Natural hazard risk analysis in the framework of water safety plans.

The available literature on natural hazard risk analysis focused on the implementation of water safety plans (WSPs) is surprisingly quite poor, despite the significant increase in the number and severity of disasters and adverse effects on drinking water supply systems generated by natural hazards. At the same time, WSPs that conveniently account for natural hazards with a comprehensive approach 'from source to tap' are still scarce as they typically occur at larger spatial scales and adequate prevention, mitigation and adaptation require efficient inter-institutional collaborations. The aim of this paper is to highlight the main bottlenecks for water utilities to include natural hazards in the development of their WSPs. The research adopted a stakeholders-oriented approach, involving a considerable number of water utilities (168), water sectoral agencies (15) and institutions (68) across the Adriatic-Ionian Region through a stepwise process that generated joint SWOT analysis, the development of a decision support system (DSS) focused on WSPs procedures and tabletop exercises. The final outcomes generated strategic documents (REWAS - Adrion Road map for resilient water supply) that highlighted the necessity for efficient cross-sectoral and inter-institutional cooperation in the development of well-founded and robust WSPs to address natural hazard risk analysis for water supply systems (DWSS).

A source classification framework supporting pollutant source mapping, pollutant release prediction, transport and load forecasting, and source control planning for urban environments.

PURPOSE: Implementation of current European environmental legislation such as the Water Framework Directive requires access to comprehensive, well-structured pollutant source and release inventories. The aim of this work was to develop a Source Classification Framework (SCF) ideally suited for this purpose. METHODS: Existing source classification systems were examined by a multidisciplinary research team, and an optimised SCF was developed. The performance and usability of the SCF were tested using a selection of 25 chemicals listed as priority pollutants in Europe. RESULTS: The SCF is structured in the form of a relational database and incorporates both qualitative and quantitative source classification and release data. The system supports a wide range of pollution monitoring and management applications. The SCF functioned well in the performance test, which also revealed important gaps in priority pollutant release data. CONCLUSIONS: The SCF provides a well-structured approach for European pollutant source and release classification and management. With further optimisation and demonstration testing, the SCF has the potential to be fully implemented throughout Europe.