It is increasingly important to better understand the hydrodynamic and morphodynamic processes of estuaries, because climate change, sea level rise, and human activities cause perturbations and forcing that can be detrimental to coastal ecosystems and communities. It is however challenging to obtain comprehensive data of natural processes in estuaries, due to their highly dynamic nature induced by daily reversing tidal flows, and morphological change occurring over various spatial scales and timescales, ranging from tidal cycles to decades. Conducting physical scale experiments in laboratory flumes is a means to overcome these challenges, as they allow for rapid morphological development and plenty of measurement opportunities.</p> <p>In this work we present a large, publicly available dataset of 19 morphological experiments of estuaries in the Metronome tidal facility (<a href="https://www.uu.nl/Metronome" target="_blank" rel="noopener">www.uu.nl/Metronome</a>), covering almost 230,000 emulated tidal cycles (<em>T</em> = 40 s). The dataset comprises experiments with fixed perturbations in planform shape or tidal settings, temporary perturbations in initial bed morphology, and repeat experiments under the same boundary conditions. Besides, there are two complementary river experiments. The available data consists of planform masks, distributed laserscan DEMs, as well as temporally dense timelapses, orthomosaics and water depth maps computed from overhead imagery taken at fixed moments every 20 tidal cycles. Furthermore, there are occasional orthomosaics and water depth maps from 1 Hz timelapse imagery taken during several consecutive tidal cycles, and orthomosaics from 25 Hz imagery with floating plastic particles, allowing for Particle Image Velocimetry (PIV). All data has been processed through recently developed methods involving a fixed base model geometry, assuring optimal spatial and relative accuracies. The dataset allows for advancements in numerous disciplines studying estuaries, such as morphology, bar theory, chaos theory, channel network analysis, machine learning, and calibration of coastal numerical models. The dataset can be accessed through <a href="https://public.yoda.uu.nl/geo/UU01/KKEUY5.html" target="_blank" rel="noopener">https://public.yoda.uu.nl/geo/UU01/KKEUY5.html</a> (Nota et al., 2026a).