HS6.9 EDI

Globally, climate change and major socio-economic developments are triggering emerging water quality challenges, particularly in developing and transition countries. Increasing population, expanding public water supplies that fail to adequately address the treatment of wastewater flows and diffuse transfer of substances from land to water lead to significant water quality deterioration with potential risk to human and ecosystem health, food security, and the economy.
Monitoring and assessing the quality of surface water bodies are critical to obtain ambient water quality standards as called by the Sustainable Development Goals (SDGs) and to water quality management. Remote sensing can be used to monitor water quality over large areas for parameters, such as suspended sediments (turbidity), chlorophyll, and water temperature. Remote sensing can also provide spatial information on land cover and use and water extent mapping as input for water quality modelling. While in-situ measurements are meaningful for a specific point and specific time, remote sensing techniques and modelling provide a broader spatial and temporal view. Water quality parameters derived from satellite images can be used to observe the dynamics of large surface water bodies worldwide over past decades up to near-real time. On the other side, models have been used for decades to simulate current conditions, past trends and future trajectories of water quality from local to global scales. Process-based water quality modelling helps to identify the main pathway of substance transport into water systems. However, both methods require sufficient in-situ measurements for validation and testing but water quality measurements are mainly limited to the developed countries.

This session focuses on regional and global water quality research where remote sensing and modelling are combined in order to complement a water quality assessment compared to one based on monitoring data only. This would cover studies such as on Covid-19 arising on short-term as well as long-time developments such as eutrophication. The following topics are of particular interest for this session:
- Processing water quality data from remote sensing products across scales
- Comparing near-real time remote sensing information with baseline conditions obtained from modelling
- Complementing results from modelling and remote sensing
- Remote sensing facilitating water quality model development and modelling

Convener: Martina Flörke | Co-conveners: Ilona Bärlund, S. G. H. Simis, Ting TangECSECS

Globally, climate change and major socio-economic developments are triggering emerging water quality challenges, particularly in developing and transition countries. Increasing population, expanding public water supplies that fail to adequately address the treatment of wastewater flows and diffuse transfer of substances from land to water lead to significant water quality deterioration with potential risk to human and ecosystem health, food security, and the economy.
Monitoring and assessing the quality of surface water bodies are critical to obtain ambient water quality standards as called by the Sustainable Development Goals (SDGs) and to water quality management. Remote sensing can be used to monitor water quality over large areas for parameters, such as suspended sediments (turbidity), chlorophyll, and water temperature. Remote sensing can also provide spatial information on land cover and use and water extent mapping as input for water quality modelling. While in-situ measurements are meaningful for a specific point and specific time, remote sensing techniques and modelling provide a broader spatial and temporal view. Water quality parameters derived from satellite images can be used to observe the dynamics of large surface water bodies worldwide over past decades up to near-real time. On the other side, models have been used for decades to simulate current conditions, past trends and future trajectories of water quality from local to global scales. Process-based water quality modelling helps to identify the main pathway of substance transport into water systems. However, both methods require sufficient in-situ measurements for validation and testing but water quality measurements are mainly limited to the developed countries.

This session focuses on regional and global water quality research where remote sensing and modelling are combined in order to complement a water quality assessment compared to one based on monitoring data only. This would cover studies such as on Covid-19 arising on short-term as well as long-time developments such as eutrophication. The following topics are of particular interest for this session:
- Processing water quality data from remote sensing products across scales
- Comparing near-real time remote sensing information with baseline conditions obtained from modelling
- Complementing results from modelling and remote sensing
- Remote sensing facilitating water quality model development and modelling