Daniela Rivera-Ruiz

The application of the Multispectral Instrument (MSI) aboard Sentinel-2A/B constellation for assessing water quality in Chilean lakes represents an emerging area of research, particularly for the environmental monitoring of optically complex water bodies. Similarly, atmospheric correction processors applied to aquatic environments, such as the Case 2 Networks (C2RCC-Nets), are notably underrepresented. This study evaluates the capability of C2RCC-Nets using different neural networks—Case-2 Regional/Coast Color (C2RCC), C2X-Extreme (C2X), and C2X-Complex (C2XC)—to estimate Secchi depth in Lake Lanalhue (eutrophic), Lake Villarrica (oligo-mesotrophic), and Lake Panguipulli (oligotrophic). The evaluation used different statistical methods such as Spearman’s correlation and normalized error metrics (nRMSE, nMAE, and nbias) to assess the agreement between satellite-derived data and in situ measurements. C2XC demonstrated the best fit for Lake Lanalhue, with an nRMSE = 33.13%, nMAE = 23.51%, and nbias = 8.57%, in relation to the median ground truth values. In Lake Villarrica, the C2XC neural network displayed a moderate correlation (r_s = 0.618) and error metrics, with an nRMSE of 24.67% and nMAE of 20.67%, with an nbias of 4.21%. In the oligotrophic Lake Panguipulli, no relationship was observed between estimated and measured values, which could be related to the fact that the selected neural networks were developed for very case 2 waters. These findings highlight the need for methodological advancements in processing satellite-derived water quality products for Chile’s optical water types, particularly for very clear waters. Nonetheless, this study underscores the need for model-specific calibration of C2RCC-Nets, as lakes with different optical water types and trophic states may require tailored training ranges for inherent optical properties.

Aquifer surveillance is key to understanding the dynamics of groundwater reservoirs. Attention should be focused on developing strategies to monitor and mitigate the adverse consequences of overexploitation. In this context, ground surface deformation monitoring allows us to estimate the spatial and temporal distribution of groundwater levels, determine the recharge times of the aquifers, and calibrate the hydrological models. This study proposes a methodology for implementing advanced multitemporal differential interferometry (InSAR) techniques for water withdrawal surveillance and early warning assessment. For this, large open-access images were used, a total of 145 SAR images from the Sentinel 1 C-band satellite provided by the Copernicus mission of the European Space Agency. InSAR processing was carried out with an algorithm based on parallel computing technology implemented in cloud infrastructure, optimizing complex workflows and processing times. The surveillance period records 6-years of satellite observation from September 2016 to December 2021 over the city of Chillan (Chile), an area exposed to urban development and intensive agriculture, where ~80 wells are located. The groundwater flow path spans from the Andes Mountain range to the Pacific Ocean, crossing the Itata river basin in the Chilean central valley. InSAR validation measurements were carried out by comparing the results with the values of continuous GNSS stations available in the area of interest. The performance analysis is based on spatial analysis, time series, meteorological stations data, and static level measurements, as well as hydrogeological structure. The results indicate seasonal variations in winter and summer, which corresponds to the recovery and drawdown periods with velocities > −10 mm/year, and an aquifer deterioration trend of up to 60 mm registered in the satellite SAR observation period. Our results show an efficient tool to monitor aquifer conditions, including irreversible consolidation and storage capacity loss, allowing timely decision making to avoid harmful exploitation.

Flash floods, produced by heavy seasonal rainfall and characterized by high speeds and destructive power, are among the most devastating natural phenomena and are capable of causing great destruction in very little time. In the absence of hydrological data, morphometric characterization can provide important information on preventive measures against flash floods. A priority categorization of hydrographic units in the Cañete River basin was carried out using morphometric analysis together with a weighted sum analysis (WSA) based on a statistical correlation matrix. The delineation of the drainage network was performed based on Digital Elevation Model (DEM) data from the Shuttle Radar Topography Mission (SRTM). The Cañete River basin was subdivided into 11 sub-basins, and 15 morphometric parameters were selected. The priority category (very high, high, and moderate) of each sub-basin was assigned according to the value of the composite factor obtained through WSA. The results of this analysis showed that 26.08% of the total area is under a very high flash flood risk (sub-basins 3, 9, and 11), 38.46% is under a high flash flood risk (sub-basins 5, 7, 8, and 10), and 35.45% is under a moderate flash flood risk. This study concludes that flash floods predominate in sub-basin 3 and that downstream areas present characteristics of river flooding (sub-basins 9 and 11).

Lake temperature has proven to act as a good indicator of climate variability and change. Thus, a surface temperature analysis at different temporal scales is important, as this parameter influences the physical, chemical, and biological cycles of lakes. Here, we analyze monthly, seasonal, and annual surface temperature trends in south central Chilean lakes during the 2000–2016 period, using MODIS satellite imagery. To this end, 14 lakes with a surface area greater than 10 km² were examined. Results show that 12 of the 14 lakes presented a statistically significant increase in surface temperature, with a rate of 0.10 °C/decade (0.01 °C/year) over the period. Furthermore, some of the lakes in the study present a significant upward trend in surface temperature, especially in spring, summer, and winter. In general, a significant increase in surface water temperature was found in lakes located at higher altitudes, such as Maule, Laja and Galletué lakes. These results contribute to the provision of useful data on Chilean lakes for managers and policymakers.