Improving mean water lake surface elevation estimates using dense lidar measurements from the GEDI satellite mission

Abstract

Lakes are an essential component of the global water cycle and are considered as sentinels of climate change. An accurate estimate of lake's water levels is necessary for reliable continuous monitoring of their water balance. Due to their huge number worldwide, satellite altimetry has been identified as an efficient tool for measuring their temporal variations of water level. This technique can reach an accuracy of a few centimeters for water level estimates over large lakes. Due to the coarse across-track spatial resolution of the radar altimetry missions, their spatial sampling only covers a small part of the lakes surface. To obtain an accurate estimate of the lake water level, it is necessary to apply a correction to account for the small-scale orthometric height undulations occurring on the lake area and not present in the current global geoid models. In this study, the high-density lidar measurements from GEDI are used to estimate the mean lake surface. From the 1,366,211 GEDI data over 1239 tracks acquired over more than 6000 km2 of the surface of Lake Issy-Kul (Kyrgyzstan, Central Asia) between May 2019 and mid-November 2021, 654,592 shots over 843 tracks were selected after a multi-step quality-check and processed to generate a mean lake surface of Lake Issyk-Kul. Comparison between the GEDI-based mean lake surface and GNSS kinematic surveys corrected from the lake level variations exhibit an RMSE of 0.065 m. The principal objective of performing such mean lake surface is to further use it in the framework of the calibration/validation of the Surface Water and Ocean Topography (SWOT) mission.