Search Results (13)

Submerged aquatic vegetation plays a fundamental role as a habitat for the biodiversity of marine species. To carry out the research and monitoring of submerged aquatic vegetation more efficiently and accurately, it is important to use advanced technologies such as underwater robots. However, when conducting underwater missions to capture photographs and videos near submerged aquatic vegetation meadows, algae can become entangled in the propellers and cause vehicle failure. In this context, a neurobiologically inspired control architecture is proposed for the control of unmanned underwater vehicles with redundant thrusters. The proposed control architecture learns to control the underwater robot in a non-stationary environment and combines the associative learning method and vector associative map learning to generate transformations between the spatial and velocity coordinates in the robot actuator. The experimental results obtained show that the proposed control architecture exhibits notable resilience capabilities while maintaining its operation in the face of thruster failures. In the discussion of the results obtained, the importance of the proposed control architecture is highlighted in the context of the monitoring and conservation of underwater vegetation meadows. Its resilience, robustness, and adaptability capabilities make it an effective tool to face challenges and meet mission objectives in such critical environments. Full article

Hydropower can have significant impacts on riverine ecosystems due to hydropeaking (i.e., artificial rapid and short-term fluctuations in water flow and water levels downstream and upstream of hydropower stations) that negatively affect downstream fish. However, when it comes to analyzing species habitat use and availability above and below small hydropower plants (SHPPs), studies conducted at the microhabitat scale are scarcer, particularly in Mediterranean rivers. The goal of this study is to assess the seasonal (early and late summer) and size-related (juveniles and adults) microhabitat use by native fish above and below SHPPs. Fish were sampled by a modified point electrofishing procedure, and a multivariate approach was used to analyze microhabitat use and availability data from sites located upstream (reference) and downstream (disturbed) from two SHPPs in northeast Portugal. Cover and water depth were the most influential variables in the use of microhabitat for all species at both the reference and disturbed sites, although some differences in the variable rankings were found. Leuciscids exhibited similar patterns of non-random (i.e., selective) microhabitat use between the reference and the disturbed sites. Overall, the seasonal and size-related patterns in species microhabitat use were similar, with the majority of species displaying seasonal patterns in microhabitat use from early summer to late summer. This study showed that differences in fish microhabitat use between downstream SHPP and upstream reference sites were negligible. Cover might have had a significant role in tempering the effects of detrimental environmental conditions, namely, peaking flows, by providing hydraulic shelter, highlighting the need to maintain riparian vegetation strips and mosaics of submerged aquatic macrophytes, as well as the provision of coarse substrata that can be critical for fish. Future studies are needed to better clarify how different size classes of fish select microhabitats when facing past and present hydropeaking conditions. Full article

The flow in arid and semi-arid regions changes significantly during seasons, letting many vegetation patches develop in different parts of rivers. In the presence of aquatic plants in streams, different flow structures have resulted. When the water level increases in these rivers, the presence of vegetation patches influences the turbulent flow structures, which may considerably change the estimation of key hydraulic parameters. The results of earlier investigations indicated that a wide range of submerged and non-submerged vegetation influences the hydrodynamic features of flows in rivers and streams. In the present investigation, two pools with various slopes of entry and exit sections were used to conduct eight independent experiment runs. In addition, a vegetation patch over the entire pool section has been set up to investigate the effects of the vegetation patch on flow structures in pools. The effect of two slopes of 5 and 10 degrees for both entrance and exit of the pools on flow structure has been investigated. Considering two aspect ratios of 2.0 and 2.7, the distributions of flow velocity, Reynolds normal and shear stresses, turbulence intensities, turbulent kinetic energy (TKE), quadrant analysis, and spectral analysis have been studied at the trailing edge of the vegetation patch along an artificial pool. Results show that, for large entrance and exit slopes (10 degrees), the TKE distribution profiles have no specific form. However, the TKE values have a convex-shaped distribution pattern with the maximum TKE value near the bed when the slopes of the entrance and exit sections of the pool are small (5 degrees). Results showed that both ejections and sweeps govern the turbulence structures and coherent motions at the trailing edge of the vegetation patch along the pool. The geometry, entrance, and exit slopes of the pool have no effect on the validation of power spectral function compared to the presence of a vegetation patch in a flatbed. Full article

Aquatic vegetation appears very often in rivers and floodplains, which significantly affects the flow structure. In this study, experiments have been conducted to investigate the effects of submerged vegetation arrangement patterns and density on flow structure. Deflected and non-bending vegetation is arranged in square and staggered configurations in the channel bed of a large-scale flume. Results showed that the staggered configuration leads to intensified streamwise velocity, turbulence kinetic energy (TKE), and Reynolds shear stress (RSS) compared to the square configuration. When vegetation density is low (λ = 0.04 and λ = 0.07), the produced wake in the rear of the vegetation is more expansive than that with high vegetation density (λ = 0.09 and λ = 0.17) because the velocity in the center of four vegetation elements is lower than that in the middle of two vegetation elements with low vegetation density. Results of TKE in the wake zone of the deflected vegetation indicate that the maximum root-mean-square velocity fluctuations of flow occur at the sheath section (z/H = 0.1) and the top of the vegetation (z/H = 0.4). In the wake zone behind the vegetation elements, the maximum value of the RSS occurred slightly above the interface between deflected vegetation and the non-vegetation layer, showing the Kelvin–Helmholtz instability that is associated with inflectional points of the longitudinal velocity. Within the range of vegetation density in this study (0.04 < λ ≈< 0.23), as the vegetation density increases, the negative and positive values of RSS throughout the flow depth increase. Full article

Aquatic submerged vegetation is widespread in rivers. The transverse distribution of flow velocity in rivers is altered because of the vegetation. Based on the vegetation coverage, the cross-section of the ecological channels can be divided into the non-vegetated area and the vegetated area. In the vegetated area, we defined two depth-averaged velocities, which included the water depth-averaged velocity, and the vegetation height-averaged velocity. In this study, we optimized the ratio of these two depth-averaged velocities, and used this velocity ratio in the Navier–Stokes equation to predict the lateral distribution of longitudinal velocity in the open channel that was partially covered by submerged vegetation. Based on the Navier–Stokes equations, the term “vegetation resistance” was introduced in the vegetated area. The equations for the transverse eddy viscosity coefficient ξ, friction coefficient f, drag force coefficient C_d, and porosity α were used for both the non-vegetated area and the vegetated area, and the range of the depth-averaged secondary flow coefficient was investigated. An analytical solution for predicting the transverse distribution of the water depth-averaged streamwise velocity was obtained in channels that were partially covered by submerged vegetation, which was experimentally verified in previous studies. Additionally, the improved ratio proposed here was compared to previous ratios from other studies. Our findings showed that the ratio in this study could perform velocity prediction more effectively in the partially covered vegetated channel, with a maximum average relative error of 4.77%. The improved ratio model reduced the number of parameters, which introduced the diameter of the vegetation, the amount of vegetation per unit area, and the flow depth. This theoretical ratio lays the foundation for analyzing the flow structure of submerged vegetation. Full article

Aquatic vegetation plays a critical role in aquatic environments and provides various valuable services. To characterize vegetation, vegetation density and flexibility are usually used as parameters, but aquatic vegetation found in nature may have a non-uniform distribution of density in the vertical direction. Studies have shown that this non-uniformity could impact the flow structure and flow resistance. With the aim of studying the effect of vertical variation of submerged vegetation density on the flow resistance and bulk flow characteristics, the hydrodynamics of three types of wooden model vegetation elements were compared in the laboratory. Vegetation models had the same density but different vertical distributions of density. All other influential parameters were kept constant so that any differences in the flow structure and the flow resistance would be attributable to the distribution of density in the vertical direction. The results show that the vertical distribution of submerged vegetation density impacts the flow field, bed shear stress, and flow resistance. There was a 41% difference in the value of the drag coefficient produced by the models. The distance between the bed and the geometrical center of vegetation elements was introduced as a parameter to quantify the effect of the vertical distribution of vegetation. There is a direct relation between this parameter with both the drag and Manning’s coefficients. The findings of this can study help researchers and practitioners use relevant vegetation parameters. Full article

Submerged aquatic vegetation (SAV) is a critical component of aquatic ecosystems. It is however understudied and rapidly changing due to global climate change and anthropogenic disturbances. Remote sensing (RS) can provide the efficient, accurate and large-scale monitoring needed for proper SAV management and has been shown to produce accurate results when properly implemented. Our objective is to introduce RS to researchers in the field of aquatic ecology. Applying RS to underwater ecosystems is complicated by the water column as water, and dissolved or suspended particulate matter, interacts with the same energy that is reflected or emitted by the target. This is addressed using theoretical or empiric models to remove the water column effect, though no model is appropriate for all aquatic conditions. The suitability of various sensors and platforms to aquatic research is discussed in relation to both SAV as the subject and to project aims and resources. An overview of the required corrections, processing and analysis methods for passive optical imagery is presented and discussed. Previous applications of remote sensing to identify and detect SAV are briefly presented and notable results and lessons are discussed. The success of previous work generally depended on the variability in, and suitability of, the available training data, the data’s spatial and spectral resolutions, the quality of the water column corrections and the level to which the SAV was being investigated (i.e., community versus species.) Full article

The main purpose of this study is to investigate the effects of aquatic plants with no leaves (L0), 4 leaves (L4), 8 leaves (L8), and 12 leaves (L12) on the mean streamwise velocity, turbulence structure, and Manning’s roughness coefficient. The results show that the resistance of submerged aquatic plants to flow velocity is discontinuous between the lower aquatic plant layer and the upper free water layer. This leads to the difference of flow velocity between the upper and lower layers. An increase of the number of leaves leads to an increase in the flow velocity gradient in the upper non-vegetation area and a decrease in the flow velocity in the lower vegetation area. In addition, aquatic plants induce a momentum exchange near the top of the plant and increase the Reynold’s stress and turbulent kinetic energy. However, because of the inhibition of leaf area on the momentum exchange, the Reynold’s stress and turbulent kinetic energy increase first and then decrease with the increase in the number of leaves. Quadrant analysis shows that ejection and sweep play a dominant role in momentum exchange. Aquatic plants can also increase the Reynold’s stress by increasing the ejection and sweep. The Manning’s roughness coefficient increases with the increasing number of leaves. Full article

Research of interactions between in-channel vegetation and flow structure is important for the restoration of aquatic ecosystems. This study aims to investigate the impact of the vegetation patch density on the wake structure. We used uniform fiberglass circular cylinders to simulate the non-submerged rigid plant community. In addition, a wide range of vegetation patch densities was considered and a 3D acoustic Doppler velocimeter (ADV) was used to measure local flow velocities. High-density vegetation patches correlated with a high maximum turbulent kinetic energy and a double-peak phenomenon for the lateral distribution. In conclusion, differences between Reynolds shear stresses near the bed surface upstream and downstream of vegetation patches correlate with the vegetation density. Full article

Aquatic vegetation in rivers and coastal regions controls the flow structure in terms of mean velocity and turbulence. The vegetation in the flow affects the transportation of nutrients, microbes, dissolved oxygen, sediment, and contaminants; therefore, the flow characteristics of different types of vegetation layers should be examined in order to understand the effects of vegetation on the flow structure. In this paper, the effect of the submergence ratio and SVF (Solid Volume of Fraction) of a vegetation patch, which was present across half of the channel in a spanwise direction, on the flow structure at the wake region was examined. For this purpose, different submergence ratios with different SVFs were considered in the experiments, and velocity measurements were performed in the wake region of the vegetation layer with an Acoustic Doppler Velocimeter (ADV). According to the results, the effect of different vegetation heights and SVFs on the velocity distribution was obtained. Moreover, inflectional velocity distribution over the cross-section in the wake region of the vegetation layer was obtained, and it was concluded that jet flow occurred in the non-vegetated half of the channel due to the vegetation layer. Full article

Monitoring of aquatic vegetation is an important component in the assessment of freshwater ecosystems. Remote sensing with unmanned aircraft systems (UASs) can provide sub-decimetre-resolution aerial images and is a useful tool for detailed vegetation mapping. In a previous study, non-submerged aquatic vegetation was successfully mapped using automated classification of spectral and textural features from a true-colour UAS-orthoimage with 5-cm pixels. In the present study, height data from a digital surface model (DSM) created from overlapping UAS-images has been incorporated together with the spectral and textural features from the UAS-orthoimage to test if classification accuracy can be improved further. We studied two levels of thematic detail: (a) Growth forms including the classes of water, nymphaeid, and helophyte; and (b) dominant taxa including seven vegetation classes. We hypothesized that the incorporation of height data together with spectral and textural features would increase classification accuracy as compared to using spectral and textural features alone, at both levels of thematic detail. We tested our hypothesis at five test sites (100 m × 100 m each) with varying vegetation complexity and image quality using automated object-based image analysis in combination with Random Forest classification. Overall accuracy at each of the five test sites ranged from 78% to 87% at the growth-form level and from 66% to 85% at the dominant-taxon level. In comparison to using spectral and textural features alone, the inclusion of height data increased the overall accuracy significantly by 4%–21% for growth-forms and 3%–30% for dominant taxa. The biggest improvement gained by adding height data was observed at the test site with the most complex vegetation. Height data derived from UAS-images has a large potential to efficiently increase the accuracy of automated classification of non-submerged aquatic vegetation, indicating good possibilities for operative mapping. Full article

Aquatic vegetation has important ecological and regulatory functions and should be monitored in order to detect ecosystem changes. Field data collection is often costly and time-consuming; remote sensing with unmanned aircraft systems (UASs) provides aerial images with sub-decimetre resolution and offers a potential data source for vegetation mapping. In a manual mapping approach, UAS true-colour images with 5-cm-resolution pixels allowed for the identification of non-submerged aquatic vegetation at the species level. However, manual mapping is labour-intensive, and while automated classification methods are available, they have rarely been evaluated for aquatic vegetation, particularly at the scale of individual vegetation stands. We evaluated classification accuracy and time-efficiency for mapping non-submerged aquatic vegetation at three levels of detail at five test sites (100 m × 100 m) differing in vegetation complexity. We used object-based image analysis and tested two classification methods (threshold classification and Random Forest) using eCognition^®. The automated classification results were compared to results from manual mapping. Using threshold classification, overall accuracy at the five test sites ranged from 93% to 99% for the water-versus-vegetation level and from 62% to 90% for the growth-form level. Using Random Forest classification, overall accuracy ranged from 56% to 94% for the growth-form level and from 52% to 75% for the dominant-taxon level. Overall classification accuracy decreased with increasing vegetation complexity. In test sites with more complex vegetation, automated classification was more time-efficient than manual mapping. This study demonstrated that automated classification of non-submerged aquatic vegetation from true-colour UAS images was feasible, indicating good potential for operative mapping of aquatic vegetation. When choosing the preferred mapping method (manual versus automated) the desired level of thematic detail and the required accuracy for the mapping task needs to be considered. Full article

A passive method for remote sensing of the nuisance green algae Cladophora glomerata in rivers is presented using an unmanned aerial vehicle (UAV). Included are methods for UAV operation, lens distortion correction, image georeferencing, and spectral analysis to support algal cover mapping. Eighteen aerial photography missions were conducted over the summer of 2013 using an off-the-shelf UAV and three-band, wide-angle, red, green, and blue (RGB) digital camera sensor. Images were post-processed, mosaicked, and georeferenced so automated classification and mapping could be completed. An adaptive cosine estimator (ACE) and spectral angle mapper (SAM) algorithm were used to complete the algal identification. Digital analysis of optical imagery correctly identified filamentous algae and background coverage 90% and 92% of the time, and tau coefficients were 0.82 and 0.84 for ACE and SAM, respectively. Thereafter, algal cover was characterized for a one-kilometer channel segment during each of the 18 UAV flights. Percent cover ranged from <5% to >50%, and increased immediately after vernal freshet, peaked in midsummer, and declined in the fall. Results indicate that optical remote sensing with UAV holds promise for completing spatially precise, and multi-temporal measurements of algae or submerged aquatic vegetation in shallow rivers with low turbidity and good optical transmission. Full article