Carlo Tebano

An Ontology Framework for Flooding Forecasting

Floods can cause significant damage and disruption as they often affect highly urbanized areas. The capability of knowledge using and sharing is the main reason why the ontologies are suited for supporting the phases of forecasting in (near-) real time disastrous flooding events and managing the flooding alert and emergency. This research work develops an ontology, FloodOntology for floods forecasting based on continuous measurements of water parameters gathered in the watersheds and in the sewers and simulation models. Concepts are captured across the main involved domains i.e. hydrological/hydraulic domains and SN-based monitoring domain. Classes hierarchies, properties and semantic constraints are defined related to all involved entities, obtaining a structured and unified knowledge-base on the flooding risk forecasting, to be integrated in expert systems.

SISI Project: Developing GIS-Based Tools for Vulnerability Assessment

In the framework of a wider research project, aimed at developing an high performance computing infrastructures in Southern Italy, the SISI project aims at developing customized GIS tools for vulnerable site selection in Italian territory. Vulnerable sites will be defined based on co-presence of different dangerous/vulnerable geographic features in given areas. Morphological and topological criteria will possibly be included in territorial diagnostics.

QMorphoStream: processing tools in QGIS environment for the quantitative geomorphic analysis of watersheds and river networks

The quantitative geomorphic analysis is a powerful tool for the study of geomorphology and landforms, as it provides objective methods to describe the main properties of drainage basins by means of an appropriate set of parameters. Over the last decades, GIS techniques and processing tools have been widely applied to the geomorphic analysis, and specific applications were developed, essentially using commercial software. In the present paper, the first experimental version of QMorphoStream, an originally developed set of processing tools for quantitative geomorphic analysis in QGIS environment, is presented. Besides the obvious advantage in terms of cost reduction, the choice of an open source development environment allowed us to integrate original algorithms with both QGIS built-in functions and processing tools available in the developers’ community.

A SWE Architecture for Real Time Water Quality Monitoring Capabilities Within Smart Drinking Water and Wastewater Network Solutions

The world is facing a water quantity and quality crisis. These global concerns are addressing water sector operators to smart technological solutions that realize the so-called smart drinking water and wastewater networks. Water quality preservation is one of the essential services that smart water utilities have to guaranteed. The water quality monitoring systems include a variety of in situ sensors with several sensor protocols and interfaces. Sensor integration as well as real time sensor readings accessibility and interoperability across the interconnected layers of functionality needed for a comprehensive smart water network solution are the challenges should be tackled. The objective of this research work has been to develop a standardized OGC SWE (Sensor Web Enablement) architecture that enables the integration and real time access to the various continuous and networked sensors can be installed along drinking water and wastewater networks, and real time sensor data browsing, querying and analyzing capabilities across the components of a smart water network solution. Furthermore, a web based geo-console and a QGIS SOS client application have been developed ad hoc for supporting utilities to effectively manage their water treatment and optimize quality-testing processes.

Applying the SWE Framework in Smart Water Utilities Domain

Water leakage, water contamination, inability to detect water quality are some of the problems affecting the existing drinking water infrastructures. Unmanaged wastewater can be a source of pollution, a hazard for the health of human populations and the environment alike. The majority of wastewater infrastructures results in massive run-off and flooding of cities in case of extreme rainfall events. One of the ways to address these problems is by creating smart water utilities, equipping them of smart distributed sensing systems, integrated with advanced information systems. The integration of the diverse networked sensors involved in the water utilities management is not straightforward. The objective of this research work has been to develop a OGC SWE (Sensor Web Enablement) architecture across different applications in the smart water utilities domain, capable of integrating the various networks of in-situ sensors and processing sensor observations into decision support systems, realizing sensor related services and data delivery.

An integrated infrastructure for distributed waste water quality monitoring and decision support

Waste water management plant protection is a major concern for water cycle management entities. The rapid identification and possible localization of anomalous or even malicious waste liquids immission may allow for undertaking pollution risk mitigation actions (e.g. using of ancillary basins) and reduce maintenance costs. Pervasive monitoring of the transport network is hence needed although economic and technical issues prevent its implementation. The SIMONA project is aimed to design, deploy and test an integrated, intelligent, pervasive monitoring infrastructure based on a network of low cost/low maintenance quali-quantitative multisensor nodes. A scalable data processing facility permit the ingestion and the processing of the data stream while a set of models provide for quali-quantitative forecasting increasing the manager situational awareness about the smart infrastructure. All the information is made available via a GIS based Web HCI.