Detailed knowledge of nearshore topography and bathymetry is required for a wide variety of purposes, including ecosystem protection, coastal management, and flood and erosion monitoring and research, among others. Both topography and bathymetry are usually studied separately; however, many scientific questions and challenges require an integrated approach. LiDAR technology is often the preferred data source for the generation of topobathymetric models, but because of its high cost, it is necessary to exploit other data sources. In this regard, the main goal of this study was to present a methodological proposal to generate a topobathymetric model, using low-cost unmanned platforms (unmanned aerial vehicle and unmanned surface vessel) in a very shallow/shallow and turbid tidal environment (Bahía Blanca estuary, Argentina). Moreover, a cross-analysis of the topobathymetric and the tide level data was conducted, to provide a classification of hydrogeomorphic zones. As a main result, a continuous terrain model was built, with a spatial resolution of approximately 0.08 m (topography) and 0.50 m (bathymetry). Concerning the structure from motion-derived topography, the accuracy gave a root mean square error of 0.09 m for the vertical plane. The best interpolated bathymetry (inverse distance weighting method), which was aligned to the topography (as reference), showed a root mean square error of 0.18 m (in average) and a mean absolute error of 0.05 m. The final topobathymetric model showed an adequate representation of the terrain, making it well suited for examining many landforms. This study helps to confirm the potential for remote sensing of shallow tidal environments by demonstrating how the data source heterogeneity can be exploited.

The aim of this work is to evaluate the applicability of the 3D model obtained through Structure-from-Motion (SFM) from unmanned aerial vehicle (UAV) imagery, in order to characterize bioerosion patterns (i.e., cavities for roosting and nesting) caused by burrowing parrots on a cliff in Bahía Blanca, Argentina. The combined use of SFM-UAV technology was successfully applied for the 3D point cloud model reconstruction. The local point density, obtained by means of a sphere of radius equal to 0.5 m, reached a mean value of 9749, allowing to build a high-resolution model (0.013 m) for resolving fine spatial details in topography. To test the model, we compared it with another point cloud dataset which was created using a low cost do-it-yourself terrestrial laser scanner; the results showed that our georeferenced model had a good accuracy. In addition, an innovative method for the detection of the bioerosion features was implemented, through the processing of data provided by SFM like color and spatial coordinates (particularly the y coordinate). From the 3D model, we also derived topographic calculations such as slope angle and surface roughness, to get associations between the surface topography and bioerosion features.

Understanding the drivers and how they affect ecosystem metabolism is essential for developing effective management policy and plans. In this study, net ecosystem production (NEP), ecosystem respiration (R), and gross primary production (GPP) rates were estimated in relation to physicochemical, hydrological, and meteorological variables in La Salada (LS) and Sauce Grande (SG), two shallow lakes located in an important agricultural region with water management. LS is a mesosaline, mesotrophic-eutrophic lake, whereas SG is a hyposaline and eutrophic lake. GPP and R showed daily and seasonal variations, with R exceeding GPP during most of the study period in both lakes. Net heterotrophic conditions prevailed during the study period (NEP LS: −1.1 mmol O₂ m⁻² day⁻¹ and NEP SG: −1.25 mmol O₂ m⁻² day⁻¹). From data analysis, the temperature, wind speed, and lake volume are the main drivers of ecosystem metabolism for both lakes. Despite the significant differences between the two lakes, the NEP values were similar. The different hydrological characteristics (endorheic vs. flushing lake) were crucial in explaining why the two different systems presented similar ecosystem metabolic rates, emphasizing the importance of water management.

The accuracy assessment of three different Normalized Difference Water indices (NDWIs) was performed in La Salada, a typical lake in the Pampean region. Data were gathered during April 2019, a period in which floods occurred in a large area in the Southwest of the Buenos Aires Province (Argentina). The accuracy of the estimations using spaceborne medium-resolution multi-spectral imaging and the reliability of three NDWIs to highlight shallow water features in satellite images were evaluated using a high-resolution airbone imagery as ground truth. We show that these indices computed using Landsat-8 and Sentinel-2 imagery are only loosely correlated to the actual flooded area in shallow waters. Indeed, NDWI values vary significantly depending on the satellite mission used and the type of index computed.

We present an experimental analysis of hydraulic roughness variations due to changes in alluvial cover in a mixed bedrock-alluvial meandering channel with larger bedrock roughness than alluvial roughness. Three sets of experiments were conducted in a highly sinuous flume: one with bare bedrock, and two with enough sediment to cover 21% and 78% of the bedrock respectively. We compare our results with data from experiments previously conducted in the same flume with flat- and smooth-bed, and data from experiments with fully alluvial conditions. Our results show that: (1) hydraulic resistance in a mixed bedrock-alluvial channel changes with the degree of alluviation; (2) hydraulic resistance is greater for bare-bedrock conditions, and decreases as sediment supply increases; (3) if bedforms appear, hydraulic resistance may be larger than for bare bedrock conditions due to form drag; (4) fluctuations in alluvial cover due to freely-migrating bars lead to instantaneous changes in hydraulic resistance.

This work combines in situ measurements with a time series of satellite turbidity derived from Landsat 8-OLI images to provide a first synoptic overview of the main hydrometeorological drivers of turbidity in the Bahía Blanca Estuary (Argentina). An empirical relationship between turbidity and SPM concentrations was established for the study area (R² = 0.92; RMSE = 0.098 mg m⁻³; NMAE = 6.2%). Several atmospheric correction schemes and turbidity retrieval algorithms were tested and the combination of the SWIR-v and the retrieval algorithm by Dogliotti et al. (2015) were applied to 121 Landsat 8-OLI scenes (2013–2021). The effects of tides, winds, and rainfall on satellite turbidity were evaluated through Generalized Linear Models (GLM) built for three different sectors along Canal Principal, from the inner zone to its mouth. Regardless of the zone, cumulative rainfall had negligible effects on turbidity. Tides had a significant effect in the inner and middle zones. In the inner zone, higher turbidity values significantly associated with ebb tide conditions, which produce erosion. In the middle section tidal current speeds positively correlated with turbidity, suggesting sediment resuspension over shallow banks. Close to the mouth of the estuary, turbidity responded entirely to winds. Winds blowing from de NW, aligned with the azimuth of Canal Principal, would aid to the export of estuarine sediments to the shelf.