Water Quality Management - River Dynamics and Integrated River Management - page 600

respect to pathogens. Culture-independent, molecular methods detect genetic targets of organisms found
in a specific host. These methods include detection of human enteroviruses and adenoviruses, host-specific
species of Bacteroides, or virulence genes in E. coli (Bower et al., 2005). Fecal anaerobes, such as
Bacteroides, have long been suggested as alternative indicators to the fecal coliform groups (Bower et al.,
2005). Fecal anaerobes compose the majority of fecal bacteria in the gastrointestinal tract of humans and
may be present at 1000 times higher densities than the fecal coliform group, making these organisms
highly sensitive indicators of fecal pollution. The advent of molecular methods has made it more feasible
to detect these organisms in contaminated waters. Certain species of fecal anaerobes have been identified
as host specific, and PCR assays based on the 16S rRNA genes of certain species including the human-
specific 16S gene, or closely related groups of species, allow the simultaneous detection of indicators and
the source of the indicators (Bower et al., 2005). The research group of Dr. Sandra McLellan of the Great
Lakes WATER Institute has been successfully using tests for Bacteroides to find sources of human fecal
contamination throughout the rivers draining Milwaukee, U.S.

9.4.1.3 Simulation of Indicator Bacteria Levels
Even though indicator bacteria have many shortcomings for assessing human health impacts as described
in the previous section, fecal coliforms and E. coli remain the parameters defining bacterial pollution in
water bodies in most countries and their levels often are simulated using computer models. After
discharge to a water body, fecal coliform and E. coli decay/loss is dominated by several factors such as
sunlight, temperature, salinity, sedimentation, resuspension, predation, and aftergrowth. For example,
Fair et al. (1971, p. 641) note the destruction of enteric bacteria is more rapid in:
(1) heavily polluted waters than in clean waters
(2) warm weather than in cold weather
(3) shallow, turbulent waters than in deep, sluggish water bodies
(4) in salt water than in fresh water.
A broad review of these factors can be found in Bowie et al. (1985) and Crane and Moore (1986).
Wilkinson et al. (1995) and Jin et al. (2004) demonstrated that bed sediments also may be a significant
source of fecal coliforms during sediment resuspension due to storms.
Crane and Moore (1986) reviewed several models that had been proposed to simulate fecal coliform
concentrations in stream flow (similar models can be applied to E. coli ). They noted that Mancini (1978)
made an interesting effort to integrate the data found in other studies into a model that directly accounted
for the effects of temperature, solar radiation, and salinity. Manacini's (1978) model generally is considered
the most complete model of the fecal coliform decay/loss process (Thomann and Mueller 1987, p. 237),
and it is given as follows:

(0.8 0.006 P ) D I ( ) t v

> @

T 20

k

SW

1.07

0

1 exp( K D ) F

s

(9.36)

e p

24 K D D

e

where I t is the surface solar radiation in

cal/cm 2 . h, K is the vertical light extinction coefficient in 1/m, F is the fraction of the bacteria attached
to particles, and v is the settling velocity of particulate bacterial forms in m/day. When detailed data are
available to parameterize this model and to define the fecal coliform or E. coli loads to the water body,
this model may be used very effectively as shown by Connolly et al. (1999) in the simulation of pathogens
in Mamala Bay, Hawaii.
In many modeling cases, the use of a simple model is justified by the fact that the uncertainty in the
input loads is considerably high so that the use of a very detailed kinetic structure is impractical.
Generally, a simple first-order kinetics decay model is used to characterize the change of the coliform

P is the percent seawater, D is a proportionality constant, 0 ()

SW