Md Safat Sikder (University of Illinois Urbana-Champaign, United States); George Allen (Virginia Tech, United States); Sylvain Biancamaria (Université de Toulouse, Laboratoire d’Études en Géophysique et Océanographie Spatiales (LEGOS) (CNES/CNRS/IRD/UT3), Toulouse, France, France); Casey Brown (University of Massachusetts Amherst, United States); Jean-François Crétaux (Université de Toulouse, Laboratoire d’Études en Géophysique et Océanographie Spatiales (LEGOS) (CNES/CNRS/IRD/UT3), Toulouse, France, France); Huilin Gao (Texas A&M University, United States); Colin Gleason (University of Massachusetts Amherst, United States); Tamlin Pavelsky (University of North Carolina at Chapel Hill, United States); Laurence Smith (Brown University, United States); Chunqiao Song (Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing, China, China); Mélanie Trudel (University of Sherbrooke, Canada)

Lakes and reservoirs are among the most widespread inland water repositories. A conservative estimate from the SWOT Prior Lake Database (PLD) identifies nearly 6 million permanent and intermittent lakes larger than 1 ha worldwide, of which at least 8-9% are artificial reservoirs. These water bodies span diverse landscapes and climate zones, with their storage dynamics reflecting a complex interplay of hydrological processes and human interventions. However, the sheer number of lakes presents a significant observational challenge for geodetic satellites. Consequently, most global studies on lake storage dynamics have focused either on interannual trends in a limited number of large lakes (typically a few thousand) or on intra-annual variability across a broader set of lakes but with sparse temporal resolution (often averaging few than five observations per lake per year). While tracking interannual trends remains essential, improving intra-annual observations is critical for capturing the role of lakes in regulating seasonal flow regimes, buffering terrestrial water storage, and mediating carbon and energy fluxes. For reservoirs, tracking intra-annual variability is especially important for inferring operational practices and mitigating seasonal water disparities.

Here, we leverage the first two years of SWOT science data to advance the understanding of Earth’s transient seasonal water storage in millions of lakes and reservoirs, through two complementary typological frameworks: origin-based and behavior-based. First, we adopt a conventional, origin-based typology, which differentiates among reservoirs, glacial lakes, and other natural lakes, to assess intra-annual storage dynamics across these predefined lake classes. This approach helps reveal spatial patterns and aids interpretation of their underlying mechanisms. However, we argue that origin-based typology alone is insufficient to capture the intertwined complexity of global lake behaviors. To address this limitation, we introduce the first global lake typology based on observed water level phenology. This behavior-based typology provides a novel lens for understanding the diverse ways in which lakes respond to, and modulate, regional hydroclimatic variability and anthropogenic influences. Together, these two perspectives demonstrate SWOT’s unprecedented capability to illuminate nuanced dimensions of seasonal lake dynamics, offering an essential step forward for limnological science and the monitoring of lacustrine environments at the global scale.