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The current state-of-the-art lens monitoring campaign, COSMOGRAIL, typically visits each of its target every few nights during each of several observing seasons each lasting many months. For example, \citet{TewesEtal2013b} present 9 seasons of monitoring for the lensed quasar RXJ1131$-$1231 where the mean season length was 7.7 months ($\pm 2$ weeks) and the median cadence was 3 days. These observations were taken in the same R-band filter, with considerable attention paid to photometric calibration and PSF estimation based on the surrounding star field. This data allowed \citet{TewesEtal2013b} to measure a time delay of 91 days to 1.5\% precision.   While this quality of measurement is possible for small samples (a few tens) of lenses, the larger sample of lensed quasars lying in the LSST survey footprint will all be monitored over the course of its ten year campaign, but at lower cadence and with shorter seasons. We can In the simplest possible ``universal cadence'' observing strategy, we would  expect the mean cadence to be around 4 days,but this is  in any filter; filter, and with some variation with time as the scheduler responds to the needs of the various science programs and the changing conditions;  the gaps between observations in the same filter will tend to be longer \citep{IvezicEtal2010,LSSTSciBook}; the \citep{IvezicEtal2010,LSSTSciBook}. The  season length in this strategy  is likely to be approximately 4 months (with variation among filters), in order to keep the telescope pointing at low airmass. The primary impact of the shorter season length will be to make it hard to measure time delays of more than 100 days; the LSST universal cadence time delay lens sample would be biased towards delays shorted than this.     The universal cadence strategy may turn out not to be optimal; we can explore various LSST observing strategies by simulating lightcurves with a range of cadences and season lengths. The shorter cadences and longer seasons are closer to those obtained by COSMOGRAIL; blind analysis of those datasets will provide understanding of the accuracy available to that program as its lens sample increases.     The remaining variables in the mock lightcurve generation pertain to the photometric uncertainties applied to the observed fluxes. \citet{TewesEtal2013a} provide a summary of possible sources of uncertainty and error in the photometric measurements, and we follow this in generating lightcurves with realistic uncertainties, including in the accuracy of the error reporting. The OM10 mock lens sample contains a variety of quasar image brightnesses, allowing us to investigate time delay accuracy as a function of signal to noise, or for LSST, source magnitude.