ABSTRACT. The development of sound regulatory standards for fecal
bacterial contamination in streams requires the determination of
bacterial export rates at the watershed scale. This study reports
Escherichia coli (E. coli) and fecal coliform bacteria export rate
dynamics for two agricultural watersheds in till landscapes of the U.S.
midwest. Bacteria concentrations in streams were lowest during the
December-February period and were not significantly correlated (P >
0.05) to discharge, suggesting that discharge was not a good indicator
of bacteria concentration in the study watersheds. Annual E. coli and
fecal coliform export rates were similar between watersheds and varied
between 4.60 x [10.sup.+12] MPN/[km.sup.2]/yr and 6.56 x [10.sup.+12]
MPN/[km.sup.2]/yr for E. coli and between 2.56 x [10.sup.+14]
MPN/[km.sup.2]/yr and 3.33 x [10.sup.+14] MPN/[km.sup.2]/yr for fecal
coliform (MPN = most probable number). Although discharge was poorly
correlated to bacteria concentration, annual E. coli and fecal coliform
exports were dominated by a few precipitation events during which high
flow and high bacteria concentrations occurred simultaneously. In both
watersheds, 90% and 50% of annual E. coli exports occurred in
approximately 16% and 2% of the time, respectively. Similarly, 90% and
50% of annual fecal coliform exports occurred in approximately 18% and
2-2.5% of the time in both watersheds. Considering the importance of
some high flow events on annual bacterial export, we propose that
management efforts should be focused on best management practices
capable of efficiently controlling bacterial transport to streams during
storms. Although high bacteria concentrations can occur at baseflow,
bacteria loadings at baseflow are small and have limited impact on
annual bacterial export rates at the watershed scale.
Keywords: Escherichia coli, fecal coliform, export rate, Midwest,
watershed
**********
Coliform bacteria are naturally-occurring organisms in the
environment and in the feces of all mammals. Although the presence of
coliform bacteria in drinking water may not be harmful to humans, it
indicates that disease--causing organisms may be present in the water
system (Washington Department of Health 2007). The presence of fecal
coliform (FC) and Escherichia coli (EC) bacteria in freshwater almost
always indicates recent fecal contamination, and is an indicator that
pathogenic organisms may be present in water. Consequently, FC and EC
bacteria are widely considered as water quality indicators and are
routinely monitored both in streams and freshwater systems (Nagels et
al. 2002; Collins & Rutherford 2004).
Although potential sources of FC and EC bacteria to streams are
known (e.g., septic systems and livestock operation), a review of the
literature revealed that much uncertainty remains regarding the
variables controlling the fate of FC and EC bacteria in the environment
after they leave the gastro-intestinal tract of the host organism. For
instance, Wickham et al. (2006) indicate that land use and soil
characteristics are correlated with fecal bacterial contamination. The
authors found that streams in some Maryland watersheds with well-drained
and erodible soils, and a high proportion of urban land adjacent to
streams, had the highest likelihood of fecal bacterial contamination.
Others have shown that flow conditions, sediment transport and
precipitation were also related to EC concentration in streams (Mallin
et al. 2001; Tyrrel & Quinton 2003; Reeves et al. 2004; Collins
& Rutherford 2004). In addition, research indicates that seven-day
antecedent precipitation and turbidity influenced the spatial and
temporal variations of EC loads in watersheds in Tennessee (mixed land
use in karst landscape) and Indiana (agricultural land use in till
landscape) (Gentry et al. 2006; Vidon et al. 2008a).
[FIGURE 1 OMITTED]
Much uncertainty therefore remains surrounding the processes
controlling FC and EC dynamics in streams. This strongly limits our
ability to predict hot spots of bacterial contamination as well as total
maximum daily loads for regulatory purposes. Although organisms react to
concentration, load determination is essential to determine bacterial
loading of downstream reservoirs and to develop better predictive models
of bacteria export at the watershed scale. Indeed, one critical step
toward the development of sound regulatory standards for bacterial
contamination in freshwater streams is the assessment of bacterial load
at the watershed scale for a variety of land uses and geomophological
settings. This includes the determination of bacterial export rates
(MPN/[km.sup.2]/yr) for inclusion in export and risk assessment models.
With the exception of Line et al. (2008), who reported FC export rates
between 1.81 x [10.sup.+12] MPN/[km.sup.2]/yr and 1.9 x [10.sup.+13]
MPN/[km.sup.2]/yr for residential and low density industrial watersheds
in North Carolina, very few studies report actual bacterial export rates
at the watershed scale. Gentry et al. (2006) and Vidon et al. (2008a)
report EC daily loads but do not report annual export rates. A limited
number of studies reporting annual bacterial loads is likely due to the
high variability of bacterial concentration in streams and subsequent
difficulty to determine accurately stream bacterial load. Nevertheless,
although errors in bacterial load estimates are certainly high,
determining annual export rates is of critical importance to proper
watershed management.
This study reports monthly and annual export rates of EC and FC
bacteria for two agricultural watersheds in till landscapes of the U.S.
Midwest, near Indianapolis, Indiana. The objectives of this study were:
1) to determine EC and FC export rates for two watersheds with similar
land uses, and 2) to determine whether discharge could be used as a good
indicator of EC and FC export at the watershed scale. The implications
of our results for watershed management are briefly discussed.
METHODS
Site deseription.--The two experimental sub-watersheds used in this
study (FB8 and SB4) are located in Eagle Creek watershed
(39[degrees]55'15" N, 86[degrees]21'01" W) in the
nearly flat Tipton Till Plain near Indianapolis, Indiana (Fig. 1).
Indiana has a temperate continental and humid climate. The average
annual temperature for central Indiana is 11.7 [degrees]C with an
average January temperature for Eagle Creek Watershed of -3.0[degrees]C
and an average July temperature of 23.7[degrees]C. The long-term average
annum precipitation (1971-2000) in the watershed is 105 cm (NOAA 2005).
Precipitation is relatively evenly distributed throughout the year,
which typically precludes the need for irrigation in summer time.
Average stream discharge nevertheless varies with seasons owing to
higher evapotranspiration in summer months. Highest stream discharge is
observed in March while the lowest discharge typically occurs in
September (Clark 1980). Artificial drainage of agricultural soils is
common in these two watersheds where soils are generally poorly to
somewhat poorly drained (Campling et al. 2002) and belong for the most
part to the Crosby-Treaty-Miami association (Hall 1999). Land use is
similar in both watersheds (Table 1) and is dominated by agriculture
(mainly corn-soybean rotation) (82-87%). A limited number of household
using septic systems are located in the watershed (exact number is
unknown). Those septic systems could act as a possible point source of
EC and FC in the watersheds. No confined animal feeding operations are
located in the watersheds.
Hydrological and water quality measurements.--Watershed boundaries
and channel stream lengths were established using ArcGIS surface
hydrology tools and 30 m U.S. Geological Survey digital elevation model
(DEM) data.
The 2004 Natural Resources Conservation Service 1 m imagery was
used to determine land use in each of the watersheds studied. Stream
discharge (Q) at the outlet of watersheds FB8 and SB4 was estimated
based on daily discharge measurements made at the nearby USGS Zionsville
stream gauging station (Station #3353200) following the general
equation:
[Q.sub.station] =
[[A.sub.station]/[A.sub.zionville]/[Q.sub.zionsville] (1)
where [Q.sub.station] is the discharge for each stream monitoring
station ([m.sup.3]/s), [Q.sub.zionsville] is the discharge measured at
the USGS Zionsville stream gauging station ([m.sup.3]/s),
[A.sub.zionville] is the area upstream from Zionsville monitoring
station ([km.sup.2]) and [A.sub.station] the area upstream from each
station ([km.sup.2]) (USGS 2005). This equation was used because
discharge typically scales linearly or nearly linearly with contributing
area (Dunne & Leopold 1978; Pazzaglia et a1.1998). Instantaneous
discharge was also measured in the field in 2005 to check for the
accuracy of estimated discharge using a Doppler velocity meter (SONTEK
Flow Tracker). In this study, high flow is defined as the 75th
percentile for discharge ([Q.sub.75]), i.e., the discharge exceeded 25%
of the time based on long-term discharge measurements obtained at the
USGS stream gauging station.
Water samples were collected on a bi-weekly to monthly basis
between storms, with additional sampling during storms between April
2005 and March 2006. Over a 12-month period, a total of 23 samples was
collected in each watershed, with 10 of them collected during high flow
conditions. Over the course of the study period, 12 precipitation events
generated high flow conditions (Q > [Q.sub.75]) and one water sample
at high flow was collected for 10 out of 12 events (Fig. 2). Field
blanks and triplicate analysis of selected samples were performed for
quality control and samples were kept on ice after sampling until return
to the laboratory. FC and EC concentrations (most probable number (MPN)
of colony forming unit per 100 ml) were measured within a few hours of
collection for a total of 46 samples. FC concentration was determined
using membrane filtration technique (standard method SM9221D), and EC
concentration was measured using the E. coli Test using EC-MUG Medium
and read using a fluorometer (long-wavelength UV) (standard methods
SM9221-F) (Eaton et al. 2005).
Bacterial export rates were determined by summing storm and
non-storm bacterial export rates (Line et al. 2008). Specifically,
non-storm export rates were calculated by multiplying EC or FC
concentrations for each non-storm period by the total discharge volume
for each period. Storm export rates were determined by multiplying the
bacterial concentration in the grab sample for each storm studied by the
total discharge volume for each storm. Storm samples were generally
collected near peak flow during each of the storms studied. The two
storms for which bacterial concentration were not available (storms 2
and 12) were small storms where streamflow barely exceed the 75th
discharge percentile. For these two storms, bacterial concentrations
were interpolated based on concentration before and after the storms. It
is important to note that considering that daily bacteria loads between
baseflow and high flow vary by approximately two orders of magnitude,
and that EC concentrations significantly increase during storms (Vidon
et al. 2008a), there is likely a large error in estimated bacterial
loads in this study. Although we believe that export rates are of the
correct order of magnitude, the potential impact of inherent calculation
errors for load estimates should be taken into account when interpreting
results. Simple t-tests are used to determine significant difference
between samples.
[FIGURE 2 OMITTED]
RESULTS AND DISCUSSION
EC and FC concentrations in streams.--FC and EC bacteria
concentrations are shown for SB4 and FB8 watersheds in Fig. 2. A grab
sample for bacterial concentration measurements was collected for each
of the storm events shown in Fig. 2 (upper panel) except for storms 2
and 12. However, compared to the other 10 events for which bacterial
concentration were monitored, these events were small. Not having FC or
EC concentration data for these two events is therefore unlikely to
significantly affect bacterial loads estimated on an annual basis. It is
possible, however, that the absence of samples for storm 2 (May 2007)
affected monthly estimates of EC and FC loads for the month of May.
Median FC concentrations were 14850 MPN/100ml and 30366 MPN/100 ml in
SB4 and FB8, respectively. Similarly, median EC concentrations during
the study period were 200 and 280 MPN/100 mL in SB4 and FB8. Data
therefore indicate that bacterial concentrations tended to be slightly
higher in FB8 than SB4. Although some natural variability in bacterial
concentration was expected between watersheds SB4 and FB8, it is unclear
why bacterial concentrations were significantly (P > 0.05) higher in
FB8 than in SB4. Considering the small surface area of the watersheds
studied (13-14 [km.sup.2]), it is possible that a single source of
bacterial contamination in FB8 could have created these differences. For
instance, a failing septic system in one of the farm households located
in FB8 (4.31% urban) could have lead to this variability.
Data in Fig. 2 also indicate higher FC concentrations during the
March-September period than during the rest of the year. Similarly, EC
concentrations in both watersheds were higher between April and November
than during the rest of the year. With the exception of SB4 watershed
where FC concentration was significantly correlated to discharge
(correlation coefficient = 0.79, P < 0.01), correlation analysis
showed no significant correlation (correlation coefficient < 0.3, P
> 0.05) between discharge and FC in FB8 watershed or EC in either of
the watersheds studied. The lack of significant relationship between
discharge and bacterial concentration in the watersheds studied is
especially clear during the December to March period during which five
high flow events occurred while FC and EC concentrations remained low
most of the time. The only exception is for FC in SB4 watershed for
storm 11, where FC reached its highest value for the study period. These
results are consistent with those reported by Gentry et al. (2006) in a
mixed land use watershed in Tennessee where the authors indicated a poor
correlation (correlation coefficient = 0.06) between EC concentration
and discharge. They are, however, in contrast with those reported by Kay
et al. (2008) for a series of watersheds in the UK where fecal bacteria
concentrations were typically more than one order of magnitude higher at
high flow than during baseflow conditions.
Higher EC concentrations in the April-November period were
consistent with the results reported by Vidon et al. (2008b) indicating
that there was a higher probability of high EC concentration in the
spring/summer/ fall than in the winter for the watersheds studied. Kay
et al. (2008) also found higher fecal bacteria concentrations in summer
than winter, especially during high flow conditions. It is possible that
the higher concentration of bacteria in the spring and summer occurred
because FC and EC colonies were more likely to thrive in the stream at
higher temperatures during the summer when flow is low, than during
winter. Nevertheless, there was no evidence in the data allowing us to
validate this hypothesis.
Overall, discharge appears to be a poor indicator of EC and FC
concentration in streams in this region of the country. Seasons, on the
other hand, may control to some extent bacterial concentration in the
streams studied. More studies need to be conducted to further determine
the parameters controlling temporal variability in bacterial
concentration in the watersheds studied (e.g., temperature, antecedent
moisture conditions).
FC and EC export rates.--Monthly and annual FC and EC export rates
between April 2005 and March 2006 are shown in Fig. 3 for watersheds SB4
and FB8. Annual EC and FC export rates were similar (same order of
magnitude) between watersheds SB4 and FB8. Specifically, annual EC
export rates were 6.56 x [10.sup.+12] MPN/[km.sup.2]/yr and 4.60 x
[10.sup.+12] MPN/[km.sup.2]/yr in SB4 and FB8 watersheds, respectively.
FC export rates were 3.33 x [10.sup.+14] MPN/[km.sup.2]/yr and 2.56 x
[10.sup.+14] MPN/[km.sup.2]/yr in SB4 and FB8, respectively. Line et al.
(2008) reported FC export rates varying between 1.81 x [10.sup.+12]
MPN/[km.sup.2]/yr and 1.9 x [10.sup.+13] MPN/[km.sup.2]/yr for
residential and low density industrial watersheds in North Carolina.
Annual FC export rates reported in this study are therefore 1 to 2
orders of magnitude higher than in the Line et al. (2008) study. Most
houses located in our watersheds were on septic systems and were built
before regulations on septic system design and installation were
implemented in the state of Indiana. It is therefore highly likely that
a small number of failing septic systems in both SB4 and FB8 contributed
to the higher bacterial contamination in our watersheds than in the
North Carolina study. Other factors such as soil and animal activity may
also have affected our results. Vidon et al. (2008a) also reported that
EC concentrations in the watersheds studied were higher than in a mixed
land use watershed in karstic landscape of Tennessee. Finally, Tedesco
et al. (2005) reported acute contamination of fresh water by EC bacteria
in most areas of the larger Eagle Creek watershed where the sites are
located. Further research is needed to determine why bacterial
contamination is more acute in these agricultural watersheds of the U.S.
Midwest than in North Carolina coastal watersheds or karstic watersheds
in Tennessee. We hypothesize that a small number of failing septic
systems or unreported manure application as fertilizer in the spring may
explain why bacterial contaminations were so high in the watersheds
studied.
[FIGURE 3 OMITTED]
Consistent with higher bacteria concentration in spring/summer/fall
than in winter (December--January--February), monthly export rates tend
to be higher in the spring/ summer/fall period than in winter. In FB8,
lowest EC export rates occurred in December, January and February in
spite of 25% of precipitation events occurring during these three months
(events 7-10) (Fig. 2). In SB4, EC monthly loads were also low in
December, January and February compared to spring (April, June, July) or
Fall (November). FC export rates in both watersheds presented a similar
seasonal pattern as did EC export rates in SB4. Specifically, FC export
rates were lowest in December, January and February, and highest in
March, April, June, July, September and November. Low loads in May were
likely due the fact that no samples were collected for storm 2 (May
2007). Low loads in August were likely related to extremely low flow and
the absence of high flow events in August (Fig. 2). Although loads were
low in May and August, overall, loads tended to be higher in
spring/summer than in winter. Our results are consistent with those
reported by Line et al. (2008) and Kay et al. (2008) who indicated lower
bacterial export rate in winter than during the rest of the year.
Although instantaneous EC and FC concentrations may be poorly
correlated to instantaneous discharge, further analysis of the data
revealed that annual EC and FC export rates were driven by a few events
during which both high flow and high EC or FC concentrations occurred
simultaneously. Figure 4 shows the cumulative EC and FC loads as a
function of time (Figs. 4, 5), as well as the distribution of EC and FC
daily loads and their respective probability of occurrence for the study
period (Figs. 6, 7). In both SB4 and FB8 watersheds, 90% of EC exports
at the watershed scale occurred in approximately 16% of the time and 50%
of EC exports occurred in only in 2% of the time (Fig. 4). This suggests
that annual EC export rates at the watershed scale are dominated by a
few high flow periods during which both flow and EC concentration happen
to be high. Indeed, even though the total annual export rates in SB4 and
FB8 watersheds were between 6.56 x [10.sup.+12] MPN/[km.sup.2]/yr and
4.60 x [10.sup.+12] MPN/[km.sup.2]/ yr, daily EC export rates above
[10.sup.+12] MPN/[km.sup.2]/ day occurred only 0.2% of the time in SB4
and never occurred in FB8. EC export rates above [10.sup.+11]
MPN/[km.sup.2]/day occurred only approximately 3.5% of the time in
either SB4 or FB8 watersheds and EC export rates above [10.sup.+10]
MPN/[km.sup.2]/day occurred only 21% of the time in either watershed
(Fig. 6). Daily EC export rates above [10.sup.+11] MPN/[km.sup.2]/day
all occurred during storms 1, 3, 5, and 8 in SB4 (Fig. 2). In FB8
watershed, daily EC export rates above [10.sup.+11] MPN/[km.sup.2]/day
all occurred during storms 1, 3, 4, and 5 (data not shown). During these
events, export rates were 2 to 3 orders of magnitude higher than during
the rest of the year. These storms were not necessarily those which
generated the highest discharge (Fig. 2) but corresponded to storms for
which a combination of relatively high flow and high EC concentration in
the streams were observed simultaneously. This is consistent with the
poor correlation previously reported between EC concentration and
discharge in the watersheds studied for a 12 month period.
[FIGURES 4-7 OMITTED]
Patterns of FC export rates were very similar to those of EC
bacteria (Figs. 5, 7). Specifically, 90% of FC exports at the watershed
scale occurred in 13% of the time in SB4 watershed and in 18% of the
time in FB8 watershed (Fig. 5). Similarly, 50% of FC exports occurred in
2.2% and 2.5% of the time in SB4 and FB8 watersheds, respectively.
Similar to EC, high FC daily loads mainly occurred during a limited
number of precipitation events during the year. In SB4 watershed, FC
daily loads above [10.sup.+12] MPN/[km.sup.2]/day occurred for only
storms 1, 3, 5, 8, and 11. In FB8 watersheds, FC daily loads above
[10.sup.+12] MPN/[km.sup.2]/day only occurred for storms 1, 3, 4, and 5
(data not shown).
Overall, this pattern of dominance of a few storms combining high
flow and high bacteria concentration in annual contaminant loads is
consistent with what has been observed by others for contaminants like
pesticides that are exported via overland flow in a very similar way to
EC or FC. For instance, Shipitalo & Owens (2006) indicate that
herbicide transport for seven small watersheds (0.45-0.79 ha) in Ohio
was dominated by hot moments of pesticide transport in precipitation
driven overland flow during precipitation events. Out of a total of 1800
storm events monitored, 60-99% of herbicide loss was due to the five
largest transport events during the 9-year study period.
WATERSHED MANAGEMENT IMPLICATIONS
Overall, data indicated that annual bacterial export rates were
dominated by discharge events during which high discharge and high EC
and FC concentrations occurred simultaneously, in spite of the lack of
consistent positive correlation between bacteria concentration and flow
over a 12 month period. We propose that large concentration and loads of
EC and FC bacteria during selected storm events may have long-lasting
effects on downstream water quality even after return to baseflow.
Indeed, there is evidence in the literature that EC bacteria and other
coliform bacteria can be transported downstream and persist in the
environment for over a year in some instances (Palmateer et al. 1989;
Lang & Smith 2007). More specifically, Koirala et al. (2008)
reported short-term and long-term persistence for coliform bacteria in
streams ranging from four days to approximately one year, respectively.
Minimizing bacterial export rates during storms is therefore critical in
order to improve water quality at the watershed scale. In spite of the
limitations associated with load calculations owing to the variability
of bacterial concentrations in streams, we believe that the trends
observed in this study can be used to develop better management
strategies at the watershed scale. We propose that management efforts to
minimize bacterial contamination of freshwater systems should be focused
on best management practices capable of efficiently controlling
bacterial transport to streams during storms as minimizing bacterial
concentration in streams at baseflow would have only a limited impact on
downstream bacterial loading as both high flow and high bacteria
concentration are necessary to significantly impact loading.
Conducting similar studies in a variety of watersheds with various
land uses and contrasting geomorphological characteristics and climates
would help further generalize the results of this study.
ACKNOWLEDGMENTS
This research was supported by a Central Indiana Water Resources
Partnership (C.I.W. R.P.) grant to Dr. Vidon and a C.I.W.R.P. Fellowship
to M.A. Campbell. The C.I.W.R.P. is a research and development program
between Veolia Water Indianapolis and the Center for Earth and
Environmental Science (C.E.E.S.) at Indiana University-Purdue University
at Indianapolis (IUPUI). The authors would like to thank Dr. Tedesco and
C.E.E.S for logistical support, and Bob E. Hall and Vince Hernly for
technical support and help in the field.
Manuscript received 4 November 2008, revised 16 February 2009.
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P. Vidon and M.A. Campbell: Department of Earth Sciences and Center
of Earth and Environmental Science, SL118, Indiana University-Purdue
University, Indianapolis, 723 W. Michigan Street, Indianapolis, Indiana
46202 USA
E. Soyeux: Veolia Environment, Research Department, 36-38 Avenue
Kleber, 75116 Paris, France
Table 1.--Land use and site characteristics for
FB8 and SB4 watersheds.
FB8 SB4
watershed watershed
Area ([km.sup.2]) 13.29 13.67
Stream length (km) 9.41 7.88
Drainage density 0.71 0.58
Mean slope (%) 0.47 0.39
Agricultural land use (%) 82.2 87.0
Urban land use (%) 4.3 3.4
Forested land use (%) 5.9 3.2
Herbaceous land use (%) 8.4 6.2