| Abstract |
The objective of the project is to develop and validate a new decision support system (DSS) for the risk assessment and management for the prevention and/or reduction of the negative impacts caused by human activities on the water/sediment/soil system at river basin scale in fluvial ecosystems. The DSS will combine and integrate environmental and geo-physical data from earth observation systems, on-site sensors and geo-referenced information, advanced computer simulation and graphical visualisation methods and artificial intelligence tools for generating knowledge contributing to the assessment of the ecological impact of hazards in fluvial ecosystems and the design of effective response actions maximising the integrity and safety of the ecosystem and human life.
The new DSS (hereafter also called the RAMWASS DSS) will be the result of the development, integration and validation of the essential technologies provided the project partners:
" A powerful and universal technology for the transfer of high resolution data emanating from modern earth observation systems and on-site sensors into classified and usable information to be ingested as input data for the WASS simulation system (CIMNE)
" Advanced computational methods for the fast and accurate simulation of different hazard situations in the fluvial ecosystems, as well as for evaluating the effect of alternative response actions (UPC, CISM, Univ. of Hannover, Univ. of Lüneburg).
" Innovative ICT tools for data input and the 3D visualisation of the environment hazard simulations (CIMNE)
" An artificial neural network (ANN) based decision model educated using innovative Monte Carlo simulation tools developed by CIMNE. The ANN model will be the kernel of the new integrated RAMWASS DSS for assisting in quasi real time public administrators and emergency services in the risk assessment of hazards in the selected fluvial ecosystem, in the design and management of specific preventive approach and in the identification of mitigation and remediation measures (CIMNE).
A crucial activity of the project will be the in-depth calibration, validation and assessment of the performance, scalability and effectiveness of the DSS in its application to three relevant fluvial ecosystems in Europe: 1) The marsh area of the Doñana Park in Spain; 2) the biosphere reserve Elbe Riverland in the Elbe river valley in Germany and 3) the marshland and lagoons of the Po river delta in Italy. |
