Impact of the Patos Lagoon jetties on inner-shelf circulation and water propertiesAbstract
The jetties on the Patos Lagoon mouth are 4 km long and form a conspicuous feature in a monotonous coast line. Under steady northeasterly winds-the prevailing local wind-an eddy is formed in the leeward of the jetties. This study investigated the circulation and water properties in the inner shelf affected by this eddy. We conducted a field experiment to collect hydrodynamic and water property data in the lee of the jetties during a prolonged event of strong northeasterly winds. These conditions promote lagoon outflow and eddy formation. Current velocity and direction were measured using four acoustic doppler current profilers (ADPC) deployed parallel to the coast line. Vertical profiles of water properties (salinity, temperature, turbidity, chlorophyll and dissolved oxygen) were measured using a CTD along transects. To complement the field experiment, high-resolution Sentinel-2 satellite imagery acquired under similar conditions was analyzed, along with wind reanalysis data from ERA5. Results revealed that eddy formation occurs under both NE and W/NW winds, the spatial extent and core position of which are modulated by wind intensity and relative angle to the jetties. Brackish water outflow through the jetties induces strong stratification, leading to a decoupling of the upper and bottom layers. This produces a vertically sheared flow, with the surface layer moving seaward and the bottom layer moving landward, toward the jetties. However, the observed salinity and temperature distributions suggest that the bottom layer also exhibits a cross-shelf (onshore) component indicating upwelling, which may contribute to the transport of fine sediments shoreward. An identified region of low dissolved oxygen saturation suggests hypoxic conditions likely associated with the intense stratification.
Keywords:
Eddy; Stratification; Hypoxia; Hydrodynamics
INTRODUCTION
The continental shelf is the region connecting the continent shores to the open ocean and plays a crucial role in the transfer of materials from continents to the world oceans, ultimately affecting the marine ecology, biological productivity and fate of organic matter (Mann and Lazier, 2005). This region is a key area for interdisciplinary research due to its environmental significance, and is highly affected by cross-shelf exchanges of sediments, nutrients, larvae, phytoplankton, and contaminants. These materials originate from various sources, including river discharge, outfalls, coastal erosion processes, or atmospheric deposition (Austin et al., 2002; Lentz and Fewings, 2012; Moulton et al., 2023).
The continental shelf is divided into the outer and inner shelf, with the latter referring to the coastal sector in which turbulent boundary layers from the surface and bottom occupy the entire water column and the strongest water property gradients are observed (Lentz, 1995). The synergistic interactions between physical processes occurring on the inner shelf play a fundamental role in determining the fertility of the region and sustaining primary production by regulating nutrient availability, turbulence, and vertical mixing of the water column (Brink, 2016; Moulton et al., 2023; Simpson and Sharples, 2012).
Shelf hydrodynamics are driven by the combined action of wind, tides, river discharge, and surface waves, interacting with coastal bathymetry and shoreline geometry (Brink, 2023). Its flow regime is typically stratified due to the proximity of continental inputs and the seasonal radiative balance (Simpson and Sharples, 2012). Balance between buoyancy-driven stratification and turbulence-induced mixing directly influences nutrient distribution, biological production, and the oxygenation of deeper layers. Stratified conditions limit vertical exchanges, promoting the formation of subsurface chlorophyll-a maxima (SCM) and enhancing oxygen depletion processes in the bottom layers, potentially leading to hypoxia (Simpson and Sharples, 2012).
The along-shelf flow component on the inner continental shelf is typically more energetic and dominant in terms of water column transport, often exhibiting a unidirectional pattern. The cross-shelf component, in turn, although less energetic, is more complex due to the influence of the coastal boundary and cross-shelf forcing mechanisms. For example, remotely driven Ekman transport can induce local coastal upwelling or downwelling. The processes modulating cross-shelf transport of materials also affect nutrient availability, regulate water residence time, redistribute heat and salinity, influence the transport of planktonic organisms, and determine the biogeochemical balances in the region (Brink, 2016; Gill and Clarke, 1974; Moulton et al., 2023; Simpson and Sharples, 2012). Presence of a promontory enhances cross-shelf mixing processes on the inner shelf (Russell and Vernell, 2017).
The Rio Grande do Sul state coast is characterized by an extensive coastal plain, with a sandy shoreline stretching for approximately 600 km. The only prominent and rigid feature along this coastline is the Rio Grande jetties, located between Chuí, 215 km to the south, and Torres, 390 km to the north (Figure 1). The jetties extend nearly perpendicular to the shoreline, reaching approximately 4 km offshore and intersecting the 15 m isobath at their seaward end. Under N-NE wind conditions, inner shelf currents flow southward (Cruz and Schettini, 2025) and a clockwise coastal eddy forms on the leeward side of the jetties (Franzen et al., 2023; Vinzon et al., 2009). Because the jetties are permeable, low-salinity water flows through them, increasing the stratification of the adjacent inner shelf (Cruz and Schettini, 2025).
This study investigates the effects of the eddy formed in the shadow zone of the western jetty on the circulation and distribution of water properties, focusing on its influence on the transport of suspended particulate matter. Remote sensing data and in situ measurements of oceanographic and meteorological variables were analyzed to describe the distribution of physical and biological properties during northeasterly wind conditions, and the spatial configuration of the eddy under different synoptic scenarios.
Study area
The Rio Grande do Sul state continental shelf extends approximately along a northeast-southwest axis between Arroio Chuí (34°S) and Torres (29°S), exhibiting a coastline characterized by a sandy coastal plain and few prominent features, except for the mouth of Patos Lagoon (Figure 1). The shelf width varies between 100 and 180 km, with the shelf break depth at around 180 m and a gentle bottom slope. In the vicinity of the Patos Lagoon mouth, the shelf is relatively flat, featuring extensive sandy banks to the north and south (Corrêa et al., 2019; Fachin, 1998; Martins et al., 2003).
The jetties at Rio Grande Bar, at the Patos Lagoon mouth, were constructed in the 1910s and are among the largest coastal engineering works of their time (Bicalho, 1983; Motta, 1969). Its construction aimed to stabilize the lagoon bar, ensure navigation safety, and provide access to the Port of Rio Grande. Construction began in 1911, and in its final configuration, the jetties extended 4 km from the coastline (Bicalho, 1983; Cunha and Calliari, 2009; Motta, 1969). The construction material used was loose stones and, in 2010, the jetties were modified with tetrapod blocks (Migliorini and Guimarães, 2008), resulting in a permeable structure, with the final portion located 15 m deep.
Location of the anchored ADCPs (#1, #2, #3, #4), CTD profile collection trajectories (#T1, #T2, #T3, #T4, and #L), and SimCosta Buoys (RS2, RS4 and RS5). Bathymetric contours were obtained from the Brazilian Navy nautical charts.
The region’s climate is classified as humid temperate with hot summers (Cfa) according to the Köppen-Geiger classification. Monthly average air temperature ranges between 11° C (July) and 23°C (January), with an annual average of 19°C (Reboita and Kruche, 2018). NE winds predominate throughout the year, blowing nearly parallel to the coastline, with higher intensity in spring (Cruz and Schettini, 2025; Reboita and Kruche, 2018; Saraiva et al., 2003). The wind regime is disturbed cyclically by the passage of frontal systems occurring at intervals of 6 to 11 days (Stech and Lorenzetti, 1992).
Local tide is mixed with a diurnal predominance, with an average amplitude of 0.3 m, and does not play a significant role in the hydrodynamics (Moller et al., 2007) since the flow is primarily driven by local wind (Costa et al., 2011; Cruz and Schettini, 2025; Soares and Möller, 2001; Zavialov et al., 2002). Currents on the continental shelf respond mainly to the wind regime (Soares and Möller, 2001). Currents on the inner shelf (20 and 15 m) displayed patterns consistent with Ekman force balance, where southward longitudinal currents showed a return flow in the deeper layers of the water column (Costa et al., 2011; Cruz and Schettini, 2025).
Exchange patterns between the lagoon and the coastal region have been investigated by Hartmann and Schettini (1991), Moller et al. (2001), and Marques and Moller (2008), Santa-Rosa and Schettini (2024). During high rainfall periods, river discharge predominates and drives ebb flow. During low rainfall periods, wind becomes the primary control of exchange processes, acting both locally and remotely due to the Ekman mechanism. Winds from the northern quadrant force dominant ebb flow, producing a buoyant plume on the shelf. Coastal water quality is also influenced by the fluvial discharge of the Plata River (Muelbert et al., 2008; Piola et al., 2008).
MATERIAL AND METHODS
Field data
A field experiment was designed to capture the hydrodynamic patterns in the leeward of the jetties during a period of strong northeast wind. Based on climatological data, these conditions are expected particularly at the end of spring and the beginning of summer (Cruz and Schettini, 2025). Experiment logistics were organized and a waiting period was established starting from October 2023. The experiment was conducted on November 28, 2023. Considering that the hydrodynamic regime is primarily wind-driven and that astronomical tides are not significant, the experiment involved data recording for approximately 10 hours. Water, current speed, and direction data were recorded simultaneously at four points along the inner shelf (Figure 1), and water properties (salinity, temperature, and turbidity) were recorded along four cross-shore sections and one parallel to the coast (Figure 1).
Vertical profiles of temperature, salinity, turbidity, chlorophyll-a, and dissolved oxygen were collected using a JFE RINKO multiparameter profiler. Several sampling points were distributed along four cross-shore transects (#T1, #T2, #T3, and #T4) and one alongshore transect (#L) relative to the coastline (Figure 1). Sampling track locations were recorded using a GARMIN GPS device.
Sea level, current speed, and direction data were recorded using an Acoustic Doppler Current Profilers (ADCP) deployed at four locations along the alongshore transect (#L), approximately 1.5 km from the coastline, with 1 km spacing between sites. Nortek Aquadopp Profilers were used-one operating at 2 MHz and three at 1 MHz. The 2 MHz ADCP was deployed at point #1, at a depth of 6.5 m. Depths at the other points were: point #2, 7.4 m; point #3, 8.5 m; and point #4, 7.2 m. ADCP data acquisition started at 06:20 and ended at 16:30. The 2 MHz ADCP was configured to record speed profiles in 0.1 m cells, whereas the 1 MHz profilers used 0.3 m cells. Current speed data were averaged over 120-second intervals, with measurements recorded every 5 minutes.
Current data from the Rio Grande Channel were obtained from the RS2 oceanographic buoy of the SimCosta project (https://simcosta.furg.br), located approximately 8 km upstream of the jetty outlet (Figure 1). The RS2 buoy is equipped with a downward-facing 600 kHz ADCP, positioned 0.7 m deep, with a blanking distance of 0.5 m and a cell size of 1 m. The bottommost cells were removed to eliminate outliers caused by acoustic side-lobe interference with the seafloor. Data were then depth-averaged to obtain the mean current direction and speed. Observed wind data were obtained from the RS4 and RS5 buoys of the aforementioned project (Figure 1), located near the study area, covering the period from 2019 to 2024.
Data Processing
Current speed data were rotated using principal component analysis (PCA) to obtain the longitudinal and transverse current components based on maximum variance and to determine the angle between these vectors and true north. Rotation angles at points #1, #2, #3, and #4 were 74.2°, 64.9°, 48°, and 40°, respectively. Current speed data were used in this study to investigate the transfer of physical and biological properties in the region and to calculate the Richardson number. Cruz and Schettini (2025) conducted a more detailed investigation using these current data and provided a more robust foundation regarding property transfer processes.
A key factor influencing this transfer of physical and biological properties is water column stratification, which occurs due to variations in temperature and salinity and can inhibit vertical mixing of water masses and property exchange (Simpson and Sharples, 2012). Stratification stability was assessed by calculating the Richardson number (Ri), a dimensionless parameter that indicates the tendency of a flow toward stratification. Ri values below 0.25 suggest unstable flow where generated turbulence is sufficient to promote vertical fluid mixing. Conversely, values above 0.25 indicate that stabilizing forces dominate over current shear, preventing vertical mixing. Richardson number is given by
in which N is the Brunt-Väisälä buoyancy frequency, which represents a measure of vertical motion stability determined by the density gradient (ρ), divided by the term representing shear force ∂u/∂z.
Turbidity data obtained from the optical backscatter sensor (OBS) of the multiparameter probe were converted to suspended sediment concentration (SSC) using the calibration curve:
Remote sensing and wind reanalysis
Sentinel-2 satellite imagery (https://www.esa.int/Applications/Observing_the_Earth/Copernicus/Sentinel-2) was used to analyze eddy patterns under different environmental conditions. The images feature four spectral bands with 10 m spatial resolution, a 290 km orbital swath width, available data from 2016 to present, and a revisit frequency of ~5 days. All available images for the study area were visually inspected, selecting those with minimal cloud cover and clearly visible eddy structures. From 1304 available images of the study region, 22 were selected for analysis.
Raw satellite data were downloaded as individual spectral bands (e.g., red, green, and blue) and processed using Python algorithms. Each band was handled separately and then combined into RGB composites. To enhance visual interpretation, a percentile stretching method (2-98%) was applied to each spectral band. This technique adjusts pixel values based on the lower and upper percentiles of their distribution, thereby enhancing contrast and emphasizing relevant oceanographic structures. Importantly, this approach improves the distinction between patterns without altering the original color balance of the image. For the dates of the selected images, we used wind reanalysis data from the ERA5 numerical model provided by the Copernicus Climate Change Service (C3S). ERA5 offers global atmospheric reanalysis data with a spatial resolution of ~31 km and hourly temporal resolution, generated by the European Centre for Medium-Range Weather Forecasts (ECMWF) prediction model.
Wind speed and direction variables at 10 m above sea level were extracted to ensure adequate synoptic representation, since observational data from meteorological buoys contained temporal gaps that prevented climatological analysis of all images. However, the buoy observational data were used to calculate the root mean square error (RMSE) between observed and modeled values to assess the reanalysis data accuracy. Additionally, ERA5 data were interpolated to a new grid with ~3 km resolution to improve data visibility.
RESULTS
The presentation sequence was organized as follows: (1) flow characterization, (2) water properties, and (3) satellite imagery. Representative images showing distinct synoptic conditions are presented in the main text. All selected images are provided in the Supplementary Material.
Flow characterization
Figure 2 shows the time series of current speed for the along-shelf component at both surface and near-bottom levels. Positive values indicate flow direction toward the jetties, whereas negative values indicate flow away from the jetties. All four instruments showed similar patterns. Surface layer flows away from the jetties, whereas the bottom layer flows toward the jetties. At the beginning of the field experiment (before 08:00), the flow at all points was unidirectional toward the jetties, except for point #4. Notably, surface data were actually collected approximately 1-2 m below the water surface.
Time series of (a) along-shelf and (b) cross-shelf current speed for the four ADCP measurement points (#1, #2, #3, #4). Solid lines represent the uppermost layer measured by the ADCP. Dashed lines indicate the bottommost layer.
Figures 3a and 3b display the vertical profiles of the alongshore and cross-shore current components, respectively. These profiles represent the temporal median values with their corresponding occurrence percentile intervals for each measurement level. Alongshore flow exhibits vertical direction reversal, with the surface layer thickness increasing with distance from the jetties (Figure 3a). The cross-shore component showed vertically unidirectional patterns in terms of median values, but with significantly greater variance (Figure 3b). Variability was highest at point #1, featuring a broader distribution of both median and percentiles toward the coast. At points #2 and #3, the percentiles and median distribution were predominantly oriented seaward, whereas at ADCP #4 the distribution was directed landward.
Figure 3c presents the vertical profiles of density and Richardson number values. All profiles show water column stratification, with Ri values > 0.25 coinciding with the pycnocline, indicating stratification stability. At points #1, #2, #3 and #4, the depth where the 0.25 threshold is exceeded ranges from 1.3-1.9 m, 2.5-4 m, 2.7-5.1 m, and 2.3-5 m, respectively. The abrupt pycnocline boundary seen at #1 becomes smoother as the distance from the jetty increases (#2, #3 and #4), with the thickness of the layer where depth exceeds the 0.25 Ri threshold matching the range of pycnocline boundary smoothing.
(a) and (b): vertical profiles of alongshore and cross-shore current components, respectively. The median value is shown by the black line, whereas the 1st, 5th, 25th, 75th, 95th, and 99th percentiles are displayed through blue shades. The depth at each point and the distance between them are proportional to actual field measurements. (c) Vertical profiles of density (blue) and Richardson number (red) calculated for the same period as the density profile. Red dashed line indicates the 0.25 Ri threshold.
Water properties
Figure 4 presents the distributions of temperature, salinity, SSC, chlorophyll-a, and dissolved oxygen for the longitudinal section (#L) and transverse sections (#T1-T4). All sections exhibited water column stratification for salinity and temperature, with salinity ranging from 14 g/kg at the surface to >30 g/kg at the bottom layer, and temperature varying from >20°C at the surface to 17°C at the bottom layer. In section #L, the thermocline and halocline coincide and deepen with increasing distance from the jetties. Near the jetties (~220 m), thermocline occurs at ~1-m depth, increasing to ~2 m at a distance of 4.8 km (Figure 4a1). Similarly, the halocline boundary near the jetties is at ~1-m depth, deepening to ~4 m at 4.8 km distance (Figure 4b1).
In transverse sections #T1-T4, the thermocline and halocline are more pronounced in deeper regions (Figure 4b2-5). Near the coast, salinity and temperature profiles are more homogeneous. The halocline and thermocline boundaries in sections #T1, #T2, #T3, and #T4 are most clearly defined at distances of approximately 200 m, 750 m, 1000 m, and 1500 m from the coast, respectively (Figures 4a1-5, 4b1-5).
SSC distribution in the longitudinal section (#L) showed maximum values near the surface within 1 km of the jetty, whereas maximum bottom values occurred between 2 and 3 km from the jetties (Figure 5c1). In section #T1, near-surface SSC values remained nearly homogeneous throughout the entire section (Figure 4c2). In contrast, sections #T2 and #T3 exhibited higher near-surface SSC values both near the coast and in the offshore region (Figure 4c3-4). Section #T4 exhibited elevated SSC profiles only near the margins, with relatively lower values toward the open ocean. Near the bottom, two distinct high-SSC regions were observed: one located close to the beach, influenced by surf zone processes, and another between 1 km and 1.5 km from the coast (Figure 4c1-5).
Chlorophyll-a distribution in section #L reached maximum values both near the surface and near the bottom. Surface values showed a gradual decrease with increasing distance from the jetty (Figure 4d1). In the transverse sections, higher values occurred near the coast and close to the bottom. In sections #T1, #T3, and #T4, an intermediate layer with elevated chlorophyll-a concentrations was observed, showing reasonable alignment with the pycnocline position (Figure 5d1-5).
Dissolved oxygen saturation distribution in section #L exhibited stratification throughout the entire section, with near-saturation surface values dropping below 40% in the bottom layer, following the distribution patterns of salinity and temperature (Figure 4e1-5). In all transverse sections, the highest dissolved oxygen saturation values occurred at the surface and near the coast throughout the water column. At depth, all sections showed a zone of minimum saturation approximately 1-1.5 km from the coast. Low-saturation area was most extensive in section #T1 and progressively decreased across sections through to #T4.
Longitudinal (#L) and transverse (#T1, #T2, #T3, and #T4) sectional distributions of temperature, salinity, suspended sediment concentration (SSC), chlorophyll-a (Chl), and dissolved oxygen (DO) saturation. In the first column plots, the white dashed contour (18°C) indicates the approximate thermocline boundary. In the second column plots, the white contour (28 g kg⁻¹) marks the approximate halocline boundary. In the fifth column plots, the white dashed contour (45%) delineates regions favorable to hypoxic conditions.
Figure 5 shows the horizontal spatial distributions for the surface (up to 1-m depth) and bottom (up to 1 m above the seabed) layers. Note that the color scales used for the same variable differ between depth levels to enhance gradient visualization.
Spatial distribution of temperature, salinity, suspended sediment concentration (SSC), chlorophyll-a (Chl-a), and dissolved oxygen (DO), calculated from data collected in the transverse and longitudinal sections. The first column plots (a-e) show the mean distribution for the upper 2 m water column, while the second column plots (f-j) display the mean distribution from 1 m above the seabed. The white 18°C contour in (a) and 28 g kg⁻¹ contour in (b) mark the approximate thermocline and halocline positions, respectively. The white 45% contour in (j) identifies the region prone to hypoxic conditions.
Surface distributions of temperature and salinity (Figures 5a and b) indicate upwelling near the coast, where temperatures are lower and salinity is higher. Moving away from the coast toward the jetty, temperature increases while salinity decreases, reflecting the gradient formed by estuarine water outflow through the jetties and lagoon mouth. In the bottom layer, temperature and salinity gradients are less pronounced, with warmer temperatures near the coast (shallower areas) and further from the jetties. Notably, the lowest temperatures occur not in the deepest offshore zone but in an intermediate band (Figure 5f), a pattern also evident in the sectional distributions (Figure 4a1-a4).
Surface distribution of Chl-a and SSC follows the salinity pattern, though Chl-a shows elevated values along the coast (Figure 5c-d). Near the bottom, the highest Chl-a and SSC values occur in the central region, with chlorophyll generally decreasing seaward (Figure 5h-i). Surface DO saturation (Figure 5e) shows near-saturation levels across most of the area, with lower values (~60%) near the coast where surface temperatures are coldest (Figure 5a). Bottom DO saturation (Figure 5j) displays a zone of lower saturation (<40%) along the central portion, mirroring the bottom temperature distribution (Figure 5f). The highest values occur toward the coast and SW direction.
Satellite images
As no satellite imagery was available for the exact field survey dates, images acquired under relatively similar meteorological conditions were analyzed to provide a larger-scale synoptic perspective. A total of 22 Sentinel-2 satellite images were selected and combined with atmospheric conditions simulated by the ERA5 reanalysis model at the time of image acquisition. These images were obtained under wind conditions with a mean direction of 222° (SW) and average speed of 3.8 m/s. Of the 22 images, 18 were acquired with winds between 201°-282° (W-SW), whereas 3 showed a mean wind direction of 172° (S).
Summary of selected periods from Sentinel-2 satellite imagery, with corresponding atmospheric conditions obtained from the ERA5 reanalysis model and RS4-5 buoys of the SimCosta (SC) project. Current conditions were derived from ADCP data collected by the SimCosta project’s RS2 buoy. Satellite image acquisition time was 13:20 for all dates.
Due to varying atmospheric conditions in each image, the duration of each event was defined considering periods when wind direction fell within the E-N quadrant (180°-270°), either starting at or spanning the satellite image acquisition time. Average event duration was 2 days and 9 hours, with a maximum of 5 days and 3 hours recorded on January 9, 2022. Table 1 summarizes the dates of selected satellite images, atmospheric conditions, and current velocity/direction recorded by the RS-2 buoy on the Rio Grande Channel. All current directions indicate ebb tide conditions.
On the field survey date (2023-11-28), the east-north (E-N) wind event lasted approximately 6 days, from 2023-11-25 to 2023-12-02. During this period, average wind speed and direction were 9.2 m/s and 199°, respectively, with a maximum wind speed of 10.3 m/s. Although no satellite images were available near the field survey date, the synoptic conditions recorded on 2020-02-12 (Figure 6) were similar according to SimCosta buoy data (Table 1). On this date, the eddy center location is visible approximately 3 to 4 km from the midpoint of the west jetty. Near the margins, between 1 and 2 km from the coast, two small counter-rotating vortices are observed opposite to the main eddy, forming a complex structure in the shadow zone of the jetty.
Sentinel-2 satellite image acquired on November 2, 2023. The yellow vectors indicate wind direction and intensity. The scale in the lower right corner represents 2 km (spatial reference) and 4 m/s (wind intensity reference).
In Figure 7, the synoptic conditions showed wind directions with more oblique or perpendicular angles relative to the jetty (approximately 153°), indicating that even without direct influence from the physical barrier created by the jetties, the eddy structure remained well-defined. On 2020-02-12 and 2021-04-19, average wind direction was similar to that observed on 2020-11-20 (Figure 7), approximately 188° and 174°, respectively, and on all these dates, the eddy was easily identified in the shadow zone.
Sentinel-2 satellite image acquired on November 20, 2020. The yellow vectors indicate wind direction and intensity. The scale in the lower right corner represents 2 km (spatial reference) and 4 m/s (wind intensity reference).
On 2021-03-20, wind conditions were most intense, with speeds reaching 11.6 m/s and direction nearly parallel to the jetty axis. Currents within the lagoon also recorded their highest values at approximately 1.4 m/s. Although cloud cover hindered precise estimation of the eddy extent, its boundaries can be inferred to have reached at least 12 km from the western jetty (Figure 8).
Sentinel-2 satellite image acquired on March 20, 2021. The yellow vectors indicate wind direction and intensity. The scale in the lower right corner represents 2 km (spatial reference) and 4 m/s (wind intensity reference).
A wind direction near the E quadrant (270°) also leads to eddy formation, though with typically reduced extension. On 2022-04-24, with wind speeds of 7.5 m/s and direction of 266°, the eddy boundaries extended approximately 4 km from the western jetty (Figure 9).
Figure 10 shows a less-defined eddy structure compared with other analyzed dates. This occurred because the wind direction on 2023-04-22-approximately 288°-did not favor eddy maintenance, initiating its dissipation.
During certain periods (2019-04-13, 2020-11-20, 2021-04-19, 2024-03-07), water percolation from inside the jetties to the western jetty’s shadow zone is visible, as shown by Cruz and Schettini (2025b). Figure 11 illustrates this water inflow through the jetties on 2024-03-07.
Sentinel-2 satellite image acquired on April 24, 2022. The yellow vectors show wind direction and intensity. The scale in the lower right corner represents 2 km (spatial reference) and 4 m/s (wind intensity reference).
Sentinel-2 satellite image acquired on April 22, 2023. The yellow vectors display wind direction and intensity. The scale in the lower right corner represents 2 km (spatial reference) and 4 m/s (wind intensity reference).
Sentinel-2 satellite image acquired on March 7, 2024, showing water percolation through the jetties into the western jetty’s shadow zone. The scale in the lower right corner represents 2 km (spatial reference) and 4 m/s (wind intensity reference).
DISCUSSION
The coast adjacent to the Patos Lagoon mouth, to the west (Cassino Beach), experiences cyclical episodes of mud deposition on its beach (Calliari et al., 2007 and 2009). Pockets of unconsolidated mud paint the inner shelf off the beach and, following certain storms, this material is eroded, transported shoreward, and deposited on the beach (Calliari et al., 2001; Pereira et al., 2011). The mechanisms responsible for forming and maintaining these inner shelf mud deposits, and the origin of the mud itself, remain poorly understood. However, given that these deposition events occur within a very narrow stretch of shoreline-approximately 5 to 10 km from the lagoon mouth-, the jetties and their associated circulation likely play a role in this process.
The eddy formed leeward of the jetties can be clearly observed in the high-resolution satellite images. From them we learn about how complex are the patterns formed by the interactions between the jetties, the wind action which will produce strong along-shelf currents (Cruz and Schettini, 2025), and the water outflow from the lagoon, either through its mouth or the permeable jetties. The eddy dynamics was assessed with hydrodynamic numerical models to investigate the effect of the Patos Lagoon outflow on mud deposition in the inner shelf, considering the lagoon as the main sediment source (Franzen et al., 2023; Marques et al., 2010; Vinzon et al., 2009;). Cruz and Schettini (2025) assessed the inner shelf sediment dynamics and found that bottom exchange processes (erosion and deposition) may be the primary mechanism controlling sediment availability in the water column. The ultimate origin of the sediment could be either the Patos Lagoon or the La Plata Estuary. Although the latter is located nearly 450 km southwards to the local study area, this is a relatively small distance when considering the potential transport of along-shelf currents.
Based on experimental observations, Cruz and Schettini (2025b) evinced that the inner shelf leeward hydrodynamics of the lagoon jetties are more complex than previously thought. The jetties are permeable, allowing brackish water to flow through and thus leading to strong vertical stratification. Along-shelf currents are bidirectional, with surface flow moving away from the jetties and bottom flow moving toward them. Cross-shelf currents are significantly weaker than the along-shelf currents. In the present analysis, near-bottom cross-shelf currents presented a residual onshore transport (upwelling), as evinced by the horizontal distribution of salinity and temperature (Figure 2b), which indicates the intrusion of colder, saltier waters. This mechanism helps explain sediment accumulation in the lee of the jetties, where near-bottom resuspension may be gradually transported shoreward.
Surface distributions of chlorophyll-a and suspended sediment concentration (SSC) were strongly and inversely correlated with salinity, indicating their origin from the lagoon outflow-both from the inlet and through the jetties. While the mouth outflow behaves as a buoyant plume, with higher kinetic energy and more dynamic dispersion (Marques et al., 2010), the water passing through the jetties promotes a slower, more efficient distribution of nutrients across the inner shelf surface layer. This slower flow results in a longer residence time after release, potentially enhancing biological productivity, as indicated by elevated chlorophyll-a concentrations (Braga et al., 2008; Muelbert et al., 2008).
Surface nutrient availability, combined with pycnocline acting as a physical barrier to vertical mixing, may explain the formation of a subsurface chlorophyll maximum (SCM), as observed in the cross-sectional profiles. Below the pycnocline, restricted vertical diffusion produces a rapid decline in dissolved oxygen (DO) levels, creating favorable conditions for hypoxia development (~30% saturation) (Fennel and Testa, 2019; Rabalais et al., 2010). This pattern results from the interaction of three coupled processes: (i) DO consumption by bacterial respiration and organic matter decomposition; (ii) advection of oxygen-poor water masses toward the coast by bottom currents; and (iii) limited atmospheric ventilation and SCM oxygenation due to the pycnocline barrier.
Similar hypoxia-favoring mechanisms occur in the Louisiana Dead Zone, where excess nutrients from rivers lead to increased primary production but also decrease dissolved oxygen (DO) in bottom waters (Rabalais and Turner, 2003). Upwelling regions exhibit analogous behavior, as the upwelled deep waters from beyond the shelf break can introduce low-DO waters, either through natural oxygen depletion or via organic matter decay stimulated by upwelled nutrients (Connolly et al., 2010). These hypoxic conditions may cause mortality, reduced physiological capacity in aerobic organisms and macrofauna, biodiversity loss, and a shift toward more hypoxia-resistant species (Diaz and Rosenberg, 1995; Brauko et al., 2020; Rabalais et al., 2010).
CONCLUSIONS
This study investigated the oceanographic conditions in the leeward of the Patos Lagoon mouth jetties under prevailing northeasterly winds. Under these conditions, an eddy forms and brackish water flows out through the permeable jetties, affecting the distribution of physical and biological properties in the area. Satellite imagery analysis evinced the spatial complexity of the eddy and how its characteristics vary with wind conditions. Field-collected data allowed for a detailed assessment of water properties on the inner shelf sheltered by the jetties.
Brackish water outflow through the jetties induces strong stratification, producing a decoupling of the upper and bottom layers. This results in a vertically sheared flow, with the surface layer moving seaward and the bottom layer moving landward, toward the jetties. However, the observed salinity and temperature distributions suggest that the bottom layer also exhibits a cross-shelf (onshore) component indicating upwelling, which may contribute to the transport of fine sediments shoreward. An identified region of low dissolved oxygen saturation was suggests hypoxic conditions likely associated with the intense stratification.
Acknownledgements
We would like to thank all the individuals who helped during the intensive field experiment. We are also thankful for the support from the Brazilian National Council for Scientific and Technological Development (CNPq, #316037/2021-4 & #404847/2021-8), through INCT-COI and PELD Estuário da Lagoa dos Patos. To the Brazilian Federal Agency for Support and Evaluation of Graduate Education (CAPES) for GC’s scholarship. CAFS research fellowship CNPq #309572/2025-8.
Data availability statement:
The Jupyter Notebooks containing the code used for data processing are available on GitHub (https://github.com/GuiCruz/Jetties_Shadow_Zone). The Reanalysis wind data is available from Copernicus (https://cds.climate.copernicus.eu/). Field observations are available upon request to the corresponding author.
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AI Use statement:
The authors declare that artificial intelligence (AI) tools were used in the preparation of this manuscript. Specifically, AI-assisted language models were employed to improve clarity, grammar, and readability of the text. All scientific content, interpretations, and conclusions were developed by the authors, who take full responsibility for the accuracy and integrity of the work. No AI tools were used for data analysis, generation of results, or drawing scientific conclusions.
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Supplementary material:
No supplementary material available.
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Funding:
This work was supported by the Brazilian National Council for Scientific and Technological Development (CNPq) under Grant Nos. 316037/2021-4 and 404847/2021-8.
Edited by
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Associate Editor:
Leandro Ponsoni
