Effect of satellite altimetry sampling error in estimating reservoir storage and outflow

Abstract

The potential of satellite imagery to complement the in-situ gauge networks in monitoring freshwater is well established. However, Temporal Sampling (TS) intervals of satellite altimetry impart significant uncertainty compared to daily or sub-daily in-situ gauge measurements. This study examines the effect of infrequent TS from satellite altimetry, i.e. 10-Day (Jason-2/3), 21-Day (SWOT), 27-Day (Sentinel-3A) and 35-Day (SARAL/AltiKa) for the evaluation of reservoir storage and outflow. The metrics of Relative Error (RE), Root Mean Squared Deviation (RMSD), and the correlation between altimetry-based and in-situ observations have been used for the evaluation. Results show that the altimeters having a high TS frequency, such as 10-Day or 21-Day, performed well with RMSD less than 0.2 m and correlation more than 98% in estimating satellite-based storage and outflow compare to coarse 27-Day or 35-Day TS. This study improves the understanding of sampling error in satellite altimetry, which has immense potential for future SWOT altimeter mission.

Keywords:

• Satellite altimetry
• temporal sampling error
• reservoir storage and outflow
• surface water and ocean topography (SWOT)

Acknowledgments

Authors are thankful to MOSDAC for providing SARAL/AltiKa data, AVISO for providing Jason satellite altimetry data. We equally thank India-Water Resources Information System for providing in-situ water levels of the reservoir. We are also thankful to Andhra Pradesh Water Resources Information & Management System and Karnataka State Natural Disaster Monitoring Centre, respectively for providing reservoir discharge data of Srisailam and Tungabhadra dam.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

DST CNRS ProjectAuthors thank the support through DST CNRS project (DST-CNRS/2018-19-01/109) and the support through DST Centre of Excellence in Climate Studies, IIT Bombay through project DST/CCP/CoE/140/2018(G).