The Data Analysis Pipeline for the SDSS-IV MaNGA IFU Galaxy Survey:
  Emission-Line Modeling
  SDSS-IV MaNGA (Mapping Nearby Galaxies at Apache Point Observatory) is the
largest integral-field spectroscopy survey to date, aiming to observe a
statistically representative sample of 10,000 low-redshift galaxies. In this
paper we study the reliability of the emission-line fluxes and kinematic
properties derived by the MaNGA Data Analysis Pipeline (DAP). We describe the
algorithmic choices made in the DAP with regards to measuring emission-line
properties, and the effect of our adopted strategy of simultaneously fitting
the continuum and line emission. The effect of random errors are quantified by
studying various fit-quality metrics, idealized recovery simulations and repeat
observations. This analysis demonstrates that the emission lines are well-fit
in the vast majority of the MaNGA dataset and the derived fluxes and errors are
statistically robust. The systematic uncertainty on emission-line properties
introduced by the choice of continuum templates is also discussed. In
particular, we test the effect of using different stellar libraries and simple
stellar-population models on the derived emission-line fluxes and the effect of
introducing different tying prescriptions for the emission-line kinematics. We
show that these effects can generate large ($>$ 0.2 dex) discrepancies at low
signal-to-noise and for lines with low equivalent width (EW); however, the
combined effect is noticeable even for H$\alpha$ EW $>$ 6~\AA. We provide
suggestions for optimal use of the data provided by SDSS data release 15 and
propose refinements on the \DAP\ for future MaNGA data releases.
