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.

Lakes, rivers, estuaries and ocean waters control many important natural functions at the regional-global level. Hence, integrative and frequent long-term water monitoring is required globally. This paper describes the main features and innovations of a low-cost monitoring buoys network (MBN) deployed in a temperate region of Argentina. The MBN was designed to record extended time series at high-frequency, which is of great value for the scientific community, as well as for decision-makers. In addition, two innovative designs belonging to two versions of moored buoys (i.e. shallow waters and coastal marine waters) were presented. It was shown that the cost of either of two versions of the buoy is low, which can be considered as the main advantage.

An assessment of wind energy potential was carried out in five sites (four onshore and one offshore) in South-West (SW) of Buenos Aires province (Argentina). We use high-resolution wind data (2 and 5 min) for the period 2009-2012. The power law was used to estimate the wind speed at 30, 40, and 60 m height from the anemometer position. Turbulence intensity and wind direction were analyzed. Statistical analyses were conducted using two-parameter Weibull distribution. A techno-economic analysis based on a set of commercial wind turbines was performed in those sites. The results derived from this work indicate that the SW of Buenos Aires province represents a promising area for the wind energy extraction, which would encourage the construction of wind farms for electricity generation.

Identificar el potencial de los recursos energéticos renovables es de gran interés dentro de la planificación energética. El objetivo principal de este estudio es evaluar los recursos eólico, solar y undimotriz en el Suroeste de la provincia de Buenos Aires (Argentina), analizando su potencial para la producción de electricidad, su relación con la carga de demanda, y la integración entre los mismos. Se emplearon datos de cuatro estaciones de monitoreo. En términos generales, se halló que los mayores niveles de potencia se observan en los meses de verano, coincidiendo con la máxima demanda eléctrica, alcanzando valores medios de hasta 1.06 kW m-2 (viento - 30 m de altura-), 0.56 kW m-2 (solar) y 4.60 kW m-1 (ola). Se aplicó el coeficiente de correlación de Pearson para evaluar las relaciones entre los recursos renovables a múltiples escalas temporales. Con respecto a la asociación entre los recursos eólico y solar, se encontró que éstos mostraron correlaciones altas y positivas, lo que significa que no pueden ser complementarios entre sí para su explotación combinada. Sin embargo, la mayoría de los pares de recursos restantes, tales como viento (continental/onshore) versus ola, solar versus ola, viento (offshore) versus viento (continental/onshore) y viento (offshore) versus solar, mostraron resultados prometedores para la complementariedad.

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We performed the accuracy assessment of three different Normalized Difference Water Indices (NDWIs) in water bodies during April 2019, a period in which floods occurred in a large proportion of 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, was evaluated using a high resolution airbone imagery as ground-truth. It is shown 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.