Many studies have identified the first Bush phenomenon as being a rela
tively high load of pollutants in the initial phases of combined sewer
flow. In systems without storage, this first Bush of pollutants may b
e discharged from the system and result in the heavy pollution of the
receiving watercourse. However, by the inclusion of a storage tank, th
is first Bush can be retained and the effluent be discharged in a cont
rolled manner. To optimise the storage volume, both the total pollutan
t load discharged and the temporal variation in pollutant concentratio
n within an event need to be predicted. Sophisticated models like QSIM
and MOUSETRAP to predict the pollutants in urban sewer hows are alrea
dy available. However, the data requirements for these models are exte
nsive, which usually limit their application to major or environmental
ly sensitive schemes. This paper describes the development of site spe
cific regressional relationships to predict the first flush load of su
spended solids in combined sewer flow and these may be used for storag
e tank design. Data from two sites at Great Harwood and Clayton-le-Moo
rs in the Northwest of England has been used to develop predictive equ
ations which relate the first Bush load of suspended solids and the hy
drological parameters most likely to influence sewer flow quality. A m
ultiple stepwise linear regression technique has been utilised for thi
s purpose. The maximum rainfall intensity, maximum inflow, rainfall du
ration and the antecedent dry weather period were found to be the most
important parameters influencing the first flush load of suspended so
lids. The equations were verified using an independent set of data and
gave good predictions of the first flush load for the sites considere
d. This study has the limitation that the equations are catchment spec
ific. However, as more data for different catchments becomes available
, it may be possible to establish standard coefficients for applicatio
n to a wide range of catchment conditions. Copyright (C) 1996 Elsevier
Science Ltd.