Use of isotopes for studying nitrogen processes in a wetland within the Venice Lagoon watershed

The present study is based on the use of isotopes for evaluating the efficiency of nutrients removal of a wetland, in particular nitrogen and nitrates, also between the different habitats present in the wetland. Nutrients like nitrogen and phosphorus, normally distributed as fertilizers, are among the principal causes of diffuse pollution. This is particularly important in the Adriatic Sea, which is frequently subjected to eutrophication phenomena. So it is very crucial requalification of wetland, in which there are naturally depurative processes such as denitrification and plant uptake, which allow the reduction of pollutant loads that flow in water bodies. In this study nutrient reduction is analyzed in the wetland of the Comuna drain, which waters flow in the Venice lagoon. Chemical and isotopical analyses were performed on samples of water, vegetation, soil and sediments taken in the wetlands of the Comuna drain in four different periods of the year and on data of nitrogen and phosphorus concentration obtained by the LASA of the University of Padova. Values of total nitrogen and nitrates were obtained in order to evaluate the reduction within the different systems of the wetland. Instead, the isotopic values of nitrogen and carbon were used to evaluate which process influence more nitrogen reduction and to understand the origin of the nutrient, if it is from fertilizers, waste water or sewage. To conclude, the most important process in the wetland of the Comuna drain is plant uptake, in facts the bigger percentage of nitrogen reduction was in the period of vegetative growth. So it is important the study of isotopes in plant tissues and water residence time, whose increase would allow a greater reduction of nutrients.

Ecological distribution of semi-demersal fishes in space and time on the shelf of Antalya Gulf

In this study we provide a baseline data on semidemersal fish assemblages and biology in a heterogeneous and yet less studied portion of the shelf of Antalya Gulf. The distribution of fish abundance in three transects subjected to different fisheries regulations (fishery vs non fishery areas), and including depths of 10, 25, 75, 125, 200 m, was studied between May 2014 and February 2015 in representative months of winter, spring, summer and autumn seasons. A total of 76 fish species belonging to 40 families was collected and semidemersal species distribution was analyzed in comparison with the whole community. Spatial distribution of fish was driven mainly by depth and two main assemblages were observed: shallow waters (10-25; 75 m) and deep waters (125-200 m). Significant differences among transects were found for the whole community but not for the semidemersal species. Analysis showed that this was due to a strong relation of these species with local environmental characteristics rather than to a different fishing pressure over transects. Firstly all species distribute according to the bathymetrical gradient and secondly to the bottom type structure. Semidemersal species were then found more related to zooplankton and suspended matter availability. The main morphological characteristics, sex and size distribution of the target semidemersal species Spicara smaris (Linnaeus, 1758), Saurida undosquamis (Richardson, 1848), Pagellus acarne (Risso, 1827) were also investigated.

Near Real-Time Detection Of Pipe Bursts in Water Distribution Systems

The research work presented in the thesis describes a new methodology for the automated near real-time detection of pipe bursts in Water Distribution Systems (WDSs). The methodology analyses the pressure/flow data gathered by means of SCADA systems in order to extract useful informations that go beyond the simple and usual monitoring type activities and/or regulatory reporting , enabling the water company to proactively manage the WDSs sections. The work has an interdisciplinary nature covering AI techniques and WDSs management processes such as data collection, manipulation and analysis for event detection. Indeed, the methodology makes use of (i) Artificial Neural Network (ANN) for the short-term forecasting of future pressure/flow signal values and (ii) Rule-based Model for bursts detection at sensor and district level. The results of applying the new methodology to a District Metered Area in Emilia- Romagna’s region, Italy have also been reported in the thesis. The results gathered illustrate how the methodology is capable to detect the aforementioned failure events in fast and reliable manner. The methodology guarantees the water companies to save water, energy, money and therefore enhance them to achieve higher levels of operational efficiency, a compliance with the current regulations and, last but not least, an improvement of customer service.