Marine Litter in Indonesia
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Marine Litter in Indonesia
Tr a c k i n g m a c r o - p l a s t i c f r o m r i v e r m o u t h s
with Argos buoys and modelling
Olivia
FAUNY
Fauny, O., Lucas, M., Dufau, C., and Voisin, J.-B.: Marine Litter in Indonesia – Tracking macro-
plastic from river mouths with Argos buoys and modelling, EGU General Assembly 2021, online, Sponsored by
19–30 Apr 2021, EGU21-15416, https://doi.org/10.5194/egusphere-egu21-15416, 2021.
Introduction
Marine plastic, a global issue coming from rivers
Ocean Clean Up
Indonesia committed to reduce its plastic emission at sea
by 70% before 2025
Majority of plastic pollution is discharged by rivers
Overtime, megaplastic become nanoplastic. The longer it stays in the
environment, the smaller it becomes.
88–95% of plastic in the ocean comes from just 10 › Need to locate hotspot of macrowaste accumulation
rivers, mostly in S-E Asia. › Collect macrowaste on land is much cheaper and safer than at sea
Jakarta, Indonesia
Goal and Methodology : A double approach
Determine accumulation areas of
macro-waste at sea and on shore
In-situ tracking Oceanography simulations
Release at river mouths and tracking Drift modelling using wind and current
of debris-like Argos drifters forcings
Financed by For the count of
Three rivers studied in the project
Three of the main Indonesian rivers have been
chosen, based on :
› The quantity of waste discharged
› The absence of waste-collecting nets
› Their path within or nearby major cities and
populated provinces
Musi
750km long through the South of Sumatra
Flows through Palembang city (1.6M ppl., 2019)
660k kg of plastic emission/year (Clean Up Foundation)
Cisadane
138 km long along the North-West of Java
Many affluents flow through Jakarta (10.6M ppl., 2020)
1.6M kg of plastic emission/year (Clean Up Foundation)
Bengawan Solo
549km long, the longest river of Java
Flows from the South to the North-East of the island
300k kg of plastic emission/year (Clean Up Foundation)
Musi (Sumatra) Cisadane (Java) B. Solo (Java)
In-Situ approach Release of Argos drifting buoys
First releases : 23 Argos drifters at sea
2 drifters have been released as a trial on
7 Mar. 2020 by KKP, KHLK, Menkomar
and CLS at Cisadane river mouth
+ 5 drifters in Cisadane, 16 Jul. 2020
+ 5 drifters in B. Solo, 20 Jul. 2020
+ 5 drifters in Musi, 23 Jul. 2020
Features of a MAR-GE/T drifter
› Floatable, designed to drift
+ 6 drifters in Cisadane, 20 Oct. 2020 › Autonomy up to 450 days
› Transmission rate : 1 position/hour
› Global satellite coverage (Argos)
River mouth (release point)
Drifter position on the 11 Nov. 2020
Drifters trajectory, grouped by location and
Positions of drifters (extract from the 11 Nov. 2020) date of release:
Cisadane, Feb. 2020
Cisadane, Jul. 2020
B. Solo, Jul. 2020
Musi, Jul. 2020
11 devices grounded within 10 days Cisadane, Oct. 2020
7 devices grounded within 1 month
5 devices still drifting in Nov. 2020
Modelling approach Drift study
Use of a Lagrangian modelling tool : MOBIDIRFT
Drift parameters
Coefficient of METOC data
Probabilistic mode:
› Number of particles
› Disturbance on forcings
› Initial position radius
OBJECT RESULTING PARTICLES
▫ Shape (Point, polygone, ▪ Position step by step
line) DRIFT COMPUTATION ▪ Speed and age
▫ Start date ▪ Trajectory
▫ Initial position ▪ Ensemble statistics
METOC Data
Surface current
Tide current
Wind field
Bathymetry
FORCING MODELS Current Wind Tide CMEMS NCEP Fes 2014 Extent : Global Extent : Global Extent : Global Frequency : 1 hour Frequency : 3 hours Frequency : 1 hour Resolution : 1/12° Resolution : 1/8° Resolution : 1/16° Provider : Mercator Océan Provider : NOAA Provider : CNES/LEGOS/CLS
Drift computation
Marine debris displacement speed =
0-3% Wind coefficient X Wind speed
+ 100% Surface current coefficient X Surface current speed
+ 100% Tidal current coefficient X Tidal current speed
Deterministic approach Probabilistic approach
Shift in the initial position
1 constant initial position Each drifting particle affected by
→ Winds + disturbance
1 drifting particle affected by → Currents + disturbance
→ Winds
→ CurrentsOn the importance of the wind coefficient
The wind impact is a crucial component to simulate Three wind coefficients have been taken into account here to
realistic pathways of debris at the sea surface, directly represent a diversity of debris:
linked to the buoyancy of debris.
› 0% for immerged waste included on the surface mlayer
Testing wind coefficients from 0% to 20% in a Lagrangian (plastic bags, straws,…)
analysis using Lyapunov Exponents in the Roatan area,
Leonard and Lucas (2020) evidenced that a 6% value was › 1.5% for semi-immerged debris - based on the Mar-GE/T
the best proxy to reproduce the observed accumulation calibration (plastic bottles,…)
area. › 3% for mostly emerged and light debris with a higher
E. Leonard and M. Lucas, 2020 : Identifying plastic accumulation in coastal seas: the sensitivity to wind (styrofoam,…)
Roatan Island case study, Marine Pollution Bulletin, 154Calibration of simulations using a drifter
To set the parameters of the drift simulations, an
extract of a Mar-GE/T trajectory was used.
Different combinations of parameters were
tested to find the best match with the in-situ
drift. Among these parameters :
› models of wind and surface currents
› frequency of forcing inputs
› coefficients of wind and current
› disturbance on forcing for the probabilistic
particles
› …
A comparative analysis of speed and direction
were then conducted to find the closest result.Results Focus on Cisadane river
› Map in relative amount (%)
› Moderate dispersion of particles
around Indonesia
› Hotspot of grounded particles
around Jakarta region45%
8 km long
› Map in relative amount (%)
› Concentration of most of the
particles along a short coastline
› 99.6% of particles are grounded 3
months after being disseminatedGlobal dispersion for the three rivers : Cisadane, Musi and B. Solo
› Map of relative amount (%)
› Dispersion of particles around Indonesia,
especially Java Sea
› 3 main hotspots of concentration located
on land and close to each river mouth
› 97.1% of the total amount of particles are
grounded 3 months after being
disseminated
› The mean duration of a particle drift is
between 1.1 and 14.1 days, depending
on the river it came fromConclusion
› A local study of an environmental global concern
› impact of 3 Indonesian rivers onto adjacent seas.
› Estimation of the hotspots of macro-plastic accumulation with :
› 23 ARGOS satellite-tracked drifters released in river mouths to monitor in-
situ the pathways of floating macro-plastics
› Lagrangian modeling, including several wind effects on macro-plastic and
a probabilistic approach
→ The knowledge of the river flows and waste discharged quantity is important
to deploy the drifters at the right place/right time. The release of a pack of
(at least) 5 drifters is needed to evaluate their dispersion.
→ Coastal dynamics are crucial to simulate macro-plastic behavior from the
river mouth to open ocean. High-resolution realistic model for winds and
surface currents are needed.
To go further…
› Take into account the remobilization of grounded particles
› New drifters and tags for macro-waste are being developped, more sustainable and plastic-freeYou can also read
