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The project will develop a new framework and innovative technologies for monitoring of the environment. The principal idea of the proposed framework is integration of measurements of environmental variables from in-situ and remote sensing with process-based environmental modelling to provide the best (most cost-effective) estimate of the environmental state and its uncertainty in space and time. The project will develop integrated solutions that consider monitoring of environmental variables in soil, inland water bodies (groundwater, rivers, wetlands and lakes), marine waters and air in one unified system. The framework will be flexible in order to address monitoring at a range of scales, from national and regional environmental monitoring programmes to the monitoring of eco-systems at local scales. Furthermore, the framework can be used to monitor the effects of implementation of new environmental technologies, regionally as well as locally. The proposed framework is also essential for effective detection of trends in environmental variables due to changes in the driving forces such as changes in emissions or climate change. A key issue and innovative component of the project is estimation of the uncertainty of the environmental state. Provision of the uncertainty is important to optimise the monitoring efforts. The project will develop optimisation procedures that consider uncertainty and costs of the monitoring for optimal location and measurement frequency of in-situ sensors in combination with remote sensing information to provide the most cost-effective monitoring strategy. The developed technologies will be demonstrated in a regional-scale case study for integrated monitoring and modelling of nitrogen including atmospheric deposition on land and water bodies, agricultural loading of soils and transformation in hydrological media and marine waters. In addition, a number of minor case studies will demonstrate the value of monitoring and modelling at local scale for selected environmental variables and media.
StatusCurrent
Period01/01/0931/12/12
Financing sourceUnknown
Research programmeUkendt
Amount0.00 Danish kroner
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ID: 2283810