Decision Support Systems (DSS) are considered innovative tools to cope with climate change related issues and support decision-makers in a sustainable management of natural resources and in the implementation of Integrated Coastal Zone Management (ICZM) and adaptation plans. Involving DSS end users since the beginning of the development of a DSS is recognised as fundamental in order to design a tool that can meet stakeholders needs. However, from the analysis of the risk based DSSs at the regional and/or local scale, emerges a lack of application of participatory approaches, despite their acknowledged relevance to the current scientific literature and regulations. Accordingly, in order to respond to the needs of the DSS end users (i.e. public institutions dealing with coastal management and administration), this paper describes the development of a participative approach for a DSS named DESYCO, aimed at the assessment of climate change related impacts and risks on natural and human systems. The participative approach was carried out by means of the integration of participative moments in the DESYCO framework, the identification of potential end users through a preliminary stakeholder analysis and finally the design, administration and analysis of a questionnaire addressed to the end users identified in the case study area of the North Adriatic Italian coast. 37 potential DSS end users for the case study were identified and addressed by a survey investigating their knowledge about climate change impacts on coastal zone, ICZM strategy and implementation, DSS functionalities. The questionnaire allowed to gain information that both confirmed the validity of the methodology choices of DESYCO and supplied some useful contribution to the selection of further stakeholders. From the results it emerges a lack of knowledge about ICZM and climate change issues. Moreover public institutions ask for short time frame hazard scenarios while the DSS, depending on the available information supplied by models, focuses especially on long term scenarios

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