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Sediment is the main factor that limits the reservoir lifetime. Therefore, sediment classification is an essential tool for planning and operating reservoir management measures. There has been important development in the hydroacoustic classification of lakebed, especially with linear systems. The main restrictions while using linear hydroacoustic systems for lakebed classification are the shallow penetration in high-frequency applications or the low vertical and horizontal resolution when using low frequencies. With the new developments in the area of echo sounders, parametric systems can achieve high penetration while preserving the high vertical and lateral resolution. To investigate the performance of parametric systems, a new lakebed classification approach was implemented by using a SES2000 Compact. The area studied was the Passauna reservoir in Parana State, Brazil. We used the first echo division method for processing the acoustic data combined with sediment core and grab sampling. The two physical parameters investigated, were the share of the finest fraction (<63 µm) and wet bulk density (WBD). The results showed a high correlation between the primary frequency of 100 kHz (166 µs pulse length) and the physical parameters. Additionally, a significant correlation was observed with the acoustic parameters at 10 kHz frequency. The best correlating acoustic parameter was Attack/Decay (E1´/E1). The gas presence was found to be an important factor determining the penetration depth of the parametric system and the performance of the classification. The advantages of parametric systems, such small directivity and layering effect, represent the major restrictions in sediment classification applications.

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Bubble-mediated transport is the predominant pathway of methane emissions from inland waters, which are a globally significant sources of the potent greenhouse gas to the atmosphere. High uncertainties exist in emission estimates due to high spatial and temporal variability. Acoustic methods have been applied for the spatial mapping of ebullition rates by quantification of rising gas bubbles in the water column. However, the high temporal variability of ebullition fluxes can influence estimates of mean emission rates if they are based on reduced surveys. On the other hand, echo sounding has been successfully applied to detect free gas stored in the sediment, which provide insights into the spatial variability of methane production and release. In this study, a subtropical, midsize, mesotrophic drinking water reservoir in Brazil was investigated to address the spatial and temporal variability of free gas stored in the sediment matrix. High spatial resolution maps of gas content in the sediment were estimated from echo-sounding surveys. The gas content was analyzed in relation to water depth, sediment deposition, and organic matter content (OMC) available from previous studies, to investigate its spatial variability. The analysis was further supported by measurements of potential methane production rates, porewater methane concentration, and ebullition flux. The largest gas content (above average) was found at locations with high sediment deposition, and its magnitude depended on the water depth. At shallow water depth (&lt;10 m), high methane production rates support gas-rich sediment, and ebullition is observed to occur rather continuously. At larger water depth (&gt;12 m), the gas stored in the sediment is released episodically during short events. An artificial neural network model was successfully trained to predict the gas content in the sediment as a function of water depth, OMC, and sediment thickness (R2 = 0.89). Largest discrepancies were observed in the regions with steep slopes and for low areal gas content (&lt;4 L m−2). Although further improvements are proposed, we demonstrate the potential of echo-sounding for gas detection in the sediment, which combined with sediment and water body characteristics provides insights into the processes that regulate methane emissions from inland waters.

Soil degradation and reservoir siltation are two of the major actual environmental, scientific, and engineering challenges. With the actual trend of world population increase, further pressure is expected on both water and soil systems around the world. Soil degradation and reservoir siltation are, however, strongly interlinked with the erosion processes that take place in the hydrological catchments, as both are consequences of these processes. Due to the spatial scale and duration of erosion events, the installation and operation of monitoring systems are rather cost- and time-consuming. Modeling is a feasible alternative for assessing the soil loss adequately. In this study, the possibility of adopting reservoir sediment stock as a validation measure for a monthly time-step sediment input model was investigated. For the assessment of sediment stock in the reservoir, the commercial free-fall penetrometer GraviProbe (GP) was used, while the calculation of sediment yield was calculated by combining a revised universal soil loss equation (RUSLE)-based model with a sediment delivery ratio model based on the connectivity approach. For the RUSLE factors, a combination of remote sensing, literature review, and conventional sampling was used. For calculation of the C Factor, satellite imagery from the Sentinel-2 platform was used. The C Factor was derived from an empirical approach by combining the normalized difference vegetation index (NDVI), the degree of soil sealing, and land-use/land-cover data. The key research objective of this study was to examine to what extent a reservoir can be used to validate a long-term erosion model, and to find out the limiting factors in this regard. Another focus was to assess the potential improvements in erosion modeling from the use of Sentinel-2 data. The use of such data showed good potential to improve the overall spatial and temporal performance of the model and also dictated further opportunities for using such types of model as reliable decision support systems for sustainable catchment management and reservoir protection measures.

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