EU EDF – SOPAC Project Report 133 Reducing Vulnerability ...

EU EDF – SOPAC Project Report 133 Reducing Vulnerability of Pacific ACP States

TUVALU TECHNICAL REPORT Hydrodynamic Model of Funafuti:

Water Circulation and Applications

October 2008

Funafuti, approach from north

Prepared by:

Herve Damlamian

SOPAC Secretariat

September 2005

PACIFIC ISLANDS APPLIED GEOSCIENCE COMMISSION

c/o SOPAC Secretariat

Private Mail Bag

GPO, Suva

FIJI ISLANDS

http://www.sopac.org

Phone: +679 338 1377

Fax: +679 337 0040

www.sopac.org

[email protected]

Important Notice

This report has been produced with the financial assistance of the European Community; however, the views expressed herein must never be taken to reflect the official opinion of the

European Community.

Tuvalu: Funafuti hydrodynamic model EU EDF-SOPAC Reducing Vulnerability of Pacific ACP States – iii

EU-SOPAC Project Report 133 – Damlamian 2008

Contents

EXECUTIVE SUMMARY ........................................................................................................ 1

1. INTRODUCTION ....................................................................................................... 2

2. PHYSICAL CHARACTERISTIC ............................................................................... 3

2.1 Background ................................................................................................................ 3 2.2 Tides .......................................................................................................................... 4 2.3 Wind ........................................................................................................................... 4

3. MODEL DESCRIPTION ............................................................................................ 5

3.1 Bathymetry model ...................................................................................................... 5 3.2 Bottom roughness ...................................................................................................... 6

4. CALIBRATION ......................................................................................................... 7

4.1 Surface elevation ....................................................................................................... 7 4.2 Current speed ............................................................................................................ 8

5. MODEL RESULTS ................................................................................................... 9

5.1 Water circulation in Funafuti lagoon ........................................................................... 9

6. SEDIMENT PLUME DISPERSION ......................................................................... 11

6.1 Background .............................................................................................................. 11 6.2 Description of the sediment dispersion model ......................................................... 12

7. RESULTS AND DISCUSSION ............................................................................... 15

7.1 Non-cohesive sediment (sand) ................................................................................ 16 7.2 Cohesive sediment (mud) ........................................................................................ 16

8. CONCLUSION ........................................................................................................ 17

9. REFERENCES........................................................................................................ 17

APPENDICES ....................................................................................................................... 18

Appendix 1: Current vectors at neap tide ........................................................................... 18 Appendix 2: Current vectors at spring tide ......................................................................... 19 Appendix 3: Sediment dispersion outputs .......................................................................... 20

iv – Tuvalu: Funafuti hydrodynamic model EU EDF-SOPAC Reducing Vulnerability of Pacific ACP States


List of Figures

Figure 1: Location of Tuvalu in the South Pacific. ........................................................... 2

Figure 2: Map of Funafuti. ............................................................................................... 3

Figure 3: Tide gauge data at Fongafale. ......................................................................... 4

Figure 4: November to March wind rose. ........................................................................ 4

Figure 5: April to October wind rose. .............................................................................. 4

Figure 6: Map showing the different data used to create the bathymetry. ...................... 5

Figure 7: Bathymetry of Funafuti. .................................................................................... 6

Figure 8: Map of bottom roughness as a function of depth. ............................................ 6

Figure 9: Current meter deployment and tide gauge location. ........................................ 7

Figure 10: Calibration of the tide model with actual ADP records. .................................... 7

Figure 11: Calibration with ADP1. ..................................................................................... 8

Figure 12: Calibration with ADP2. ..................................................................................... 8

Figure 13: Water circulation at neap tide. ......................................................................... 9

Figure 14: Water circulation at spring tide during flood. .................................................. 10

Figure 15: Water circulation at spring tide during ebb. ................................................... 10

Figure 16: Dredging method using suction and discharge pumps. ................................. 11

Figure 17: Aggregate resource area of Funafutu. ........................................................... 12

Figure 18: Sedimentation rate of finest particles in the resource area. ........................... 13

Figure 19: Sedimentation of non-cohesive particles after 10 days dredging. ................. 15

Figure 20: Impacted zone from a dredging operation near Fongafale. ........................... 16

Acknowledgements

Thanks to:

Jens Krüger, Physical Oceanographer and Dr Arthur Webb, Aggregates Management adviser of the SOPAC/EU project, for their assistance throughout.

Jean Pages, retired from the IRD, for providing much advice

Juan Savioli, from DHI, who showed me how to use Mike21 during a one-week workshop.

Tuvalu: Funafuti hydrodynamic model EU EDF-SOPAC Reducing Vulnerability of Pacific ACP States – 1


EXECUTIVE SUMMARY

Damlamian, H. 2008: Hydrodynamic Model of Funafuti, Tuvalu: Water Circulation and Applications. EU EDF 8 – SOPAC Project Report 133. Pacific Islands Applied Geoscience Commission: Suva, Fiji, iv + 21 p.

With the development of powerful computers, numerical models are increasingly being used to simulate processes of nature. Mike21 is one example of professional modeling software for two-dimensional free surface flows; it comes in modular form with four main application areas: coastal hydraulics and oceanography, waves, sediment processes and environmental hydraulics.

Like most Pacific atolls, Funafuti in Tuvalu suffers from natural hazards (storm surge, tsunami), poor water quality, etc. Especially the limited availability of land, a common issue for an atoll, means vulnerability to coastal erosion.

As part of the SOPAC/EU project, reducing the vulnerability of Pacific states, the development of a two-dimensional hydrodynamic model of Funafuti was undertaken. This task, the first of its kind developed by the SOPAC/EU team, was also part of a coastal engineering training exercise.

Two numerical models were developed. The first, a hydrodynamic model, simulates the water circulation in the lagoon depending on tide and wind-induced current. This model gives an understanding of the hydrodynamic mechanism taking place in the lagoon. Three main water circulation patterns are extracted, emphasizing the role of wind and tide-induced current as well as how they challenge each other.

Using this model as a management tool, one can address any future coastal management project in Funafuti. Using the hydrodynamic model as a baseline water quality scenario can assist in evaluating dredging operations, erosion, etc.

The second model, of a sediment plume dispersion, was developed to illustrate the possibilities of applying this new management tool. Since beach mining significantly increase the erosion along the coast of Funafuti, it appears as a real threat to sustain the atoll environment. In collaboration with SOPAC, the Funafuti government have promoted an alternative way to collect aggregates, by dredging. Such an operation causes particles of sediment to be released in the water column, creating a sediment plume. At excessive rates, this plume could strongly affect components of the ecosystem such as lagoon fish and coral.

Prior to this work, a possible aggregate resource area had been surveyed by SOPAC and sediment data collected in the resource area. Using the hydrodynamic model, a sediment dispersion plume model demonstrates the dispersion of the finest sediment particles.

Both models were built with a grid resolution of 100 m, which reflects the computation limitations faced at the time of development.

2 – Tuvalu: Funafuti hydrodynamic model EU EDF-SOPAC Reducing Vulnerability of Pacific ACP States


1. INTRODUCTION

Harbours and lagoons are all subject to some, or all, of the following disturbances: pollution, wave action, storm surge, seiching, tsunami, erosion and sedimentation, and sea-level rise. Studies linked to coastal management are often limited by the data sets available, seasonal variations and cost.

Numerical modeling provides an opportunity to view and analyse coastal problems and risks. It permits a valuable symbiosis between development and application, with minimal penalties for error.

The work carried out at the Ocean and Island program of SOPAC and presented in this report focuses on the development of a hydrodynamic model of Funafuti Atoll in Tuvalu, in the central South Pacific (Figure 1). The model simulates wind- and tide-induced current; because of computation power limitations, no wave-induced flux is considered. .

The model used is Mike 21 (DHI 2004). It gives not only an understanding of the water circulation in the lagoon, which provides basic information for further coastal or lagoon management projects; it could also be used to directly address any impacts related to such projects.

To showcase the possibilities offered by such a tool, the hydrodynamic model is used as a baseline to produce a sediment dispersion model. Its results document the possible impact from a dredging operation close to Fongafale, the most populated islet of Funafuti.

Figure 1: Location of Tuvalu in the South Pacific.



2. PHYSICAL CHARACTERISTIC

2.1 Background

Tuvalu is located between 4° and 13.2° S latitude and 172.7° and 176.8°E longitude. Its exclusive economic zone is approximately 900 000 km2.

The capital is Funafuti, the largest of the nine atolls that form the Tuvalu islands chain and is located at 179°7’E and 8°30’S. The atoll reef rim surrounds a large lagoon of about 240 km2 whose mean depth is between 30 and 35 m. The lagoon opens to the ocean through several natural reef channels along the western and southeastern reef.

Figure 2: Map of Funafuti (from Smith & Woodward 1992).



2.2 Tides

A tide gauge in Fongafale (Figure 2) permanently records surface elevation data. Data are available through the South Pacific sea level and monitoring project (www.pacificsealevel.org).

Tides in Funafuti are semi-diurnal with a significant inequality between two consecutive peaks. The tidal range varies between 1.9 m and 0.15 m, respectively, at spring and neap tide (Figure 3).

surface elevation [m]

00:002004-09-05

00:0009-10

00:0009-15

00:0009-20

00:0009-25

00:0009-30

-0.8

-0.6

-0.4

-0.2

0.0

0.2

0.4

0.6

0.8

1.0

Figure 3: Tide gauge data at Fongafale.

2.3 Wind

The 2004 annual wind data (www.pacificsealevel.org) show the wind in Funafuti to be seasonal. From November to March (Figure 4), the south-easterly and north-westerly winds compete, with a strong westerly wind reaching more than 10 m/s. From April to October, the wind is southeasterly dominant not exceeding 6 m/s.

N

Calm31.67 %

10 %

Palette

Above 106 - 104 - 62 - 4

Below 2

N

Calm33.02 %

10 %

Figure 4: November to March wind rose. Figure 5: April to October wind rose.



3. MODEL DESCRIPTION

3.1 Bathymetry model

Several sources of data were used to create the bathymetry (Figure 6):

Soundings from HMNZ Monowai, from a survey carried out in 1983;

Single-beam data echosounder sounding collected by SOPAC (Smith 1995);

Multibeam data echosounder sounding collected by SOPAC/EU (Krüger 2008).

On the western reef, a deep channel of about 47 m depth connects the lagoon with the ocean. The reef slope is highly variable with an average of about 26° and a maximum slope of 79° (Figure 7).

Figure 6: Map showing the different data used to create the bathymetry. 2005 Multibeam data (green), 1995 Singlebeam data (red), 1983 soundings (blue). Source: Krüger 2008.



Figure 7: Bathymetry of Funafuti.

3.2 Bottom roughness

A Bottom roughness map was used to calibrate the model. The bed roughness was mapped on a rectangular 100 m grid. The roughness is expressed by the Manning number and is chosen for each cell according to its depth (Figure 8).

Figure 8: Map of bottom roughness as a function of depth: for a water level from 0 to –10m: 1/M=28; from –20 to –10m: 1/M=30; from –100 to –20 m: 1/M=32; below 100m: 1/M=35.



4. CALIBRATION

Calibration was performed using tide gauge data at Fongafale and 4 Acoustic Doppler Profilers (ADP), deployed during the 2005 SOPAC/EU survey (Figure 9).

4.1 Surface elevation

Figure 10 shows the comparison between the extracted model data and the real records of surface elevation. The tide is clearly very well simulated by the model.

Figure 10: Calibration of the tide model with actual ADP records.

Figure 9: Current meter deployment and tide gauge location.



4.2 Current speed

For the current speed at ADP 1, located in the north of the lagoon, real and simulated data are a good match (Figure11).

However, at ADP2 (Figure 12) there are significant differences between the datasets. Indeed, from 21 to 25 September, fluctuations described by the real data are not represented by the model. This can be explained as follows:

At neap tide, the tidal current is weak. The current that is wave-induced can play a greater role in the circulation. As ADP2 is deployed close to a deep western channel, the wave-induced flow could have created the high peaks seen in Figure 12. As the wave-induced currents have not been included in the model, it cannot detect them.

Figure 11: Calibration with ADP1: Plot comparison between real data (red line) and model data (back line).

Figure 12: Calibration with ADP2: Plot comparison between real data (blue line) and model data (green line).



5. MODEL RESULTS

5.1 Water circulation in Funafuti lagoon

This section describes the water circulation resulting from the tide and wind-induced current. This analysis is only valid for the calm wave climate surrounding Funafuti.

5.1.1 Neap tide

During neap tide, the wind-induced current is dominant. During the simulation period, the wind came mostly from the southeast and generated an inflow across the eastern channel; this leads to the circulation illustrated in Figure 13.

Figure 13: Water circulation at neap tide.

5.1.2 Spring tide

At spring tide, the tidal current gets stronger and overcomes the wind-induced current. Two different patterns occur. During flood, the tide comes in and forces the water inside the lagoon (Figure 14). During ebb, the tide goes out and forces the water out of the lagoon (Figure 15).

As the lagoon is filling up from each direction during flood, vortexes are created in the middle of the lagoon.



Figure 14: Water circulation at spring tide during flood.

Figure 15: Water circulation at spring tide during ebb.



6. SEDIMENT PLUME DISPERSION

6.1 Background

6.1.1 Dredging method

Dredging consists of excavation of material from the sea, river or lakebed and its relocation elsewhere. This method is usually applied to improve the navigable depths in ports, harbours, and shipping channels; or to win minerals from underwater deposits. Other applications are to improve drainage, reclaim land, improve sea defence, or remove and relocate contaminated materials.

The dredge stirs up sediment and causes sediment plumes to be dispersed. Currents and sediment gravity influence the sediment-water mixture that forms the plume.

Several negative impacts of sediment plume on water quality, marine ecology, fish and shellfish can be expected:

Elevated turbidity causes reduction of photosynthesis by phytoplankton, algae and rooted vegetation. Reduction of visibility makes feeding difficult for some fish.

Increase of suspended sediment will cause reduction of dissolved oxygen levels, and will release absorbed heavy metals or toxic organics from fine-grained suspended solids. This can cause interference with the respiration and feeding of fish, impediment to mobility, or irritation to tissues, making infection or invasion by parasites more likely.

Sedimentation will cause covering of the bottom near the dredging site, smothering bottom-dwelling organisms, reducing or eliminating food supply, or reducing habitat diversity.

To investigate the impact from the sediment plume, the model simulates a system with two pumps. One extracts the aggregates from the site using a suction pump while the other pump discharges water and particles near the seabed (Figure 16).

Figure 16: Dredging method using suction and discharge pumps.



6.1.2 Resources areas

Beach mining significantly increases the erosion impact on the coast. In order to discourage this, SOPAC delimited a resource area (Figure 17), covering 2.4 km2, suitable for proposed dredging operations (Smith 1995). An estimated 24 million cubic metres of sediment could be extracted here.

The possible impact of such a project can be modeled if the distribution of sediment grain size in the resource area, as well as parameter defining the particle (settling velocity, density, etc) are known. The model can simulate the dispersion of the sediment plume from the dredging operation.

This model looks at dispersion of only the finest sediment particles released from the dredging overflow. Heavier particles are assumed to settle down close to the water column where they have been released. Two types of particle are considered: non-cohesive sediment with a size of 62.5 μm (sand), and cohesive sediment, with a grain size of 4.0 μm. The latter describes the dispersion of mud (approximated limit before flocculation).

Removal of lagoon sand by dredging can result in an increased rate of erosion of nearby beaches due to alteration of the wave energy impinging on the beach. However, it is unlikely to occur here since the dredging area in the lagoon becomes shallower towards the open sea and lies within an already low and relatively deep basin surrounded by coral shoals and reef platforms. This configuration fortuitously protects the beaches from any effects of dredging sand (Smith 1995).

6.2 Description of the sediment dispersion model

This section gives a brief overview of the main parameter chosen for the simulation.

6.2.1 Time step and simulated period

As a rule of thumb, a particle should not move more than one grid cell in each timestep, otherwise the numerical integration of the stochastic differential equation that controls the particle motion becomes unstable.

In the resource area, the maximum current speed, Umax, does not exceed 1.0 m/s and the grid spacing, x, is 100 metres. From the definition of the Peclet number the maximum timestep can now be calculated as t < x/Umax. Hence a 100-seconds time step was chosen. The model simulates a 12-day period.

Figure 17: Aggregate resource area of Funafuti.



6.2.2 Sources

To simulate the overflow discharge, a source is inserted in the dredging site releasing the overflow sediment plume emerging from the near-bottom discharge pump. The source is defined by its horizontal and vertical position, and its flux of fine sediment at its location.

The sedimentation rate of the finest particles is taken from Smith (1995) and mapped in the resource area using a linear interpolation method.

6.2.2a Source positions

For each particle type, an overflow discharge was simulated in several key locations in the resource area, with all sources located 2 m above the seabed.

6.2.2b Flux

For a realistic idea of the overflow discharge for cells within the resource area, the pump system needs to be known. Because at this stage no dredging method has been chosen, the pump used in this model is the one described by Cruickshank and Morgan (1996). Its overflow discharge can be estimated as follows:

Solids pumped = 19 m3/h

Water pumped = 170 m3/h

The overflow of fine particles is assumed to be the percentage of the fine-grained particles in the sediment multiplied by the volume of solids pumped. This gives the predicted flux for each grid point in the resource area. As the dredging is to be conducted for three hours per day, a time series file was also created for each grid point in the resource area.

Figure 18: Sedimentation rate of finest particles in the resource area.



6.2.3 Dispersion

The model uses dispersion proportional to the current. The proportional factors are:

Longitudinal Direction fLong = 1

Transversal Direction fTrans = 1

Vertical Direction fVert = 0

For the short-term conditions of interest, we can assume the plume to maintain a fairly constant thickness as it is transported by tidal and wind current and dispersed laterally by turbulent processes. We do not need to include vertical dispersion in this model, which simplifies the model and is a conservative assumption: any significant vertical dispersion will lower the predicted suspended particulate concentrations.

6.2.4 Type of particles

The dispersion of two different types of particles was investigated: non-cohesive sediment (grain size 62.5 μm) and cohesive sediment (4.0 μm). The chosen dimension allows us to ignore flocculation and develop the worst-case scenario.

The last parameter is the Critical Shields parameter for motion. A typical value is 0.045 for sand, and around 0.2 for mud. In the absence of a local value for the density of sediments, 1.667 was chosen (Cruickshank & Morgan 1996).

6.2.5 Settling velocity

Settling velocity depends on the size of the particles: of a single free particle it can be estimated using Stokes’ law, which can be represented by, for example:

Where s = sediment density (kg/m3), = viscosity (m2/s), = density of water, ws = settling velocity (m/s), g = acceleration due to gravity (m/s2) and d = grain size (m).

Accordingly, the settling velocity value is 1.57 m/s for sand and 6.8x10–3 m/s for mud. The Viscosity value was taken from Ramsing and Gundersen (2001).



7. RESULTS AND DISCUSSION

Dredging operations can affect the ecosystem of Funafuti in many ways. This model looked at the rate of suspended particles added to the water column as well as their sedimentation, providing an understanding of the possible impact of such an operation.

Two types of sediment were used to simulate the sediment plume dispersion: cohesive with a grain size of 4 μm (mud) and non-cohesive with a grain size of 62.5 μm (sand). The model simulates 3 hours per day dredging for a period of 10 days.

Coral reefs are very sensitive to increased sedimentation and turbidity. Destruction of coral reefs may lead to increased coastal erosion and to a significant reduction in fish population. When looking at an impacted zone from a dredging operation, a limit of acceptable damage has to be defined.

No coral reef is in constant growth. For instance, during major tropical storm events, all reefs undergo losses in coral cover and often erosion of their physical structure. Recovery time from such natural events can be used as a measure of acceptable damage, usually represented by a recovery time of one year.

Two acceptable limits have to be set up in the model: one limit of sedimentation rate and one limit of suspended particles. The outcome of the study strongly depends on how accurately those acceptable limits are determined. Investigation using laboratory experiments was beyond the scope of this study and crucial information such as ambient rates of suspended particles and of sedimentation was not available. Such data provide an understanding of the resistance of the marine life to dredging operation.

Some assumptions have to be made. In general, corals can clear themselves from 100 mg/cm2/day (Lasker 1980) without the help of current, or in the Indo Pacific Region even up to 230 mg/cm2/day (Pastorok and Bilyard 1985). In Funafuti lagoon, a large enclosed shallow-water environment, the natural recovery rate is also expected to be high. Therefore a sedimentation rate of 10 mg/cm2/day above the natural condition was presumed not to cause irreversible damage to the coral; this is used as the acceptable limit of sedimentation rate.

In the Great Barrier Reef, corals have become acclimatised to higher sediment loads exceeding 100 mg/L (Hopely et al. 1991). For Funafuti lagoon, a limit of 10 mg/L (or 0.01 kg/m3) above the natural condition was considered sensible and acceptable.

Figure 19: Sedimentation of non-cohesive particles after 10 days dredging.



7.1 Non-cohesive sediment (sand)

The model shows that no dispersion is expected from the non-cohesive sediment grain with a size of 62.5 μm. All those particles settle quickly after being released (Figure 19).

7.2 Cohesive sediment (mud)

No local information on the grain size of cohesive particles is available. A grain size of 4 μm is used as this is the limit before flocculation takes place.

After 10 days, the suspended particles released at four sources are found in the same area as where they have already settled (Appendix 2). Therefore it seems fair to assume that after 10 days, the sediment plume has reached its maximum dispersion.

A map of the impacted zone was developed (Figure 20) by modelling the sediment plume dispersion from all simulated sources. Dredging the proposed resource area would thus lead the sediment plume to be dispersed over an area of 8.5 km2. In the coral zone, the suspended particle concentration nowhere exceeds 1 mg/L and sedimentation rate is less than 1 mg/cm2/day. Given the acceptable limit assumed, no damage in the sensitive area should be caused by dredging in this resource area.

The results of this model should be interpreted carefully as this model application is only preliminary. An extensive data collection survey is to be undertaken before reaching any rigorous conclusion.

Figure 20: Impacted zone from a dredging operation near Fongafale. The yellow line marks the resource area, red the impacted zone, and blue the coral zone.



8. CONCLUSION

The hydrodynamic model Mike21 was applied to simulate the water circulation in Funafuti lagoon. Simulation results were analysed to extract the dominant circulation patterns.

Three main water circulation patterns are evident in Funafuti lagoon. At spring tide, the tide-induced current controls the water movement leading to two distinct water circulations; when the tide comes in (flood) and when the tide goes out (ebb). During neap tide, tide-induced current gets weaker and wind-induced current controls the water motion.

No wave-induced current was considered in this study: this leads to a temporary calibration mismatch with current data from an ADP deployed near a channel.

This model was then used as a baseline to estimate the impacted zone of a dredging operation in two different sites in a proposed dredging area. Using sediment sample data collected from an aggregates resource area, a sediment plume dispersion was developed to illustrate the possibilities offered using the Funafuti model.

The model predicts no irreversible damage to possibly sensitive areas. However, more data would be required to reach any rigorous conclusion. It is recommended that prior to any dredging operation, more data such as the ambient sedimentation rate, the ambient suspended particle rate, the particle density, and – most importantly – data to calibrate the dispersion model, are collected.

This model is the first of its kind developed under the SOPAC/EU project and surely helps building our numerical modelling capacity. Limitations such as computer power, data collection and appropriate numerical modelling tools are being looked into.

9. REFERENCES

Cruickshank, M.J. and. Morgan, C.L. 1996. Proposed dredging in basin A offshore from Nuku’alofa, Kingdom of Tonga. Environment impact assessment for the Kingdom of Tonga. Ministry of Lands, Survey & Natural Resources, Appendix to trip report 234.

DHI 2004. Mike 21 Reference Manual

Global Coral Reef Alliance_sedimentation http://globalcoral.org/SEDIMENTATION.html

Hopely et al. 1991. Responses of seagrass to nutrients in the Great Barrier Reef, Australia.

Institut de Recherche pour le Développement http://com.univ-mrs.fr/IRD

Krüger J. 2008. High-resolution bathymetric survey of Tuvalu. EU EDF8-SOPAC project report 50.

Lasker, H. R. 1980. Sediment rejection by reef corals: the roles of behavior and morphology in Montastrea cavernosa (Linnaeus). Journal experimental marine Biology and Ecology 47: 77–87.

Pastorok, R.A. and Bilyard, G.R. 1985. Effects of sewage pollution on coral-reef communities. Marine Ecology Progress Series 21: 175–189.

Ramsing, N. and Gundersen, J. 2001. Seawater and gases, tabulated. physical parameters of interest to people working with. microsensors in marine systems. Limnology and Oceanography.

Smith, R. 1995. Assessment of Lagoon sand and Aggregate Resources, Funafuti Atoll, Tuvalu, SOPAC technical report 212.



APPENDICES

Appendix 1: Current vectors at neap tide



Appendix 2: Current vectors at spring tide



Appendix 3: Sediment dispersion outputs

Sedimentation after 10 days Suspended particles after 10 days

SOURCE 1 (245,179)

SOURCE 2 (232,156)



Sedimentation after 10 days Suspended particles after 10 days

SOURCE3 (244,163)

SOURCE4 (241,171)

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