Development of water level estimation algorithms using SARAL/Altika dataset and validation over the Ukai Reservoir, India

S. Chander; D. Ganguly

doi:10.1117/12.2227808

12 May 2016 Development of water level estimation algorithms using SARAL/Altika dataset and validation over the Ukai Reservoir, India

S. Chander, D. Ganguly

Author Affiliations +

Proceedings Volume 9878, Remote Sensing of the Oceans and Inland Waters: Techniques, Applications, and Challenges; 98780M (2016) https://doi.org/10.1117/12.2227808
Event: SPIE Asia-Pacific Remote Sensing, 2016, New Delhi, India

Abstract

Water level was retrieved, using AltiKa radar altimeter onboard the SARAL satellite, over Ukai reservoir using modified retrieval algorithms specifically for inland water bodies. The methodology was based on waveform classification, waveform retracking and dedicated inland range corrections algorithms. The 40 Hz waveforms were classified based on the linear discriminant analysis (LDA) and Bayesian classifier. Waveforms were retracked using Brown, Threshold, and Offset Centre of Gravity methods. Retracking algorithms were implemented on full waveform and sub-waveforms (only one leading edge) for estimating the improvement in the estimated range. ECMWF operational, ERA reanalysis pressure fields and global ionosphere maps were used to exactly estimate the range corrections. The microwave and optical images were used for estimating the extent of the water body and altimeter track location. Four GPS field trips were conducted, same day on the SARAL pass, using two Dual frequency GPS. One GPS was mounted close to Dam as static mode and the other was used on a moving vehicle within the reservoir in Kinematic mode. Tide gauge dataset was provided by the flood cell, Ukai dam authority for the time period 1972-2015. The altimeter retrieved water level results were then validated with the GPS survey and in-situ tide gauge dataset. With good selection of virtual station (waveform classification, back scattering coefficient), Ice-2 retracker and subwavefom retracker both works better with overall RMSE better than 15 cm. The results supports that AltiKa dataset, due to smaller foot-print and sharp trailing edge of Ka band waveform, can be utilized for more accurate water level information over inland water bodies.

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S. Chander and D. Ganguly "Development of water level estimation algorithms using SARAL/Altika dataset and validation over the Ukai Reservoir, India", Proc. SPIE 9878, Remote Sensing of the Oceans and Inland Waters: Techniques, Applications, and Challenges, 98780M (12 May 2016); https://doi.org/10.1117/12.2227808

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KEYWORDS

Global Positioning System

Satellites

Radar

Algorithm development

Data processing

Kinematics

Contamination

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