Abstract. The Ganges-Brahmaputra-Meghna delta in Bangladesh is one of the largest and most populated deltas in the world and threatened by relative sea level rise (RSLR). Renewed sediment deposition through tidal river management (TRM), a controlled flooding with dike breach, inside the lowest parts of the delta polders (so-called “beels”) can potentially counterbalance RSLR. The potential of TRM application in different beels across southwestern Bangladesh, however, still remains to be determined. We used a 2D morphodynamic model to explore the physical controls of five variables on total sediment deposition inside the beels during TRM: river tidal range (TR), river suspended sediment concentration (SSC), inundation depth (ID), width of the inlet (IW) and surface area of the beel (BA). Non-linear regression models (NLMs) were developed using the results of 2D models to quantify how sediment deposition inside the beels depends on these variables. The NLMs have an average coefficient of determination of 0.74 to 0.77. Application of the NLMs to 234 beels of southwestern Bangladesh indicates that TRM operation in beels located closer to the sea will retain more sediment as a result of decreasing SSC further inland. Beels in the western part retain more sediment because of lower average land surface elevation. Smaller beels have higher potential to raise land surface elevation due to nonlinear increase of sediment deposition per day (SPD) with beel area. Compartmentalization of larger beels may increase their potential to raise land surface elevation. Thus, the length of time of TRM application in cyclic order will need to vary across the delta to counterbalance RSLR, depending on current beel land surface elevation and local TRM sediment accumulation rates. We found that operating TRM only during the monsoon season is sufficient to raise land surface in 96 % and 80 % of all beels by more than 3 and 5 times the yearly RSLR, respectively. Applying TRM only seasonally offers huge advantages as to keeping the land available for agriculture during the rest of the year. The methodology presented here applying regression models based on 2D morphodynamic modeling may be used for the low-lying sinking deltas around the world to provide an a-priori estimation of sediment deposition from controlled flooding to counterbalance RSLR.