HYDRAS - Improving drought monitoring through assimilating multi-source remote sensing observations in hydrologic models

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Context and objectives

Given the expected increase in extreme events due to climate change, more drought events can be expected in the future. These events have often devastating impacts on society and the environment. Adequate monitoring of these events is of utmost importance within disaster management. Remote sensing can provide important information, though does not allow for a complete assessment of droughts as

  1. Only measurements of the surface are obtained and
  2. The spatial and temporal resolutions are often too coarse. Combining remote sensing with land surface models is generally opted for, and is already in place in many drought monitoring systems.

However, these systems can be improved with respect to

  1. The use of multiple sources of remote sensing data,
  2. The modelling approach used and
  3. The updating of models based on remotely sensed observations. If any of these components can be improved, a more precise monitoring and modelling can be expected, and therefore enhanced predictions of droughts can be made.

The objective of HYDRAS+ is to work on these three domains and to demonstrate the benefits of the joint assimilation of several remote sensing sources in land surface models. It furthermore aims at assessing whether conceptual models can be used instead of complex and computation-expensive land surface models. If so a faster computation of droughts at very large scale becomes possible.
HYDRAS+ aims at developing methodologies that can improve many of the currently existing drought monitoring systems. Any improvement will have positive consequences for disaster management as it will allow for an improved management of resources, reducing the number of casualties.


Project outcome

Expected scientific results

Several scientific results are expected with respect to:
• Downscaling remote sensing data to the model resolution
• Conceptual modelling of the mass and energy balance at large scale
• Data assimilation of a suite of remote sensing observations
• Merging of data from different sensors
• Dual state-parameter estimation
• Recommendations to the use of remote sensing data in land surface models
• Recommendations to improving operational drought monitoring/forecast systems

Expected products and services

The main products that can be expected are new methodologies and insights in the application of remotely sensed observations in land surface models in order to improve drought monitoring. The products that will initially be delivered will be contributions to workshops/conferences/symposia and publications in peer-reviewed journals. However, end users (mainly organizations that provide drought forecasts and space agencies) will be informed on the advances made through this project, and how these may benefit their services.

• ECWMF (European Centre for Medium-Range Weather Forecasts)
• ESA (European Space Agency)
• NASA (National Aeronautics and Space Administration)
• JRC (Joint Research Centre)
• Developers of drought monitoring/forecasting systems
• IPCC (Intergovernmental Panel on Climate Change)
• Specialist companies providing water management services (Deltares, Arcadis, DHI …)
Stakeholders which would profit from improved drought monitoring and forecasting systems:
• Water managers responsible for e.g. irrigation scheduling
• FAO (Food and Agriculture Organization)
• UNESCO (United Nations Educational, Scientific and Cultural Organization)
• NGO’s (e.g. PROTOS)