Methodological evaluation of river discharges derived from remote sensing and land surface models

Area of Science:

• Hydrology
• Remote Sensing
• Earth Science

Background:

• Accurate river discharge estimation is crucial for water resource management and flood prediction.
• Traditional methods are limited by sparse gauge networks, necessitating alternative approaches.
• Remote sensing and hydrologic models offer complementary methods for large-scale discharge assessment.

Purpose of the Study:

• To evaluate and compare river discharge estimates derived from satellite remote sensing and land surface models across the CONUS.
• To assess the performance of different remote sensing techniques (GRACE TWSA, satellite altimetry) and land surface models (NOAH, CLSM).
• To identify the strengths and limitations of each approach under various hydroclimatic conditions.

Main Methods:

• Utilized total water storage anomalies (TWSA) from GRACE and water surface elevations from JASON-2/3 and Sentinel-3 satellites.
• Employed surface and subsurface runoff from NOAH and CLSM land surface models, routed via the Hillslope River Routing model.
• Validated discharge estimates using Kling-Gupta Efficiency (KGE) and USGS stream gauge data.

Main Results:

• Satellite altimetry demonstrated good performance across a range of river discharges.
• GRACE TWSA effectively captured mean river flows.
• NOAH land surface model generally outperformed CLSM, though performance varied with hydroclimatic conditions and drainage area.
• GLDAS models, particularly CLSM, showed limitations in snow-dominated, semi-arid, and regulated systems, often overestimating discharge magnitude and timing.

Conclusions:

• Both satellite-derived discharge methods are effective, offering valuable insights into river dynamics.
• Land surface model performance is sensitive to model physics, forcings, and assimilation techniques, highlighting areas for improvement.
• Further research is needed to refine hydrologic models for accurate simulation in challenging hydroclimatic environments.