Article thumbnail

MODELKEY: A decision support system for the assessment and evaluation of impacts on aquatic ecosystem

By GOTTARDO S., SEMENZIN E., ZABEO A. and MARCOMINI A.

Abstract

The MODELKEYDSS aims at interlinking and integrating different analytical tools and exposure/effect models in order to evaluate risks posed by pollution to aquatic ecosystems at river basin scale and to identify areas (hot spots) in need of management. In particular, the system helps decision makers and water managers in fulfilling the European Water Framework Directive requirements (EUWFD2000/60/CE), which establishes a framework for Com- munity action in the field of water policy and promotes the achievement of the ‘‘good’’ quality status in all surface waters (rivers, lakes, coastal and transitional waters) by 2015. Currently, the system is under development but a dedicated risk-based DPSIR framework schematizing objectives, outputs and methodologies as well as the overall technical structure of the DSS are already defined. In general, the system is characterized by an ‘‘open configuration’’ able to manage and integrate different types of data, parameters and models and free- ing end users to include their own specific tools. The tiered procedure for evaluating ecological risks is based on two phases accomplishing multiple functions at both river basin and site-specific scales: data exploration and evaluation, quality status classification, identification of causes, economic ana- lysis of water uses, hot spot prioritization, and provision of monitoring recom- mendations. Each phase leads to calculation of flexible Integrated Risk Indices (IRI) by means of Multi Criteria Decision Analysis (MCDA). Specifically, five Lines of Evidence (LOE) for grouping different environmental information are considered: biology, chemistry, toxicology, physico-chemistry, and hydromor- phology. Moreover, environmental information is integrated with socio- economic factors related to different water uses in order to prioritize hot spots to be managed. The results will support decision makers in targeting future manage- ment actions on the most critical ecological endpoints, stressors and hot spots

Publisher: Springer Verlag
Year: 2009
OAI identifier: oai:iris.unive.it:10278/18990
Download PDF:
Sorry, we are unable to provide the full text but you may find it at the following location(s):
  • http://hdl.handle.net/10278/18... (external link)

  • To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.

    Suggested articles