To obtain a high-quality computational grid, needed to resolve the boundary layer properly, specific criteria need to be met as for the spatial resolution near boundaries (flume walls, rough bed elements, and mussel surface). A progressive coarsening then allows limiting the number of total computational cells (Figure 4). Preliminary results are shown, for demonstrative purposes, in terms of water velocity, pressure, and wall shear stress (Figures 5-7).

The next steps include comparing the model results with measured velocity profiles to validate the numerical model, then extending the study to a set of mussels disposed with different spatial density and analysing the hydrodynamic transport associated to the filtering activity of mussels, which they achieve through the incurrent and excurrent siphons located on their upper side.

2. ANALYSIS OF EFFECTS OF HYDRODYNAMIC PROCESS ON RIVER ECOSYSTEMS COMMUNITIES

Assessment and validation of mussels’ behavioral endpoints as potential indicators of hydrological stressors

WP2 – MONITORING: Task 2.3 

WP3 – PROCESSES: Task 3.3

Introduction

The first stage in sustainable ecosystem management is the detection of disturbance and of its impact in the target ecosystem. Environmental monitoring increasingly makes use of indicator species, that is, easily monitored organisms whose conditions reflect those of the environment where they are found. The use of these indicator species is based on the hypothesis that they can provide a response to environmental change that reflects its effects on the entire biotic community. Although the use of indicator species in environmental monitoring is reliable and cost-effective, it is quite challenging to select a specific indicator and then identify its relation with the specific stressors. The usefulness of the indicator species will strictly depend on the selected indicator species and on the selected response variables. The most suitable species to act as indicators are those with a high sensitivity to changes in their environment, while the most suitable variables are those showing an efficient and reliable relationships between the indicator species and the underlying processes of interest. Freshwater mussels (Fig 1), which are among the most sensitive freshwater organisms, also fulfill the requests for reliability, robustness, responsiveness and reproducibility that characterize a good indicator. Long used as indicators of good water quality, they have not yet been applied to detect physical disturbance factors, such as temperature and hydrological regime variations. The increasingly devastating hydrological changes affecting our rivers require monitoring methods based on rapid responses, such as those provided by behavioral reactions of mussels. The assessment of detection limits for stressors and of the exposure time needed to elicit an alarm response is necessary in order to understand the sensitivity of a sentinel-based behavioural system and its applicability to water monitoring. Valvometric responses were tested in response to chemical pollution, changes in temperature or light intensity, particulate suspended solids. However, in spite of the well-documented sensitivity of mussels to hydromorphological changes that alter flow regime, an evaluation of the eligibility of behavioural responses for detecting hydrodynamic stressor is still lacking.

Aims and ongoing activities

The present study will test 4 sublethal behavioural endpoints with the aim of adapting the use of animal-attached remote-sensing technology to assess of hydrological ecosystem impacts and to define vital minimum outflow (DMV) for safeguarding communities and ecosystem services. To this end, we sampled mussels from different environments (Fig. 2) and we are now testing the responses of mussels under controlled conditions (Fig. 3). Several experiments were conducted to record both the basic behavior of mussels in the absence of stressors and that in response to changes in flow (Fig. 4, 5 and 6).

Preliminary results 

Preliminary results suggest that during transients and in the presence of sediment transport, mussels change their behavior, showing an increase of their valve opening-closure frequencies and amplitudes (Fig. 6). These results are encouraging to support the use of mussels as biosensor also in their natural habitat (rivers or lakes) to monitor the occurrences of natural events involving hydro-morphological variations, as floods.

3. ANALYSIS OF EFFECTS OF HYDRODYNAMIC PROCESS ON RIVER ECOSYSTEMS COMMUNITIES (Palermo University Laboratory)

Activities:

Workpackage WP2 –Tasks 2.3

Workpackage WP3 – Task 3.3

In the ambit of these activities, experiments have been conducted a straight laboratory flume constructed at the Hydraulics laboratory – University of Palermo (Italy).

During the experiments the valve movements of mussels were monitored, as shown in Fig. 1. The Hall element sensor equipped with a serial cable were attached to the mussel valves (Fig. 2). As an example, Figure 2 shows a single mussel with sensor for the valve movements monitoring.

The aim of the aforementioned experiments was to monitor the mussel’s behavioural response due to the variation of flow discharge and in presence of sediment transport, as during a flood.

In the absence of hydrodynamic stresses (standard conditions) the valve movements were also monitored when the mussels were kept in an aquarium with dechlorinate-aerated water (Fig. 3). The aim of such an experiment was to monitor the mussel’s behavioural response due to walking movements and/or filtration.

The collected data have been used to analyze the mussels’ behavioural response to hydrodynamic stresses. She statistical analysis of collected signals was performed and a Matlab code was used to estimate the frequency and the amplitude of the mussels’ response. As an example, Fig. 4 reports the average signal measured during an experimental run characterized by a sudden increase of flow rate after 4 hours from an initial value of Q2, lower to that corresponding to incipient sediment motion, to Q6, with high sediment transport.

As Figure 5 shows during the aforementioned experimental run, the mussels modify their behaviour identifying a “transition” behaviour after the sudden increase of sediment transport.

Workpackage WP4 –Tasks 4.3

In order to analyze how the bed roughness and the presence of the animal on the bed can affect the kinematic characteristics of the flow, experimental tests have been carried out in the straight gravel-bed channel present at the hydraulic laboratory of the University of Palermo, both in the absence and in the presence of one mussel in the center of the channel (Figure 6). During the tests the instantaneous values of the longitudinal, transverse and vertical velocity components were measured in the conditions shown in the Figure 7. These data have been used to estimate the flow velocity field and the flow turbulent structure along the channel. As an example, Figure 8 shows the contour map of the preliminary results (resultant transversal velocity) obtained at section corresponding to the location of mussel’s siphons (not alive mussel). These experimental data will be also used to calibrate the 3D simulation model.

4. DEVELOPMENT OF A SYSTEM MADE OF A RADAR WITH 2 FREQUENCY-SCANNING ANTENNAS (ONE RECEIVING AND ONE TRANSMITTING)

In the context of WP2 (Monitoring) and WP3 (Processes), UNIPG developed a system made of a radar with 2 antennas: one receiving and the other one transmitting.

The Radar is mounted on a tilting plane. The tilt angle is automatically detected with the use of an accelerometer (ADXL345 from Analog Devices), located near the receiving antenna. The radar is battery powered with 7.4 LiPo rechargeable battery.

The radar controller is based on a Raspberry Pi 3, powered with a powerbank.

The low frequency signal is acquired with the usage of a USB oscilloscope (Picoscope 2206B), controlled with the Raspberry Pi.

The acquired data can be processed directly with the Raspberry Pi or transferred to a PC for offline processing. The Raspberry is remotely controlled with an SSH client, the file is transferred wirelessly to the PC with a SFTP client.

All the software developed for the radar (Raspberry controller and data analysis) is public and available on GitHub.

Radar controller software: https://github.com/giocic2/hydro-radar-controller

Data analysis software: https://github.com/giocic2/hrc-data

test 1 – electromechanical rotating target

The radar was used to scan a grid of points on the ground. Each point is a pair of coordinates that corresponds to a specific beam direction (horizontal coordinate) and a specific tilt angle (vertical coordinate). The beam direction is selected controlling the frequency of the transmitted signal. The tilt angle is controlled manually and automatically measured with an accelerometer.

The picture shows where is the peak of the received power, that correctly matches the target position.

Experiment procedure:

• 1) Fix tilt angle

• 2) Fix beam direction

• 3) Acquire baseband signals

• 4) Estimate received power

• 5) repeat 3), 4) changing beam direction

• 6) repeat 2), 3), 4), 5) changing tilt angle

test 2 – vibrating target

The radar was also used for a second test with a vibrating target. The experiment was performed similarly to the first test.

The final picture shows where is the peak of the received power, that correctly matches the target position.

Field

1. INSTALLATION OF THE PHOTOGRAPHIC MONITORING SYSTEM OF THE PAGLIA RIVER USING LS-PIV PROCESSING

In the context of WP2 (Monitoring) and WP3 (Processes), CNR developed a photographic monitoring system and LS-PIV processing.

The final goal of the monitoring system is to provide photographic data for the measurement of the surface velocity of a river. Further requirements are the automatic high-frequency data acquisition, the data transmission in real time and an autonomous power supply.

The identified site for the monitoring system installation is the Adunata Bridge in Orvieto, on the Paglia River. Specifically, the instrumentation has been installed on the parapet external side, looking downwards the river flow.

According to such requirements, it has been designed and realised a modular system composed of A) acquisition module equipped with a camera, B) surveying webcam, C) remotely controlled management module, D) power module and E) solar panel (Figure 1).

The adopted camera of the acquisition module is a 32 MPx mirrorless Canon EOS M6 mark II, equipped with 24 mm focal lens, set in autofocus mode. This camera can acquire full resolution image bursts at 14 fps. The surveying webcam is a HikVision 4K IP camera equipped with infrared sensor. The management module is composed of a Raspberry-Pi 4 that controls the photo acquisition using the gPhoto2 software released with GNU LGPL license. Additionally, the management module is equipped with a 4G modem that allows remotely access to the system. The power module includes a back-up battery and a solar panel.

INSTALLATION OF THE MONITORING STATION

On 10 June 2021, the modular photographic monitoring system has been anchored to the bridge. The installation involved a complex intervention that required hanging operations using ropes and individual protection equipment (Figure 2).

During the intervention, it was arranged a temporary network of geocoded ground control points (GCPs) for the orthorectification of the acquired photographs (Figure 3).

On 1 September 2021, it was conducted a maintenance intervention of the monitoring system during which a UAV survey was conducted for the realisation of a high-resolution DSM and an orthophoto (Figure 4).

PRELIMINARY RESULTS

In this section, the first preliminary results obtained using LSPIV technique are briefly presented. The processed data concern a single burst at 14 fps lasted one second acquired on 7 September at 11 am.

The LSPIV processing has been conducted using LAMMA software (https://github.com/niccolodematteis/LAMMA), which has been developed by the Geohazard Monitoring Group. LAMMA uses an optimised algorithm that reduces processing times and outlier occurrence. Its adoption for LSPIV applications is still in an experimental phase.

LAMMA’s output is a map of planar displacement vectors (expressed in px) lying on the image plane (Figure 5). The results geocoding is done by applying a transformation matrix that assigns to every 2D image pixel georeferenced 3D world coordinates. This allows to convert the measured displacements in metric units (Figure 6). For the geocoding operation, it was adopted the DSM acquired during the UAV survey resampled at 1 m resolution. It has been estimated a georeferencing uncertainty <1 m.

2. SURFACE VELOCITY ESTIMATE THROUGH IMAGE PROCESSING

In the framework of WP1-task 2.1, an image processing procedure to evaluate the surface velocity of the flow, preliminarily calibrated at University of Palermo also by means of laboratory tests, has been applied in river sites. A first application has been conducted along a river reach of the Oreto river (Sicily) (Figure 1). Figure 2 reports the estimated spatial distribution of the free surface velocity in the examined area (area delimited by the red dashed of Figure 1) and Figure 3 reports the horizontal profile of the estimated free surface velocity along the transect A.

Fig. 2 Estimated surface flow velocity distribution V (m/s) in the examined area.

3. DEVELOPMENT AND APPLICATION OF TECHNIQUES FOR THE MEASUREMENT AND EVALUATION OF THE SEDIMENT TRANSPORT2.

To achieve the main goals of ENTERPRISING (DEVELOPMENT AND APPLICATION OF TECHNIQUES FOR THE MEASUREMENT AND EVALUATION of THE SEDIMENT TRANSPORT), it is essential to tests all the methods out of the laboratory in the real situation. PAGLIA river is the first river that our group is interested in working on it. Three zones have been chosen along the river for field study.

Monitoring the sediment transportation by using colored sediment in floodplain

To understand the capacity of erosion in the floodplain (Riverside) area in Barca-Vecchia location, some squares (1*1 meter) are colored on the riverside. During the Flood, some sediments move and after the flood by disappearing colored sediment on the squares, it is easy to calculate the percentage of erosion in this area.

Grain size curve by using photogrammetry

One of the new methods which replicate the old method for providing the grain-size curve is Photogrammetry by using the BaseGrain software. This software can realize the grain size of sediments on the pictures. The result of this method for riverside in Barca-Vecchia shows we can trust this method.

Turbidimeters and hydroprofilometer

New tools with more accuracy can help us to collect data closer to the real data. Modern TURBIDIMETERS lets us do accurate, reliable turbidity measurements, and HYDROPROFILOMETER measures the velocity and water level, and temperature in shallow water by ultrasonic sensors. These tools passed some tests and now, they are ready to install in Ponte-Adunata zone.

Temperature bar

Some studies have shown the changing the temperature in each layer of riverbed can tell us about erosion in this cross-section. If some vertical sensor bars install on the riverbed and receive data remotely, we can observe the erosion live! Based on the previous investigation on this issue, we found suitable spots to install the bars in Barca-Vecchia.

Mussel and climatic disturbances

Mussels have been used as biological monitors since 1986 in Germany, and nowadays many countries worldwide use them in real-time monitoring systems to detect disturbances in ecosystems, including surface water, groundwater, effluent, and drinking water. Valvometry uses the mussels’ capacity to open and close their shells when exposed to abnormal conditions as an alarm to indicate possible disturbances in the environment. Hall sensor technologies and Arduino software were used to recording the valve movements of mussels. By collecting these signals in some different hydraulic conditions, and turn them to frequency and amplitude, it would be easy to realize the mussel’s behaviour in each hydraulic condition. In Barca-Vecchia and Ponte-Adunata some places have been chosen for cages of mussels on two sides of the river.

Refinement of the entropy-based methodology

UNITN group developed and applied the entropy (Shannon-Tsallis) pdf distribution of the resting time and the length in ordinary bedload based on Einstein’s theory. The comparison of two entropy distribution (Shannon-Tsallis) illustrates that the results of both methods are close. The following graphs show the pdf distribution of resting time made by Luigi and Hassan using Einstein’s theory (fig. Right) and the results of the entropic distribution of Tsallis of resting time (fig. Left), both for different values of sediment discharge (qs).