Publications des scientifiques de l'IRD

Boithias Laurie, Ribolzi Olivier, Lacombe G., Thammahacksa C., Silvera Norbert, Latsachack K., Soulileuth B., Viguier Marion, Auda Y., Robert E., Evrard O., Huon S., Pommier T., Zouiten C., Sengtaheuanghoung O., Rochelle-Newall Emma. (2021). Quantifying the effect of overland flow on Escherichia coli pulses during floods : use of a tracer-based approach in an erosion-prone tropical catchment. Journal of Hydrology, 594, 125935 [12 p.]. ISSN 0022-1694.

Titre du document
Quantifying the effect of overland flow on Escherichia coli pulses during floods : use of a tracer-based approach in an erosion-prone tropical catchment
Année de publication
2021
Type de document
Article référencé dans le Web of Science WOS:000641589600043
Auteurs
Boithias Laurie, Ribolzi Olivier, Lacombe G., Thammahacksa C., Silvera Norbert, Latsachack K., Soulileuth B., Viguier Marion, Auda Y., Robert E., Evrard O., Huon S., Pommier T., Zouiten C., Sengtaheuanghoung O., Rochelle-Newall Emma
Source
Journal of Hydrology, 2021, 594, 125935 [12 p.] ISSN 0022-1694
Bacterial pathogens in surface waters threaten human health. The health risk is especially high in developing countries where sanitation systems are often lacking or deficient. Considering twelve flash-flood events sampled from 2011 to 2015 at the outlet of a 60-ha tropical montane headwater catchment in Northern Lao PDR, and using Escherichia coli as a fecal indicator bacteria, our objective was to quantify the contributions of both surface runoff and sub-surface flow to the in-stream concentration of E. coli during flood events, by (1) investigating E. coli dynamics during flood events and among flood events and (2) designing and comparing simple statistical and mixing models to predict E. coli concentration in stream flow during flood events. We found that in-stream E. coli concentration is high regardless of the contributions of both surface runoff and sub-surface flow to the flood event. However, we measured the highest concentration of E. coli during the flood events that are predominantly driven by surface runoff. This indicates that surface runoff, and causatively soil surface erosion, are the primary drivers of in-stream E. coli contamination. This was further confirmed by the step-wise regression applied to instantaneous E. coli concentration measured in individual water samples collected during the flood events, and by the three models applied to each flood event (linear model, partial least square model, and mixing model). The three models showed that the percentage of surface runoff in stream flow was the best predictor of the flood event mean E. coli concentration. The mixing model yielded a Nash-Sutcliffe efficiency of 0.65 and showed that on average, 89% of the in-stream concentration of E. coli resulted from surface runoff, while the overall contribution of surface runoff to the stream flow was 41%. We also showed that stream flow turbidity and E. coli concentration were positively correlated, but that turbidity was not a strong predictor of E. coli concentration during flood events. These findings will help building adequate catchment-scale models to predict E. coli fate and transport, and mapping the related risk of fecal contamination in a global changing context.
Plan de classement
Pollution [038] ; Santé : généralités [050] ; Hydrologie [062] ; Biologie du sol [074]
Description Géographique
LAOS
Localisation
Fonds IRD [F B010081447]
Identifiant IRD
fdi:010081447
Contact