Investigating diversity gradients helps to understand biodiversity drivers and threats. However, one diversity gradient is seldomly assessed, namely how plant species distribute along the depth gradient of lakes. Here, we provide the first in-depth characterization of depth diversity gradients (DDG) of submerged macrophytes across different lakes. We characterize the DDG for additive richness components (alpha, beta, gamma), assess environmental drivers and address temporal change over recent years. We take advantage of yet the largest dataset of macrophyte occurrence along lake depth (274 depth transects across 28 deep lakes) as well as of physio-chemical measurements (12 deep lakes from 2006 to 2017 across Bavaria), provided publicly online by the Bavarian State Office for the Environment. We found a high variability in DDG shapes across the study lakes. The DDG for alpha and gamma richness are predominantly hump-shaped, while beta richness shows a decreasing DDG. Generalized additive mixed-effect models indicate that the maximum alpha richness within the depth transect (R_max) is significantly influenced by lake area only, whereas for the corresponding depth (D_max) are influenced by light quality, light quantity and layering depth. Most observed DDGs seem generally stable over recent years. However, for single lakes we found significant linear trends for Rmax and Dmax going into different directions. The observed hump-shaped DDGs agree with three competing hypotheses: the mid-domain effect, the mean-disturbance hypothesis, and the mean-productivity hypothesis. The DDG amplitude seems driven by lake area (thus following known species-area relationships), whereas skewness depended on physio-chemical factors, mainly water transparency and layering depth. Our results provide insights for conservation strategies and for mechanistic frameworks to disentangle competing explanatory hypotheses for the DDG.