Editorial Feature

Underwater Drones Could Perform Fish Surveys in Reservoirs

Reservoirs are artificial ecosystems with several benefits but are also significant contributors to severe environmental changes in inland waterways. The rise in water level and stratification results in dramatic environmental changes, particularly in the reservoir's lower levels, resulting in static, anoxic, and uniform ecosystems.

Underwater Drones Could Perform Fish Surveys in Reservoirs

Image Credit: iurii/Shutterstock.com

Gillnets positioned at various levels of the water column, telemetry, environmental DNA, and hydroacoustic have all been utilized to determine the vertical distribution of fish in reservoirs. These tools enable significant advancements in aquatic ecology, but they have biases and limits like any other instrument. Small Remotely Operated Vehicles (ROVs) are yet to be thoroughly tested in reservoirs as a technique for simultaneously capturing both abiotic and biotic data.

ROVs are submersible robotic devices that can be controlled in real-time from the surface. Each ROV has its own technical characteristics depending on the manufacturer and the intended usage, with a wide range of power, autonomy, depth, attachments, and price.

However, this equipment consists of a camera set in an impermeable container with propellers for maneuvering, which is connected to a cable on the surface that transmits video and telemetry information. Underwater drones are small ROVs that weigh between −3 and 20 kg. The use of ROVs for non-destructive fish visual surveys is a fast-expanding field.

The study's primary goal is to offer a new method for visually surveying freshwater reservoirs using underwater drones (small ROV class) for environmental data and fish cataloging.

Researchers also detail the benefits, drawbacks, and restrictions of using underwater drones in reservoirs for the first time. The hope is that these results will contribute to improved understanding of the processes that control fish distribution in changing settings as well as the development of this innovative non-invasive technology for inland water environmental monitoring.


Figure 1 illustrates how the transects followed the margin slope, starting in the profundal zone and climbing in a zigzag pattern to the littoral zone.

Schematic model showing the dimensions and limits (in meters) of the zones along the steep slopes (littoral, transition and profundal), physicochemical water stratification column (eplimnion, metalimnion and hypolimnion) of the Lajes Reservoir during the summer.

Figure 1. Schematic model showing the dimensions and limits (in meters) of the zones along the steep slopes (littoral, transition and profundal), physicochemical water stratification column (eplimnion, metalimnion and hypolimnion) of the Lajes Reservoir during the summer. Image Credit: Guedes and Araújoal, 2022

Figure 2 shows how the operation was carried out from a boat by two personnel, one in charge of video and the other in the care of the cables.

Remotely operated vehicle model Genneino T1 being operated from a boat in the Lajes Reservoir, Rio de Janeiro State, Brazil.

Figure 2. Remotely operated vehicle model Genneino T1 being operated from a boat in the Lajes Reservoir, Rio de Janeiro State, Brazil. Image Credit: Guedes and Araújoal, 2022


PERMANOVA (P = 128.8, P <0.001) revealed significant variations in environmental variables (physicochemical + habitat) across the vertical zones, but no significant differences in periods (day vs. night) or interactions zone vs. period (Table 1).

Table 1. Results of two-way ANOVA on aligned ranks transformation (Anova ART) and the permutational analysis of variance (PERMANOVA) comparing the environmental variables between the vertical zones and periods. Source: Guedes and Araújoal, 2022

Anova ART Zone Period Zone × Period Post-hoc test
Temperature (°C) 275.2*** 3.12 4.2 Lit > Tra > Pro
Dissolved oxygen (mg/L) 488.1*** 3.63 10.7*** Lit > Tra > Pro
Depth (m) 981.1*** 7.2** 0.4 Lit < Tra < Pro
Leaves (%) 48.1*** 0.7 1.11 Lit = Tra > Pro
Branchs (%) 80.2*** 4.6 7.4** Lit > Tra > Pro
Clay (%) 0.5 1.5 1.1 Lit = Tra > Pro
Rocks (%) 17.5*** 0.9 2.2 Lit = Tra > Pro
PERMANOVA Df Pseudo-F R2  
Zone 2 128.8 *** 0.49 Lit ≠ Tra ≠ Pro
Period 1 1.6 > 0.01  
Zone x Period 2 2.19 > 0.01  
Residuals 254   0.49  
Total 259   1  


**p < 0.01, ***p < 0.001

The first PCA axis (57.6% of the explained variation, Figure 3) illustrated the environmental variations between the different vertical zones.

Ordination diagram from the two first axes of principal component analysis (PCA) on environmental variables in the three zones of the steep slope margins of the Lajes Reservoir, Brazil.

Figure 3. Ordination diagram from the two first axes of principal component analysis (PCA) on environmental variables in the three zones of the steep slope margins of the Lajes Reservoir, Brazil. Image Credit: Guedes and Araújoal, 2022

A total of 442 specimens were found, divided into five orders, six families, and 12 species (Figure 4 and 5).

Photographic records of different species of fish produced by the underwater drones in the Lajes Reservoir, Rio de Janeiro State, Brazil.

Figure 4. Photographic records of different species of fish produced by the underwater drones in the Lajes Reservoir, Rio de Janeiro State, Brazil. Image Credit: Guedes and Araújoal, 2022

Boxplots of fish occurrence in different vertical zones (m) along the steep slopes of the Lajes Reservoir. Red circles indicate the mean depth of the occurrences. Only species with relative abundance?>?3% of the total number of fish were plotted.

Figure 5. Boxplots of fish occurrence in different vertical zones (m) along the steep slopes of the Lajes Reservoir. Red circles indicate the mean depth of the occurrences. Only species with relative abundance > 3% of the total number of fish were plotted. Image Credit: Guedes and Araújoal, 2022

Vertical zones (PERMANOVA, F = 25.5; P <0.001) and periods (P = 4.7; P <0.01, Table 2) showed differences in the fish assemblage structure.

Table 2. Results of PERMANOVA for comparing differences in the fish assemblage structure between the three vertical zones and two periods. Source: Guedes and Araújoal, 2022

Source df MS Pseudo- F R2
Zone 2 2.33 25.54*** 0.16
Period 1 0.43 4.74** 0.015
Zone × period 2 0.18 2.06 0.013
Residuals 254 0.09   0.8
Total 259      
Pair wise test for the fixed factors
Zone t   Period t
Littoral × transition 28.0***   Day × Night 4.02**
Littoral × profundal 31.1***      
Transition × profundal 1.52      


df degree of freedom, MS Mean square; R2 coefficient of determination

Figure 6 illustrates that species richness was expected to be the highest in the littoral, followed by transition and profundal zones, based on extrapolated species diversity based on Hill numbers (q = 0).

Rarefaction/extrapolation (R/E) of fish species performed with iNEXT for the studied zones of the Lajes Reservoir, with 95% confidence intervals.

Figure 6. Rarefaction/extrapolation (R/E) of fish species performed with iNEXT for the studied zones of the Lajes Reservoir, with 95% confidence intervals. Image Credit Guedes and Araújoal, 2022


While using ROVs, researchers must first examine the equipment's particular impacts, such as varying light intensities and artificial noise, as well as the vehicle's speed, size, and depth of operation. The fish in the Lajes Reservoir react differently to the presence of the mini ROV, with some ignoring it while others appear to be drawn to it.

The fish assemblages recorded with the ROV differed significantly from those previously observed using gillnets in the Lajes Reservoir. The performance of video transects with ROV can be facilitated by hydro-environmental factors and prior knowledge of the reservoir ichthyofauna.

Introducing small, low-cost ROVs (starting at roughly $3,000) has made environmental monitoring more accessible. Other attachments, like suction samplers for benthic fauna, robotic arms, optical systems, sonar to measure zooplankton, and hydrophones, make the ROV a versatile instrument that may complement or even replace traditional means of gathering environmental data.

The profundal zone has a less organized fish assemblage, with a focus on the presence of P. lateristriga, a shallow-water native species that was unexpectedly found exploring the deep reservoir sections (at a depth of 38 m). This study reveals a diverse range of species' occupancy on the steep slopes of the Lajes reservoir, as well as the lack of fully unoccupied habitats.

As a result, fish use the reservoir littoral zone more for spawning, feeding, and refuge, resulting in greater fish quantity and diversity. The causes for fish migration to littoral zones at night are largely unclear. However, resting, bioenergetic efficiency, food chances, and predator avoidance appear to be the primary reasons. Changes in species richness during the diurnal cycle are eventually influenced by these variables.


Researchers are the first to propose using tiny ROVs to monitor fish in reservoirs. Along the steep slopes of the reservoir, researchers discovered a vertical gradient in environmental parameters, as well as different fish assemblage patterns. Scientists found that in the littoral zone, there was a higher quantity and diversity of fish, which was linked to increased environmental variability.

The biases, problems, and potential of using ROV in freshwater systems were also highlighted. Due to the prevalence of lentic circumstances, great water transparency (up to 6 m—Secchi's Disc), and substantial existing information of the ichthyofauna, the Lajes Reservoir appeared to be an appropriate case study.

The lack of research using ROVs in inland seas, in general, continues to obstruct the development of reliable procedures, protocols, and comparisons. This chasm is what makes this method so the potential for freshwater discussions and discoveries. Underwater drones can be a useful environmental instrument for collecting abiotic and biotic data at the same time, especially in deep reservoirs with a variety of ecosystems, leading in improvements in environmental monitoring.

Journal Reference

Guedes, G. H. S., & Araújo, F. G. (2022). Underwater drones reveal different fish community structures on the steep slopes of a tropical reservoir. Hydrobiologia, pp. 1–12. Available Online: https://link.springer.com/article/10.1007/s10750-021-04790-9.

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