HAL Id: hal-02600214
https://hal.inrae.fr/hal-02600214
Submitted on 16 May 2020
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Compared analysis of different sampling strategies for the monitoring of pesticide contamination in streams
Lucie Liger, C. Margoum, C. Guillemain, Nadia Carluer
To cite this version:
Lucie Liger, C. Margoum, C. Guillemain, Nadia Carluer. Compared analysis of different sampling strategies for the monitoring of pesticide contamination in streams. EGU, Apr 2014, Vienna, Austria.
pp.1, 2014. �hal-02600214�
www.irstea.fr
Compared analysis of different sampling strategies for the monitoring of pesticide contamination in streams
EGU – April 28th to May 2nd – Vienna, Austria
Contacts :
Lucie Liger; lucie.liger@irstea.fr
Nadia Carluer; nadia.carluer@irstea.fr
Liger Lucie, Margoum Christelle, Guillemain Céline, Carluer Nadia
Reference :
Rabiet, M; Margoum, C; Gouy, V; Carluer, N; Coquery, M. (2010). "Assessing pesticide concentrations and concentration dynamics and fluxes in the stream of a small vineyard watershedcatchment - Effect of sampling strategy frequency." Environmental pollution 158(3): 737-747.
IRSTEA : National Research Institute of Science and Technology for Environment and Agriculture, Irstea centre de Lyon-Villeurbanne, France
European WFD requests to achieve good qualitative and quantitative status of all water bodies in 2015.
States have to implement stream’s monitoring of organic micropollutants.
to understand the reasons of contamination.
to implement sound mitigation solutions in the watershed.
Which sampling strategy should be implemented to best fit the experimental goals?
Introduction and objectives
Different sampling strategies
Grab sampling
Flow-dependent
automatic sampling Time-related
automatic sampling
t
time
flow
t
t
Punctual concentration
Mean concentration
Flux
The Morcille river : a small watershed with high risk of pesticide contamination :
• steep slopes
• permeable sandy soils
• 70% of vineyard (Beaujolais Region, France)
Research on non-point source pollution by pesticide since 1985.
• River quality and flow monitored between 2006 and 2011.
• Pesticides analyzed in water by SPE-LC-MS/MS including Diuron (DIU) and Dimethomorph (DMM).
Fractionated samples during flood : 2 automatic samplers programmed to sample every X m3 running through the river.
Weekly grab samples : manual samples.
Weekly averaged samples : automatic samplers
programmed with a time or flow step to elaborate a weekly composite sample.
Field description and data acquisition
Step sampling influence on mean concentration
dataset 03:30 06:00 concentration
(µg/L) 7,90 15,45 4,82
% differences
with dataset 196% 61%
samples nb 14 9 6
dataset 300m3 500 m3
flux (µg/L) 14,37 14,93 16,51
% differences
with dataset 104% 115%
samples nb 14 14 8
flow- dependant concentration
(flux) Time-related concentration
July flood : mean concentration for the event
From the same dataset, the mean concentration is different if calculated to get flux or exposure.
The flood and pesticides dynamics influence the mean concentration and flux differently according to the sampling strategy elaborated.
Flow-dependent sampling leads to a mean concentration twice as high as time-related sampling.
Time step change leads to important differences of mean concentration.
Virtual
downsampling at 2 volume
steps
(calculated from flow)
Real flood data at a small step
(flow + Diuron dynamics)
Virtual
downsampling at 2 time steps (concentrations dynamic of
fractionated samples)
Four cases of weekly-averaged sample show sampling strategy influence on mean concentrations, for different flood events (flow max).
grab, time-related-averaged, flow-dependent-averaged
The order between the 3 strategies concentrations is changed from one week to another, depending on flow, pesticide monitored, timestamp.
Week 3 : the mean grab-sample (2 samples) is higher than automatic samples because it has been taken during the flow peak.
Flow-dependent sampling leads to higher mean concentration
representing the flux (the mass) of pesticide exported by the stream.
1
1 2 3 4 2 3 4
Averaged concentration comparison
For event 2, the timestamp of each sample is represented on the flow- curve.
Timestamp comparison
On this watershed, with flood and pesticides fast dynamics, the grab sampling can not be the strategy to adopt to asses the mean concentration or flux of pesticides.
The choice of sampling strategy should be done according to the monitoring aim : to assess fluxes (quantity), the sampling at a rate proportional to flow should be used; to assess exposure (mean concentration), a time dependent sampling will be better.
In any case, analysis results should be used linked with the stream hydrology dynamic during the sampling period.
Conclusions
Here, the grab sampling strategy does not collect the flood at all.
Time sampling does not take the flow peak.
Flow sampling collects only the flood
and is not
representative of the low level.
Grab
Time - related Flow - dependant
Flow
