Integration of remote sensing in water quality assessment and monitoring
Researchers: |
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A. Nonomura |
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Organisations: |
Department of Water Resources, ITC |
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Kagawa University, Japan |
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Funding: |
ITC IRF |
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Period: |
2005 – 2009 |
Background
The impact of humans on the water cycle and terrestrial water and ecosystems is of increasing importance, especially in relation to water quality. In this sense, degrading water quality contributes heavily to freshwater scarcity and water insecurity globally. Several satellite observation platforms are nowadays available and new sensors are being launched to increase our capacity in water quality assessment and monitoring. Scientific methods need to be further developed to transform satellite sensor signals into timely water quality information.
Although optical remote sensing of water quality has been subject of substantial research during the last decade, remotely sensed water quality observations still represent a sum parameter of the water quality or ecological status and physical conditions of an aquatic system at a certain moment. Interpretation of these satellite or airborne snapshots and linking them to cause – effect relationships and hydrological processes influencing the aquatic ecosystem are still poorly understood. This is mainly due to the inherent high spatial and temporal variability of aquatic systems and complexity of the hydrological land–water interaction in general. Especially, the impacts of diffuse or non-point source pollution processes on freshwater and coastal water ecosystems need further research and methodological development.
This research aims more specifically at elaborating scientific methods and remote sensing tools for assessing and monitoring diffuse source pollution impacts on water resources.
Objectives
The objectives of this research in this first phase are:
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to evaluate current remote sensing applications, sensors and platforms in their capacity to assess and monitor diffuse source pollution processes and their impacts on water bodies; |
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to review and develop remote sensing data – model integration methods using coupling of radiative transfer models with dynamic water quality models. |
