**4. Implications for farmed and wild bivalves**

Coastal water quality is strictly correlated to the food safety of bivalves. In fact, mollusc bivalves are filter feeders, and they can accumulate microbiological and chemical contaminants from surrounding water. Bivalves are generally cultivated or collected along with the coastal areas where their nutrients are abundant and flow from inland water. But the rivers can also discharge faecal bacteria, mostly from untreated wastewater [80]. The malfunctioning of urban waste water treatment plants or their by-pass during the severe rain events can contribute to the release faecal bacteria into the river. This can pose a potential risk to the consumers of bivalves that can accumulate these bacteria.

To avoid any health human risks, according to the EU Regulation No 627/2019 [37] the competent authorities firstly classify the production areas (Class A, B, and C) through specific monitoring campaigns. Then, they continue to control the level of faecal contamination of the bivalves according to the specific surveillance monitoring plan. The bacterium *E. coli* is used as a faecal indicator organism. For the Class A assignment, for example, the samples (80%) shall not exceed 230 *E. coli* per 100 g of flesh and intravalvular liquid. From this Class, molluscs can be collected for direct human consumption. During the sanitary control, if the mollusc health standards are not met, the competent authorities shall close the production areas and/or reclassify them [37].

As a decision support system for the competent authority, several studies have investigated the correlation between the increase of bacterial concentration in molluscs and weather conditions [40–49, 81–83]. The prediction of local precipitation and river discharges have been used as early warning signals for mollusc bacterial contamination [84, 85]. The advantages are multiple—i) to avoid the collection of the potentially contaminated product; ii) to avoid any temporary closing of production areas; iii) to optimise the monitoring surveillance programme; iv) to ensure the health of consumers.

Generally, results demonstrated that the correlation is site-specific and it depends on numerous factors, such as the geographical location, land use, and catchment size.

From ancient times, the Adriatic basin is particularly devoted to the bivalve farming and fishing in the lagoons and along the coasts. Here, the influence of the weather condition and river run-off on the bivalve hygiene condition has been investigated [41, 86, 87].

In the central Adriatic coast of the Marche region, recently, Ciccarelli et al. [88] published the correlation between the concentration of *E. coli* in the natural banks of *Chamelea gallina* and the local precipitation from 2016 to 2020. The results showed that the rainfall events were significant for the increase of *E. coli* (> 230 MPN/100 g) in the molluscs collected from the south sampling points. In the same region, the increase of *Salmonella* spp. detected in bivalves was reconducted in 2015 and 2016 to the severe meteorological events [89].

In the Northern Adriatic Sea, the CADEAU project [90] developed specific indexes to evaluate the potential microbial pollution impact of urban waste water treatment plants on the farmed molluscs in the Municipality of Chioggia (Venice, Italy). It provides indexes of dilution for *E. coli* based on the bacterial decay due to salinity, temperature, and solar radiation [90].

In the following sections, we report some "site-specific" study cases carried out in the Abruzzo region, on the central Adriatic coast of Italy.

## **4.1 The study case of wild clams and farmed mussels in the Pescara province**

In 2021, Colaiuda et al. [41] published the case study in the Pescara province (Abruzzo Region, Italy) that was already detailed in the paragraph 2.2. Here, two production areas of wild clams (*C. gallina*) and one farm of mussels (*Mytilus galloprovincialis*) facing the Pescara River were investigated (**Figure 1**). In **Figure 1**, Pescara 1 and 2 are the production areas of clams, the other is the farm of mussels. Thanks to the CapRadNet project, this study executed a correlation analysis between river discharge trough to the CHyM model, precipitation in the catchment area, and the concentrations of *E. coli* detected in the bivalves during the official monitoring programme. The referring period was from August 1, 2015 to July 31, 2016. The EU reference method to detect *E. coli* was ISO-16649-3 [91]. Results were expressed as the most probable number – MPN per 100 g of flesh and intravalvular liquid of mollusc. Microbiological data were downloaded from the database of the project CAPS2 developed also the informative tool "CAPS2 WEB GIS" useful for the management of the production areas. The classification of the three production areas (Class A) was viewable in the CAPS2 WEB GIS [92]. The competent authority was the unique authorised user to modify the classification and the boundaries of the production areas in the CAPS2 WEB GIS.

The results showed that the concentration of *E. coli* in molluscs increased within 6 days of a river discharge peak (**Figure 2**). Moreover, 87% of cases of high concentration of *E. coli* were consequent to the increased river flow, while 60% of cases to the precipitation. These results suggested that the Pescara River discharge was the potential hydrometeorological driver of *E. coli* in facing molluscs to be further evaluated with specific sampling before and after discharge peak at the river mouth.

#### **4.2 The study case of mussel farm in the Teramo province**

The research project FORESHELL was funded by the FLAG Costa Blu through the 2014-20 EMFF programme of the Abruzzo Region. It is aimed at developing sanitary/weather-environmental predictive technological tools to enhance the efficiency and sustainability of a mussel farm in the Teramo province (Giulianova city, Abruzzo region, Italy) [93]. This production area of *M. galloprovincialis* was classified as Class A, and it is facing the Salinello and Vibrata Rivers far away almost 3 miles from the coast (**Figure 6**).

The hydrological model (CHyM) has analysed the hydrographic basins of the rivers and it has been forecasting the discharge peaks. Before and after these events, a sample of freshwater at the river mouths, and of molluscs and sea water at the farm have been collected for the *E. coli* detection [91]. Preliminary results showed that until September 2021, there were four meteorological events (**Table 1**) that did not cause a peak discharge at the river mouth. Results did not register a significant increase of *E. coli* in the mussels (**Figure 7**). At the same time, the environmental parameters such as sea water temperature, salinity, Chl-a, sea currents, and wave motion are acquired by the satellites and *in situ* probes.

*Coastal Water Quality: Hydrometeorological Impact of River Overflow and High-resolution… DOI: http://dx.doi.org/10.5772/intechopen.104524*

#### **Figure 6.**

*Sampling points at river mouths and at the farm in the Abruzzo region.*


**Table 1.**

*FORESHELL project: Description of meteorological events.*

The web application for data visualisation is under construction, as well as the early warning signalling to the farmer by mail/SMS/WhatsApp. The alerts are referred to the potential faecal contamination of molluscs predicted through hydrological data and other parameters that can damage the farm, such as high temperature and wave motion.

Furthermore, the growth of mussels is constantly monitored with biometric controls.

In conclusion, the first period of project execution was characterised by precipitation scarcity that did not cause any discharge peaks at the river mouths without any presence of *E. coli* in the molluscs. Further analyses are expected to be executed during the rainy period of the autumn and winter seasons.

#### **4.3 Satellite data for bivalves**

Recently, satellite data and maps are increasingly used for the identification of areas intended for aquaculture, for the knowledge of the environmental conditions useful for shellfish farming and fishing, for the prediction of potentially harmful events, etc. The knowledge of parameters such as temperature, salinity, and turbidity give important information to managing bivalve production. For example, data on Chl-a could be useful to understand the food disposal for molluscs or the prediction of algal bloom potential toxic.

The projects AQUACULTURE2000 and VALUE-SHELL analyse satellite data, such as pH, temperature, and CO2, to assess the possible contribution of mussel farming in sequestering carbon from seawater through the biocalcification processes in the northern Adriatic Sea by mitigating the effects of climate change [94].

In 2021, the total suspended matter, temperature, and Chl-a estimated from satellite acquisitions have been used to predict the presence of radioactivity in molluscs [95].

Along the Adriatic coast facing the Abruzzo region where several farms are placed, two pilot studies were conducted. The goal was to calibrate algorithm coefficients, at a local scale, to set up a processing chain that derives accurate concentration maps of chlorophyll and suspended solids from the satellite, as said, taking advantage of the high frequency of revisit time and high spatial resolution of the satellite acquisitions.

The first study estimated Chl-a and sediment dispersions in the sea, derived from Sentinel-2 images, compared with *in situ* data acquired by means of a multiparametric probe in the monitoring stations that Agenzia Regionale per la Tutela dell'Ambiente (ARTA) Abruzzo monthly checks [96]. The Case-2 Regional Coast Color processor in ESA SNAP software was used, applying the C2RCC-Nets algorithm [97], whose parameters have been set using *in situ* measurements, specifically the salinity and temperature variables. This preliminary study provided encouraging results with only four sampling dates—for example, the concentration map of TSM of 09/03/2018 is reported (**Figure 8**).

In the second study [98], the authors developed the Water Color Data Analysis System (WC-DAS), a tool for the operational generation of maps and indicators useful in the monitoring of water quality. The tool, in its first release, allows the processing of satellite optical multispectral data acquired by Sentinel-3 OLCI, Sentinel-2 MSI, and Landsat-8 OLI sensors, using the algorithms Case 2 Regional CoastColour (C2RCC) [97] and Atmospheric Correction for OLI "lite" (ACOLITE) [99].

The tool was tested in the central Adriatic coastal zone, setting the local parameters according to the *ad hoc in situ* sampling campaign that ARTA Abruzzo carried out along the Abruzzo coast, simultaneously with the satellites overpasses (example in **Figure 9**).

The results show performances of calibrated algorithms and the data system's suitability to contribute to the production of monitoring maps and indicators,

*Coastal Water Quality: Hydrometeorological Impact of River Overflow and High-resolution… DOI: http://dx.doi.org/10.5772/intechopen.104524*

informing domain-specific decision-making and supporting services for integrated coastal zone management.

#### **Figure 8.**

*Concentration maps of Total Suspended Matter along Abruzzo coast in the Adriatic Sea, as elaborated with the C2RCC processor from Sentinel-2 imagery of 09/03/2018.*

#### **Figure 9.**

*Turbidity, Total Suspended Matter, Chlorophyll-a maps along Abruzzo coast, facing Pescara river mouth, as derived from Water Colour Data Analysis System Tool.*
