2008 (top) and the 17th of September, 2008 (bottom), respectively. Right panels: SSC at the surface extracted from the respective longitudinal (top panels) and transversal (bottom panels) profiles (C, F).
Neutral Period

<figure><img src="image_11.png" /></figure>

ENSO Period

<figure><img src="image_12.png" /></figure>

<figure><img src="image_13.png" /></figure>

<figure><img src="image_14.png" /></figure>

Figure 8 – Seasonal average suspended sediment concentrations (SSC) for the study region during winter (A) and summer (C) in the neutral period (2005-2006), and during winter (B) and summer (D) in the period experienced ENSO conditions (2008-2009).

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<figure><img src="image_15.png" /></figure>

Figure 9 – Average suspended sediment concentrations (SSC) (left column) and their averaged normal velocities (red represents outflow and blue is inflow) and the transversal velocity components (vectors; right column) along transects made across the Río de la Plata (T2) and the Patos Lagoon (T4), respectively, during the neutral period (2005-2006) and the period influenced by the ENSO cycle (2008-2009). The white dotted line indicates the position of the Patos Lagoon mouth. The colour scale for SSC has not been standardised for easy viewing, and for the La Plata River, the red colour indicates sediment concentrations ranging between 50 and 200 mg/l.
Neutral Period

<figure><img src="image_16.png" /></figure>

<figure><img src="image_17.png" /></figure>

<figure><img src="image_18.png" /></figure>

ENSO Period

<figure><img src="image_19.png" /></figure>

<figure><img src="image_20.png" /></figure>

<figure><img src="image_21.png" /></figure>

Figure 10 – Mass flux (red indicates export and blue import) of suspended sediment and time series of the cumulative mass flux into the cross-section in the Patos Lagoon mouth (T4) during (A) a neutral period (2005-2006) and (B) a period under the influence of the ENSO cycle (2008-2009), and in the cross-section of the Río de la Plata (T2) during (C) a neutral period (2005-2006) and (D) a period under the influence of the ENSO cycle (2008-2009). The South Oscillation Index (SOI) during (E) a neutral period (2005 - 2006), and (F) a period under the influence of the ENSO cycle (2008-2009).
Neutral Period

<figure><img src="image_22.png" /></figure>

ENSO Period

<figure><img src="image_23.png" /></figure>

<figure><img src="image_24.png" /></figure>

<figure><img src="image_25.png" /></figure>

<figure><img src="image_26.png" /></figure>

<figure><img src="image_27.png" /></figure>

Figure 11 – The first three empirical orthogonal function (EOF) modes of suspended sediment concentration (SSC) across the domain for the neutral period (2005-2006) (left column) and for the period under the influence of an ENSO cycle (2008-2009) (right column). The red areas (positive values) represent the regions where the concentration of the suspended sediment has a high spatial pattern, in contrast, the blue areas (negative values) represent the regions where the SSC has a low spatial pattern.
<figure><img src="image_28.png" /></figure>

Figure 12 – The first three empirical orthogonal function (EOF) modes of suspended sediment concentration (SSC) along the longitudinal section of the Río de la Plata (T1) for the neutral period (2005-2006) (left column) and for the period under the influence of an ENSO cycle (2008-2009) (right column). The dotted lines represent the position of the mouth in longitudinal view. The red areas (positive values) represent the regions where the concentration of the suspended sediment has a high spatial pattern, and in contrast, the blue areas (negative values) represent the regions where the SSC has a low spatial pattern.

<figure><img src="image_29.png" /></figure>

Figure 13 – The first three modes of the empirical orthogonal function (EOF) analysis of suspended sediment concentrations (SSC), along the transversal profile of the Río de la Plata (T2) for the neutral period (2005-2006) (left column) and for the period under the influence of an ENSO cycle (2008-2009) (right column).
column). The red areas (positive values) represent the regions where the concentration of the suspended sediment has a high spatial pattern. In contrast, the blue areas (negative values) represent the regions where the SSC has a low spatial pattern.

<figure><img src="image_30.png" /></figure>

Figure 143 – The first three modes of the empirical orthogonal function (EOF) analysis of suspended sediment concentrations (SSC) along the transversal profile of the Patos Lagoon mouth (T4) for the neutral period (2005-2006) (left column) and the period under the influence of an ENSO cycle (2008-2009) (right column). The dotted lines represent the position of the mouth in longitudinal view. The red areas (positive values) represent the regions where the concentration of the suspended sediment has a high spatial pattern, and in contrast, the blue areas (negative values) represent the regions where the SSC has a low spatial pattern.
<figure><img src="image_31.png" /></figure>

Figure 15 – The first three modes of the empirical orthogonal function (EOF) analysis of suspended sediment concentrations (SSC) on the longitudinal profile at the Patos Lagoon mouth (T5) for the neutral period (2005-2006) (left column) and for the period under the influence of an ENSO cycle (2008-2009) (right column). The dotted lines represent the position of the Patos Lagoon mouth. The red areas (positive values) represent the regions where the concentration of the suspended sediment has a high spatial pattern; in contrast, the blue areas (negative values) represent the regions where the SSC has a low spatial pattern.
<figure><img src="image_32.png" /><figcaption>Figure 16 – (A) Time series of the Río de la Plata discharge (orange) and suspended sediment concentrations (SSC; blue) for the period 2005-2006 (green dot - Figure 1). (B) Cross-spectrum of local energy using Mexican hat wavelet analyses where the contour lines enclose regions with a 95% confidence interval. The dashed line indicates the region of influence where the border effects become important. (C) Average global power spectrum where the dashed line represents the 95% confidence level. (D) Time series of the Río de la Plata discharge (orange) and suspended sediment concentrations (blue) for the period 2008-2009 (green dot; Figure 1). (E) Cross-spectrum of local energy using the Mexican hat wavelet analysis; the contour lines involve regions with a 95% confidence interval and the dashed line indicates the region of influence where the border effects become important. (F) Average global power spectrum; the dashed line represents the 95% confidence level.</figcaption></figure>
<figure><img src="image_33.png" /><figcaption>Figure 17 – (A) Time series of fluvial discharge from the Patos Lagoon (red) and sediment concentrations (blue) for the period 2005-2006 (green dot - Figure 1). (B) Cross-spectrum of local energy using the Mexican hat wavelet analysis. The contour lines enclose regions with a 95% confidence interval and the dashed line indicates the influence with which the border effects become important. (C) Global spectrum indicating the average time of each cycle; the dashed line represents the 95% confidence level. (D) Time series of fluvial discharge from the Patos Lagoon (red) and sediment concentrations (blue) for the period 2008-2009 (green dot - Figure 1). (E) Cross-spectrum of local energy using the Mexican hat wavelet analysis; the contour lines involve regions with a 95% confidence interval and the dashed line indicates the influence with which the border effects become important. (F) Global spectrum indicating the average time each cycle takes place over. The dashed line represents the 95% confidence level.</figcaption></figure>
<figure><img src="image_34.png" /><figcaption>Figure 18 – (A) Time series of wind intensity (orange) and suspended sediment concentrations (SSC) in the Río de la Plata (blue) for the period 2005-2006 (green dot - Figure 1). (B) Cross-spectrum of local energy between the time series using Morlet wavelet analysis. The contour lines enclose regions with a 95% confidence interval. The dashed line indicates the region of influence where the border effects become important. (C) Average global power spectrum where the dashed line represents the 95% confidence level. (D) Time series of wind intensity (orange) and SSC of the Río de la Plata (blue) for the period 2008-2009 (green dot - Figure 1). (E) Cross-spectrum of local energy between the time series using Morlet wavelet; the contour lines involve regions with a 95% confidence interval and the dashed line indicates the region of influence where the border effects become important. (F) Average global power spectrum, where the dashed line represents the 95% confidence level.</figcaption></figure>
<figure><img src="image_35.png" /><figcaption>Figure 19 – (A) Time series of wind intensity (orange) and suspended sediment concentrations (SSC) in the Patos Lagoon (blue) for the period 2005-2006 (green dot - Figure 1). (B) Cross-spectrum of local energy between the series using Morlet wavelet; the contour lines enclose regions with a 95% confidence interval and the dashed line indicates the region of influence where the border effects become important. (C) Average global power spectrum; the dashed line represents the 95% confidence level. (D) Time series of wind intensity (red) and SSC in the Patos Lagoon (blue) for the period 2008-2009 (green dot - Figure 1). (E) Cross-spectrum of local energy between series using Morlet wavelet analysis; the contour lines involve regions with a 95% confidence interval and the dashed line indicates the influence with which the border effects become important. (F) Average global power spectrum; the dashed line represents the 95% confidence level.</figcaption></figure>
<figure><img src="image_36.png" /><figcaption>Figure 20 – (A) Time series of discharge from the Río de la Plata for the period influenced by the ENSO cycle. (B) Hovmöller diagram elaborated with the time series of suspended sediment concentrations (SSC) extracted along transect T6. SW is the limit of the closest transect to the Río de la Plata and NE the closest limit to the Patos Lagoon. (C) Time series of discharge in the north of the Patos Lagoon for the period influenced by the ENSO cycle.</figcaption></figure>
2005 – 2006

<figure><img src="image_37.png" /></figure>

<figure><img src="image_38.png" /></figure>

<figure><img src="image_39.png" /></figure>

2008 – 2009

<figure><img src="image_40.png" /></figure>

<figure><img src="image_41.png" /></figure>

<figure><img src="image_42.png" /></figure>

Figure 21 – The first three empirical orthogonal function (EOF) modes of suspended sediment concentrations (SSC) along the T6 transect on the internal platform for the neutral period (2005-2006) (left column) and for the period under the influence of an ENSO cycle (2008-2009) (column right). The red areas (positive values) represent the regions where the concentration of the suspended sediment has a high spatial pattern and in contrast, the blue areas (negative values) represent the regions where the concentration of the suspended sediment has a low spatial pattern.

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## Appendix A - Details about the simulation and model set-up

The analysis of the behaviour and variability of the dynamics of sediments in suspension for the Southwest Atlantic Inner Continental Shelf was performed with numerical modelling techniques, using the TELEMAC 3D model. Six hydrodynamic simulations were carried out, with a duration of 730 days for the years 2005 to 2006, and 2008 to 2009, with the following configuration:

<table><caption>Table A1 - Set-up of the simulations</caption><thead><tr><th>Simulation</th><th>Description</th><th>La Plata<br>Discharge</th><th>Patos<br>Lagoon<br>Discharge</th><th>2005-<br>2006</th><th>2008-<br>2009</th></tr></thead><tbody><tr><td>SIM 1</td><td>Model<br>forced with<br>all physical<br>forces for<br>the period<br>from 2005<br>to 2006;</td><td>X</td><td>X</td><td>X</td><td></td></tr><tr><td>SIM 2</td><td>Forced<br>model with<br>all physical<br>forces for<br>the period<br>from 2008<br>to 2009;</td><td>X</td><td>X</td><td></td><td>X</td></tr></tbody></table>
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The methodological steps developed in this work are presented in Figure A1, and detailed below.

<figure><img src="image_43.png" /><figcaption>Figure A1 - Summary of the methodological steps used in this work.</figcaption></figure>

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Appendix B - Initial and Boundary Conditions

<figure><img src="image_44.png" /><figcaption>Figure B1 - Salinity fields used as an initial condition in the surface layer of the model in January 2005 (A) and January 2008 (B).</figcaption></figure>

<figure><img src="image_45.png" /><figcaption>Figure B2 - Data prescribed as the boundary condition at the ocean boundary at points L1 and L2 (sea surface elevation) (A), V1 and V2 (current velocity) (B), and S1 and S2 (salinity) (C) for the period 2005-2006. The boundary conditions for 2008-2009 are not presented.</figcaption></figure>
<figure><img src="image_46.png" /></figure>

Figure B3 - Time series of the freshwater discharge from the Guaíba River, Camaquã River, São Gonçalo Channel and the Rio de la Plata for both studied periods (2005-2006 and 2008-2009).

Figure B4 shows the frequency distribution of the time series of wind intensity for the simulated periods (2005-2006 and 2008-2009), indicating that the wind velocity varied between 0.19 m/s and 20.3 m/s, with the average around 5.63 m/s for the simulation between the years 2005-2006, and with a predominant northeast direction. The strongest winds, however, are from the southwest. For the simulation between 2008-2009 the wind varied between 0.04 m/s and 7.32 m/s, with a predominant northeast direction and stronger winds in the southeast direction.

<figure><img src="image_47.png" /></figure>

Figure B4 - Wind Rose for the frequency distribution of the time series of wind intensity and direction, for the years 2005-2006 (A) and 2008-2009 (B).
<figure><img src="image_48.png" /><figcaption>Figure B5 - Time series of intensity used as a superficial forcing in the simulation.</figcaption></figure>

<table><caption>Table B1 - Summary of the sources of data prescribed in the initial and boundary conditions.</caption><thead><tr><th>Forcing</th><th>Data Source</th></tr></thead><tbody><tr><td>Continental Discharge</td><td>Guaiba and Camaquã - (National Water Agency);<br>São Gonçalo - Rating Curve Method<br>(Oliveira et al., 2015);<br>La Plata - Naval Hydrography Service of Argentina</td></tr><tr><td>Wind</td><td>ECMWF - ERA Interim</td></tr><tr><td>Tide</td><td>TPXO</td></tr><tr><td>Velocity</td><td>TPXO</td></tr><tr><td>Level</td><td>TPXO</td></tr><tr><td>Salinity</td><td>HYCOM + NCODA 1/12°</td></tr><tr><td>Suspended Sediment</td><td>Fine Silt</td></tr><tr><td>Bottom Sediment</td><td>Fine Silt</td></tr><tr><td>Suspended Sediment Concentration</td><td>Patos Lagoon - Marques et al., 2010<br>La Plata - Moreira and Simionato, 2019</td></tr></tbody></table>
The calibration and validation of the model consist of comparisons between model results and in situ data for the same period and location, which are quantified based on statistical analyses such as the root mean square error (RMSE) and the Relative Mean Absolute Error (RMAE) (Janssen et al, 1997; Lalbeharry, 2001; Lalbeharry et al., 2001; Wastra et al., 2001; 2004; Bidlot et al., 2002; Sutherland et al., 2004).

The Root Mean Square Error (RMSE) determines the magnitude of the mean square error module (i.e., without considering if the number is negative or positive) between the observations and the values calculated by the model, according to the following mathematical expression:

$$RMSE = \sqrt{\frac{\sum_{i=1}^{n} (m_i - o_i)^2}{n}} \qquad (1)$$

Where, *m* is a model result, *o* is measured or observed data point and *n* is the number of points.

The RMAE indicates the average relative error between the measurements and the results obtained in the model, which was used to quantify the quality of the results found in the best calibration experiment and in the validation tests of the TELEMAC mode (Wastra et al., 2001). The average absolute value of the observed values and the modelled values are given by:

$$\langle |X| \rangle = \frac{1}{n} \sum_{i=1}^{n} |X_i| \qquad (2)$$

$$\langle |Y| \rangle = \frac{1}{n} \sum_{i=1}^{n} |Y_i| \qquad (3)$$

Where *X* are observed values, and *Y* are modelled values, with each of the values being in the same spatial and temporal position. These values can be scalar (wave height or water level) or vectors (currents). The angular parenthesis expresses the mean and, respectively, the *X* and *Y* modules. Similarly, the mean absolute error (MAE) is given by:

$$MAE = \langle |Y - X| \rangle \qquad (4)$$

The quality of the modelling can be assessed by the RMAE value, as follows:
$$RMAE = \frac{\langle |Y - X| \rangle}{\langle |X| \rangle} = \frac{MAE}{\langle |X| \rangle} \qquad (5)$$

<table><caption>Table C1. Rating scale for the relative mean absolute error (RMAE) (Sutherland et al., 2004 and Walstra et al., 2001)</caption><thead><tr><th>Qualification</th><th>Excellent</th><th>Good</th><th>Reasonable</th><th>Poor</th><th>Bad</th></tr></thead><tbody><tr><th>RMAE</th><td>≤0.2</td><td>0.2 – 0.4</td><td>0.4 – 0.7</td><td>0.7 – 1.0</td><td>> 1.0</td></tr></tbody></table>
Appendix D - Calibration tests carried out for the hydrodynamic model and respective errors when comparing with data from the Patos Lagoon and the La Plata River.

Table D1. Parameters used in the calibration of the model, with the respective RMAE results for each of the tests (Patos Lagoon and Río de la Plata level). The results of the RMAE for the test with the best approximation in relation to the measured values are marked in bold.

<table><thead><tr><th>Test</th><th>Wind Influence Coefficient</th><th>Vertical Turbulence</th><th>Horizontal Turbulence</th><th>Bottom Friction Laws</th><th>Friction Coefficient</th><th>RMAE Cassino Beach</th><th>RMAE La Plata River</th></tr></thead><tbody><tr><td>01</td><td>3x10<sup>-6</sup></td><td>K-ε</td><td>Smagorinsky</td><td>Manning</td><td>0.01</td><td>0.1452</td><td>0.2993</td></tr><tr><td>02</td><td>3x10<sup>-6</sup></td><td>K-ε</td><td>Smagorinsky</td><td>Manning</td><td>0.02</td><td>0.3573</td><td>0.2478</td></tr><tr><td>03</td><td>3x10<sup>-6</sup></td><td>K-ε</td><td>Smagorinsky</td><td>Manning</td><td>0.03</td><td>0.3919</td><td>0.2612</td></tr><tr><td>04</td><td>3x10<sup>-6</sup></td><td>K-ε</td><td>Smagorinsky</td><td>Manning</td><td>0.04</td><td>0.2547</td><td>0.3641</td></tr><tr><td>05</td><td>3x10<sup>-6</sup></td><td>K-ε</td><td>K-ε</td><td>Manning</td><td>0.01</td><td>0.1987</td><td>0.2998</td></tr><tr><td>06</td><td>3x10<sup>-6</sup></td><td>K-ε</td><td>K-ε</td><td>Manning</td><td>0.02</td><td>0.1825</td><td>0.2664</td></tr><tr><td>07</td><td>3x10<sup>-6</sup></td><td>K-ε</td><td>K-ε</td><td>Manning</td><td>0.03</td><td>0.2564</td><td>0.2334</td></tr><tr><td>08</td><td>3x10<sup>-6</sup></td><td>K-ε</td><td>K-ε</td><td>Manning</td><td>0.04</td><td>0.2417</td><td>0.1785</td></tr><tr><td>09</td><td>3x10<sup>-6</sup></td><td>Prandlt</td><td>Smagorinsky</td><td>Manning</td><td>0.01</td><td>0.3214</td><td>0.4568</td></tr><tr><td><strong>10</strong></td><td><strong>3x10<sup>-6</sup></strong></td><td><strong>Prandlt</strong></td><td><strong>Smagorinsky</strong></td><td><strong>Manning</strong></td><td><strong>0.02</strong></td><td><strong>0.1521</strong></td><td><strong>0.1801</strong></td></tr><tr><td>11</td><td>3x10<sup>-6</sup></td><td>Prandlt</td><td>Smagorinsky</td><td>Manning</td><td>0.03</td><td>0.1625</td><td>0.3698</td></tr><tr><td>12</td><td>3x10<sup>-6</sup></td><td>Prandlt</td><td>Smagorinsky</td><td>Manning</td><td>0.04</td><td>0.1847</td><td>0.3667</td></tr><tr><td>13</td><td>3x10<sup>-6</sup></td><td>Prandlt</td><td>K-ε</td><td>Manning</td><td>0.01</td><td>0.1965</td><td>0.3412</td></tr><tr><td>14</td><td>3x10<sup>-6</sup></td><td>Prandlt</td><td>K-ε</td><td>Manning</td><td>0.02</td><td>0.1752</td><td>0.1987</td></tr><tr><td>15</td><td>3x10<sup>-6</sup></td><td>Prandlt</td><td>K-ε</td><td>Manning</td><td>0.03</td><td>0.3412</td><td>0.3438</td></tr><tr><td>16</td><td>3x10<sup>-6</sup></td><td>Prandlt</td><td>K-ε</td><td>Manning</td><td>0.04</td><td>0.2987</td><td>0.3360</td></tr><tr><td>17</td><td>3x10<sup>-6</sup></td><td>Tsanis</td><td>Smagorinsky</td><td>Manning</td><td>0.01</td><td>0.3024</td><td>0.3978</td></tr><tr><td>18</td><td>3x10<sup>-6</sup></td><td>Tsanis</td><td>Smagorinsky</td><td>Manning</td><td>0.02</td><td>0.4125</td><td>0.3682</td></tr><tr><td>19</td><td>3x10<sup>-6</sup></td><td>Tsanis</td><td>Smagorinsky</td><td>Manning</td><td>0.03</td><td>0.4187</td><td>0.3769</td></tr><tr><td>20</td><td>3x10<sup>-6</sup></td><td>Tsanis</td><td>Smagorinsky</td><td>Manning</td><td>0.04</td><td>0.3657</td><td>0.3572</td></tr><tr><td>21</td><td>3x10<sup>-6</sup></td><td>Tsanis</td><td>K-ε</td><td>Nikuradse</td><td>1x10<sup>-5</sup></td><td>0.4126</td><td>0.4409</td></tr><tr><td>22</td><td>3x10<sup>-6</sup></td><td>Tsanis</td><td>K-ε</td><td>Nikuradse</td><td>2x10<sup>-5</sup></td><td>0.3952</td><td>0.4215</td></tr><tr><td>24</td><td>3x10<sup>-6</sup></td><td>Tsanis</td><td>K-ε</td><td>Nikuradse</td><td>3x10<sup>-5</sup></td><td>0.3458</td><td>0.4712</td></tr><tr><td>25</td><td>3x10<sup>-6</sup></td><td>Tsanis</td><td>K-ε</td><td>Nikuradse</td><td>4x10<sup>-5</sup></td><td>0.2147</td><td>0.4412</td></tr></tbody></table>
<table><tr><td>26</td><td>3x10<sup>-6</sup></td><td>K-ε</td><td>Smagorinsky</td><td>Nikuradse</td><td>1x10<sup>-5</sup></td><td>0.1452</td><td>0.4181</td></tr><tr><td>27</td><td>3x10<sup>-6</sup></td><td>K-ε</td><td>Smagorinsky</td><td>Nikuradse</td><td>2x10<sup>-5</sup></td><td>0.3878</td><td>0.4571</td></tr><tr><td>28</td><td>3x10<sup>-6</sup></td><td>K-ε</td><td>Smagorinsky</td><td>Nikuradse</td><td>3x10<sup>-5</sup></td><td>0.2478</td><td>0.2347</td></tr><tr><td>29</td><td>3x10<sup>-6</sup></td><td>K-ε</td><td>Smagorinsky</td><td>Nikuradse</td><td>4x10<sup>-5</sup></td><td>0.1698</td><td>0.4516</td></tr><tr><td>30</td><td>3x10<sup>-6</sup></td><td>K-ε</td><td>K-ε</td><td>Nikuradse</td><td>1x10<sup>-5</sup></td><td>0.4215</td><td>0.3219</td></tr><tr><td>31</td><td>3x10<sup>-6</sup></td><td>K-ε</td><td>K-ε</td><td>Nikuradse</td><td>2x10<sup>-5</sup></td><td>0.4987</td><td>0.3315</td></tr><tr><td>32</td><td>3x10<sup>-6</sup></td><td>K-ε</td><td>K-ε</td><td>Nikuradse</td><td>3x10<sup>-5</sup></td><td>0.3651</td><td>0.2669</td></tr><tr><td>33</td><td>3x10<sup>-6</sup></td><td>K-ε</td><td>K-ε</td><td>Nikuradse</td><td>4x10<sup>-5</sup></td><td>0.3412</td><td>0.2033</td></tr><tr><td>34</td><td>3x10<sup>-6</sup></td><td>Prandlt</td><td>Smagorinsky</td><td>Nikuradse</td><td>1x10<sup>-5</sup></td><td>0.2981</td><td>0.2155</td></tr><tr><td>35</td><td>3x10<sup>-6</sup></td><td>Prandlt</td><td>Smagorinsky</td><td>Nikuradse</td><td>2x10<sup>-5</sup></td><td>0.2786</td><td>0.2029</td></tr><tr><td>36</td><td>3x10<sup>-6</sup></td><td>Prandlt</td><td>Smagorinsky</td><td>Nikuradse</td><td>3x10<sup>-5</sup></td><td>0.4127</td><td>0.9785</td></tr><tr><td>37</td><td>3x10<sup>-6</sup></td><td>Prandlt</td><td>Smagorinsky</td><td>Nikuradse</td><td>4x10<sup>-5</sup></td><td>0.4579</td><td>0.2049</td></tr><tr><td>38</td><td>3x10<sup>-6</sup></td><td>Prandlt</td><td>K-ε</td><td>Nikuradse</td><td>1x10<sup>-5</sup></td><td>0.3217</td><td>0.3284</td></tr><tr><td>39</td><td>3x10<sup>-6</sup></td><td>Prandlt</td><td>K-ε</td><td>Nikuradse</td><td>2x10<sup>-5</sup></td><td>0.3258</td><td>0.4569</td></tr><tr><td>40</td><td>3x10<sup>-6</sup></td><td>Prandlt</td><td>K-ε</td><td>Nikuradse</td><td>3x10<sup>-5</sup></td><td>0.2569</td><td>0.5214</td></tr><tr><td>41</td><td>3x10<sup>-6</sup></td><td>Prandlt</td><td>K-ε</td><td>Nikuradse</td><td>4x10<sup>-5</sup></td><td>0.1987</td><td>0.4396</td></tr><tr><td>42</td><td>3x10<sup>-6</sup></td><td>Tsanis</td><td>Smagorinsky</td><td>Nikuradse</td><td>1x10<sup>-5</sup></td><td>0.2356</td><td>0.4789</td></tr><tr><td>43</td><td>3x10<sup>-6</sup></td><td>Tsanis</td><td>Smagorinsky</td><td>Nikuradse</td><td>2x10<sup>-5</sup></td><td>0.2147</td><td>0.2369</td></tr><tr><td>44</td><td>3x10<sup>-6</sup></td><td>Tsanis</td><td>Smagorinsky</td><td>Nikuradse</td><td>3x10<sup>-5</sup></td><td>0.2987</td><td>0.4213</td></tr><tr><td>45</td><td>3x10<sup>-6</sup></td><td>Tsanis</td><td>Smagorinsky</td><td>Nikuradse</td><td>4x10<sup>-5</sup></td><td>0.4126</td><td>0.4978</td></tr><tr><td>46</td><td>3x10<sup>-6</sup></td><td>Tsanis</td><td>K-ε</td><td>Nikuradse</td><td>1x10<sup>-5</sup></td><td>0.2713</td><td>0.2336</td></tr><tr><td>47</td><td>3x10<sup>-6</sup></td><td>Tsanis</td><td>K-ε</td><td>Nikuradse</td><td>2x10<sup>-5</sup></td><td>0.2678</td><td>0.2245</td></tr><tr><td>48</td><td>3x10<sup>-6</sup></td><td>Tsanis</td><td>K-ε</td><td>Nikuradse</td><td>3x10<sup>-5</sup></td><td>0.2956</td><td>0.2668</td></tr><tr><td>49</td><td>3x10<sup>-6</sup></td><td>Tsanis</td><td>K-ε</td><td>Nikuradse</td><td>4x10<sup>-5</sup></td><td>0.2456</td><td>0.2987</td></tr></table>
# 1. Analysis of Seasonal Behaviour of Estuarine Dynamics and the Inner Shelf

## 1.1. Sea Level

Figure E1 (A-D) characterises the seasonal field of sea-level rise for the entire studied domain during the simulated periods 2005-2006 (neutral period) and 2008-2009 (ENSO period), respectively, where the colour scale varies from -30 to +30 cm. The results in the summer period (Figures E1-A and E1-B) indicate that the effects of the tide and fluvial discharge promote a pile of water on the Argentine coast of the Río de la Plata region, while in the northern Patos Lagoon region, the local effect of northeast winds causes a decrease in the water level (Simionato et al., 2001; Castelão and Möller, 2003). This combination of effects will establish a barotropic pressure gradient towards the sea, and favour ebb flows, both for the Río de la Plata and the Patos Lagoon (Simionato et al., 2001; Castelão and Möller, 2003). The results of the winter period (Figures E1-C and E1-D) show an opposite scenario: the local effect of the south quadrant wind results in the stacking of water on the Uruguayan bank of the La Plata River, while in the Patos Lagoon this stacking occurs in the northern region of the lagoon (Simionato et al., 2001; Castelão and Möller, 2003). In this scenario, the barotropic pressure gradient is weakened, favouring flood flows (Möller et. al., 2001; Fernandes et. al., 2002).

<figure><img src="image_49.png" /></figure>
<figure><img src="image_50.png" /></figure>

Figure E1 - Seasonal behaviour of sea level for the study region, in the summer 2005-2006 (A), summer 2008-2009 (B), winter 2005-2006 (C) and winter 2008-2009 (D).

In comparing the simulated years, it is clear that there is a decrease in the gradient of elevation of the lagoon level, that is, the difference between the maximum elevation and the minimum elevation. The gradient is smaller in years under the influence of the ENSO phenomenon than in a typical year in the region. As the second modelled period is characteristic of La Niña (January and February, 2008) and El Niño (November and December, 2009), a possible cause for the decrease in the gradient is the high flow of the river that occurs in characteristic El Niño years, and which results in a big difference in the level between the continent and the ocean. For the La Plata River, Guerrero et. al. (2014) explain that despite the change in level between the two periods, the Río de la Plata discharge is not affected by the ENSO anomaly, as much as by interannual variations caused by local seasonality. Thus, the variation in the Río de la Plata level gradient is a response to seasonal variability and not to the interference of the El Niño and La Niña events. Matano et. al. (2014) highlight the year of 2009 as an “outbreak” within the pattern presented by the Río de la Plata discharge.

## 1.2. Salinity

Regarding the saline field behaviour, it is known from the literature that the Southwest Atlantic Inner Shelf is a region marked by the presence of long strips of low salinity in regions close to the coast (Möller et al., 2008). This is a result of the pattern of freshwater input from the Río de la Plata and the Patos Lagoon, in addition to the presence of coastal currents from the southern tip of the continent and the local wind regime (Matano et al., 2014). The strong seasonal oscillations of the southwest wind (i.e., from the southwest) during winter and northeast wind (i.e., from the northeast) during summer, therefore control the saline field in the region.
<figure><img src="image_51.png" /></figure>

<figure><img src="image_52.png" /></figure>

<figure><img src="image_53.png" /></figure>

<figure><img src="image_54.png" /></figure>

Figure E2 - Seasonal behaviour of the salinity field for the study region, in the summer 2005-2006 (A), summer 2008-2009 (B), winter 2005-2006 (C) and winter 2008-2009 (D).

Figure E2 (A-D) characterises the seasonal salinity field for the entire studied domain during the simulated periods. Analysing the results of the summer of 2005-2006 (Figure E2A), it appears that the plume retracts and is trapped upstream of the river, as verified by Piola et al. (2000). These upstream extensions are driven by the internal dynamics of the river and the strength of the local wind (Soares et al., 2007b; Palma et al., 2008; Matano and Palma, 2010a; 2010b; 2013) which, in the summer (Figures E2A and E2B), comes predominantly from the northeast and is responsible for trapping the plume in the region near the Río de la Plata mouth. During the winter (Figures E2C and E2D), the southeast wind predominates in the region and the saline plume expands further downstream, and with the contribution of the coastal current formed by the southeast wind action, it reaches greater latitudes (28°S) (Piola et al., 2000).

When comparing the simulated years, a significant change in the saline field is not evident in the years 2008-2009 when compared to the period previously simulated. In the summer, a small variation in the saline plume migrating towards northwards can be seen (Figure E2B). The plume is more restricted to the
mouth for the years 2008-2009, as it doesn't spread so much along the coast towards the north. In winter, the difference is a little more visible on the platform, where the saline plume expands a lot both to the north and offshore, surpassing the Patos Lagoon mouth and reaching the north of the grid, corroborating the results presented by Piola et al. (2000).

## 1.3. Current Velocity

As with the salinity field, the current regimes on the internal platform are strongly modulated by the local action of the wind (Soares et al., 2007a). During the summer, currents therefore migrate towards the south, modulated by the northeast wind characteristic of the region and the season. During the winter, on the other hand, the contribution of the southeast wind in the region intensifies the currents moving in northerly direction along the coast, changing the salinity and level fields as seen previously.

<figure><img src="image_55.png" /><figcaption>Figure 4 - Seasonal behaviour of the speed field for the study region, in the summer 2005-2006 (A), summer 2008-2009 (B), winter 2005-2006 (C) and winter 2008-2009 (D).</figcaption></figure>

Figure 19 shows the results of the current speed field for the summer and winter of the years 2005-2006 (Figures E3A and E3C) and for the summer and winter of 2008-2009 (Figures B3B and B3D). For the
first simulated period in the summer, an intensified coastal current towards the south is seen, with speeds ranging from 0.2 to 0.4 m/s, which corroborates the results of Ghisolfi et al. (2003) and Soares et al. (2007a). In winter, the results show that the current is more intensified than in the summer, but in the opposite direction – i.e. northwards through the action of a southeasterly wind - as proposed by Ghisolfi et al. (2003). The currents in the results vary in magnitude from 0.35 to 0.40 m/s.

When comparing the first simulation with the second, an intensification in the currents in both summer and winter is evident. This intensification is more evident in the north of the studied region, where the average velocity surpasses 0.45 m/s, possibly due to the effects of El Niño (Pimenta et al., 2005).