Horizontal bar rack bypass systems (HBR-BS) are characterized by a horizontal bar rack (HBR) with narrow clear bar spacing of 10–20 mm and an adjacent bypass (BS) to efficiently protect and guide downstream moving fish at water intakes. The small bar spacing may lead to operational challenges, such as clogging and high head losses. This study investigated whether combining an HBR with a low-voltage electric field (e-HBR) allows one to increase the clear bar spacing while maintaining a high standard of fish protection and guidance efficiency. To this end, an HBR-BS with 20 mm bar spacing and an e-HBR-BS with 20 and 51 mm bar spacing were tested with spirlin (Alburnoides bipunctatus) and European eel (Anguilla anguilla) in a laboratory flume. The racks were electrified with 38 V pulsed direct current. The protection efficiency of the e-HBR with 51 mm was 96% for spirlin and 86% for eels, which are similar results to those of the HBR with 20 mm. Some eels passed through the e-HBR, but only when they were parallel to the rack. Fish injuries of variable severeness due to the electrification were observed. The results highlight the potential of hybrid barriers for the protection of downstream moving fish. However, fish injuries due to electricity may occur; and reporting applied voltage, electrode geometry, resulting electric field strength and the pulse pattern of the electrified rack setup is necessary to ensure comparability among studies and to avoid injuries.

To study the fish behavioral response to up- and downstream fish passage structures, live-fish tests are conducted in large flumes in various laboratories around the world. The use of multiple fisheye cameras to cover the full width and length of a flume, low color contrast between fish and flume bottom and non-uniform illumination leading to fish shadows, air bubbles wrongly identified as fish as well as fish being partially hidden behind each other are the main challenges for video-based fish tracking. This study improves an existing open-source fish tracking code to better address these issues by using a modified Mask Regional-Convolutional Neural Network (Mask R-CNN) as a tracking method. The developed workflow, FishSeg, consists of four parts: (1) stereo camera calibration, (2) background subtraction, (3) multi-fish tracking using Mask R-CNN, and (4) 3D conversion to flume coordinates. The Mask R-CNN model was trained and validated with datasets manually annotated from background subtracted videos from the live-fish tests. Brown trout and European eel were selected as target fish species to evaluate the performance of FishSeg with different types of body shapes and sizes. Comparison with the previous method illustrates that the tracks generated by FishSeg are about three times more continuous with higher accuracy. Furthermore, the code runs more stable since fish shadows and air bubbles are not misidentified as fish. The trout and eel models produced from FishSeg have mean Average Precisions (mAPs) of 0.837 and 0.876, respectively. Comparisons of mAPs with other R-CNN-based models show the reliability of FishSeg with a small training dataset. FishSeg is a ready-to-use open-source code for tracking any fish species with similar body shapes as trout and eel, and further fish shapes can be added with moderate effort. The generated fish tracks allow researchers to analyze the fish behavior in detail, even in large experimental facilities.

Sediment traps are crucial elements for flood protection in mountain rivers with high sediment transport capacity. Existing structures often interrupt the channel connectivity. Ideally, a sediment trap should be permeable for bed load during non-hazardous floods and ensure sediment retention during hazardous discharges. A new sediment trap concept, fulfilling these requirements was recently developed and tested in a laboratory flume. A guiding channel trough the deposition area is combined with a slot check dam having an upstream bar screen with bottom clearance. This study aims to validate the proposed concept with a finer sediment mixture on an experimental set-up. Furthermore, we provide improved recommendations for bar screen design regarding minimal bar spacing and the range of applicable clearance heights. Optimal bar spacing and clearance heights of the bar screen are determined through individual tests of the bar screen with steady discharges and varying sediment supply intensity. The best performing bar screen configuration is subsequently tested in combination with a slot check dam using a flood hydrograph to simulate the influence of quasi-unsteady discharge. The proposed concept corresponds to a combined mechanical-hydraulic control and works well for a large range of grain sizes, if the bar screen is correctly adapted.