A Large-Scale Evaluation of SWOT-Derived Water Surface Elevations: Precision Drivers and Strategies to Enhance Data Availability

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Authors: Thiago Lappicy, Daniel Beltrão, Luana Oliveira Sales, Tati Almeida, Guilherme Gomes Pessoa, Saulo Souza, Renato Prata de Moraes Frasson, Rejane Ennes Cicerelli
Cited by: 1
References: 58

Abstract

High-quality water surface elevation (WSE) measurements are critical in hydrological applications, yet no systematic evaluation of the Surface Water and Ocean Topography (SWOT) mission exists for Brazil’s diverse lake systems, where satellite observations are essential given limited in situ monitoring. We evaluated WSE from SWOT over 132 Brazilian lakes, comparing LakeSP, Raster_250m, and Raster_100m products against field measurements over a 20-month period. The 68th percentile errors were under 29 cm for the full dataset, below 12 cm for Flag = 0, and below 21 cm for Flag = 1, indicating good agreement but also the presence of outliers and the need for data screening. A Random Forest analysis identified quality flags, lake geometry, and cross-track distance as key drivers of WSE precision. Flag = 0 is overly restrictive, retaining only 22% of observations, while Flag = 1 contains anomalous data. The SWOT Quality-Range Threshold for Lakes (SQRTL) filter combines Flag = 0 with cross-track constrained Flag = 1 observations. SQRTL more than triples data availability relative to Flag = 0, maintaining comparable precision (68th percentile below 16 cm) and reducing median revisit from 88–123 days to 16–18 days for raster products and from 25 to 14 days for LakeSP. These results provide the first large-scale SWOT WSE evaluation over Brazilian lakes and a transferable filtering framework applicable wherever SWOT and field observations overlap, with potential to extend monitoring to over 100,000 water bodies in the SWOT Prior Lake Database.

Fields of Study & Subjects

Strategic Planning and Analysis Flood Risk Assessment and Management Aquatic Ecosystems and Phytoplankton Dynamics

Publication details

Journal / source
Remote Sensing
Publisher
MDPI AG
Volume
18
Issue
10
Pages
1609–1609
Publication date
17 May 2026
Language
EN