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Content archived on 2024-05-27

Data Integration System for MARine pollution and water quality


Marine monitoring of water quality and pollution is carried out in many different ways around Europe, using either aircraft or ship based observations, satellite data, in situ measurements from automatic buoys or Ferry Box systems, or by various combinations of these methods. Forecasting of physical parameters is carried out more or less operationally, whereas modelling of bio-chemical processes is more on the research level. Coupled physical-biochemical models and oil drift models are in some cases used in semi-operational mode. Previous projects have addressed specific observing methods or information system, which facilitate access to data. Little effort has been put into combining monitoring and forecasting of marine pollution and water quality in one system, and to develop end-to-end service chains, which can operate across national borders. This is the aim of DISMAR.

Develop an intelligent system for monitoring and forecasting of the marine environment to improve management of natural or man-induced pollution crises in coastal and ocean regions of Europe, supporting public administrations and emergency services responsible for prevention, mitigation and recovery of crisis such as oil spill pollution and harmful algae bloom. A prototype will be built for integration of multi-source data and numerical models for use in forecasting and risk assessment. The capability of a prototype will be tested and evaluated by regional applications. The benefit of using satellite data in synergy with other observing systems will be demonstrated in the context of GMES.

Work description:
The main challenge of DISMAR is to develop a system which can
1) provide access to a wide range of data types relevant for the marine environment, both archived and near-real time data;
2) combine observational data with models for improved forecasting and risk assessment;
3) synthesize information from various data sources, sensors and model simulations using data fusion methods;
4) be useful as a decision support and crisis management system.

DISMAR will reach these goals through the following workpackages:
WP100: Project management;
WP200: Requirement analysis and DISMAR prototype design, focusing both on user requirements and technical choices related to GIS and web-system;
WP300: Select and provide existing data, products and models relevant for the project;
WP400: Exploit new observations and models which have significant potential to improve quality of marine monitoring of oil spills and algae blooms;
WP500:Define and implement a structure for data and products, including metadata, useful for all study areas for oil pollution and water quality applications;
WP600: Develop a prototype user-specific decision support system for cost-effective management of crisis due to oil pollution and harmful algae bloom incidents;
WP700: Regional demonstrations of the prototype system and validation by feedback from users;
WP800: Multi-sensor data feature extraction using data fusion techniques, and combinations of model predictions and image data;
WP900: DISMAR results will be disseminated to identified end-users, to the scientific community, through the GMES implementation and to the EU via EEA;
WP1000: Evaluation and assessment.

1: Architecture and design study of the system completed (month 6);
2: Harmonised data and product repository, version 1. Processing chain for existing data/model simulations (month 12);
3: DISPRO-1 developed. Processing chain for new observing capabilities (month 22);
4: Complete validation of DISPRO-1 (month 24);
5: DISPRO-2 developed. Data/products repositories fully populated (month 34);
6: Complete validation of DISPRO-2 and finalize all project tasks (month 36).

Call for proposal

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EU contribution
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Thormoehlensgate, 47

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Total cost
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Participants (15)