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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Genetic Microbial Source Tracking Support QMRA Modeling for a Riverine Wetland Drinking Water Resource
|
|---|---|
| Published in |
Frontiers in Microbiology, July 2021
|
| DOI | 10.3389/fmicb.2021.668778 |
| Pubmed ID | |
| Authors |
Julia Derx, Katalin Demeter, Rita Linke, Sílvia Cervero-Aragó, Gerhard Lindner, Gabrielle Stalder, Jack Schijven, Regina Sommer, Julia Walochnik, Alexander K. T. Kirschner, Jürgen Komma, Alfred P. Blaschke, Andreas H. Farnleitner |
| Abstract |
Riverine wetlands are important natural habitats and contain valuable drinking water resources. The transport of human- and animal-associated fecal pathogens into the surface water bodies poses potential risks to water safety. The aim of this study was to develop a new integrative modeling approach supported by microbial source tracking (MST) markers for quantifying the transport pathways of two important reference pathogens, Cryptosporidium and Giardia, from external (allochthonous) and internal (autochthonous) fecal sources in riverine wetlands considering safe drinking water production. The probabilistic-deterministic model QMRAcatch (v 1.1 python backwater) was modified and extended to account for short-time variations in flow and microbial transport at hourly time steps. As input to the model, we determined the discharge rates, volumes and inundated areas of the backwater channel based on 2-D hydrodynamic flow simulations. To test if we considered all relevant fecal pollution sources and transport pathways, we validated QMRAcatch using measured concentrations of human, ruminant, pig and bird associated MST markers as well as E. coli in a Danube wetland area from 2010 to 2015. For the model validation, we obtained MST marker decay rates in water from the literature, adjusted them within confidence limits, and simulated the MST marker concentrations in the backwater channel, resulting in mean absolute errors of < 0.7 log10 particles/L (Kruskal-Wallis p > 0.05). In the scenarios, we investigated (i) the impact of river discharges into the backwater channel (allochthonous sources), (ii) the resuspension of pathogens from animal fecal deposits in inundated areas, and (iii) the pathogen release from animal fecal deposits after rainfall (autochthonous sources). Autochthonous and allochthonous human and animal sources resulted in mean loads and concentrations of Cryptosporidium and Giardia (oo)cysts in the backwater channel of 3-13 × 109 particles/hour and 0.4-1.2 particles/L during floods and rainfall events, and in required pathogen treatment reductions to achieve safe drinking water of 5.0-6.2 log10. The integrative modeling approach supports the sustainable and proactive drinking water safety management of alluvial backwater areas. |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Switzerland | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 21 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 21 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 4 | 19% |
| Other | 3 | 14% |
| Professor > Associate Professor | 2 | 10% |
| Student > Master | 2 | 10% |
| Student > Ph. D. Student | 1 | 5% |
| Other | 3 | 14% |
| Unknown | 6 | 29% |
| Readers by discipline | Count | As % |
|---|---|---|
| Environmental Science | 5 | 24% |
| Engineering | 4 | 19% |
| Medicine and Dentistry | 2 | 10% |
| Immunology and Microbiology | 1 | 5% |
| Philosophy | 1 | 5% |
| Other | 2 | 10% |
| Unknown | 6 | 29% |
Attention Score in Context
This research output has an Altmetric Attention Score of 47. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 09 September 2021.
All research outputs
#782,517
of 23,310,485 outputs
Outputs from Frontiers in Microbiology
#392
of 25,616 outputs
Outputs of similar age
#20,315
of 436,461 outputs
Outputs of similar age from Frontiers in Microbiology
#11
of 1,154 outputs
Altmetric has tracked 23,310,485 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 25,616 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.4. This one has done particularly well, scoring higher than 98% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 436,461 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 95% of its contemporaries.
We're also able to compare this research output to 1,154 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 99% of its contemporaries.