  A forward modelling approach provides simple, fast and realistic simulations
of galaxy surveys, without a complex underlying model. For this purpose, galaxy
clustering needs to be simulated accurately, both for the usage of clustering
as its own probe and to control systematics. We present a forward model to
simulate galaxy surveys, where we extend the Ultra-Fast Image Generator to
include galaxy clustering. We use the distribution functions of the galaxy
properties, derived from a forward model adjusted to observations. This
population model jointly describes the luminosity functions, sizes,
ellipticities, SEDs and apparent magnitudes. To simulate the positions of
galaxies, we then use a two-parameter relation between galaxies and halos with
Subhalo Abundance Matching (SHAM). We simulate the halos and subhalos using the
fast PINOCCHIO code, and a method to extract the surviving subhalos from the
merger history. Our simulations contain a red and a blue galaxy population, for
which we build a SHAM model based on star formation quenching. For central
galaxies, mass quenching is controlled with the parameter M$_{\mathrm{limit}}$,
with blue galaxies residing in smaller halos. For satellite galaxies,
environmental quenching is implemented with the parameter
t$_{\mathrm{quench}}$, where blue galaxies occupy only recently merged
subhalos. We build and test our model by comparing to imaging data from the
Dark Energy Survey Year 1. To ensure completeness in our simulations, we
consider the brightest galaxies with $i<20$. We find statistical agreement
between our simulations and the data for two-point correlation functions on
medium to large scales. Our model provides constraints on the two SHAM
parameters M$_{\mathrm{limit}}$ and t$_{\mathrm{quench}}$ and offers great
prospects for the quick generation of galaxy mock catalogues, optimized to
agree with observations.
