  We develop a modeling framework for bioluminescence light found in the deep
sea near neutrino telescopes by combining a hydrodynamic model with a
stochastic one. The bioluminescence is caused by organisms when exposed to a
non-constant water flow, such as past the neutrino telescopes. We model the
flow using the incompressible Navier-Stokes equations for Reynolds numbers
between 300 and 30000. The discretization relies on a finite element method
which includes upwind-stabilization for the velocity field. On top of the flow
model, we simulate a population of random microscopic organisms. Their movement
and emission are stochastic processes which we model using Monte Carlo methods.
We observe unique time-series for the photon counts depending on the flow
velocity and detector specifications. This opens up the possibility of
categorizing organisms using neutrino detectors. We show that the average
light-yield and pulse shapes require precise flow modeling, while the emission
timing is chaotic. From this we construct a fast modeling scheme, requiring
only a subset of computationally expensive flow and population modeling.
