Altimetry-derived surface water data assimilation over the Nile Basin

Area of Science:

• Hydrology
• Remote Sensing
• Water Resource Management

Background:

• Global hydrological models are crucial for understanding water resources.
• Satellite data integration enhances model accuracy, especially in data-scarce regions like the Nile Basin.
• Traditional data assimilation methods are used to combine model and satellite data.

Purpose of the Study:

• To enhance a land-based hydrological model using satellite radar altimetry data.
• To study water storage changes over the Nile Basin.
• To assimilate altimetry-derived surface water storage into the model for the first time.

Main Methods:

• Ensemble Kalman Filter (EnKF) for data assimilation.
• Assimilation of altimetry-derived surface water storage (2003-2016).
• Evaluation using ground measurements and space observations.

Main Results:

• Successful improvement of hydrological model outputs, particularly surface water components.
• Increased correlation (0.44) between surface water storage changes and satellite radar altimetry water level variations.
• Reduced surface water discharge root-mean-square errors (RMSE) by approximately 33%.

Conclusions:

• Satellite radar altimetry assimilation significantly enhances hydrological model performance.
• The improved model provides more accurate insights into water storage dynamics in the Nile Basin.
• This approach is valuable for water resource management in data-limited areas.