Full waveform inversion (FWI) methods can produce high-resolution images of the physical properties of the subsurface. FWI has become a powerful tool for time-lapse or 4D seismic inversion, with applications in the monitoring of reservoir changes with injection and production, and potentially long term storage of carbon. Current time-lapse FWI strategies include the parallel strategy (PRS), the sequential strategy (SQS), the double-difference strategy (DDS), the common-model strategy (CMS), and the central-difference strategy (CDS). PRS time-lapse inversion is affected by convergence differences between the baseline and monitoring inversions, as well as non-repeatable noise and non-repeatable acquisition geometries between surveys. The other strategies are largely efforts to fix the sensitivities of PRS, but robust solutions are still sought. We hypothesize that several problems in time-lapse FWI arise from the independence of step lengths during updating. This is supported by synthetic data tests, which indicate that stepsize-sharing reduces artifacts caused by the variability in PRS convergence. Two strategies, which we refer to as stepsize-sharing PRS (SSPRS) and stepsize-sharing CMS (SSCMS), are then designed to address these remaining issues. The SSPRS appears to be particularly well-suited for reducing artifacts caused by convergence differences, non-repeated noise, non-repeatable source locations, and biased starting models. This breadth of robustness does not appear in any of the other approaches tested. Especially given that SSPRS through its sharing incurs half of the time cost of seeking stepsizes compared with the PRS and DDS, and the total computational cost of SSPRS is less than half of that of the CMS and CDS.