Effect of Human Development on Bacteriological Water Quality in Coastal Watersheds

Mallin, Michael A.; Williams, Kathleen E.; Esham, E. Cartier; Lowe, R. Patrick

doi:10.1890/1051-0761(2000)010[1047:eohdob]2.0.co;2

Cited by 353 publications

(203 citation statements)

References 23 publications

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“…In urban areas, the combination of extensive impervious surface cover and high density of storm drains promote the rapid flushing of bacteria from lawns, roads, and other surfaces into streams (Frenzel & Couvillion, 2002;Mallin et al, 2000). However, we have documented high concentrations of E. coli and total coliforms under baseflow, rather than storm flow, conditions.…”

Section: Urban Land Cover and Bacterial Abundancementioning

confidence: 66%

“…For example, Frenzel and Couvillion (2002) found that concentrations of E. coli, fecal coliforms, and enterococci were higher in stream sub-basins with higher human population densities in and near Anchorage, Alaska. Similarly, Mallin, Williams, Esham, and Lowe (2000) found that fecal coliform abundance correlated positively with human population density, percentage of developed land, and percentage of impervious surface in five tidal creek basins in North Carolina.…”

Section: Urban Land Cover and Bacterial Abundancementioning

confidence: 85%

“…Nonetheless, the highest concentrations of coliforms measured in our study (>60,000 cells/100 ml) occurred in the urban headwaters. A number of studies have provided evidence that pets (dogs and cats) are the primary sources of enteric bacteria in urban runoff and streams (Kelsey, Porter, Scott, Neet, & White, 2004;Mallin et al, 2000;Young & Thackston, 1999). The urban headwaters of Big Brushy Creek flow through residential areas where pet feces could be sources of coliform bacteria.…”

Section: Urban Land Cover and Bacterial Abundancementioning

confidence: 99%

“…In addition, the slightly higher rainfall in winter may increase run-off of coliforms to streams. Mallin et al (2000) have noted that fecal coliform abundance correlates positively with nitrate and phosphate concentrations and turbidity in tidal creeks along the coast of North Carolina. This observation raises the possibility that increased nutrient loading and turbidity from urban areas might enhance the growth or survival of coliform bacteria in streams and rivers.…”

Section: Urban Land Cover and Bacterial Abundancementioning

confidence: 99%

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Urban Influences on Stream Chemistry and Biology in the Big Brushy Creek Watershed, South Carolina

Lewis

Mitchell

Andersen

et al. 2007

Water Air Soil Pollut

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Naturally high total dissolved solids and upstream agricultural runoff often mask the influence of urban land cover on stream chemistry and biology. We examined the influence of headwater urbanization on the water chemistry, microbiology, and fish communities of the Big Brushy Creek watershed, a 96 km 2 drainage basin in the piedmont of South Carolina, USA. Concentrations of most major anions and cations (especially nitrate, sulfate, chloride, sodium, potassium, and calcium) were highest in the urban headwaters and decreased downstream. Generally, the highest concentrations of suspended coliform bacteria occurred in the urban headwaters. In contrast, stream habitat quality and the abundance, species richness, and species diversity of fishes did not differ significantly between urban and rural sites. Discharge of wastewater treatment plant effluent at one rural location caused an increase in concentrations of many solutes and possibly the abundance of benthic algae. We hypothesize that atmospheric dry deposition and domestic animal wastes are important sources of stream solutes and of coliform bacteria, respectively, in the urban headwaters. The lack of significant differences in fish abundance and diversity between urban and rural sites may indicate that urban development in the Big Brushy Creek watershed has not yet degraded habitat conditions greatly for stream fishes. Alternatively, agriculture or other land uses may have degraded stream habitat quality throughout the watershed prior to urbanization.

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Section: Urban Land Cover and Bacterial Abundancementioning

confidence: 66%

Section: Urban Land Cover and Bacterial Abundancementioning

confidence: 85%

Section: Urban Land Cover and Bacterial Abundancementioning

confidence: 99%

Section: Urban Land Cover and Bacterial Abundancementioning

confidence: 99%

See 2 more Smart Citations

Urban Influences on Stream Chemistry and Biology in the Big Brushy Creek Watershed, South Carolina

Lewis

Mitchell

Andersen

et al. 2007

Water Air Soil Pollut

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“…Liebezeit and Wostmann (2010) stated that the most dominant fecal contamination in the water of the Siak River in Pekanbaru was caused by the large population. Mallin et al, (2000) explained that the abundance of fecal coliform significantly correlated with the number of inhabitants in the basin, and even highly correlated with the percentage of land area developed in the watershed.…”

Section: Total Coliform Oil and Fatmentioning

confidence: 96%

The Quality of Water of the Downstream of the Siak River, Riau Province, Based on Tidal Condition

et al. 2017

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The quality of water in a river is affected by its natural condition and pollutant input originated from activities conducted around the river. In the Siak river, however, the black water effect influences the distribution of the pollutant in general. To understand the quality of water in the black water affected by an area, a study was conducted from December 2015 to July 2016. The water was sampled during low and high tides, in 8 sampling sites that were distributed along the river, from the mouth of the river in Siak Sri Indrapura Regency to upstream in Palas Village, Kampar Regency (around 180 km from the mouth of the river). The results showed that in the downstream of the Siak river, the quality of water during the low and high tides was worse than the 3 rd Class Water Quality Standard issued by the Government Regulation (GR No. 82 / 2001) except for the concentration of nitrate, total coliform, Hg, oil and fat. The BOD was 14-39.2 mg/L (the high tide) and 17-45.6 mg/L (the low tide), COD was 51.76-80.62 mg/L (the high tide) and 51.76-69.12 mg/L (the low tide), NH 3 -N was 0.03-1.09 mg/L (the high tide) and 0.03-0.92 mg/L (the low tide), while the NO 2 -N was 0.13-0.17 mg/L (the high tide) and 0.13-0.22 mg/L (the low tide). Based on the Storet Index, the water of the downstream in the Siak river during the low and the high tide can be categorized as heavily polluted (score -52 to -70), and it tends to decline during the high tide.

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Spatial scales of optical variability in the coastal ocean: Implications for remote sensing and in situ sampling

et al. 2016

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Use of ocean color remote sensing to understand the effects of environmental changes and anthropogenic activities on estuarine and coastal waters requires the capability to measure and track optically detectable complex biogeochemical processes. An important remote sensor design consideration is the minimum spatial resolution required to resolve key ocean features of physical and biological significance. The spatial scale of variability in optical properties of coastal waters has been investigated using continuous, along‐track measurements collected using instruments deployed from ships, aircraft, and satellites. We defined the average coefficient of variance, trueCV¯a, within an image pixel as the primary statistical measure of subpixel variability and investigated how trueCV¯a changes as a function of the Ground Sampling Distance (GSD). In general, d trueCV¯a/dGSD is positive, indicating that the subpixel variability increases with GSD. The relationship between trueCV¯a and GSD is generally nonlinear and the greatest rate of change occurs at small spatial scales. Points of distinct transition in the relationship between trueCV¯a and GSD are evident between 75 and 600 m, varying depending on the location and the optical parameter, and representing the GSD above which most of the spatial variability due to small‐scale features is subsumed within a pixel. At GSDs greater than the transition point, most of the small‐scale variability occurs at subpixel scales and, therefore, cannot be resolved. On average, the transition GSD is around 200 m. The results have application in both sensor design and in situ sampling strategy in support of coastal remote sensing operations.

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Effect of Human Development on Bacteriological Water Quality in Coastal Watersheds

Cited by 353 publications

References 23 publications

Urban Influences on Stream Chemistry and Biology in the Big Brushy Creek Watershed, South Carolina

Urban Influences on Stream Chemistry and Biology in the Big Brushy Creek Watershed, South Carolina

The Quality of Water of the Downstream of the Siak River, Riau Province, Based on Tidal Condition

Spatial scales of optical variability in the coastal ocean: Implications for remote sensing and in situ sampling

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