Objective
In recent years, most of the western European countries have suffered severe droughts as well as extreme flood events. Multi-purpose reservoirs allowed a certain mitigation of the detrimental impacts of these extreme events, which still had significant impact on economic, social and ecological aspects of life. As a result, the need to build better tools for more efficient operation of reservoirs, better protection of people and ecosystems, and ultimately, a better water resources management, have become important issues. It is indeed necessary for the water manager to have as accurate tools as possible to efficiently forecast the evolution of water resource and therefore to manage reservoir to satisfy economic and social interests. In some cases, existing structures have shown their limits and needed to be optimised.
The AIMWATER project has been designed to demonstrate how multi-purpose reservoir management could be improved through integration of Earth Observations data in commonly used decision-support hydrological models. Reservoirs are a key-element of water resource systems in the European Union and World wide. They provide multiple benefits, such as flood control, increased water supplies and maintenance of streamflow levels needed for dilution of pollutants, navigation and recreation. This project will deal with the two most important aspects of multi-purpose reservoir operation: flood control and irrigation water supply, under two contrasting European climates: humid temperate (Northern France) and semi-arid Mediterranean (Southern Portugal).
One of the main objectives of AIMWATER is to improve the performances of the commonly-used hydrological tools in a reservoir operational context. The proposed work is based on the assumption that, the soil moisture information derived from EO data can significantly improve the performance of soil moisture accounting catchment models. A better forecasting tool will result in reduced uncertainties in the information available to the reservoir manager, and thus will lead to a more efficient reservoir operation. The other main objective will be to help reservoir managers assess the potential benefits gained through the use of developed models.
The novel aspect of this project 1ies in its attempts to directly assimilate radar-derived soil moisture information into a hydrological catchment model. The assimilation of these data should provide an efficient tool to minimise the negative social and economic impacts of extreme hydrological events on the communities.
It is expected that the AIMWATER project will result in real improvement in water resources management.
Benefits from the project include: first, from the economic point of view, the mitigation of the detrimental effects of floods or long periods of low flows, which could save billions of ECU worth of damages. Secondly, from scientific point of view, the improvement in model performance gained by assimilating of EO data should in turn improve the cost effectiveness of the existing models which will be adapted in this project.
This is a reasonable and achievable objective, because AIMWATER will build on extensive previous development, in the fields of radar signal treatment and hydrological modelling.
Fields of science
- engineering and technologycivil engineeringwater engineeringirrigation
- natural sciencesearth and related environmental scienceshydrology
- engineering and technologyelectrical engineering, electronic engineering, information engineeringinformation engineeringtelecommunicationsradio technologyradar
- natural sciencesbiological sciencesecologyecosystems
- engineering and technologyenvironmental engineeringnatural resources managementwater management
Topic(s)
Call for proposal
Data not availableFunding Scheme
CSC - Cost-sharing contractsCoordinator
92163 ANTONY
France