  Superstatistics is a general method from nonequilibrium statistical physics
which has been applied to a variety of complex systems, ranging from
hydrodynamic turbulence to traffic delays and air pollution dynamics. Here, we
investigate water quality time series (such as dissolved oxygen concentrations
and electrical conductivity) as measured in rivers, and provide evidence that
they exhibit superstatistical behaviour. Our main example are time series as
recorded in the river Chess in South East England. Specifically, we use
seasonal detrending and empirical mode decomposition (EMD) to separate trends
from fluctuations for the measured data. With either detrending method, we
observe heavy-tailed fluctuation distributions, which are well described by a
log-normal superstatistics for dissolved oxygen. Contrarily, we find a double
peaked non-standard superstatistics for the electrical conductivity data, which
we model using two combined $\chi^2$-distributions.
