  Detecting H2O in exoplanet atmospheres is the first step on the path to
determining planet habitability. Coronagraphic design currently limits the
observing strategy used to detect H2O, requiring the choice of specific
bandpasses to optimize abundance constraints. In order to examing the optimal
observing strategy for initial characterization of habitable planets using
coronagraph-based direct imaging, we quantify the detectability of H2O as a
function of signal-to-noise ratio (SNR) and molecular abundance across 25
bandpasses in the visible wavelength range (0.5-1 micron). We use a
pre-constructed grid consisting of 1.4 million geometric albedo spectra across
a range of abundance and pressure, and interpolate the produce forward models
for an efficient nested sampling routine, PSGnest. We first test the
detectability of H2O in atmospheres that mimix a modern-Earth twin, and then
expand to examine a wider range of H2O abundances; for each abundance value, we
constrain the optimal 20% bandpasses based on the effective signal-to-noise
ratio (SNR) of the data. We present our findings of H2O detectability as
functions of SNR, wavelength, and abundance, and discuss how to use these
results for optimizing future coronographic instrument design. We find that
there are specific points in wavelength where H2o can be detected down to 0.74
micron with moderate-SNR data for abundances at the upper end of Earth's
presumed historical values, while at 0.9 micron, detectability is possible with
low-SNR data at modern Earth abundances of H2O.
