SWOT pixel cloud elevation accuracy assessment over synthetic small water bodies

Accurate observations of water surface elevation (WSE) are essential for small waterbodies (WBs) due to their role in agriculture, biodiversity, and hydrology. This study (i) evaluates SWOT PIXC WSE accuracy over synthetic small WBs (0.5–50 ha) built along the shoreline of Lake Léman, Switzerland and (ii) assesses filtering criteria to improve WSE accuracy while preserving data. Pixel-scale accuracy is computed using SWOT pixels within a 50 m shoreline buffer, while WB-scale accuracy uses median pixel elevation per date. After outlier removal, pixels classified as water-edge (class 3) and open-water (class 4) provide the best accuracy, with a 1-sigma absolute error of 24.2 cm at the pixel scale. Aggregation at the WB scale substantially improves accuracy, reducing errors from ~17.4 cm (0.5 ha) to ~8 cm (50 ha). Eight filtering strategies were tested: a multi-variable filter achieved the highest pixel accuracy (19 cm) but excluded ~58% of pixels, whereas simpler filters based on one or two variables produced similar accuracy (~20 cm) while removing only 17%–37% of observations, offering a more practical balance. At the WB scale, filtering is most beneficial for small WBs (0.5–3 ha), reducing error to 15.7 and 12.4 cm, respectively, while removing 12%–15% of days. For larger WBs (~50 ha), all strategies achieve ~8 cm accuracy, so strict filtering provides minimal benefit.