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.

Digitalization and real-time control to mitigate environmental impacts along rivers: Focus on artificial barriers, hydropower systems and European priorities.

Hydropower globally represents the main source of renewable energy, and provides several benefits, e.g., water storage and flexibility; on the other hand, it may cause significant impacts on the environment. Hence sustainable hydropower needs to achieve a balance between electricity generation, impacts on ecosystems and benefits on society, supporting the achievement of the Green Deal targets. The implementation of digital, information, communication and control (DICC) technologies is emerging as an effective strategy to support such a trade-off, especially in the European Union (EU), fostering both the green and the digital transitions. In this study, we show how DICC can foster the environmental integration of hydropower into the Earth spheres, with focus on the hydrosphere (e.g., on water quality and quantity, hydropeaking mitigation, environmental flow control), biosphere (e.g., improvement of riparian vegetation, fish habitat and migration), atmosphere (reduction of methane emissions and evaporation from reservoirs), lithosphere (better sediment management, reduction of seepages), and on the anthroposphere (e.g., reduction of pollution associated to combined sewer overflows, chemicals, plastics and microplastics). With reference to the abovementioned Earth spheres, the main DICC applications, case studies, challenges, Technology Readiness Level (TRL), benefits and limitations, and transversal benefits for energy generation and predictive Operation and Maintenance (O&M), are discussed. The priorities for the European Union are highlighted. Although the paper focuses primarly on hydropower, analogous considerations are valid for any artificial barrier, water reservoir and civil structure which interferes with freshwater systems.

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.

An Open Surface Drifter for River Flow Field Characterization.

The continuous observation of flows is required to assess a river's ecological status, to allocate irrigation withdrawals, to provide sustainable hydropower production and to plan actions as well as develop adaptive management plans. Drifters have the potential of facilitating the monitoring and modeling of river behavior at a fraction of traditional monitoring costs. They are floating objects equipped with sensors able to passively follow the movements of water. During their travel, they collect and transmit information about their movement and their surrounding environment. In this paper, we present and assess a low-cost (<150 EUR) customizable drifter developed with off-the-shelf components. The open drifter is capable of handling the majority of use cases defined in the specialized literature and in addition it offers a general river flow characterization toolkit. One of the main goals of this work is to establish an open hardware and software basis to increase the use of drifters in river studies. Results show that the proposed drifter provides reliable surface velocity estimates when compared to a commercial flow meter, offering a lower cost per data point and in contrast to traditional point measurements it can be used to identify and classify large-scale surface flow patterns. The diverse sensor payload of the open drifter presented in this work makes it a new and unique tool for autonomous river characterization.

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.

Man-made flows from a fish's perspective: autonomous classification of turbulent fishway flows with field data collected using an artificial lateral line.

The lateral line system provides fish with advanced mechanoreception over a wide range of flow conditions. Inspired by the abilities of their biological counterparts, artificial lateral lines have been developed and tested exclusively under laboratory settings. Motivated by the lack of flow measurements taken in the field which consider fluid-body interactions, we built a fish-shaped lateral line probe. The device is outfitted with 11 high-speed (2.5 kHz) time-synchronized pressure transducers, and designed to capture and classify flows in fish passage structures. A total of 252 field measurements, each with a sample size of 132 000 discrete sensor readings were recorded in the slots and across the pools of vertical slot fishways. These data were used to estimate the time-averaged flow velocity (R2 = 0.952), which represents the most common metric to assess fishway flows. The significant contribution of this work is the creation and application of hydrodynamic signatures generated by the spatial distribution of pressure fluctuations on the fish-shaped body. The signatures are based on the collection of the pressure fluctuations' probability distributions, and it is shown that they can be used to automatically classify distinct flow regions within the pools of three different vertical slot fishways. For the first time, field data from operational fishway measurements are sampled and classified using an artificial lateral line, providing a completely new source of bioinspired flow information.