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Government of Sri Lanka METRO COLOMBO URBAN DEVELOPMENT PROJECT

(MCUDP)

The Consultancy Services for the Preparation of a Management Strategy for Wetlands and Carrying out an Assessment of Water Quality in the Inland Waterways and Lakes within Metro Colombo Area

Technical Report 04 PHYSICAL FEATURES

Water quality, lake, sediment and soil issues WETLAND MANAGEMENT STRATEGY

No.MCUDP/PHRD/03

January 2016

WETLAND MANAGEMENT STRATEGY ‐ Technical Report 04 ‐ PHYSICAL FEATURES_Water quality, lake, sediment and soil issues Metro Colombo Urban Development Project ‐ Consultancy Services for the Preparation of Management Strategy for Wetlands and Carrying out an Assessment of Water Quality in the Inland Waterways and Lakes within Metro Colombo Area

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TEAM MEMBERS

Rob MCINNES ................................................ Team leader

Sibila JAKSIC .................................................. Institutions and policy Project manager

Rob MCINNES ................................................ Ecosystem services_PRA_Questionnaires

Mark EVERARD .............................................. Ecosystem services

Anusha BANDARA ......................................... Ecosystem services _Economic valuation

Lalith AMARALAL ........................................... Ecosystem services_PRA

GREEN MOVEMENT ...................................... Ecosystem services _Questionnaires

Devaka WEERAKOON .................................... Biodiversity

Gilles MOYNOT .............................................. Biodiversity

Guillaume SALMON ....................................... Communication Plan

Nicolas BARGIER ........................................ Water and soil quality

Ranjana PIYADASA ..................................... Water and soil quality

Pierre RIGAUDIERE ........................................ Physical features_Hydrology

Anura RANWALA ........................................... Physical features_Hydrology

GIS team : Thilina Buddima PALLETHANNE, Anthony ROUÉ, Vu Hai LE, Inakshi KARUNAWARDANA,

Olivier PETOT (ASCONIT) and “SAFEGE” GIS team

Supportive roles :

Missaka HETTIARACHCHI ............................. Institutions and policy

Mathieu SOUQUET ....................................... Wetland Management Strategy

Keerthi Sri JAYAWARDENA ........................... Hydrology background

Indrasiri L.H .................................................. Expert GIS

Janaka DHARMASENA .................................. Urban planning issues

Emmanuel THIRY .......................................... Advisory on governance issue

Field assessment and survey were accomplished with participation of GREEN MOVEMENT staff for

ecosystem services assessment and students from Colombo University for water quality and

ecological surveys.


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Metro Colombo Wetland Management Strategy was developed as a complementary initiative

towards achieving capacity enhancement for flood and drainage management under the World Bank

funded Metro Colombo Urban Development Project.

The study received grant funding from the Japan Policy and Human Resources Development Fund

and was directly supervised by the Wetland Management Division of the Sri Lanka Land Reclamation

and Development Corporation :

Dr. N. S. Wijayarathne ‐ Deputy General Manager

L C G Soysa ‐ AGM ‐ Coordinator

W D C T Gunasiri ‐ Environmental Scientist ‐ Surface and Ground Water and Soil surveys

P D Pindeniya ‐ Ecologist ‐ Biodiversity Field surveys

Ranoshi Siripala ‐ Ecologist ‐ Biodiversity Field surveys

Kumudu Shirani ‐ Engineer ‐ Ecosystem Service Assessment

U Y I L Dharmasoma ‐ Surface and Ground Water surveys

Dammika Marasinghe ‐ Administrative Officer ‐ Social Surveys


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CONTENTS

1 EXECUTIVE SUMMARY ___________________________________ 1

2 OBJECTIVES OF THE STUDY ________________________________ 4

3 METHODOLOGY AND PROTOCOLS __________________________ 4

3.1. Surface water ____________________________________________________ 4

3.2. Beira lake _______________________________________________________ 10

3.3. Sediment _______________________________________________________ 12

3.4. ground water ____________________________________________________ 15

4 SURFACE WATER FUNCTIONING OF THE WETLAND ___________ 18

4.1. In situ parameters ________________________________________________ 18

4.2. Laboratory parameters ____________________________________________ 22

4.3. Phytoplankton community structure _________________________________ 32

4.4. Historical data ___________________________________________________ 38

4.5. water quality Synthesis ____________________________________________ 43

5 BEIRA LAKE ___________________________________________ 45

5.1. Water __________________________________________________________ 45

5.2. Sediment water __________________________________________________ 49

5.3. Sediment _______________________________________________________ 50

5.4. Beira lake hydrosystem analysis ____________________________________ 53

5.5. Beira lake action plan _____________________________________________ 53

6 SURFACE WATER QUALITY MONITORING NETWORK: A NEW STRATEGY ____________________________________________ 56

6.1. current water quality monitoring assessment in Colombo area ___________ 57

6.2. Formulate effectiveness monitoring program/design: Use new parameters and know how to exploit results ________________________________________ 58


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7 WETLAND GROUNDWATER FUNCTIONING __________________ 68

7.1. Introduction _____________________________________________________ 68

7.2. Water levels _____________________________________________________ 68

7.3. groundWater quality ______________________________________________ 69

7.4. Required data for a suitable monitoring ______________________________ 70

8 APPENDICES ___________________________________________ 71

Appendix 1 ‐ Inlets to Beira Lake _________________________________________ 71

Appendix 2 –Water framework directive quality scoring ______________________ 71

Appendix 3 – Historical data _____________________________________________ 71

Appendix 4 – Water quality distribution in Metro Colombo wetlands catchment: Map ___________________________________________________________ 71


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1 EXECUTIVE SUMMARY Surface water

Forty water quality monitoring locations across the surface drainage network system have been selected for investigation. These locations take into account the main objectives of the project and the requirement to understand actual water quality variation across the wetlands of Metropolitan Colombo. The current SLLRDC monitoring network of eight sampling points is included in the project locations in order to verify historical data.

The sampling period does not cover an annual cycle, which should be the minimal length of time for accurate and reliable conclusions. Despite that, the relatively stable climate in Colombo allows some strategic lessons to be learnt.

Based on this small dataset, and using only the first campaign to assess water quality on the top water layer (water sampling location), we can conclude for the canals with reference to the UE Water Framework Directive (WFD) Scores that:

‐ Very bad quality found in 50% of the network

‐ Bad water quality found in 15% of the network

‐ Medium quality found in 15% of the network

‐ Good quality found in 20% of the network

Ammonia, phosphorus and total dissolved solids (TDS) are the main problematic parameters particularly in the western area.

Regarding the historical data (from 2004 to 2014), we can conclude:

‐ The historical network shows a bad or very bad quality for 64% of the stations, which concurs with the assessment from this study.

‐ The pollution increase is growing faster from 2010 to now. Eventhough as a result the actual water quality is poor, the anthropogenic pollution sources can be easily identified and reduced with an efficient management plan. At a larger time‐scale, 5‐years pollutions can even been considered as a short time pollution, with a natural ecological potential still remaining on the watershed.

‐ Most parameters that are showing a reduction in quality are due to domestic waste water. For instance:

o Turbidity: sharp deterioration since 2010 ; o BOD: deterioration since 2010; o COD: deterioration since 2010; o Ammonia: partially deterioration since 2011; o Phosphate: high deterioration in 2014.

‐ From the end of 2014 water quality seems to improve for all parameters.

‐ Parliament Lake and Kelani river remains in a good or medium quality only regarding to those parameters. However, degradation has also been record since 2010.

‐ The historical dissolved oxygen values seem to be very low and show no correlation with sampling results produced during this study. Other parameters are substantially equivalent. It does raise questions about SLLRDC laboratory reliability or reliability of the University sampling.

With regard to Beira Lake, the following are the main conclusions :


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‐ Permanent Chla high rate seems to be maintained by: on the one hand, new input of nitrogen and phosphorus from catchment area, on the other hand by the nutrients stock in sediment water.

‐ Sediment water represents a main stock of nutrients for the whole lake system. A management plan needs to embed sediment dredging activities or/and reduction in nutrient level in sediment.

‐ Bloom variations create difficult biogenic condition: in one hand top layer alkaline pH, in the other hand, bottom layer low oxygenation.

‐ During this sampling period, bottom layer conditions are still not abiotic: pH does not become very acid, dissolved oxygen (DO) level medium, iron and manganese dissolved part is bad but it could be worst, taking account permanent bloom and trophic status.

‐ Chlororphyla confirms hypertrophic status.

‐ The microbiological contamination is not really high level, indeed waste water collection seems to be partially successful.

‐ The sediment does not show huge micropollutants contamination. On the other hand, the sediment possess medium to bad heavy metal contamination (in particular lead and zinc). Dredging activities need to be clearly regulated and fishing strictly prohibited during such works.

‐ Salinity increase in the bottom layer (2 meters depth) during a period infers that the salted water wedge is clearly not far from the top of aquifer.

For the phytoplankton assessment, Cyanophyceae mainly dominate the population of all sites, and especially on 5 in‐lake locations: Beira Lake, East Lake and Floating Market. The cell densities are higher for those stations, without however reaching a 20000 cells/mL (only for potentially toxic taxa) threshold, considered as health hazardous in Europe.

Those potentially toxic taxa (Lyngbya, Microcystis, Oscillatoriaet Phormidium) were identified on most of the sites excepted stations 4, 9 and 12. Blooms have not been observed neither quantified with the phytoplankton population analysis, but need to be monitored especially throughout yearly climatic fluctuation. Indeed, favorable conditions for algae blooms can occur with climatic seasonal variation.

To conclude, we define two different action plans:

‐ For Beira Lake: Our study fills some specific gaps (sediment quality) but considerable elements are missing in order to have a complete and comprehensive overview. The main compartments are the fauna (fish, worms in sediment, zooplankton) and flora (algae). In the same way, it is absolutely necessary to undertake such a study for the duration of at least one year, and ideally for three years. Nevertheless, the course of action mentioned in previous studies basically remains strong and is developed.

‐ Water quality monitoring strategy: According to this assessment, we have designed a monitoring strategy. This should only be considered as the first step in the development of the whole strategy. Nevertheless we proposed key points for both Activities 1 and 2.


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Groundwater

Underground water bodies have annual cycles, depending on climate (rainfall, temperature) and seasons. In that respect, a 5‐week monitoring is totally inadequate to draw firm conclusions: information collected during 5 weeks is just a little pattern of the whole year cycle. There is no correct data interpretation possible with such a short monitoring period.


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2 OBJECTIVES OF THE STUDY This study is divided into three parts:

Wetland Surface water functioning:

The purpose of this study is :

A. In the one hand : to assess water quality in canals through a large water quality monitoring network in order to know chemical caracteristics and pollution amount;

B. In the other hand: to assess water quality in Beira Lake to have a better understanding of relationships between each compartments (water, sediments).

Wetland Groundwater functioning:

The main objectives are to understand groundwater quality and to evaluate the relationships between groundwater and wetland physical hydrology and water quality.

Water quality monitoring network improvement:

Using previous results, trying to improve the monitoring to achieve a better real time understanding of the situation by the WMB and an appropriate management.

3 METHODOLOGY AND PROTOCOLS

3.1. SURFACE WATER Selection of the monitoring stations location across the surface drainage network

Forty water quality monitoring locations across the surface drainage network system have been selected. These locations take into account the main objectives of the project and the requirement to understand actual water quality variation. The current SLLRDC monitoring network of eight sampling points is included in the project locations in order to verify historical data. The precise monitoring locations across the surface water drainage system are selected accordingly to the following features:

• Topography; • Stream order; • Stagnant flow areas; • Inflows and outflows of lakes and wetlands; • Depth of the water body; • Direction of the surface water flow and distance from the water body; • Adjacent land use; • Potential pollution risks from the surrounding area; • Geological and hydrological characteristics; and • Vegetation of the area.


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A field survey was conducted before selecting the exact monitoring pointsposition torecord and clarify the above characteristics, to ensure synergy with other field activities and to assess the accessibility of each location for monitoring.

Monitoring methodology

Monthly monitoring was conducted from April to August. The monitoring evaluation involved a combination of in situ assessments using hand‐held water quality meters and the collection of water samples for laboratory analysis. The following parameters have been recorded using in situ field instruments:

• pH • Electrical conductivity • Salinity • Turbidity • Temperature • Dissolved oxygen.

For each canal or stream location up to five in situ points were monitored for the above parameters to verify cross sectional water quality variation. This has involve recording water quality parameters from locations adjacent to each bank, at the surface, mid‐depth and just above channel bed in the middle of the water course (see drawing above). Those measurements helped to detect the presence of saltwater intrusion within the surface drainage network.

Monthly samples have been collected from all forty locations for laboratory chemical analysis. Samples were collected both during the rainy and dry season. Each sample was collected at mid‐depth of the water body, stored in clean sampling bottles and kept cool during transportation to the laboratory. Analyses were conducted at the SGS Lanka (Pvt) Ltd laboratory using standard analytical techniques. The following parameters were ascertained through analysis of the collected samples:

• pH • Total suspended solids • Ammonia (NH 3) • Nitrate (as N) • Phosphate (PO4) • Chemical Oxygen Demand • Biological Oxygen Demand • Total faecal coliforms • E‐coli • Chlorophyll • Algal diversity.

During sampling local information was registered on a standardised monitoring sheet. Any features or activities which could influence water quality were recorded, such as presence of litter, influent discharge, morphological disturbance to the channel or substrate or watercourse management activities such as removal of invasive species. A GPS location was taken for each sampling site.


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Table 1. Sampling site: localization and justification

SLLRDC Station No.

Station No. Location

Details of Sampling Location

Justification for the selection Descriptions of site

Coordinates

X Y

1 Canal at

KottawaNorth

Act as a control point in the upper catchment

Predominant valley can be identified as sallow vee and flow type is smooth. The vegetation type isuniform and grasses ispredominant.

79.95464 6.856662

2 Canal at Pathiragoda

Udahamullaela

Act as a control point in the upper catchment

Predominant valley can be identified as U‐ shape valley and flow type can be mention as

unbroken waves. The river substrate is not be visible. Bank material is soil. Vegetation type is

scattered grasses.

79.92638 6.863267

18 3 Parliamentlake Maha ela Water inlet to the

Parliament lake

Predominant valley can be identified as U‐ shape valley and flow type can be mention as

unbroken waves. The river substrate is not be visible. Bank material is soil. Vegetation type is

uniform. Grasses are predominant.

79.9328 6.868419

4 Water inlet to Parliament

lake Canal

To determine the load of pollutants coming

to the lake

Predominant valley can be identified as sallow vee and flow type is smooth. The bed of river

can be seen. Bank material is earth. The vegetation type is grasses.

79.92177 6.876351

5 Dammaladeniyamedaela

Water inlet to

Parliament lake

To determine the load of pollutants comes to

the lake

Predominant valley can be identified as sallow vee and flow type is smooth. Bank material is earth and wetland can be identified this area. Vegetation type is complex and can be seen

grasses, herbs and shrubs.

79.91228 6.877982

6 Atunkedeniyamedaela Canal


the lake

Predominant valley can be identified as sallow vee and flow type is smooth. Bank material is earth. Vegetation type is uniform and grasses

are predominant.

79.93538 6.886891

7 Parliamentlake

Inside the lake

To determine the suitability for

recreation, to assess the impact of variation of water quality to the

Parliament

8 Parliamentlake

Inside the lake

To determine the suitability for

recreation, to assess the impact of variation of water quality to the

Parliament

3 9 BattaramullaNorth

Water outlet of Parliament

lake

To determine the load of pollutants to the

downstream from the tank

Predominant valley can be identified as sallow vee and flow type is smooth. Bank

materialisearth and vegetation type is grasses. 79.90431

6.910329

10 Diyawannaathuruela Canal


the marsh

Predominant valley can be identified as sallow vee and stagnant water with floating plants. Bank material is earth. Vegetation type is

complex and shrubs and grasses are predominant.

79.90837 6.923055

11 Kolonnawa Marsh

Water inlet to

Kolonnawa marsh


the marsh

Predominant valley can be identified as U‐shape valley and flow type can be mention as smooth

with waves. Bed of canal cannot be seen. Vegetation type is complex and trees are

dominant.

79.89921 6.916103

12 Kiththampahuwa canal

Closer to Kolonnawa Marsh


downstream from the marsh

Predominant valley can be identified as U‐shape valley and flow type is smooth. Bank material is earth and vegetation type is grasses. Floating

plants have covered surface of water.

79.89868 6.928643


closer to Methotam

ulla garbage dump

The canal is polluted with the leachate

from garbage dump, wash‐offs etc

Predominant valley can be identified as shallow vee and flow type can be mention as smooth. The vegetation type is uniform and there are

one type (grasses).

79.88913 6.942005


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SLLRDC Station


Details of Sampling

Justification for the selection Descriptions of site Coordinates


Closer to the

Orugodawatte

Petroleum Corporatio

n

The canal is polluted with the effluents from Petroleum Corporation

Predominant valley can be identified as U‐shape valley and flow type can be mention as smooth. The vegetation type isuniform and grasses are

predominant.

79.88993 6.951741

15 Kolonnawa Marsh



Predominant valley can be identified as U‐shape valley and flow type is smooth. Bed of canal cannot be seen. Bank material is earth and

vegetation type is grasses.

79.88606 6.917273

10 16 Serpentine canal

Highly polluted canal, highly populated slum

area

Predominant valley can be identified as concave/bowl and flow type is smooth. Bed of canal cannot be seen and Bank material is

cement.

79.88289 6.918497

17 HeenEla Marsh

Water inlet to the marsh


the marsh

Predominant valley can be identified as U‐shape valley and flow type is smooth. Bed of canal cannot be seen and Bank material earth.

79.88903 6.909878

18 Kotte Marsh Water inlet to Kotte marsh


the marsh

Predominant valley can be identified as shallow vee and flow type is smooth. Bed of canal cannot

be seen and vegetation type is uniform and grasses are predominant.

79.89443 6.90467

19 Kotte Marsh

Water outlet of the Kotte marsh



Predominant valley can be identified as U‐shape valley and flow type is smooth. Bank material is

earth with cement wall. Vegetation type is uniform and grasses are predominant.

79.8918 6.877905

20 Kirulapone canal

Canal crossing Baseline road

To identify the level of Salinity intrusion

Predominant valley can be identified as U‐shape valley and flow type is smooth. Bank material is earth. Vegetation type is uniform and grasses

are predominant.

79.87671 6.888006

21 Kirulapone canal

Closer to Havelock

city

To identify the level of Salinity intrusion, Level of pollutants flows into the sea

Predominant valley can be identified as U‐ shape valley

79.8596 6.879494

22 Dehiwala canal

Closer to Pamankada

To identify the level of Salinity intrusion, load of pollutants flows

into the sea

Predominant valley can be identified as U‐ shape valley 79.86343

6.862976

01 23 Dematagoda Canal

Baseline road

crossing Dematagoda canal

Highly populated area, low income community

Predominant valley can be identified as U‐shape valley and flow type can be mention as smooth. Bank wall material is cement and bank surface is

earth. Bed of canal cannot be seen. The vegetation type is uniform and there is one type

(grasses).

79.87807 6.927744

24 St. Sebastian Canal

Drain to the Beira lake

Highlypopulated area Predominant valley can be identified as U‐ shape valley

79.86623 6.936193

22 25 St. Sebastian Canal

North of the St

Sebastian canal

To identify the trend of water quality changes with the distance, highly polluted canal

Predominant valley can be identified as U‐ shape valley 79.87463

6.950804

26 26 St. Sebastian Canal

Closer to Nagalagam street and Sedawatte‐Ambatale

road

To determine the load of pollutants flows into Kelani River


79.87801 6.956827

27 Redbanaela Mattakullya area

To determine the load of pollutants flows

into the sea


79.86475 6.956028


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SLLRDC Station


Details of Sampling

Justification for the selection Descriptions of site Coordinates

28 KarandagahamulaKumbur

aela

Water inlet to

Parliament lake

To determine the quality of the water comes to the lake

Predominant valley can be identified as concave/bowl and flow type is smooth. The bank top vegetation type is uniform and there are

short herbs or grasses.

79.92763 6.900973

29 Thalahena tank

Water inlet to the

Thalahena tank


the tank

Predominant valley can be identified as sallow vee and flow type is smooth. Bank top

vegetation type is simple and there are two or three vegetation types. Such as grasses, herbs

and shrubs.

79.94752 6.880272

30 Evarihena tank

Outlet of the tank


downstream from the tank

Predominant valley can be identified as deep vee and flow type can be mention as unbroken sanding waves. The vegetation type is uniform

and there are one type (grasses).

79.9577 6.888764

31 Canal passing through the paddy land

After joining both

‘Medeniyamedaela’

and ‘Deniyayawelyayamed

aela’

To identify the pollutant levels,

mainly agrochemicals add into the water ways run through

paddy field

Predominant valley can be identified as U‐shape valley and flow type can be mention as smooth. The vegetation type is uniform and there are one type (grasses). Bed of canal cannotbeseen.

79.95356 6.92719

32 Mulleriyawa tank

Centre of the tank

This station represents the general water quality of the tank

Tank surface covered with floating plants. Bed of tank cannot be seen.

79.94296 6.934336

33 Mahawelaela Canal To assess the level of pollutants add into

downstream

No obvious valley sides and stagnant water can be identified. Vegetation type is simple and

shrubs are predominant. 79.92818

6.936155

34 Ambataleela Close to

projectboundary

To identify the level of pollutants flow into

Kelani river

Predominant valley can be identified as U‐shape valley and flow type can be mention as smooth. The vegetation type is complex. Bed of canal

cannot be seen.

79.94656 6.937449

29 35 Norris Canal

Closer to the

National hospital, Colombo

Pollution level is comparatively high due to the adjacent

hospital

Predominant valley can be identified as U‐ shape valley. Bank materialiscement.

79.865875 6.921892

36 South Beire Lake Lake

37 South Beire Lake Lake

38 West Beire Lake Lake




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Figure 1. Surface water sample locations


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3.2. BEIRA LAKE Selection of the monitoring point location in the Beira Lake

The in situ water sampling locations were selected by using a systematic sampling method (Figure 2). A grid method was used to determine the sampling locations. In each water body that comprise the larger Beira Lake eight to ten sampling points were selected for in situ analysis. All the locations were marked with a GPS. Laboratory water analysis were conducted to measure pH, electrical conductivity, salinity, total dissolved solids, temperature, and dissolved oxygen using the hand‐held instruments. Desk‐based reviews were conducted to collect historical data on the water quality and catchment land use to understand the present day context of the Lake. In order to fully understand the functioning of the Lake the following items have been prepared as a result of the work:

• Mapping of the surface drainage catchments. • Mapping of the sewer system. • Mapping of the storm water system. • Mapping of characterized inflow discharges to the lake. • Comprehensive analysis of the hydrologic and hydraulic functioning of the catchment. • Synthesis of the recent project that was implemented to disconnect the illegal

communications between storm and sewer system. • Identification of issues.

The above information was synthesized into a summary which identifies the issues and makes recommendations on future management and improvements. This summary aimed to include, non‐exhaustively:

• Identification and classification of pollutions sources. • Ownership of pollution sources. • Identification of historical and current water vectored problems. • Identification of future or planned problems to be addressed (e.g. hospital, etc.). • An assessment of the efficiency of the works already undertaken. • Recommendations on restoration and improvement works including source control, in‐Lake

works and regulating/policy‐related approaches.


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Figure 2.Sampling Locations of the Beira Lake)


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Figure 3. Inlets to Beira Lake

3.3. SEDIMENT Rationale

Sediments can serve as a sink as well as a potential source for toxic and conventional pollutants. Even if discharges of pollutants to water bodies are greatly reduced or completely eliminated, contaminated sediments can serve as a continuing source of pollution to the aquatic environment contributing to both ecological and human impacts.

Sampling methodology

Sediment samples were collected from five water bodies: Beira Lake, Diyawanna Lake and Thalangama Tank. Three samples were taken from Beira Lake (one for each of the three distinct parts of the lake system) and one from the each of the other two lakes (Figure 5 and Table 2). In each distinct lake three sediment samples were taken and to derive a composite sample. All the locations were identified using a hand‐held GPS. Sediment samples were collected using a grab (Figure 4), transferred to sample containers and cooled for transport to the laboratory. Sediment analyses were conducted by the SGS. The laboratory analysis assessed the sediment for the following parameters, even though the utility of some of the parameters was limited as they represent pore water:


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• pH; • Conductivity; Turbidity; • Total suspended solids; • Temperature; • Dissolved oxygen; • Chemical Oxygen Demand; • Biological Oxygen Demand; • Salinity; • Total faecal coli‐forms; • E‐coli; • Heavy metals; • Polyaromatic hydrocarbons; • PCBs; • Pesticides; • Nitrogen; • Ammonia; • Nitrate; • Nitrite; • Free ammonia; • Total phosphorus; • Phosphate; • Aluminium; • Iron; • Manganese.

Figure 4. Sediment sampling


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Table 2. Sampling location in Beira Lake

No Card Lake/ Tank X Y 1 A

Beira Lake (1st Lake) 79o 51.423' E 6o 55.372' N

2 B 79o 51.212' E 6o 55.653' N 3 C 79o 50.973' E 6o 55.781' N 4 D

Beira Lake (2nd Lake – Gangarama)79o 50.921' E 6o 55.065' N

5 E 79o 51.046' E 6o 55.035' N 6 F 79o 51.176' E 6o 54.974' N 7 G

FloatingMarket 79o51.148' E 6o 55.958' N

8 H 79o51.212' E 6o 55.937' N 9 I 79o 51.292' E 6o 55.912' N 10 J

Diyawanna Lake 79o 55.131' E 6o 53.154' N

11 K 79o 54.918' E 6o 53.294' N 12 L

Talangama Tank 79o 56.824' E 6o 53.408' N

13 M 79o 56.853' E 6o 53.408' N 14 N 79o 56.883' E 6o 53.411' N

Figure 5. Sediment sample locations


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3.4. GROUND WATER Introduction

The groundwater quality in the Metropolitan Colombo urban area, and particularly in the Sri Lankan Parliament lake area, has been under threat over the past few decades with the increase of urbanization, industrial development and extensive application of fertilizer in agricultural activities together with high rates of water extraction resulting rapid groundwater depletion, saline intrusion and groundwater pollution (Nandaseela S., Ranjana.U.KPiyadasa, 2015). Groundwater is constantly moving and it is replenished by rainfall, particularly from rainfall events and during the monsoon rains from April to July including wet and dry periods. Groundwater levels and flow rates vary with the seasons. Bacteria levels in the upper part of an aquifer can fluctuate between harmless to lethal values over the sampling period. The water chemistry and bacteria levels can also change with depth below ground due to different human activities surrounding the area. In general, deeper groundwater tables tend to give an accurate overview of the chemical profile of the aquifer whereas the quality of shallow aquifer is more likely to be easily disturbed (for instance flash floods, discrete pollution events) and therefore will not reflect potential chronic pollution Therefore the boreholes were designed to draw from deeper groundwater rather than shallower water that may have been recently contaminated.

Selection of the boreholes and borehole construction

Six borehole locations were selected considering the objective to understand current groundwater quality and the relationship with wetlands and Parliament Lake. During selecting process, the following characteristics were considered along with discussions with the client:

• Topography of the area; • Direction of the surface water flow; • Distance from the water body; • Potential pollution risks from the surrounding area; • Geological and hydrological characteristics; • Vegetation of the area; and • Security of the well.

Field verification was conducted prior to drilling to identify above mentioned characteristics and the access requirements for drilling equipment and monthly monitoring.

Construction was carried out by contract with the Water Resources Board (WRB‐ Government Organization). The final locations were recorded using GPS. The boreholes were excavated to a total depth of 15 to 20m. Borehole logs were recorded for each location. Well construction was monitored and drilling samples were collected during the borehole construction by technical officers from the University of Colombo.

Borehole water sample analysis

The following laboratory analysis (as per surface water samples) were conducted for monthly alter samples taken from the six boreholes over the period between August and September:


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• pH; • Conductivity; • Turbidity; • Total suspendedsolids; • Dissolvedoxygen; • Ammonia (NH 3); • Nitrate (as N); • Phosphate (PO4); • Chemical OxygenDemand; • Biological Oxygen Demand; • Salinity; • Total faecal coliforms; • E‐coli; • Chlorophyll.

In addition to the laboratory analysis, in situ measures were conducted for pH, electrical conductivity, salinity, total dissolved solids, temperature and dissolved oxygen using hand‐held instruments. Laboratory analyses were conducted by the SGS.

Measuring the groundwater levels

Measurements were taken from a fixed reference point such as the top of the borehole casing or a particular point on the rising pipe. The reference point was marked with tape or paint, and its elevation recorded. When the water level in the well is shallow (below 2m under ground level) ordinary measuring tape can be used to measure the water surface, however when the water level is below 2m below ground level water levels were measured by an electronic ‘dipper’. During the monitoring process, local information was recorded on the well monitoring sheets. Features near the well which might influence water quality, such as swallow holes, rivers, lakes, fuel storage tanks, effluent pipes, farmyards, roads, septic tank percolation areas and soakaways were recorded. For

each feature, the distance from the well and whether it is up‐slope, down‐slope or across‐slope from the well was recorded. Observations were confined to the area extending 60m up‐slope of the well and approximately 15m down‐slope of the well.

Data analysis and outputs

The objectives were to assess seasonal variation in water levels for the six boreholes but their building was too late to achieve this goal. However, water quality data have been compared among the six locations in order to identify spatial or temporal relationships.


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Figure 6. Location of boreholes around Parliament Lake


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4 SURFACE WATER FUNCTIONING OF THE WETLAND

This section gives an overview of chemical quality in the study area during 4 months and provides some key points to understand the canal functioning system.

The assessment has been divided into two components:

‐ In situ water chemistry: sampled four times and from the top to the bottom layer within the water body. This provides information of how water quality evolves.

‐ Laboratory water chemistry: single sample that provides a picture of the amount of pollution.

All the data have been scored by using European Water Framework Directive classification (Appendix 2). The scores are based on scientific approach according to aquatic life tolerance of fish, invertebrates (insect larvae, worms, etc.) and algae regarding pollution assessed. However, Sri Lankan context of fauna/flora being probably different in some way than European area, that is why we have made the choice not to take account scores relating to temperature as well as conductivity and salinity due to coastal situation of the canal system. However, according to aquatic life, we kept up scores for pH, Dissolved Oxygen, Turbidity (and TSS/TDS), BOD, COD, Ammonia, Nitrate, Phosphate, Chlorophyll a and coliforms (including E. coli).

4.1. IN SITU PARAMETERS In situ parameters provide information on the relationship between the watershed environment (air, sediment) and water chemistry. It can be the fastest way of identifying an imbalance in an ecosystem. Each parameter is described with regard to problems and,where possible,pollution sources:

pH

pH scale runs from 0 to 14, however in a water body values that are roughly between 6 and 8 are not usually indicative of any ecosystem imbalance. pH is the most stable parameter across the canal system and practically pH neutral (mean = 6.8). It ranges from 6.3 to 7.4 and can be considered to be non problematic for aquatic life.

pH is also:

‐ Very stable from one location to another;

‐ Very stable within the water column;

‐ Very stable during the 4 sampling periods: maximum variation reached 1.4 in Kolonnawa Canal in the bottom layer.


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Conductivity/Salinity

Taking into account the fact that the sensor calculates salinity using conductivity, temperature and pressure, salinity evolves in line with conductivity which is typical for Colombo where very low variation of temperature and pressure persist.

High rates of conductivity can be associated with pollution, but also due to saline intrusion. We can also consider the implications of proposed sea level rise, which may be as much as 0.658m over the next 50 years (UNDP, 2012 Hazard profiles of Sri Lanka). Due to the small data set it may be difficult in our case to discriminate the reason of increasing conductivity value.

The field observations are the following:

‐ No stratification along the water column during May, July and August campaigns contrary to July campaign: Canal Kottawa North, Kirulapone canal, Dehiwalacanal, Redbanaela. On these locations, conductivity increase with depth.

‐ Conductivity ranges all over the stations between 76 µS/cm in Atunkedeniyamedaela and 4200 µS/cm in Dehiwala canal (bottom layer, 1.20 depth).

‐ Mean conductivity reaches 330 µS/cm but the median value is slightly lower in May and July and slightly higher in June and August correlated with more marine water upwelling. The Dehiwala canal can present conductivity from 255 to 4200 µS/cm. Locations without saline influence show frequently conductivity between 130 and 200 µS/cm. It is an appropriate value for freshwater aquatic life.

We can describe 3 areas :

‐ South‐East and lakes : low conductivity

‐ North‐West and Kolonnawa area: medium conductivity

‐ Coastal North and South: high conductivity and brackish water


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Figure 7. Conductivity results on network

Temperature

The temperature is a more unstable parameter while remaining in a range of 25.5 and 34°C. Tropical climate, narrow air temperature range and shallow depth in wetlands can explain such low variability especially in the top layer.

Depending on the air temperature, sampling time and rainfall, the difference of temperature between the top and the bottom of the wetland can reach 2°, the bottom being most of the timecooler except in Kinda Canal. In this location, in June and July a lower temperature on the top layer has been observed(1 or 2°C lower than bottom layer). We cannot explain this exception in particular by comparing to nearest stations (Kirulapone canal and Heen Ela).However, during the June campaign, the temperature in Kirulapone canal decreased to 25.5°C accompanied by a shallow salinity increasing. The probable saline water input would have had an impact on few stations during this event.

Apart from previous anomaly, there is no correlation between temperature and other parameters: conductivity and salinity increasing does not affect systematically temperature. That is why the temperature variability seems to be mostly led by weather events.

Dissolved oxygen

Oxygen concentration in freshwater depends on temperature, gas exchange between water and air (helped by water turbulence), photosynthesis/respiration/decomposition phenomena and organic matter mineralization. Therefore, sampling time has a real impact on dissolved oxygen rates. Aquatic life is impossible below minimum concentration and each faunistic species has its own requirements in terms of oxygen needs


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Campaign data demonstrate a very good range of dissolved oxygen (DO): the main stations are saturated (7.5 mg/l) with oxygen mainly in June but also throughout the sampling period except in August campaign. May and July campaigns are slightly lower saturation (near 7 mg/l). Concentration between locations in the same campaign is really homogenous (very low standard deviation) and it can be considered as fully compatible with the aquatic life. There are no permanent under saturated locations and no difference within the water column (only due to temperature variation creating over‐saturated concentration in depth).

The most stressing period remains the August campaign. DO decreases lower than 6 mg/l (considered as “good quality” for aquatic life) in 7 stations :

‐ Water inlet to Parliament Lake (St 4): the top layer shows 5.6 mg/l while other parameters are stable. It may indicate point‐source pollution.

‐ Dammaladeniyamedaela (St 5): same as St 4. It could suggest a pollution originating from south west of Parliament lake.

‐ Dematagoda Canal (St 14): Closer to the Kolonnawa Petroleum Corporation this station present a 5.5 mg/l concentration correlated to high conductivity (or salinity?).

‐ Dematagoda Canal (St 23): Station known as highly polluted area, the dissolved oxygen value is the lowest in this dataset (5mg/l). Very paradoxical situation: top and mid layer is relatively saline and over‐saturated whereas bottom layer is undersaturated and low conductivity.

‐ St. Sebastian Canal (St 26): This station should indicate the load of pollutants flows into Kelani River. The dissolved oxygen rate is low (5.7 mg/l) but it is not a value of concern.

‐ Redbanaela (St 27): Same value as St. Sebastian Canal but in the brackish water, so the saturation is lower in saline water.

‐ Norris Canal (St 35): Like Dammaladeniyamedaela Station, the dissolved oxygen rate is relatively low (5.3 mg/l) and suggest pollution maybe due to adjacent hospital.

Finding such issue only during August campaign while other parameters remain relatively stable can be an indicator of chronic or seasonal pollution which would require further investigations.

Total Dissolved Solids (TDS)

TDS level rise mainly causes water turbidity, and consequently slows photosynthesis and disturbs the trophic web (flora and fauna) particularly when it is permanent. TDS can be naturally important in river showing a high sediment transport or in lentic area like wetlands. But in a polluted area, the sources can be agricultural and road runoff, soil contamination, etc. and generally associated with nutrient runoff (N, P, C).

We use French and WFD standards to classify values. It seems to be a very harsh scoring system regarding this parameter because we do not know the natural TDS rate in Colombo low flow canal system. Nevertheless, the scores is a reflection of scientific reality: lower the TDS is, lower the stress on aquatic life is.


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TDS remains high during all the sampling period. The lowest value (28.9 mg/l) was found in Atunkedeniyamedaela in May. It means that low turbidity and TDS exist in Sri Lanka area but it is really exceptional.

TDS fluctuated as follows during the sample period: lower in May and July (from 106 to 128 mg/l) and higher in June and August (203 and 201 mg/l) showing a normal link with rainfall. But it interesting to notice that the median range from 100 to 125 mg/l. Only a few stations show a very high rate (more than 250 mg/l) correlated to conductivity increasing (more than 500 µS/cm): Kolonnawa Canal (St 10) in August, Kittampahuwa canal (St 13) in June and July, Dematagoda Canal (St 14) from June to August, Dehiwala canal (St 22) in June and August, St. Sebastian Canal (St 25) in August and finally Redbanaela (St 27) from June to August. The station 22 and 27 are closer to the sea (it can be a brackish water) but also potentially polluted, so source of TDS increasing is not easy to discriminate.

4.2. LABORATORY PARAMETERS To complete the previous assessment, a few parameters have been analyzed in laboratory during the first campaign in May. According to the urban nature of the area and pollution sources already identified, the analyses focused on nutrients, phytoplankton and microbiology.

General comments:

Total suspended solids (TSS)

This parameter shows a better situation than TDS, but 3 stations seem heavily polluted and 5 slightly polluted.

BOD

Fairly good status, but once again 5 stations are polluted and 3 others slightly polluted.

COD

This is the first parameter to show the bad water quality in the Colombo area. 30% of the sampling stations are in a bad or very bad status and 4 stations in a medium status.

Free ammonia

This is the most worrying parameter and a reliable pollution indicator. 43% of the stations present a very bad score and 11% a bad score (more than 2 mg/l). Ammonia comes from organic matter mineralization (). Waste water and agricultural uses are the main sources in polluted areas. It can be toxic for aquatic life over 2 mg/l. Under normal oxygenated conditions ammonia is not very stable and can become nitrite or nitrate. It is even more surprising because dissolved oxygen is very high (often saturated).

Nitrate


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In contrast to ammonia, nitrate is very low for all station and the situation seems really very good. It is a main paradoxical point because the nitrate is the stable form of nitrogen in water but in 50% of the stations ammonia is higher.

Figure 8. Nitrogen degradation cycle

NitrogenGas

OrganicMatter (decomposition)


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Table 3. Physico‐chemical results on network (May 2015)

Sample no Location pH

EC (µS/cm) Temp (C°) DO (ppm)

Salinity (ppt)

TDS (mg/L)

Total Suspended

SolidsBOD COD

Free Ammonia

as N

Nitrate as N

Total phosphate

Chlorophyll a (mg/m3) Coliforms E.coli

1 Canal at Kottawa North 6.5 163.3 32.3 6.9 0.07 72.7 143 12 96 <0,04 1.7 0.08 <3 33 172 Canal at Pathiragoda 6.5 270.0 33.1 6.8 0.11 126.2 4 <5 8 <0,04 2.5 <0,07 <3 33 173 Parliament lake 6.9 165.7 32.2 6.9 0.07 73.9 <2 <5 8 <0,04 1.3 <0,07 <3 23 174 Water inlet to Parliament lake 6.7 238.1 32.9 6.8 0.10 110.2 8 <5 22 2.28 0.6 0.28 <3 22 115 Dammaladeniya meda ela 6.6 279.1 30.7 7.0 0.12 130.8 25 <5 28 3.79 0.1 0.18 <3 34 136 Atunkedeniya meda ela 7.5 76.1 34.0 6.7 0.04 28.9 17 <5 24 <0,04 0.3 <0,07 7 27 117 Parliament lake 6.9 270.2 33.1 6.8 0.11 126.3 9 <5 8 <0,04 1.3 <0,07 <3 33 138 Kinda Canal 6.7 228.0 30.8 7.1 0.10 105.1 18 <5 25 2.72 <0,1 0.32 6 33 139 Kolonnawa Canal 7.0 141.0 29.8 7.2 0.07 61.5 9 <5 11 <0,04 0.4 <0,07 4 49 1310 Kolonnawa Canal 6.1 261.2 32.2 6.8 0.11 121.8 59 <5 33 <0,04 0.2 <0,07 <3 130 13011 Kolonnawa Canal 6.7 168.9 29.3 7.2 0.08 75.5 8 <5 21 <0,04 0.4 <0,07 5 110 11012 Kittampahuwa canal 6.9 342.6 28.2 7.3 0.16 162.6 13 <5 35 10 0.1 0.26 3 27 1113 Kittampahuwa canal 6.8 340.5 29.3 7.3 0.15 161.6 18 <5 51 39 0.1 0.44 <3 22 814 Dematagoda Canal 7.0 477.2 28.5 7.4 0.22 230.2 12 7 66 42 0.3 0.45 3 33 1315 Kolonnawa Marsh 6.5 237.2 28.9 7.2 0.11 109.7 67 12 94 26 0.3 2.5 <3 79 1316 Serpentine canal 6.5 371.8 29.0 7.2 0.17 177.3 56 8 52 14 0.1 1 <3 33 817 Heen Ela Marsh 6.5 234.0 29.7 7.2 0.10 108.1 84 <5 74 7.45 0.2 0.59 5 33 1118 Kotte Marsh 6.9 144.1 30.3 7.2 0.07 63.0 186 21 134 <0,04 0.6 0.12 3 33 1119 Kotte Marsh 6.6 263.7 29.3 7.2 0.12 123.0 7 <5 16 5.12 0.3 0.27 5 79 2320 Kirulapone canal 6.8 211.6 30.8 7.2 0.09 96.9 12 <5 24 6.85 <0,1 0.28 5 22 821 Heen Ela 6.8 315.2 31.0 7.0 0.14 148.9 22 <5 26 5.7 <0,1 0.27 4 27 1322 Dehiwala canal 6.7 267.0 32.1 7.1 0.11 124.7 23 15 76 18 <0,1 <0,07 4 23 823 Dematagoda Canal 6.8 276.1 28.7 7.2 0.12 129.3 32 6 57 11 0.2 1.3 8 49 824 Kirulapana Canal 6.9 181.8 31.1 7.1 0.08 81.9 <2 <5 14 <0,04 0.6 <0,07 4 79 1325 St. Sebastian Canal 6.6 242.9 30.4 7.2 0.11 112.6 14 <5 32 8.3 0.3 0.77 <3 33 1126 St. Sebastian Canal 6.7 254.7 30.7 7.2 0.11 118.5 14 <5 29 7.75 0.2 0.72 <3 8 527 Redbana ela 6.7 395.9 29.5 7.1 0.18 189.4 85 18 156 11 0.2 1.3 <3 33 1128 Karandagahamula Kumbura ela 6.4 195.9 29.3 7.1 0.09 89.0 36 6 37 0.98 0.1 0.16 4 33 1329 Thalahena tank 6.5 138.6 29.9 7.0 0.06 60.3 10 <5 14 <0,04 0.6 0.07 3 33 830 Evarihena tank 6.7 119.4 30.2 7.0 0.06 50.6 <2 <5 7 <0,04 0.6 <0,07 <3 33 11

31 Canal passing through the paddy land 6.9 138.7 30.6 6.9 0.06 60.3 <2 <5 11 <0,04 0.7 <0,07 4 22 11

32 Mulleriyawa tank 7.8 248.9 33.9 6.0 0.10 115.6 <2 <5 20 <0,04 0.1 <0,07 5 23 833 Mahawela ela 6.9 140.7 30.2 6.9 0.06 61.3 12 <5 56 3.6 <0,1 0.08 <3 49 1334 Ambatale ela 6.9 139.0 29.9 7.2 0.06 60.5 106 <5 36 <0,04 0.6 <0,07 <3 33 1735 Norris Canal 6.6 318.4 29.1 7.2 0.14 150.5 18 <5 29 11 0.2 0.99 <3 33 11

Mean 37.6 11.7 40.9 11.8 0.5 0.6 4.6 40.0 18.1Med 18.0 12.0 29.0 8.0 0.3 0.3 4.0 33.0 11.0SD 43.9 5.5 35.4 11.4 0.5 0.6 1.4 25.6 25.8Max 186.0 21.0 156.0 42.0 2.5 2.5 8.0 130.0 130.0Min 4.0 6.0 7.0 1.0 0.1 0.1 3.0 8.0 5.0


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Figure 9. Physico‐chemical results on network (May 2015)

.


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Phosphate

This parameter also highlights the pollution status of the monitoring stations: 23% are in bad or very bad situation and 23% are in medium status.

Chlorophyll a

The general status is very good. Chlorophyll a rate is overall very low. It is surprising in such a slow‐moving canal system enhanced by large amount of nutrients, but it can be explained by the very important TDS rate which keeps down the primary production (contrary to Beira Lake).

Coliforms and E. coli

This parameter indicates a very good bacteriological water quality all over the area. This result is really surprising too because of many waste water inlets in canal system. If further analysis confirms this state, this is a good point.

Synthesis

Finally, with this small dataset and using only the first campaign to assess water quality on the top layer (water sampling location) and without taking TDS parameter when it is the only one to downgrade the station, we can conclude:

‐ Very bad quality : 50% of this network

‐ Bad water quality: 15% of this network

‐ Medium quality: 15% of this network

‐ Good quality: 20% of this network

Table 4.Physico‐chemical water quality synthesis (May 2015)

Sample n° Location Justification for the selection Downgradingparameter Final

Quality*

1 Canal at Kottawa North Act as a control point in the upper catchment TDS, TSS, COD Verybad 2 Canal at Pathiragoda Act as a control point in the upper catchment TDS Medium*3 Parliament lake Water inlet to the Parliament lake TDS Good*

4 Water inlet to Parliament lake To determine the load of pollutants coming to the lake DO, TDS, NH4, PO4 Bad

5 Dammaladeniya meda ela To determine the load of pollutants comes to the lake DO, TDS, NH4 Bad

6 Atunkedeniya meda ela To determine the load of pollutants comes to the lake TDS Good

7 Parliament lake To determine the suitability for recreation, to

assess the impact of variation of water quality to the Parliament

TDS Medium*

8 Kinda Canal To determine the suitability for recreation, to

assess the impact of variation of water quality to the Parliament

TDS, NH4, PO4 Bad

9 Kolonnawa Canal To determine the load of pollutants to the downstream from the tank TDS Good*


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10 Kolonnawa Canal To determine the load of pollutants comes to the marsh TDS, TSS, COD Medium*

11 Kolonnawa Canal To determine the load of pollutants comes to the marsh TDS Good*

12 Kittampahuwa canal To determine the load of pollutants to the downstream from the marsh TDS, COD, NH4, PO4 Verybad

13 Kittampahuwa canal The canal is polluted with the leachate from garbage dump, wash‐offs etc TDS, COD, NH4, PO4 Verybad

14 Dematagoda Canal The canal is polluted with the effluents from Petroleum Corporation

DO, TDS, BOD, COD, NH4, PO4

Verybad

15 Kolonnawa Marsh To determine the load of pollutants to the downstream from the marsh

TDS, TSS, BOD, COD, NH4, PO4

Verybad

16 Serpentine canal Highly polluted canal, highly populated slum area TDS, TSS, BOD, COD, NH4,

PO4 Verybad

17 HeenEla Marsh To determine the load of pollutants comes to the marsh

TDS, TSS, BOD, COD, NH4, PO4

Verybad

18 Kotte Marsh To determine the load of pollutants comes to the marsh TDS, TSS, BOD, COD Verybad

19 Kotte Marsh To determine the load of pollutants to the downstream from the marsh TDS, NH4, PO4 Verybad

20 Kirulapone canal To identify the level of Salinity intrusion TDS, NH4, PO4 Verybad

21 HeenEla To identify the level of Salinity intrusion, Level of pollutants flows into the sea TDS, NH4, PO4 Verybad

22 Dehiwala canal To identify the level of Salinity intrusion, load of pollutants flows into the sea TDS, BOD, COD, NH4, PO4 Verybad

23 Dematagoda Canal Highly populated area, low income community DO, TDS, COD, NH4, PO4 Verybad 24 Kirulapana Canal Highlypopulated area TDS Good*

25 St. Sebastian Canal To identify the trend of water quality changes with the distance, highly polluted canal TDS, COD, NH4, PO4 Verybad

26 St. Sebastian Canal To determine the load of pollutants flows into Kelani River DO, TDS, NH4, PO4 Verybad

27 Redbanaela To determine the load of pollutants flows into the sea

DO, TDS, TSS, BOD, COD, NH4, PO4

Verybad

28 KarandagahamulaKumburaela To determine the quality of the water comes to the lake TDS, BOD, COD, NH4 Medium

29 Thalahena tank To determine the load of pollutants comes to the tank TDS Good*

30 Evarihena tank To determine the load of pollutants to the downstream from the tank TDS Good*

31 Canal passing through the paddy land To identify the pollutant levels, mainly

agrochemicals add into the water ways run through paddy field

TDS Good*

32 Mulleriyawa tank This station represents the general water quality of the tank TDS Medium*

33 Mahawelaela to assess the level of pollutants add into downstream TDS, COD, NH4 Bad

34 Ambataleela To identify the level of pollutants flow into Kelani river TDS, TSS, BOD Bad

35 Norris Canal Pollution level is comparatively high due to the adjacent hospital DO, TDS, COD, PO4 Verybad

* Scoring : European Water Framework Directive


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Figure 10. Water quality assessment – May 2015 (WFD Score)


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Figure 10a. Water quality assessment distribution map according wetland zoning codes– May 2015 (WFD Score)


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4.3. PHYTOPLANKTON COMMUNITY STRUCTURE

Global overview

i. Species richness

The inventories allowed identifying 43 taxa among all stations. Those taxa belong to 8 phytoplanktonic classes:

• Cyanophyceae : 11 taxa, • Xanthophyceae : 2 taxa, • Chlorophyceae : 14 taxa, • Bacillariophyceae : 9 taxa, • Zygnematophyceae : 3 taxa, • Chrysophyceae : 1 taxon, • Euglenophyceae : 2 taxa, • Ulvophyceae : 1 taxon.

The average species richness is of 7.3 taxa per station. It ranges from 2 (on station 2) to 15 taxa (on stations 18 and 21). For stations 1 to 3, there is no specific trend regarding the phytoplankton species richness values, either according to the canal nature or location criteria. However, for stations 36 to 40 which are on lakes, poor species richness has been observed, with 3 to 6 taxa recorded on each station. The main tendencies of taxa population for each site are the following:

4 phytoplankton classes (Cyanophyceae, Chlorophyceae, Bacillariophyceae and Zygnematophyceae) co‐dominate the population for stations 23 and 32, due to the poor species richness (4 taxa, 1 taxa per category).

On stations 8, 13, 14 and 27, 3 classes co‐dominate : Cyanophyceae, Xanthophyceae et Chlorophyceae ;

Cyanophyceae and Chlorophyceae co‐dominate on stations 1, 11, 21, 24 and 28 ; Cyanophyceae and Xanthophyceae co‐dominate on station 2 ; Bacillariophyceae dominate on stations 3 and 20 ; Chlorophyceae dominate on sites 4,7, 9, 16, 17, 18, 19, 26 and 29 ; Cyanophyceae dominate on sites 5, 6, 10, 20, 22, 25, 31, 33, 34, 35, 36, 37, 38, 39 and 40.

ii. Cell densities

Phytoplankton cell densities proportion can fluctuate due to the colonial nature of certain species. Indeed, a colony which consists of several cells will count as one subject, and therefore the cell density will be lower for colonial species.

Cell densities range from 203 cells per liter (station 30) to 3871667 cells per liter for station 36. As for overall trends:


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Bacillariophyceae dominate sites 3 and 30 populations ; Xanthophyceae dominate sites 21 and 32 ; Chlorophyceae dominate the population of 15 sites : 4, 6, 7, 8, 9, 11, 12, 17, 18, 22, 24, 26,

28, 29 and 34 ; Cyanophyceae are greater within the population of 20 stations: 1, 2, 5, 10, 13, 14, 15, 16, 19,

20, 23, 25, 27, 33, 35, 36, 37, 38, 39 and 40.

Phytoplanktonic population composition and blooms

i. Dominant taxa

Table below summarises the proportions of dominating taxa, i.e. taxa which proportions within a population is above 5%. Underlined in yellow are the ones with a proportion from 5 to 10% ; in orange the ones from 10 to 50%, and in red the ones above 50%. Table 5. Dominant taxa in population for stations 1 to 5.

Stations 106‐1 106‐2 106‐3 106‐4 106‐5 106‐6 106‐7 106‐8 106‐9 106‐10 106‐11 106‐12 106‐13 106‐14 106‐15CyanophyceaeChroococcus sp. 14.5Gomphosphaeria sp. 13.7Lyngbya sp. 5.8 6.1 9.2 16.7Microcystis sp.Oscillotoria spp. 57.1 17.5 31.9 48.1 24.2 22.5 52.1 38.3 61.3 50.0Spirulina sp. 43.3XanthophyceaeTribonema sp. 28.6 14.1 23.6 22.2Vaucheria sp. 8.3 7.3 15.9 11.2 26.7 16.1ChlorophyceaeActinastrum spp. 12.5Microspora sp. 26.7 66.7 15.8 33.1 43.9 8.9Monoraphidium sp.Pediastrum spp. 10.0 25.4 21.7 50.1 15.8 21.9 14.2 34.6 55.5 5.0 22.6Planktosphaeria sp.Scenedesmus spp. 8.3 5.3BacillariophyceaeAmphora sp. 6.3Fragilaria sp. 19.0Gyrosigma spMelosira sp. 7.1Navicula sp.Nitzschia spp. 8.0 26.4 16.7ZygnematophyceaeSpirogyra spp. 8.0 16.7Zygnema sp. 10.0 13.7 14.3ChrysophyceaeDinobryon sp. 5.3Unknown Filamentous sp 14.3 14.7 11.2 15.0

Total % dominant species 90.0 100 84.1 100 81.2 98.1 94.7 93.4 78.8 92.6 87.5 100 94.2 100 95.8


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Table 6. Dominant taxa in population for stations 16 to 30.

The population of 21 stations has one taxon which exceeds 50% of the global population. Those stations are the 2, 4, 6, 10, 12, 14, 15, 17, 19, 20, 21, 24, 27, 29, 31, 35, 36, 37, 38, 39 and 40. Fifteen of which are dominated first by Cyanophyceae, second by Clorophyceae. For all those stations the population is unbalanced, with one taxa dominating over the rest of the population. For the other stations, the population is more even, with fewer dominant taxa, and in weaker proportions. The amount of dominant taxa ranges from 1 (station 36) to 7 (stations 7 and 30), with a total proportion comprised between 80 and 100%. This means that the groups of non‐dominant taxa are a small fraction of the population.

Stations 106‐16 106‐17 106‐18 106‐19 106‐20 106‐21 106‐22 106‐23 106‐24 106‐25 106‐26 106‐27 106‐28 106‐29 106‐30CyanophyceaeChroococcus sp. 8.0 5.4 5.4Gomphosphaeria sp.Lyngbya sp. 11.3 6.6Microcystis sp. 9.0 7.6 30.8Oscillotoria spp. 35.8 5.1 60.1 61.3 5.9 16.5 38.2 17.1 34.6 38.0 62.5 50.1 12.3Spirulina sp.XanthophyceaeTribonema sp. 12.3 6.2 52.8 5.5 21.2 23.4 12.5Vaucheria sp. 6.7 14.4 7.7ChlorophyceaeActinastrum spp. 14.9 6.6 11.8Microspora sp. 60.1 20.4 6.6 8.0 33.5 68.3 7.7 14.3Monoraphidium sp. 13.4 5.8Pediastrum spp. 23.9 17.9 26.6 16.4 11.3 26.8 6.5 13.5 32.9 25.0 29.2 35.7 26.1Planktosphaeria sp. 7.7Scenedesmus spp.BacillariophyceaeAmphora sp.Fragilaria sp. 6.4Gyrosigma sp 6.6Melosira sp. 14.7 16.7Navicula sp. 12.3Nitzschia spp.ZygnematophyceaeSpirogyra spp. 12.3Zygnema sp. 5.3 35.3 9.4ChrysophyceaeDinobryon sp.Unknown Filamentous sp 11.9

Total % dominant species 95.5 83.2 78.3 100 97.3 83.5 89.0 100 97.3 83.7 100 100 83.1 100 95.6


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Table 7. Dominant taxa within population of stations 31 to 40.

ii. Blooms

Total cell densities are presented in the Table 8, in which also appears the physico‐chemical quality for each station (with colors, from very good in blue to bad in red). The top cell density was observed on station 36 (South West Beira Lake) with 3871,1 cells/mL. This station was classified as bad according to its chemical quality. The lowest cell density was observed on station 30 (Evarihena Tank), classified as very good quality. The highest densities, within a 145,7 cell/mL gap from the top one, were observed on stations 31, 36, 37, 38, 39 and 40. Station 31 was classified as good chemical quality whereas stations 36 to 40 were ranked from bad to very bad quality. As no tendency can be identified from those observations, it is therefore not accurate to link cell density and chemical quality.

Stations 106‐31 106‐32 106‐33 106‐34 106‐35 106‐36 106‐37 106‐38 106‐39 106‐40CyanophyceaeChroococcus sp. 30.7 93.8 58.6 57.0 34.2 12.7Gomphosphaeria sp. 7.5Lyngbya sp. 8.3 21.3Microcystis sp. 12.5 19.4 6.3 15.4Oscillotoria spp. 19.5 20.8 51.1 5.5Spirulina sp. 53.8 12.5 12.0 29.9 60.3 66.8XanthophyceaeTribonema sp. 46.3 22.4Vaucheria sp. 41.7ChlorophyceaeActinastrum spp.Microspora sp. 21.9 10.5Monoraphidium sp.Pediastrum spp. 36.8Planktosphaeria sp.Scenedesmus spp.BacillariophyceaeAmphora sp.Fragilaria sp.Gyrosigma spMelosira sp.Navicula sp.Nitzschia spp.ZygnematophyceaeSpirogyra spp. 12.2Zygnema sp. 15.8ChrysophyceaeDinobryon sp.Unknown Filamentous sp

Total % dominant species 84.4 100 95.8 85.5 72.3 93.8 97.5 98.7 94.5 94.8


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Table 8. Cell density (cells/mL) and chemical quality classification for each station

In France, specific processes (sanitary regulation) must be triggered as toxic taxon cell density rises above 20000 cells/mL. This number has not been recorded at any stations during the study.

Sample no Location Water quality Density/mL

1 Canal at Kottawa North 15.0

2 Canal at Pathiragoda 0.7

3 Parliament lake 2.1

4 Water inlet to Parliament lake 0.6

5 Dammaladeniya meda ela 7.7

6 Atunkedeniya meda ela 75.6

7 Parliament lake 2.4

8 Kinda Canal 3.8

9 Kolonnawa Canal 53.0



12 Kittampahuwa canal 0.5

13 Kittampahuwa canal 3.0

14 Dematagoda Canal 1.9

15 Kolonnawa Marsh 3.0

16 Serpentine canal 1.7

17 Heen Ela Marsh 6.8

18 Kotte Marsh 13.5

19 Kotte Marsh 0.5

20 Kirulapone canal 7.5

21 Heen Ela 14.1

22 Dehiwala canal 27.3

23 Dematagoda Canal 11.3

24 Kirulapana Canal 12.3

25 St. Sebastian Canal 6.9

26 St. Sebastian Canal 8.6

27 Redbana ela 1.0

28 Karandagahamula Kumbura ela 2.2

29 Thalahena tank 0.9

30 Evarihena tank 0.203

31 Canal passing through the paddy land 145.7

32 Mulleriyawa tank 3.4

33 Mahawela ela 0.5

34 Ambatale ela 3.0

35 Norris Canal 5.9

36 South West Beira lake 3871.7

37 South West Beira lake 1275.0

38 East lake 1358.8

39 East lake 195.8

40 Floating Market 868.3


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Table 9. Cell densities (cells/mL) for the main genders under Cyanophyceae class (*= potentially toxic taxa)

The Cyanophyceae taxa which are the most represented within the populations are Chroococcus, Microcystis et Spirulina. Among the identified taxa, Lyngbya, Microcystis, Oscillatoria et Phormidium are known to be potentially toxic.

The most important density (above 100 cells/ml) have been only been observed on lake locations, for stations 36 to 40. The maximum density is for Chroococcus taxon (non toxic) on station 36: 3633.3 cells/mL.

Stations Chroococcus sp. Lyngbya sp.* Microcystis sp.* Oscillotoria spp.* Phormidium sp.* Spirulina sp.106‐1 0.5 6.5106‐2 0.4106‐3 0.367 0.033106‐4106‐5 1.1 0.444 0.111 2.4106‐6 0.25 36.3106‐7 0.075 0.575106‐8 0.85106‐9106‐10 0.063 3.9106‐11 0.567 0.133106‐12106‐13 0.275 1.2106‐14 1.2106‐15 0.5 1.5106‐16 0.15 0.6106‐17 0.35106‐18 0.5 1.533 1.033106‐19 0.033 0.3106‐20 0.6 0.067 4.6106‐21 0.767 0.533 0.067 0.833106‐22 0.333 0.167 4.5 0.333106‐23 4.3106‐24 0.667 2.1106‐25 0.067 0.133 2.4106‐26 3.3106‐27 0.625106‐28 0.667 0.067106‐29 0.467106‐30 0.025106‐31 44.7 6 78.333106‐32 0.667106‐33 0.04 0.06 0.1 0.06106‐34 0.08 0.08 0.08106‐35 1.25 3 0.25106‐36 3633.3 191.7106‐37 747.5 247.5 27.5 152.5106‐38 775 85 75 406.3106‐39 67 8 118106‐40 110 133.3 580


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Those densities are well below the 20000 cells/mL threshold and only one potentially toxic taxon, Microcystis, exceeds 100 cells/ml on three stations. The densities for the other potentially toxic taxa are lower.

2. Conclusions

Chlorophyll measures have shown that the monitoring sites located on the lakes (stations 36 to 40) have higher and quite significant phytoplankton biomass.

The identification and cells densities measures have not pointed out appalling proportion values nor toxic algae blooms.

However, Cyanophyceae mainly dominate the population of all sites, and especially on 5 in‐lake locations: Beira Lake, East Lake et Floating Market. The cell densities are higher for those stations, without however reaching a 20000 cells/mL (only for potentially toxic taxa) threshold, considered as health hazardous in France.

Those potentially toxic taxa (Lyngbya, Microcystis, Oscillatoria et Phormidium) were identified on most of the sites excepted stations 4, 9 and 12. Blooms have not been observed, or quantified with the phytoplankton population analysis, but need to be monitored especially throughout yearly climatic fluctuation. Indeed, favorable conditions for algae blooms can occur with climatic seasonal variation.

4.4. HISTORICAL DATA Given the small dataset available for this study, we used existing data provided by SLLRDC to have a complementary overview of the watershed.

All the graphs are presented in Appendix 3. to the key lessons are highlighted from the graphs :

pH

Data from SLLRDC monitoring network match with this study dataset. pH ranges from 6 to 8 but can reach 5 to 10. Since beginning of 2013, the general trend is to shift from slightly acid to slightly basic all over the network. Floating market shows the greatest gap between slightly acid to very basic.

Conductivity

Data from SLLRDC monitoring network matches with study dataset. Conductivity remains stable apart from 4 stations:

‐ St 2: End point of St. Sebestian Canal (Outlet to Beira lake)

‐ St 19: Station No.02 :Diyawanna Oya , Battaramulla south Pelawatte.

‐ St 24: Beira Lake just behind Pettah private bus stand.

‐ St 25: St.Sebestian Canal about 200m downstream from location no.02


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For these four stations, we notice a conductivity increasing since beginning of 2012. Three of them are linked with Beira lake outlet. The last one is an inlet in Parliament Lake but nearest stations (St 18 and 20) do not follow the same trend.

Temperature

Data from SLLRDC monitoring network matches with this study dataset. The mean temperature range from 27° to 32° and min/max form 26° to 34°. Only two stations present a slightly different trend: st 24 and 25 show a temperature increase (about 2 or 3 degrees). Once again it relates to Beira lake outlet in St. Sebastian Canal.

Dissolved oxygen

Data from SLLRDC monitoring network do not match with this study dataset apart for station 3 (Bridge on Kotte north canal), station 20 (Diyawanna Oya ,Battaramulla north Diyawanna Oya outlet) and station 21 (Kelaniya river close to new bridge upper stream to confluence of St.Sebestian canal). These ones range between 6 and 7 mg/l. The rest of the network presents low or very low (mean 3 mg/l) and very erratic dissolved oxygen rate. If the sampling time can explain a part from this trend, the situation was mainly under‐saturated from 2004 to end of 2012. Since beginning of 2013, the trend is increasing DO but more erratic.

During May 2015, water samplings have been led by both SLLRDC and University team on 3 stations (St. 3/9/20). For each of them, SLLRDC team found about 4.80 mg/l of oxygen whereas University team record 7.3 mg/l. The difference cannot be only explains by the sampling time, but several explanations such as the equipment used, time and day of probe calibration in relation with the atmospheric pressure variation, professional training and exact position of the probe in the water (surface, mid‐depth, bottom) can be advanced.

Yet what are the implications of such differences in dataset? It is difficult to determine which team is nearest to field reality however, if SLLRDC team was correct conditions for aquatic life would be very difficult during the ten year (and the study did not reveal this to be the case). On the other hand, very high ammonia rates could be explained by a undersaturated environment. This issue really needs further investigations to direct certain part of wetland management plan.

Salinity

Data from SLLRDC monitoring network matches with this study dataset. In the SSLRDC network we can distinguish three groups of stations:

‐ Mainly freshwater : average salinity lower than 0.015% (0.15ppt) and never over 0.1%

‐ Seasonal brackish water: average salinity between 0.015 and 0.5% fluctuating all along the year in particular during dry season.

‐ Brackish water: more than 0.5% and occasionally lower than 0.015%.


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Table 10. Salinity groups on historical network

There is no real trend but in some stations (St 12/13/14) we can find a slight salinity increase since the beginning of 2012.

Turbidity

Turbidity has not been measured during these campaigns so there is no correlation between the two data sets. However, TDS and TSS are linked to turbidity, that is why we can confirm that most of the canal system presents a medium or bad quality regarding turbidity.

Historical data are quite interesting for two reasons:

‐ From the monitoring start to early 2009, turbidity levels are predominantly lower than 30 NTU (average: 15 NTU). This is indicative of good or very good quality over the network.

‐ From the beginning 2010 to the present day and particularly to mid‐2012, a harsh turbidity increase reaching an average of 55 NTU but very variable. Since that time, turbidity fluctuates and is very high, having a strong, constant and damaging influence on aquatic life.

BOD

Data from SLLRDC monitoring network match with this study dataset. BOD fluctuates as the turbidity along this period (after and before beginning of 2010) but it is generally lower since beginning of 2014.

Two groups of station can be discriminate:

Group St N° Location

Mainly Freshwater

02 End point of St. Sebestian Canal (Outlet to Beira lake). 03 Bridge on Kotte north canal 04 Railway bridge on Torrington canal. 08 Bolgoda canal down stream of Kaudana Attidiya scheme. 13 Mahawattecanal , Kotte road bridge , Rajagiriya. 18 Station No.01 :Diyawanna Oya , Kimbulawala Madiwela. 19 Station No.02 :Diyawanna Oya , Battaramulla south Pelawatte. 20 Station No.03 :Diyawanna Oya , Battaramulla north Diyawanna Oya outlet. 24 Beira lake just behind Pettah private bus stand. 25 St. Sebestian Canal about 200m downstream from location no.02

Seasonal brackish water

09 Weras Ganga on Borupana road ferry crossing 11 St. Sebestian Canal bridge near Ingurukade junction. 12 Dematagoda canal , Kolonnawa bridge near the Petroleum Corporation. 14 Kirillapona canal , Near Open Unversity Bridge 21 Kelany river close to new bridge upper stream to confluence of St.Sebestian canal. 22 St. Sebestian Canal north lock gate. 23 Kelany river close to Victoria bridge downstream confluence of St.Sebestian canal. 26 St. Sebestian Canal (north) outfall to Kelani river. 27 Bloemendel , Branch earthen drain coming through garbage pile. 28 Bloemendel , Canal at the confluence of earthern drain of 27

Brackish water 05 Galle road bridge on Wellawatte canal. 06 Galle road bridge on Dehiwala canal.


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Table 11. BOD groups on historical network

Group St N° Location Low to medium BOD

2 End point of St. Sebestian Canal (Outlet to Beira lake) 3 Bridge on Kotte north canal. 8 Bolgoda canal down stream of Kaudana Attidiya scheme. 14 Kirillapona canal , Near Open Unversity Bridge 18 Station No.01 :Diyawanna Oya , Kimbulawala Madiwela. 19 Station No.02 :Diyawanna Oya , Battaramulla south Pelawatte. 20 Station No.03 :DiyawannaOya , Battaramulla north Diyawanna Oya outlet. 21 Kelany river close to new bridge upper stream to confluence of St.Sebestian canal. 23 Kelany river close to Victoria bridge down stream confluence of St.Sebestian canal.

High BOD and erratic variation

4 Railway bridge on Torrington canal. 5 Galle road bridge on Wellawatte canal. 6 Galle road bridge on Dehiwala canal. 9 Weras Ganga on Borupana road ferry crossing 11 St. Sebestian Canal bridge near Ingurukade junction. 12 Dematagoda canal ,Kolonnawa bridge near the Petroleum Corporation. 13 Mahawattecanal , Kotte road bridge , Rajagiriya. 22 St. Sebestian Canal north lock gate. 24 Beira lake just behind Pettah private bus stand. 25 St. Sebestian Canal about 200m downstream from location no.02 26 St. Sebestian Canal (north) outfall to Kelany river. 27 Bloemendel , Branch earthen drain coming through garbage pile. 28 Bloemendel , Canal at the confluence of earthern drain of 27


COD

Data from SLLRDC monitoring network matches this study dataset. COD fluctuates as the turbidity and BOD along this period (after and before beginning of 2010) but it is generally lower since beginning of 2014.

Two groups of stations can be discriminated :


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Table 12. Salinity group on historical network

Group St N° Location Lowto medium COD

2 End point of St. Sebestian Canal (Outlet to Beira lake) 3 Bridge on Kotte north canal. 14 Kirillapona canal , Near Open Unversity Bridge 18 Station No.01 :Diyawanna Oya , Kimbulawala Madiwela. 19 Station No.02 :Diyawanna Oya , Battaramulla south Pelawatte. 20 Station No.03 :Diyawanna Oya , Battaramulla north Diyawanna Oya outlet. 21 Kelany river close to new bridge upper stream to confluence of St.Sebestian canal. 23 Kelany river close to Victoria bridge downstream confluence of St.Sebestian canal.

High COD and erratic variation

4 Railway bridge on Torrington canal. 5 Galle road bridge on Wellawatte canal. 6 Galle road bridge on Dehiwala canal. 8 Bolgoda canal down stream of Kaudana Attidiya scheme. 9 Weras Ganga on Borupana road ferry crossing 11 St. Sebestian Canal bridge near Ingurukade junction. 12 Dematagoda canal ,Kolonnawa bridge near the Petroleum Corporation. 13 Mahawatte canal , Kotte road bridge , Rajagiriya. 22 St. Sebestian Canal north lock gate. 24 Beira lake just behind Pettah private bus stand. 25 St. Sebestian Canal about 200m downstream from location no.02 26 St. Sebestian Canal (north) outfall to Kelany river. 27 Bloemendel , Branch earthen drain coming through garbage pile. 28 Bloemendel , Canal at the confluence of earthern drain of 27


Ammonia

Data from SLLRDC monitoring network matches this study dataset. Ammonia fluctuates as the turbidity, BOD and COD along this period with a little lag (around the beginning of 2011) but it is generally lower since end of 2014.

Two groups of stations can be discriminated: the same as COD parameter. As stated previously, ammonia rates are really worrying because their concentration is higher than 2 mg/l and can be toxic for aquatic life. This is the case for 64% of the stations.

Nitrate

Data from SLLRDC monitoring network matches this study dataset. There is a general trend to slightly increase since the beginning of 2012, but Nitrate rate remains very low all over the network.

Phosphate

Data from SLLRDC monitoring network matches this study dataset. However there are no real discernible trends. However, for a few stations (coastal St 4/5/6 and on Kelany River St 21/23/26) and a fast increase has been recorded since the beginning of 2014, correlated with the salinity increase.

Two groups of stations can be discriminate:


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Table 13. Phosphate groups on historical network

Group St N° Location Low or medium PO4

2 End point of St. Sebestian Canal (Outlet to Beira lake) 3 Bridge on Kotte north canal. 5 Galle road bridge on Wellawatte canal. 8 Bolgoda canal down stream of Kaudana Attidiya scheme. 9 Weras Ganga on Borupana road ferry crossing 14 Kirillapona canal , Near Open Unversity Bridge 18 Station No.01 :Diyawanna Oya , Kimbulawala Madiwela. 19 Station No.02 :Diyawanna Oya , Battaramulla south Pelawatte. 20 Station No.03 :Diyawanna Oya , Battaramulla north Diyawanna Oya outlet. 21 Kelany river close to new bridge upper stream to confluence of St.Sebestian canal. 23 Kelany river close to Victoria bridge down stream confluence of St.Sebestian canal.

High PO4 4 Railway bridge on Torrington canal. 6 Galle road bridge on Dehiwala canal. 11 St. Sebestian Canal bridge near Ingurukade junction. 12 Dematagoda canal ,Kolonnawa bridge near the Petroleum Corporation. 13 Mahawatte canal , Kotte road bridge , Rajagiriya. 22 St. Sebestian Canal north lock gate. 24 Beira lake just behind Pettah private bus stand. 25 St. Sebestian Canal about 200m downstream from location no.02 26 St. Sebestian Canal (north) outfall to Kelany river. 27 Bloemendel , Branch earthen drain coming through garbage pile. 28 Bloemendel , Canal at the confluence of earthern drain of 27


4.5. WATER QUALITY SYNTHESIS Following the previous assessment, we can conclude:

‐ Historical network shows a bad or very bad quality for 64% of the stations, which is in accordance with assessment led for this study.

‐ The pollution increase is growing faster from 2010 to now. Eventhough as a result the actual water quality is poor, the anthropogenic pollution sources can be easily identified and addressed with an efficient management plan. Over a larger time‐scale, 5‐years pollution can even been considered as a short time pollution, with a natural ecological potential still remaining on the watershed.

‐ Most parameters which are exhibiting degradation are due to domestic waste water. These include :


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o Turbidity: sharp deterioration since 2010 ;

o BOD: deterioration since 2010;

o COD: deterioration since 2010;

o Ammonia: partially deterioration since 2011;

o Phosphate: high deterioration in 2014.

‐ End of 2014 seems to be better for all parameters.

‐ Parliament Lake and Kelany river remains in a good or medium quality only regarding to these parameters. However, degradation has been record since 2010 too.

‐ The dissolved oxygen values seem to be very low and do not correlate with University sampling results. Other parameters are substantially equivalent. It does raise questions about SLLRDC laboratory reliability.


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5 BEIRA LAKE

5.1. WATER Fifteen stations on the three water bodies which comprise Beira Lake have been sampled for physicochemical in situ parameters during the four months campaign from May to August. Due to time constraints, this campaign did not include the wet season. Table 15 shows results.

This program has provided many lessons about lake functioning:

Depth

The depth is roughly the same in all stations during these 4 months. The water level in the lakes is managed by a dam before discharging in the sea or into the canal. During medium or high water level this downstream control kept the same depth for all water bodies. It also means that the sediments are never exposed and drying up.

East Beira Lake is the deepest with 1.50 m to 3.75m depth. Hence, this lake is not a flat‐bottom and shows a variable bathymetry.

On the other hand, South west Beira Lake (1.45 m depth) and Floating market (around 2 meter depth) are most probably uniform depth.

pH

Contrary to the canal system, the lakes show a very alkaline pH due to primary production and continuous bloom.

During the sampling period, pH gets more alkaline over the whole water column. The end of August shows maximum basic pH over the top locations. pH reaches 10.5 value meaning that water cannot support vertebrate aquatic life (potentially causing fish kills).

However pH becomes more neutral from the top to the bottom of water column. pH decreases from 10 to 8 which provides conditions suitable for aquatic life throughout this period.

pH never become acid (less than 7). This is a very interesting point insofar as the water in canal system is mostly acid. In this way, aquatic life would be very different in these ecosystems (without taking account lotic or lentic characteristics). It is also interesting because a neutrophic lake can present acidification near the bottom layer (sometimes pH 4) associated with hydrogen sulfide release producing conditions unsuitable for fish. The lakes do not work this way but further data are required to explain why.

Conductivity

Conductivity remained fairly stable (between 250 and 300 µS/cm)in each location during the three first three campaigns. We can notice a little increase from May to August (correlated to temperature). During the last campaign, conductivity increased slightly along depth in East Lake (the deeper). It could be the result of increasing of metal solubility, Fe and Mn, but cannot be confirmed.

All values allow aquatic life.


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Temperature

The full temperature ranges from 29.3 to 35.4°C. Climate and shallow depth explain such range. Average temperature is about 31°C and August is the warmest month. The temperature decreases rapidly, 2 or 3°C, from the surface to 60‐100 cm in‐depth. It remains stable after to the bottom. So we can notice a real thermocline but the other parameters do not show such break from top to bottom layer. This thermocline represents the light penetration limit due to algae bloom. Below the thermocline and photosynthesis is extremely limited.

Dissolved Oxygen

DO generally follows the same trend than temperature in August. DO is strongly correlated to primary productivity (best in August) and likewise the thermocline, we can see an oxycline exclusively in August. Below 1 meter depth, DO is stable at 7 mg/l during May, June and July.

The second point concerns the decrease during August 13 to 6 mg/l. As just exposed, there is an existing correlation but it means that bottom layers are less oxygenated and stressful for aquatic life. Once again, shallow depth allows preserving a sufficient level of oxygen but it would be more stressful during dry season.

Salinity

Salinity is very stable (around 0.12 g/l) overtime and along the water column. The values do not translate a proper brackish water but a slightly brackish environment during the sampling period.

The only point to notice is the upwelling of the salt water wedge in August only below 2 meters depth (rare). It should be interesting to follow the trend in underground water during the same period. Indeed, salinity increase in the bottom layer can interfere with ion balance and enlighten the fact that the acidification and metal release seems not to be linked to trophic status (hypertrophic lakes).


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Table 14. Physico‐chemical in situ parameters on water ‐ Beira Lake stations (May to August 2015)

Lake NameSample No

Latitude Longitude Depth C1 C2 C3 C4 C1 C2 C3 C4 C1 C2 C3 C4 C1 C2 C3 C4 C1 C2 C3 C4 C1 C2 C3 C4

0 8.1 8.6 9.8 9.6 230.7 254.8 307.8 302.3 30.2 33.2 33.9 34.3 7.05 7.1 6.4 5.49 0.10 0.11 0.13 0.10 106.5 150 150 142.830 9.2 9.0 272.1 305.1 32.6 32.2 6.4 11.8 0.11 0.10 130 143.860 7.1 8.4 8.0 8.0 272.9 254.8 290.7 325.8 29.3 32.5 31.3 30.8 7.14 7.1 6.2 6 0.12 0.11 0.13 0.10 127.6 150 150 154.290 7.7 7.8 298.1 327.5 31.3 30.7 6.4 6.36 0.13 0.10 150 155120 6.8 7.1 6.9 7.4 270 255.3 303.4 343 29.3 31.1 31.7 31.1 7.18 7.4 6.7 5.36 0.12 0.11 0.13 0.10 126.2 170 180 162.8150 7.9 303.5 31 5.94 0.10 1430 8.1 8.1 10.0 9.3 228.6 223.2 275.1 299.1 30.2 30.2 33.4 32.6 6.87 6.9 6.4 11.38 0.10 0.10 0.11 0.10 105.4 105 140 140.830 9.3 297.9 32.5 9.5 0.10 140.260 9.1 299.6 32 8.88 0.10 14190 8.7 307.2 31.1 7.54 0.10 144.9120 7.3 7.3 8.9 7.9 264.5 253.4 288.3 320.7 29.4 29.4 31.5 30.6 7.01 7.0 6.5 7.41 0.12 0.12 0.12 0.10 123.4 123 140 151.6150 7.8 320 30.5 6.93 0.10 151.3180 7.8 323.6 30.2 6.48 0.10 151210 7.9 354.6 30.2 5.52 0.20 168.6250 6.9 7.5 8.8 274.8 274.8 288.6 29.3 29.3 32.1 7.24 7.2 6.6 0.12 0.12 0.12 128.6 128 1500 9.3 9.3 10.0 229.4 242.1 245 31 31 32.9 6.77 6.8 13.81 0.10 0.10 0.10 105.8 105 113.630 9.7 248.1 32.2 12.2 0.10 115.260 9.4 262.4 30.8 9.8 0.10 122.4120 8.7 8.7 9.0 230 230 318.5 30.1 30.1 30.7 7.08 7.1 7.4 0.10 0.10 0.10 106.1 106 150.5190 9.0 341.8 30.8 6.24 0.10 163.40 9.5 9.5 9.5 232.8 213.4 300.8 31.3 31.3 31.5 6.81 6.8 12.77 0.10 0.10 0.10 107.5 110 141.690 8.0 323.2 30.4 6.72 0.10 152.9170 8.1 8.0 8.4 248.1 248.1 319.8 30.1 30.1 29.9 7.1 7.1 5.57 0.11 0.11 0.10 115.2 115 151.20 9.8 8.6 9.6 9.9 237 277.2 274.6 316.2 31.6 32.2 33.3 32.7 6.74 7.4 6.6 13.46 0.10 0.12 0.11 0.10 109.6 120 140 149.430 9.6 9.8 274.5 307.9 33.3 32.7 6.6 10.82 0.11 0.10 140 145.250 9.1 8.5 229 270 30.9 30.1 6.81 7.4 0.10 0.12 105.6 12060 9.0 9.3 279.4 301.8 32.4 31.4 6.6 9 0.12 0.10 140 142.290 8.3 9.0 285.5 308.4 31.1 31.1 6.6 8.4 0.12 0.10 140 145.5100 9.1 7.1 230.3 250.4 31 31.6 6.98 7.5 0.10 0.11 106.3 120120 8.3 8.7 285 312.2 31.1 30.7 6.6 7.87 0.12 0.10 140 147.4150 8.1 7.6 8.2 8.4 243.9 264.3 288.4 316.8 30.1 30.9 30.8 30.7 7.24 7.6 6.6 7.54 0.11 0.11 0.13 0.10 113.1 120 140 149.7180 7.7 8.2 291.4 321 30.4 30.9 6.6 7.13 0.13 0.10 150 151.8200 8.0 7.9 245.4 268.4 30 30.7 7.08 7.6 0.11 0.12 113.8 120210 7.5 8.2 297.1 325.9 30.4 30.9 6.6 7.12 0.13 0.10 150 154.2240 7.5 8.0 297.8 333.1 31.2 30.9 6.7 7.15 0.13 0.10 150 157.9250 7.4 7.6 243.7 268.9 29.4 30.1 7.11 7.7 0.11 0.12 113.0 120270 7.4 7.9 306.4 339.4 30.3 30.9 6.6 7.17 0.13 0.10 150 161300 7.3 7.7 7.3 7.9 253.4 271 313.4 348.1 29.6 31.1 30.4 30.8 7.14 7.7 6.7 7.14 0.11 0.12 0.14 0.20 117.9 120 160 165.4330 7.3 7.9 313 353.6 30.8 30.8 6.8 7.17 0.14 0.20 160 168.1375 7.3 8.2 7.3 7.8 238.1 271.2 313 369.9 29.8 31 31.3 30.8 7.07 7.6 6.8 7.18 0.11 0.12 0.13 0.20 110.2 130 160 176.30 8.5 8.5 9.9 229 230 301.8 31 30.7 31.4 6.74 6.7 7.55 0.10 0.10 0.10 105.6 105 142.2

265 8.2 8.1 9.8 253.4 253.4 308.4 29.4 30.1 31.1 7.11 7.1 5.33 0.11 0.11 0.10 117.9 120 145.50 6.9 7.0 9.2 268.7 268.7 303.7 29.8 31.1 29 7.02 7.0 13 0.12 0.12 0.10 125.5 125 143.1

Bot ? 6.8 7.0 8.8 303.7 303.7 335.9 29.4 31 30.4 7.17 7.2 7.47 0.14 0.14 0.10 143.1 140 159.30 9.7 9.9 10.2 10.4 219.4 285.6 332.6 456.6 30.6 33.5 33.3 35.4 6.9 6.9 6.1 9.16 0.10 0.12 0.14 0.20 100.8 130 140 219.870 9.4 9.2 276.6 354.6 32.8 32.9 6.3 8.89 0.12 0.10 140 168.6145 7.1 8.3 8.3 8.8 262.9 286.1 277.6 300.7 30 31.7 33.3 32.9 7.13 7.2 6.5 8.4 0.12 0.12 0.12 0.10 122.6 130 140 141.60 8.8 9.1 9.5 8.4 303.1 265.9 262.8 301 30.3 32.6 32.4 31.5 6.8 7.1 6.4 7.55 0.13 0.11 0.11 0.10 142.8 130 130 141.770 7.8 7.7 268.6 315.3 31.5 31.1 6.5 5.33 0.12 0.10 130 148.9145 6.9 7.4 7.2 8.0 277.8 302.1 283.9 311.7 30.1 30.8 31.2 30.4 7.11 7.3 6.7 5.77 0.12 0.13 0.12 0.10 130.1 140 160 147.10 9.5 9.5 9.2 216.9 216.9 303.7 30.5 30.5 29 7.28 7.3 10.85 0.10 0.10 0.10 99.5 100 143.1

145 7.5 7.5 7.5 232.2 232.2 335.9 30.2 30.6 30.4 7.06 7.1 8.26 0.10 0.10 0.10 107.2 110 159.30 9.8 9.8 10.4 232.1 232.1 466.1 31.1 33.5 32.1 6.86 6.9 13 0.10 0.10 0.20 107.2 110 224.6

145 7.7 7.7 8.4 234.8 234.8 305.1 30 31.7 31.8 7.13 7.1 7.47 0.10 0.10 0.10 108.5 110 143.80 9.8 9.8 9.3 228.7 228.7 295.7 31.1 32.6 32.2 6.88 6.9 10.23 0.10 0.10 0.10 105.5 105 139.1

145 7.7 7.7 9.1 226.7 226.7 299.3 30.3 30.1 32.2 7.1 7.1 10.12 0.10 0.10 0.10 104.5 105 140.90 8.1 8.1 8.4 210.8 210.8 231.7 31.1 31.1 31.2 6.87 6.9 8.54 0.09 0.09 0.10 96.5 100 107

185 8.0 8.0 7.9 228.4 237 265.1 30.8 31 30.9 7.45 7.0 7.54 0.10 0.10 0.10 105.3 105 123.70 8.1 7.3 9.3 10.5 230.20 346.4 323.5 255.5 30.1 30.5 32.7 32.1 7.05 7.4 6.5 10.2 0.10 0.15 0.14 0.10 106.2 170 150 118.9

205 7.6 7.3 7.9 8.3 248.40 347.7 339.4 260.1 29.8 30.6 32.8 31.9 7.18 7.4 6.7 9.16 0.11 0.15 0.14 0.10 115.4 170 230 121.20 8.0 8.0 9.6 215.8 215.9 231.1 31.3 31.4 31.4 6.88 7.1 8.47 0.09 0.09 0.10 99.0 100 106.7

1.9 7.8 7.9 9.3 224.9 213.8 247.9 31.1 31.2 30.8 7.15 7.2 7.23 0.10 0.97 0.10 103.6 100 115.1Mean 8.1 8.1 8.4 8.8 243.4 256.0 293.4 312.8 30.3 31.1 31.9 31.3 7.0 7.2 6.5 8.3 0.11 0.13 0.12 0.11 112.9 122.0 149.3 147.7Med 8.0 8.0 8.3 8.8 233.8 254.1 288.6 308.4 30.2 31.0 31.5 31.1 7.1 7.1 6.6 7.5 0.10 0.11 0.13 0.10 108.0 120.0 150.0 145.5SD 0.9 0.8 1.0 0.8 22.6 32.8 19.2 41.9 0.7 1.0 1.1 1.1 0.2 0.3 0.2 2.3 0.01 0.14 0.01 0.03 11.3 19.5 18.9 21.0Max 9.8 9.9 10.2 10.5 303.7 347.7 339.4 466.1 31.6 33.5 33.9 35.4 7.5 7.7 6.8 13.8 0.14 0.97 0.14 0.20 143.1 170.0 230.0 224.6Min 6.8 7.0 6.9 7.4 210.8 210.8 262.8 231.1 29.3 29.3 30.3 29.0 6.7 6.7 6.1 5.3 0.09 0.09 0.11 0.10 96.5 100.0 130.0 106.7

East Beira lake

*0 = 0 layer in the LakeMid = Middle layer in the LakeBot = Botem layer in the Lake

6° 55.979'N 79° 51.275'E

6° 55.957'N 79° 51.339'E

6° 55.932'N 79° 51.419'EL 3

Floating market

South West Beira lake

L 1

L 2 (40)

79° 51.211'EL 4

L 5 6° 55.116'N 79° 51.211'E

6° 55.035'N 79° 51.130'E

6° 55.035'N

Conecting

L 3

L 3

L 1 (36)

L 2 (37)

L 6

L 1 (38)

L 5 (39)

6° 55.828'N

6° 55.828'N

6° 55.438'N

L 4

L 2

79° 51.029'E

79° 51.289'E

6° 55.828'N 79° 51.159'E

6° 54.964'N

6° 55.071'N

79° 51.301'E

79° 51.024'E

DO (ppm)

79° 51.551'E

6° 55.568'N 79° 51.420'E

6° 55.471'N 79° 50.808'E

Salinity (ppt) TDS (mg/L)

6° 55.698'N 79° 51.290'E

pH EC (µS/cm) Temp. ( C° )


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Concerning chemical values (assessed in laboratory), we can notice :

TSS

Values are medium to bad but not really worrying if we considered the algae bloom.

BOD and COD

These two parameters show a really poor water quality in particular for the COD which is very poor in the 3 parts of the lake.

N (ammonia and nitrate)

This major nutrient is found at a really low level. The major pollution source is urban, that is why the most of nitrogen input is directly consumed by primary production (algae). According to that, dissolved nitrogen is very low. This nutrient is apparently the “limiting factor” to algae development. It means that if we monitor increase of N input we can monitor bloom increasing. Actually the algae production is based on the capacity of sediment to release the nitrogen stock in an assimilable form to algae. In the other hand, dead algae drop to the bottom of the lake to be decayed by bacterian compartment, increasing nitrogen stock in the sediment and water in sediment.

P (phosphate)

This second major nutrient, contrary to nitrogen, is found at a high level with a relatively good bioavailability. The P input is higher than algae can consumed for their growth, so the excess remains dissolved. This phenomenon is typical for city lakes1

Chlorophyll a

It is one of the ways to quantify primary production. This value confirms the very high level of algae. This permanent bloom reflects the actual imbalance of this lake functioning. The lakes remain in a hypertrophic status.

Coliforms and E. coli

In contrast, microbiological contamination seems very low in such a case of urban pollution. These values really need to be confirmed during another sampling campaign, but in that case, it shows the success of the waste water collection all around the 3 parts of the lake.

In general: there are no significant differences between the 3 lakes. However, we must be careful of station 36, in the South West Beira Lake which showed the worst values for the main parameters. This part of Beira lake has already been restored during a first management plan but it seems that this action plan has not succeeded in dealing with all the compartments.

1Talita Silva, Bruno Lemaire, Brigitte Vinçon‐Leite. Suivi du phytoplacton dans les lacs urbains à l’aide d’une bouée instrumentée : le cas du lac d’Enghien les Bains. Daniel Thevenot. 22èmes Journées Scientifiques de l'Environnement ‐ Reconquête des environnements urbains: les défis du 21ème siècle, Feb 2011, Créteil, France. JSE‐2011 (9), 2011, JournéesScientifiques de l'Environnement


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Table 15. Physico‐chemical parameters on water ‐ Beira Lake stations

Parameters

Locations Floating Market South West Beira lake East lake

40 36 37 38 39 Total Suspended Solids 82 102 73 44 63 BOD 18 20 10 16 12 COD 114 130 72 111 78 Free Ammonia as N <0.04 <0.04 3.48 <0.04 <0.04 Nitrate as N <0.1 0.1 <0.1 0.2 0.1 Total phosphate 0.66 1.3 0.83 0.7 0.67 Chlorophyll a(mg/l) 0.487 0.148 0.578 0.368 0.530 Coliforms 23 8 23 5 23 E.coli 13 8 13 2 13


5.2. SEDIMENT WATER This compartment is currently assessed based on the French lake diagnosis (IRSTEA2, 2003). It seems to be the first time that this has been done for Beira Lake (e.g. bibliography Interim report 1). However it represents an interface between water column and sediment and gives more information about lake functioning. Of course this initial assessment cannot deliver precise answers but it can open a new way of comprehending the Beira lake issues.

Firstly all analysis led during this first campaign presents a high risk regarding water pollution according to EU WFD. Apart from nitrate, under standards, which can be explained by chemical cycle of nitrogen in sediment compartment, ammonia, nitrite (very toxic) and total nitrogen contents are really high. South West Beira Lake and East Beira Lake are extremely similar in term of nutrient level (including different forms of Phosphorus).

The heavy input of nutrients by different outlets during many decades has led to heavy primary productivity support by new inputs and from within the sediment water stock. This compartment acts like bank, helped by relative shallow depth, catching degradation product (nutrients) in case of heavy production and releasing nutrients to maintain production.

In temperate areas, temperature and low levels of sunlight in lakes in the winter can stop this cycle, but in tropical areas there is a permanent primary productivity (temperature and sunlight allow this functioning) and this can only be stop by decreasing nutrient inputs.

Iron and manganese concentrations are also very high but are not a pollution index. Iron and manganese could be natural markers of geochemical backgrounds. However, South West Beira and East Beira lake are, once again, very high but similar. By contrast the Floating market water show very high level (five to ten times other content). The last station is clearly polluted.

2Rapid lake diagnosis


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Table 16. Physico‐chemical parameters on sediment water ‐ Beira Lake stations

Parameters (mg/L) Locations

Floating market South West Beira East Beira Free Ammonia. as N 19.4 35.3 36.2 Nitrate (as NO3) <0.4 <0.4 4.1 Nitrite (as NO2) 7.9 13.8 11.5 Total Nitrogen (as N) 32 61 48 Total Phosporus. as P <0.07 8.4 Total phosphate (as PO4) 201 Aluminium (as Al) 493 92.5 41 Iron (as Fe) 545 69 53.5 Manganese (as Mn) 4.36 0.75 0.59


5.3. SEDIMENT The sediment analysis shows a relatively good content according to EU WFD standards. Nutrient and organic carbon are quite low in opposition with heavy primary productivity and trophic status (hypertrophic). Dredging activities in South West Beira Lake and the Floating Market could explain such difference between observed and forecasted levels. However, East Beira lake sediment content is really unexpected.

Similarly, chemical samples do not show any pesticides or PAH contamination. If agriculture or industry are clearly not the major pollutant activities, domestic and road traffic pollutants contribute to water contamination. In this case, the absence of PAH seems really paradoxical, but if it is confirmed, it should be a very interesting and a reason to hope for managing a part of Beira lake issues.

Nevertheless, heavy metal concentration shows important contamination in particular regarding zinc, lead and to a lesser extent mercury in East Beira Lake. All these heavy metals are both generated by industrial or domestic activities and are frequently found in old urban lake due to, among other things, waste water facilities (old pipe).

This last point also demonstrates the importance of dredging sediments for every watershed in order to restore and improve ecosystems functioning.


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Table 17. Physico‐chemical parameters on sediment ‐ Beira Lake stations

Parameters Locations

Floating market South West Beira East Beira

Organic carbon(%) 2.5 2.9 1.7Total Nitrogen(as N)(%) 0.7 0.6 0.4

Phosphorus soluble in Sodium Hydrogen Carbonate Solution(%) 0.4 0.4 0.5Zinc(as Zn)(mg/kg) 623 654 635.5Copper(as Cu)(mg/kg) 79 111 108.1Arsenic(as As)(mg/kg) 8.7 11.8 5.7Mercury(as Hg)(mg/kg) 0.32 0.55 1.1Cadmium(as Cd)(mg/kg) 0.99 2.1 Chromium(as Cr)(mg/kg) 34 51 96.5Lead(as Pb)(mg/kg) 169 180 118.4Nickel(as Ni)(mg/kg) 21 23 41.6Iron(as Fe)(%) 2.44 3.7 4.27Manganese(as Mn)(mg/kg) 273 227 240 PolynuclearAromaticHydrocarbons Acenapthene BDL** BDL BDL Dibenz(a.h) anthracene BDL BDL BDL Fluoranthene BDL BDL BDL Fluorene BDL BDL BDL Indeno(1.2.3‐cd) pyrene BDL BDL BDL Naphthalene BDL BDL BDL Phenanthrene BDL BDL BDL Pyrene BDL BDL BDL Acenaphthylene BDL BDL BDL Anthracene BDL BDL BDL Benzo (a) anthracene BDL BDL BDL Benzo (b) fluoranthene BDL BDL BDL Benzo (k) Fluoranthene BDL BDL BDL Benzo (g.h,i) perylene BDL BDL BDL Benzo (a) pyrene BDL BDL BDL Chrysene BDL BDL BDL OrganoChlorine Pesticides Alpha BHC BDL BDL BDL P,P‐DDE BDL BDL BDL Alpha ‐ Endosulfan BDL BDL BDL Beta Endosulphan BDL BDL BDL EndosulphanSulphate BDL BDL BDL Endrin BDL BDL BDL Endrinaldehyde BDL BDL BDL EndrinKetone BDL BDL BDL Heptachlor BDL BDL BDL Heptachlorepoxide BDL BDL BDL Hexachlorobenzene BDL BDL BDL Beta BHC BDL BDL BDL 2,4‐D BDL BDL BDL Butachlor BDL BDL BDL Isoroturon BDL BDL BDL Alachlor BDL BDL BDL


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Methoxychlor BDL BDL BDL Aldrin BDL BDL BDL Dieldrin BDL BDL BDL Gamma BHC (Lindane) BDL BDL BDL Delta BHc BDL BDL BDL O, P‐ DDT BDL BDL BDL P,P‐DDT BDL BDL BDL O,P‐DDD BDL BDL BDL P,P‐DDD BDL BDL BDL O,P‐DDE BDL BDL BDL OrganoPhosphorus Pesticides Azinphos‐methyl BDL BDL BDL Malathion BDL BDL BDL Mevinphos BDL BDL BDL Monocrotophos BDL BDL BDL Parathionethyl BDL BDL BDL Parathionmethyl BDL BDL BDL Phorate BDL BDL BDL Phosmet BDL BDL BDL Phosphamidon BDL BDL BDL Atrazine BDL BDL BDL Trichlorofon BDL BDL BDL Chlorofenvinfos BDL BDL BDL Simazine BDL BDL BDL Chloropyrifos BDL BDL BDL Diazinon BDL BDL BDL Dichlorvos BDL BDL BDL Dimethoate BDL BDL BDL Fenitrothion BDL BDL BDL Fonophos BDL BDL BDL Fenthion BDL BDL BDL PolychlorinatedBiphenyls 2,3‐Dichlorobiphenyl BDL BDL BDL 2,4,5‐Trichlorobiphenyl BDL BDL BDL 2,2',4,4'‐Tetrachlorobiphenyl BDL BDL BDL 2,2',3',4,6'‐Pentachlorobiphenyl BDL BDL BDL 2,2',4,4',5,6'‐hexachlorobiphenyl BDL BDL BDL 2,2',3,3',4,4',6‐Heptachlorobiphenyl BDL BDL BDL 2,2',3,3',4,5',6,6'‐Octachlorobiphenyl BDL BDL BDL

* Scoring : European Water Framework Directive **BelowDetectionLimit


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5.4. BEIRA LAKE HYDROSYSTEM ANALYSIS The sampling period does not cover a year cycle, which should be the minimal length of time for accurate and reliable conclusions. Despite that, the relatively stable climate in Colombo have indicated some strategic lessons:

‐ A permanent bloom seems to be maintained by: on the one hand, new input of nitrogen and phosphorus from the catchment area, on the other hand by the nutrients stock in sediment water.

‐ Sediment water represents a main stock of nutrients for the whole lake system. A management plan needs to embed sediment dredging activities or/and reduction nutrient level in sediment.

‐ Bloom variations create difficult biogenic conditions: for instance with a top layer of alkaline pH, and a bottom layer of low oxygenation.

‐ During this sampling period, the bottom layer conditions were still not abiotic: pH did not become very acid, DO level remained medium, iron and manganese dissolved part was poor but it could be worst, taking account the permanent bloom and trophic status.

‐ Chlororphyla confirms hypertrophic status.

‐ The microbiological contamination is not really of a high level, indeed waste water collection seems to be partially successful.

‐ The sediment does not show major micro‐pollutant contamination. However, the sediment contains medium to bad heavy metal contamination (in particular lead and zinc). Dredging activities need to be clearly regulated and fishing strictly prohibited during such works.

‐ Salinity increase in the bottom layer (2 meters depth) during a period indicates that the saline water wedge is clearly not far from the top of aquifer.

5.5. BEIRA LAKE ACTION PLAN Various studies3have already shown that the Beira lake hydrosystem is heavy polluted and has a hypertrophic status. Our study fills some specific gaps (sediment quality) but considerable elements are missing in order to have a complete and comprehensive overview. The main elements include the fauna (fish, worms in sediment, zooplankton) and flora (algae). In the same way, it is absolutely necessary to lead such study during at least one year, and ideally during three years. It means sampling every three months a few parameters and every year all of them.

3“Restoring Beira Lake ‐ An Integrated Urban Environmental Planning Experience in Colombo, Sri Lanka” Dissanayake Leonard and Ravi Pereira, 1996, and Trophic status of the restored South‐West and non restored East Beira Lakes A.I.Kamaladasa and Y.NA. Jayatunga, 2007


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Nevertheless, the course of action mentioned in previous studies basically remains strong:

1. Reduction of pollutant loadings into the Lake addressed pollution entering the lake from its catchment:

BOD, COD, TDS, nitrogen and phosphorus still increase in different compartments (water, sediment water, sediment). Previous restoration in South East Lake did not have the expected effects and the overall quality is approximately the same in the two lakes. Only the Floating market seems less polluted probably because recent dredging had an effect in a smaller area.

Obviously, the first activity before beginning other actions is to decrease the discharges from all the inlets in Beira Lake. It is the only way to stop nutrients and heavy metal inlet in the lake.

It already means to assess status and water quality of all the inlets arriving in Beira Lake for example by conducting 24 hours integrated water quality monitoring. Once each discharge point is monitored and characterized, we could then look at green solutions to address single or combined discharge points. For instance we could route multiple discharge points in one area into a constructed wetland if the chemical parameters could be treated through an appropriately designed wetland.

2. Only if the first activity is complete, restoration procedure can be delivered. Even though the nutrient inlets can be stopped, we have seen that the sediment water and sediment behave like a bank, so that algae bloom can persist for several years or decades.

Water, sediment water and sediment quality also resulted in:

a. Heavy metal concentrations indicate that there is a strong need to treat sustainably with the lake sediments.

b. Algae filtration has no significant value as a result of heavy nutrient rate which maintains primary production system.

c. Dilution (supplying water from another source like Kelany River) will have no real and sustainable impact to reduce algae bloom due to huge nutrient stock in water sediment and sediment.

d. Phytophage fish will have no impact apart from the end of restoration plan, in case of bloom decrease. Actual chemical indicators do not allow fish population to be sustained (basic pH, high TSS, low oxygen, etc.) and it does not fix the problem of nutrient amount in the lake. It is another link in the foodweb, but not a key‐factor.

e. Using biofan, in the same way as phytophage fish, it could be interesting as soon as nutrient rate is lower and/or deoxygenation cause disturbing effects (metal and H2S discharge) in bottom layer. A biofan enables oxygenation and mixes water column. On one hand, it can allow fauna and flora development in lake. On the other hand, if it is a shallow depth lake, it can mix sediment water and maintain nutrient discharge therefore, increase primary productivity (algae bloom).

That is why the second activity would be the dredging of all the lakes sediments. It means that during this period (one or two years) the bloom would be even more intense probably causing more turbidity, more deoxygenation leading to hydrogen sulfide (H2S) gas discharge. The whole dredging sediment must be placed in an appropriate landfill (high lead, mercury and zinc rates) or ideally they should be decontaminated before being placed over land.


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Online water quality monitoring is needed during dredging activity in order to prevent high gaseous discharge potentially toxic for hydrosystem (in St Sebestian Canal and Kelany river) and for the neighborhoods of the lakes (people in hotel, industry, etc.). Chemical monitoring device on buoys could be used for early warning. In parallel, monitoring every three month must be led on water column, algae, sediment, and worms in sediment in order to assess when to stop dredging.

3. This two first steps completed, and only after, third step can be a more smooth restoration plan including shoreline beautification, development of recreational facilities, fish restocking (with indigenous species), etc.

Each activity needs an appropriate monitoring system developed in due course.

In our view, however, certain issues should be more clearly defined or emphasized, management plan must follow this process to be successful. If technical stakeholders want to begin by second or third step, funders will probably be disappointed by the lack of progress.


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6 SURFACE WATER QUALITY MONITORING NETWORK: A NEW STRATEGY This part presents a proposed strategy to assess water quality in order to build management plan allowing water improvement in Colombo area. Protection and enhancing ecosystem services can be achieve only by a better understanding of how these water bodies function in order to focus efforts on the main critical issue.

According to this, we have developed this monitoring strategy. This should not be considered a final strategy but represents an initial outline from which a final strategy can be implemented. Nevertheless we identify the key points for both Activities 1 and 2.

Table 18. Colombo Water Quality Monitoring Network Design and capacity building

Colombo Water Quality Monitoring Network Design and capacity building

Objective:provide an effective water quality monitoring network to Colombo area

Result: monitoring generates information on ecological impacts which can be used to adapt water management policies and other environmental policies in order to improve water quality

Activity 1:Current water quality monitoring assessment in Colombo area (Sri Lanka)

- Needs and priorities of key users - Means to assess quality (field staff, laboratory, etc.) - Database and online information

Activity 2: Formulate effectiveness monitoring program/design (objectives, location, frequency, method, parameters) and stakeholder’s roles (SLLRDC, Ministry…)

Activity 3: Training requirement Assessment and Capacity Building program of SLLRDC

- Increase reliability of current monitoring - Strengthen team

Activity 4: Definition of relevant parameters for Colombo area (for wetland and brackishwater),building new indicators (including bio-indicator) and scoring by research institutes/universities partnership

- Identification of reference stations (access, well spread in the area) - Building and implementing scoring system for each chemical parameters - Buying and setting up sensor and data transmission system - Assessing and improving existing biotic index (based on macro-invertebrates) - Building and implementing a new biotic index based on phytoplankton and/or Diatoms, Worms in

sediment, etc…

Activity 5: Management of chemical and hydro-biological monitoring database (including physic-chemical, biological and hydro-morphological data)

- Implementation of the database/GIS with regular updating and active data sharing between users - Foster collaboration mechanism between data producers

Activity 6: Formulate guidelines/white paper which specifies roles of SLLRDC and other stakeholders to monitor water quality

Option: Integration on monitoring data into wider water policy including cumulative impact issues and issue relevant regulations


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6.1. CURRENT WATER QUALITY MONITORING ASSESSMENT IN COLOMBO AREA

Needs and priority of key users

There is an increasing demand for water quality information around the world to protect lives and ecosystems from the adverse impacts of pollution. Moreover, water quality information is needed for planning and decision making in many socio‐economic sectors whose outputs are quality sensitive such as integrated water resources management, agriculture, industry, health and tourism.

Although, as stated in a UN‐Water Country Briefs Project4: “Investments in coordinated data collection, collation, analysis and dissemination is vital to demonstrate the benefits of water‐related investments to governments, donors and also private investors”, in most middle income countries these agencies are facing a number of institutional and financial challenges preventing them from responding to the demands for accurate and timely available information.

WMD can become a monitoring network manager for the whole Colombo area but it means that division needs to know all end‐users needs and how to provide them. A first task should be to assess all the potential users of this data and how they can use it. SLLRDC will be a primary data user so the WMD should find the best way to share new data and to collect information coming from other users (industry, irrigation, road, etc.) and monitor the quality and compatibility of the data.

Means to assess water quality

In the same way that monitoring networks have to be optimized, it is absolutely necessary to have a good understanding of the means, human resource and material, to complete this task successfully.

Such an understanding can provide information of over or underestimated parts but also help to define the most beneficial approach from a capacity building program by focusing on main lack of means in the actual team.

To improve and make this information available to the public: database and online GIS

Monitoring results must be adequately consolidated, analyzed and used. Actually, there is no system for regular monitoring or updating information, and when WMD monitoring data or surveys have been carried out they have generally addressed only the capturing of chemical information, not the provision of information and services to end‐users.

In order to achieve this goal, we propose three steps:

4 http://www.unwater.org/about/en/


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- To build a Quality Management System (QMS) from the laboratory to the end‐users: on every step, an auditor needs to check the data and produces a report classified in the QMS. This task is performed during water sampling, probe calibration, data entry, etc.

- Each WMD agent should use the foreground which they own, or ensure that it is used. It means that the data used to build charts, maps, etc. are also used for water quality synthesis, in meetings, in newsletters, etc. This also helps to ensure the quality of the data by being faced with other users. For example, water quality of Colombo annual synthesis displayed through maps for each parameter monitored. The report produced aims to establish the status of the wetlands and canals at a given time and to observe trends compared with previous situations. When an environmental issue is identified a program of remediation should be undertaken. Annual reporting may be also expected to evaluate the efficiency of monitoring in terms of site location, sampling parameters and protocols.

- The basis of any effective monitoring program is a reliable baseline data set against which is used to evaluate and compare future environmental data. The database collected during several years is also a repository of information needed to forecast the environmental impacts of any remediation project. Moreover, the data volume is higher every year and the need of organization is a critical feature. In order to disseminate this information, a data base is not sufficient: it has to be linked to a GIS web portal. The data management system is built on a computerized database engine with web, user/data interface and GIS capabilities. Users could be internal (SLLRDC) or external (other ministry, project engineer, NGOs, ordinary citizen).

6.2. FORMULATE EFFECTIVENESS MONITORING PROGRAM/DESIGN: USE NEW PARAMETERS AND KNOW HOW TO EXPLOIT RESULTS

Objectives

The objective is to measure the response of aquatic communities to anthropogenic stressors on account of water quality, habitat quality and biotic interactions. The environmental stressors include toxic substances, urban influences, sedimentation, etc. Global monitoring will allow assessing the main disturbance but will not be focused on special impact. It refers to long‐term monitoring or a supervisory control.

The monitoring network could be enhanced by operational control when a remediation plan is led in a restricted area to monitor effectiveness of measures. It could be the case with an operational control all around Beira Lake in case of management plan.


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Third monitoring network is the investigative control. It aims to identify the pollution source and the functioning of a water body before building a management plan. It can also be the case of Beira Lake or Kolonnawa Marsh for example.

Fourth monitoring network, but logically the first to be proposed and integrated to a supervisory control, is the reference control. The idea is to monitor undisturbed reference sites over a wide range of natural environmental variation, developing a predictive model that relates the habitat attributes of these sites to their biotic community, and then predicting the expected community assemblage for a particular project site (“test site”) in reference condition.5 By comparing the forecasted community to the present‐proved one, the test site is assessed and its quality is compared to the reference environmental conditions. The identified reference conditions allow providing for example thresholds for physic‐chemical and biological parameters or community structures for aquatic species. A reference station network is set up to monitor impacts compared with undisturbed/reference condition sites.

A best use of existing networks

We have previously shown monitoring network used by SLLRDC (since 2004) and the one implemented in this study. There is also the monitoring network managed by the CEA: although it is not focused on the Metropolitan Colombo area, its few stations provide a fair information source mostly because the whole watershed of Kelany river is covered by this network. In an Integrated Water Resource Management (IWRM) approach, monitoring water quality all along the river is a very relevant approach.

The first step should be to redesign the actual SLLRDC network for optimization and modernization to answer current need. The second step is to build a pollution sources map to focus on major source of disturbance. The third step is to have an even representation of basin types (size and land‐use).

Nevertheless, according to first results we encourage WMD to follow a few recommendations synthesize in the table.

5Bailey et al. 2004


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Table 19. Recommendations to adapt WMD historical water quality network : sites locations

St N° Location Comments

2 End point of St. Sebestian Canal (Outlet to Beira lake) Continue

3 Bridge on Kotte north canal. Continue

4 Railway bridge on Torrington canal. Continue

5 Galle road bridge on Wellawatte canal. Very close to 6 and too much influenced by coastal water

6 Galle road bridge on Dehiwala canal. Very close to 5 and too much influenced by coastal water

8 Bolgoda canal down stream of Kaudana&Attidiya scheme. Out of study area

9 Weras Ganga on Borupana road ferry crossing Out of study area

11 St. Sebestian Canal bridge near Ingurukade junction. Continue

12 Dematagoda canal ,Kolonnawa bridge near the Petroleum Corporation.

Continue

13 Mahawattecanal , Kotte road bridge , Rajagiriya. Continue

14 Kirillapona canal , Near Open Unversity Bridge Continue

18 Station No.01 :Diyawanna Oya , Kimbulawala Madiwela. Continue

19 Station No.02 :Diyawanna Oya , Battaramulla south Pelawatte.

Continue

20 Station No.03 :Diyawanna Oya , Battaramulla north Diyawanna Oya outlet.

Continue

21 Kelany river close to new bridge upper stream to confluence of St.Sebestian canal.

Continue

22 St. Sebestian Canal north lock gate. Continue

23 Kelany river close to Victoria bridge downstream confluence of St.Sebestian canal.

Stop : similar to 26 and CEA monitoring site (6)

24 Beira lake just behind Pettah private bus stand. Floating market?

25 St. Sebestian Canal about 200m downstream from location no.02

Continue

26 St. Sebestian Canal (north) outfall to Kelany river. Continue

27 Bloemendel , Branch earthen drain coming through garbage pile.

Stop: close to 28 and very similar trend

28 Bloemendel , Canal at the confluence of earthern drain of 27 Continue


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Table 20. Recommendations to enrich WMD historical water quality network with study network

Sample n° Location

Comments

1 Canal at Kottawa North Upstream site but polluted. Another reference site need to be determinated

2 Canal at Pathiragoda Stop. Same trend as site 3

3 Parliament lake Continue. Eq. to SLLRDC 18

4 Water inlet to Parliament lake Stop. Same trend as site 5

5 Dammaladeniya meda ela Investigative control, every 2 years

6 Atunkedeniya meda ela Pollution free zone : to sample every 5 years

7 Parliamentlake Pollution free zone : to sample every 5 years

8 Kinda Canal Pollution free zone : to sample every 5 years

9 Kolonnawa Canal Continue. Eq. to SLLRDC 3

10 Kolonnawa Canal Low pollution zone : to sample every 5 years

11 Kolonnawa Canal Pollution free zone : to sample every 5 years

12 Kittampahuwa Canal Add to SLLRDC network

13 Kittampahuwa Canal Add to SLLRDC network

14 Dematagoda Canal Continue. Eq. to SLLRDC 12

15 Kolonnawa Marsh Investigative control, every 2 years

16 Serpentine Canal Eq. to SLLRDC 10 (no monitoring)

17 Heen Ela Marsh Continue. Eq. to SLLRDC 13

18 Kotte Marsh Investigative control, every 2 years

19 Kotte Marsh Add to SLLRDC network

20 Kirulapone Canal Continue. Eq. to SLLRDC 14

21 Heen Ela Investigative control, every 2 years

22 Dehiwala Canal Add to SLLRDC network

23 Dematagoda Canal Start. Eq. to SLLRDC 1 (no monitoring)

24 Kirulapana Canal Pollution free zone : to sample every 5 years

25 St. Sebastian Canal Continue. Eq. to SLLRDC 22

26 St. Sebastian Canal Continue. Eq. to SLLRDC 26

27 Redbanaela Add to SLLRDC network

28 Karandagahamula Kumburaela Pollution free zone : to sample every 5 years

29 Thalahena tank Pollution free zone : to sample every 5 years

30 Evarihena tank Pollution free zone : to sample every 5 years

31 Canal passing through the paddy land Pollution free zone : to sample every 5 years

32 Mulleriyawa tank Pollution free zone : to sample every 5 years

33 Mahawela ela Investigative control, every 2 years

34 Ambatale ela To stop : similar to CEA monitoring site (4)

35 Norris Canal Start. Eq. to SLLRDC 29 (no monitoring)


Page | 62

Figure 11. CEA monitoring network


Page | 63

Figure 12. Water quality networks in Colombo area (2015)


Page | 64

Parameters and frequency

There are several methods for assessing water quality to ensure the efficiency of water quality monitoring. Each method has its own particular application, advantages and disadvantages in terms of precision, reliability, discrimination6, ecological effect measurement and costs (Table 20). The combination of several techniques is preferred. Bio‐monitoring methods are useful for assessing the overall impact because they integrate long‐term pollution information.

Table 21. Performance of water monitoring techniques

Criterion of performance Physicochemical monitoring

Biological monitoring

Discrimination Good E.g. “what kind of

pollution?”

Poor

Precision Good e.g. “what is the level of the contaminant?”

Poor

Reliability* Poor Goode.g. « Does 2 or 3 samples enough during 2 years?»

Measure of ecological effects

No Yese.g. “Does the ecosystem affected by this disturbance?”

Cost high low or middle

*how representative is a single or a limited number of samples

Physico‐Chemical parameters

Parameters and sampling frequency is not easy to define without a better understanding of dedicated means (resources and budget). Nevertheless, we try to provide elements to design a most efficient network.

Table 22. Recommendations to adapt WMD historical water quality network: chemical parameters

Parameter Actual Frequency Proposed Frequency

Comments

Water Canal/Stream pH Monthly Monthly

Electrical Conductivity Monthly Monthly Turbidity Monthly Monthly

Dissolved Oxygen Monthly Monthly Salinity Monthly Monthly

Temperature Monthly Monthly Nitrate Monthly Monthly Nitrite ‐ Monthly

Ammonia Monthly Monthly

6Discrimination means the capacity of a specific monitoring to determine precisely the disturbance reason.


Page | 65

Phosphate Monthly Monthly COD Monthly Monthly BOD Monthly Monthly

Total Dissolved Solids Monthly Monthly Total Organic Carbon ‐ 4 times /year Hydrogencarbonate ‐ 4 times /year

Calcium ‐ 4 times /year Magnesium ‐ 4 times /year

Sodium (Natrium) ‐ 4 times /year Potassium ‐ 4 times /year Chlorides ‐ 4 times /year Sulphates ‐ 4 times /year Arsenic 4 times /year Fluorides 4 times /year Cyanides 4 times /year

Total Iron (Fe) 4 times /year Total Manganese (Mn) 4 times /year

Pesticides ‐ 4 times /year Organic micropollutants ‐ 4 times /year

PAH ‐ 4 times /year Water Lake

pH Monthly Real time Data buoyElectrical Conductivity Monthly Real time Data buoy

Turbidity Monthly Real time Data buoyDissolved Oxygen Monthly Real time Data buoy

Salinity Monthly Real time Data buoyTemperature Monthly Real time Data buoy

Nitrate Monthly 4 times/year Ammonia Monthly 4 times/year Phosphate Monthly 4 times/year

COD Monthly 4 times/year BOD Monthly 4 times/year

Total Dissolved Solids Monthly 4 times/year Nitrite ‐ 4 times/year

Total Organic Carbon ‐ 4 times/year Chlorides ‐ 4 times/year Sulphates ‐ 4 times/year

Hydrogencarbonate ‐ 4 times/year Calcium ‐ 4 times/year

Magnesium ‐ 4 times/year Sodium (Natrium) ‐ 4 times/year

Potassium ‐ 4 times/year Pesticides ‐ 4 times/year

Organic micropollutants ‐ 4 times/year PAH 4 times/year

Sediment Canal/Stream


Page | 66

Organic micropollutants ‐ Once/year PAH ‐ Once/year

Metals (As, Cd, Cr, Cu, Hg, Ni, Pb, Zn ‐ Once/year Pesticides ‐ Once/year

Sediment Lake Organic micropollutants ‐ Once/year

PAH ‐ Once/year Metals (As, Cd, Cr, Cu, Hg, Ni, Pb, Zn ‐ Once/year

Pesticides ‐ Once/year Organicmatter ‐ Once/year Total Nitrogen ‐ Once/year

Total Phosphorus ‐ Once/year 1 time/year

Iron ‐ Once/year

Manganese ‐ Once/year

Cyanides ‐ Once/year

Organic matter (measured by loss of ignition) ‐ Once/year

Grain size ‐ Once/year Sediment water Lake

Total Nitrogen ‐ Twice/year Total Phosphorus ‐ Twice/year

Phosphate ‐ Twice/year Ammonia ‐ Twice/year

Iron ‐ Twice/year

Manganese ‐ Twice/year Biology river Diatoms ‐ Once/year

Invertebrates ‐ Once/year Fish ‐ Once/year

Worms ‐ Once/year Biology lake Secchi depth ‐ 4 times/year Chlorophyla ‐ 4 times/year

Algae (all the phytoplankton) ‐ 4 times/year Worms ‐ Once/year

Hydro‐biological indicators help evaluate connections between the various components belonging to an aquatic system, such as the physicochemical quality of water, aquatic fauna and flora. Hydro‐biological indicators include :

• Microscopic algae : chlorophytes, chromophytes (diatoms) compound by periphyton and phytoplankton,

• Macrophytes (helophytes, hydrophytes…), • Microscopic animals (Copepod, Rotifer, Cladocer, Protozoon, …), • Benthic invertebrates (mollusks, insects, worms, …), • Fish.


Page | 67

The principle of hydrobiology monitoring mainly consists in understanding conditions required from each aquatic species to survive and reproduce in the aquatic environment, their relationships with each other and the relation they have with the aquatic environment, and especially with the water quality (space‐time evolution). Hydrobiology takes a great role in freshwater quality monitoring networks. Thus, through time, experts have developed different biotic indexes for classifying waters quality according to the biotic communities that they supported. It is necessary to use a broad and adapted set of indexes in order to establish a river's "overall” hydro‐biological quality.

Colombo University already monitors benthic invertebrates. The use of this bio‐indicator should be facilitating as the WMD team use biotic index for benthic invertebrates. On the other hand, a relevant index for phytoplankton does not exist. It may be a strategic development to build an adapted index. However, several community structure indexes (Shannon and Weaver index, etc.) could be sufficient in a first time. For example, the effectiveness monitoring in Europe is based on both several biotic compartments, but largely phytoplankton in slow flow area.

Others biological compartments seem to be uirrelevant due to warm, silty, eutrophic (rich in nutrients) waters that is why these two groups should be the basis of bio‐monitoring efforts in Colombo area. In such canals and wetland, turbidity damages the vegetation development and makes it too difficult to sample.

Equipment

To monitor and manage the water quality in the water bodies, different ways can be used: sampling team for the laboratory parameters or remote device. Such sensors are connected with a data Logger through cables or a wireless link and can measure temperature, pH, salinity, conductivity, DO, turbidity and chlorophyla. There are few functioning automatic stations or real time data transmission.

Figure13. Radio communication and data buoy

In the case of Colombo, due to an easy access to the sampling stations and stable value all along the year it seems not necessary to use such equipment on canals. Well trained staff might be sufficient.

The use of remote monitoring could be more interesting for Beira Lake where the WMD may need real time data in order to adapt technical response to algal bloom. Based on a good baseline study, such monitoring device could forecast (temperature, Chla, etc.) rapid degradation and enable the WMD to use appropriate management tools.


Page | 68

7 WETLAND GROUNDWATER FUNCTIONING

7.1. INTRODUCTION Underground water bodies have annual cycles, depending on climate (rainfall, temperature) and seasons. In that respect, a 5‐week monitoring is totally inadequate: information collected during 5 weeks is just a little pattern of the whole year cycle. There is no correct data interpretation possible with such a small time monitoring.

7.2. WATER LEVELS

Figure14. Water level

All we have here is relative water levels with respect to the ground, ie the highest values are the deepest ones. Water table is the deepest at borehole SLLRDC3 and the shallowest at SLLRDC2. Water table variations are rather small, but monitoring is too short to draw a conclusion.

We are unable to define which borehole is upstream and which one is downstream because we lack altitude of boreholes. Absolute water table levels are calculated by:

Absolute water level = Borehole altitude – water level with respect to the ground

The water table is flowing from highest absolute water levels to lowest ones.

0

0,5

1

1,5

2

2,5

3

3,5

4

Water level from groun

d

Water levels

1 Diyatha Uyana

2 SLLRDC 1

3 SLLRDC 2

4 SLLRDC 3

5 Kimbulawala Kamatha

6 Palam Thuna Junction


Page | 69

7.3. GROUNDWATER QUALITY pH

Figure15. pH on groundwater

pH variations are interesting: nearly all boreholes show decreasing pH from an average 8 to an average 6.5. In this period, we are in a decreasing part of the pH curve, and monitoring must continue for us to see how pH behaves in the rest of the year.

pH is an important indicator, showing chemical changes in the underground water, sign of possible changes in aquifer supply (introduction of rain water from the surface for example) or changes in its interfering with the sea (depending of relative levels of the water table and the sea).

6

6,5

7

7,5

8

8,5

pH

pH

1 Diyatha Uyana

2 SLLRDC 1

3 SLLRDC 2

4 SLLRDC 3




Page | 70

Salinity

Figure16. Salinity on groundwater

Salinity is stable but with a decreasing trend. Salinity is related to sea water intrusion. It is once again an important indicator of the water table chemistry.

Other parameters

Oxygen concentrations are quite high for a water table, showing that aquifer does interfere with surface water.

7.4. REQUIRED DATA FOR A SUITABLE MONITORING As seen in above text, a 5‐week monitoring is far too short to draw any meaningful conclusions. To be able to draw significant conclusions, the following are needed:

A localization map, with borehole names ; Borehole altitudes, to calculate absolute water levels and establish water flow directions; At least a one‐year monitoring of parameters ( water table, pH, salinity, DO, Temperature, TDS, EC) to have a complete water cycle;

To introduce at least a pollutant indicator from surface, as water table is near the surface, to monitor exchanges with surface water: nitrate, ammonium or total phosphorus are appropriate;

Make clear units of measured parameters.

0

0,1

0,2

0,3

0,4

0,5

0,6Salin

ity

Salinity

1 Diyatha Uyana

2 SLLRDC 1

3 SLLRDC 2

4 SLLRDC 3




Page | 71

8 APPENDICES

Appendix 1 ‐ Inlets to Beira Lake

Appendix 2 –Water framework directive quality scoring

Appendix 3 – Historical data

Appendix 4 – Water quality distribution in Metro Colombo wetlands catchment: Map

T

The Consulan Asses

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tancy Servissment of W

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uary 2016

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WETLAND MANAGEMENT STRATEGY ‐ Technical Report 04 ‐ PHYSICAL FEATURES_Water quality, lake, sediment and soil issues _Appendices

Page | 2

Appendix 1

Inlets to Beira Lake

PS No. Location Number

Descriptions of Inlet Status Coordinates

East North

B 1 1 Active waste water drain Invisible 98422 190698

B 2 2 Storm water pipe Visible 98422 190703


B 4 4 Active waste water pipe Visible 98393 190719






B 10 10 Active waste water drain Visible 98285 190763






B 16 16 Storm water pipe waste Visible 97994 190823

B 17 17 Inactive waste water pipe Visible 97981 190862














B 31 31 Active waste water pipe Inisible 98442 190844






B 37 37 Active waste water pipe Invisible 97901 191014















East North














B 89 63 Active Storm water pipe Visible 97968 192474






























B 119 93 Inactive Storm water pipe Visible 98520 192249
















Page | 3



East North









































East North































B 202 176 Cannel Visible 97835 192490

B 203 177 Cannel Visible 97875 192484




Page | 4

Appendix 2

Water Framework Directive Quality Scoring European and French Water quality Scores

Ecological status

Quality class Blue Green Yellow Orange RedQuality Index 80 60 40 20

Oxydable & org mattersDO (mg/l) 8 6 4 3BOD5 (mg/l O2) 3 6 10 25COD (mg/l O2) 20 30 40 80KmnO4 (mg/lO2) 3 5 8 10DOC (mg/l C) 5 7 10 12NitrogenousNH4+ (mg/l-NH4) 0.1 0.5 2 5NKJ (mg/L N) 1 2 4 10NO2 (mg/l-NO2) 0.03 0.1 0.5 1NitratesNO3 (mg/l-NO3) 2 10 25 50Substances containing phosphorusTotal Phosphore (mg/l) 0.05 0.2 0.5 1PO43 (mg/l-PO4 0.1 0.5 1 2suspended particulesMES (mg/l) 5 25 38 50Turbidity (ntu) 2 35 70 105PhytoplanktonO2 saturation rate 110 130 150 200PH 8 8.5 9.0 9.5Chlorophyl a + pheopigments (mg/l) 10 60 120 240

Quality class Blue Green Yellow Orange RedQuality Index 80 60 40 20

Micro-organismsthermotolerant coliforms (u/100ml) 20 100 1000 2000Faecal streptococci (u/100ml) 20 100 250 400


Page | 5

Bathing and Recreational status

Irrigation status

Quality Class Blue Green Yellow Orange Red

Very good Good Medium Bad Very bad

Mineralisation

Dry residue (105°) 500 1500 2500 3500

Chlorides (mg/l) 180 360 700 *

Micro‐organisms

Thermotolerant coliforms (u/100ml) 100 * * *

Total coliforms (u/100ml) 1,000 * * *

Trace minerals on raw water

Arsenic (µg/l) 100 * 2000 *

Cadmium (µg/l) 10 * * *

Total chromium (µg/l) 100 * * *

Nickel (µg/l) 200 * 2000 *

Lead (µg/l) 200 * 2000 *

Selenium (µg/l) 20 * * *

Copper (µg/l) 200 1000 5000 *

Zinc (µg/l) 5000 * * *

* No existing class

Quality Class Blue Green Red

Very good Good Very bad

Suspended particules

TDS/TSS (mg/l) 25 50

Secchi 200 100

Micro-organisms

Thermotolerant coliforms (u/100ml) 100 2000

Total coliforms (u/100ml) 500 10,000

Faecal streptococci (u/100ml) 100 *


Page | 6

Water livestock status



Nitrogenous

NO2- (mg/l) 0.1 30

Nitrates

Nitrates (mg/l) 50 450

Mineralisation

Dry residue (105°) 1000 5000

Sulfates (mg/l) 250 1000

Calcium (mg/l) 1000 *

Sodium/Natrium (mg/l) 150 2000


Arsenic (µg/l) 50 500

Cadmium (µg/l) 5 20

Total chromium (µg/l) 50 1000

Mercury (µg/l) 1 3

Nickel (µg/l) 50 1000

Lead (µg/l) 50 100

Selenium (µg/l) 10 50

Copper (µg/l) 500 5000

Zinc (µg/l) 5000 50,000

Aquaculture status



Oxydable and org matters

DO (dissolved oxygen, mg/l) 7 5

BOD5 (mg/l O2) 5 10

Nitrogenous

NH4+ (mg/l) 0.1 5

NO2- (mg/l) 0.03 1

Nitrates

Nitrates (mg/l NO3-) 10 100

Substances containing Phosphorus

Total phosphorus (mg/l P) 0.01 3

Phytoplankton

Chlorophyl a + pheopigments (µg/l) 10 120

Suspended particules

TDS/TSS (mg/l) 10 50

Acidification

pH min pH max

6.5 8 *

Mineralisation

Calcium (mg/l) min Calcium (mg/l) max

50 160 *


Mercury (µg/l) 0.05 2

Lead (µg/l) 30 *

Copper (µg/l) 10 *

Zinc (µg/l) 4 *

Free cyanide 5 *


Page | 7

Sri Lankan water status thresholds according CEA (intentionally not used during this study in order to have more thresholds)

Drinking water – Sri Lankan status*

Category 2 : Drinking water with simple treatment is used to determine Very good thresholds Category 5: Drinking water with conventional treatment is used to determine Good thresholds

Quality Class Blue Green RedVery good Good Verybad

Oxydable and orgmattersDO (dissolved oxygen, mg/l) 6 4

BOD5 (mg/l O2) 3 5COD (mg/l O2) 15 30NitrogenousNH4

+ (mg/l)pH < 7.5 pH = 8.0 pH = 8.5

0.94 0.59 0.22

NitratesNitrates (mg/l NO3

‐) 5Substances containing Phosphorus

Total phosphorus (mg/l P) 0.7 Suspended particules

Turbidity (NTU) 5AcidificationpH minpH max

6.0 8.5

6.09.0

MineralisationHardness CaCO3 (mg/l) 250 600

Chlorides (mg/l) 200 Cyanides (mg/l) 0.005 Fluorides (mg/l) 1.5 Sulfates (mg/l) 250

Trace minerals on raw waterCadmium (µg/l) 5

Total chromium (µg/l) 50 Iron (µg/l) 300 1000Lead (µg/l) 50

Manganèse (µg/l) 1000 Mercury (µg/l) 1Nickel (µg/l) 100

Selenium (µg/l) 10 Zinc (µg/l) 1000

Total Arsenic (µg/l) 10 Aluminium (µg/l) 200 Micro‐organisms

Total coliforms (u/100ml) 5000 Faecalcoliform (u/100ml) 250 600

*Without Organis micro Pollutants thresholds

Sri Lankan Standards 614:1983 _ Sri Lanka Standards Institute

Portable water ‐ Physical and Chemical requirements

Characteristic Maximum desirable level

Maximum Permissible level

Color 5 units 30 units

odour unobjectionable unobjectionable

Taste unobjectionable unobjectionable

Turbidity 2 Jackon T.B 8 Jacson T.M

pH 7.0‐ 8.5 6.5‐ 9.0

Electrical Conductivity

750 µs/cm 3500 µs/cm

Chloride (as Cl) mg/l 200 1200

Free residual Chloride (as Cl2)

mg/l 0.2

Alkalinity (total as CaCO3)

mg/l 200 400

Free ammonia mg/l 0.06

Albuminoid ammonia

mg/l 0.15

Nitrate (as N) mg/l 10

Nitrite (as N) mg/l 0.01

Fluoride (as F) mg/l 0.6 1.5

Total phosphates (as PO4)

mg/l 2.0

Total residue mg/l 500 2000

Total hardness (as CaCO3)

mg/l 250 600

Total Iron mg/l 0.3 1.0

Sulphate (as SO4) mg/l 200 400

Anionic detergents mg/l 0.2 1.0

Phenoliccompounds (as phenolic OH)

mg/l 0.001 0.002

Grease mg/l 1.0

Calcium (as Ca) mg/l 100 240

Magnesium mg/l 30 140

Copper (as Cu) mg/l 0.05 1.5

Manganese mg/l 0.05 0.5

Zinc (as Zn) mg/l 5.0 15

Aluminum (as Al) mg/l 0.2

COD mg/l 10

As mg/l 0.05 1.0

Cd mg/l 0.005 1.0

CN mg/l 0.05 1.0

Pb mg/l 0.05 1.0

Hg mg/l 0.001 1.0

Se mg/l 0.01 1.0

Cr mg/l 0.05 1.0


Page | 8

Bathing water – Sri Lankan status*

Quality Class Blue RedVery good Verybad

Oxydable and orgmatters DO (dissolved oxygen, mg/l) 5

BOD5 (mg/l O2) 4 COD (mg/l O2) 20

Nitrates Nitrates (mg/l NO3

‐) 5 Substances containing Phosphorus

Total phosphorus (mg/l P) 0.7 Acidification pH minpH max

6.0 9.0

Mineralisation Cyanides (mg/l) 0.005

Trace minerals on raw water Manganèse (µg/l) 1000 Mercury (µg/l) 1 Nickel (µg/l) 100


Total Arsenic (µg/l) 50 Micro‐organisms

Total coliforms (u/100ml) 1000 Faecalcoliform (u/100ml) 50

*Without Organis micro Pollutants thresholds

Fish and aquatic life – Sri Lankan status*

Quality Class Blue RedVery good Very bad




‐) 5 Substances containing Phosphorus

Total phosphorus (mg/l P) 0.4 Acidification pH minpH max

6.0 8.5


Trace minerals on raw water Cadmium (µg/l)Hardness<60

60‐120 120‐180 >180

0.2 0.8 1.3 1.8

Chromium (µg/l) 2 Iron (µg/l) 300 Lead (µg/l)Hardness<60

60‐120 120‐180 >180

1 2 4 7

Manganèse (µg/l) 1000 Mercury (µg/l) 0.1 Nickel (µg/l)Hardness<60

60‐120 120‐180 >180

25 65 110 150


Total Arsenic (µg/l) 50 Micro‐organisms

Total coliforms (u/100ml) 20,000*Without Organis micro Pollutants thresholds


Page | 9

Irrigation and agriculture ‐ Sri Lankan status*



BOD5 (mg/l O2) 5 Nitrates

Nitrates (mg/l NO3‐) 5

Substances containing Phosphorus Total phosphorus (mg/l P) 0.7 Suspended particules

TDS/TSS (mg/l) 500 Acidification pH minpH max

6.0 8.5

Mineralisation Conductivity (dS/m) 0.7

Sodium absorption ratio (SAR) 6‐15 Residual Sodium Carbonate (RSC) 1.25

Chlorides (mg/l) 100 Cyanides (mg/l) 0.005 Sulfates (mg/l) 1000

Trace minerals on raw water Manganèse (µg/l) 1000 Mercury (µg/l) 1 Nickel (µg/l) 100 Zinc (µg/l) 1000 Boron (µg/l) 500

Total Arsenic (µg/l) 50 Aluminium (µg/l) 5.0 Micro‐organisms

Total coliforms (u/100ml) 1000 *Without Organis micro Pollutants thresholds

Other uses ‐ Sri Lankan status*





‐) 5 Nitrogenous NH4

+ (mg/l)pH < 7.5 pH = 8.0 pH = 8.5

9.1 4.9 1.6

Substances containing Phosphorus Total phosphorus (mg/l P) 0.7

Acidification pH minpH max

5.5 9.0


Trace minerals on raw water Cadmium (µg/l) 5

Total chromium (µg/l) 50 Copper (µg/l) 100 Lead (µg/l) 50

Manganèse (µg/l) 1000 Mercury (µg/l) 2 Nickel (µg/l) 100 Zinc (µg/l) 1000

Total Arsenic (µg/l) 50 *Without Organis micro Pollutants thresholds


Page | 10

Appendix 3

Historical data

SLLRDC Monitoring network


Page | 11

pH

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7/13

01/0

1/14

01/0

7/14

Station 8 p

0123456789

10

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

01/0

1/07

01/0

7/07

01/0

1/08

01/0

7/08

01/0

1/09

01/0

7/09

01/0

1/10

01/0

7/10

01/0

1/11

01/0

7/11

01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14

Station 9 p

0123456789

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

01/0

1/07

01/0

7/07

01/0

1/08

01/0

7/08

01/0

1/09

01/0

7/09

01/0

1/10

01/0

7/10

01/0

1/11

01/0

7/11

01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14

Station 11 p

0123456789

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

01/0

1/07

01/0

7/07

01/0

1/08

01/0

7/08

01/0

1/09

01/0

7/09

01/0

1/10

01/0

7/10

01/0

1/11

01/0

7/11

01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14

Station 12 p

0123456789

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

01/0

1/07

01/0

7/07

01/0

1/08

01/0

7/08

01/0

1/09

01/0

7/09

01/0

1/10

01/0

7/10

01/0

1/11

01/0

7/11

01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14

Station 13 p


Page | 12

0123456789

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

01/0

1/07

01/0

7/07

01/0

1/08

01/0

7/08

01/0

1/09

01/0

7/09

01/0

1/10

01/0

7/10

01/0

1/11

01/0

7/11

01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14

Station 14 p

0123456789

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

01/0

1/07

01/0

7/07

01/0

1/08

01/0

7/08

01/0

1/09

01/0

7/09

01/0

1/10

01/0

7/10

01/0

1/11

01/0

7/11

01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14

Station 18 p

0123456789

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

01/0

1/07

01/0

7/07

01/0

1/08

01/0

7/08

01/0

1/09

01/0

7/09

01/0

1/10

01/0

7/10

01/0

1/11

01/0

7/11

01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14

Station 19 p

0123456789

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

01/0

1/07

01/0

7/07

01/0

1/08

01/0

7/08

01/0

1/09

01/0

7/09

01/0

1/10

01/0

7/10

01/0

1/11

01/0

7/11

01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14

Station 20 p

0123456789

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

01/0

1/07

01/0

7/07

01/0

1/08

01/0

7/08

01/0

1/09

01/0

7/09

01/0

1/10

01/0

7/10

01/0

1/11

01/0

7/11

01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14

Station 21 p

0123456789

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

01/0

1/07

01/0

7/07

01/0

1/08

01/0

7/08

01/0

1/09

01/0

7/09

01/0

1/10

01/0

7/10

01/0

1/11

01/0

7/11

01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14

Station 22 p

0123456789

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

01/0

1/07

01/0

7/07

01/0

1/08

01/0

7/08

01/0

1/09

01/0

7/09

01/0

1/10

01/0

7/10

01/0

1/11

01/0

7/11

01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14

Station 23 p

0

2

4

6

8

10

12

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

01/0

1/07

01/0

7/07

01/0

1/08

01/0

7/08

01/0

1/09

01/0

7/09

01/0

1/10

01/0

7/10

01/0

1/11

01/0

7/11

01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14

Station 24 p

0123456789

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

01/0

1/07

01/0

7/07

01/0

1/08

01/0

7/08

01/0

1/09

01/0

7/09

01/0

1/10

01/0

7/10

01/0

1/11

01/0

7/11

01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14

Station 25 p

0123456789

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

01/0

1/07

01/0

7/07

01/0

1/08

01/0

7/08

01/0

1/09

01/0

7/09

01/0

1/10

01/0

7/10

01/0

1/11

01/0

7/11

01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14

Station 26 p

0123456789

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

01/0

1/07

01/0

7/07

01/0

1/08

01/0

7/08

01/0

1/09

01/0

7/09

01/0

1/10

01/0

7/10

01/0

1/11

01/0

7/11

01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14

Station 27 p

0123456789

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

01/0

1/07

01/0

7/07

01/0

1/08

01/0

7/08

01/0

1/09

01/0

7/09

01/0

1/10

01/0

7/10

01/0

1/11

01/0

7/11

01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14

Station 28 p


Page | 13

Conductivity

0

0,1

0,2

0,3

0,4

0,5

0,6

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

01/0

1/07

01/0

7/07

01/0

1/08

01/0

7/08

01/0

1/09

01/0

7/09

01/0

1/10

01/0

7/10

01/0

1/11

01/0

7/11

01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14

Station 2 Cond…

00,10,20,30,40,50,60,70,80,9

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

01/0

1/07

01/0

7/07

01/0

1/08

01/0

7/08

01/0

1/09

01/0

7/09

01/0

1/10

01/0

7/10

01/0

1/11

01/0

7/11

01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14

Station 3 Cond…

0

0,2

0,4

0,6

0,8

1

1,2

1,4

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

01/0

1/07

01/0

7/07

01/0

1/08

01/0

7/08

01/0

1/09

01/0

7/09

01/0

1/10

01/0

7/10

01/0

1/11

01/0

7/11

01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14

Station 4 Cond…

0

10

20

30

40

50

60

70

80

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

01/0

1/07

01/0

7/07

01/0

1/08

01/0

7/08

01/0

1/09

01/0

7/09

01/0

1/10

01/0

7/10

01/0

1/11

01/0

7/11

01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14

Station 5 Cond…

0

10

20

30

40

50

60

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

01/0

1/07

01/0

7/07

01/0

1/08

01/0

7/08

01/0

1/09

01/0

7/09

01/0

1/10

01/0

7/10

01/0

1/11

01/0

7/11

01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14

Station 6 Cond…

0

0,5

1

1,5

2

2,5

3

3,5

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

01/0

1/07

01/0

7/07

01/0

1/08

01/0

7/08

01/0

1/09

01/0

7/09

01/0

1/10

01/0

7/10

01/0

1/11

01/0

7/11

01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14

Station 8 Cond…

0

1

2

3

4

5

6

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

01/0

1/07

01/0

7/07

01/0

1/08

01/0

7/08

01/0

1/09

01/0

7/09

01/0

1/10

01/0

7/10

01/0

1/11

01/0

7/11

01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14

Station 9 Cond…

0123456789

10

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

01/0

1/07

01/0

7/07

01/0

1/08

01/0

7/08

01/0

1/09

01/0

7/09

01/0

1/10

01/0

7/10

01/0

1/11

01/0

7/11

01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14

Station 11 Cond…

00,5

11,5

22,5

33,5

44,5

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

01/0

1/07

01/0

7/07

01/0

1/08

01/0

7/08

01/0

1/09

01/0

7/09

01/0

1/10

01/0

7/10

01/0

1/11

01/0

7/11

01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14

Station 12 Cond…

0

0,5

1

1,5

2

2,5

3

3,5

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

01/0

1/07

01/0

7/07

01/0

1/08

01/0

7/08

01/0

1/09

01/0

7/09

01/0

1/10

01/0

7/10

01/0

1/11

01/0

7/11

01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14

Station 13 Cond…


Page | 14

0

5

10

15

20

25

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

01/0

1/07

01/0

7/07

01/0

1/08

01/0

7/08

01/0

1/09

01/0

7/09

01/0

1/10

01/0

7/10

01/0

1/11

01/0

7/11

01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14

Station 14 Cond…

0

0,2

0,4

0,6

0,8

1

1,2

1,4

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

01/0

1/07

01/0

7/07

01/0

1/08

01/0

7/08

01/0

1/09

01/0

7/09

01/0

1/10

01/0

7/10

01/0

1/11

01/0

7/11

01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14

Station 18 Cond…

0

0,05

0,1

0,15

0,2

0,25

0,3

0,35

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

01/0

1/07

01/0

7/07

01/0

1/08

01/0

7/08

01/0

1/09

01/0

7/09

01/0

1/10

01/0

7/10

01/0

1/11

01/0

7/11

01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14

Station 19 Cond…

0

0,2

0,4

0,6

0,8

1

1,2

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

01/0

1/07

01/0

7/07

01/0

1/08

01/0

7/08

01/0

1/09

01/0

7/09

01/0

1/10

01/0

7/10

01/0

1/11

01/0

7/11

01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14

Station 20 Cond…

0

2

4

6

8

10

12

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

01/0

1/07

01/0

7/07

01/0

1/08

01/0

7/08

01/0

1/09

01/0

7/09

01/0

1/10

01/0

7/10

01/0

1/11

01/0

7/11

01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14

Station 21 Cond…

0123456789

10

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

01/0

1/07

01/0

7/07

01/0

1/08

01/0

7/08

01/0

1/09

01/0

7/09

01/0

1/10

01/0

7/10

01/0

1/11

01/0

7/11

01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14

Station 22 Cond…

0

2

4

6

8

10

12

14

16

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

01/0

1/07

01/0

7/07

01/0

1/08

01/0

7/08

01/0

1/09

01/0

7/09

01/0

1/10

01/0

7/10

01/0

1/11

01/0

7/11

01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14

Station 23 Cond…

0

0,1

0,2

0,3

0,4

0,5

0,6

0,7

0,8

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

01/0

1/07

01/0

7/07

01/0

1/08

01/0

7/08

01/0

1/09

01/0

7/09

01/0

1/10

01/0

7/10

01/0

1/11

01/0

7/11

01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14

Station 24 Cond…

0

0,1

0,2

0,3

0,4

0,5

0,6

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

01/0

1/07

01/0

7/07

01/0

1/08

01/0

7/08

01/0

1/09

01/0

7/09

01/0

1/10

01/0

7/10

01/0

1/11

01/0

7/11

01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14

Station 25 Cond…

0

2

4

6

8

10

12

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

01/0

1/07

01/0

7/07

01/0

1/08

01/0

7/08

01/0

1/09

01/0

7/09

01/0

1/10

01/0

7/10

01/0

1/11

01/0

7/11

01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14

Station 26 Cond…

0

2

4

6

8

10

12

14

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

01/0

1/07

01/0

7/07

01/0

1/08

01/0

7/08

01/0

1/09

01/0

7/09

01/0

1/10

01/0

7/10

01/0

1/11

01/0

7/11

01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14

Station 27 Cond…

0123456789

10

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

01/0

1/07

01/0

7/07

01/0

1/08

01/0

7/08

01/0

1/09

01/0

7/09

01/0

1/10

01/0

7/10

01/0

1/11

01/0

7/11

01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14

Station 28 Cond…


Page | 15

Temperature

0

5

10

15

20

25

30

35

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

01/0

1/07

01/0

7/07

01/0

1/08

01/0

7/08

01/0

1/09

01/0

7/09

01/0

1/10

01/0

7/10

01/0

1/11

01/0

7/11

01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14

Station 2 Temp…

0

5

10

15

20

25

30

35

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

01/0

1/07

01/0

7/07

01/0

1/08

01/0

7/08

01/0

1/09

01/0

7/09

01/0

1/10

01/0

7/10

01/0

1/11

01/0

7/11

01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14

Station 3 Temp…

0

5

10

15

20

25

30

35

40

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

01/0

1/07

01/0

7/07

01/0

1/08

01/0

7/08

01/0

1/09

01/0

7/09

01/0

1/10

01/0

7/10

01/0

1/11

01/0

7/11

01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14

Station 4 Temp…

05

10152025303540

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

01/0

1/07

01/0

7/07

01/0

1/08

01/0

7/08

01/0

1/09

01/0

7/09

01/0

1/10

01/0

7/10

01/0

1/11

01/0

7/11

01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14

Station 5 Temp…

0

5

10

15

20

25

30

35

40

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

01/0

1/07

01/0

7/07

01/0

1/08

01/0

7/08

01/0

1/09

01/0

7/09

01/0

1/10

01/0

7/10

01/0

1/11

01/0

7/11

01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14

Station 6 Temp…

0

5

10

15

20

25

30

35

40

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

01/0

1/07

01/0

7/07

01/0

1/08

01/0

7/08

01/0

1/09

01/0

7/09

01/0

1/10

01/0

7/10

01/0

1/11

01/0

7/11

01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14

Station 8 Temp…

0

5

10

15

20

25

30

35

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

01/0

1/07

01/0

7/07

01/0

1/08

01/0

7/08

01/0

1/09

01/0

7/09

01/0

1/10

01/0

7/10

01/0

1/11

01/0

7/11

01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14

Station 9 Temp…

0

5

10

15

20

25

30

35

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

01/0

1/07

01/0

7/07

01/0

1/08

01/0

7/08

01/0

1/09

01/0

7/09

01/0

1/10

01/0

7/10

01/0

1/11

01/0

7/11

01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14

Station 11 Temp…

0

5

10

15

20

25

30

35

40

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

01/0

1/07

01/0

7/07

01/0

1/08

01/0

7/08

01/0

1/09

01/0

7/09

01/0

1/10

01/0

7/10

01/0

1/11

01/0

7/11

01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14

Station 12 Temp…

0

5

10

15

20

25

30

35

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

01/0

1/07

01/0

7/07

01/0

1/08

01/0

7/08

01/0

1/09

01/0

7/09

01/0

1/10

01/0

7/10

01/0

1/11

01/0

7/11

01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14

Station 13 Temperature


Page | 16

0

5

10

15

20

25

30

35

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

01/0

1/07

01/0

7/07

01/0

1/08

01/0

7/08

01/0

1/09

01/0

7/09

01/0

1/10

01/0

7/10

01/0

1/11

01/0

7/11

01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14


0

5

10

15

20

25

30

35

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

01/0

1/07

01/0

7/07

01/0

1/08

01/0

7/08

01/0

1/09

01/0

7/09

01/0

1/10

01/0

7/10

01/0

1/11

01/0

7/11

01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14

Station 18 Temp…

0

5

10

15

20

25

30

35

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

01/0

1/07

01/0

7/07

01/0

1/08

01/0

7/08

01/0

1/09

01/0

7/09

01/0

1/10

01/0

7/10

01/0

1/11

01/0

7/11

01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14

Station 19 Temp…

0

5

10

15

20

25

30

35

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

01/0

1/07

01/0

7/07

01/0

1/08

01/0

7/08

01/0

1/09

01/0

7/09

01/0

1/10

01/0

7/10

01/0

1/11

01/0

7/11

01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14

Station 20 Temp…

0

5

10

15

20

25

30

35

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

01/0

1/07

01/0

7/07

01/0

1/08

01/0

7/08

01/0

1/09

01/0

7/09

01/0

1/10

01/0

7/10

01/0

1/11

01/0

7/11

01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14

Station 21 Temp…

0

5

10

15

20

25

30

35

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

01/0

1/07

01/0

7/07

01/0

1/08

01/0

7/08

01/0

1/09

01/0

7/09

01/0

1/10

01/0

7/10

01/0

1/11

01/0

7/11

01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14

Station 22 Temp…

0

5

10

15

20

25

30

35

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

01/0

1/07

01/0

7/07

01/0

1/08

01/0

7/08

01/0

1/09

01/0

7/09

01/0

1/10

01/0

7/10

01/0

1/11

01/0

7/11

01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14

Station 23 Temp…

0

5

10

15

20

25

30

35

40

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

01/0

1/07

01/0

7/07

01/0

1/08

01/0

7/08

01/0

1/09

01/0

7/09

01/0

1/10

01/0

7/10

01/0

1/11

01/0

7/11

01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14

Station 24 Temp…

0

5

10

15

20

25

30

35

40

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

01/0

1/07

01/0

7/07

01/0

1/08

01/0

7/08

01/0

1/09

01/0

7/09

01/0

1/10

01/0

7/10

01/0

1/11

01/0

7/11

01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14

Station 25 Temp…

0

5

10

15

20

25

30

35

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

01/0

1/07

01/0

7/07

01/0

1/08

01/0

7/08

01/0

1/09

01/0

7/09

01/0

1/10

01/0

7/10

01/0

1/11

01/0

7/11

01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14

Station 26 Temp…

0

5

10

15

20

25

30

35

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

01/0

1/07

01/0

7/07

01/0

1/08

01/0

7/08

01/0

1/09

01/0

7/09

01/0

1/10

01/0

7/10

01/0

1/11

01/0

7/11

01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14

Station 27 Temp…

0

5

10

15

20

25

30

35

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

01/0

1/07

01/0

7/07

01/0

1/08

01/0

7/08

01/0

1/09

01/0

7/09

01/0

1/10

01/0

7/10

01/0

1/11

01/0

7/11

01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14



Page | 17

DISSOLVED OXYGEN

0

2

4

6

8

10

12

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

01/0

1/07

01/0

7/07

01/0

1/08

01/0

7/08

01/0

1/09

01/0

7/09

01/0

1/10

01/0

7/10

01/0

1/11

01/0

7/11

01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14

Station 2 Dissolved

0123456789

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

01/0

1/07

01/0

7/07

01/0

1/08

01/0

7/08

01/0

1/09

01/0

7/09

01/0

1/10

01/0

7/10

01/0

1/11

01/0

7/11

01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14

Station 3 Dissolved

0

1

2

3

4

5

6

7

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

01/0

1/07

01/0

7/07

01/0

1/08

01/0

7/08

01/0

1/09

01/0

7/09

01/0

1/10

01/0

7/10

01/0

1/11

01/0

7/11

01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14

Station 4 Dissolved

0

2

4

6

8

10

12

14

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

01/0

1/07

01/0

7/07

01/0

1/08

01/0

7/08

01/0

1/09

01/0

7/09

01/0

1/10

01/0

7/10

01/0

1/11

01/0

7/11

01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14

Station 5 Dissolved

0123456789

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

01/0

1/07

01/0

7/07

01/0

1/08

01/0

7/08

01/0

1/09

01/0

7/09

01/0

1/10

01/0

7/10

01/0

1/11

01/0

7/11

01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14

Station 6 Dissolved

02468

1012141618

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

01/0

1/07

01/0

7/07

01/0

1/08

01/0

7/08

01/0

1/09

01/0

7/09

01/0

1/10

01/0

7/10

01/0

1/11

01/0

7/11

01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14

Station 8 Dissolved

02468

1012141618

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

01/0

1/07

01/0

7/07

01/0

1/08

01/0

7/08

01/0

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Station 9 Dissolved

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Station 11 Dissolved

0

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Page | 18

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05

1015202530354045

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Page | 19

SALINITY

0

0,01

0,02

0,03

0,04

0,05

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01/0

1/14

01/0

7/14

Station 2 S…

0

0,005

0,01

0,015

0,02

0,025

0,03

0,035

01/0

1/04

01/0

7/04

01/0

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01/0

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01/0

1/14

01/0

7/14

Station 3 S…

00,005

0,010,015

0,020,025

0,030,035

0,040,045

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

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01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14

Station 4 S…

00,5

11,5

22,5

33,5

44,5

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

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1/12

01/0

7/12

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1/13

01/0

7/13

01/0

1/14

01/0

7/14

Station 5 S…

0

0,5

1

1,5

2

2,5

3

3,5

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

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01/0

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01/0

7/13

01/0

1/14

01/0

7/14

Station 6 S…

00,020,040,060,08

0,10,120,140,160,18

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

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01/0

1/14

01/0

7/14

Station 8 S…

0

0,2

0,4

0,6

0,8

1

1,2

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

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1/06

01/0

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1/12

01/0

7/12

01/0

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01/0

7/13

01/0

1/14

01/0

7/14

Station 9 S…

0

0,1

0,2

0,3

0,4

0,5

0,6

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

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7/06

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7/11

01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14

Station 11 S…

0

0,05

0,1

0,15

0,2

0,25

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

01/0

1/07

01/0

7/07

01/0

1/08

01/0

7/08

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1/09

01/0

7/09

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7/10

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1/11

01/0

7/11

01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14

Station 12 S…

0

0,01

0,02

0,03

0,04

0,05

0,06

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

01/0

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01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14

Station 13 S…


Page | 20

0

0,2

0,4

0,6

0,8

1

1,2

1,4

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

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1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14

Station 14 S…

0

0,002

0,004

0,006

0,008

0,01

0,012

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

01/0

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1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14

Station 18 S…

0

0,002

0,004

0,006

0,008

0,01

0,012

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

01/0

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1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14

Station 19 S…

0

0,005

0,01

0,015

0,02

0,025

0,03

0,035

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

01/0

1/07

01/0

7/07

01/0

1/08

01/0

7/08

01/0

1/09

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7/10

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7/11

01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14

Station 20 S…

0

0,1

0,2

0,3

0,4

0,5

0,6

0,7

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

01/0

1/07

01/0

7/07

01/0

1/08

01/0

7/08

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1/09

01/0

7/09

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7/10

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1/11

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7/11

01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14

Station 21 S…

00,05

0,10,15

0,20,25

0,30,35

0,40,45

0,5

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

01/0

1/07

01/0

7/07

01/0

1/08

01/0

7/08

01/0

1/09

01/0

7/09

01/0

1/10

01/0

7/10

01/0

1/11

01/0

7/11

01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14

Station 22 S…

0

5

10

15

20

25

30

35

40

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

01/0

1/07

01/0

7/07

01/0

1/08

01/0

7/08

01/0

1/09

01/0

7/09

01/0

1/10

01/0

7/10

01/0

1/11

01/0

7/11

01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14

Station 23 S…

0

0,005

0,01

0,015

0,02

0,025

01/0

1/04

01/0

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Station 24 S…

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Station 25 S…

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Station 26 S…

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Station 27 S…

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Station 28 S…


Page | 21

TURBIDITY

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Station 2 Tu…

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Station 3 Tu…

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Station 4 Tu…

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Station 5 Tu…

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Station 6 Tu…

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Station 8 Tu…

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Station 9 Tu…

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Station 11 Tu…

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Station 12 Tu…

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Station 13 Tu…


Page | 22

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Station 14 Tu…

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Station 18 Tu…

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Station 19 Tu…

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Station 20 Tu…

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Station 21 Tu…

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Station 22 Tu…

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Station 23 Tu…

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Station 24 Tu…

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Station 25 Tu…

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Station 26 Tu…

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Station 27 Tu…

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Station 28 Tu…


Page | 23

BOD

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Station 2 Bio Chemical Oxgen …

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020406080

100120140160180

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COD

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Station 2 Chemical Oxigen …

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Page | 27

AMMONIA

0

1

2

3

4

5

6

7

01/0

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7/05

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7/11

01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14

Station 2 Ammoni…

0123456789

10

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

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01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14

Station 3 Ammoni…

0

5

10

15

20

25

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

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7/11

01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14

Station 4 Ammoni…

0

5

10

15

20

25

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

01/0

1/07

01/0

7/07

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01/0

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1/10

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01/0

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7/11

01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14

Station 5 Ammoni…

0

5

10

15

20

25

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

01/0

1/07

01/0

7/07

01/0

1/08

01/0

7/08

01/0

1/09

01/0

7/09

01/0

1/10

01/0

7/10

01/0

1/11

01/0

7/11

01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14

Station 6 Ammoni…

0

1

2

3

4

5

6

7

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

01/0

1/07

01/0

7/07

01/0

1/08

01/0

7/08

01/0

1/09

01/0

7/09

01/0

1/10

01/0

7/10

01/0

1/11

01/0

7/11

01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14

Station 8 Ammoni…

0

2

4

6

8

10

12

14

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

01/0

1/07

01/0

7/07

01/0

1/08

01/0

7/08

01/0

1/09

01/0

7/09

01/0

1/10

01/0

7/10

01/0

1/11

01/0

7/11

01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14

Station 9 Ammoni…

0

10

20

30

40

50

60

70

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

01/0

1/07

01/0

7/07

01/0

1/08

01/0

7/08

01/0

1/09

01/0

7/09

01/0

1/10

01/0

7/10

01/0

1/11

01/0

7/11

01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14

Station 11 Ammoni…

0

20

40

60

80

100

120

140

01/0

1/04

01/0

7/04

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1/05

01/0

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7/11

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7/12

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7/13

01/0

1/14

01/0

7/14


0

20

40

60

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140

01/0

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7/05

01/0

1/06

01/0

7/06

01/0

1/07

01/0

7/07

01/0

1/08

01/0

7/08

01/0

1/09

01/0

7/09

01/0

1/10

01/0

7/10

01/0

1/11

01/0

7/11

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01/0

7/14



Page | 28

0

2

4

6

8

10

12

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

01/0

1/07

01/0

7/07

01/0

1/08

01/0

7/08

01/0

1/09

01/0

7/09

01/0

1/10

01/0

7/10

01/0

1/11

01/0

7/11

01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14


0

0,5

1

1,5

2

2,5

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

01/0

1/07

01/0

7/07

01/0

1/08

01/0

7/08

01/0

1/09

01/0

7/09

01/0

1/10

01/0

7/10

01/0

1/11

01/0

7/11

01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14


0

0,5

1

1,5

2

2,5

3

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

01/0

1/07

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7/07

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7/11

01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14


00,20,40,60,8

11,21,41,61,8

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

01/0

1/07

01/0

7/07

01/0

1/08

01/0

7/08

01/0

1/09

01/0

7/09

01/0

1/10

01/0

7/10

01/0

1/11

01/0

7/11

01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14


0123456789

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

01/0

1/07

01/0

7/07

01/0

1/08

01/0

7/08

01/0

1/09

01/0

7/09

01/0

1/10

01/0

7/10

01/0

1/11

01/0

7/11

01/0

1/12

01/0

7/12

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01/0

7/13

01/0

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01/0

7/14


0

10

20

30

40

50

60

70

01/0

1/04

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7/04

01/0

1/05

01/0

7/05

01/0

1/06

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7/06

01/0

1/07

01/0

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01/0

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1/09

01/0

7/09

01/0

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7/10

01/0

1/11

01/0

7/11

01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14


0123456789

10

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

01/0

1/07

01/0

7/07

01/0

1/08

01/0

7/08

01/0

1/09

01/0

7/09

01/0

1/10

01/0

7/10

01/0

1/11

01/0

7/11

01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14


02468

1012141618

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

01/0

1/07

01/0

7/07

01/0

1/08

01/0

7/08

01/0

1/09

01/0

7/09

01/0

1/10

01/0

7/10

01/0

1/11

01/0

7/11

01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14


0

10

20

30

40

50

60

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

01/0

1/07

01/0

7/07

01/0

1/08

01/0

7/08

01/0

1/09

01/0

7/09

01/0

1/10

01/0

7/10

01/0

1/11

01/0

7/11

01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14


0

5

10

15

20

25

30

35

40

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

01/0

1/07

01/0

7/07

01/0

1/08

01/0

7/08

01/0

1/09

01/0

7/09

01/0

1/10

01/0

7/10

01/0

1/11

01/0

7/11

01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14


0

20

40

60

80

100

120

140

160

01/0

…

01/0

…

01/0

…

01/0

…

01/0

…

01/0

…

01/0

…

01/0

…

01/0

…

01/0

…

01/0

…

01/0

…

01/0

…

01/0

…

01/0

…

01/0

…

01/0

…

01/0

…

01/0

…

01/0

…

01/0

…

01/0

…


0

20

40

60

80

100

120

140

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

01/0

1/07

01/0

7/07

01/0

1/08

01/0

7/08

01/0

1/09

01/0

7/09

01/0

1/10

01/0

7/10

01/0

1/11

01/0

7/11

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Page | 29

NITRATE

0

0,5

1

1,5

2

2,5

3

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

01/0

1/07

01/0

7/07

01/0

1/08

01/0

7/08

01/0

1/09

01/0

7/09

01/0

1/10

01/0

7/10

01/0

1/11

01/0

7/11

01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14

Station 2 Nitrate …

0

0,5

1

1,5

2

2,5

3

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

01/0

1/07

01/0

7/07

01/0

1/08

01/0

7/08

01/0

1/09

01/0

7/09

01/0

1/10

01/0

7/10

01/0

1/11

01/0

7/11

01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14


00,10,20,30,40,50,60,70,80,9

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

01/0

1/07

01/0

7/07

01/0

1/08

01/0

7/08

01/0

1/09

01/0

7/09

01/0

1/10

01/0

7/10

01/0

1/11

01/0

7/11

01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14


0

0,1

0,2

0,3

0,4

0,5

0,6

0,7

0,8

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

01/0

1/07

01/0

7/07

01/0

1/08

01/0

7/08

01/0

1/09

01/0

7/09

01/0

1/10

01/0

7/10

01/0

1/11

01/0

7/11

01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14


0

0,2

0,4

0,6

0,8

1

1,2

1,4

1,6

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

01/0

1/07

01/0

7/07

01/0

1/08

01/0

7/08

01/0

1/09

01/0

7/09

01/0

1/10

01/0

7/10

01/0

1/11

01/0

7/11

01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14


0

0,2

0,4

0,6

0,8

1

1,2

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

01/0

1/07

01/0

7/07

01/0

1/08

01/0

7/08

01/0

1/09

01/0

7/09

01/0

1/10

01/0

7/10

01/0

1/11

01/0

7/11

01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14


0

0,2

0,4

0,6

0,8

1

1,2

01/0

1/04

01/0

7/04

01/0

1/05

01/0

7/05

01/0

1/06

01/0

7/06

01/0

1/07

01/0

7/07

01/0

1/08

01/0

7/08

01/0

1/09

01/0

7/09

01/0

1/10

01/0

7/10

01/0

1/11

01/0

7/11

01/0

1/12

01/0

7/12

01/0

1/13

01/0

7/13

01/0

1/14

01/0

7/14


0

0,2

0,4

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2

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1

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02468

101214161820

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Page | 34

Appendix 4 Water quality distribution in Metro Colombo wetlands catchement

Map1. Water quality assessment May 2015 (WFD Score) and Wetland Code (see Appendix1 from Final Report : Characterization of the wetlands of CMR)

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