Effect of thermo-velocity barriers on fish: influence of water temperature, flow velocity and body size on the volitional swimming capacity of northern straight-mouth nase (Pseudochondrostoma duriense).

Water temperature and flow velocity directly affect the fish swimming capacity, and thus, both variables influence the fish passage through river barriers. Nonetheless, their effects are usually disregarded in fishway engineering and management. This study aims to evaluate the volitional swimming capacity of the northern straight-mouth nase (Pseudochondrostoma duriense), considering the possible effects of water temperature, flow velocity and body size. For this, the maximum distance, swim speed and fatigue time (FT) were studied in an outdoor open-channel flume in the Duero River (Burgos, Spain) against three nominal velocities (1.5, 2.5 and 3 m s-1 ) and temperatures (5.5, 13.5 and 18.5°C), also including the changes between swimming modes (prolonged and sprint). Results showed that a nase of 20.8 cm mean fork length can develop a median swim speed that exceeds 20.7 BL s-1 (4.31 m s-1 ) during a median time of 3.4 s in sprint mode, or 12.2 BL s-1 (2.55 m s-1 ) for 23.7 s in prolonged mode under the warmest scenario. During prolonged swimming mode, fish were able to reach further distances in warmer water conditions for all situations, due to a greater swimming speed and FT, whereas during sprint mode, warmer conditions increased the swim speed maintaining the FT. In conclusion, the studied temperature range and flow velocity range influence fish swimming performance, endurance and distance travelled, although with some differences depending on the swimming mode. The provided information goes a step forward in the definition of real fish swimming capacities, and in turn, will contribute to establish clear passage criteria for thermo-velocity barriers, allowing the calculation of the proportion of fish able to pass a barrier under different working scenarios, as well designing of the optimized solutions to improve the fish passage through river barriers.

A Step to Smart Fishways: An Autonomous Obstruction Detection System Using Hydraulic Modeling and Sensor Networks.

Stepped fishways are structures that allow the free movement of fish in transversal obstacles in rivers. However, the lack of or incorrect maintenance may deviate them from this objective. To handle this problem, this research work presents a novel low-cost sensor network that combines fishway hydraulics with neural networks programmed in Python (Keras + TensorFlow), generating the first autonomous obstruction/malfunction detection system for stepped fishways. The system is based on a network of custom-made ultrasonic water level nodes that transmit data and alarms remotely and in real-time. Its performance was assessed in a field study case as well as offline, considering the influence of the number of sensing nodes and obstruction dimensions. Results show that the proposed system can detect malfunctions and that allows monitoring of the hydraulic performance of the fishway. Consequently, it optimizes the timing of maintenance on fishways and, thus, has the potential of automatizing and reducing the cost of these operations as well as augmenting the service of these structures. Therefore, this novel tool is a step forward to achieve smart fishway management and to increase their operability.

A step forward in fishway engineering: Validation and implementation of advanced algorithms for effective stepped fishway design, modeling, and retrofitting.

Stepped fishways are the main alternative to allow fish migration in river obstacles. Their design is a multidisciplinary process, where civil engineering meets biology. This can bias the fishway design towards one discipline, which may cause low efficiencies or inadequate solutions. Likewise, it is often challenging to incorporate new discoveries into well-established design principles. To solve these problems, we have developed a novel tool named "Escalas". Escalas is a multipurpose platform for the assisted design, 1D simulation, assessment, and correction of stepped fishways. Escalas architecture allows fishway assessment during different hydraulic scenarios in the river (i.e., different water levels and discharges in the river), automatic dimensioning considering fish's physical needs, the study of any type of stepped fishway, to test solutions for malfunctioning or to assess fishway retrofitting. This is achieved by a modular variable definition during fishway design or definition, which allows multiple combinations of connections within and/or between cross-walls and independent discharge equation definition. This work aims to introduce Escalas to the research and engineering community, describe its algorithms, and show and validate its performance by its use in real and practical cases. Among others, results demonstrate how the tool can reproduce uniform and non-uniform performances on stepped fishways and allows fishway retrofitting to make hydraulic conditions compatible with fish usage during different river scenarios. Therefore, this work represents a step forward in the fishway engineering discipline by applying methods of engineering informatics and providing a technical and scientific base to make engineering decision-making more reliable and accessible as well as to incorporate new advances in fishway research into the engineering design process.

Potamodromous brown trout movements in the North of the Iberian Peninsula: Modelling past, present and future based on continuous fishway monitoring.

Brown trout uses river flow and thermal regimens as main stimuli for initiating and maintaining behavioral reactions such as migration and spawning. Therefore, anthropogenic alterations on these factors may have strong impacts on its populations. The aim of this work is to understand these consequences by assessing potamodromous brown trout movements in the past and present, and to model future responses. For this, brown trout movements in a fishway in the Marin River (Bidasoa basin, Northern Iberian Peninsula) have been monitored from 2008 to 2017. Random forest regression has been used to assess the influence of environmental variables on brown trout movements and to model the response under hypothetical climatic and hydrological scenarios. Results show that brown trout uses the fishway during the whole year, with more upstream movements during the spawning season. The model is able to predict accurately the timing and number of migrants. Its use under hypothetical climate change and flow regulation scenarios shows a delay in the migration time. Therefore, modelling using large time series can be a powerful tool to define management and conservation strategies and prepare compensation measures for future scenarios.