scholarly journals Spatial modeling of tidal and land use impacts on Escherichia coli contamination and fluctuation in Asia's urban river environmental gradient

2021 ◽  
Author(s):  
Andri A Wibowo
Keyword(s):  
Escherichia Coli ◽  
Land Use ◽  
Spatial Modeling ◽  
Environmental Gradients ◽  
High Tide ◽  
River Mouth ◽  
River System ◽  
Urban River ◽  
Land Use Impacts ◽  
E Coli

In the river, pathogens are the leading cause for rivers to exceed water and health quality standards. The GIS based spatial modeling and analysis were conducted to estimate Escherichia coli (E. coli) contaminated river bodies based on environmental and spatial gradients such as dissolved oxygen, pH, tidal, temperature and current in Asia urban river located in Kapuas river of Kalimantan. The E. coli was sampled from the river mouth up to the upstream land uses dominated by residential. The E. coli contamination was higher in the river mouth and in residential area as well. Likewise, E. coli contamination was higher during the low tide than high tide. During the high tide, the E. coli contamination were significantly affected by temperature and current (r2>0.5). Meanwhile, during the low tide, there were no dominant environmental factors that affect E. coli contamination. Hence, by knowing the spatial model of E. coli contamination driven by tidal, land use and environmental gradients, this paper has contributed to the advance management of water and river system.

scholarly journals Effects of land use and water quality on greenhouse gas emissions from an urban river system

2020 ◽  
Author(s):  
Long Ho ◽  
Ruben Jerves-Cobo ◽  
Matti Barthel ◽  
Johan Six ◽  
Samuel Bode ◽  
...  
Keyword(s):  
Water Quality ◽  
Land Use ◽  
Urban Areas ◽  
Anthropogenic Activities ◽  
Ghg Emissions ◽  
Flow Characteristics ◽  
River System ◽  
Urban River ◽  
Polluted Water ◽  
Land Use Types

Abstract. Rivers act as a natural source of greenhouse gases (GHGs) that can be released from the metabolisms of aquatic organisms. Anthropogenic activities can largely alter the chemical composition and microbial communities of rivers, consequently affecting their GHG emissions. To investigate these impacts, we assessed the emissions of CO2, CH4, and N2O from Cuenca urban river system (Ecuador). High variation of the emissions was found among river tributaries that mainly depended on water quality and neighboring landscapes. By using Prati and Oregon Indexes, a clear pattern was observed between water quality and GHG emissions in which the more polluted the sites were, the higher were their emissions. When river water quality deteriorated from acceptable to very heavily polluted, their global warming potential (GWP) increased by ten times. Compared to the average estimated emissions from global streams, rivers with polluted water released almost double the estimated GWP while the proportion increased to ten times for very heavily polluted rivers. Conversely, the GWP of good-water-quality rivers was half of the estimated GWP. Furthermore, surrounding land-use types, i.e. urban, roads, and agriculture, significantly affected the river emissions. The GWP of the sites close to urban areas was four time higher than the GWP of the nature sites while this proportion for the sites close to roads or agricultural areas was triple and double, respectively. Lastly, by applying random forests, we identified dissolved oxygen, ammonium, and flow characteristics as the main important factors to the emissions. Conversely, low impact of organic matter and nitrate concentration suggested a higher role of nitrification than denitrification in producing N2O. These results highlighted the impacts of land-use types on the river emissions via water contamination by sewage discharges and surface runoff. Hence, to estimate of the emissions from global streams, both their quantity and water quality should be included.

scholarly journals High quantities of multidrug-resistant Escherichia coli are present in the Machángara urban river in Quito, Ecuador

2019 ◽  
Vol 18 (1) ◽  
pp. 67-76 ◽  
Author(s):  
David Ortega-Paredes ◽  
Pedro Barba ◽  
Santiago Mena-López ◽  
Nathaly Espinel ◽  
Verónica Crespo ◽  
...  
Keyword(s):  
Escherichia Coli ◽  
Resistance Index ◽  
River Pollution ◽  
Multidrug Resistant ◽  
Urban River ◽  
Health Concern ◽  
Natural Environments ◽  
E Coli ◽  
Folate Pathway ◽  
Class 1

Abstract Urban river pollution by multidrug-resistant (MDR) bacteria constitutes an important public health concern. Epidemiologically important strains of MDR Escherichia coli transmissible at the human–animal–environment interfaces are especially worrying. Quantifying and characterizing MDR E. coli at a molecular level is thus imperative for understanding its epidemiology in natural environments and its role in the spread of resistance in precise geographical areas. Cefotaxime-resistant E. coli was characterized along the watercourse of the major urban river in Quito. Our results showed high quantities of cefotaxime-resistant E. coli (2.7 × 103–5.4 × 105 CFU/100 mL). The antimicrobial resistance index (ARI) revealed the exposure of the river to antibiotic contamination, and the multiple antibiotic resistance index indicated a high risk of contamination. The blaCTX-M-15 gene was the most prevalent in our samples. Isolates also had class 1 integrons carrying aminoglycoside-modifying enzymes and folate pathway inhibitors. The isolates belonged to phylogroups A, B1 and D. Clonal complex 10 was found to be the most prevalent (ST10, ST44 and ST 167), followed by ST162, ST394 and ST46. Our study provides a warning about the high potential of the major urban river in Quito for spreading the epidemiologically important MDR E. coli.

scholarly journals In-stream <i>Escherichia coli</i> modeling using high-temporal-resolution data with deep learning and process-based models

2021 ◽  
Vol 25 (12) ◽  
pp. 6185-6202
Author(s):  
Ather Abbas ◽  
Sangsoo Baek ◽  
Norbert Silvera ◽  
Bounsamay Soulileuth ◽  
Yakov Pachepsky ◽  
...  
Keyword(s):  
Escherichia Coli ◽  
Land Use ◽  
Deep Learning ◽  
Subsurface Flow ◽  
Fate And Transport ◽  
Learning Model ◽  
E Coli ◽  
Deep Learning Model ◽  
Surface And Subsurface Flow ◽  
Process Based Models

Abstract. Contamination of surface waters with microbiological pollutants is a major concern to public health. Although long-term and high-frequency Escherichia coli (E. coli) monitoring can help prevent diseases from fecal pathogenic microorganisms, such monitoring is time-consuming and expensive. Process-driven models are an alternative means for estimating concentrations of fecal pathogens. However, process-based modeling still has limitations in improving the model accuracy because of the complexity of relationships among hydrological and environmental variables. With the rise of data availability and computation power, the use of data-driven models is increasing. In this study, we simulated fate and transport of E. coli in a 0.6 km2 tropical headwater catchment located in the Lao People's Democratic Republic (Lao PDR) using a deep-learning model and a process-based model. The deep learning model was built using the long short-term memory (LSTM) methodology, whereas the process-based model was constructed using the Hydrological Simulation Program–FORTRAN (HSPF). First, we calibrated both models for surface as well as for subsurface flow. Then, we simulated the E. coli transport with 6 min time steps with both the HSPF and LSTM models. The LSTM provided accurate results for surface and subsurface flow with 0.51 and 0.64 of the Nash–Sutcliffe efficiency (NSE) values, respectively. In contrast, the NSE values yielded by the HSPF were −0.7 and 0.59 for surface and subsurface flow. The simulated E. coli concentrations from LSTM provided the NSE of 0.35, whereas the HSPF gave an unacceptable performance with an NSE value of −3.01 due to the limitations of HSPF in capturing the dynamics of E. coli with land-use change. The simulated E. coli concentration showed the rise and drop patterns corresponding to annual changes in land use. This study showcases the application of deep-learning-based models as an efficient alternative to process-based models for E. coli fate and transport simulation at the catchment scale.

scholarly journals Adjacent Terrestrial Landscapes Impact the Biogeographical Pattern of Soil Escherichia coli Strains in Produce Fields by Modifying the Importance of Environmental Selection and Dispersal

2021 ◽  
Vol 87 (6) ◽  
Author(s):  
Jingqiu Liao ◽  
Peter Bergholz ◽  
Martin Wiedmann
Keyword(s):  
Public Health ◽  
Escherichia Coli ◽  
Land Use ◽  
Enteric Bacteria ◽  
Content Type ◽  
E Coli ◽  
Biogeographic Pattern ◽  
Environmental Selection ◽  
Forest Sites ◽  
Land Use Types

ABSTRACT High-quality habitats for wildlife (e.g., forest) provide essential ecosystem services while increasing species diversity and habitat connectivity. Unfortunately, the presence of such habitats adjacent to produce fields may increase risk for contamination of fruits and vegetables by enteric bacteria, including Escherichia coli. E. coli survives in extrahost environments (e.g., soil) and could be dispersed across landscapes by wildlife. Understanding how terrestrial landscapes impact the distribution of soil E. coli strains is of importance in assessing the contamination risk of agricultural products. Here, using multilocus sequence typing, we characterized 938 E. coli soil isolates collected from two watersheds with different landscape patterns in New York State, USA, and compared the distribution of E. coli and the influence that environmental selection and dispersal have on the distribution between these two watersheds. Results showed that for the watershed with widespread produce fields, sparse forests, and limited interaction between the two land use types, E. coli composition was significantly different between produce field sites and forest sites; this distribution appears to be shaped by relatively strong environmental selection, likely from soil phosphorus, and slight dispersal limitation. For the watershed with more forested areas and stronger interaction between produce field sites and forest sites, E. coli composition between these two land use types was relatively homogeneous; this distribution appeared to be a consequence of wildlife-driven dispersal, inferred by competing models. Collectively, our results suggest that terrestrial landscape attributes could impact the biogeographic pattern of enteric bacteria by adjusting the importance of environmental selection and dispersal. IMPORTANCE Understanding the ecology of enteric bacteria in extrahost environments is important for the development and implementation of strategies to minimize preharvest contamination of produce with enteric pathogens. Our findings suggest that watershed landscape is an important factor influencing the importance of ecological drivers and dispersal patterns of E. coli. Agricultural areas in such watersheds may have a higher risk of produce contamination due to fewer environmental constraints and higher potential of dispersal of enteric bacteria between locations. Thus, there is a perceived trade-off between priorities of environmental conservation and public health in on-farm food safety, with limited ecological data supporting or refuting the role of wildlife in dispersing pathogens under normal operating conditions. By combining field sampling and spatial modeling, we explored ecological principles underlying the biogeographic pattern of enteric bacteria at the regional level, which can benefit agricultural, environmental, and public health scientists who aim to reduce the risk of food contamination by enteric bacteria while minimizing negative impacts on wildlife habitats.

scholarly journals Effects of hydrological regime and land use on in-stream Escherichia coli concentration in the Mekong basin, Lao PDR

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Paty Nakhle ◽  
Olivier Ribolzi ◽  
Laurie Boithias ◽  
Sayaphet Rattanavong ◽  
Yves Auda ◽  
...  
Keyword(s):  
Escherichia Coli ◽  
Land Use ◽  
Surface Water ◽  
Stream Water ◽  
Fecal Contamination ◽  
Lao Pdr ◽  
Fecal Matter ◽  
E Coli ◽  
Sampling Campaign ◽  
Tropical Conditions

AbstractIn the basin of Mekong, over 70 million people rely on unimproved surface water for their domestic requirements. Surface water is often contaminated with fecal matter and yet little information exists on the underlying mechanisms of fecal contamination in tropical conditions at large watershed scales. Our objectives were to (1) investigate the seasonality of fecal contamination using Escherichia coli as fecal indicator bacteria (FIB), and (2) establish links between the fecal contamination in stream water and its controlling factors (hydrology and land use). We present the results of (1) a sampling campaign at the outlet of 19 catchments across Lao PDR, in both the dry and the rainy seasons of 2016, and (2) a 10-day interval monitoring conducted in 2017 and 2018 at three point locations of three rivers (Nam Ou, Nam Suang, and Mekong) in northern Lao PDR. Our results show the presence of fecal contamination at most of the sampled sites, with a seasonality characterized by higher and extreme E. coli concentrations occurring during the rainy season. The highest E. coli concentrations, strongly correlated with total suspended sediment concentrations, were measured in catchments dominated by unstocked forest areas, especially in mountainous northern Lao PDR and in Vientiane province.

Effects of seasonal hydrology and land use on in-stream Escherichia coli concentration in the lower Mekong basin, Laos

2020 ◽  
Author(s):  
Paty Nakhle ◽  
Olivier Ribolzi ◽  
Laurie Boithias ◽  
Sayaphet Rattanavong ◽  
Yves Auda ◽  
...  
Keyword(s):  
Escherichia Coli ◽  
Water Quality ◽  
Land Use ◽  
Suspended Sediment ◽  
Fecal Contamination ◽  
Field Monitoring ◽  
Partial Least Square ◽  
Water Levels ◽  
Mekong River ◽  
E Coli

&lt;p&gt;Despite being a basic human right, limited access to clean water is still a major concern in developing countries lacking adequate sanitary infrastructure. A significant proportion of the global population directly depends on surface water resources which are often contaminated with fecal matter. The presence of fecal contamination in waterbodies is often detected using fecal indicator bacteria like &lt;em&gt;Escherichia coli&lt;/em&gt;. According to 2016 UNEP report, about one third to one half of Asian rivers are estimated to be severely polluted, with monthly in-stream concentrations of fecal coliform bacteria exceeding 1000 cfu.100 mL&lt;sup&gt;-1&lt;/sup&gt;. Although various studies on small tropical catchments have improved our understanding of &lt;em&gt;E. coli&lt;/em&gt; behavior in a tropical context, little information exists on the underlying mechanisms at large watershed scales during dry and wet seasons. Our study focuses on Mekong River and its main tributaries in Laos, an area that has witnessed rapid changes in land use and deterioration of water quality over the last three decades. We aim (1) to examine the seasonality of &lt;em&gt;E. coli&lt;/em&gt; concentrations in stream waters, and (2) to identify the main factors controlling&lt;em&gt; E. coli&lt;/em&gt; in-stream concentration, such as land use, hydrometeorology, and suspended sediment concentrations, through field monitoring of a range of catchments across Laos. To this end, we used two different sets of field data monitoring at multiple temporal and spatial scales. First, a total of 18 catchment outlets located between 15&amp;#176;N and 20&amp;#176;N, were sampled twice in 2016, during both dry and rainy seasons, covering a broad range of catchment sizes (240 - 25946 km&amp;#178;), as well as geographical and topographical features. Second, three northern rivers, Nam Ou, Nam Suang, and Mekong River, have been sampled every 10 days since July 2017. Our results shed the light on contamination over the year in all three catchments (100-100000 MPN.100 mL&lt;sup&gt;-1&lt;/sup&gt;), with higher &lt;em&gt;E. coli&lt;/em&gt; concentrations during the rainy season, associated with higher water levels, and higher concentrations of total suspended sediment (TSS) in streams. Partial Least Square (PLS) regression showed a strong positive correlation between &lt;em&gt;E. coli&lt;/em&gt; concentrations and the percentage of unstocked forests area. Unstocked forests are exposed to erosion processes resulting in high concentrations of suspended sediment and particle-attached &lt;em&gt;E. coli&lt;/em&gt; in-stream concentrations. In contrast, catchments with larger protected and naturally regenerated forest and grassland areas were associated with lower &lt;em&gt;E. coli&lt;/em&gt; and TSS concentrations. These analyses highlight the importance of adequate land management in tropical context to reduce soil loss and water quality degradation. Furthermore, our results reveal the importance of improving our understanding of fate and transport of fecal contamination through field monitoring at various spatial and temporal scales, in order to assess the risk to public health, and the impact on ecosystem services, such as contaminant retention.&lt;/p&gt;

scholarly journals Spatial and Temporal Characterization of Escherichia coli, Suspended Particulate Matter and Land Use Practice Relationships in a Mixed-Land Use Contemporary Watershed

Water ◽  
2020 ◽  
Vol 12 (5) ◽  
pp. 1228
Author(s):  
Fritz Petersen ◽  
Jason A. Hubbart
Keyword(s):  
Land Use ◽  
Particulate Matter ◽  
Suspended Particulate Matter ◽  
Agricultural Land ◽  
Agricultural Land Use ◽  
Land Use Impacts ◽  
E Coli ◽  
Suspended Particulate ◽  
Mixed Land Use ◽  
Land Use Practices

Understanding land use practice induced increases in Escherichia (E.) coli and suspended particulate matter (SPM) concentrations is necessary to improve water quality. Weekly stream water samples were collected from 22 stream gauging sites with varying land use practices in a representative contemporary mixed-land use watershed of the eastern USA. Over the period of one annual year, Escherichia (E.) coli colony forming units (CFU per 100 mL) were compared to suspended particulate matter (SPM) concentrations (mg/L) and land use practices. Agricultural land use sub-catchments comprised elevated E. coli concentrations (avg. 560 CFU per 100 mL) compared to proximate mixed development (avg. 330 CFU per 100 mL) and forested (avg. 206 CFU per 100 mL) sub-catchments. Additionally, agricultural land use showed statistically significant relationships (p < 0.01) between annual E. coli and SPM concentration data. Quarterly PCA biplots displayed temporal variability in land use impacts on E. coli and SPM concentrations, with agricultural land use being closely correlated with both pollutants during Quarters 2 and 3 but not Quarters 1 and 4. The data collected during this investigation advance the understanding of land use impacts on fecal contamination in receiving waters, thereby informing land use managers on the best management practices to reduce exposure risks.

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