Abstract

Bayou Lafourche, which is the sole drinking water source for 300,000 people in Louisiana, has failed to consistently meet its designated use criteria set by the Louisiana Department of Environmental Quality (LDEQ). This resulted in a total maximum daily load to be imposed on the Bayou by the Environmental Protection Agency (EPA). These designated use water quality criteria include fecal coliform (FC) levels for drinking water source, primary contact recreation, and secondary contact recreation. The goal of this study was to identify and enumerate anthropogenic nonpoint source FC contamination from malfunctioning home sewage systems in the Bayou's watershed. Thirty-four sites along the Bayou were selected for the study. Samples were analyzed for optical brightener ratios, FC CFU/100 mL (mFC), Escherichia coli, and three human markers, including human polyomavirus BK, the Archaeon Methanobrevibacter smithii, and the human-associated Brevibacterioides HF 183 eubacteria. Frequencies of sites with all three anthropogenic molecular markers are considered positive for human fecal contamination. This study provided data to address the problem of malfunctioning on-site sewage systems in the Bayou Lafourche watershed.

INTRODUCTION

Nonpoint source (NPS) pollution is the leading contributor to water quality problems in the United States (Gentry-Shields et al. 2012). Nonpoint sources of contamination may be attributed to urban and agricultural runoff, leakage from septic or sewer systems, and stormwater runoff (Bergeron et al. 2015, 2016, 2017). Methods have been developed in which certain microorganisms are used to indirectly identify probable sources of anthropogenic fecal pollution in Bayou Lafourche. This is known as microbial source tracking (MST) (McQuaig et al. 2009; Bird et al. 2019).

Bayou Lafourche is located in the Barataria basin in southern Louisiana and is a distributary of the Mississippi River, which starts at Donaldsonville and flows generally southeast for approximately 108 miles to the Gulf of Mexico (Bird et al. 2019). This Bayou serves as the main source of drinking water for a population of about 300,000 and also serves as a habitat for recreational activities, such as fishing and boating. It also provides access to the Gulf of Mexico and many other waterways. Because of this heavy usage, the quality of water in Bayou Lafourche is of vital importance. Since Bayou Lafourche waterways have failed to meet the LDEQ's designated use criteria for acceptable water quality, a total maximum daily load (TMDL) had to be developed in order to reduce fecal indicator bacteria (FIB) and potential enteric pathogens (McQuaig et al. 2009). TMDL plans for pathogen reduction are often difficult because the plan relies on indicator bacteria, which do not give much insight into the source(s) of pollution (McQuaig et al. 2009). In addition, precipitation can facilitate the transport of enteric bacteria and viruses into surface waters by overwhelming wastewater treatment plants, saturating soils (thereby decreasing the efficiency of septic system drain fields), and resulting in direct runoff or groundwater base flow from urban and rural areas (Gentry-Shields et al. 2012). Resuspension associated with rain events may also reintroduce sediment-associated microbes into surface waters and has been shown to increase the concentration of fecal indication bacteria (FIB), coliphages, and enteroviruses in marine and estuarine waters (Gentry-Shields et al. 2012).

In 1972, the Clean Water Act was introduced and section 303(d) of the Act required all states to identify those bodies of water not meeting their designated water use standards and to develop a TMDL for those water bodies (McQuaig et al. 2009). Louisiana Department of Environmental Quality (LDEQ) sets designated water use criteria standards for its bodies of water in the state of Louisiana. These include microbial fecal coliform (FC) standards for drinking water supply, primary contact recreation, secondary contact recreation, and oyster propagation and harvesting. The current goal of the TMDL for Bayou Lafourche is to decrease anthropogenic FC levels instream by 45% during summer months (LDEQ 2012; Belding & Boopathy 2018; Bird et al. 2019).

Fluorometry is a chemical source tracking (CST) method, which identifies human fecal matter by detecting optical brighteners (OBs) (Hartel et al. 2008). OBs are fluorescent whitening agents (FWA) that are found in most household detergents for the purpose of brightening fabrics to compensate for undesired yellowing in clothing (Hagedorn et al. 2005; Cao et al. 2009). OBs have aromatic structures that are activated by light in the near UV range of 360–365 nm and emit light in the blue range of 415–445 nm (Hartel et al. 2008). In the United States, 97% of laundry detergents contain DSBP (4,4′-bis92-sulfostyry bisphenol) and/or DAS1 (4,4′-diamino-2,2′-stilbene-disulfonic acid), both of which are highly soluble (Hartel et al. 2008; Cao et al. 2009). Although these water-soluble compounds have a high affinity for cellulosic material, a small but substantial percentage is lost to the wastewater (Hartel et al. 2007, 2008). The mixing of wastewater and graywater in home plumbing systems allows for the detection of OBs in both septic and sewage systems (Cao et al. 2009). So, it can be implied that high OBs that decay when exposed to UV light are good indicators of human fecal contamination in the bayou. The concern with OB measurements using fluorometry is that some organic matter or aromatic compounds absorb and emit light at wavelengths similar to that of OBs which may give false-positive readings (Cao et al. 2009).

Fecal coliforms and Escherichia coli have been used as indicator organisms to assess the presence of fecal contamination of water samples (Anderson et al. 2005; Girones et al. 2010). The presence of high levels of these indicators suggest fecal pollution and potential health risks, but it is often difficult to link FIB like E. coli to a particular pollution source because E. coli is abundant in warm-blooded animals (Roslev & Bukh 2011). The recovery of FIB does not distinguish the specific source of pollution, so these indicators can sometimes underestimate the health risks associated with recreational water usage (McQuaig et al. 2006). The FIB found in NPS runoff like stormwater is commonly assumed to be derived from animal sources like domestic pets and local wildlife, but there is growing evidence that stormwater systems can be contaminated with sewage due to a failing infrastructure or cross-connections between the stormwater and sewage systems (Sauer et al. 2011). Monitoring for FIB in stormwater does not provide definitive information on the possible sources of contamination, which is a major shortcoming of only stormwater evaluations (Sidhu et al. 2013). Because identifying sources of pollution is challenging, MST and CST methods have been used to distinguish between human and nonhuman sources of fecal pollution in environmental waters (McQuaig et al. 2006; Sidhu et al. 2013).

The detection of sewage has been demonstrated with anthropogenic molecular markers from microorganisms and viruses, which would be a more definitive indicator of fecal contamination (Leskinen et al. 2010). The human polyomavirus BK (HPyV-BK), human-associated anaerobic bacteria Bacteroidales and archaebacteria Methanobrevibacter smithii have been used to track anthropogenic waste in many water systems (Bower et al. 2005; Fong et al. 2005; Gordon et al. 2013). The HPyV-BK is nonpathogenic, maintains lifelong productive infections in the kidneys, and is excreted in urine from human populations; thus high titers have been documented in municipal sewage (McQuaig et al. 2006; Harwood et al. 2009). The HPyV-BK sensitivity, specificity, and correlation with other human-associated markers imply that using HPyV-BK could be a useful predictor of human fecal pollution in environmental waters and a useful component of MST (McQuaig et al. 2006).

Methanobrevibacter smithii is an anaerobic archaeon and the most prominent methanogen in the human gastrointestinal tract, which has been found at concentrations of 107 to 1010 organisms per gram in feces (Ufnar et al. 2006; McQuaig et al. 2012). Fecal anaerobes make up the majority of fecal bacteria in the gastrointestinal tract of humans and may be present at 1,000-fold higher densities than the FC group, making these organisms highly sensitive indicators of fecal pollution (Bower et al. 2005). Harwood et al. (2009) reported HpyVs and M. smithii each more human-specific than human Bacteroidales, and thus expected both to be useful additions to human MST.

Bacteroides spp. are Gram-negative, strictly anaerobic, nonspore-forming bacilli that exceed standard FIB, such as coliforms and enterococci in human and animal feces (McQuaig et al. 2012). They occur at concentrations of 109 to 1011 organisms per gram in feces and 109Bacteriodales organisms per 100 mL in sewage (McQuaig et al. 2012). Meanwhile, traditional FIB concentrations in untreated sewage are approximately 107 CFU per 100 mL for total coliforms and 106 CFU per 100 mL for fecal coliforms and enterococci (McQuaig et al. 2012). The Bacteroidales are dominant members of the intestinal microflora in many animals, including humans, and were correlated with the presence of pathogenic enteric bacteria in environmental waters (Walters et al. 2007; Gordon et al. 2013). Human-associated Bacteroidales have been used as alternative indicators to fecal coliforms in previous studies to detect human fecal input in environmental waters (Bernhard & Field 2000; Bower et al. 2005). The human-associated Bacteroidales polymerase chain reaction (PCR) method has been found to detect sewage in more dilute samples than the HPyV or the M. smithii PCR methods and therefore has the most immediate relevance to regulatory limits based on indicator bacteria concentrations (Harwood et al. 2005; 2009).

The overall goal of this study was to investigate the correlations between OBs, mFC, E. coli, and PCR data in selected sites in Upper Bayou Lafourche and to determine if there is a correlation among these parameters to identify the source of fecal contamination in the water. The novelty of this study is it will accurately identify the problem of malfunctioning on-site sewage systems in the Bayou Lafourche watershed and also will demonstrate the use of OBs along with human fecal markers as a practical application tool to monitor watershed for fecal contamination from a human source.

MATERIALS AND METHODS

Study area

Bayou Lafourche, a branch of the Mississippi River, is located in the Barataria basin of southern Louisiana. Bayou Lafourche is a distributary of the Mississippi River, which starts at Donaldsonville and flows southeast for approximately 108 miles to the Gulf of Mexico. The 34 sites included bayou surface water at bridges and nonpoint sources such as culverts and ditches that directly led into Bayou Lafourche in Ascension (ASCE) and Assumption Parishes (ASSU). The general study site is given in Figure 1. Specific Site IDs were assigned based on parish location starting at the Mississippi River and numbered in sequential order as shown in Figure 2(a)2(f) and Table 1 provides the GPS coordinates for these sites. Study sites began at the Mississippi River in Donaldsonville and continued through Ascension and Assumption parishes until the final site at Frank's Lane in Lafourche parish (LAFO). The land use is predominately rural and agricultural. Culverts and ditches draining homes and subdivisions with single dwelling package plants (PP) that emptied directly or indirectly into Bayou Lafourche were chosen for sampling based on a sanitary, microbiological, and OB survey of NPS inputs to the bayou from both LA 1 and HWY 308 during the summer of 2011.

Table 1

Site ID, description, latitude and longitude, wastewater management of study sites

Parish site IDSampling site brief descriptionLatitudeLongitudeWastewater management
ASCE-1 Mississippi River 30.10763 −90.98754 River 
ASCE-2 PEOPLES Water Intake 30.10647 −90.99157 WT 
ASCE-3a Albert (W. 10th) Street (Donaldsonville) 30.10088 −90.99348 a 
ASCE-4 Popeyes/Stage/hwy LA 1/culvert 30.09747 −91.00112 WT 
ASCE-5a Rondinaud Lane (From Hwy 1) 30.09657 −91.00602 a 
ASCE-6 2165 LA1 ditch 30.09593 −91.02417 PP 
ASCE-7a LA 943 30.08709 −91.02958 a 
ASSU-1 7436LA1 30.06698 −91.02831 PP 
ASSU-2a HWY 998 (Belle Rose) 30.0499 −91.04082 a 
ASSU-3 Tyler Lane/LA1 30.01685 −91.04706 PP 
ASSU-4 Hwy 70 (Paincourtville)/LA1 30.00055 −91.05332 AG 
ASSU-5A Hwy 1005/LA1 culvert 29.99424 −91.0556 PP 
ASSU-5B LA1/bayouside culvert 29.9942 −91.0556 PP 
ASSU-6a St. Vincent Church 29.99323 −91.05408 a 
ASSU-7 College Point/Canaan Baptist Church/Hwy 308/culvert 29.98994 −91.03596 PP 
ASSU-8a Spur 70 (Plattenville) 29.9894 −91.02932 a 
ASSU-9a Bridge St. 29.98899 −91.02415 a 
ASSU-10 St. Benedict Church bayouside culvert 29.98272 −91.01869 PP 
ASSU-11a Hospital Road (Napoleonville) 29.95535 −91.03018 a 
ASSU-12a Hwy 1008 29.94149 −91.02329 a 
ASSU-13 Jefferson St./Ace Hardware/LA1/culvert 29.94029 −91.02266 WT 
ASSU-14 Assumption Water Plant Intake/LA1/bayou sample 29.93526 −91.01575 WT 
ASSU-15a HWY 1010 29.8986 −90.98867 a 
ASSU-16A Georgette Street ditch 29.87065 −90.99386 PP 
ASSU-16B Cancienne Rd Back canal 29.86096 −90.98226 PP 
ASSU-16C Cancienne Rd Levee Backend canal 29.85885 −90.98533 PP 
ASSU-16D Cancienne Road at LA1 in Bayou 29.85921 −90.98562 PP 
ASSU-17a HWY 1011 29.85985 −90.98073 a 
ASSU-18a Hwy 398/1247 (Labadieville) 29.84007 −90.95428 a 
ASSU-19 Convent St./LA 1 culvert 29.83989 −90.95481 PP 
ASSU-20 Brule Street/Labadieville/ LA 1 culvert 29.83935 −90.95454 PP 
ASSU-21A Pear St./Canal/LA1 29.99423 −90.05545 PP 
ASSU-21B Pear St./Bayou/LA1 29.83672 −90.95028 PP 
LAFO-1a Frank Lane (Supreme) 29.81632 −90.88052 a 
Parish site IDSampling site brief descriptionLatitudeLongitudeWastewater management
ASCE-1 Mississippi River 30.10763 −90.98754 River 
ASCE-2 PEOPLES Water Intake 30.10647 −90.99157 WT 
ASCE-3a Albert (W. 10th) Street (Donaldsonville) 30.10088 −90.99348 a 
ASCE-4 Popeyes/Stage/hwy LA 1/culvert 30.09747 −91.00112 WT 
ASCE-5a Rondinaud Lane (From Hwy 1) 30.09657 −91.00602 a 
ASCE-6 2165 LA1 ditch 30.09593 −91.02417 PP 
ASCE-7a LA 943 30.08709 −91.02958 a 
ASSU-1 7436LA1 30.06698 −91.02831 PP 
ASSU-2a HWY 998 (Belle Rose) 30.0499 −91.04082 a 
ASSU-3 Tyler Lane/LA1 30.01685 −91.04706 PP 
ASSU-4 Hwy 70 (Paincourtville)/LA1 30.00055 −91.05332 AG 
ASSU-5A Hwy 1005/LA1 culvert 29.99424 −91.0556 PP 
ASSU-5B LA1/bayouside culvert 29.9942 −91.0556 PP 
ASSU-6a St. Vincent Church 29.99323 −91.05408 a 
ASSU-7 College Point/Canaan Baptist Church/Hwy 308/culvert 29.98994 −91.03596 PP 
ASSU-8a Spur 70 (Plattenville) 29.9894 −91.02932 a 
ASSU-9a Bridge St. 29.98899 −91.02415 a 
ASSU-10 St. Benedict Church bayouside culvert 29.98272 −91.01869 PP 
ASSU-11a Hospital Road (Napoleonville) 29.95535 −91.03018 a 
ASSU-12a Hwy 1008 29.94149 −91.02329 a 
ASSU-13 Jefferson St./Ace Hardware/LA1/culvert 29.94029 −91.02266 WT 
ASSU-14 Assumption Water Plant Intake/LA1/bayou sample 29.93526 −91.01575 WT 
ASSU-15a HWY 1010 29.8986 −90.98867 a 
ASSU-16A Georgette Street ditch 29.87065 −90.99386 PP 
ASSU-16B Cancienne Rd Back canal 29.86096 −90.98226 PP 
ASSU-16C Cancienne Rd Levee Backend canal 29.85885 −90.98533 PP 
ASSU-16D Cancienne Road at LA1 in Bayou 29.85921 −90.98562 PP 
ASSU-17a HWY 1011 29.85985 −90.98073 a 
ASSU-18a Hwy 398/1247 (Labadieville) 29.84007 −90.95428 a 
ASSU-19 Convent St./LA 1 culvert 29.83989 −90.95481 PP 
ASSU-20 Brule Street/Labadieville/ LA 1 culvert 29.83935 −90.95454 PP 
ASSU-21A Pear St./Canal/LA1 29.99423 −90.05545 PP 
ASSU-21B Pear St./Bayou/LA1 29.83672 −90.95028 PP 
LAFO-1a Frank Lane (Supreme) 29.81632 −90.88052 a 

aBridges.

WT, Municipal Wastewater Treatment Plant; PP, Individual Package Plant(s); AG, Agricultural.

Figure 1

A general view of the sampling sites from the Mississippi River to the Bayou Lafourche in the city of Thibodaux, Louisiana, USA with the state of Louisiana map inset.

Figure 1

A general view of the sampling sites from the Mississippi River to the Bayou Lafourche in the city of Thibodaux, Louisiana, USA with the state of Louisiana map inset.

Figure 2

Clusters A–F show the detailed site maps of Bayou Lafourche with specific sampling sites. Table 1 has more information on these sites including GPS coordinates.

Figure 2

Clusters A–F show the detailed site maps of Bayou Lafourche with specific sampling sites. Table 1 has more information on these sites including GPS coordinates.

Sample collection

Samples were divided into groups of three and collected once a week with alternating spatial and temporal morning and afternoon collections: group 1 had 11 sites, group 2 had 11 sites, and group 3 had 12 sites for a total of 34 sites. Group 1 consisted of: ASCE-1–ASSU-4 (11 sites); group 2 consisted of: ASSU-5A–ASSU-14 (11 sites); and group 3 consisted of: ASSU-15–LAFO-1 (12 sites) as indicated in Figure 2.

An ice chest and thermometer were used to store the collected samples in an ice water bath at 4–10 °C. A blank consisting of DI water from our lab was always included for each sample collection. At each sampling site, a 1,000 mL whirl-pak bag (Nasco) was used to store at least 500 mL of water. The samples were put on ice and kept out of the sunlight by storing in an ice chest. All samples were processed within 6 h.

Fecal coliform detection

The detection of fecal coliforms is commonly used for analyzing environmental water quality. Samples were processed according to the membrane filtration technique as per the American Public Health Association's Standard Methods for the Examination of Water and Wastewater (APHA 1998).

Collected water samples were maintained on ice until processing. Each sample was inverted 25 times and then aliquoted into 250 mL Erlenmeyer flasks. Each sample was filtered through a separate membrane filtration unit using a 0.45 μM filter (Fisher Scientific, Pittsburgh, PA). Four volumes of 0.01 mL, 0.1 mL, 1 mL, and 10 mL, respectively, were filtered and the filters placed on Chrom-ECC petri plates. Chrom-ECC is a differential medium recommended for presumptive identification of E. coli and other coliforms in food and environmental samples (CHROMagar, Paris, France). For all volumes less than 10 mL, 10 mL of PBS was added to the filter before the sample was added. All of the petri plates were then placed in the 44.5 °C incubator for 18–24 h. After the samples were incubated, the colonies were interpreted and counted. On Chrom-ECC agar, E. coli appears as blue colonies. A detailed procedure is given in the Supplemental section.

Optical brighteners

The OB decay was determined by exposing water samples to low-wave ultraviolet (UV) light using a handheld Turner fluorometer to differentiate OB fluorescence from FWA and natural organic matter fluorescence. The quality controls used for each sample collection consisted of a deionized water (DI) blank, a laboratory fortified blank, an OB standard (10% PTSA, 1,3,6,8-pyrene tetrasulfonic acid tetrasodium salt) (Turner Design, Sunnyville, CA), and a laboratory fortified blank of a 0.005% solution of laundry detergent (2× Tide liquid, original scent, Procter & Gamble, Cincinnati, OH).

An aliquot of each sample including quality controls was put into separate 100 mL test tubes. Each sample was centrifuged at 2000 RPM for 10 min in order to standardize the samples and remove the turbidity. Each centrifuged sample supernatant was micropipetted into polymethacrylate cuvettes (10 × 10 × 45 mm, Turner Designs). The cuvettes were filled with 2 mL sample. OB levels for each sample were initially read using a Turner Aquafluor Handheld Fluorometer. Each sample was then exposed to UV light (wavelength 365 nm) with a UV BLAK-RAY longwave ultraviolet bench lamp (UVP, Model B-100 A, San Gabriel, CA) at intervals of 5 and 10 min. After each exposure, OB levels were recorded. All measurements were taken in duplicate and reported as averages. The percent degradation was calculated according to the manufacturer's instruction.

PCR detection of human Polyomaviruses (HPyV-BK), human Bacteroidales, and M. smithii from environmental waters

After the data were analyzed, the samples that exceed secondary contact recreation limit mFC counts and had positive OB readings were selected to be examined by the PCR detection of HPyV-BK, human Bacteroidales, and M. smithii. For each selected sample, approximately 500 mL of the environmental water sample was placed into a sterile beaker containing a magnetic stir bar. The pH probe was initially sterilized, and then re-sterilized between samples by immersing it in 10% bleach solution (∼30 s), and rinsing in sterile DI water. The probe was then immersed in 10% sodium thiosulfate solution and finally rinsed with sterile DI water. The probe was then ready for use in a water sample. The pH of the water sample was adjusted to 3.0–3.5 using 20% HCl while stirring because lowering the pH gives the viral capsids a net positive charge.

The sample was placed into the Beckman Coulter Avanti J-E centrifuge at 10,000 RPM at 10 °C for 20 min. The supernatant of the sample was then filtered through a 0.45 μM pore nitrocellulose filter. At least 300 mL were processed. Using sterile forceps, the 0.45 μM filter was folded and placed into a bead tube from the Mo Bio PowerSoil DNA extraction kit (Mo Bio Laboratories, Inc., Carlsbad, CA). If there was a pellet from the sample, then it was placed into a separate bead tube. The bead tubes containing the filters were stored at −80 °C until DNA extraction processing. The DNA of every sample was extracted using the manufacturer's instructions from the Mo Bio PowerSoil DNA kit. The extracted DNA was then stored at −80 °C until PCR processing. The primers and target DNA used (specific primer details are given in Supplemental Table 1) were human polyomavirus BK, total Bacteroidales, human Bacteroidales, and M. smithii.

To run the HPyV-BK, total Bacteroidales, human Bacteroidales, and M. smithii PCR, the reaction mix Go Taq Green (Promega, Madison, WI) was used. Each 25 μL reaction contained: GoTaq Green Master Mix 12.5 μL, forward primer (10 μM) 1.0 μL, reverse primer (10 μM) 1.0 μL, sterile PCR grade water 8.5 μL, and the template 2.0 μL. A thermocycler program was used for HPyV-BK, total Bacteroidales, human Bacteroidales, and M. smithii.

In order to visualize the reaction, 10 μL of each sample was loaded onto a 2% agarose gel for use with HPyV-BK. It was stained with 4 μL of ethidium bromide for each 100 mL, and the gel was run with 8 μL of a 100 bp DNA molecular weight marker. A 1% agarose gel was used for total Bacteroidales, human Bacteroidales, and M. smithii and it was stained with 4 μL of ethidium bromide for each 100 mL. Gels were loaded with 10 μL of each sample and run with 8 μL of a 100 bp DNA molecular weight marker (Fisher Scientific, Pittsburgh, PA).

Statistical analysis

Binary logistic regression was used to analyze the correlations between each method.

RESULTS AND DISCUSSION

Fecal coliform criteria

A total of 437 samples were collected for this study. Samples were collected starting in June 2011 and completed by August 2012. All sites were evaluated for FC counts, E. coli counts, OB reading, OB 5% reduction, and OB ratio. Thirty-four sites were evaluated and the geometric mean was calculated for FC counts and E. coli counts (Table 2).

Table 2

Geometric mean of FC and E. coli counts from Bayou Lafourche study

  Geometric mean(range) (CFUa 100 mL−1) 
SiteNo. of times sampledFCE. coli
ASCE-1 12 213(50–1,000) 33 (18–140) 
ASCE-2 12 109 (20–1,532) 43 (10–145) 
ASCE-3a 12 280(50–2,000) 46 (10–252) 
ASCE-4 12 152,106 (1,636–930,000) 8,628 (718–160,000) 
ASCE-5a 12 596 (155–9,091) 127 (10–636) 
ASCE-6 13 9,286 (685–310,000) 664 (181–8,000) 
ASCE-7a 14 1,084 (236–17,000) 239 (64–5,000) 
ASSU-1 14 267,954 (95,455–950,000) 60,911 (270–530,000) 
ASSU-2a 14 1,085 (218–8,739) 152 (36–4,363) 
ASSU-3 12 415,468 (36,364–980,000) 85,070 (145–480,000) 
ASSU-4 14 1,109 (82–480,000) 216 (20–51,181) 
ASSU-5A 12 11,098 (541–118,182) 267 (40–2,000) 
ASSU-5B 13 1,998 (20–85,455) 122 (10–2,636) 
ASSU-6a 14 1,111 (198–6,667) 183 (20–420) 
ASSU-7 12 178,644 (2,216–970,000) 42,673 (963–400,000) 
ASSU-8 14 1,098 (218–5,315) 188 (90–390) 
ASSU-9 13 1,029 (150–6,486) 209 (100–372) 
ASSU-10 13 4,792 (135–270,000) 171 (20–11,818) 
ASSU-11a 13 587 (140–2,273) 145 (70–380) 
ASSU-12a 12 567 (73–4,144) 182 (45–1,636) 
ASSU-13 12 1,666 (255–40,000) 94 (10–2,000) 
ASSU-14 13 772 (20–26,364) 203 (70–763) 
ASSU-15a 13 555 (90–3,423) 112 (60–818) 
ASSU-16A 13 2,273 (155–34,545) 236 (40–3,727) 
ASSU-16B 13 717 (40–10,455) 84 (10–5,272) 
ASSU-16C 13 1,116 (70–11,636) 91 (20–5,818) 
ASSU-16D 13 3,477 (100–51,818) 161 (30–4,454) 
ASSU-17a 13 666 (55–7,545) 120 (30–2,400) 
ASSU-18a 14 773 (60–12,973) 110 (20–4,414) 
ASSU-19 13 6,478 (391–63,000) 90 (10–3,000) 
ASSU-20 11 144,909 (7,064–490,000) 141 (27–2,972) 
ASSU-21A 13 2,007 (110–50,000) 365 (20–29,090) 
ASSU-21B 13 3,104 (541–37,273) 436 (10–19,090) 
LAFO-1a 13 641 (73–5,946) 88 (20–2,600) 
  Geometric mean(range) (CFUa 100 mL−1) 
SiteNo. of times sampledFCE. coli
ASCE-1 12 213(50–1,000) 33 (18–140) 
ASCE-2 12 109 (20–1,532) 43 (10–145) 
ASCE-3a 12 280(50–2,000) 46 (10–252) 
ASCE-4 12 152,106 (1,636–930,000) 8,628 (718–160,000) 
ASCE-5a 12 596 (155–9,091) 127 (10–636) 
ASCE-6 13 9,286 (685–310,000) 664 (181–8,000) 
ASCE-7a 14 1,084 (236–17,000) 239 (64–5,000) 
ASSU-1 14 267,954 (95,455–950,000) 60,911 (270–530,000) 
ASSU-2a 14 1,085 (218–8,739) 152 (36–4,363) 
ASSU-3 12 415,468 (36,364–980,000) 85,070 (145–480,000) 
ASSU-4 14 1,109 (82–480,000) 216 (20–51,181) 
ASSU-5A 12 11,098 (541–118,182) 267 (40–2,000) 
ASSU-5B 13 1,998 (20–85,455) 122 (10–2,636) 
ASSU-6a 14 1,111 (198–6,667) 183 (20–420) 
ASSU-7 12 178,644 (2,216–970,000) 42,673 (963–400,000) 
ASSU-8 14 1,098 (218–5,315) 188 (90–390) 
ASSU-9 13 1,029 (150–6,486) 209 (100–372) 
ASSU-10 13 4,792 (135–270,000) 171 (20–11,818) 
ASSU-11a 13 587 (140–2,273) 145 (70–380) 
ASSU-12a 12 567 (73–4,144) 182 (45–1,636) 
ASSU-13 12 1,666 (255–40,000) 94 (10–2,000) 
ASSU-14 13 772 (20–26,364) 203 (70–763) 
ASSU-15a 13 555 (90–3,423) 112 (60–818) 
ASSU-16A 13 2,273 (155–34,545) 236 (40–3,727) 
ASSU-16B 13 717 (40–10,455) 84 (10–5,272) 
ASSU-16C 13 1,116 (70–11,636) 91 (20–5,818) 
ASSU-16D 13 3,477 (100–51,818) 161 (30–4,454) 
ASSU-17a 13 666 (55–7,545) 120 (30–2,400) 
ASSU-18a 14 773 (60–12,973) 110 (20–4,414) 
ASSU-19 13 6,478 (391–63,000) 90 (10–3,000) 
ASSU-20 11 144,909 (7,064–490,000) 141 (27–2,972) 
ASSU-21A 13 2,007 (110–50,000) 365 (20–29,090) 
ASSU-21B 13 3,104 (541–37,273) 436 (10–19,090) 
LAFO-1a 13 641 (73–5,946) 88 (20–2,600) 

aBridges.

Bold represents exceeding 2,000 secondary contact recreation and drinking water intake limit.

The ingestion of water that is contaminated with human or animal feces poses the greatest risk for infections with enteric pathogens. Since enteric pathogens may not be detected when at low concentrations, the detection of indicator organisms is widely used to identify potential sources of fecal contamination. E. coli, Enterococci, and FC have been used for water quality monitoring due to low cost, ease of use, and as an indicator of the presence of pathogens in surface waters and the risk of disease (Sauer et al. 2011; Kishinhi et al. 2013). In Bayou Lafourche, the analysis of surface waters from the bayou and influent runoff sites were sampled monthly and were evaluated for two bacterial indicators: FC and E. coli. Influent sites in this study consisted of ditches and culverts that eventually flow to Bayou Lafourche.

Water samples were collected for a year alternating between rain and non-rain events and time of day. Surface waters from the bayou were collected on bridges that cross the waterway. As seen in Table 2, only water directly from the Mississippi River at the intake for Bayou Lafourche (ASCE-1) met the state's criteria for primary contact recreational use of water. All remaining sites, based on geometric mean calculations, did not meet the primary contact criteria, but all sites were within the state guidelines for secondary contact recreation/Drinking Water Intake (SCR/DWI). The evaluation of rain events shows an increase in the recovery of fecal coliforms and E. coli. These data represent the increased levels of potential anthropogenic contamination entering the waterway as NPS contamination. One site (ASCE-7), a rural area with older homes, exceeds the secondary recreation contact limits of the state during these events.

A total of 23 sites that drain directly into the bayou were selected based on earlier results. A total of 14 of these sites failed to meet the State on Louisiana criteria for secondary contact recreational based on fecal coliform (FC) levels. Two sites selected are drinking water intakes for Ascension Parish (ASCE-2) and Assumption Parish (ASSU-14). Each of these sites met the criteria for drinking water intake. Two of the cities along the bayou are incorporated: Donaldsonville (ASCE 1-4) and Napoleonville (ASSU 11-13). One of these sites (ASCE-4) failed to meet the secondary contact recreation limit. This area is a mixed commercial and residential area on both sides of the bayou. Of the remaining sites, 10 areas failed to meet the secondary contact and drinking water intake criteria. ASCE-6 in Ascension Parish is a rural/agricultural area, and ASSU-1, ASSU-3, ASSU-5A, ASSU-5B, ASSU-7, AASU-10, AASU-16A, AASU-16D, AASU 19, and AASU-21B in Assumption Parish are older residential areas on either side of the bayou. All of the waterway samples for fecal coliforms taken at bridges were elevated as compared to the original water entering the waterway (ASCE-1). However, all of the bridge sites remain within acceptable limits for secondary contact and drinking water intake but are not acceptable for primary contact recreation.

The influence of rain on areas of the study was noted at sites ASSU-10, ASSU-16A-C, and ASSU 21A and ASSU 21B. All sites were analyzed for the effect of rain and non-rain events on the recovery of fecal coliforms and E. coli. Though most of the bayou surface water sites showed some increase with rain events, there was no significant difference in the recovery of fecal coliforms. However, the recovery of E. coli in surface water showed a significant difference (p < 0.05). All of the influent sites failed to show any significant difference with rain events for either fecal coliforms or E. coli. Higher numbers of FIB and enteric pathogens have been previously reported following rain events (Englande et al. 2002; Sidhu et al. 2013). Effluent from poorly operating septic tank systems that are discharged to drainage ditches leading to waterways contribute to anthropogenic contamination (Englande et al. 2002). Leakages in aging sewage infrastructure and cross connections are under-recognized sources of sewage contamination in stormwater (Sidhu et al. 2013).

In this study, the FC input was somewhat diluted when it reached the bayou due to the larger volume of water as compared to a smaller volume of influent. In other studies of Mississippi waterways, high numbers of fecals were observed in Bayou Heron and Bayou Cumbest by Kishinhi et al. (2013). The area around Bayou Heron is surrounded by many trees that harbor different species of animals and birds, similar to Bayou Lafourche (Kishinhi et al. 2013). Studies using MST have revealed that wildlife and waterfowl make important contributions to fecal counts (Kishinhi et al. 2013). Monitoring for traditional indicators alone does not necessarily address the presence of human fecal pollution but is one tool among many in microbial water quality assessment. According to Hill et al. (2006) in Bayou Dorcheat (North Louisiana), NPS pollution that is carried by surface runoff has a significant effect on bacterial levels in water resources, and it was found that a significant increase in the FC numbers may be associated with average rainfall amounts. Fecal coliforms cannot be evaluated alone as an indicator of anthropogenic contamination in Bayou Lafourche.

Since fecal coliforms are found in both animal and human sources and vary greatly in their potential to predict human pathogens, measuring their levels contributes little to our determination of anthropogenic contamination. Testing for E. coli is more specific than FC because E. coli is only found in warm-blooded animals. According to Sidhu et al. (2013), high numbers of E. coli have been observed in the stormwater runoff and are likely due to the presence of fresh fecal contamination from sewage leakage and animal sources. In this study, the recovery of E. coli was used to evaluate samples for anthropogenic molecular markers. Samples with high FC concentration and E. coli data were used for analysis with PCR results for molecular markers associated with anthropogenic contamination.

Optical brightener criteria

The detection of OBs for anthropogenic contamination has been shown to better predict anthropogenic contamination (Cao et al. 2009). The data for OB are given in Figure 3.

Figure 3

Sites during rain and no rain events with OB reading of 15 FU or greater indicate potential anthropogenic contamination.

Figure 3

Sites during rain and no rain events with OB reading of 15 FU or greater indicate potential anthropogenic contamination.

All bridge sites had initial OB readings of less than 15 FU and was considered negative. During some of the rain events, 2 bridge sites (ASSU-18 and LAFO-1) had OB readings over 15 but did not have an 8% reduction with 5-min UV exposure indicating possible natural organic matter fluorescence. Eighteen of the influent sites were tested for the 8% reduction following UV exposure. Ten sites were then tested for the OB ratio according to procedures by Cao et al. (2009). The sites of ASCE-6 in Ascension Parish, ASSU-1, ASSU-3, ASSU-5B, ASSU-7, ASSU-10, ASSU-13, and ASSU-19 in Assumption Parish met all the OB ratio criteria for anthropogenic contamination when looking at the overall geometric mean. All sites tested positive for OB ratio are older rural locations on the east (HWY 308) and west (LA Hwy 1) bank of Bayou Lafourche.

The combination of FC and OB criteria showed that the sites of ASCE-6, ASSU-5B, ASSU-13, and ASSU-19 exceed the 400 FC/100 mL primary contact recreation limit and the <1.5 ratio. The sites of ASSU-1, ASSU-3, and ASSU-7 exceed the 2,000 FC/100 mL secondary contact recreation and drinking water intake limits.

Fluorometry-based OB detection is advantageous compared to other MST methods because it is rapid, simple, and inexpensive (Hartel et al. 2008). High initial fluorescence has been found to correspond with high levels of fecal bacteria in field studies (Hartel et al. 2008). In this study, initial OB readings of 15 fluorescence units (FU) or greater was the criterion for ‘potential anthropogenic contamination.’ Samples with initial OB reading of 15 or greater FU and a 5-min UV degradation of 8% or greater were exposed to UV light for an additional 5 min. A ratio of 1.5 or less for the 10-min to 5-min exposure is an indication of ‘positive anthropogenic contamination’. All data were calculated as a geometric mean. Based on geometric means at the data, samples failing the criteria for any of the tests were excluded from the subsequent dataset. Of the samples tested for initial OB levels, 18 sites were tested for an 8% reduction. Of these 18 sites, only 10 met criteria or ratio of reduction testing. Only 7 sites of the 34 met criteria for anthropogenic contamination by CST.

A concern with using OB measurements in water from ditches and the bayou is that some organic matter and aromatic compounds absorb and emit light at wavelengths similar to that of OBs (Hartel et al. 2008). According to Cao et al. (2009), organic compounds degrade at a slower rate when exposed to UV light as compared to laundry detergent, which will degrade rapidly when exposed to UV light. Therefore, the sites that exceeded the first OB criteria for ‘potential anthropogenic’ were then exposed to UV light for 5 min in order to further determine whether the water at each site had anthropogenic or natural organic compounds. Sites that showed a degradation of 8% or greater indicated a ‘probable anthropogenic contamination’.

Rain events showed site-specific changes in the detection of OBs. OB detection for sites ASSU-5A, ASSU-5B, and ASSU-10 during rain events met ‘probable anthropogenic’ criteria (initial reading of greater than 15 FU). OB detection for the influent sites of ASSU-3, ASSU-7, ASSU-13, ASSU-19, and ASSU-20 during no rain events met ‘probable anthropogenic’ criteria. None of the bridge sites met the ≥8% reduction criteria confirming that these sites were not anthropogenic. The samples that met the criteria of >8% UV reduction criteria for probable anthropogenic were further tested for % reduction.

Each ‘probable anthropogenic’ sample was exposed to an additional 5 min of UV exposure and calculated as a ratio of 10 min/5 min for % reduction ratio. A ratio of 1.5 or less for the 10-min to 5-min UV exposure was designated as an indication of positive ‘anthropogenic contamination’ for OBs. The sites ASCE-6 in Ascension Parish, ASSU-1, ASSU-3, ASSU-5A, ASSU-7, ASSU-13, and ASSU-19 in Assumption Parish met all of the OB ratio criteria for ‘anthropogenic contamination’ using geometric mean determinations. These sites are considered positive for CST. All of these sites are from rural areas along the east and west bank of Bayou Lafourche. These residents use either PP or septic tanks for the treatment of wastewater.

Two bridge sites, ASSU-18 and LAFO-1, met the criteria for potential anthropogenic contamination during single rain events, but these samples did not meet the criteria (8% reduction with 5 min UV exposure) for the presence of anthropogenic markers. All other bridge sites are not considered anthropogenic according to preliminary OB criteria. Both water intake sites, ASCE-2 (Assumption Parish) and ASSU-14 (Assumption Parish), did not meet the criteria for initial OB and are negative for CST.

However, a positive OB ratio alone was not used as the final indicator of anthropogenic contamination in Bayou Lafourche. They were used in combination with FC data to further confirm these sites as anthropogenic. The combination of FC and OB criteria showed that the sites of ASCE-6, ASSU-1, ASSU-3, ASSU-5B, ASSU-7, ASSU-13, and ASSU-19 exceeded the Department of Environmental Quality limit of 2,000 FC/100 mL for the drinking water intake and the secondary contact recreation limit and the ≤1.5 OB ratio. These sites were positive for both CST and MST. These sites were further evaluated using three anthropogenic molecular markers to confirm if the sites were human in origin.

Polymerase chain reaction

A total of 129 samples were selected to run for PCR in this study based on passing both the FC and OB criteria (Table 3). Of the 129 samples, 27/129 were found to be positive by PCR for HB, 45/129 were found to be positive for MS, and 25/129 were found to be positive for HPyV. Binary logistic regression was used to find a predictive relationship between FC, EC, OB, OB 5% reduction, OB ratio, and anthropogenic molecular markers during rain and no rain events.

Table 3

Number of positive PCRs for human markers of fecal pollution from Bayou Lafourche Study

SiteNo. of times sampled for PCRNo. of samples positive by PCR/no. of samples tested
HBMSHpyV
ASCE-1 1/1 0/1 0/1 
ASCE-2 12 0/12 1/12 0/12 
ASCE-3a 0/0 0/0 0/0 
ASCE-4 12 0/12 5/12 1/12 
ASCE-5a 1/1 0/1 0/1 
ASCE-6 1/7 2/7 0/7 
ASCE-7a 0/1 1/1 0/1 
ASSU-1 14 8/14 6/14 7/14 
ASSU-2a 0/3 1/3 0/3 
ASSU-3 12 9/12 7/12 7/12 
ASSU-4 0/1 0/1 0/1 
ASSU-5A 1/6 1/6 1/6 
ASSU-5B 10 1/10 2/10 2/10 
ASSU-6a 0/1 0/1 1/1 
ASSU-7 11 0/11 6/11 3/11 
ASSU-8 0/1 1/1 0/1 
ASSU-9 0/0 0/0 0/0 
ASSU-10 2/5 1/5 0/5 
ASSU-11a 0/0 0/0 0/0 
ASSU-12a 0/0 0/0 0/0 
ASSU-13 0/5 3/5 0/5 
ASSU-14 0/5 2/5 0/5 
ASSU-15a 0/1 1/1 0/1 
ASSU-16A 0/4 1/4 1/4 
ASSU-16B 0/0 0/0 0/0 
ASSU-16C 0/0 0/0 0/0 
ASSU-16D 0/1 0/1 0/1 
SiteNo. of times sampled for PCRNo. of samples positive by PCR/no. of samples tested
HBMSHpyV
ASCE-1 1/1 0/1 0/1 
ASCE-2 12 0/12 1/12 0/12 
ASCE-3a 0/0 0/0 0/0 
ASCE-4 12 0/12 5/12 1/12 
ASCE-5a 1/1 0/1 0/1 
ASCE-6 1/7 2/7 0/7 
ASCE-7a 0/1 1/1 0/1 
ASSU-1 14 8/14 6/14 7/14 
ASSU-2a 0/3 1/3 0/3 
ASSU-3 12 9/12 7/12 7/12 
ASSU-4 0/1 0/1 0/1 
ASSU-5A 1/6 1/6 1/6 
ASSU-5B 10 1/10 2/10 2/10 
ASSU-6a 0/1 0/1 1/1 
ASSU-7 11 0/11 6/11 3/11 
ASSU-8 0/1 1/1 0/1 
ASSU-9 0/0 0/0 0/0 
ASSU-10 2/5 1/5 0/5 
ASSU-11a 0/0 0/0 0/0 
ASSU-12a 0/0 0/0 0/0 
ASSU-13 0/5 3/5 0/5 
ASSU-14 0/5 2/5 0/5 
ASSU-15a 0/1 1/1 0/1 
ASSU-16A 0/4 1/4 1/4 
ASSU-16B 0/0 0/0 0/0 
ASSU-16C 0/0 0/0 0/0 
ASSU-16D 0/1 0/1 0/1 

aBridges.

During no rain events, microbial indicators of EC vs HpyV (R2 = 0.1019, P = 0.0097) and EC vs MS (R2 = 0.0562, P = 0.0269) both showed a correlation. FC concentrations did not show a correlation with any of the anthropogenic markers for both no rain and rain events. During no rain events, OB indicators of OB ratio vs HpyV (R2 = 0.1994, P = 0.0022), OB 5 min vs HpyV (R2 = 0.184, P = 0.0031), OB 5 min vs HB (R2 = 0.0841, P = 0.0099), and OB ratio vs HB (R2 = 0.0972, P = 0.0056) each showed a correlation. All OB indicator criteria did not show any correlations with anthropogenic markers during rain events (statistical analysis is given in Supplemental Tables 2 and 3).

Anthropogenic markers

Based on FC, the absence of markers is at or below 104 for all markers (Figure 4). The presence of markers for this study was detected at 105 for HB and HPyV based on FC. MS can be found between 104 and 105. The percent occurrence of HB was 20.9%, the percent occurrence of HPyV was at 18.5%, and the percent occurrence for MS was at 33.06% (Figure 5). The sensitivity of HB was 59.26%, the sensitivity of HpyV was 62.96%, and the sensitivity of MS was 55.56% (Table 4). The specificity of HB was 77.78%, the specificity of MS was 88.89%, and the specificity of HpyV was 100%.

Table 4

Percent sensitivity and specificity of markers

Molecular markers% Sensitivity% Specificity
Human Bacteriodales HF 183 59.26 77.78 
Methanobrevibacter smithii 55.56 88.89 
Human polyomavirus BK 62.96 100 
Molecular markers% Sensitivity% Specificity
Human Bacteriodales HF 183 59.26 77.78 
Methanobrevibacter smithii 55.56 88.89 
Human polyomavirus BK 62.96 100 
Figure 4

The presence and absence of anthropogenic markers in relation to the total amount of FC present.

Figure 4

The presence and absence of anthropogenic markers in relation to the total amount of FC present.

Figure 5

The percent occurrence of each molecular marker.

Figure 5

The percent occurrence of each molecular marker.

The human polyomavirus BK (HPyV-BK), human-associated anaerobic bacteria Bacteroidales H183(HB), and archaebacteria Methanobrevibacter smithii (MS) have been used to track anthropogenic waste (Bower et al. 2005; Fong et al. 2005). Molecular detection of viruses offers several advantages over traditional viral assays, such as cell culture. PCR viral detection is less laborious and time-consuming and is more specific and sensitive than cell culture (Fong et al. 2005). The PCR is capable of detecting viruses that are either difficult to grow in cultured cells or replicate without producing cytopathogenic effects in cells (Fong et al. 2005). The HPyV-BK is nonpathogenic, maintains lifelong productive infections in the kidneys, and is excreted in urine from human populations, which resulted in high titers in municipal sewage (McQuaig et al. 2006; Harwood et al. 2009). This marker is found in most of the population but not all. The HPyV-BK sensitivity, specificity, and correlation with other human-associated human markers imply that using HPyV-BK could be a useful predictor of human fecal pollution in environmental waters and a useful component of MST (McQuaig et al. 2006).

Methanobrevibacter smithii is an anaerobic archaeon and the most prominent methanogen in the human gastrointestinal tract, which has been found at concentrations of 107 to 1010 organisms per gram in feces (Ufnar et al. 2006; McQuaig et al. 2012). Fecal anaerobes make up the majority of fecal bacteria in the gastrointestinal tract of humans and may be present at 1,000-fold-higher densities than the FC group making these organisms highly sensitive indicators of fecal pollution (Bower et al. 2005). Bacteroides spp. are Gram-negative, strictly anaerobic, non-spore-forming bacilli that exceed standard FIB such as coliforms and enterococci in human and animal feces (McQuaig et al. 2012). They occur at concentrations of 109 to 1011 organisms per gram in feces and 109Bacteriodales organisms per 100 mL in sewage (McQuaig et al. 2012). Human-associated Bacteroidales have been used as alternative indicators to fecal coliforms in previous studies to detect human fecal input in environmental waters (Bower et al. 2005).

In this study, 45/124 were found to be positive for MS and 25/124 were found to be positive for HpyV. The MS had the highest number of samples that were found to be positive, probably because it is a prominent marker in the human GI tract, but it is not the most human-specific. In other studies, HpyV has been shown to be the most human-specific (100%); however, the human-associated Bacteroidaes and M. smithii were 96% and 98% specific (Harwood et al. 2009). All three markers have been shown to be 100% sensitive in a previous study (Harwood et al. 2009). In this study, the HpyV showed 100% specificity and the HB and MS showed 77.78% and 88.89% specificity, respectively. The HpyV also had the highest sensitivity (62.96%) and the HB and MS showed 59.26% and 55.56% sensitivity, respectively. The absence of all molecular markers in this study is at or below 104. The markers were detected at 105 for HB and HPyV. The MS can be found between 104 and 105. Human Bacteroides is present at higher concentrations in sewage and therefore is a more sensitive marker in dilute samples (Gordon et al. 2013). Harwood et al. (2009) reported HpyVs and M. smithii each more human-specific than human Bacteroidales, thus expected both to be useful additions to human MST.

Binary logistic regression was used to find a predictive relationship between FC, EC, OB, OB 5% reduction, OB ratio, and anthropogenic molecular markers during rain and no rain events. During no rain events, microbial indicators of EC vs HpyV and EC vs MS showed a correlation. The FC concentrations did not show a correlation with any of the anthropogenic markers for both no rain and rain events. This indicated that FC was not a good indicator to determine if sites were anthropogenic for both rain and no rain events and that E. coli is a better indicator than FC. According to McQuaig et al. (2006), high FIB counts in the absence of marker detection were not unexpected because there are many sources of fecal bacteria other than human fecal pollution, including stormwater and agricultural runoff. Several studies have suggested that FC levels cannot be used to predict the occurrence of human viruses (Fong et al. 2005). The lack of correlation between indicator organisms and human-associated markers observed in this study is not an unusual outcome (McQuaig et al. 2006). The Bacteroides marker was detected by PCR during combined sewer overflow events with E. coli levels of <235 CFU and there were instances in which the human-specific Bacteroides marker was absent when E. coli levels were in excess of EPA-recommended levels (McQuaig et al. 2006).

In this study, during no rain events, the OB ratio vs HpyV, OB 5 min% reduction vs HpyV, OB 5 min% reduction vs HB, and OB ratio vs HB each showed a correlation. All OB indicator criteria did not show any correlations with anthropogenic markers during rain events. So, OB readings alone are not a good indicator but using the OB 5 min% reduction and the OB ratio during no rain events gave a predictive relationship when combined with HB or HpyV. In application to Bayou Lafourche, using more than one human sewage marker would be beneficial to exploit each marker. In this study, using HpyV or HB with OB ratio or OB 5 min% reduction during no rain events would be the best indicator to predict anthropogenic contamination in Bayou Lafourche. The MS marker should not be used in Bayou Lafourche as an indicator because it was the least sensitive and specific marker of this study along with having no correlation to any OB criteria. The absence of any of the three markers means that either there is no human input in that source or that the input was too diluted for the methods to detect. The elimination of anthropogenic contamination will help restore water quality to its designated uses for drinking water, and primary and secondary contact recreation.

The practical application of this study shows the use of anthropogenic sewage markers to positively identify the fecal origin in the watershed, so the corrective measures can be taken to rectify the malfunctioning sewage treatment systems. This method can be used easily in the developing countries where fecal contamination of watershed is a very common occurrence.

CONCLUSIONS

The standard fecal indicator bacteria such as FC are currently used for water quality monitoring in Louisiana, but the difficulty is that they are found in both animal and anthropogenic sources. These fecal coliforms can vary in their ability to carry human pathogens therefore measuring FC levels insufficiently contributes to knowledge of human contamination in Bayou Lafourche. In this study, initial OB readings, FC, E. coli, and M. smithii were found not to be good indicators of human fecal contamination. So, we recommend using the two anthropogenic sewage markers HB and HPyV in Bayou Lafourche because it would be beneficial to exploit each marker. We also suggest using HpyV or HB with OB ratio or OB 5 min% reduction during no rain events as the best indicator to predict anthropogenic contamination in Bayou Lafourche. In future studies, long-term monitoring of Bayou Lafourche is recommended to monitor the water quality using anthropogenic sewage markers.

SUPPLEMENTARY MATERIAL

The Supplementary Material for this paper is available online at https://dx.doi.org/10.2166/aqua.2019.063.

ACKNOWLEDGEMENT

This project was financially supported by a grant from the Louisiana Department of Environmental Quality.

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