Case of Lake Ranomafana in Antsirabe

MINISTRY OF HIGHER EDUCATION and SCIENTIFIC RESEARCH ------UNIVERSITE OF TOLIARA ------Faculty of Science ------Department of Chemistry ------

A thesis presented to the University of Toliara in fulfilment of the requirement for the degree of

DOCTOR OF SCIENCE Option: Lake Management and Wastewater Treatment

LAKE REMEDIATION TECHNIQUES: CASE OF LAKE RANOMAFANA IN ANTSIRABE

Presented by Yves Jean Michel MONG

Defended on December 2, 2011

Jury: Pr. RANAIVOSON Eulalie (IHSM of Toliara) President Pr. RANAIVOSON Eulalie (IHSM of Toliara) Internal Reporter Dr. YDSTEBØ Leif (IVAR/University of Stavanger) External Reporter Dr. RABENEVANANA Man Wai (IHSM) Director of thesis Pr. RAVELONAND RO Pierre (CNRE) Examiner Pr. BILSTAD Torleiv (University of Stavanger) Examiner Pr. KOMMEDAL Roald (University of Stavanger) Examiner

Declarations

This thesis is the result of my own work and includes nothing which is the outcome of work done in collaboration except field and lab work, jointly carried out with the assistance and help of two former Masters of Science students from the University of Stavanger, Norway.

This thesis is not substantially the same as any that I have submitted, or, is being concurrently submitted for a degree or diploma or other qualification at the University of Toliara or any other University or similar institution. No substantial part of my thesis has already been submitted, or, is being concurrently submitted for any such degree, diploma or other qualification at the University of Toliara or any other University or similar institution.

Yves Jn. M. MONG

Acknowledgements

I am most grateful to the coordination members of NUFU project, Pr Torleiv Bilstad (University of Stavanger) and Dr. RABENEVANANA Man Wai (Fishery and Marine Science Institute of Toliara), , for their inspiration, input, and advice on this project from the proposal up to the thesis defence.

I would like to thank especially my scientific advisor, Dr. Leif Ydstebø (partial time at the University of Stavanger and full time at Water and Renovation Utility of Stavanger Region or IVAR), for his supervision and mentoring on this project. I am grateful for the opportunity to complete a research project with his guidance and motivation.

I am thankful to all members of Jury, especially Pr RANAIVOSON Eulalie, who accepted to sit and evaluate the scientific value and originality of the present work.

Thanks go to the members of NUFU project evaluation committee, Pr Gerard LASSERE, Pr MARA Edouard, Dr Jacky RAZANOELISOA, Dr John BEMIASA, for their comments and advise on how to improve the realisation of this project.

I acknowledge the needed assistance from Mrs RASOLOFOMANANA Lilia and Anne Lise HEGGO, former Masters of Science graduates from the University of Stavanger, without whom any field data would be available. I greatly appreciated their time and efforts in the field and lab.

To the director of National Environmental Research Centre (CNRE), Pr RAVELONANDRO H. Pierre, who accepted to sit as member of Jury, and all colleagues working at the Water testing lab, I am grateful for their support and encouragement.

Funding to this project was provided by NUFU project, whose members have always believed in me and the potential I have to fulfil this project up to its materialization. So, I express my thanks and gratitude to Norwegian Government through the NUFU project.

I am grateful for the love and support from my family and wife, Irène. Their patience and reassurance helped generate confidence and motivation for completing this thesis project.

Last but not least, I am thankful to Madam RAVAOARISOA Léa for her commitment to help resolve whatever kind of problem related to our academic activities. Madam Léa always responds present for us and our problems, especially financial.

Abstract

Lake Ranomafana is a very shallow tropical, urban, man-made lake located in the town centre of Antsirabe city. Many years since (probably by the 1970s) this artificial lake has experienced increasing severe physical alteration and water quality problems (green colour, bad smell), characteristics of eutrophic status, caused by discharge of domestic wastewater without any prior treatment. Furthermore, the lake also is regularly subject to invasion of water hyacinth. These water quality problems are affecting two sensitive social and economical areas related to the development of the municipality of Antsirabe, namely: public health and tourism.

The mayor of Antsirabe, during a meeting with the delegation of NUFU project, raised her concern about the related impacts of the lake status degradation. The NUFU project has been called upon to clean and find out any site specific alternative approaches to restoring the lake status.

This project, through preliminary water quality surveys (2005 and 2008) and water quality monitoring (2009) identified important suspended solids loading, nutrients enrichment, and consequently algal bloom, and accumulation of inert organic matter as the main stressors of the lake.

A simplified lake management model was developed, using some of the field data, to help determine different scenarios of remediation appropriate for the lake current conditions. The model was used to evaluate not only the current conditions of the lake, but also several management alternative approaches for the reduction of the different external and internal loadings into the lake.

The results of the different simulations suggest that the reduction of soluble reactive phosphate, ammonia, and dissolved organic matter as COD on the one hand, and the reduction of sediment internal loading on the other hand would achieve significant positive change in the current altered health of the lake. But doing nothing, in addition to the effect of global warming leading to deficit of rainfall, would condemn the lake to slowly but surely return back to its original nature: a swampy land. Key words: Lake Ranomafana, lake management model, lake status degradation, loading, water quality, remediation, restoration

Résumé

Le Lac Ranomafana est un lac artificiel, tropical, peu profond, et situé en zone urbaine dans la partie centrale de la ville d’Antsirabe. Il y a plusieurs années de cela (probablement dans les années 1970), ce lac a été l’objet d’une sévère altération physique de plus en plus avancée, accompagnée de problèmes de dégradation de la qualité de l’eau (couleur verte, mauvaise odeur), qui sont des signes caractéristiques de problème d’eutrophisation. Le rejet d’eaux usées domestiques sans traitement préalable en est suspecté d’être l’origine de ce problème. Par ailleurs, le lac est aussi régulièrement envahi par une colonie de jacinthes d’eau. Ces problèmes affectent surtout et en particulier deux domaines sensibles liés au développement de la municipalité d’Antsirabe à savoir : la santé publique et le tourisme.

Aussi, le maire de la ville d’Antsirabe, au cours d’une rencontre avec une délégation du projet NUFU (Projet Norvégien pour l’Enseignement supérieur), a exprimé sa vive préoccupation concernant les impacts de la dégradation de l’état du lac. De ce sens, le projet NUFU a été sollicité pour résoudre le problème du lac et surtout trouver des approches spécifiquement adaptées aux conditions locales en vue de sa restauration.

La présente étude, à travers des enquêtes préliminaires réalisées en 2005 et en 2008 et suivies par une campagne de suivi (monitoring) durant presque l’année 2009, a identifié le transport important de matière solides en suspension, l’apport, plus que nécessaire, en éléments nutritifs causant la prolifération d’algues, et l’accumulation de matières organiques inertes comme étant les principales sources de pression sur le lac.

De ce fait, un modèle simplifié conçu pour la gestion du lac a été développé à partir de l’utilisation des données obtenues sur terrain afin de déterminer les différents scenarios appropriés, pour la restauration du lac dans ses conditions actuelles d’existence. Le modèle a été utilisé pour évaluer non seulement les conditions actuelles du lac, mais également la capacité des différentes approches alternatives à réduire les différents apports externes et internes. Mots clés : Lac Ranomafana, modèle de gestion de lacs, état de dégradation du lac, charge, qualité de l’eau, rémédiation, restauration.

Tables of contents

CHAPTER 1 Introduction ...... 1 1.1. Historical context of the city of Antsirabe, location of the site study ...... 1 1.1.1. Antsirabe, the city of salt ...... 1 1.1.2. Origin of the Lake Ranomafana ...... 3 1.2. Context administrative, Social, and economical of Antsirabe ...... 5 1.3. Problem statement ...... 9 1.4. Objectives of the project ...... 12 1.5. Thesis layout ...... 13 1.6. Literature review ...... 13 1.6.1. Eutrophication process ...... 15 1.6.2. Trophic status ...... 17 1.6.3. Limiting factor...... 19 1.6.4. Carrying capacity ...... 20 1.6.5. Modelling ...... 21 1.6.6. Water and Wastewater treatment ...... 22 CHAPTER 2 Materials and methods ...... 23 2.1. Field work and study site ...... 23 2.1.1. Design of the monitoring programme ...... 23 2.1.1.1. Objective and principle ...... 23 2.1.1.2. Description of the study site: Lake Ranomafana ...... 24 2.1.1.2.1. Physical environment ...... 24 2.1.1.3. Selection of the measurement and sampling stations ...... 28 2.1.1.4. Monitoring media and measured variables ...... 30 2.1.1.5. Frequency and timing of sampling ...... 31 2.1.1.6. Field work and sample collection...... 31 2.1.1.6.1. Water ...... 31 2.1.1.6.2. Sediment ...... 33 2.1.1.6.3. Description of the field measurement ...... 33 2.2. Laboratory analyses and analytical methods ...... 34 2.2.1. Analyses of water samples ...... 35 2.2.1.1. Determination of biochemical oxygen demand (BOD) ...... 35 2.2.1.2. Determination of chemical oxygen demand (COD) ...... 36

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2.2.1.3. Determination of nitrogen compounds ...... 37 2.2.1.3.1. Nitrate ...... 37 2.2.1.3.2. Nitrite ...... 37 2.2.1.3.3. Total Kjeldahl nitrogen (TKN) ...... 38 2.2.1.4. Determination of phosphorus compounds ...... 38 2.2.1.4.1. Reactive phosphate ...... 39 2.2.1.4.2. Total phosphorus ...... 39 2.2.1.5. Solids analyses ...... 39 2.2.1.5.1. Total suspended solids (TSS) and volatile solids (VSS) ...... 39 2.2.1.5.2. Total solids (TS) and total volatile solids (TVS) ...... 40 2.2.1.6. Analysis of chlorophyll a ...... 41 2.2.1.7. Alkalinity ...... 42 2.2.1.8. Silica ...... 42 2.2.2. Statistical analyses ...... 42 2.2.3. Analyses of sediment samples ...... 42 2.2.3.1. Texture and particle size ...... 43 2.2.3.2. Total solids (TS) and total volatile solids (TVS) ...... 43 2.2.3.3. Determination of phosphorus compounds ...... 43 2.2.3.3.1. Dissolved orthophosphate ...... 44 2.2.3.3.2. Total phosphorus ...... 44 2.2.3.4. Determination of total nitrogen ...... 44 2.2.3.5. Determination of iron and manganese ...... 44 2.2.3.6. Sediment nutrients flux ...... 45 2.2.4. Assurance quality (AQ) and Quality control (QC) of the CNRE water testing laboratory 46 2.3. Development of Lake Ranomafana model ...... 46 2.3.1. General considerations...... 46 2.3.2. Overview of the modelling platform AQUASIM ...... 48 2.3.3. Conception of the system ...... 50 2.3.4. Main state variables ...... 51 2.3.4.1. Oxygen ...... 52 2.3.4.2. Nitrogen ...... 52 2.3.4.3. Phosphorus ...... 54 2.3.4.4. Dissolved organic matter as COD ...... 55

2.3.4.5. Phytoplankton ...... 56 2.3.4.6. Heterotrophic bacteria ...... 57 2.3.4.7. Autotrophic bacteria ...... 57 CHAPTER 3 Results and Discussion ...... 59 3.1. External loadings to the lake ...... 59 3.1.1. Preliminary Survey of external loadings in October and November 2005 ...... 60 3.1.1.1. Influents discharge ...... 61 3.1.1.2. General variables ...... 62 3.1.1.3. Organic matter ...... 63 3.1.1.4. Nutrients ...... 63 3.1.2. Preliminary assessment of external loadings in June 2008 ...... 63 3.1.2.1. General variables ...... 64 3.1.2.2. Nutrients ...... 65 3.1.2.3. Organic matter ...... 65 3.1.3. Characterization of external loadings through monitoring in 2009 ...... 65 3.1.3.1. General variable ...... 67 3.1.3.2. Nutrients ...... 68 3.1.3.3. Organic compounds ...... 71 3.1.4. Rough estimates of average annual nutrients and organic loads in Lake Ranomafana 72 3.1.5. Discussion ...... 73 3.1.5.1. Variation of the influents discharge ...... 74 3.1.5.2. Physical patterns of discharged influents ...... 75 3.1.5.3. Variation of nutrients in influents discharged ...... 77 3.1.5.4. Nature and pattern of organic loads ...... 78 3.1.5.5. Compliance of influents loads to national existing effluent standard (Decree N°2003/464) ...... 79 3.2. Characterisation of Lake Ranomafana current conditions ...... 79 3.2.1. Characterisation of Lake Ranomafana physical conditions ...... 80 3.2.1.1. Absorption of light and light penetration ...... 82 3.2.1.2. Water temperatures ...... 85 3.2.2. Characterisation of Lake Ranomafana chemical conditions ...... 87 3.2.2.1. Conductivity ...... 87 3.2.2.2. Turbidity ...... 88 3.2.2.3. pH of Lake Ranomafana water ...... 89

3.2.2.4. Dissolved oxygen of the lake water ...... 90 3.2.2.5. Daytime variation of dissolved oxygen (DO) and oxygen saturation in the lake... 93 3.2.2.6. Level and variation of nutrients concentration in the lake water ...... 96 3.2.2.6.1. Nitrogen compounds ...... 96 3.2.2.6.2. Phosphorus compounds ...... 100 3.2.2.6.3. Other nutrients ...... 103 3.2.2.7. Level and variation of organic compounds in the lake ...... 103 3.2.2.7.1. Biochemical oxygen demand (BOD) ...... 104 3.2.2.7.2. Chemical oxygen demand (COD) ...... 105 3.2.2.8. Variation of total solids and suspended solids ...... 106 3.2.2.8.1. Total solids ...... 107 3.2.2.8.2. Nature of total solids in the lake water ...... 108 3.2.2.8.3. Total suspended solids ...... 110 3.2.2.8.4. Nature of Total suspended solids in the lake ...... 111 3.2.2.8.5. Total dissolved solids ...... 112 3.2.2.8.6. Alkalinity ...... 114 3.2.3. Characterisation of Lake Ranomafana biological condition ...... 115 3.2.3.1. Variation of the chlorophyll a ...... 115 3.2.3.2. Other phytoplanktonic communities ...... 116 3.2.3.3. Fish and crayfish ...... 117 3.2.3.4. Macrovegetation ...... 118 3.2.4. Characterisation of Lake Ranomafana sediments chemical conditions ...... 119 3.2.4.1. Nutrients ...... 120 3.2.4.1.1. Total nitrogen ...... 120 3.2.4.1.2. Soluble reactive phosphate ...... 121 3.2.4.1.3. Total phosphorus ...... 122 3.2.4.1.4. Other inorganic compounds ...... 123 3.2.4.2. Total Solids and total volatile solids ...... 124 3.2.4.3. Characteristics and nature of Lake Ranomafana sediments ...... 126 3.2.5. Discussion ...... 128 3.2.5.1. Determinants of the physical shape of the lake ...... 128 3.2.5.2. Determinants of the lake chemical characteristics...... 130 3.2.5.2.1. Conductivity ...... 130 3.2.5.2.2. Turbidity ...... 131

3.2.5.2.3. pH and alkalinity ...... 131 3.2.5.2.4. Dissolved oxygen ...... 133 3.2.5.2.5. Nutrients ...... 135 3.2.5.2.6. Organic compounds ...... 139 3.2.5.2.7. Carrying capacity of Lake Ranomafana...... 140 3.2.5.3. Characterisation of Lake Ranomafana trophic status ...... 142 3.3. Partial conclusion ...... 146 3.3.1. Current condition of Lake Ranomafana ...... 146 3.3.1.1. Physical conditions...... 146 3.3.1.2. Chemical conditions ...... 147 3.3.1.2.1. Chemical characteristics of external loading ...... 147 3.3.1.2.2. Chemical characteristics of the lake water...... 148 3.3.1.2.3. Biological conditions ...... 150 3.3.1.2.4. Sediment characteristics ...... 151 3.3.1.2.5. Trophic status and carrying capacity ...... 151 CHAPTER 4 Modelling Lake Ranomafana management scenarios ...... 152 4.1. Simulation of the lake behaviour under current conditions ...... 152 4.1.1. Growth of algae and oxygen production ...... 152 4.1.2. Growth of autotrophic bacteria ...... 154 4.1.3. Growth of heterotrophic bacteria ...... 155 4.1.4. Dissolved organic matter as COD ...... 156

4.1.5. Nutrients as PO 4, NH 4, and NO 3 ...... 157 4.1.6. Accumulation of sediment and Particulate organic matter (slowly biodegradable COD) 158 4.1.7. Partial conclusion ...... 159 4.1.8. Limitation of the model ...... 160 4.2. Simulation with external loading treatment by reducing 50% of pollutants loading ...... 160 4.2.1. Growth of algae and oxygen production ...... 161 4.2.2. Growth of autotrophic bacteria ...... 161 4.2.3. Growth of heterotrophic bacteria ...... 162 4.2.4. Dissolved organic matter as COD ...... 163

4.2.5. Nutrients as PO 4, NH 4, and NO3 ...... 164 4.2.6. Accumulation of sediments and slowly biodegradable organic matter ...... 165 4.3. Simulation with external loading treatment by reducing 50% of phosphorus loading .... 165

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4.3.1. Nitrogen compounds ...... 165 4.3.2. Dissolved organic matter as COD ...... 166 4.3.3. Accumulation of inert organic matter as sediment and slow biodegradable organic matter 167 4.4. Simulation with external loading treatment by reducing 50% of dissolved organic loading (COD) 168 4.4.1. Algae growth and oxygen production ...... 168 4.4.2. Growth of autotrophic bacteria ...... 168 4.4.3. Growth of heterotrophic bacteria ...... 169 4.4.4. Dissolved organic matter as COD ...... 170 4.4.5. Nutrients ...... 170 4.4.6. Accumulation of inert organic matter and slow biodegradable organic matter ...... 171 4.4.7. Available applied wastewater treatment methods ...... 172 4.4.7.1. Waste stabilisation ponds (WSPs) ...... 174 4.4.7.2. Constructed wetland...... 175 4.5. Simulation of in-lake treatment ...... 177 4.5.1. Algae growth and production of oxygen ...... 177 4.5.2. Growth of heterotrophic bacteria ...... 178 4.5.3. Dissolved organic matter as COD ...... 179 4.5.4. Nutrients ...... 180 4.5.5. Accumulation of inert organic matter as sediment and slow biodegradable organic matter 180 4.5.6. Internal measures for nutrient and algal control ...... 181 4.6. Simulation of combined reduction of external and internal loadings ...... 183 4.6.1. Growth of algae and production of oxygen ...... 183 4.6.2. Growth of heterotrophic bacteria ...... 184 4.6.3. Dissolved organic matter ...... 185 4.6.4. Nutrients ...... 185 4.6.5. Accumulation of inert organic matter and slow biodegradable organic matter ...... 186 4.6.6. Partial conclusion presenting the different alternatives ...... 187

4.6.6.1. Reduction of external loading by 50% reduction of PO 4, NH 4, and COD simultaneously ...... 187 4.6.6.2. Reduction of phosphorus as phosphate by 50% ...... 188 4.6.6.3. Reduction of COD external loading by 50% ...... 188 4.6.6.4. In-lake treatment by reduction of internal loading ...... 188

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4.6.6.5. Combine reduction of external and internal loadings ...... 189 CHAPTER 5 Cost-benefit analysis of Lake Ranomafana remediation ...... 190 5.1. Remediation of the Lake Ranomafana ...... 190 CHAPTER 6 Synthesis of modelling results ...... 193 6.1. The main stressors of the lake ...... 193 6.2. Scenarios of Lake Ranomafana remediation ...... 193 CHAPTER 7 General conclusions ...... 197 7.1. Final conclusion ...... 197 7.2. Further research ...... 198

List of Tables

Table 1: Result of analysis of mineral water (1000 g) from spring water of Antsirabe ...... 3 Table 2: Antsirabe Population growth prediction ...... 7 Table 3: Sanitation practices in the city of Antsirabe ...... 8 Table 4: Monthly Insulation pattern ...... 27 Table 5: Main characteristics of sampling stations ...... 29 Table 6: Media and variables used for monitoring Lake Ranomafana ...... 30 Table 7: Size of sample and preservative treatments for transport and storage ...... 32 Table 8: Oxygen process kinetics ...... 52 Table 9: ammoniacal nitrogen processes kinetics ...... 53 Table 10: Phosphorus processes kinetics ...... 54 Table 11: Organic matter (COD) from detritus process kinetic ...... 56 Table 12: Algae biologic processes kinetic rate ...... 56 Table 13: Heterotrophic bacteria processes kinetic rate ...... 57 Table 14: Autotrophic bacteria processes kinetic rate ...... 57 Table 15: Symbols used in kinetics rate ...... 58 Table 16: Summary of filed measurement performed in October and November 2005 ...... 62 Table 17: Summary of measurement carried out in June 2008 ...... 64 Table 18: Range and mean concentrations of soluble phosphate (reactive phosphate) and inorganic nitrogen found in influents discharged into the lake ...... 68 Table 19: Variation of Total Kjeldahl Nitrogen concentration as function of sampling period and season ...... 69 Table 20: Estimated gross annual nutrient and organic loads on Lake Ranomafana ...... 73 Table 21: Watershed dwellers water consumption and estimated domestic wastewater generated . 74 Table 22: Sanitation practice within municipality of Antsirabe ...... 75 Table 23: Variation of ratios of organic matter in influents as function of season and origin ...... 78 Table 24: Extract from the National Standard for wastewater discharge ...... 79 Table 25: Physical features of Lake Ranomafana ...... 80 Table 26: Variation of depth measured from sampling stations ...... 81 Table 27: Lake Ranomafana water turbidity ...... 89 Table 28: Variation of pH with season and sampling time ...... 89 Table 29: Average daytime variation of dissolved oxygen, saturation of oxygen, pH, and temperature...... 95 Table 30: Quality of the lake water during invasion of water hyacinth ...... 119 Table 31: Means and ranges (in parentheses) nutrients content of surface sediments from the 5 stations ...... 123 Table 32: Iron and Manganese contents of Lake Ranomafana sediments ...... 124 Table 33: Texture of Lake Ranomafan sediments as a function of clay, silt, and sand contents ...... 127 Table 34: Concentrations of phosphorus, nitrogen in VSS and N/P ratios...... 142 Table 35: Trophic state of Lake Ranomafana ...... 143 Table 36: Carlson’s trophic State Index calculated from Secchi depth and Chlorophyll a, and Total phosphorus ...... 144 Table 37: Generally applied wastewater treatment methods (UNEP, 2002) ...... 172

Table 38: Efficiency ratio (0.0 - 1.0) matrix relating pollution parameters and wastewater treatment methods (after Jansen and Jørgensen, 1988) (UNEP, 2002) ...... 174 Table 39: Vegetation type and water column contact in constructed wetlands (Kayombo et al., 2005) ...... 177 Table 40: Available techniques used for sediments remediation ...... 182 Table 41: Economic effects of eutrophication and benefits of reducing eutrophication (adapted from UNEP, 2002) ...... 191 Table 42: Synthesis of management scenarios for the rmediation of Lake Ranomafana...... 194

List of Figures

Figure 1: Antsirabe seen from south (1885), Source (Dahl, 2010) ...... 1 Figure 2: The hot spring Ranomafana, Source (Dahl, 2010) ...... 2 Figure 3: Ranomafana bathing houses, Source (Dahl, 2010) ...... 2 Figure 4: Originally location of Lake Ranomafana in a swampy zone, Source (Dahl, 2010) ...... 4 Figure 5: Panorama view of Lake Ranomafana and surrounding (1946), Source (Dahl, 2010) ...... 4 Figure 6: Panorama from Ranomafana (1946), Source (Dahl, 2010) ...... 5 Figure 7: Location of the city of Antsirabe ...... 6 Figure 8: Lake Ranomafana as final destination of domestic garbage ...... 8 Figure 9: Catching fishes and "Foza orana" (invading crustecian specie, Procambarus sp ) ...... 11 Figure 10: The city of Antsirabe with infrastructure and sanitation facilities, Source: SOMEAH/SOGREA (2004) ...... 11 Figure 11: Southwestern traditional fishing pirogue used for field work ...... 24 Figure 12: Lake Ranomafana and surrounding watershed (Google Earth, 2011) ...... 25 Figure 13: Monthly mean temperature variation ( source: Direction Générale de la Météorologie ) .... 26 Figure 14: Monthly rainfall variation ( Source: Direction Générale de la Météorologie ) ...... 27 Figure 15: Annual wind regimes in Antsirabe (source www.weatheronline.co.uk) ...... 28 Figure 16: Location of sampling stations ( Google Earth, 2011 ) ...... 29 Figure 17: Secchi disc for transparency measurement ...... 34 Figure 18: Schematic presentation of media quality monitoring ...... 35 Figure 19: Materials for testing nutrient flux between sediment and water column ...... 45 Figure 20: The modelling program "AQUASIM 2.0" ...... 49 Figure 21: Conceptual view of Lake Ranomafana ...... 50 Figure 22: Conceptual diagram of Lake Ranomafana ( modified from Sagehashi and Sakoda et al, 2001 ) ...... 51 Figure 23: Location of inlets to the lake ...... 60 Figure 24: Permanent main inlets (northeast and northwest) ...... 66 Figure 25: Total suspended solids loading from the two main inlets ...... 67 Figure 26: Nature of suspended solids discharged in the lake ...... 68 Figure 27: Variation of total nitrogen and total phosphorus loading as a function of sampling period ...... 70 Figure 28: Variation of organic matter loading as a function of sampling period ...... 72 Figure 29: Bathymetric map of Lake Ranomafana (February 2009) ...... 82 Figure 30: Seasonal variation of light extinction coefficient and Secchi depth in the morning ...... 83 Figure 31: Seasonal variation of light extinction coefficient and Secchi depth in the afternoon ...... 84 Figure 32: Seasonal variation of Lake Ranomafana's water temperatures ...... 86 Figure 33: Seasonal Variation of Lake Ranomafana water conductivity ...... 88 Figure 34: Variation of surface and bottom dissolved oxygen as a function of sampling station, season and time...... 92 Figure 35: Location of the daytime monitoring of dissolved oxygen, temperature, and pH...... 93 Figure 36: Variation of nitrate concentrations as a function of sampling period, time and sampling station...... 97 Figure 37: Variation of Total Kjeldahl nitrogen as a function of sampling period, time and sampling station...... 98

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Figure 38: Variation of total nitrogen as a function of stations, period, of sampling, and time...... 100 Figure 39: Variation of reactive phosphate as a function of sampling station, period, and time of sampling ...... 101 Figure 40: Variation of Total phosphorus as a function of sampling stations, period, and time of sampling ...... 102 Figure 41: Variation of Biochemical oxygen demand as a function of station location, period, and time of sampling ...... 105 Figure 42: Variation of chemical oxygen demand as a function of sites location, period, and time of sampling ...... 106 Figure 43: Variation of Total solids as a function of sampling stations, period, and time of sampling ...... 108 Figure 44: Variation of Total solids composition as a function of season of sampling ...... 109 Figure 45: Variation of Total suspended solids as a function of sites location, season, and time of sampling ...... 111 Figure 46: Variation of organic fraction in the suspended solids of the lake water as a function site, period, and time of sampling ...... 112 Figure 47: Variation of Total dissolved solids (TDS) as a function sites location, period, and time of sampling, and variation of Total dissolved volatile solids (TDVS) content ...... 114 Figure 48: Variation of chlorophyll a concentration as a function of sites location, period, and time of sampling ...... 116 Figure 49: "Foza orana" ( Procambarus sp ) collected nearby north-eastern effluent inlet, into the littoral vegetation ...... 118 Figure 50: Water hyacinth covering the whole lake surface ...... 119 Figure 51: Variation of Total nitrogen in sediments surface layers as a function of stations location and sampling period ...... 121 Figure 52: Variation of Soluble reactive phosphate in sediments surface layers as a function of sites location and sampling period ...... 122 Figure 53: Variation of Total phosphorus as a function of sites location and sampling period ...... 123 Figure 54: Variation of Total solids and percentages of Total volatile solids in sediments according to season and sites location ...... 126 Figure 55: Sediment particle distribution (diagram according to US Department of Agriculture Textural Classification, Kim, Choi et al, 2003 ) ...... 127 Figure 56: Seasonal variation of average Secchi depths ...... 129 Figure 57: Correlation between Secchi depth and logarithm of average Total suspended solids ...... 129 Figure 58: Seasonal variation of average ambient temperature, average morning, and afternoon lake water temperature ...... 130 Figure 59: Seasonal variation of average pH values as a function of sampling level (morning) ...... 133 Figure 60: Variation of Dissolved oxygen and Chlorophyll a generated by phytoplanktonic algae (Morning and Afternoon) ...... 134 Figure 61: Variation of oxygen and pH in surface and bottom levels (Morning) ...... 135 Figure 62: Variation of nutrients concentrations with chlorophyll a (Morning and Afternoon) ...... 138 Figure 63: Variation of TN/TP ratio with chlorophyll a (Morning and Afternoon) ...... 139 Figure 64: Variation of COD/VSS ratios as function of season and time (average values) ...... 140 Figure 65: Potential nutrient-limited and non-nutrient-limited causes for deviation of biomass-based trophic state index, in the morning and afternoon (Wetzel, 2001) ...... 145

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Figure 66: Simulation of algae growth and oxygen production under current conditions ...... 154 Figure 67: Simulation of autotrophic bacteria growth under current conditions...... 155 Figure 68: Simulation of heterotrophic bacteria growth under current conditions ...... 156 Figure 69: Simulation of chemical oxygen demand (COD) under current conditions ...... 157 Figure 70: Simulation of nutrients (PO4 and NH4/NO3) consumption under current conditions ..... 158 Figure 71: Simulation of production and accumulation of inert and particulate organic matter under current conditions ...... 159 Figure 72: Simulation of algae growth and oxygen production under reduction of 50% of external pollutants...... 161 Figure 73: Simulation of autotrophic bacteria growth under 50% reduction of external loading...... 162 Figure 74: simulation of heterotrophic bacteria growth under 50% reduction of external loading .. 163 Figure 75: Simulation of the fate of dissolved organic matter as COD under 50% reduction of external loading ...... 163 Figure 76: Simulation of nutrients availability under 50% reduction of external loading ...... 164 Figure 77: Simulation of the accumulation of sediments and slow biodegradable organic matter under 50% reduction of external loading ...... 165 Figure 78: Simulation of inorganic nitrogen availability under 50% reduction of phosphorus external loading ...... 166 Figure 79: Simulation of the fate of dissolved organic matter as COD under 50% reduction of phosphorus external loading ...... 167 Figure 80: Simulation of the accumulation of inert matter as sediment and slow biodegradable organic matter under 50% reduction of external phosphorus loading ...... 167 Figure 81: Simulation of algae growth and oxygen production under 50% reduction COD external loading ...... 168 Figure 82: Simulation of autotrophic bacteria growth under 50% reduction of dissolved organic matter (COD) ...... 169 Figure 83: Simulation of heterotrophic bacteria growth under 50% reduction of external dissolved organic loading ...... 170 Figure 84: Simulation of dissolved organic degradation under 50% reduction of COD external loading ...... 170 Figure 85: Simulation of nutrients under 50% reduction of dissolved organic matter external loading ...... 171 Figure 86: Simulation of the accumulation of inert and slow biodegradable organic matter under 50% COD reduction ...... 172 Figure 87: emergent macrophyte treatment system with horizontal sub-surface flow (Kayombo et al. (2005) citing Brix, 1993) ...... 176 Figure 88: emergent macrophyte treatment system with surface flow (Kayombo et al. (2005) citing Brix, 1993) ...... 176 Figure 89: Simulation of algae growth and production of oxygen under no and reduced sediments internal loading ...... 178 Figure 90: Simulation of heterotrophic bacteria growth under no and reduced sediments internal loading ...... 179 Figure 91: Simulation of organic matter as COD degradation under no and reduced internal loading ...... 179

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Figure 92: Simulation of nutrients availability under no and reduced internal supply of phosphorus ...... 180 Figure 93: Simulation of accumulation of inert organic matter and slow biodegradable organic matter under no and reduced internal loading...... 181 Figure 94: Simulation of algae growth and oxygen production under combine external and internal loading reduction ...... 184 Figure 95: Simulation of heterotrophic bacteria growth under combine reduction of external and internal loadings ...... 184 Figure 96: Simulation of dissolved organic matter degradation under combine reduction of external and internal loadings ...... 185 Figure 97: Simulation of nitrogen compounds availability under combine reduction of external and internal loadings ...... 186 Figure 98: Simulation of inert and slow biodegradable organic matter accumulation under combine reduction of external and internal loadings ...... 186 Figure 99: Possible fate of the lake without any management strategy ...... 196

Glossary

Aerobic refers to system in which some oxygen is present. Algae are small, often microscopic, aquatic plants in a water body. They exist either as phytoplankton (i.e., free floating cells) or as periphyton (i.e., filamentous algae attached to rocks or other underwater objects). Anaerobic refers to system in which oxygen is not present. Anoxic refers to the condition of lack of dissolved oxygen i.e. deoxygenated water. Anthropogenic refers to everything originating from human source. Aquatic environment is a general phrase that indicates the combination of physical, biological, and chemical conditions present in lakes, rivers, wetlands, rivers, and oceans. Biomass is the total mass of living material in a given body of water.

BOD 5 is biological demand of oxygen originating from the degradation of organic matter by microorganisms during 5 days. Buffering capacity is a measure of the ability of a system to meet changes imposed from the environment by minor changes in the system. Chlorophyll is the green pigment in a plant cell that absorbs the solar energy in the process of photosynthesis of new organic matter. COD is chemical oxygen demand and is measured as the amount of oxygen supplied by the chemical oxidation agent chromate to degrade organic matter by chemical means. Cost/benefit analysis is a process comparing the cost of a given action, such pollution control programme, with the expected benefits of the action, such as better water quality. The comparison usually is expressed in strictly monetary terms. Diffuse or non-point pollution source refers to pollution coming from many widely spreading sources in contrast to point source, where one point (often a pipeline or stream, canal) can be indicated. Generally, it is not possible to collect pollutants coming from diffuse sources. Therefore it is necessary to find solutions which do not built on environmental technology (also called end-of-the pipeline technology). Ecology is the study of the distribution and abundance of organism and the physicochemical and biological processes that determine the structure and function of ecosystems. Effluent is the liquid waste from municipal sewage, and septic sources, which is released to the surface waters, such as lakes, reservoirs, and steams. Eutrophic lake or water reservoir is a water body receiving large amount of nutrients from its watershed. It is characterized by high photosynthetic activity and low water transparency. Flushing is the action leading to volume of lake water being replaced. Food web structure refers to the number of organisms at different trophic levels in a community. Examples of trophic levels include primary producers, such as algae or other aquatic plants, herbivores and predators. Hypereutrophy or hypertrophy is the final stage of the eutrophication process. The system is unstable and eutrophication usually irreversible. Control of external nutrient sources is

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ineffective as the system generates sufficient nutrients from the anaerobic sediments to support the growth of algae. The excessive development of the phytoplankton is due to very high input of nutrients and organic matter. Aquatic organisms consume this matter and oxidize it. It leads to a deficit of oxygen dissolved in water, particularly at the bottom, accumulation of silt, death of fish and deterioration of water taste. It limits a possibility to use the water for drinking water supply. Internal loading refers to the release of nutrients in a water body from sources, such as sediments, decomposition of litter or carcasses or excretion, in contrast to external loading where the nutrients come from the watershed or atmosphere. Internal loading includes the concept of recycling of nutrients that have ultimately entered as an external load. Limnologist is a specialist in the study of fresh water lakes, particularly their biological, chemical and physical characteristics. Limnology is the study lakes, reservoirs, wetlands and rivers, and includes their physical, chemical and biological aspects. Littoral zone refers to the water in the lake or reservoir that is closest to the shore, in contrast to the deeper waters in the centre of the lake or reservoir. Macrovegetation includes macrophytes, which are macroscopic (polycellular) plants which can either be submerged (i.e. completely covered by water) or emergent (i.e. only partly covered by water). it is also possible to distinguish between rooted plants, which have their roots in the sediment, or floating plants, which are floating on the water surface. Morphometry is the description of lake’s or reservoir physical structure, such as depth, shoreline length, etc. Nitrification refers to the process where ammonium is converted to nitrate. Organic matter refers to any molecules produced by plants, animals and human, which contain carbon. pH is a measure of the acidity of a solution and is defined as the negative logarithm of the hydrogen ion concentration in the solution. It shows how acid or alkaline is the solution. Photosynthesis is the process by which plants and some bacteria use energy from light to form organic matter from inorganic substrates. Phytoplankton refers to the community of lower, predominantly single cell plants inhabiting the water mass. Remediation refers to a treatment programme for attempting to control lake or reservoir eutrophication. The programme can consist of external nutrient control measures, in-lake control measures or both measures. Secchi disk is a white plate that is lowered into a lake or reservoir to determine the transparency of the water by recording the depth where it can no longer be seen. Sedimentation is the process of sediment particles accumulating on lake bottom. Sediments are materials in lake or reservoir, which are either suspended in the water column or deposited on the bottom. They usually consist of the remains of aquatic organisms, precipitated minerals and eroded material from the watershed. Watershed is he land area from which rainfall drains into a single water body.

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Wetland refers to aquatic habitat in which plants, in contrast to microalgae, are predominant. Includes swamps, marshes, bogs and shallow lakes. Zooplankton is a community of invertebrate organisms inhabiting the water mass, usually feeding on bacteria, phytoplankton and/or detritus. Serve as food for higher level organisms, including fish.

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Abbreviations/Acronyms

CNRE: Centre National de Recherches sur l’Environnement

DTIE: Division of Technology, Industry and Economics

INSTAT: Institut National des Statistiques (National Institut of Statistics)

IWAPRC: International Association on Water Pollution Research and Control

NUFU: Norwegian Higher Education Programme

OCDE: Organisation for Economic Co-operation and Development

PCD : Plan Communale de Développement (Commune Development Plan)

UNEP: United Nation Environment Program

UNICEF: United Nations International Children’s Emergency Fund

USEPA: United States of America Environmental Protection Agency

Symbols

CaCO 3: calcium carbonate Chlo. a: chlorophyll a BOD: biological oxygen demand COD: chemical oxygen demand Fe: iron ISS: inorganic suspended solids ITS: inorganic total solids Mn: manganese N: nitrogen

+ NH 4 : ammonium ion

N-NH 4: ammonium nitrogen

N-NO 3: nitrate nitrogen

O2: oxygen

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P: phosphorus

PO 4: orthophosphate

P-PO 4: orthophosphate phosphorus SRP: soluble reactive phosphate (soluble reactive phosphorus) TDS: total dissolved solids TDVS: total dissolved volatile solids TKN: total kjeldahl nitrogen TN: total nitrogen TP: total phosphorus TS: total solids TSS: total suspended solids TVS: total volatile solids

CHAPTER 1 Introduction

1.1. Historical context of the city of Antsirabe, location of the site study

1.1.1. Antsirabe, the city of salt

By the beginning of 18 th century, Andrianony, one prince from Alasora, built the small village of Soamalaza during his migration in the Vakinankaratra region. Then, after the arrival of Norwegian missionary (1869 -1872), comprising Martinius Borgen, minister Dahle, and the Pastor Rosaas, who built the first house made of brick, the village changed its name as Antsirabe.

Originally, Antsirabe was a small village with a few miserable houses for prisoners (gadralava), particularly criminals punished by the Merina kingdom. They have been sent in Antsirabe to work in a mining quarry digging lime, salt, and sulfur. The name of the city Antsirabe came from salt (sira), which literally means a place where there is a lot of salt. This place was also the main source of raw material for the construction in Imerina in the nineteenth century.

Figure 1: Antsirabe seen from south in 1885, Source (Dahl, 2010)

The development of Antsirabe as city was closely related to the arrival and settlement of the multitalented Norwegian missionary named Pastor Thorkild G. Rosaas in 1872 (Dahl, 2011). Indeed, Rosaas not only built the oldest building in Antsirabe called “Sitasiona” in 1872, but also a Lutheran church (Figure 1). From 1887 to 1907, he constructed 131 buildings in the leper colony in Ambohipiantrana and made the first street in Antsirabe. He also built the first water adduction canal to Antsirabe and to Ambohipiantrana (leprosy colony). The most important research work Pastor Rosaas carried out was related to the first analysis of the hot

water spring (Figure 2) performed by Dr Borchrevinck in 1873. It was discovered after analysing the water spring that there is a similarity of its composition with the famous French water spring ‘’Vichy’’. This was the origin of the name of spring water produced in Antsirabe currently called “Ranovisy”.

Figure 2: The hot spring Ranomafana, Source (Dahl, 2010)

It is noteworthy that a bathing house for the queen Ranavalona II was built by Rosaas nearby the hot springs Ranovisy, where she used to rest after a long trip to Fianarantsoa. On the other hand, the hot springs Ranomafana were developed and were used for treatment of rheumatism. Few bathing houses were built around the sources (Figure 3).

Figure 3: Ranomafana bathing houses, Source (Dahl, 2010)

Thermal and mineral water sources of Antsirabe have been ever since subject to quite many researches and analyses for medical and therapy purposes. The listed parameters in Table 1

were analysed by Pr Waage P. (1890) and reported in the magazine “Le Progrès de l’Imerina” on 31 December 1890.

Table 1: Result of analysis of mineral water (1000 g) from spring water of Antsirabe Mineral component Concentration (g) Sodium bicarbonate 4.6668 Potassium chloride 0.3165 Calcium sulphate 0.2943 Magnesium chloride 0.2827 Sodium chloride 0.2269 Silicon acid 0.1304 Calcium bicarbonate 0.0814 Iron bicarbonate 0.0028 Source: Scientific journal “Le Progrès de l’Imerina”

The spring water samples were at that time being found highly alkaline and rich in bicarbonate, with a density of 1.0046. Many others analyses followed the ones performed by the Norwegian missionary, which afterwards fully established the therapeutic value of both thermal and mineral water source of Antsirabe. Different kind of diseases ranging from rheumatism, stomach ulcer, enteritis, chronic bronchitis, cystitis, to diabetes, were treated by using spring waters in Antsirabe. This seemed to be the beginning of water cure in Antsirabe, but also the spa, which treatment activities are believed to be closely related to the origin of Lake Ranomafana.

1.1.2. Origin of the Lake Ranomafana

After the discovery of the thermal and mineral water sources in Antsirabe up to 1900s, most of research works carried out on these sources were fully focused on their therapeutic values. There is no document or literature mentioning the lake and its origin. However, some of these documents noted more and more the decrease of water pressure in the bathing houses without explaining the probable cause. In 1912, one French hydrogeologist, Pierre de la BATHIE, brought more clarification about the origin of thermal water, but also the cause of water pressure decreasing. Indeed, the hydrogeologist conducted a series of drilling within both the southern valley (at the location of the current Ranovisy plant) and northern valley (around the current spa) nearby the Norwegian missionary and concluded that the thermal sources are earlier to the stratified ash depot within both southern and northern valleys. He also concluded that the decreasing water pressure and flow was due to loss of gas. As follow up of his works, Pierre de la BATHIE created, in 1923, a man-made lake in a swampy area within the northern valley (Figure 4) so as to regulate and stabilise gas pressure (Asimbolarimalala, 2008). It is worthwhile noting that the spa was built in 1917 and opened in 1923, leading to the conclusion that there is a close relationship between the construction of the spa and the creation of Lake Ranomafana. Even still confused, the discharge of used water from bathing houses, later transformed in spa, was taken into consideration in the creation of the lake to regulate gas pressure in the area.

Figure 4: Originally location of Lake Ranomafana in a swampy zone, Source (Dahl, 2010)

According to Asimbolarimalala (2008) another French hydrogeologist, LENOBLE A, completed the works of Pierre de la BATHIE in 1941 through series of drilling around the thermal zone. In view of the continuing decrease of water pressure, he confirmed the cause of water low pressure due to loss of gas. He was the first to study the geological characteristics of the thermal zone in 1946. By this time, Lake Ranomafana was in function as shown in Figure 5.

Figure 5: Panorama view of Lake Ranomafana and surrounding in 1946, Source (Dahl, 2010)

From initially a system created to regulate and stabilise loss of gas and indirectly reduce the decrease of thermal water pressure, Lake Ranomafana had slowly shifted its role as a system to contain volcanic gas and recreational area to a receptor of untreated municipal wastewater (domestic and storm water runoff) from surrounding catchment areas, leading to its water quality degradation. However, the spa and Lake Ranomafana have, since their creation, fulfilled the role of landmark of the city of Antsirabe (Figure 6). This is why, since the 1980s, the municipality of Antsirabe (I) has made the improvement of the lake water quality, if not the complete restoration of the lake, its priority. Two master plans, elaborated respectively in 1986 and 2003, encompassed schemes to restore the lake and surrounding for the benefit of tourism, recreation, and particularly sanitation and public health, but these projects ended up without any kind of materialization for lack of financial support.

The little improvement the municipality has been able to carry out was the removal of low income illegal dwellings built on the southwestern shoreline of the lake and regularly removal of water hyacinth ( Eichhornia crassipes ) in the lake, an invasive free floating aquatic plant. To complete our understanding of Lake Ranomafana issues, one needs to have an overview of the social and economic context in the city of Antsirabe.

Figure 6: Panorama from Ranomafana in 1946, Source (Dahl, 2010)

1.2. Context administrative, Social, and economical of Antsirabe

Presently, Antsirabe is the capital of the region of Vakinankaratra, which comprises 7 districts, namely Antanifotsy, Antsirabe I, Antsirabe II, Ambatolampy, Betafo, Faratsiho, and Mandoto. The region is geographically situated between latitude 18°59’ and 20°03’ South and longitude 46°17’ and 47°19’ East. With an area of 17496 km 2, the region is home to about 1 982 000 inhabitants.

The city of Antsirabe, administratively named Antsirabe (I), is geographically located between latitude 19°52’ South and longitude 47°02’ East at 1540m of altitude (Figure 7). With an area of about 122 km 2, the city is delimited northward by the rural commune of Andranomanelatra, southward by the rural commune of Vinaninkarena, eastward by the rural commune of Ambohidranandriana, and westward by the rural communes of Antanimandry and Belazao.

The city of Antsirabe is the third biggest city of Madagascar. The commune is comprised of 59 Fokontany (neighbourhood), which are divided into 6 bigger zones, namely Antsenakely Andraikiba, AAAA (4 A), Ampatana, Manodidina ny Gara Ambilombe, Mahazoarivo Avarabohitra, and Soamalaza Mahatsinzo. The city is home to estimated 190 472 inhabitants (Estimation of INSTAT, 2007), with a density of 1058 inhabitants/km 2. With 80% below 35 years, the population is relatively young (Communal Development Plan (PCD), 2006) and predominantly feminine, with 52.65% female and 47.35% male.

Figure 7: Location of the city of Antsirabe

From point of view demographic, the development of the industrial sector in Antsirabe has been the main cause of migration from rural area to the city. Dwelling settlement has followed the establishment of industrial plants. The average size of households is of 4.4. According to the Communal Development Plan (PCD, 2006) the followings are the most populated neighbourhoods, i.e. with a number of inhabitants above 5000:

- Antsirabe Afovoany Atsinana, with 8766 inhabitants; - Mahazoarivo Nord, with 8764 inhabitants; - Mahazoarivo Sud, with 8609 inhabitants; - Mahazina, with 5109 inhabitants; - Miaramasoandro, with 6291 inhabitants; - Ivory , with 6533 inhabitants; and - Ambohimena, with 11 689 inhabitants.

The population growth prediction from 2008 up to 2023, according to the survey conducted by relevant service of the Commune of Antsirabe, is presented in Table 2 below. It is worthwhile noting that the district of Antsirabe is, in 2011, home to 207 414 inhabitants.

Table 2: Antsirabe Population growth prediction Zone (Firaisana) Population Population Population Population Population 2003 2008 2013 2018 2023 Soamalaza 23 675 29 026 35 588 43 633 53 506 Mahatsinjo Mahazoarivo 41 277 50 606 62 048 76 074 93 286 Avarabohitra Ampatana 13 250 16 245 19 917 24 420 29 945 Mandriankeniheny Manodidina ny 24 185 29 651 36 355 44 573 54 658 Gara Ambilombe 4 A 41 092 50 379 61 769 75 733 92 868 Antsenakely 37 129 45 520 55 812 68 429 83 912 Andraikiba Total 180 608 221 427 271 489 332 862 408 175 Source: PCD 2006, Commune Urbaine d’Antsirabe

With respect to socio-economical situation, Antsirabe and its rural areas are poles to multisector development ranging from handicraft, agriculture, farming, gem, tourism, to industry. Antsirabe’s most developed sectors are farming, agriculture, and industry. Indeed, different varieties of vegetables, cereals, and fruits are being grown in Antsirabe and surrounding areas. The region is also well known for its farming sector, from which most dairy products found on the Malagasy market come from. Food industries are well presented within Antsirabe region like TIKO (dairy products), SOCOLAIT (dairy products, dietetic products), and STAR (beer, soft drink).The biggest textile industries of the country (COTONA, AQUARELLE) are also established in the city, as well as a cigarette (SACIMEN) and cement (Holcim) factories.

Antsirabe, as capital of the region of Vakinankaratra, provides multitude of infrastructures and facilities (Hospital, school, Private Universities, and different administrative centers). Finally, Antsirabe is a place for holiday and tourism, with in particular its thermal facilities and its lakes. Apart from having Lake Ranomafana, there are two bigger lakes around Antsirabe, namely Lake Tritriva (volcanic origin) and Lake Andraikiba, which is the main source of water supply for the city.

In spite the development of most socio-economical sectors, the city of Antsirabe, alike bigger agglomerations throughout Madagascar, does have unresolved issues related to population growth and land use. Beyond the fact that solid waste management leaves much to be desired, access to water supply and adequate sanitation doesn’t really differ from national urban rates of respectively 66% and 27.15% (WaterAid Madagscar, 2010). However, these rates are believed, according to Unicef (2010), to be in regression compared to 2008, because of political crisis leading to lack of funding. Unhealthy conditions and lack of infrastructure for sanitation, in addition to precarious access to potable water, are the leading causes of death due to diarrhoea for children under 5 years, mainly in slum

areas. Furthermore, insalubrity is exacerbated by a generalized bad behaviour of dumping and throwing garbage in sewerage system. Most sewer systems remain clogged because of dumped garbage. Heavy rain conveys certain garbage through sewerage system till the receptor such as Lake Ranomafana (Figure 8).

Figure 8: Lake Ranomafana as final destination of domestic garbage

Owing to the nature of sanitation practice in the whole city of Antsirabe, it seems that Lake Ranomafana is only partly affected by discharge of municipal wastewater. According to the survey report written by SOMEAH/SOGREA on behalf of the JIRAMA (2004), more than 50% of the household are using pit latrine, while those using septic tank do not necessarily discharge domestic wastewater to sewerage system (Table 3).

Table 3: Sanitation practices in the city of Antsirabe

Type of Main source of Greywater On-site Main zones of individual potable water disposal system wastewater localization sanitation treatment

Individual Septic tank Along RN7, Z3, Type I JIRAMA channel in the and/or Z4 backyard improved latrine Public stand Thrown in the Central part Type II Pit latrine pump backyard mainly Z2, Z4, Z5, Z6 Thrown in the Public stand backyard and/or Everywhere but Type III pump , and dumped in an Pit latrine mainly Z4, Z5, Z6 borehole individual channel or trench for

greywater

Dumped in a Z4 using trench trench for for greywater greywater and and garbage, Type IV Borehole domestic Pit latrine while Z2, Z4, garbage or in a and Z6 using pit trench for for composting composting

Dumped in the backyard and/or Mainly Z2 and Type V Natural sources Pit latrine in an individual Z4, less in Z5 channel

Source: SOMEAH/SOGREA report (2004); Zn refers to the division of the city in zones (6); RN7: National road 7 going to Fianarantsoa.

The same report confirmed that Lake Ranomafana is not affected by any industrial effluent discharge since all industrial factories discharged untreated or partially treated wastewater to River Sahatsio for the eastern part and River Sahalombo for the western part of the city. So what are then the stake related to the degradation of Lake Ranomafana conditions (physical, aesthetical, and chemical) that makes its restoration a priority of the municipality of Antsirabe.

1.3. Problem statement

Unlike the two others lakes within Antsirabe region, namely Lake Tritriva and Lake Andraikiba, the existence and functions of Lake Ranomafana are related to the following issues quite sensitive and relevant for the social and economical development of the municipality of Antsirabe (Figure 10): tourism, recreation, sanitation, and public health.

Tourism and recreation: In the past, Lake Ranomafana fulfilled a double role as a descriptive symbol of the city (also landmark), being exceptionally located in the centre of the town, and as a recreational park for tourists and local population with their children. However, owing to lack of maintenance, dilapidated recreational equipment, pleasure garden and site being completely neglected in the past, illegal constructions slowly invaded the surrounding area leading to the development of slum neighbourhood. Illegal constructions not only degraded the scenery of the site but also contributed to the pollution of the lake by lakeside residents defecating around, dumping solid waste, and discharging domestic wastewater. Lake Ranomafana site has then lost its double function.

It is noteworthy that the current mayor with the municipality staff took a commendable initiative to remove all illegal constructions around the lake and pave the surrounding

pathway. Employees from the municipality are also planting flowers to make more attractive the site around the lake.

Sanitation: Initially intended to be a recreational park for tourists and particularly for local population, Lake Ranomafana has been also playing a significant role as receptor of municipal wastewater from surrounding neighbourhoods. From the second master plan (Scheme for urban sanitation) in 2003 it was estimated around 870 m 3/d of domestic wastewater discharged into the lake by 39,527 inhabitants in addition to surface runoff coming from 125 Ha of catchment areas. The discharge of domestic wastewater and runoff rich in nutrients (reactive phosphorus and nitrogen) and heavily contaminated by pathogens in addition to domestic solid waste has accelerated the alteration of the lake aesthetic, water quality, and seemingly its trophic status. During hot season, rotten egg smell is felt by people passing around the lake. This is why the lake is being named from local population “Lac Ranomaimbo”, which literally means lake with smelling water. The origin of the smell will be explained in Chapter 2 within chemical characteristics of the lake.

Public health: Water from the outlet of the lake is being used to irrigating watercress field downstream, making watercress harmful and unfit for local consumption and putting farmers at risk of contracting parasites and pathogens. Same risk threatens low income people, who frequently come to catch fishes in the lake by using nets or big traditional baskets. Nowadays, invading and fast multiplying crustacean specie, popularly called “Foza orana” ( Procambarus sp ), seems to have been colonizing lake’s vegetated shoreline, and so are also collected by clothes hand washers along the lake shoreline (Figure 9). So, instead of resolving sanitation problem, the lake, receiving untreated municipal wastewater, represents a potential public health risk.

It is well known and specified from the current Water and Sanitation policy the big responsibility of the municipality as the owner of the whole water and sanitation infrastructure of the city and as the principal promoter of better access to water and sanitation for the residents, particularly for the poor and vulnerable population. In this way, the municipality, aware of the stake, through its mayor Olga Ramalason, voiced specific concerns over the degradation of Lake Ranomafana conditions, and in particular about the water quality related problems on public health. As all former projects to rehabilitating the lake conditions failed to come true, because of the cost relatively high, the goal of this research project was to propose different alternatives of site specific and cost effective approaches suitable for Lake Ranomafana restoration.

Figure 9: Catching fishes and "Foza orana" (invading crustecian specie, Procambarus sp )

Figure 10: The city of Antsirabe with infrastructure and sanitation facilities, Source: SOMEAH/SOGREA (2004)

1.4. Objectives of the project

Hypothesis: Prior to the start of this research project, suspected issues contributing to the current conditions of Lake Ranomafana included altered water quality due to heavy discharged of domestic wastewater, elevated algal growth favoured by continuous supply of nutrients from influents, and suspended solids from spa influents discharge. The trophic status of the lake is suspected to be hypereutrophic but reversible, with an appropriate management approach.

Primary objective: Determine site specific management scenarios to restoring Lake Ranomafana that would be appropriate for Antsirabe municipality from point of view technical performance, financial cost and social benefit, and also level of operation and maintenance. The first desired output of this primary objective is a generic computer model capable of predicting Lake Ranomafana behaviour with different restoration scenarios. Then, the second desired output is going to be a series of lakes restoration alternative approaches capable of reversing the ongoing visible eutrophication process while achieving the quality target of the municipality for a healthy and recreational site. The last but not least desired output must be a better understanding of the lake physical, chemical, and biological functioning and the reason of its overall quality deterioration. The following tasks will be used to reach this objective: Task 1: Identify the sources of influents going to the lake and quantify the external loading to the lake, particularly in terms of nutrient and organic loadings;

Task 2: Characterise current conditions of the lake from point of view physical, chemical, and biological conditions for a better understanding of visible ongoing eutrophication process and characterisation of the lake trophic status;

Task 3 : Develop and evaluate a computer model of the lake processes under current conditions;

Task 4: Use computer model to predict the lake’s behaviour with different scenarios of external loading reduction;

Task 5: Review, evaluate, and compare in-lake restoration techniques that are appropriate to local constraints while capable of reversing the ongoing visible eutrophication process;

Task 6 : Use computer model to predict the lake’s behaviour with different in-lake restoration scenarios.

Task 7 : Provide a series of alternative scenarios potentially capable of reversing the current situation Secondary objective: Evaluate the relevant factors that would make alternative restoration techniques possible to be implemented and the socio-economical benefits of restoring Lake Ranomafana. This will be achieved through the following task:

Task 1 : Evaluate the cost-benefit of restoring the lake;

1.5. Thesis layout

This thesis contains seven chapters and additionally a reference list and appendices. The content of the remaining chapters is outlined below:

Chapter 2 contains details on materials and methods used both for monitoring of the lake and for developing the lake model. Chapter 3 presents the results of the diagnostic carried out through the lake monitoring. Chapter 4 provides the results of Lake Ranomafana modelling, both under current conditions and under assumed management scenarios. Chapter 5 introduces one decision-making tool that could be used for any project to managing the lake. Chapter 6 provides a synthesis of the modelling results in a form of alternative scenarios. Chapter 7 contains the general conclusions.

1.6. Literature review

A shallow lake or pond is usually defined as a permanent standing body of water that is sufficiently shallow to allow light penetration to the bottom sediments adequate to potentially support photosynthesis of higher aquatic plants over the entire basin (Wetzel, 2001). Generally less studied than large lakes, the millions of shallow lakes, impoundment, and ponds of few meters depth are frequently less attractive and spectacular but important in number and usage. According to Wetzel (2001), many human activities are associated with and dependent upon shallow waters and wetlands. In addition, maximum biodiversity of freshwater ecosystems occurs where wetland and littoral habitat heterogeneity interfaces with pelagic regions. Few years ago, Madagascar, fully aware of the highly valued biodiversity and valuable resources found in this type of aquatic system, joined the Ramsar Convention for the protection of wetland. But now, most of these rich ecosystems are under wide range of anthropogenic threat, which not only jeopardizes the biodiversity, but particularly accelerates their life cycle.

The origin and occurrence of shallow lakes range from natural depression, lowland areas, flood plains of major river ecosystems (Wetzel, 2001), but also fortuitously or intentionally 13

man-made shallow lakes and ponds for agricultural, water storage, or recreational purposes. Although every shallow lake is unique system (size , depth, volume), their main characteristics are relatively similar, that is, most of them do have no thermal stratification as do large and deep lakes. Also, in shallow lakes, the littoral can and often does extend over the entire lake or pond basin (Wetzel 2001). As general feature, the same author underlines the turbidity issue from abiotic and biotic sources, which may prevent light from reaching the sediments, but the lakes or ponds are sufficiently shallow for this potential condition to occur.

Shallow lakes or ponds, likewise most inland surface freshwater, are being under threat of growing pressure related to human development and settlement. Unlike large and deep lakes or flowing rivers shallow lakes are more vulnerable to anthropogenic pressure owing to their morphometric characteristics that tend to amplify any kind of pressure. Anthropogenic pressure affecting shallow lakes ranges from overexploitation of resources, discharge of untreated wastewater (either municipal, domestic, or industrial), drainage of runoff from diffuse sources of pollution such as agriculture area or atmospheric origin, and sedimentation from upland erosion. Inherent stressors of shallow lakes are diverse and not always visible. They might affect the different compartment of the lakes ecosystem such as water column, sediment, and vegetation leading to the degradation of lakes status and conditions. Those stressors can be classified in 3 main categories: physical, chemical, and biological. It’s worth noting that although sometimes from different sources, those stressors may generate even worst combine effect on lake systems. For example, untreated municipal wastewater can discharge heavy metals, hydrocarbon residue, nutrients, bacteria, and solids.

In the United States, likewise in developed countries, the states cited nutrients, metals (such as mercury), sewage, sedimentation, and nuisance species as the top causes of impairment. Leading known sources of impairment included agricultural activities and atmospheric deposition, although for many lakes, the sources of impairment remain unidentified (USEPA, 2010). Developing country sources of impairment are likely a bit different. Indeed most of these countries suffer from lack of proper sanitation, lack of solid waste disposal, shanty town in addition to damaging agricultural practice leading to upland erosion and downstream aquatic system sedimentation. For urban wetland including shallow lakes most of them are usually being used as receptor of untreated sewage causing eutrophication problem.

Shallow lakes impairments not only damage the entire lakes ecosystem, but also negatively affect their uses such as recreational, water storage for domestic, agricultural, or industrial purposes. The most visible and worldwide impairment affecting urban shallow lakes is eutrophication due to discharge of untreated municipal wastewater. This is the case of Lake Ranomafana, which visually seems impaired by discharge of untreated sewage from surrounding urban watershed.

1.6.1. Eutrophication process

Eutrophication is differently defined according to the area of study; however referring to the Greek origin of the word “eutrophic”, which means well-fed, eutrophication is sometimes used in the context of increases in nutrient loading. The word eutrophy (from the German adjective eutrophe) in general signifies to “nutrient rich”, and Naumann introduced in 1919 the concepts of oligotrophy and eutrophy. According to UNEP (2002) eutrophication of lakes and reservoirs is enrichment with plant nutrients, mainly phosphorus and nitrogen, which enter as solutes and bound to organic and inorganic particles. By contrast, certain authors highlighted the use of the term in a more reactive context by limnologists and oceanographers, that is, referring to increases in biological productivity and/or standing crops. The same author underlined the close relationship between increased nutrients and increased biological productivity and stated that increases in nutrient loading may not result in increased productivity if other factors limit the use of nutrients, and that increases in productivity may not lead to increased standing crop because of the nature and magnitude of loss functions, such as grazing, death, sedimentation, dilution, and export. For the present study, both definitions seem to be valid for the case of Lake Ranomafana affected by different pressure from surrounding watershed leading to visual eutrophication status.

The interest on eutrophication in aquatic ecology started from few decades ago when the algal bloom started to affect lakes and coastal zones of developed countries in Europe and North America. It was then due to the increased urbanization and the increased discharge of nutrient per capita, in addition to growth in the production and use of fertilizers as detergents containing phosphate have been banned long time ago. In contrast, surface water eutrophication problems in developing country are caused by the lack of adequate sanitation practice and proper disposal of solid waste leading to discharge of untreated wastewater and solid waste into water body such as lakes, river, and sea.

Due to lack of funding , but also to lack of good knowledge about the negative impacts of such doing (improper sanitation of practice, improper management of domestic garbage) leading to the absence awareness, eutrophication has began to be the main problem of developing country’s surface water, and marine coastal water. Related problems that always accompany eutrophication are seafood poisoning, diarrhoea, and parasites.

From view point limnology eutrophication involves the presence of two inseparable elements that make it to happen: available nutrients, and algae. Indeed, the specific response of algae to increases in nutrient concentrations is dependent on the relative availability of the nutrient in question before the increase. Two cases might be possible according to nutrient availability: - If the nutrient is present at growth-limiting concentrations, increases in availability should stimulate productivity, assuming the absence of other limiting factors such as light availability; alternatively, 15

- If the nutrient is already present at saturating, then additional nutrient may result in little response.

On the other hand, the amount, rate, and manner of nutrient addition can also affect the type of algae that responds to the increase. So, the impacts of nutrient increases can be both qualitative and quantitative in nature. Anyway, eutrophication is generally considered to be undesirable problem, although it is not always so, because of the impact on water uses such as water supply, swimming, boating. The economical costs of eutrophication as well might be significant depending on affected aquatic system uses. For the UNEP (2002) enhanced growth and increased abundance of aquatic plants often results in reductions in water quality, while Novics (2009) underlined the effect of abundant plant growth producing an undesirable disturbance to the balance of organisms (structural and functional changes, decrease in biodiversity, higher chance for invasion, fish kill, etcetera) and to the quality of water (cyanobacterial blooms, depletion of oxygen, liberation of corrosive gases, and toxins). The same author recognised that during the last four decades, eutrophication has undoubtedly been the most challenging global threat to the quality of our fresh water resources.

Phosphorus and nitrogen had been recognized for several decades in agriculture as critical nutrients that often limit plant growth and productivity, and that under most lake conditions, the most important factors causing the shift from a lesser to more productive state are phosphorus and nitrogen (Wetzel, 2001). However, nitrogen addition alone failed to trigger phytoplankton growth (Novics, 2009). Indeed, according to the same author, in most lakes, biomass was determined by the amount of phosphorus, while nitrogen was the controlling factor in only few cases. Typical plant organic matter of aquatic algae and macrophyte contains phosphorus, nitrogen, and carbon approximately in the ratios: 1P:7N:40C per 100 dry weight or 1P:7N:40C per 500 wet weight (Wetzel (2001), citing, Vallentyne, 1974).

While the importance of both phosphorus and nitrogen capacity to trigger eutrophication of surface waters was for long time well established, the understanding of where do they come from and the causal-effect relationship with the health of aquatic system becomes even more critical to finding out solutions for reversing the situation. In this way, trophic categories of oligo-, meso-, and eutrophy, nowadays widely called trophic status, introduced by Naumann in 1919, were gradually analyzed in increasingly quantitative ways, in terms of nutrient concentrations, phytoplankton biomass, chlorophyll concentrations, and water transparency in addition to the classical characterization of hypolimnic oxygen conditions (Wetzel, 2001). This is generally done for evaluating how critical the rate of loading of nutrients from surrounding drainage has become to trophic conditions. And lately much attention has been directed to the internal recycling of nutrients within lakes and stream.

As one can see, reversing status from being eutrophic to oligotrophic led aquatic ecologists to finding out the relationship between nutrients loading rate and trophic status. This relationship was defined according to different physical and chemical parameters affected by nutrients loading rate.

1.6.2. Trophic status

The word “trophy” originates from the Greek word “trophē” which means nourishment or pertaining to nutrition or connected to with source of nutrition. In order to classify a plant or animal community or to assess its quality status, for example, as a result or anthropogenic disturbance, trophic indices were developed. They are mostly applied in aquatic communities since aquatic ecosystem are relatively stable in space and time (Pavluk and De Vaate, 2008).

The trophic status of a water body is a hybrid concept referring to the nutritive state (especially phosphorus) of a lake or pond, but is often described in terms of biological activity that occurs as a result of nutrient levels. The introduction of trophic status concept is related to the concept of nutrient loading, which implies that a relationship exists between the quantity of nutrient entering a water body and its response to that nutrient input. So the idea behind the trophic status concept was to express the effects of this relationship in terms of some quantifiable index of productivity or water-quality parameter (e.g., chlorophyll concentrations and water transparency) (Wetzel, 2001). Lately, this capacity to assess the effects of nutrient loading evolved to research of tool capable of predicting nuisance population occurrence in the water body whenever critical levels of dissolved nutrients were exceeded. Wetzel (2001) cited Vollenweider (1966, 1968) as the first to formulate definitive quantitative loading criteria for phosphorus and nitrogen and expected trophic conditions in water bodies. He defined boundaries between oligotrophic and eutrophic lakes by relating nutrient loadings to mean depth (as a measure of lake volume) and later refined these relationships.

On the other hand, according to the same author the evaluation of the trophic status of a lake has great practical importance. Eutrophication status must be known before remedial corrective measures can be implemented in relation to the desired use for any lake. But, on the other hand, researches for generic tool capable of predicting changes in water body related to changes in the phosphorus loading continued to developed after Vollenweider works. In this way, many models were developed and tested for capacity to predict probability of oligotrophic, intermediate, or eutrophic conditions developing in phosphorus- limited lakes in response to various loading regimes (Wetzel, 2001). These models based on many data also, as reported by the same author, permit estimates of permissible loading rate of phosphorus and nitrogen while still allowing tolerable conditions of productivity. According to Vollenweider (1968), cited by Wetzel (2001), provisional loading rates of nitrogen and phosphorus required to maintain lakes in a steady state depend on mean

depth. So, for lake having 5 m mean depth, permissible loading for nitrogen and phosphorus is of 1.0 and 0.07 g m -2 yr -1, respectively, whereas dangerous loading for nitrogen and phosphorus is of 2.o and 0.13 g m -2 yr -1. Furthermore the unalterable tolerable loading level of 10 mg P m -3 remains valid, while the excessive loading level has been increase slightly to 25 mg P m -3 (Wetzel (2001) citing Vollenweider and Kerekes, 1980).

Meanwhile, Carlson introduced a simple production-based trophic state index (TSI) using phytoplankton biomass as a basis for a continuum of trophic states of lakes and reservoirs under both nutrient-limiting and non nutrient-limited conditions (Wetzel (20019 citing Carlson, 1977, 1980, 1992; Carlson and Simpson, 1996). Carlson TSI system is based upon Secchi depth as a mean of characterizing algal biomass. According to Carlson, this index system has the advantages of easily obtained data, simplicity of absolute values, valid relationships. The TSI incorporates most lakes in a scale of 0 to 100. Each major division (10, 20, 30, etc9 represent a doubling of algal biomass. Carlson TSI is calculated by using the following formulae:

60 14.41ln Equation (1.1)

9.81 ln 30.6 Equation (1.2)

14.42 ln 4.15 Equation (1.3)

, in which SD is Secchi depth (m), CHL is chlorophyll a concentration (mg m -3), and TP refers to total phosphorus (mg m -3).

Each of these three variables can theoretically be used to classify a water body, because they are interrelated by linear regression. If the three TSI values are not similar to each other, it is likely that algal growth may be light- or nitrogen-limited instead of P-limited, or that Secchi disk transparency is affected by erosional silt particles rather than by algae or something else (Pavluk and De Vaate, 2008).

According to Mayhew and Mayhew (1991) Carlson’s Trophic State Index has been used successfully to categorize a wide variety of lakes, and generally there is good agreement between indices calculated using different parameters such as chlorophyll a and transparency. The same author reported that it happens in certain conditions, due to non- algal turbidity (siltation and wave action) and very algal turbidity, that indices do not show any good relationship and agreement. In this case, trophic status as measured by chlorophyll a is artificially low, and that transparency, being usually easy to measure and a good indicator of productivity, is rejected as a measure of lake status under the assumption that it does not reflect algal productivity. This situation was reported by Mayhew and Mayhew (1991) for lakes with high silt loadings.

Another important characteristic of a water body, particularly lakes system, is the limiting factor, which determines to what extent the level of algae biomass growth may increase.

1.6.3. Limiting factor

One of the puzzles limnologists tried to solve was to explain why some lakes were more productive than others (Bachmann, undated). The issue related to lakes productivity was in practice of interest for both fish production and lake management. But, unlike the former, the latter was much more concerned about learning how to decrease the productivity of lakes in order to maintain or increase water clarity.

Primarily developed in the plant sciences, the concept of limiting factor was lately applied to lakes and ponds to explain the productivity differences between lakes. it says that the factor in the environment that is in shortest supply relative to the needs of plants will determine the amount of plant material produced. In other words, algae and aquatic plants, the primary producers in aquatic ecosystems, require the major nutrients-carbon, nitrogen, and phosphorus-in the approximate proportion of 41C to 7N to 1P (by weight). If one of these nutrients is present in a lower proportion, it may limit the algae or plant growth. This understanding is the foundation of Liebig’s Law of the Minimum, which states that the growth of a plant is limited by the material in least supply. So the question of interest is which of the three major nutrients is most likely to limit aquatic productivity.

The concept of limiting factors has achieved great success in the lakes related areas, where several lines of evidence have been used to show that the elements most often present in the smallest amounts relative to the needs of plant were either phosphorus or nitrogen. Actually every 100 grams of carbon used by plants in growth requires about 7 grams of nitrogen and 1 gram of phosphorus. However, in general carbon dioxide is plentiful in the atmosphere and in water, carbon seldom is limiting to aquatic productivity. Nitrogen gas is also abundant in the atmosphere, and many blue-green algae are nitrogen fixers. This means that they can convert nitrogen gas into the organic nitrogen required in cellular use. By contrast, phosphorus has no gaseous phase. Although it is found in phosphate rocks, fertilizers, human and animal waste, and organic material, and is required in a relative small proportion by aquatic plants, phosphorus is the most often the limiting nutrient in freshwater systems.

The limiting role of phosphorus does not necessarily mean that it is in short supply. Rather, it refers to the importance of phosphorus in regulating aquatic production. The addition to a phosphorus-limited system results in additional algae or plant growth. This is why phosphorus is the target of most lake management programs addressing excessive enrichment and plant growth. It is noteworthy that the concept of limiting factors is a valuable tool for lake and reservoirs management. It provides a logical and scientific basis for

determining what regulates the algal populations in a water body and leads to management option for their control.

As far as algae are concerned water temperature, light, and pH could play the role of limiting factor when high concentrations of phosphorus and nitrogen are supplied to the aquatic system. Phosphorus or nitrogen that is being supplied by whatever sources has certain capacity to sustain algae growth, and that capacity is called “carrying capacity.

1.6.4. Carrying capacity

The concept of carrying capacity of the resources in a given ecosystem to sustain a population has proved very helpful in planning measure to control the size of that population (Chorus and Mur, 1999). In other words, when applied to algae and cyanobacterial, this means asking questions such as: - How much biomass can be sustained on the basis of the amount of nitrogen available? - How much biomass can be sustained on the basis of the amount of phosphorus available? - How much biomass can be sustained with the amount of light that penetrate into the water? From practical point of view, at one moment or during one season, one of these three resources will limit the possible amount of biomass at a lower biomass level than the others. Furthermore the limiting resource may change seasonally, or according to the location of lakes whether at higher latitude or lower latitude (tropical climate).

Turbidity that is generated by excess supply of nutrients leads generally to light becoming the resource limiting further growth, and in this situation algal biomass will be light-limited rather than nutrient-limited..

The carrying capacity is a tool for managing a water body, as it is important to be able to estimate which of the key resources (light, nitrogen, or phosphorus) is likely to control phytoplankton biomass in any given system. According to Chorus and Mur (1999), that leads to ask the following question: - Which resource determines the carrying capacity for phytoplankton? - How high is the carrying capacity?

One approach recommended by the same author is to look at the relative amounts of these nutrients in phytoplankton biomass, known as “Redfield ratio” by mass (Chorus and Mur (1999) citing Round, 1965). These ratios are: 42C:8.5H:57O:7N:1P. It is important to note that hydrogen and oxygen are never limiting in aquatic environment.

On the other hand, cyanobacterial and many other phytoplankton organisms have developed storage mechanisms for phosphate (known as luxury uptake). These enable them to store enough phosphate for 3-4 cell divisions. As a consequence, one cell can multiply into 8-16 cells without requiring any further phosphate uptake, and biomass can increase by a factor of 10 or more even dissolved phosphate is entirely depleted (Chorus and Mur, 1999). This is why it is difficult to predict biomass growth, in addition to already biomass present, from the concentration of dissolved phosphate.

Another kind of tool that may help manage lakes system is modelling. Nowadays, this kind of tool is widely developed when it comes to aquatic ecology related issues.

1.6.5. Modelling

Ecological modelling originates from Lotka-volterra and Streeter-Phelps in the 1920s, while the comprehensive use of models in environmental management started in the beginning of the 1970s (Jørgensen, 1999). Today more than 4000 ecological models have been used in research or environmental management. The development of modelling tool is based on better knowledge of how the ecosystem is functioning, the focal problem to be resolved, and enough data to be used as input.

In practice one needs models for different purposes, such as analysing tool, interpolation, extrapolation, and budgeting, models to quantify immeasurable processes, model prediction as a management tool. The main advantage of using models is that we can assess the consequences of our actions in advance and at very low cost.

According to Soetaert and Herman (2009) a model is assumed to be right until proven wrong. Their development, as in other scientific disciplines, follows different phases. A model must start by defining the problem and the objective for the modelling. Models are based on and start with the writing of the conceptual model, in which all the components of interest must be related to each other according to the kind of relation existing between each components (for example exchange of energy, substances). At this point, in order to simplify, should be made all assumptions. Then the interactions and flow between components are translated into mathematical formulation in a form of a set of differential equation(s). The parameters in the equation must be assigned values from either measurements or literature, or by using estimation procedure.

After the values are assigned, one may look to for a method that will give a mathematical solution to the problem. Finding the mathematical solution allows the calculation of variable dynamics or how variable of interest evolves in time.

The comparison of the output of the model to field or experimental data will check whether the model represents accurately the real system, and this process is called validation. Then,

one can check as well how sensitive is the model to certain parameters through the sensitivity process. The results of all these processes and checking lead the developer to decide for immediate application when judged good enough or reformulate to improve the output.

Models are being widely used for lake management for predicting or assessing the dynamic or behaviour of one or more component, and in wastewater treatment as tool for designing the treatment plant (for example capacity, process).

1.6.6. Water and Wastewater treatment

There are a wide variety of water and wastewater technology but the choice of treatment operation depends on the quality and variability of the raw water source and the treatment objectives, which may vary for industrial as opposed to municipal needs (Drosde, 1997). Wastewaters are normally treated by a combination of physical-chemical and biological operations. However, these operations can be used without any combination or combine. Review of the different techniques relevant to the present study is given in Chapter 4.

CHAPTER 2 Materials and methods

Since 2005 sporadic or short term survey of Lake Ranomafana water quality has been conducted in order to have a vague idea on how the quality of water is affected by the discharge of wastewater to the lake, and about the trends of changes in water quality with respect to time as a result of changing anthropogenic pressure (demography, sanitation practice, slum area) from surrounding neighbourhoods. As those data presented wide gaps with respect to chemical and biological parameters, making not possible the trophic status of the lake to be defined and the process of degradation to be understood, it was documented and decided that only a monitoring programme would provide required data to thoroughly study Lake Ranomafana. This was the reason of designing and implementing the monitoring programme on the lake in Antsirabe over the year 2009.

The objective of this chapter is to present the approach used to realise the field work within the lake and on the two main inlets (inlets East and West) over the year 2009. The materials and methods used in the field and in the laboratory for conducting chemical/biological testing and, for collecting water and sediment samples are also presented in this chapter in addition to the explanation of the modelling development as a tool for studying the chemical and biological processes taking place in the lake while clarifying its behaviour when experiencing different cases of pollution mass loading.

In parallel to the laboratory testing of water and sediment samples, experimentation on collected samples of sediment was performed at the laboratory in order to understand the flux of nutrients between sediment and water column.

2.1. Field work and study site

2.1.1. Design of the monitoring programme

By definition, according to J. Bartram and R. Ballance (1996), “Monitoring” is the long-term, standardised measurement and observation of the aquatic environment in order to define status and trends. It is important to emphasize the collection of data for the below purposes during the monitoring term, which was fulfilled by carrying out field work.

2.1.1.1. Objective and principle

The field work, as part of the lake study, consisted of almost one year-monitoring of both Lake Ranomafana and its main inlets for the following objectives: - Collect baseline data on the pollution mass loading discharged into the lake from the main inlets;

- Collect monitoring data for better characterizing the lake, from point of view physical, chemical and, biological patterns; - Collect baseline data for a better understanding of the lake’s functioning and the origin of the physicochemical and biological processes it undergoes, leading to its quality and status degradation; and also - Collect data for developing models that can simulate the lake behaviour facing different cases of pollution mass loading.

It consisted of performing physical and chemical measurement at different selected stations within the lake, and of collecting water and sediment samples from those stations and from two main inlets.

The field measurement and testing conducted in the lake and completed in the laboratory at CNRE in Antananarivo aimed at understanding the functioning of the lake and at characterizing its trophic status. The collected data were also used for modelling the lake. In order to facilitate access to each station a fishing pirogue (Figure 11) from southwestern of the country was used to carry out monthly field work in the lake.

Figure 11: South western traditional fishing pirogue used during field work

2.1.1.2. Description of the study site: Lake Ranomafana

2.1.1.2.1. Physical environment

The current field work was conducted in Lake Ranomafana (Figure 12), a very shallow and small size urban man-made lake located within a valley in the centre of the city of Antsirabe (latitude 19°52’ S, longitude 47°01’ E). According to the second Master Plan document of Antsirabe municipality (Scheme for urban sanitation, 2003) the catchment area of the lake is of 125Ha including the following neighbourhoods: Fokontany Atsimon-tsena (14Ha, western part), Fokontany Antsenakely (10Ha, eastern part), Fokontany Avaratsena, Mahazoarivo avaratra/atsimo (87 Ha), and the zone of the lake and the spa infrastructure (14Ha, with the

swimming pool building), and home to 39,527 inhabitants. The lake’s watershed is mainly urban residential areas, and it is comprised of dwelling houses, hotels, hospital, confessional and administrative buildings, market, swamp areas, and rice field area.

Figure 12: Lake Ranomafana and surrounding watershed (Google Earth, 2011)

The Ranomafana Lake is naturally supplied with water from the thalweg north to the lake, the source of thermal water (formerly called hot spring Ranomafana), and a water resurgence coming from eastern part of the lake. It also receives both storm water runoff and wastewater from the surrounding neighborhoods and the spa treatment centre through inlets.

Wastewater from the spa treatment centre is usually warmer around 34°C to 37°C. The Master plan document provided an estimated discharge of domestic wastewater into the lake as about 870m 3/d (our estimation was about 874m 3/d). The influent comes permanently from two inlets (East and North-west). However, there are other 8 more or less small inlets discharging to Lake Ranomafana. They are flowing mostly during the rainy season from around the end of October to the end of April. They are used for discharging storm water runoff from around neighbourhoods. As such, they transport sediments and solid waste local population used to throw or dump in this drainage system. It is noteworthy that there is no industrial wastewater discharge running in the lake. On the other hand, there is no outlet but rather a water gate for regulating the level of the lake. Thin stream of water escapes from the gate towards a canal which crosses a watercress field southward.

The discharge of domestic wastewater rich in nutrients (reactive phosphorus and nitrogen) and heavily contaminated by pathogens has accelerated the degradation of the lake water quality, particularly its trophic status. The climate of the region of Vakinankaratra and particularly Antsirabe is classified as tropical in altitude, above 900 m, since being part of the High plateau. It is characterised by a mean annual temperature below 20°C. There are three distinct seasons:

- An humid and more or less warm season from November to April; - A dry and cold season from April to July; - A dry and relatively warm season from mid August to October.

Antsirabe, being situated more or less in the centre of the region of Vakinankaratra, is in the high altitude zone where the annual mean temperature is around 13°C with maxima of 26°C and minima of 1°C (Figure 13).

Monthly mean temperature 25

19,7 19,7 19,2 19,2 19,4 20 17,8 17,8 15,3 15,5 15 13 12,8 13,3

10 Temperature(°C) 5

0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Month Figure 13: Monthly mean temperature variation (source: Direction Générale de la Météorologie )

In the most part of the region of Vakinankaratra, the dry season commences from May to November whereas the rainy season starts from December to April. As concern the city of Antsirabe, the average annual rainfall is estimated to 1330.6 mm, and the regime of precipitation is as shown in Figure 14.

Monthly rainfall regimes 350 291 300

250 218 215 200 177 Rainfall (mm) Rainfall 150 112 88 100 69

50 20 8 6 5 16 0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Month

Figure 14: Monthly rainfall variation (Source: Direction Générale de la Météorologie )

The rainy season is characterised by a sunny morning before a rainy afternoon which sometimes occurs as heavy local storms up to the beginning of the night.

The duration of insulation does not vary too much along the year although longer duration is observed during dry season from April to November (Table 4).

Table 4: Monthly Insulation pattern Month

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Duration of insulation (Hours) 6 6 8 8 7 7 7 8 9 8 9 6

Located within a zone of depression, the prevailing wind pattern in Antsirabe is either East or North-East. The wind speed may reach 7 to 10 km/h. The afternoon seems to be much windy. The wind pattern is shown in Figure 15.

Figure 15: Annual wind regimes in Antsirabe (source www.weatheronline.co.uk)

Due to the specificity of Lake Ranomafana (small area, very shallow, absence of natural outlet), most of the hydrological characteristics of lakes such as hydraulic retention time, that are relevant to the study cannot be defined accordingly. As Bartram and Ballance (2001) stated, thermal stratification does not occur in lakes less than about 10 m deep because wind across the lake surface and water flow through the lake tend to encourage mixing. Field data do confirm this statement as far as temperature is concerned.

2.1.1.3. Selection of the measurement and sampling stations

In order to implement a site specific and effective monitoring programme, with appropriate temporal and spatial resolution to detect changes in water quality (Udy et al , 2005) and to collect representative samples from the lake while taking into consideration the morphology and the shape of the lake, 5 sampling stations have been selected within the lake. In this study, sampling station is referred to as the exact place at which the sample is taken (Bartram and Ballance, 2001) and the field measurement is carried out. Their location is related to the physical environment of the lake, as: - Station 1 relates to the location of the inlet East, - Station 2 still relates to the inlet East with a view on the horizontal dispersion of the pollution loading from the inlet East, - Station 3 relates to the location of the inlet North, - Station 4 represents the middle of the lake, and - Station 5 nearby the gate. All sampling stations are accessible only by pirogue and situated at different depth (Figure 16).

Figure 16: Location of sampling stations (Google Earth, 2011 )

The characteristics of each sampling and measurement station are given in Table 5.

Table 5: Main characteristics of sampling stations Coordinate Station Depth (m) Altitude (m) Latitude Longitude 1 19°52’148 S 47°01’877 E 0.6 1485 2 19°52’196 S 47°01’861 E 0.6 1485 3 19°52’190 S 47°01’813 E 0.6 1485 4 19°52’260 S 47°01’826 E 0.7 1485 5 19°52’345 S 47°01’817 E 0.9 1485

Inlets Origin and comments Inlets East Resurgence, clean water from the source is used for washing clothes before the discharge in the lake Inlet West From the northern part of the lake streaming domestic wastewater discharge from surrounding neighbourhoods

2.1.1.4. Monitoring media and measured variables

The choice of media and variables used for the monitoring of Lake Ranomafana was made in order to achieve the objectives of the study aforementioned, with a special focus on the trophic state of the lake and modelling lake’s processes. So, the principal media which have been used for the entire duration of the monitoring were: - Water, - Particulate matter (suspended particulates and deposited sediments). The water part consisted of 2 components as following: - From the lake, - From the main inlets (east and west) having permanent flow. On the other hand, selected variables, being tested included physical, chemical, and biological, and consisted of two sets: - Variables measured in situ, - Variables measured in the laboratory.

Table 6 below gives more details about each medium and related variable tested on.

Table 6: Media and variables used for monitoring Lake Ranomafana Medium Sampling station Collected Variables tested Variables tested sample in situ in laboratory TSS, VSS, TS, TVS, TDS, TDVS, Temperature, Reactive Depth, pH, Phosphate, Conductivity, Total Lake Water Water Dissolved Phosphorus, Ranomafana, oxygen, Nitrite, Nitrate, Turbidity, TKN, Total Transparency Nitrogen, BOD, COD, Chlorophyll a

Reactive Phosphate, Total Inlet East, inlet Water Water Phosphorus, North Nitrite, Nitrate, TKN, Total Nitrogen Humidity, TS, TVS, Reactive Particulate Lake Deposited phosphate, matter Ranomafana sediment Total Phosphorus, Total Nitrogen

It is worth while noting that the most common combination of variables readily testable in situ, consisting of temperature, pH, conductivity, dissolved oxygen, turbidity, depth, and transparency, were measured on field while sampling water and sediment.

2.1.1.5. Frequency and timing of sampling

Based on existing data gathered during previous surveys, and according to specialised literature (Bartram and Ballance, 2001; Chapman, 1992), the sampling frequency on a monthly basis is supposed acceptable for eutrophication monitoring. The timing of the sampling was scheduled during the first week of the month, on Wednesday. The choice of the sampling day was justified by the BOD analysis constraint avoiding the seventh day of reading to fall during the weekend. Sampling and field measurement were carried out twice, in the morning and in the afternoon, in order to capture the effect of biological processes that take place on day time (algal biomass, dissolved oxygen, pH).

2.1.1.6. Field work and sample collection

During the previous survey of the quality of Lake Ranomafana all field measurement and water sampling activities were carried out at different locations along the lake’s shoreline, because of the lack of pirogue or small boat. That problem was resolved in 2009 when a fishing pirogue was used for accessing sampling stations located within the lake. Each station was exactly located with A Garmin GPS 48 prior sampling and field measurement.

2.1.1.6.1. Water

Because of the distance between the CNRE laboratory, based in Antananarivo, and the study site in Antsirabe, the field work associated with the collection, preservation, and transport of samples was of fundamental importance as obtaining a sample that is fully representative

(Bartram and Ballance, 2001) in order to avoid compromising the whole sampling process and particularly the integrity of each sample collected.

2 acid-washed high density polyethylene containers of 1 litre capacity were utilized for collecting grab sample of water from each sampling station at about 20 cm below the surface. These high density polyethylene containers were also used for storing and transporting water samples from the study site to the CNRE Laboratory after stabilising with preservative. 1ml of concentrate sulphuric acid was added to one sample collected for COD, total nitrogen, and total phosphorus analyses while none preservative was added to another sample intended for BOD, solids, and chlorophyll a analyses.

On the other hand, for nutrients analysis (reactive PO 4, NO2, and NO 3) purpose, 100 ml of sample from non acidified sample, was filtrated using a syringe filter unit designed for quick filtration of up to 20 ml of water. 0.45 µm glass microfiber filters GF/C of 25 mm diameter were used with the syringe filter unit. The filtrate was chemically preserved with one drop of concentrate sulphuric acid prior to storing in a 250 ml low density polyethylene container.

For storage and transport purpose, all containers were kept into a big icebox refrigerated with icepacks. Treatment and chemical preservative used during each field campaign are summarised in Table 7 below.

Table 7: Size of sample and preservative treatments for transport and storage Treatment Maximum Parameter to Type of Sample size Sample type and permissible be tested container (ml) Preservative storage time BOD HDPE 1000 Grab sample Cool box 6h 1 ml H SO , COD HDPE 1000 Grab sample 2 4 7d Cool box Nitrogen 1 ml H SO , HDPE 1000 Grab sample 2 4 7d Kjeldahl Cool box Filter on Nitrate GF/C filter, 2 + LDPE 100 Grab sample drops of 1-2d

Nitrite H2SO 4, cool box Filter on GF/C filter, 2 Reactive LDPE 100 Grab sample drops of 28d phosphorus H2SO 4, cool box

Total nitrogen HDPE 1000 Grab sample Cool box 6h Total HDPE 1000 Grab sample Cool box 6h phosphorus TSS HDPE 1000 Grab sample Cool box 6h TS HDPE 1000 Grab sample Cool box 6h Chlorophyll a HDPE 1000 Grab sample Cool box 6h HDPE: High density polyethylene, LDPE: Low density polyethylene, cool box containing ice packs Source: Water quality monitoring, (Bartram and Ballance, 1996)

2.1.1.6.2. Sediment

Samples of sediment were also collected from the 5 sampling stations within the lake using one Van Veen grab sampler that is suitable for collecting undisturbed surface sediment. This model of sediment sampler is made from stainless steel with surface of 250 cm 2, and it could be hand-operated from the pirogue. 25 ml polystyrene container was filled with sediment collected from each station, and stored in an icebox refrigerated with icepacks. It is noteworthy that sediment samples were collected only in the morning.

2.1.1.6.3. Description of the field measurement

As mentioned in the paragraph treating “Monitoring media and variables” the most common variables readily measurable in situ were measured during the sampling process. Prior calibrated portable meter, WTW Multi 340i, was used for measuring the following parameters:

- Temperature : was performed during pH measurements as the WTW portable meter can be set to do so, provided the temperature sensor is being connected. Being a very shallow lake, only one measurement near the surface was considered as there was no significant difference with the measurement at the bottom. - pH : directly measured near the surface and at the bottom, values were recorded after each stable measured value was reached by using the “AutoRead” (AR) function, which is usually used for checking the stability of the measurement signal. - Conductivity : as per temperature only one value was recorded for both surface and bottom. - Dissolved oxygen : two values, near the surface and at the bottom, were recorded from each sampling station by using a WTW oxygen sensor CellOx 325. The “Auto Read” (AR) function was also activated so as to reach stable values.

Transparency was another parameter measured at each sampling station using a Secchi disc. It is a water quality characteristic of lakes and reservoirs that varies with the combined

effects of colour and turbidity (Bartram and Ballance, 2001). The Secchi disc is made of rigid wood of 30 cm diameter and is painted black and white (Figure 17). The disc is suspended on a light rope, and a weight fastened below the disc helps to keep the suspension rope vertical while a measurement is being made. Transparency was measured as well twice, in the morning and in the afternoon, through a shaded area of water surface.

Figure 17: Secchi disc for transparency measurement

Complementary to transparency is turbidity, which was measured at each sampling station with a quick and reliable instrument, portable microprocessor turbidity meter HI 93703 HANNA (Figure 17). The meter covers a 0 to 1000 FTU range in two scales: 0 to 50 FTU and 50 to 1000 FTU. It functions by passing a beam of infrared light through a vial containing the sample being measured.

Depth measurement at each sampling station was also performed during most of the field work by using either a depth meter or a metered sounding pole. It is worthwhile noting that manual soundings of depth were made at the beginning of the monitoring in February 2009. Instead of using transects between shoreline points as should be, the depth at different locations within the lake was measured and recorded, and then plotted in order to establish the depth contours map.

2.2. Laboratory analyses and analytical methods

Complementary to measurement performed in situ during field work, all collected samples, either water or sediments, were brought to the central laboratory at CNRE in Antananarivo and immediately analysed. Due to storage conditions constraint the samples of water with no preservative were given priority to analyses. In that way BOD and nutrients were tested first while the preserved ones and the samples of sediment were kept in refrigerator.

The Figure 18 below presents an overview of what kind analysis the collected samples were destined for.

Samples

Water Sediment

1000 ml in 1000 ml in 100 ml Dilution Dilution TS, TVS HDPE HDPE in LDPE

BOD, TSS, + Filtration, Filtration TN, TP

TS, Chl. a, H2SO 4 + H 2SO 4 TN, TP

COD NO 3, NO 2 , R. PO 4 R. PO 4

Figure 18: Schematic presentation of media quality monitoring

2.2.1. Analyses of water samples

2.2.1.1. Determination of biochemical oxygen demand (BOD)

Biological oxygen demand is the estimated amount of oxygen that is required by microorganisms whilst breaking down organic matter. The BOD test measures the oxygen consumed by bacteria whilst oxidizing organic matter under aerobic conditions (Tebbutt, 1998). In that way BOD is used as an approximate measure of the amount of biochemically degradable organic matter in a sample (Bartram and Ballance, 1996) by measuring the amount of oxygen consumed by bacteria during the 5-day incubation period at 20°C in a refrigerating incubator.

According to the standard method used, NF T90 – 103 (December 1970), the principle of the method is that microorganisms, mainly bacteria, degrade organic matter in the tested sample, and the corresponding oxygen consumption being measured. The sample is diluted to an extent level so that the oxygen into the sample is sufficient to maintain degradation over 5-day period. For this purpose the sample was prepared by adding well aerated dilution water containing seed, which was made from fresh sewage effluent added to prior aerated distilled water containing phosphate buffer solution and nutrient salt solution.

Two dilutions were prepared from 40 ml and 70 ml of grab sample to be diluted to 330 ml each with dilution water. Karlsruhe BOD bottles of 330 ml capacity were filled with diluted samples and were incubated at 20°C in a refrigerating incubator over 5-day period. The dissolved oxygen content of the liquid was determined before and after incubation, the difference gave the BOD (ref equation 2.1). Each sample was analyzed with duplicates at different dilutions, and the BOD value was obtained from the average of the duplicates.

BOD = F (To – T5) – (F – 1)(Do –D5) (Equation 2.1) Where: - Do: the oxygen content of the blank (BOD bottle filled only with seeded dilution water) at the time of filling, mg/l - D5: the oxygen content of any dilution of the sample at the time of filling of the vials, mg/l - To: the oxygen content of this dilution of the sample after 5 days incubation, mg/l - F: the dilution factor and given by the formula F = V1/Vo, with V1 the volume of the incubation bottle (330 ml) and Vo the volume of undiluted sample. -

2.2.1.2. Determination of chemical oxygen demand (COD)

Chemical oxygen demand is a measure of the oxygen equivalent of the organic matter in a water sample that is susceptible to oxidation by a strong chemical oxidant (Chapman, 1992), potassium dichromate in our case. Although COD can be determined on either filtered or unfiltered samples, the COD tests were carried out using the latter to obtain total COD. Using the standard method, AFNOR T91/K (September 1971, ISO 6060), whose principle consists of boiling the sample under acidic condition and under reflux with potassium dichromate (K 2Cr 2O7) along with silver sulphate (Ag 2SO 4) playing the role of oxidation catalyst, and sulphate mercury (II) (HgSO 4) is being used to inhibit any eventual chloride ions. Part of the dichromate is reduced by organic matter and the excess is being titrated with ferrous ammonium sulphate (Fe (NH 4)2(SO 4)2.2H 2O).

The COD value is determined by calculating the quantity of potassium dichromate reduced by using the following equation:

COD = 8000 c (V1 – V2)/Vo (Equation 2.2) Where: - c: concentration of the solution of ferrous ammonium sulphate (mol/l) c = 5 x 0.04 x 6/v = 1.2/v, with v the used volume (in ml) of solution of ferrous ammonium sulphate for its titration. - Vo: volume of the sample, ml

- V1: volume of the solution of ferrous ammonium sulphate used for blank titration, ml - V2: volume of the solution of ferrous ammonium sulphate used for sample titration, ml - (V1>V2)

2.2.1.3. Determination of nitrogen compounds

Very essential for living organisms as an important constituent of proteins, nitrogen, as part of it cycle, generally undergoes biological and non-biological transformation in the environment to produce organic and inorganic forms of nitrogen. Inorganic nitrogen occurs - - + in a range of oxidation states as nitrate (NO 3 ) and nitrite (NO2 ), the ammonium ion (NH 4 ) and molecular nitrogen (N 2), (Chapman, 1992). As concern algae growth that might be limited by more than one nutrient (Jørgensen, 1980), nitrogen may happen to be the limiting factor leading to this element playing significant role as far as lake management is concerned.

2.2.1.3.1. Nitrate

Determination of nitrate is quite important as it gives a general indication of the nutrient status and level of organic pollution. The most highly oxidised form of nitrogen compounds is commonly present in surface and ground waters, because it is the end product of the aerobic decomposition of organic nitrogenous matter (Bartram and Ballance, 1996).

According to the sodium salicylate method from Rodier (2001), the principle of nitrate determination is based on the transformation of nitrate, when in the presence of sodium salicylate, into yellow colour paranitrosalicylate. This latter, sensitive to a colorimetric determination, was then determined by using Beckman DU 64 spectrophotometer at a wavelength of 415 nm. A calibration curve was used for the calculation of the nitrogen concentration, expressed as mg N-NO 3/l of sample. To express results in NO 3, multiply the result by a factor of 4.43.

2.2.1.3.2. Nitrite

Likewise nitrate, the determination of nitrite also finds its importance as being part of a general indication of the nutrient status and level of organic pollution. As an intermediate oxidation stage not normally present in large amounts (Tebbutt, 1998), nitrite is an unstable form of oxidised nitrogen generated during biochemical processes in surface water. It is formed either by the oxidation of ammonia or by the reduction of nitrate, also known as nitrification in a well oxygenated medium and denitrification in a poor oxygenated medium.

During this study, all nitrite testing was performed according to the method described by Alain Aminot Chaussepied and Marcel (1983). The principle of the method is based on the following reaction phases: (1) nitrite reacts with sulphanilamide under strong acid condition (pH<2) producing an intermediate product called diazo, (2) diazo reacts with N-(1-naphthyl)- ethylenediamine dihydrochloride to form an intensely pink-coloured azo-compound, as presented below. + NH 2SO 2C6H4-NH 2 + NO 2 + 2H (NH 2SO 2C6H4-N≡N) + 2H 2O (1)

Then, the diazo reacts with N-(1-naphthyl)-ethylenediamine dihydrochloride to form azo- compound of pink coloured:

+ (NH 2SO 2C6H4-N≡N) + C 10 H7 – NH – (CH 2)2 – NH 2 →NH 2SO 2C6H4 - N=N – C10 H6 – NH – (CH 2)2 – + NH 2 + H (2)

The dye is proportional to the concentration of nitrite present in the sample, and the absorbance of this latter being measured at 543 nm with a Beckman DU 64 spectrophotometer. The concentration is calculated from a pre-established calibration curve.

2.2.1.3.3. Total Kjeldahl nitrogen (TKN)

Very useful determination for appreciating the level of organic and ammonia nitrogen compounds in a sample, Kjeldahl nitrogen is defined as the sum of the aforementioned compounds. Unfiltered sample was used for the determination according to the analysis protocol described in NF EN 25663 (January 1994, ISO 5663). The principle is based on the mineralisation of organic nitrogen compounds in the presence of concentrated sulphuric acid and selenium as a catalyst. After digestion, the solution containing the obtained ammonia is steam distilled in an alkaline medium using concentrated sodium hydroxide, and distillate back titrated with diluted sulphuric acid (0.02N) in the presence indicator (solution of methyl red and bromocresol green). TKN concentration, expressed as mg N l -1, is given by:

TKN = 0.02v (1000 x 18) / V (Equation 2.3)

Where: v: volume of 0.02N sulphuric acid used for the titration, ml V: volume of sample (150 ml)

2.2.1.4. Determination of phosphorus compounds

Phosphorus is an essential nutrient for living organisms and exists in water bodies as both dissolved and particulate species. It is generally the limiting nutrient for algal growth and, therefore, controls the primary productivity of a water body (Chapman, 1992). Present mostly in fertilisers and in many detergents, but also in municipal wastewater, which may

contain from 4 to 16 mg/l (Tchobanoglous et al , 2003), phosphorus generally reaches the water bodies through sewage, industrial wastes and storm run-off. The forms phosphorus compounds occur in natural waters and wastewaters comprise the orthophosphate, polyphosphate and organic phosphate, but only orthophosphates are available for biological metabolism without undergoing any breakdown.

2.2.1.4.1. Reactive phosphate

Also known as dissolved orthophosphates, reactive phosphate occurs mostly with polyphosphates and organically bound phosphates, in natural waters and wastewaters. As such, it was determined from a field filtered and acid-preserved water samples. The determination, according to the standard NF T 90-023, is based on the reaction, under acid condition, between orthophosphate and ammonium molybdate to form a complex molybdophosphoric acid, which is transformed, by reduction with ascorbic acid, to a blue coloured complex known as molybdenum. Maximum absorption of the blue complex is at 880 nm using Beckman DU 64 spectrophotometer. Potassium antimonyl tartrate is added in order to increase the coloration and the velocity of the reaction at room temperature. Pre- established calibration graph was used to calculate the concentration of reactive phosphate in mg P l -1 after measuring the absorbance of the blank using distilled water.

2.2.1.4.2. Total phosphorus

Simultaneous persulphate oxidation for the determination of total nitrogen and phosphorus compounds, according to the standard chemical methods for marine environmental monitoring (UNEP, 1991), was used for the determination of total phosphorus from raw water samples. The principle of this method consists of quantitatively converting organically bound phosphorus into phosphate with peroxodisulphate (potassium peroxydisulphate) in an alkaline medium (wet oxidation). The digestion is performed in an autoclave at 120°C for 30 minutes. Phosphorus compounds obtained after completion of the oxidation step are determined as orthophosphate according to the procedures outlined for reactive phosphate determination.

2.2.1.5. Solids analyses

Solids may be present in water bodies in suspension and/or as dissolved form. They may be of organic or inorganic origin from the catchment area, eroded from lake shore and resuspended from the lake bed.

2.2.1.5.1. Total suspended solids (TSS) and volatile solids (VSS)

They are portion of total solids retained on a filter with a specified pore size. The determination of TSS was carried out by the vacuum filtration of 100 ml of water sample through a preweighed 0.45 µm Whatman GF/C glass-fibre paper followed by 2 hours drying

in an oven at 105°C. TSS are given by the increases in weight after drying while VSS are those lost on firing at 550°C for 30 min in a muffle furnace. The combustion process converts the organic matter into carbon dioxide and water, which have volatilized.

TSS and VSS are calculated by using the following formulas:

TSS . (mg/l ) (Equation 2.4)

VSS . . (mg/l) (Equation 2.5)

Where: - Mo: the initial mass of the GF/C filter, g - M1: mass of the filter with suspended solids after evaporation at 105°C for 2 hours, g - M2: mass of the filter after ignition at 550°C for 30 min, g - Vs: volume of sample that is filtered, ml. According to Environmental chemistry laboratory experiment at the University of Stavanger we assume that the Whatman GF/C filter, after combustion, looses approximately 1% of its initial weight.

2.2.1.5.2. Total solids (TS) and total volatile solids (TVS)

“Total solids” is defined as the material residue left in the vessel after evaporation of a sample and its subsequent drying in an oven at a defined temperature. “Total solids” includes the portion retained by a filter (TSS) and the portion that passes through the filter (TDS). 30 ml of sample in a preweighed crucible porcelain is evaporated to dryness in an oven at 105°C for 24 hours and subsequently weighed. The increase in weight represents TS prior to firing the residue in a muffle furnace at 550°C for 1 hour. TVS is given by the loss in weight after combustion.

The concentrations of TS and TVS are determined using the following expressions:

TS . (mg/l ) (Equation 2.6)

TVS . (mg/l ) (Equation 2.7)

Where: - Mp: initial mass of crucible porcelain, g

- Mp1: mass of crucible porcelain with residue after evaporation at 105°C during 24 hours, g - Mp2. Mass of crucible porcelain with residue after ignition at 550°C for 1 hour, g - Vs: volume of sample, ml It is noteworthy that total dissolved solids (TDS) concentration (mg/l) was deduced from the difference between TS and TSS.

2.2.1.6. Analysis of chlorophyll a

Present in most photosynthetic organisms, chlorophyll a provides an indirect measure of algal biomass and an indication of the trophic status of a water body (Chapman, 1992). In fact, algal abundance can in turn shape the structure of aquatic ecosystem (Phlips, undated). The analysis was performed according to the method described by Bartram and Ballance (1996), which consists of filtering a volume of sample (250 ml in our case) using a 1 µm pore size glass fibre (GF/C grade) filter of 47 mm diameter followed by solvent-extraction using 8 ml of 90% acetone. The solvent extract is subsequently clarified by centrifugation for 15 min at 3,000 rev/min before measuring spectrophotometrically at the following wavelengths: 750 nm and 663 nm before acidification of the extract, 750 nm and 665 nm after acidification of the extract. Ultraviolet and Visible Beckman spectrophotometer DU 64 equipped with 1cm path length cuvettes was used for the determination. The method allows the determination of phaeophytin, which is the degradation product of chlorophyll a as the filtration process cause phytoplankton cells to die. As reported by Chapman (1996) a rough estimate of phytoplankton organic carbon can be obtained from a measurement of total pigments (i.e., chlorophyll a + phaeopigments) which represent approximately 30 times the total pigments (in mg/l). The chlorophyll and phaeophytin concentrations were calculated using the following formulas: Subtract absorbance: 663a – 750a = corrected 663a absorbance 665b – 750b = corrected 665b absorbance Values from corrected 663a and 665b absorbance are used to calculate the above elements as follow:

Chlorophyll a . : (mg/m3) (Equation 2.8)

Phaeophytin a . . . (mg/m 3) (Equation 2.9)

Where: - Ve: volume of acetone extract (litres) - Vs: volume of water sample (m 3)

- l: path length of cuvette (cm) The ratio of chlorophyll a to phaeophytin gives an indication of the effectiveness of the sample preservation (Bartram & Ballance, 1996).

2.2.1.7. Alkalinity

Alkalinity refers to the buffering capacity of a water body. It represents the ability of a water body to neutralize acids and bases thereby maintaining a fairly stable pH. Compounds such as bicarbonates, carbonates, and hydroxides, by combining with H + ions from the water, play an important role in buffering since these reactions raise the pH (more basic). A well buffered lake also means that daily fluctuation of CO 2 concentrations result in only minor changes in pH throughout the course of a day. Eutrophic (high nutrient) lakes tend to have higher alkalinity.

Few tests of alkalinity were carried out on the water samples collected from the lake by using a colorimetric method and ready to use tablet reagents that is just added to 10 ml sample in a test tube. Tests were performed on a Wagtech direct-reading photometer 7000Se (Palintest).

2.2.1.8. Silica

Silica is widespread and always present in surface and groundwater. Its determination is important as being an essential element for certain aquatic plants (principally diatoms). It is taken up during cell growth and released during decomposition and decay giving rise to seasonal fluctuations in concentrations, particularly in lakes (Chapman, 1992). Likewise alkalinity, tests were performed on a Wagtech photometer using ready to use tablet reagents to be mixed and dissolved to 10 ml of water sample in a test tube before direct-reading of the silica concentration.

2.2.2. Statistical analyses

As far as water chemical data are concerned they were subjected to statistical analyses wherever it was necessary so as to better understand the pattern of changes or variations either seasonal or site specific. SPSS 11.5 for Windows software was used to perform statistical analyses.

2.2.3. Analyses of sediment samples

The role of sediment studies in limnology has been a rapidly developing field of research as more complementary and relevant information may provide insight into, not only past alteration in chemistry, flora and fauna, but also ongoing processes that have induced changes in productivity of the lake system (G. Wetzel, 2000). Also, lots of literature on sediments clearly reveals the prominent role that they play in elemental cycling (Chapman,

1992). The use of sediment information in understanding water quality issues in lakes, however, requires intensive sampling followed by sediment samples analyses in relation to the study purpose.

2.2.3.1. Texture and particle size

Texture represents the composition of sediment constituents, generally made up of clay, silt and, sand (fine or coarse). Indeed, there is a marked relationship between the particle size and its origin (allochthonous and autochthonous matter) (Chapman, 1992). Separation of different fractions was obtained by dry sieving of sediment samples. After sieving, clay < 20 µm, silt 20-50 µm, and sand > 50 µm fractions were separated and weighted in order to calculate the percentage of each fraction. Texture is determined by using Shepard’s (1954) classification ternary diagram based on relative percentages of sand, silt, and clay.

2.2.3.2. Total solids (TS) and total volatile solids (TVS)

Sediment total solids are equivalent to dry weight, which is obtained from drying in an oven at 105°C during 24 hours around 2 g of homogenized wet and fresh sediments in weighed crucibles porcelain. Likewise water samples, crucible porcelain with residue after evaporation at 105°C was heated in a muffle furnace to 550°C for 1 hour. TS and TVS are determined according to the following formula (Tchobanoglous et al, 2003):

TS . (mg/g) (Equation 2.10)

TVS . (mg/g ) (Equation 2.11) Where: - Mp: initial mass of crucible porcelain, g - Mp1: mass of crucible porcelain with residue after evaporation at 105°C during 24 hours, g - Mp2: mass of crucible porcelain with residue after ignition at 550°C for 1 hour, g - Ms: mass of sediment sample, g

2.2.3.3. Determination of phosphorus compounds

In lake studies the importance of sediments to phosphorus cycling cannot be overlooked. According to specific conditions, principally the oxygenation of lake waters, sediments could play the role of sink and also supply to phosphorus.

2.2.3.3.1. Dissolved orthophosphate

Dissolved orthophosphate concentration was measured in solution, according to the standard NF T 90-023, after stirring around 1 g of fresh sediment with 100 ml deionised water over 30 min using magnetic stirrer. Then, the mixture was left to settle for half a day before filtering. 20 ml of filtrate were used for the spectrophotometer measurement.

2.2.3.3.2. Total phosphorus

The method used to determine total phosphorus was the same as that used for water samples, i.e. simultaneous persulphate oxidation for the determination of total nitrogen and phosphorus compounds, according to the standard chemical methods for marine environmental monitoring (UNEP, 1991). About 1 g of fresh sediment was weighted and mixed with 100 ml deionised water. After 30 minutes of magnetic stirring, 50 ml of sample were used for autoclave oxidation. The sample was then left to cool and settle. Total phosphorus was determined as orthophosphate, according to NF T 90-023, using 20 ml of supernatant.

2.2.3.4. Determination of total nitrogen

Likewise phosphorus, sediments play an important role in sequestrating and releasing nitrogen according to specific conditions, much more related to overlying lake waters quality. Total nitrogen was determined as nitrate from sample used for phosphorus and nitrogen simultaneous persulphate oxidation.

2.2.3.5. Determination of iron and manganese

The method followed was that used for the analysis of trace metals in biological and sediment samples in marine environment, according to the laboratory procedure book (IAEA, undated).

Firstly, the sediment samples were digested in closed Teflon vessels with 8 ml aqua regia, a mixture of concentrate nitric and hydrochloric acid (HNO 3 : HCl, 1/3 v/v), on hot plate for 6 hours. After digestion, samples were transferred and diluted in volumetric vessels. The diluted digests were analysed using flame atomic absorption spectrophotometer (FAAS Varian 40). Concentrations of iron and manganese were calculated (as dry weight) according to the following formula:

C .. (µg/g) (Equation 2.12)

Where: - C: concentration of element in original sample (µg g -1 dry weight) -1 - Cd: concentration of element in sample solution (µg mL ) -1 - Cb: mean concentration of element in reagent blanks (µg mL ) - V: volume of dilution of digested solution (mL) - W: dry weight of sample - F: dilution factor, if needed (=1 in case of no additional dilution other than that resulting from digestion procedure)

2.2.3.6. Sediment nutrients flux

An attempt to assess the effect of light and pH on reactive phosphate flux was carried out using sediment samples. The experiment was conducted in the light of the study realised by Spears et al (2008), but with some modifications. Sediment samples, without overlying water column, were collected from the middle part of the lake using a Van Veen grab sampler.

For the experiment, about 12 cm of sediment was put into 500 ml cylinder (internal diameter 4 cm and height 32 cm). 100 ml of deionised water was siphoned over the sediment. Few drops of hydrochloric acid were added to overlying water of the first cylinder to get acidic condition (pH=6). To the overlying water in the second cylinder were added few drops of sodium hydroxide, to create basic condition (pH=9). The third cylinder was left with only deionised water so as to have neutral condition. The experiment (Figure 19) was performed under room temperature of about 27°C.

Figure 19: Materials for testing nutrient flux between sediment and water column

The experiment consisted of leaving the cylinders in the natural room light between 8 a.m. and 4 p.m. Daily water samples (20 ml) were collected (4 p.m.) from about 1 cm above the sediment surface using a syringe and tested for reactive phosphate (NF T 90-023). Then, the cylinders were left in a cupboard in the darkness, and daily water samples were collected (4

p.m.) on same conditions. The effect of oxygen on phosphate flux was also assessed by bubbling with air (4 hours) the overlying water (10 cm above the sediment surface) using a small pump. Same volume of samples, as previously, was collected for testing reactive phosphate.

2.2.4. Assurance quality (AQ) and Quality control (QC) of the CNRE water testing laboratory

Very important to note the participation of the water testing laboratory to the SADC WaterLab profeciency testing scheme for chemical analysis of potable water in Africa in which many chemical components, such as NO 3 and PO 4, are being tested. Furthermore, the laboratory is participating to the International Atomic Energy Agency (IAEA) proficiency testing on environment samples (sediments, biota, and wastewater).

2.3. Development of Lake Ranomafana model

Full study of physical, chemical, and biological processes going on in Lake Ranomafana is complex, costly, and time consuming. In this case, modelling can be of big help. Indeed, a model is a simple representation of a complex phenomenon. It is an abstraction, and therefore does not contain all the features of the real system. However, a model does comprise all characteristic ones, those essential to the problem to be solved or described (Soetaert, Herman, 2001).

In the present study a models has been developed for several purposes. Most important of these are using the model as research tools, which may help understand the lake eutrophication problems, such as a better understanding of the complex interactions between physical, chemical, and biological processes going on within the lake (water column, water column-sediment). But models have been also developed in view of managing the system by providing the necessary background information for selecting the appropriate approach to remediating the lake. More important is the use of models as predictive tool for whatever approach of management to be evaluated with respect to capacity to reach target.

2.3.1. General considerations

According to Jørgensen (1999) ecological modelling originates from Lotka-Volterra and Streeter-Phelps in the 1020s, while the comprehensive use of models in environmental management started in the beginning of the 1970s. Lakes modelling have been used since few decades ago, particularly related to eutrophication issues. Initially the works on lake models have been concentrated on two main types of model. The first one is the Vollenweider-type model, which consists of developing model based on input-output, that is, the model is based on measurements of loadings of a lake with phosphorus and nitrogen. By using some lake parameters (e.g. retention coefficient) obtained from statistical/empirical basis, the values of these parameters are then used for calculating

consequences of changes loadings on concentration of the substances in view (Simonsen and Dahl-Madsen, 1978).

While the simplicity seems to be its principal advantage, the main limitations of this first model are the incapacity to taking into consideration yearly variations of loadings and parameter value, being a stationary model (Simonsen and Dahl-Madsen, 1978). Also, generally this type of model does not describe the biological variables which are of main interest, in addition to the influence of biological processes on the model parameters not being taken into account. Later, this relatively first generation of lake models was extended by Dillon and Rigle (Simonsen and Dahl-Madsen (1978) citing Dillon and Rigler, 1974)

High performance and dynamic eutrophication models have been more and more widely used internationally, with time dependent variations and important biological/chemical processes being taken into consideration. These latter models have been much more used for management context.

Lately models were not limited only on lakes system but were used beyond lakes management issues. In this way, models were developed for wastewater treatment, for marine environment, rivers, ecotoxicology, and so one. The basic principles of using models are relatively similar and followed the same steps or tasks. According to Wentzel and Ekama (undated) the following tasks need to be completed when models are being developed: - Identify objectives for the model: it consists of identifying the final use for the model to be developed (e,g. Lakes management). Defining objectives also imply setting up limit in time and space; - Describe the conditions within which the model is to operate (e.g. for stratified or shallow lakes); - Identify the essential compounds utilized and formed: from lake point of view that amounts to saying that components we are interested in must be define as state variables, while external variables (forcing functions) are important factors that drive or regulate the system having generally their values imposed as data series; - Identify the processes acting on these compounds: by observing changes in the compounds under a variety of conditions, or by applying mass balance. - Conceptualize a mechanistic model that qualitatively describes the kinetic and stoichiometric behaviours of the processes and compounds; - Mathematical formulation: it consists of formulating mathematically the process rates and their stoichiometric interactions with the compounds; and - Calibrate the model and test its response against that observed experimentally.

So, as far as Lake Ranomafana is concerned, the main goal for developing model is firstly, as previously mentioned, for having good insight of ongoing physical, chemical, and biological

processes in the lake related to the dynamic of its watershed. Secondly, for determining site specific management scenarios that might fit to socio-economical conditions, required technical performance, easy to handle techniques, and realistic cost. In this way, the model should be capable of predicting the lake’s behaviour when simulating different restoration scenarios, either external of or in-lake, that is, what effect of different management options for restoration of degraded system. So, model for lake management will be developed for resolving visible eutrophication the lake is subjected to, with a view to having answer to question as whether the current conditions would be reversible after undertaking restoration options.

The model will be operating in a very shallow tropical lake that is being considered as a completely mixed batch reactor of 56 300 m 3 a steady state. According to James (1994) lakes with areas up to 100 km 2 are often well mixed.

Regarding the eutrophication of lakes Jørgensen (1980) said that most attention must be paid to algae growth and nutrient cycles as a basis for the prediction of the effect of nutrients on the eutrophication processes. The same main issues are confirmed by James (1984), who stated that the majority of models of lakes and reservoirs are concerned with algal growth and inorganic nutrients. So, as concerned Lake Ranomafana being affected by pollutants loading (organic matter, solids, and nutrients), algal growth and related main biological processes, such as respiration and photosynthesis, will be subject to simulation by using model. As nutrients and organic matter are being involved in ongoing chemical and biological processes in the lake decay, aerobic mineralisation, and anaerobic mineralisation also will be assessed. In order to run the model a simulation platform is needed, so, in the present case AQUASIM will be used as a simulation platform.

2.3.2. Overview of the modelling platform AQUASIM

AQUASIM is software in a form of program designed for the identification and simulation of aquatic systems in the laboratory, in technical, and in nature (Reichert, 1998). The concepts and design of the program AQUASIM was realised by an interdisciplinary scientific team from the Swiss Federal Institute for Environmental Science and Technology (EAWAG). Comparison of measurement with model calculation is the most important method of testing theories in the natural science. According to the author the user manual there are three categories of simulation software: universal simulation software, environmental simulation programs, and system identification programs. The intention behind the design of the program AQUASIM was to provide a more universal identification and simulation tool for a class of aquatic systems important in the environmental science.

The main characteristics of AQUASIM are user-friendliness through the use of a graphical user interface, but also of a communication “language” familiar to environmental scientists. In addition, the software is extremely flexible in allowing the user to specify transformation

processes. AQUASIM as a program for the identification and simulation of aquatic system can perform the following task: simulation, identifiability analysis, parameter estimation, and uncertainty analysis (Reichert, 1998).

The old version AQUASIM 1.0 created in 1994 was updated and completed by the second version AQUAISIM 2.0 in 1998. On the other hand, Reichert (1998) reported that three versions of the program AQUASIM with different user interfaces are provided: the window interface version (aquasimw), the character interface version (aquasimc), and the batch version (aquasimb). The window version as shown in Figure 20 has been used for the present project. As displayed in Figure 20 AQUASIM consists of four subsystems. The first subsystem is for defining variables, the second for defining the compartment(s), the third for defining the process, and the fourth for defining any link in case of more than one compartment.

Figure 20: The modelling program "AQUASIM 2.0"

2.3.3. Conception of the system

Model formulation is the step where our knowledge of a natural system is translated in mathematical form. It involves two steps: the construction of a conceptual model and the formulation of this conceptual model into mathematical equations (Soetaert and Herman, 2009). The conceptual model is actually a kind of figure as diagram showing the interactions amongst different components of the system.

Being considered as a mixed batch reactor the conceptual view of the lake is shown in Figure 21.

Figure 21: Conceptual view of Lake Ranomafana

A simplified conceptual diagram of the lake as it is assumed to be for the purposes of the previously mentioned model is presented in Figure 22. The model shows the different interaction between organisms in the lake, such as phytoplankton, zooplankton, fish, heterotrophic and autotrophic bacteria, and components they need as substrate for growth in addition to detritus the product of their decomposition after death. The interaction between water and sediments also is displayed with the addition of organic transformation at the level of deeper sediment. In the model there are forcing functions or external variables, which are functions or variables of an external nature that influence the state of the ecosystem (UNEP-Pamolare, 2002) such as solar radiation, but they won’t be considered in the modelling for lacking of data. It is noteworthy that only relevant components for the purposes of the project are being presented in the conceptual diagram so as to meet the purpose of the modelling project. In this way, component as fish was showed in the diagram but not taken into consideration for lack of data. Furthermore, the processes the components are subjected to, such as ammonification, nitrification or denitrification, or hydrolosis for organic phosphorus, won’t be taken into detail consideration.

Figure 22: Conceptual diagram of Lake Ranomafana ( modified from Sagehashi and Sakoda et al, 2001 )

2.3.4. Main state variables

As a live system different compounds in Lake Ranomafana undergo chemical and biological processes leading to its current trophic status. Naturally occurring in lakes, certain process is definitely exacerbated by pollutants loading entering into the lake through effluents and urban storm and runoff. Some of these processes are suspected to generate unbalance in related compounds natural cycle in the lake and likely to cause its quality degradation. These compounds, such as oxygen, phosphorus, nitrogen, and organic compounds as chemical oxygen demand (COD), and live organisms mediating these processes (phytoplankton as chlorophyll a, heterotrophic and autotrophic bacteria) will constitute state variables of the models, that is, the components the fate of which within the lake is of big interest for the clarification of eutrophication problem in addition to management purposes. They are in bold character in the conceptual diagram.

Lake Ranomafana is an open system receiving and exchanging matters with surrounding watershed, but also with the atmosphere. The lake flushes out certain components through its outlet. So, in order to get an idea about how the lake is functioning and to try find out any causal and effect relationship, mass balance will be used for relevant compounds. In this way the general mass balance for any compound is as follow:

(Equation 2.13)

2.3.4.1. Oxygen

According to the conceptual diagram oxygen in the lake water mostly come from photosynthesis performed by phytoplankton in addition to other sources, while used during certain processes as follow: - Input through inflowing water; - Input through atmosphere (absorption); - Production in photosynthesis by algae; - Loss through outflowing water; - Consumption in respiration by bacteria, fish, algae, and zooplankton at night; - Loss through atmosphere (desorption), particularly during over-saturation.

Taking into consideration the different processes in which oxygen is being involved will provide information about the oxygen status in the lake. Table 8 summarizes the above processes. Table 8: Oxygen process kinetics Component Oxygen (O ) Rate equation Process 2

Photosynthesis 1 µmAlg *(SPO4 /KPO4 + SPO4 )*(SNH4 /KN + SNH4 )*X Alg

Adsorption 1 Kads *(C lake – Csat )

Respiration bacteria -1 µmA *(S NH4 /K NA + S NH4 )*(S O2 /K OA + S O2 )*X BA

Endogenous respiration -1 KdH *X Alg *(SO2 /KOH + SO2)

Desorption -1 Kads *(C lake - Csat )

Respiration zooplankton -1 µmZoo *(X Alg /K groAlg + X Alg )*(S O2 /K RespZoo + S O2 )*X Zoo

Respiration fish -1 µmFish *(X zoo /K groZoo + X zoo )*(S O2 /K RespFish + S O2 )*X Fish

Adsorption and desorption of oxygen from atmosphere to water and from water to atmosphere are assumed to be small in the oxygen mass balance. However, since the lake is most of the time supersaturated in oxygen, then likely desorption would prevail.

The mass balance for oxygen may be described by the following differential equation:

⁄

2.3.4.2. Nitrogen

In whatever aquatic environment, obtaining accurate N mass balance is very difficult since all related transformation processes are relatively complex. Nitrogen not only exists in different media, such algae, sediment and suspended organic particles, but also presents in various N

forms, such as NH 3-N, NO 2-N, NO 3-N, N org (nitrogen organic) (Peng and Wang, et al. (2007) citing Ferrara and Avci, 1982; Pano and Middlebrooks, 1982). The same authors reports that some parameters, such as dissolved oxygen, water temperature, pH, and light intensity, also affect these transformations.

According to the conceptual diagram in Figure 22 nitrogen as ammonium is subjected to different uptake for growth. However, nitrogen is actually produced and consumed as follow: - Input of inorganic nitrogen (ammoniacal, oxidized) from inlets; - Production of inorganic nitrogen from dead algae and bacteria (autotrophe and heterotrophe) as detritus; - Loss of inorganic nitrogen (ammoniacal, oxididized) through outflowing water; - Loss of nitrogen (ammoniacal, oxidized) by algae uptake; - Loss of inorganic nitrogen by bacteria uptake for growth; - Loss trough algae and bacteria decay.

It is worthwhile noting that ammoniacal nitrogen and nitrate nitrogen may be subjects to volatilization and denitrification, respectively, with the latter leading to volatilisation in a gas form (N 2) (Peng and Wang, et al , 2007), but these processes are being assumed negligible in the modelling.

Table 9 summarize the considered processes leading to nitrogen production and consumption with their rate equations. Table 9: Ammoniacal nitrogen processes kinetics Component Nitrogen (N) Rate equation Process

Uptake by algae -1 µmAlg *(SPO4 /KPO4 + SPO4 )*(SNH4 /KN + SNH4 )*X Alg Uptake by Autotrophic -1 µ *(S /K + S )*(S /K + S )*X bacteria mA NH4 NA NH4 O2 OA O2 BA Uptake by heterotrophic -1 µ *(COD/K + COD)*(S /K + S )*X bacteria mH COD O2 OH O2 BH

Remineralisation from sediment and nitrification of ammoniacal nitrogen are not considered in the model, although these processes likely occur in the lake.

The mass balance for ammoniacal nitrogen may be described by the following differential equation:

⁄

2.3.4.3. Phosphorus

As far as ecological modelling is concerned phosphorus has been and has continued to be the most studied component of aquatic environment owing to the fact that most eutrophication problem is mostly related to discharge of phosphorus. This latter, likewise nitrogen, may enter the aquatic system trough different external sources (untreated wastewater, urban runoff) and through internal mechanism at sediment level. Excessive loading of nutrients in addition to adequate temperature and light becomes efficient condition to biomass growth leading to imbalance of the system (Ruley and Rusch, 2004). In Lake Ranomafana case domestic wastewater and internal supply from sediment seem to be the main sources of phosphorus. It is worthwhile noting that, in opposite to nitrogen, phosphorus does not have a gas phase, but tend to accumulate in sediment. This is why most management approach to resolving eutrophication problem tends to focus on removal of phosphorus as more easy to control than nitrogen.

So, according to the conceptual diagram in Figure 22 phosphorus as phosphate are subjected to uptake by phytoplankton, autotrophic and heterotrophic bacteria. In contrast, phosphorus may be supplied by detritus after decay and decomposition of dead phytoplankton and organisms. In the lake phosphate is likely to be produced and consumed by the following processes:

- Input from influents entering the lake, especially from Northeast where lots of poor dwellers are practicing hand washing every day; - Internal loading from sediment (detritus) release at anoxic condition in which the element to which phosphate is usually bound with (Fe 3+ ) is being reduced to Fe 2+ , readily to release phosphate; - Loss of phosphorus from outflowing water; - Likely loss of phosphorus through precipitation with carbonate of calcium; - Loss of phosphorus to sediment.

Table 10 presents the kinetic expressions or rate equations for considered processes in the conceptual diagram. Table 10: Phosphorus processes kinetics Component Phosphorus (P) Rate equation Process

Uptake by algae -1 µmAlg *(SPO4 /KPO4 + SPO4 )*(SNH4 /KN + SNH4 )*X Alg Uptake by Autotrophic -1 µ *(S /K + S )*(S /K + S )*X bacteria mA PO4 PO4 PO4 O2 OA O2 BA Uptake by heterotrophic -1 µ *(S /K + S )*(S /K + S )*X bacteria mH PO4 PO4 PO4 O2 OH O2 BH

P release from detritus 1 K’ D*X D

One assumes that degradation of detritus and release of nutrients back to column water are being performed by related bacteria through hydrolysis process, that is, one assumes that the process is assimilated to a surface reaction type rate described by the following formula:

⁄ (Equation 2.14) ⁄

In order to simplify the above complex rate equation of surface reaction one assumes that the amount of detritus is very low compared to the biomass in detritus, therefore (X D/X H) becomes very small and assumed to be negligible. So, equation (xxx) above can be written as follow:

⁄ ⁄ ⁄ (Equation 2.15) /

’ So, equation (xxx) becomes (– K D*X D), where K’ D is the rate constant from the ratio of

(K D/K D).

The mass balance for phosphorus as phosphate may be depicted by the following differential equation:

⁄

2.3.4.4. Dissolved organic matter as COD

The organic matter in a wastewater may be subdivided into a number of categories (IAWPRC (undated) citing McKinney and Ooten, 1969; Dold et al ., 1980). The most important subdivision is based on biodegradability which categorizes organic matter in non- biodegradable and biodegradable. According to the conceptual diagram dissolved organic matter is produced by detritus hydrolysis, while consumed for heterophic bacteria growth. Actually the following process will produce and consume organic matter as COD:

- Input from effluents; - Release from the hydrolysis of detritus; - Uptake by heterotrophic bacteria for growth; - Loss from outflowing water.

Table 11 shows the kinetic expression of the considered process affecting organic matter as COD.

Table 11: Organic matter (COD) from detritus process kinetic Component Dissolved Process organic matter Rate equation (COD)

Release from detritus 1 K’ D*X D Uptake for heterotrophic -1 µ *(S /K + S )*(S /K + S )*X bacteria growth mH COD COD COD O2 OH O2 BH

The mass balance for dissolved organic (COD) nitrogen may be expressed by the following differential equation:

⁄

2.3.4.5. Phytoplankton

The algae of the open water of lakes and large streams, the phytoplankton, consist of a diverse assemblage of nearly all major taxonomic groups. Many of these forms have different physiological requirements and vary in response to physical and chemical parameters such as light, temperature, and nutrient regimen (Wetzel, 2001). According to the abiotic conditions (pH, light, temperature, and nutrients) the structure and composition of phytoplankton communities are dynamic and constantly changing. With respect to Lake ranomafana conceptual diagram phytoplankton is mostly affected by the following biological processes:

- Growth through photosynthesis; - Decay through mortality; - Predation by zooplankton trough food web chain:

Table 12 presents the kinetic expression of the above processes affecting phytoplankton. Only growth will be considered in the lake modelling. Table 12: Algae biologic processes kinetic rate Component Phytoplankton Rate equation Process

Growth of algae 1 µmAlg *(SPO4 /KPO4 + SPO4 )*(SNH4 /KN + SNH4 )*X Alg

Decay of algae -1 KdH *X alg *(S O2 /(K OH + S O2 )

Predation of zooplankton -1 µZoo *(X Alg /Kgraz + X Alg )*X Zoo (Jørgensen, 1980)

The mass balance for algae may be described by the following differential equation:

⁄

2.3.4.6. Heterotrophic bacteria

Organisms that use organic carbon for the formation of new biomass are called heterotrophs (Tchobanoglous, Burton et al, 2003). According to the conceptual diagram heterotrophic bacteria is subject to growth through oxidation of biodegradable organic matter under either aerobic or anoxic conditions (assumed to stop under anaerobic conditions) in order to generate biomass.

Table 13 shows the kinetic expression of the considered processes affecting heterotrophic bacteria. Table 13: Heterotrophic bacteria processes kinetic rate Component Heterotrophic Rate equation Process bacteria Aerobic growth of 1 µ *(COD/K + COD)*(S /K + S )*X heterotrophic bacteria mH COD O2 OH O2 BH Decay of heterotrophic -1 K *X *(S /(K + S ) bacteria dH BH O2 OH O2

The mass balance for heterotrophic bacteria may be expressed by the following differential equation:

⁄

2.3.4.7. Autotrophic bacteria

Autotrophic bacteria are those organisms that derive cell carbon from carbon dioxide (Tchobanoglous, Burton et al, 2003). Likewise heterotrophic bacteria they are subject to two main processes that the project is interested on: growth and decay.

Table 14 presents the kinetic expression of the considered processes autotrophic bacteria are subject to. Table 14: Autotrophic bacteria processes kinetic rate Component Autotrophic Rate equation Process bacteria Aerobic growth of 1 µ *(S /K + S )*(S /K + S )*X autotrophic bacteria mA NH4 NA NH4 O2 OH O2 BA Decay of autotrophic -1 K *X *(S /(K + S ) bacteria dA BA O2 OH O2

The mass balance for autotrophic bacteria may be depicted by the following differential equation:

⁄

Symbols used in the different matrix tables are in conformity with those used by the International Association on Water Pollution Research and Control (IAWPRC). According to IAWPRC nomenclature insoluble constituents are given the symbol X and the soluble components S. Subscripts are used to specify individual component. Table 15 explains what each symbols used in the different matrix tables stand for. Table 15: Symbols used in kinetics rate Components Nomenclature of components used Units symbol -1 Clake Concentration of oxygen in the lake water mgO 2 L -1 Csat Concentration of oxygen at saturation mgO 2 L

Kads Coefficient of air adsorption -1 KdH Decay coefficient for heterotrophic bacteria d -1 KdA Decay coefficient for autotrophic bacteria d -3 Kgraz Half saturation constant for grazing g m -1 KgroAlg Growth coefficient for algae d -1 KgroZoo Growth coefficient for zooplankton d

K’ D Rate constant from detritus degradation coefficient ratio

KNA Half saturation for ammonia for autotrophic bacteria

KN Half saturation for ammonia

KOA Half saturation for oxygen for autotrophic bacteria

KOH Half saturation for oxygen for heterotrophic bacteria

KPO4 Half saturation for phosphate -1 KRespFish Respiration coefficient for fish d -1 KRespZoo Respiration coefficient for zooplankton d -1 SNH4 Concentration of ammonia nitrogen mg L -1 SO2 Concentration of oxygen mg L

SPO4 Concentration of phosphate mg L -1 µmA Maximum growth rate for autotrophic bacteria d -1 µmAlg Maximum growth rate for algae d -1 µmFish Maximum growth rate for fish d -1 µmH Maximum growth rate for heterotrophic bacteria d -1 µmZoo Maximum growth rate for zooplankton d -3 XAlg Concentration of algae gDW m -1 XBA Concentration autotrophic bacteria mg L -1 XBH Concentration heterotrophic bacteria mg L -1 XFish Concentration of fish mg L -3 Xzoo Concentration of zooplankton g m

CHAPTER 3 Results and Discussion

The first step towards resolving the water quality issues, now affecting Lake Ranomafana, is based on a better knowledge of the situation of the lake from point of view physical, biological and, chemical. None remediation techniques would be successful without any knowledge of the lake’s characteristics and a better understanding of how it functions within the evolving and dynamic context of its watershed (demography, sanitation, water supply, sewerage system conditions, etc) to which its status is closely related to. This step within the present study is necessary for the understanding of the current problems affecting Lake Ranomafana status, which is being visually qualified as eutrophication, but also for the determination of further site specific actions towards the lake management, especially its remediation.

The purposes of presenting the different results of field tests and laboratory analyses in the following sections are to understand the dynamics patterns of physical, chemical and, biological processes going on in the lake and their relationships to its current status. On the other hand, the final goal is to facilitate the determination of the suitable alternatives of management.

In the first instance, all field tests results carried out from different surveys in 2005, 2008, and 2009 are presented in order to characterize the external loadings to Lake Ranomafana from the two main tributaries (northwester and north eastern part of the lake) (see Figure 16) and to determine any change or variation from the major parameters and their causes. Secondly, the water analysis results from the 5 selected sampling points (see Figure 16) are being introduced and evaluated according to the different biological and chemical parameters tested on the water samples collected during the monitoring campaign of 2009 so as to permit the characterization of the lake trophic status. The relationships between these parameters are also being considered and hopefully will provide the explication of the current status of the Lake Ranomafana. The last but not least is the results of sediments analyses, which give us further explanation about the current lake status and the role the sediments are playing on internal nutrients supply.

3.1. External loadings to the lake

After the meeting of combined delegation from Norway (Pr Torleiv Bilstad and two representatives from IVAR), and from two Malagasy research institutions (IHSM and CNRE) with the mayor of the municipality of Antsirabe, Ramalason Olga, during which the case of Lake Ranomafana was discussed among others issues, a preliminary survey regarding lake’s water quality and its influent loadings commenced in October and November 2005. As the season was then rainy so it was an opportunity to have some measurements from the small non permanent inlets localized north, east, south and, west.

3.1.1. Preliminary Survey of external loadings in October and November 2005

All measurements carried out during the first survey of the lake were performed on portable meters and a portable Wagtech direct-reading photometer 7000Se (Palintest). Water flows from inlets were measured on a portable spot velocity meter, Detec 3013. The instrument measures velocity by means of the ultrasonic Doppler principle. It provides automatic calculation of the average of velocity readings. Figure 20 shows the inlets location where the flow measurements have been carried out.

Figure 23: Location of inlets to the lake

3.1.1.1. Influents discharge

Knowledge of the hydrological regime of a water body is essential, even sometimes incomplete, when discussing water quality analyses. Influents discharge measurements are necessary for mass flow or hydrological balance estimation and as inputs for water quality models. According to the data measured in October 2005 the influents mass balance may be written down as follow:

- From the eastern part of the lake,

(Equation 3.1) 410

Where:

3 - QEast : total flow of influents from the eastern part of the lake (m /h) 3/ - En: inlet components flow from the eastern part of the lake watershed (m h) - From the western part of the lake,

(Equation 3.2) 3

Where:

3 - QWest : total flow of influents from the western part of the lake (m /h) 3 - Wn: inlet components flow from the western part of the lake watershed (m /h) - From the northern part of the lake,

(Equation 3.3) 94

Where:

3 - QNorth : total flow of influents from the northern part of the lake (m /h)

- Nn: inlet components flow of influents discharged from the northern part of the lake

The sum of the influents from eastern, western and, northern parts of the lake represents the total influent discharged to the lake even if most of them did not have any measured flow available.

(Equation 3.4) 507

Where:

3 - QLake : total of the influents flow going to the lake (m /h)

Consequently, the lake water mass balance is simply the difference the influents entering the lake and the portion of water leaving the lake from the outlet as follow:

(Equation 3.5)

Where

- Precipitation is about 1330 mm y -1 3 -1 - S1: Flow of the outlet, visually low (m h ) - Evaporation is about 789 mm y -1

The data from field measurements shown in Table 16 below indicate that Qlake decreased from 507 m3 h-1 to 85 m 3 h-1 over October and November, and most of the inlets either from eastern or western parts of the lake did not have visually any flow at all. Only and permanently the influents from eastern and northern parts of the lake contributed to filling up the water in the lake along the year, but also to discharging pollutants. This feature is still valid up to now.

Table 16: Summary of filed measurement performed in October and November 2005 East side (E1 – E5) North (west) (N1 – N4) Measured parameters October November October November Q (m 3 h-1) 410 30 97 55 Temperature (°C) 20.3 – 33.4 18.0 – 35.3 24.8 – 37.1 21.2 – 28.4 pH 6.68 – 7.60 6.95 – 8.92 7.02 – 7.68 7.01 – 8.08 Conductivity (mS cm -1) Nd 0.35 – 6 Nd 0.48 – 3.5 Turbidity (FTU) Nd 10.8 – 134.8 Nd 10.9 – 71.8 *SS (1.5*FTU)(mg l-1) Nd 16.2 – 202.2 Nd 16.4 – 107.7 -1 COD (mg O2 l ) 14 – 56 20 – 125 36 – 140 22 – 86 -1 BOD (mg O2 l ) 1 – 6 Nd 1 – 4 Nd -1 NO 3-N (mg N l ) Nd 0.4 – 0.8 Nd 0.4 – 0.6 -1 NH 4-N (mg N l ) 0.02 – 1.75 Nd 0.12 – 0.48 * Nd TP (mg P l-1) Nd 0.97 – 3.9 Nd 2.34 – 2.97 -1 PO 4-P (mg P l ) 0.15 – 0.31 0.2 – 1.3 0.9 – 2.2 0.09 – 2.62 Fe (mg l-1) 0.6 0.9 – 3.3 0.6 0.6 – 2.6 Ca (mg l-1) 5.21 – 23.20 Nd 6.02 – 25.62 Nd *regression of wastewater analyses at UiS laboratory; Nd: Not determined

3.1.1.2. General variables

The analyses also highlight few main characteristics of the influents going to the lake. So from temperature point of view the measurements show certain influents from eastern part reaching the lake almost at temperature ambient of the period of the year, i.e. around 20°C,

while the influents discharged from few inlets, mainly those coming from the spa, were warmer (around 35°C). On the other hand their pH ranges from neutral to relatively basic for some influents from the eastern part of the lake.

All measurements carried out for conductivity test indicate highly mineralised influents both from eastern and northern parts of the lake that topped 5000 µS/cm, especially those influents from the spa. The turbidity values once only measured in November are higher for few inlets from eastern part ranging from 10.8 to 134.8 FTU. These values are related accordingly to relatively higher concentration in suspended solids (SS) for certain influents from the same side, with maximum value of 202.2 mg l-1.

3.1.1.3. Organic matter

With regard to the organic loading the ranges of values measured from the influents, irrespective or their origins, in October and November do not show any significant change. For instance the minimum values for chemical oxygen demand (COD) were 14 (east) and 36 -1 -1 mg O2 l (northwest) in October, while they were respectively 20 and 22 mg O2 l in November. The same pattern seemed to be observed regarding the maximum values as 56 -1 (east) and 140 mg O2 l (northwest) in October compared to respectively 86 and 125 mg O2 l-1 in November. The biodegradable part of the organic loadings measured in October and expressed as biological oxygen demand (BOD) was very low with a maximum value of 6 mg/l.

3.1.1.4. Nutrients

+ Appreciable values of nutrients expressed as nitrate (NO 3), ammonium (NH 4 ), reactive phosphorus or soluble orthophosphate (PO 4), and total phosphorus (TP), are noted in the influents entering both sides of the lake, particularly for NO 3 with a maximum value of 0.8 mg N l-1. On the other hand, TP measured values in November range between 0.97 to 3.9 mg P l-1 from eastern side influents, while relatively higher range is observed from north western side, with 2.34 to 2.97 mg P l-1. Orthophosphate was tested both in October and November, but no significant variation of concentration is noted from influents coming to lake. The maximum values are around 2.2 mg P l-1 either in October or November.

3.1.2. Preliminary assessment of external loadings in June 2008

The survey performed in June 2008, with the help of an environmental chemistry student from the University of Antananarivo preparing the equivalent of Master of Science thesis, had among other objectives the remediation of Lake Ranomafana. Table 17 presents different characteristics of the influents going to the lake at that time.

Table 17: Summary of measurement carried out in June 2008 East side (E1 – E5) North (west) (N1 – N4) Measured parameters June June Colour (Pt/Co) 15 – 105 90 -135 Temperature (°C) 15.4 – 19 19 – 19.7 pH 7.85 – 8.41 7.65 – 8.14 Conductivity (mS cm -1) 0.18 – 4.97 1.91 – 2.70 Turbidity (FTU) 8 – 39 22 -35.6 TSS (mg l-1) 3 – 70 225 – 253 -1 Dissolved O 2 (mg l ) 5.3 – 8.1 1.85 - 8.06 -1 COD (mg O2 l ) 8 – 27.7 61.7 - 96.85 -1 BOD (mg O2 l ) 5.3 – 15.6 38.6 – 49.2 -1 NO 3-N (mg N l ) 0.22 – 1.14 0.32 - 0.61 -1 NO2-N (mg N l ) 0 – 0.01 0.02 - 0.06 TKN (mg N l-1) 0.96 – 3.6 2.88 – 3.40 TP (mg P l-1) 0.18 – 1.71 1.85 – 2.66 -1 PO 4-P (mg P l ) 0.03 – 0.13 0.03 – 0.07

3.1.2.1. General variables

The tests of colour conducted on influents discharged to the lake just confirm what has been visually seen regarding the aspect of these influents. Indeed, influents from north western side are relatively turbid (22-35.6 FTU) and accordingly more coloured (90-135 Pt/Co) compared to those coming from eastern side, with a range of colour values between 15 to 105 FTU. However, certain influents from eastern side also show similar values of turbidity, with maximum 39 FTU, as influents from north western side.

+ Except ammonium (NH 4 ) and mineral components (iron (Fe) and calcium (Ca)) practically the same parameters were measured and tested in June 2008 in order to further characterize the external loading to Lake Ranomafana. In this way, pH values measured from both side of the lake do not differ too much of those of 2005, with minimum values of 7.85 (east) and 7.65 (northwest). Maximum values also are in the same range, with respectively 8.41 and 8.14. Maximum conductivity values from both sides are relatively lower (4.97 mS cm -1 from east and 2.70 mS cm -1 from north) than those of November 2005 (6 and 3.5 mS cm -1).

As concern total suspended solids (TSS) influents from eastern side show maximum value of about three magnitude less than November 2005, with 70 mg l -1, whereas maximum value (253 mg l -1) from north western side are about two and half times more than November 2005. In addition, dissolved oxygen (DO) was also that time measured from both side

influents. So, eastern side exhibits higher range of value (5.3-8.1 mg l -1) compared to north western side (1.85-8.06 mg l -1).

3.1.2.2. Nutrients

Different compounds of nitrogen have been tested as in 2005 for a better knowledge of nutrients supply from these influents. So, for NO 3 both sides discharge comparable amounts of nitrogen, with maximum values of 1.14 mg N l -1 from east and 0.61 mg N l -1 from northwest. Nitrite ranges of values are quite low, particularly from eastern side (0-0.01 mg N l-1) compared to north western side (0.02-0.06 mg N l -1). However, the sum of organic and ammonia nitrogen, as total Kjeldahl nitrogen (TKN), shows higher ranges of values from both sides of the lake, with a maximum value of 3.6 mg N l -1 from eastern side and 3.40 mg N l -1 for north western side.

Phosphorus compounds have also been tested in order to have a complete view of external supply of nutrients to the lake. Soluble PO 4 shows very low ranges of values from both side of the lake, with maximum values of 0.13 mg P l -1 (east) and 0.07 mg P l -1 (northwest). In terms of total phosphorus north western side seems to supply more phosphorus compounds than eastern side, confirming then obtained data from 2005. Maximum values from eastern and north western sides are respectively of 1.71 mg P l -1 and 2.66 mg P l -1.

3.1.2.3. Organic matter

In terms of organic loading, herein reported as COD and BOD, COD range of values (8-27.7 -1 mg l O2) from eastern side is lower than that of 2005. Although not similar COD range of values from north western side is comparable to that of 2005 even if certain values from this -1 latter are well above values maximum value measured in 2008 (96.85 mg l O2). On the other hand, BOD charge from both sides shows a bit higher values reaching maximum values -1 -1 of respectively 15.6 mg l O2 (east) and 49.2 mg l O2 (northwest).

3.1.3. Characterization of external loadings through monitoring in 2009

Although carried out at sporadic period of time, the preliminary surveys conducted in 2005 and 2008 provided clarifications concerning the external loading going to the lake, particularly the nature and a rough idea of the volume, however still incomplete and very limited in time. This was the reason why to carry out a bit longer evaluation of these external loading in a form of designed monitoring. These preliminary surveys being realised during rainy (2005) and cold and dry season (2008) also had permitted to note that only two main inlets are discharging influents permanently into the lake. These are situated respectively north western (NW) and north eastern (NE) of the spa as shown in Figure 24 below.

Meanwhile, it was clear that due to these external loading, even slightly diluted, no restoration project would be possible without stopping or at least reducing at acceptable

level all kinds of external loading going to the lake prior to any eventual intervention from within the lake. In order to have a good knowledge about the characteristics of loading to be removed through any eventual treatment, it appeared imperative to obtain data from much longer period of time on main compounds. Monitoring on a monthly basis of these compounds has been carried out over period of March to December 2009 (except May, June, and July). Data related to the variation of the main pollutants of concern are expected to help select site specific alternatives with respect to treatment that suits to the loading targeted. Beyond the above expectations a better knowledge about these external loading also is helpful for a better understanding of the lake’s ecological functioning.

Figure 24: Permanent main inlets (northeast and northwest)

As follow up of the preliminary surveys, the monitoring of the influents from both north eastern and north western inlets were much more focused on few chemical parameters of concern capable of characterizing the external loading going to the lake. So, TSS, P-PO 4, TP,

NO 2, NO 3, TKN, TN, COD, and BOD were tested on samples collected from both inlets on monthly basis.

3.1.3.1. General variable

According to Figure 25 presenting the concentrations of TSS tested on influents in March and April 2009, a certain pattern is observed from the diagrams, in spite of the varying concentration of TSS. In this way, north western inlet discharges influent with relatively higher TSS compared to that of north eastern inlet. TSS from north western influent could be about 3 times higher (63 mg l -1 in March 2009) than that of north eastern influent (18 mg l -1 in March 2009).

50 ) -1 40

TSS (mg.L TSS TSS 20

0 NW NE NW NE

March April

Figure 25: Total suspended solids loading from the two main inlets

With respect to the nature of TSS in the influents, Figure 26 shows that TSS from both influents (northwest and northeast) are predominantly composed of organic matter herein expressed as Volatile suspended solids (VSS). While around 55% in March 2009, VSS in influents increases at about 70% in April. Both inlets seem to discharge influents containing significant organic matter. On the other hand, inorganic matter herein expressed as inorganic suspended solids (ISS) is found less than 50% and seems to decrease from March (northwest 46% and northeast 43%) to April (northwest 32%, northeast 29%).

VSS/ISS (Northwestern influent, March VSS/ISS (Northeastern influent, March 2009) 2009)

ISS 43% ISS 46% VSS VSS 57% 54%

VSS/ISS (Northwestern influent, April VSS/ISS (Northeastern influent, April 2009) 2009)

ISS ISS 32% 29%

VSS VSS 68% 71%

Figure 26: Nature of suspended solids discharged in the lake

3.1.3.2. Nutrients

The ranges and mean concentrations of soluble PO 4 and inorganic nitrogen as NO 3 and NO 2 from influents north western and north eastern sides of the lake over 7 months for inorganic nitrogen while only 6 months for phosphorus are presented in Table 18.

Table 18: Range and mean concentrations of soluble phosphate (reactive phosphate) and inorganic nitrogen found in influents discharged into the lake Soluble phosphate Nitrate (NO ) Nitrite (NO ) (PO ) 3 2 Sub-catchment 4 (mg N l -1) (mg N l -1) (mg P l -1) Range Mean Range Mean Range Mean North western 0.15 – 1.28 0.74 0.37 – 9.63 5.28 0.006 – 1.20 0.42 influent (NW) North eastern 0.06 – 1.04 0.36 0.25 – 5.45 1.91 0.005 – 0.20 0.07 influent (NE)

Considerable variability exists between influents discharged from each side of the lake over the period of monitoring. For soluble PO 4 (reactive phosphorus) seasonal variation in the concentration of phosphorus from influents seems obvious. Highest values from both sides

occurred during rainy season (1.28 mg P l -1 from NW and 1.04 mg P l -1 from NE in April), while lower values were found during cold and dry season. Then concentration of reactive phosphorus started to increase from December when rainfall usually commences. The mean concentration of soluble phosphate entering the lake with both north western and north eastern inlets approximated 0.55 mg P l -1.

In general, relatively high concentrations of reactive phosphorus enter the lake from north western inlet ranging from 0.15 to 1.28 mg P l -1 compared to those from north eastern, with a range of values between 0.06 and 1.04 mg P l -1.

For inorganic nitrogen, as NO 3-N, there is a conspicuous drop in concentration during cold and dry season from August to November that may reach the minimum values of 0.37 mg N l-1 (NW) and 0.25 mg N l -1 (NE) respectively, while the maximum values were found in December with respectively 9.63 mg N l -1 (NW) and 5.45 mg N l -1 (NE). As per reactive phosphorus, in general, the inorganic nitrogen concentrations were distinctly higher in influents entering the lake from north western side. The mean concentration of inorganic nitrogen entering the lake with influents was about 3.6 mg N l -1.

The same pattern related to season was being observed for nitrite expressed as NO 2-N. The ranges of concentration are relatively lower compared to those of nitrate, with 0.006 to 1.20 mg N l -1 for north western influents and 0.005 to 0.20 mg N l -1 for north eastern influents.

In terms of TKN, relatively higher concentrations are observed from north western influents, with values ranging from 3.12 to 5.76 mg N l -1 (Table 19), compared to those from north eastern influents having range of values from 1.68 to 6.96 mg N l -1. Higher concentrations occurred mostly during rainy season (December to April). The general tendency for concentrations to fall during cold and dry season also was observed for both sides influents. The mean concentration of nitrogen, representing the sum of organic and ammonia nitrogen, entering the lake from both inlets was about 3.59 mg N l -1. Table 19: Variation of Total Kjeldahl Nitrogen concentration as function of sampling period and season TKN (mg N l -1) Sub-catchment March April Aug Sept Oct Nov Dec Mean North western 4.08 3.84 3.12 3.36 4.56 3.60 5.76 4.05 influent (NW) North eastern 6.96 1.68 1.92 4.32 2.40 2.40 2.16 3.12 influent (NE)

Although the above nutrient compounds are known to be readily available for chemical processes and biological metabolism without further molecules breakdown in water, the remaining compounds of phosphorus and nitrogen cannot be neglected as they would undergo as well either chemical process (hydrolysis) or degradation by microorganism in

suitable environment. So, assessing total phosphorus (TP) and total nitrogen (TN) will provide information about those remaining compounds, such as polyphosphates, organically + bound phosphate, and organic nitrogen and ammonia/ammonium (NH 3/NH 4 ), from discharged influents.

According to Figure 27 and to the above reactive phosphate seasonal variation TP presents the same pattern, i.e. higher concentrations are observed during mostly rainy season (December and April), with the highest values of 2.33 mg P l -1 (NW influents) and of 1.42 mg P l -1 (NE influents) tested in April, while significant drop of concentrations are being found over cold and dry period (August, September, October, and November) for both sides influents. The mean concentrations over the monitoring period are of 0.96 mg P l -1 (NW influents) and of 0.48 mg P l -1 (NE influents), and the mean concentration of TP entering the lake with both sides’ influents approximated 1.44 mg P l -1. It is noteworthy that reactive phosphate seems to be the greatest part of TP representing more than 75% of the concentration, while about 25% only as both polyphosphates and organic phosphate.

Figure 27: Variation of total nitrogen and total phosphorus loading as a function of sampling period

With respect to TN, representing the sum of organic nitrogen, ammonia/ammonium, nitrite, and nitrate, the ranges of values are found between 5.10 to 15.50 mg N l -1 (NW influents) and 2.73 to 8 mg N l -1 (NE influents). Although weak tendency for concentrations to fall with seasonal change is observed, concentrations tested over cold and dry period do rather present slight decrease. Mean values are found about 9.09 mg N l -1 from NW influents, while a bit low of 5.75 mg N l -1 from NE influents. Inorganic nitrogen represents more than half part of the TN in these influents.

3.1.3.3. Organic compounds

Wastewater normally contains thousands of different organics (Henze, Harremoës et al , 2002) making it impossible to assess and measure each individual organic compound. That is why collective analyses, such as COD and BOD, are being used in order to have an approximate of organic compound in influent samples. Indeed, the BOD test carried out during 5 days, according to the method adopted, does not reveal the amount of degradable organic matter and ammonium oxidized but rather gives an approximate estimate of the weight of oxidized organic matter and indirectly the pollution extent. On the other hand, the COD analysis gives a fair estimate of the content of organic matter (Henze, Harremoës et al ).

The organic loading herein expressed as COD and BOD, going through both NW and NE inlets to the lake does not really exhibit striking seasonal variation as per above nutrients, however, a slight tendency for lower concentration during cold and dry season (September, October, November) is observed (Figure 25). For COD loading from NW influent higher -1 -1 concentrations are observed in March (81 mg O 2 l ), December (75.40 mg O 2 l ), and April -1 (50.40 mg O 2 l ), while, from NE influent, higher concentrations are found in March (62.10 -1 -1 mg O 2 l ), and in November (82.40 mg O 2 l ) followed by a drastic decrease by a factor of -1 about 4 in December (18.90 mg O 2 l ).

There is no significant predominance of concentration between BOD concentrations from either NW or NE influent. In general, very slight tendency of concentrations to decrease during cold and dry period (August, September, and October) is observed (Figure 28). Means concentration from NW and NE influent are practically similar, with respectively 23.60 mg O 2 -1 -1 l and 21.20 mg O 2 l . Same pattern also is found as concern the ranges of values for NW -1 -1 and NE influents, with 14.80 to 36.60 mg O 2 l (NW) and 8 to 39.20 mg O 2 l (NE).

Figure 28: Variation of organic matter loading as a function of sampling period

3.1.4. Rough estimates of average annual nutrients and organic loads in Lake Ranomafana

For the purpose of making a rough assessment of nutrient (reactive phosphorus (PO 4-P) and nitrate-nitrogen (NO 3-N)) and organic matter (COD) loads, the annual average concentrations of PO 4-P, NO3-N, and COD are assumed to be the mean values of concentrations measured over monitoring period from NW and NE inlets combined. So they -3 -3 -3 are of 0.55 g P m for reactive phosphorus, of 3.6 g N m , and 53.18 g O 2 m respectively. On the other hand, the average annual influent discharge is assumed to be 4354.56 m 3 x 10 3 (based on 2005 survey).

Table 20: Estimated gross annual nutrient and organic loads on Lake Ranomafana Average annual Nutrient load Organic load Nutrient source Influent discharge (m 3 x 10 3) PO 4-P NO 3-N COD (kg.y -1) (kg.y -1) (kg.y -1) NW + NE inlets 4354.56 2395 15676.42 231575.5 Specific surface loading - 24.12 157.87 2332.08 (g.m -2.y -1)

Based on the above hypotheses the estimated gross annual loads of reactive phosphorus and inorganic nitrogen as nitrate-nitrogen amounted to 2395 kg and 15676.42 kg respectively, while the organic matter as COD was of 231575.5 kg (Table 20).

When separately assessed, the estimated gross annual loads of nutrients from NW inlet -1 -1 were relatively less, with notably 601 kg.y of PO 4-P and 4288 kg.y of NO 3-N, owing to the considered inflow of 94 m 3 h-1. In contrast, higher nutrients gross loads were estimated from -1 -1 NE inlet, with respectively 1275.30 kg.y of PO4-P and 6766 kg.y of NO 3-N, because it was assumed that 410 m 3 h-1 flowed into the lake from north eastern part. Likewise nutrients, this pattern prevailed with respect to organic load for NE inlet being the one which mostly discharged organic matter, with estimated loads of 147769.80 kg.y -1 compared to 52952.80 kg.y -1 from NW inlet.

3.1.5. Discussion

When the preliminary survey of Lake Ranomafana was carried out in 2005, nobody from local (Antsirabe municipality) and Norwegian (University of Stavanger and Stavanger municipality) discussed about or proposed to conduct the feasibility study of the lake remediation. So this survey was just about to have some basic knowledge about the lake water quality issue to confirm the visual fact of seeing the water within the lake green, with smell. This physical status of the lake is related, irrespective of its origin, to many factors, both external and internal, that affect or perturb its chemical, biological, and ecological equilibrium. This perturbation, when it is exacerbated by uninterrupted supply of external loads, especially in terms of nutrient inputs, leads to the well known phenomenon called eutrophication.

On the other hand, one should not forget the existence of the national standards about discharged wastewater (Decree N° 2003/464 on 15/04/03 related to Classification of surface waters and Regulation on liquid effluents), to which the preliminary surveys aimed to, as whether the influents going to the lake and the water quality complied with the existing standards. But, first of all one needs to understand the variation of influents discharge going to the lake as loads (nutrient, organic) depends on volume of effluents

3.1.5.1. Variation of the influents discharge

All estimates regarding external loading were based on the influents flow measurements carried out in 2005. The estimated discharge of 507 m 3. d-1 (cf 3.1.1.1.) is well below the estimate obtained (870 m 3.d -1) by using the number of population in the watershed (Table 21) and assuming that a range between 70 – 80% of the consumed water is being generated to domestic wastewater.

Table 21: Watershed dwellers water consumption and estimated domestic wastewater generated Water Generated Waste Neighborhood Nb of Population* Consumption** Water (m 3.d-1) (m 3.d -1) Atsimotsena 8423 212 170 Antsenakely 3572 89 71 Avaratsena 4965 162 130 Mahazoarivo Atsimo 10764 338 216 Mahazoarivo Avaratra 11803 442 283 Total 39527 1243 870

* Data from the municipality ** Data from the JIRAMA

The difference between measured volume and calculated volume by a factor 1.7 may be explained by the following reason:

- Sanitation practices in the urban city of Antsirabe: According to a water and sanitation survey reported by the national water supply company JIRAMA (2004) the majority of households (72%) are using pit latrine with no connexion to any sewerage system, and beyond that, most of the population (81%) does not use water for either flushing faeces or cleaning after defecation. Further, the part of domestic wastewater that should be discharged through sewerage system consists mainly of grey water since 39% of household are dumping their wastewater in the backyard of their dwelling or in a drainage ditch within people’s backyard (Table 22). Only 14% of household are using sewerage system for wastewater discharge. It is worthwhile noting that even those who are using septic tank are not connected to sewerage system but rather to a cesspit containing coral stones, facilitating the infiltration underground. It is culturally proved that in spite clean water is important no attention is paid to wastewater discharge (UNEP-IETC, 1999). - Poor coverage of the sewer system: The urban city of Antsirabe alike most of the big agglomeration in the country has poor coverage of sewer system. The existing

system is combine sewerage for both wastewater from old and public buildings and for storm water runoff. Most of them are clogged for being used for dumping all kind of garbage (plastic bottles, plastic bags, rest of food, wrapping papers).

Due to the above reasons one may conclude that the calculated volume of 870 m3 d-1 is over estimated and probably far from the average volume of effluent discharged in the lake. But on the other hand, the measured volume of 507 m 3 d-1 does not take into consideration the daily variation of effluent discharge according to water usage, and also the variation of flow during rainy season and cold and dry season. But here the idea is just to have a gross appreciation of the effluent discharge.

Table 22: Sanitation practice within municipality of Antsirabe Types of sanitation facilities Percentage of household

Latrines with lost pit (pervious) 72% WC with septic tank (water-flush) 16% Latrines with impervious pit 22% Water use in the restroom Percentage of household

No 81% Yes 6% No answer 13% Wastewater fate Percentage of household

Dumped in people’s own backyard 39% Dumped in a drainage ditch within 34% people’s backyard Dumped on the street 13% Dumped in the drainage system 14%

3.1.5.2. Physical patterns of discharged influents

The different patterns of the influent loads (physical, chemical, and biological), although showing different figures in accordance with their origin (eastern side, western side), did not really show any striking loading changes over the period of 2005 to 2009, which also might indicate no big changes on watershed land use. On the other hand, due to lack of survey about land use in the neighbouring areas no obvious relationships are found which link the export to land use, vegetation cover, soils, or surface geology (White and Downes, 1977). The temperature pattern of the influents was in accordance with their origins, while varied with the ambient temperature of the season of sampling and field measurement. Indeed,

NW influents showed relatively higher temperature compared to NE influents as the formers are a mixture of diluted domestic wastewater with warmer wastewater from the spa, with a temperature around 35 to 37°C when reaching the inlet. It is noteworthy that the spa is using thermal water source, with a temperature of about 36 to 42°C at source (Asimbolarimalala, 2008). NE influents are mainly made of spring water from the eastern watershed of the lake, which is normally cold. Both sides, however, showed not big difference with respect to conductivity. Measured values are characteristic of highly mineralised water with geothermal influence, which is the case of influents entering the lake. Maximum values tested on NE and NW influents reached 6000 and 3500 µS.cm -1 respectively. Réland (1905) reporting the results of water analyses carried out on the thermal sources confirmed the high mineral content of the water, especially in bicarbonate, sulphate, chloride, sodium, potassium, and calcium. Different water samples from bathing houses were collected and analysed by the French pharmacist in Antananarivo at that time, for medical purpose, and he concluded that the thermal water is of type chloro- bicarbonated and recommended the use of water for treatment of rheumatism.

Preliminary surveys in 2005 and 2008 permitted to measure one relatively important parameter, namely pH. When measuring the effect of an effluent discharge, it can be used to help determine the extent of the effluent plume in the water body (Chapman, 1992). In general, the ranges of pH values tested on influents were relatively higher than pH neutral (pH=7). Two aspects might be regarded so as to explain these higher pH values. Firstly, influents from NE are mainly composed of spring water with naturally higher pH. Further, waters from this area neighbouring the spa also is known for having high alkalinity due to the presence of limestone in the area. Limestone is rich in carbonate, so waters flowing through limestone regions generally have high alkalinity and hence gain its good buffering capacity. The intensive hand washing along the channel affects as well the pH towards higher values.

NW influents showed higher pH. This is probably due to the composition that is mostly made of a mixture of wastewater from the spa and the swimming pool with domestic wastewater from northern watershed. According to the waters testing performed by the French pharmacist Réland (1905), thermal waters contain less carbonic acid compared to mineral water, currently known as “Ranovisy “and used for drink. The thermal waters also were reported to contain relatively higher concentration of bicarbonate, which provide good buffer capacity.

The turbidity values measured in November 2005 were relatively higher, with maximum of 135 FTU (NE) and 72 FTU (NW), compared to measured values in June 2008 (maximum NE: 39 FTU, maximum NW: 36 FTU). The formers values were tested during rainy season, indicating relatively important transport of eroded sediment from the watershed and also from the mud bath used for treatment in the spa. Lower turbidity tested in June 2008 is

probably due to the fact that every year in June, during one month, the spa is closed for pipes maintenance and calcareous deposit removal as the thermal water contains high -1 concentration of lime, with water having relatively higher hardness (about 350 mg l CaCO 3). It is worth while noting that about 23000 persons comes every year in the spa for medical treatment (L’Express de Madagascar, 2011).

Influents loads in suspended solids seems to be higher from NW inlet since the wastewater from the spa contains suspended solid from the mud treatment in addition to sediment from northern watershed erosion. The high concentrations of volatile suspended solids in influents, irrespective of their origins, might be explained from the use of sewerage system for dumping domestic garbage. Further, according to Seidl (1997), through the characterization of urban effluents during rainy season he conducted in Paris, the biodegradability of suspended solids in sewer system decreases with the intensity of rain due to the contribution of carbon less degradable from storm water runoff and deposits in sewerage system.

3.1.5.3. Variation of nutrients in influents discharged

During preliminary survey conducted in 2005, presence of nitrogen and phosphorus compounds is remarked in influents entering the lake although incomplete data. The levels of nitrate are as expected for wastewater, while ammonia is lower than expected. Some degradation or conversion of nitrogen may appear upstream the sampling points. The values of orthophosphate and total phosphorus are in accordance with the values of COD and SS, due to dilution.

More complete data confirmed the presence of nitrogen and phosphorus compounds during preliminary survey in 2008 and monitoring campaign in 2009. In spite their natural occurrence in waters, the level of concentrations tested on influents, irrespective of their origin, seems to indicate pollution from domestic wastewater and dumped solid waste, particularly for NW influents. On the other hand, nutrients in NE influents are daily enhanced, particularly with respect to phosphate, by intensive clothes hand washing along the channel. For that matter, phosphorus compounds from either NW or NE influents are mainly soluble reactive phosphate.

According to Chapman (1992), higher concentration of ammonia/ammonium could be an indication of organic pollution such as from domestic sewage, and levels in excess of 5 mg l -1

NO 3-N usually indicate pollution by human or animal waste. In general, influents nutrients loadings to the lake are seasonal, with highest contribution during rainy season and predominantly inorganic nitrogen compounds from NW inlet. This is probably due to the fact that i) a large fraction of the total phosphorus being associated with particles determines phosphorus transport to occur disproportionally during high flows, and that ii) in tropical

watersheds with negligible human disturbance, most of the nitrogen is in the dissolved organic and inorganic fractions (UNEP, 1999).

It is noteworthy that Réland (1905) also reported the presence of saltpetre (NO 3) around the wooden bath tubs used for treatment with thermal waters in the ancient bathing houses. Further, the presence of relative higher concentrations of inorganic nitrogen from stream, the Waipahihi stream in New Zealand, under geothermal influence was also reported by White and Downes (1977). So, nitrate is naturally present in the geothermal waters from the spa in addition to nitrogen and phosphorus compounds from diluted wastewater and disposed of solid waste going into the lake through NW inlet. Interesting to mention lastly the presence of silica in the geothermal waters, this was proved by the different water analysis results performed by Réland (1905).

3.1.5.4. Nature and pattern of organic loads

Few available data from 2005 survey already indicated the presence of diluted domestic wastewater that normally would contain about 500 mg l -1 COD undiluted. The organic content of influents was confirmed in 2008 survey and 2009 monitoring campaign. Although the values of COD and BOD have varied from one survey to another, probably due to the timing of sample collection, the high content in non-biodegradable organics has remained unvarying. The BOD values indicate low biodegradability of the organic compounds. In general, the non biodegradability seems to be relatively higher in NW influents compared to NE influents (Table 23). This might be due to the fact that the influents from NW are composed of diluted wastewater from more urbanized watershed and used water from the spa containing mud, while NE originates from spring water but mostly affected by solid waste dumped in the channel and clothes hand washing. According to Gray (1999) the ratio COD:BOD provides a useful guide to the proportion of organic material present in wastewaters that is biodegradable.

Table 23: Variation of ratios of organic matter in influents as function of season and origin Ratios COD:BOD (2009) March April Aug Sept Oct Nov Dec NW 2.18 2.06 6.6 1.97 Nc 2.6 2.6 influents NE 2.20 1.93 5.9 1.6 Nc 2.1 1.13 influents Nc: not calculated

Influents organic loading to the lake shows seasonal variation, with highest contribution during rainy season, which seems to be normal owing to the high solid and sediment transport during that period.

3.1.5.5. Compliance of influents loads to national existing effluent standard (Decree N°2003/464)

According to the Article 5 of the decree, in order to preserve water resources (objective of quality), effluents must be colourless, odourless, and respect the following quality (Cf Appendix A). With regard to the respect of this standard (Table 24, excerpt from national standard) few points related to the influents entering the lake should be highlighted: - Although not measured but visually appreciated, odour and colour of influents do not comply with the standard as influents are coloured and smell, particularly those from NW side. - Conductivity, temperature, turbidity, and suspended solids in general do not comply with the standard values since they are well above. - While TKN, nitrite, ammonia, and phosphate do comply with the standard values, nitrate are in general well above the standard value, therefore does not comply with. - COD and BOD do in general comply with the standard values and seldom show over values during rainy season. Table 24: Extract from the National Standard for wastewater discharge Parameters Unit Standard Organoleptic and physical factors pH 6.0 – 9.0 Conductivity µS.cm -1 200 Suspended solids mg.l -1 60 Temperature °C 30 Colour Scale Pt/Co 20 Turbidity NTU 25 Chemical factors Ammonia-nitrogen mg.l -1 15.0 Nitrate mg.l -1 20 Nitrite mg.l -1 0.2 Total Kjeldahl nitrogen mg N.l -1 20.0 3- -1 Phosphate as PO 4 mg.l 10.0 Biological factors Chemical oxygen demand mg.l -1 150 Biochemical oxygen demand mg.l -1 50

3.2. Characterisation of Lake Ranomafana current conditions

Among the few existing lake studies in Madagascar there is not one addressing eutrophication as impact of wastewater discharges and the scientific based approach to resolve the problem through lake management. This is why, in the area of lakes

management, very few if not no data are available with respect to such a kind of study as characteristics of eutrophication, role of sediment in eutrophication, eutrophication management and control, and lake restoration...

The presentation of the different monitoring data collected from monthly basis field work and laboratory tests and analyses aim at characterising current conditions (physical, chemical, and biological) of Lake Ranomafana under pressure by discharge of wastewater. Better knowledge of the lake current conditions will help define and understand its current trophic status with an in-depth scientific underpinning. The greater our understanding is, the higher is the probability that we can predict with reasonable accuracy patterns of events within aquatic ecosystems in response to human manipulations and disturbances (Wetzel, 2001).

In the first instance, physical characteristics are defined through field work data. Secondly, chemical characteristics of lake water and sediments, and the kind of relationship between these main components of the lake, are assessed and explained. Third, biological characteristics are presented through primary production data in order to understand the ongoing biological processes that might help comprehend the lake’s ecosystem functioning, while help find the different site specific management alternatives towards the lake restoration. The main objective of this sub chapter is about to characterise the current trophic status of Lake Ranomafana, which is defined lastly.

3.2.1. Characterisation of Lake Ranomafana physical conditions

Lake Ranomafana is a very shallow and relatively small size man-made tropical lake located in a valley within an urban area of the centre of the city of Antsirabe. Originally, the lake was intentionally created to counterbalance the rise of gases (CO 2 and H 2S) from the bottom volcanic layer, which tends to lower the thermal water pressure, but also for aesthetic purposes. Consequently, an artificially closed lake basin, according to water level, was formed. From point of view morphometry the lake is more or less elongated shaped, with its maximum length and its maximum width measuring respectively 505 m and 213 m. The basic parameters of the lake are given in Table 25. Fast growing, invasive and free-floating perennial aquatic plant, as mainly water hyacinth (Eichhornia crassipes ), is growing around the main inlets and sometimes invades entirely the surface of the lake, but regularly removed by the service in charge of sanitation from the municipality.

Table 25: Physical features of Lake Ranomafana Parameters Lake Ranomafana Altitude (m) 1485* Shoreline (m) About 1245* Maximum depth (m) 0.9 Mean depth (m) 0.57

Surface area (hectares = m 2 x 10 4) 9.93 Shoreline development 1.1 Total water volume (m 3) 56 300 Sediment estimate volume (m 3) >300 000 Retention time (days) 4.6 *Estimation by using Google Earth

It is noteworthy that the area and the depth of the lake vary according to the level of water. So, consequently it is a characteristic feature that the morphometry of the lake changes with time, seemingly with season (dry or rainy). Table 26 presents few recorded depth data from the 5 sampling stations in February, March, April, October, November, and December 2009.

Table 26: Variation of depth measured from sampling stations Sampling Depth (m) station February March April October November December 1 0.4 0.4 0.4 0.6 0.4 0.4 2 0.5 0.5 0.5 0.6 0.6 0.6 3 0.3 0.3 0.3 0.6 0.7 0.7 4 0.6 0.6 0.6 0.7 0.7 0.8 5 0.8 0.8 0.8 0.9 0.8 0.9

The bathymetry of a lake basin is determined accurately from a continuous record of the basin contours with an accurate sonar device (depth sounder or fathometer) (Wetzel and Likens, 2000). Lacking such equipment, the lake basin contours survey was carried out in February 2009, during the first campaign of monitoring by using a manual depth meter. No transect was used, but depths were measured along shore line, and from several points within the lake (15 points in total). The bathymetric map of Lake Ranomafana at that period is shown in Figure 29 below. The deepest part of the lake (0.8 to 0.9 m) is approximately nearby the outlet.

Owing to shallow water and wind the lake is seemingly well mixed and presents no apparent stratification at all. Being shallow and small size lake the water circulation pattern seems to be governed by the wind pattern. Lake Ranomafana is exposed to predominantly north and north easterly wind (Cf Figure 15), so the water circulation would probably follow the water surface current. However, the influx of warm water from the spa would also affect the water circulation pattern and thermal structure of the lake as solar energy dissipated as heat would do so (Wetzel and Likens, 2000)

Figure 29: Bathymetric map of Lake Ranomafana (February 2009)

3.2.1.1. Absorption of light and light penetration

Amongst others physical characteristics that have importance to the functioning of aquatic ecosystem are light impinging water as source of energy and the transparency of water or light penetration . It is well explained from limnology books that solar radiation is the major energy source for aquatic ecosystem, being biochemically converted via photosynthesis to potential chemical energy (Wetzel and Likens, 2000 ).

The absor ption of solar energy is determined and strongly influenced by suspended particles, dissolved organic and inorganic compounds. It is best characterised by the light extinction coefficient (η in m -1). In the present study, η was not directly measured on fie ld as it should have been for lacking equipment, but it was calculated by using the formulae of Poole and Atkin s (1929) cited by Wetzel (2001):

(Equation 3.6)

Where:

- Zsd : Secchi disk transparency depth (m)

Light penetration characterises lake’s water transparency and is strongly related to the characteristic of water to scattering light energy (Anderson, Lafontaine et al., 2007). It was measured by using Secchi disk. Marked seasonal fluctuations occur in response to variations in concentrations of plankton or inorganic particles (Wetzel and Likens, 2000). Figure 30 and Figure 31 show seasonal variation water transparency and the impact on the light absorption through light extinction coefficient, in the morning and in the afternoon.

12 Station 1 10

) Station 2 -1 8 Station 3 η (m 6 Station 4

4 Station 5

0 Feb Mar Apr May Aug Sep Oct Nov Dec

0,45

0,4

0,35

0,3 Station 1

0,25 Station 2 Station 3 0,2 Station 4 0,15 Secchi Secchidepth (m) Station 5 0,1

0,05

0 Feb Mar Apr May Aug Sep Oct Nov Dec

Figure 30: Seasonal variation of light extinction coefficient and Secchi depth in the morning

30 Station 1 25

) Station 2 -1 20 Station 3 η (m 15 Station 4

10 Station 5

0 Feb Mar Apr May Aug Sep Oct Nov Dec

0,6

0,5

0,4 Station 1 Station 2 0,3 Station 3 Station 4 0,2 Secchi Secchidepth (m) Station 5

0,1

0 Feb Mar Apr May Aug Sep Oct Nov Dec

Figure 31: Seasonal variation of light extinction coefficient and Secchi depth in the afternoon

According to light extinction coefficients calculated from each station there are seasonal changes between rainy and dry season. Light extinction coefficient tends to rise during dry season from April and commences to decrease from late October when rainy season is about to start. The minimum values (4.3 m -1 in the morning and 3.4 m -1 in the afternoon) are being found during rainy season in February, while maximum values of 14.2 m -1 (in the morning) and exceptionally of 34 m-1 (in the afternoon) are being reached in August and November respectively. With annual mean values of 9.2 and 10.3 m -1 respectively in the morning and in the afternoon, light extinction coefficient tends to be relatively higher in the afternoon. Higher values of extinction coefficient are much more found in the first three stations (1, 2, and 3) both in the morning and the afternoon.

In other words, the lake’s water, owing to higher concentration of suspended and dissolved compounds, absorbs significant quantity of solar energy. According to Wetzel (2001), absorption in such a situation of higher particulate suspensoids is unselective at different wavelengths. This may be an indication of higher clay residual, used to treating people, from spa wastewater that is discharged directly into the lake and affects particularly stations 1, 2, and 3, while suspended compounds tend to settle at station 4 and 5 as relatively deeper. On the other hand, the dilution brought by storm runoff and rain during rainy season might be the reason for the light extinction coefficient values to decrease.

As regards the Secchi depth, it is normal to have its values from each station both in the morning and in the afternoon, inversely proportional to those of light extinction coefficient. In this way, Secchi depth values are much higher during rainy season from December to March, with a maximum value of 0.4 m (in the morning) and 0.5 m (in the afternoon) measured in February, compared to those of measured during dry season with maximum values of 0.2 m both in the morning and the afternoon. With annual mean value of 0.2 m (in the morning and afternoon), the lake’s water transparency is very low probably due to higher suspended solids and higher densities of phytoplankton. Station 5, which is localised in deeper part of the lake generally, has higher Secchi depth, so in other words more transparent than the other stations. Again, this is probably due to tendency of suspended particulate to settle at this deepest part of the lake.

The relationship of Secchi depth to light extinction coefficient over the monitoring period is shown in Appendix B. In general, the light extinction coefficient values characterising the solar radiation absorption are higher when less transparent, while decreasing when lake’s water becomes more transparent. Higher values are being found in the afternoon which was probably due to wind rise generally occurring at this period of the day.

3.2.1.2. Water temperatures

The data from field measurements of temperature from each station over monitoring period are plotted as graphs in Figure 32. The range of water temperature within the whole lake is very small and tends to be uniform irrespective of the season. Water temperatures in each station in the morning increase from 1 to maximum 3°C in the afternoon. Seasonal changes in lake’s water temperature are observed from plotted graphs. Water temperature, both in the morning and the afternoon, commences to decrease from April to September. The minimum water temperature tends to stabilise around 17°C (in the morning) and 21°C (in the afternoon) respectively during the winter period (May to August). Likely the water temperature would go a little bit down around 15 to 16°C (Asimbolarimalala, 2008) during the most freezing period (June and July) in Antsirabe.

The average minimum water temperatures of 17.1°C (in the morning) and of 20.8°C (in the afternoon) were reached in August and May respectively, while the average maximum temperatures of 26.6°C (in the morning) and 28.2°C (in the afternoon) were measured in

November. Although, as very shallow lake, the temperature of the water therefore responds more rapidly to the onset of cool winter or chilly conditions (Fish, 1970), it is probable that the most prevailing factors influencing these temperatures over the year is the temperature of the main influents from Northeast, originally cold, and from Northwest relatively warmer, and the velocity of the wind in an open valley, in addition to the higher heat absorption from sunlight. The shallow depth also may favour the lake’s water to respond more quickly to changes in air temperature. However, it is worthwhile noting that the lake’s water temperatures never go below ambient temperature even during freezing period. No significant thermal stratification was observed from the surface to Lake Bottom as far as sampling and measurement stations are concerned.

Morning

25 Station 1 20 Station 2 15 Station 3 Station 4 10

Temperature(°C) Station 5 5

0 Feb Mar Apr May Aug Sep Oct Nov Dec

Afternoon 35

25 Station 1 Station 2 20 Station 3 15 Station 4

Temperature(°C) 10 Station 5 5

0 Feb Mar Apr May Aug Sep Oct Nov Dec

Figure 32: Seasonal variation of Lake Ranomafana's water temperatures

3.2.2. Characterisation of Lake Ranomafana chemical conditions

Good knowledge of chemical characteristics of lakes are very important as they generally reflect the impact of lakes surrounding watershed, while changes in the relevant parameters are characteristic of eutrophication (Magadza, 1979), subject of the present study.

3.2.2.1. Conductivity

The field data concerning the lake’s water conductivity are plotted in Figure 33. The range of values between each sampling station is very small, i.e. the difference of measured conductivity between each station is relatively insignificant although Station 1, which is directly under influence of the influents coming from Northeast, shows conductivity values slightly lower compared to those measured from the other stations. Seasonal changes of lake’s water conductivity values are much more striking as these values tend to decrease during rainy season (November to March) and to increase during dry season (April to October). In the morning and afternoon, the maximum values of 1570 to 1790 μS cm -1 and of 1729 to 1768 μS cm -1 respectively, were measured in October. The minimum values of 673 to 715 μS cm -1 (in the morning) and of 707 to 789 μS cm -1 (in the afternoon) were observed in March. During the dry and cold season (April to October) slight decrease of conductivity values is remarked in August before exponential increasing up to the maximum values reaching in October.

Morning 2000 1800

) 1600 -1 1400 Station 1 1200 Station 2 1000 Station 3 800 Station 4 600 Station 5 Conductivity(μS cm 400 200 0 Feb Mar Apr May Aug Sep Oct Nov Dec

Afternoon 2000 1800

) 1600 -1 1400 Station 1 1200 Station 2 1000 Station 3 800 Station 4 600 Station 5 Conductivity(μS cm 400 200 0 Feb Mar Apr May Aug Sep Oct Nov Dec

Figure 33: Seasonal Variation of Lake Ranomafana water conductivity

3.2.2.2. Turbidity

Turbidity in water is caused by suspended inorganic and organic matter, such as clay, silt, carbonate particles, fine organic particulate matter, and plankton and other small organisms (Wetzel and Likens, 2000). Their presence enhances light scattering and absorption. Lakes having high concentrations of suspended particles and/or high levels of algal cells will have high measured turbidity. The variation pattern of the lake water turbidity is presented in Table 27.

Owing to the fact that there is no thermal stratification and the lake is very shallow only one measurement per station supposed to represent the whole column of water was performed. Both in the morning and the afternoon, the maximum values of turbidity were measured in November, with 66 and 126 FTU, respectively. Minimum turbidity was observed in May (15.72 FTU) in the morning and in March (24.17) in the afternoon. Although the uneven seasonal variation, higher values of turbidity were measured generally during rainy season (November to February), however, higher values were also observed during dry season (August and September). Higher turbidity values were mostly found in the afternoon.

Table 27: Lake Ranomafana water turbidity Turbidity (FTU) Morning Turbidity (FTU) Afternoon Period Mean Max Min Mean Max Min February 30.56 ± 3 35.29 27.08 38.07 ± 6.8 49.87 32.66 March 24.76 ± 5.5 31.90 20.03 26.70 ± 2.5 29.66 24.17 April 39.14 ± 9.7 48.20 26.88 59.36 ± 26.9 106.00 37.78 May 35.50 ± 12 45.47 15.72 34.26 ± 5.1 38.20 26.67 August 39.39 ± 4.1 45.46 35.50 45.04 ± 8.7 55.00 33.03 September 57.80 ± 3.4 62.00 55.00 45.04 ± 8.7 55.00 33.03 November 52,61 ± 14.4 66.00 32.77 80.00 ± 26.7 126.00 61.00 December 38.16 ± 10.9 56.00 29.04 49.87 ± 8.3 58.00 41.10

3.2.2.3. pH of Lake Ranomafana water

The pH values from each sampling site were measured both in surface and bottom level. These values varied between 6.64 and 9.02, irrespective of the sampling level and the sampling time and season. Using one way ANOVA analysis, it was found that there was a significant (P = 0.007) variation between sampling sites, irrespective of the sampling level and the sampling period. So, stations 1, 2, and 3 showed lower mean values (7.68 ± 0.47; 7.88 ± 0.54; 7.87 ± 0.56), whereas stations 4 and 5 had higher mean values, with 8.05 ± 0.53 and 8.15 ± 0.53, respectively. The same analysis, as a mean of detecting the effect of sampling time, found significant variation (P = 0.049) of pH between morning sampling and afternoon sampling, whereas the level of sampling (surface or bottom) was not significantly different. As regards the season the highest mean pH value was measured for October (8.61 ± 0.25), while the lowest mean value of 7.35 ± 0.22 for March. The lake tended to show higher pH values during September up to December, i.e. almost during the dry season, while they tended to decrease during rainy season. Table 28 presents the pattern of variation both seasonal and daily.

Table 28: Variation of pH with season and sampling time pH Morning Afternoon Period Level Mean Max Min Mean Max Min February S 7.50 7.70 7.20 7.84 8.12 7.6 B 7.40 7.60 7.20 7.67 7.95 7.30 March S 7.25 7.35 7.14 7.59 7.80 7.41 B 7.13 7.22 7.02 7.42 7.61 7.17 April S 7.40 7.60 7.31 7.59 7.91 7.40 B 7.34 7.52 7.24 7.55 7.85 7.36 May S 7.53 8.22 6.64 7.94 8.33 7.64 B 7.51 7.87 7.27 7.79 7.96 7.66

August S 7.56 7.71 7.40 Nd Nd Nd B 7.51 7.78 7.09 Nd Nd Nd September S 8.51 8.78 8.22 Nd Nd Nd B 8.52 8.80 8.29 Nd Nd Nd October S 8.66 8.96 8.26 8.82 9.02 8.59 B 8.42 8.60 8.16 8.56 8.75 8.20 November S 8.50 8.73 8.21 8.55 8.83 7.92 B 8.44 8.71 8.04 8.30 8.80 7.62 December S 8.25 8.48 8.07 8.39 8.58 8.25 B 7.96 8.38 7.27 8.32 8.60 7.85 S: surface and B: Bottom for sampling level

3.2.2.4. Dissolved oxygen of the lake water

Dissolved oxygen (DO) is considered one of the more important measurements of water quality and is a direct indicator of a lake’s ability to support aquatic life (USEPA, 2009). Aquatic organism species have different DO requirements for optimal growth and reproduction, in addition to the fact that most of biological processes within lakes depend on presence of oxygen.

The five stations (1, 2, 3, 4, 5) displayed, as average, high levels of DO, regardless of the period, time, and level of sampling. Mean values varied between 10.54 ± 3.84 mg l -1 and 12.38 ± 3.92 mg l -1. The highest mean value was found in station 3, while the lowest means value in station 1. However, further statistical analysis using “One way ANOVA” has not found significant differences between any of the stations mean values, with P = 0.300 well above 0.05, which would have represented any significant differences between DO levels from each station.

On the other hand, when the measured values are being assessed according to the time of sampling, measurements performed in the afternoon show higher mean value (12.56 ± 2.98 mg l -1) compared to those from the morning (10.95 ± 4.46 mg l -1). The One way ANOVA analysis also confirmed evidence of significant differences between morning sampling and afternoon sampling, with P = 0.005.

Naturally, although the shallow depth of the lake, higher levels of DO, as average, were measured on the surface water, with a mean value of 12.78 ± 3.58 mg l -1, compared to bottom mean value of 10 ± 3.91 mg l -1, and this, irrespective of the period, time of sampling, and the location of stations.

When regarded from period of sampling view point, striking seasonal changes of DO are showed, irrespective of sampling stations, level, and time of sampling. In this way, increase of DO levels was observed from May up to November. Slight decrease was noticed from

December to February. The highest mean value was obtained in September (15.64 ± 4.62 mg l-1), while the lowest mean value was found in December (9.16 ± 1.77 mg l -1).

Figure 34, which consists of 4 graphs, shows the oxygen variation as a function of level of sampling (surface and bottom), time of sampling (morning and afternoon), and period of sampling (dry and rainy season).

Surface dissolved oxygen (Morning) Surface dissolved oxygen (Afternoon) 25 25 ) 20 ) 20 -1 Station 1 -1 Station 1 (mg l 15 Station 2 (mg l 15 Station 2 2 2 Station 3 Station 3 10 10 Station 4 Station 4 Dissolved Dissolved O 5 Station 5 Dissolved O 5 Station 5

0 0 Feb Mar Apr May Aug Sep Oct Nov Dec Feb Mar Apr May Aug Sep Oct Nov Dec

Bottom dissolved oxygen (Morning) Bottom dissolved oxygen (Afternoon) 25 18 16 ) 20 )

-1 14 Station 1 -1 Station 1 12 (mg l 15 Station 2 (mg l Station 2 2 2 2 10 Station 3 8 Station 3 10 Station 4 6 Station 4 Station 5 Dissolved Dissolved O Dissolved Dissolved O 5 4 Station 5 2 0 0 Feb Mar Apr May Aug Sep Oct Nov Dec Feb Mar Apr May Aug Sep Oct Nov Dec

Figure 34: Variation of surface and bottom dissolved oxygen as a function of sampling station, season and time.

3.2.2.5. Daytime variation of dissolved oxygen (DO) and oxygen saturation in the lake

Field measurements of daytime variation of surface and bottom DO and oxygen saturation were carried out within the lake from one point located in the islet in the middle of Lake Ranomafana (Figure 35). Temperature and pH also were measured with the oxygen. Measurements were performed during 10 days from 6.00 am up to 17.30 pm on two-hourly basis. 5 days of measurement were performed in September, followed by 2 days of measurement in October, 2 days in November, and one day in December.

Figure 35: Location of the daytime monitoring of dissolved oxygen, temperature, and pH.

The average daytime variation of the monitored parameters is summarises in Table 29, while raw data can be found in Appendix C. The concentration of DO in surface and in the bottom generally showed same behaviour of being relatively low from the early morning (by 6 o’clock) and continuously on rising trend up to the sunset. In surface, low DO values ranged between 0.42 to 14.01 mg l -1, while in the bottom low DO values ranged between 0.32 to 12.95 mg l -1. High DO values reached by midday and in the afternoon showed sometimes very high concentration of DO ranging between 7.58 to 34.99 mg l -1 in surface, while in the bottom high DO concentrations lagged just behind by about one or 2 mg l -1 less as such 6.87 to 30.62 mg l -1. Over the duration of measurements the highest average surface DO was 25.37 ± 9.19 mg -1 whereas to the bottom this highest average was 22.23 ± 7.25 mg l -1. Rainfall, naturally preceded by covered sky, was remarked to reduce without really stopping

DO concentrations rising, and that happened during measurements in October, November, and December.

Table 29: Average daytime variation of dissolved oxygen, saturation of oxygen, pH, and temperature. -1 pH Temperature (°C) DO (mg l ) Saturation of O 2 (%)

Date Range Average ΔpH Range Average ΔT Range Average ΔDO Range Average ΔSat O 2 Surf. Bott. Surf. Bott. Surf. Bott. Surf. Bott. Surf. Bott. Surf. Bott. Nd Nd Nd 19.6- 20.6 ± 3.4 14.01- 12.95- 22.23± 19.98± 14.06 12.13 170.8- 162.6- 285.3± 268± 183.2 172.4 03.09.09 23 1.34 28.07 25.08 5.58 4.70 354 335 73.53 66.08 Nd Nd Nd 16.4- 20.56± 6.0 12.64- 12.37- 25.37± 22.23± 22.35 18.25 149- 148.4- 303.9± 287.03± 265.8 230.1 04.09.09 22.4 2.44 34.99 30.62 9.19 7.25 414.8 378.5 111.27 97.27 7.93- 8.15± 0.47 21.3- 24.1± 5.3 0.74- 0.9- 8.98± 7.15± 15.85 14.3 10.4- 11.6- 116.24± 95.66± 205.4 198.8 18.09.09 8.4 0.16 26.6 2.19 16.59 15.2 5.63 5.39 215.8 210.4 72.66 71.61 7.99- 8.06± 0.2 21.2- 23.63± 4.2 0.42- 0.32- 4.46± 3.05± 12.47 9.71 3.4- 0.3- 54.46± 38.03± 153.2 124 22.09.09 8.19 0.07 25-4 1.65 12.89 10.03 3.90 3.29 156.6 124.3 49.27 41.78 8.11- 8.27± 0.38 20.8- 24.36± 6.5 1.65- 2.15- 9.98± 8.98± 16 12.02 18.4- 24.7- 130.42± 121.91± 208.3 178.5 29.09.09 8.49 0.13 27.3 2.48 17.65 14.17 5.79 4.46 226.7 203.2 74.56 63.85 8.22- 8.58± 0.7 23.5- 26.67± 5.5 5.47- 5.56- 18.38± 16.04± 23.06 20.4 70.6- 76- 250.36± 226.31± 309.4 290.9 09.10.09 8.92 0.24 29.0 2.12 28.53 25.96 8.08 7.41 380 366.9 111.52 106.38 8.23- 8.39± 0.28 23.2- 24.44± 3.4 3.09- 3.08- 6.61± 6.17± 9.35 10.62 40.1- 45.1- 86.75± 89.77± 130.2 144 23.10.09 8.51 0.09 26.6 1.54 12.44 13.7 3.73 4.22 170.3 189.1 59.44 59.44 Nd Nd Nd 22- 22.98± 2.9 0.65- 0.79- 4.73± 4.39± 6.93 6.08 8.2- 10- 61.8± 58.01± 91.2 83.4 02.11.09 24.9 1 7.58 6.87 2.18 1.87 99.4 93.4 29.33 25.83 7.99- 8.18± 0.44 22.1- 23.76± 3.9 4.85- 3.89- 7± 6.75± 6.11 6.27 61.3- 50.1- 91.5± 91.11± 89 91.8 27.11.09 8.43 0.16 26 1.42 10.96 10.16 1.91 1.96 150.3 141.9 27.79 28.75 7.52- 7.94± 0.9 21.6- 23.39± 3.3 1.32- 1.61- 7.22± 5.81± 9.23 6.54 17- 21- 95.1± 77.43± 120.8 88 17.12.09 8.42 0.35 24.9 1.13 10.55 8.15 3.10 2.37 137.8 109 41.24 32.20

Over the monitoring period it was also remarked that, despite the relative rapid increase of DO back to higher levels after the naturally night drop, for some days there was a slight decrease of DO around 10 o’clock followed by continuous DO increase. The saturation of oxygen also followed the same pattern as DO. The water saturation of oxygen at early hours was generally below the saturation value (100%) to reach, by midday and in the afternoon, a state of super-saturation. The low saturation values could be ten time less than saturation value, while high saturation values being 3 to 4 times more than normal, both in surface and in the bottom. Low saturation values in surface and in the bottom ranged between 3.4 to 414.8% and 0.3 to 378.5% respectively. The highest average saturation in surface was 303.9 ± 111.27%, whereas to the bottom it was 287.03 ± 97.27%. The more rainy season approached, the more saturation of oxygen’s high values decreased to about 1.5 time of the normal value. As regards the other monitored parameters, namely temperature and pH, the first one showed values that were specific

for the season, i.e. before and during rainy season, with temperature of the water ranging between 19.6 to 27.3°C. pH values, however, did not show any big gradient during daytime as varying between 7.52 to 8.92. The average values for pH ranged between 7.94 ± 0.35 to 8.58 ± 0.24, with a trend to decrease during rainy season.

3.2.2.6. Level and variation of nutrients concentration in the lake water

One of the issues addressed in this lake study concerns lakes eutrophication, which has been a big issue for lakes management in developed world during the last few decades due to increased urbanization and discharge of nutrients per capita (Jorgensen, 1980). As the same issued is being suspected for the case of Lake Ranomafana evaluation of their availability (temporally and spatially) as main factor for sustaining primary production is considered very important. Therefore, better knowledge of nutrients would help defining the trophic status of the lake in the next chapter. However, due to technical and storage constraints only basic nutrients will be addressed in the present subchapter.

3.2.2.6.1. Nitrogen compounds

In terms of nitrate levels of concentration Figure 36 illustrates the pattern of variation according to sampling station, season, and time of sampling. Over the monitoring period of time and regardless of sampling station location, period and time of sampling, the NO 3 concentration varied between minimum value of 0.12 mg l -1 and maximum value of 6.37 mg l-1, with a mean value of 1.42 ± 1.08 mg l -1.

When regarded through each sampling station mean values, the NO 3 level of concentrations varied between 1.29 ± 0.88 mg l -1 to 1.55 ± 1.05 mg l -1, with the lowest mean value found in station 1, whereas the highest in station 2. Station 3, with a mean value of 1.47 ± 1.51 and a coefficient of variation (by dividing standard of deviation by mean) of 102.72%, is being found to have concentrations that varied much than those of the other stations. It is worthwhile noting that the hot spring water is originally rich in nitrate according to survey conducted for therapeutic purposes. The ANOVA test, with P = 0.966, showed little or no evidence of significant differences between any of the station mean values.

The pattern of variation according to the period (month) of sampling, unlike that by station, is much more striking by the fact that mean values were found relatively higher between February to May, while mean values decreased from August to December. Mean values varied between a minimum of 0.49 ± 0.41 mg l -1 (August) to a maximum of 3.26 ± 1.33 mg l -1 (May). So, higher mean values tended to be observed during wet season. By checking the coefficient of variation (CV) it is found that NO 3 concentrations measured in November were much variable than those of the other months, with CV around 87%. The probable explanation of this variation would be the effect of rainy season commencing and the supply of organic compounds from domestic effluents and storm runoff in addition to NO 3 from the spa wastewater. The significant difference of mean values according to period of sampling is confirmed by the ANOVA test, with P << 0.05.

Higher mean value was found mostly in the afternoon (1.47 ± 1.04 mg l -1) compared to that of morning samples, whereas morning samples showed much variable concentrations, with CV of 83,1%. However, the ANOVA test showed no significant evidence of difference between morning and afternoon sampling mean values (P = 0.628).

(Morning)

7,00

6,00 Station 1

) 5,00

-1 Station 2 4,00 Station 3 3,00 Station 4

Nitrate(mg/l 2,00 Station 5

1,00

0,00 Feb Mar Apr May Aug Sep Oct Nov Dec

(Afternoon) 5,00 4,50 4,00 Station 1 ) 3,50 -1 3,00 Station 2 2,50 Station 3 2,00 Station 4

Nitrate(mg /l 1,50 Station 5 1,00 0,50 0,00 Feb Mar Apr May Aug Sep Oct Nov Dec

Figure 36: Variation of nitrate concentrations as a function of sampling period, time and sampling station.

As regards the variation of Total Kjeldahl nitrogen (TKN), which is the total of organic nitrogen and ammonia nitrogen, Figure 37 shows the pattern of variation according to the season, sampling station, and time of collecting sample. Irrespective of period, location of each station, and time of sampling TKN varied, over the monitoring period, between a minimum and maximum values of 3.60 mg l -1 and 10.32 mg l -1 respectively. The mean value of tested TKN concentrations is of 6.26 ± 1.24 mg l-1.

By checking TKN concentration by station it appeared that mean concentrations varied between 5.96 ± 0.91 mg l -1 to 6.66 ± 1.52 mg l -1, with the lowest value at station 4 and the highest at station 3 followed by station 1. According to the CV (22.2%) station 3 seemed to

have more variable concentrations. This might be due to its location at proximity of the input of effluents from Northwest having higher organic charge from domestic origin. The ANOVA test found no strong evidence of significant difference between station mean values, with P = 0.488.

The range of mean values according to period of sampling varied between 5.06 ± 0.91 mg l -1 to 7.06 ± 1.25 mg l -1, with August, followed by October, having the highest mean values, while December showed the lowest mean value. In light of the range of mean values, one might eventually underline the trend of having most of higher values during dry season from April to November. The difference between periods of sampling seemed to be confirmed by the ANOVA test. With P = 0.006, there is strong evidence of significant differences between sampling period mean values.

The pattern of variation of mean values according to time of sampling is not very significant although lower mean value was found in the morning (6.04 ± 1.29 mg l -1) and higher in the afternoon (6.48 ± 1.18 mg l -1). According to the ANOVA test no significant differences were found between sampling time mean values, that is, time of sampling relatively does not affect mean concentrations of TKN.

Morning 10,00 9,00 8,00 Station 1 7,00 ) -1 6,00 Station 2 5,00 Station 3 4,00

TKN TKN (mg l Station 4 3,00 2,00 Station 5 1,00 0,00 Feb Mar Apr Aug Sep Oct Nov Dec

Afternoon 12,00

10,00 Station 1

) 8,00 -1 Station 2 6,00 Station 3 Station 4 TKN TKN (mg l 4,00 Station 5 2,00

0,00 Feb Mar Apr Aug Sep Oct Nov Dec

Figure 37: Variation of Total Kjeldahl nitrogen as a function of sampling period, time and sampling station.

With respect to total nitrogen, representing the sum of organic nitrogen with ammonia/ammonium nitrogen, nitrite nitrogen, and nitrate nitrogen, the overall concentrations varied between a minimum value of 4.07 mg l -1 and maximum value of 12.20 mg l -1, with a mean value of 7.52 ± 1.45 mg l -1, regardless of location of stations, season, and time of sampling. The pattern of variation of TKN concentrations is given in Figure 38.

Going into more details by looking at station’s mean values, it appeared that mean concentrations varied between 7.24 ± 0.96 mg l -1 to 7.89 ± 2.16 mg l -1. Station 3 showed the highest mean value followed by station 1 (7.62 ± 1.55 mg l -1), whereas station 4 had the lowest mean value. No significant differences were found between station mean values, with P = 0.761. Again, station 3 seemed to be subjected to relatively more variation of concentrations, with CV = 27.4%.

As previously the most striking variation was found between period of sampling. Indeed, higher mean values were found in February, March, and April, whereas mean values decreased from August up to December having the lowest mean value. Mean values varied between 5.79 ± 1.18 mg L -1 to 8.36 ± 1.21 mg L -1. April, with CV = 21.6%, seemed to be presenting the most variable concentration. Strong evidence of differences between sampling period mean values was given through ANOVA test, with P << 0.05.

Samples collected in afternoon showed higher mean value (7.82 ± 1.49 mg L -1) compared to those of morning (7.22 ± 1.35 mg L -1), although concentrations found in the afternoon were more variable according to CV = 19.05%. The ANOVA test showed very little evidence of differences between mean values in the morning compared to that in the afternoon, with P = 0.06.

Morning 12,00

10,00 Station 1 8,00 Station 2 ) -1 Station 3 6,00 Station 4 TN (mg l TN 4,00 Station 5 2,00

0,00 Feb Mar Apr Aug Sep Oct Nov Dec

Afternoon 14,00

12,00

10,00 Station 1 ) -1 8,00 Station 2

6,00 Station 3 TN (mg l TN Station 4 4,00 Station 5 2,00

0,00 Feb Mar Apr Aug Sep Oct Nov Dec

Figure 38: Variation of total nitrogen as a function of stations, period, of sampling, and time.

3.2.2.6.2. Phosphorus compounds

Over monitoring period of time the overall concentration of reactive phosphate (orthophosphate) as phosphorus varied between o mg L -1 to a maximum value of 3.66 mg L -1 without any consideration of location of stations, sampling period, and time. Mean value was estimated to be 0.54 ± 0.55 mg L -1. The pattern of variation according to location of stations, period of sampling, and time is presented in Figure 39.

By using mean values to compare reactive phosphate data, according to location of sampling stations, the following deserves to be underline. Reactive phosphate varied between 0.48 ± 0.42 mg L -1 to 0.68 ± 0.87 mg L -1. Station 3 showed the highest mean value as the station at proximity of the Northwest effluents input, whereas station 4 did show the lowest value. The same station 3 showed high CV of 127.94%, which means quite wide variation of concentration from sample collected in this location. However, the ANOVA test showed no evidence of differences between station mean values, with P = 0.84. So the location of station seemed to not bring about significant differences of concentration.

On the other hand, the statistical analysis of reactive phosphate data by comparing each period is obviously interesting. The highest mean value was found in April and the lowest in May, with 1.56 ± 0.84 mg L -1 and 0.11 ± 0.07 mg L -1 respectively. The general trend of variation was characterized by higher values from February to April, while lower values started from May to December. The question is about the relationship of that pattern to season. According to CV August having 265.5% seemed to show more variation in concentrations. Significant differences between periods of sampling mean values were given strong evidence by ANOVA test, with P << 0.05.

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Samples collected in the afternoon presented higher mean value (0.67 ± 0.69 mg L -1) compared to that of samples collected in the morning (0.41 ± 0.33 mg L -1). Samples from the afternoon also had wide variation of concentrations, with CV of 102.9%. Strong evidence of differences was provided by ANOVA test (P = 0.03) between sampling in the morning and sampling in the afternoon as far as reactive phosphate is concerned. Probably the rise of phytoplankton during sunny time is involved in the variation pattern.

Morning 1,40

1,20

1,00 Station 1 ) -1 0,80 Station 2

(mg P L Station 3

4 0,60 Station 4 R-PO 0,40 Station 5

0,20

0,00 Feb Mar Apr May Aug Sep Oct Nov Dec

Afternoon 4,00 3,50

3,00 Station 1 ) -1 2,50 Station 2 2,00

(mg P L station 3 4 4 1,50 Station 4 R-PO 1,00 Station 5 0,50 0,00 Feb Mar Apr May Aug Sep Oct Nov Dec

Figure 39: Variation of reactive phosphate as a function of sampling station, period, and time of sampling

From Total phosphorus point of view the same pattern was seen when comparing station mean values. Indeed, station 3 showed the highest mean value (1.57 ± 0.95) followed by station 5 (1.56 ± 0.97), whereas station 4 showed the lowest value (1.40 ± 0.62). More variable concentrations were measured in station 5, with CV of 62.2%. However, the ANOVA test provided no evidence of differences between stations mean values, with P = 0.96.

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As previously differences between periods of sampling mean values were given strong evidence by ANOVA test (P << 0.05). Total phosphorus mean values varied between 0.89 ± 0.96 mg L -1 and 3.30 ± 0.57 mg L -1, with the lowest found in November and the highest value in May. The general trend was again to see lower value from August to December, while higher values started from February to May. Wide variation of concentrations was found in September having CV of 109.7%.

Afternoon sampling presented higher mean value (1.63 ± 0.83 mg L -1) compared to that of morning sampling (1.33 ± 0.80 mg L -1). However, samples collected in the morning presented more variation in concentrations, with a CV of 60.2%. Also, the ANOVA test provided little evidence of significant differences (P = 0.08) between sampling in the morning and sampling in the afternoon. The pattern of seasonal is shown in Figure 40.

Morning 4,50 4,00 3,50 Station 1

) 3,00 -1 Station 2 2,50 Station 3 2,00

TP (mg P TP L 1,50 Station 4 1,00 Station 5 0,50 0,00 Feb Mar Apr May Aug Sep Oct Nov Dec

Afternoon 4,50 4,00 3,50 3,00 Station 1 ) -1 2,50 Station 2 2,00 Station 3

TP (mg P TP L 1,50 Station 4 1,00 Station 5 0,50 0,00 Feb Mar Apr May Aug Sep Oct Nov Dec

Figure 40: Variation of Total phosphorus as a function of sampling stations, period, and time of sampling

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3.2.2.6.3. Other nutrients

Although nitrogen and especially phosphorus compounds are major components for chemical and biological processes in lakes, other elements such as iron (Fe) and silicon (Si) do play relevant role as well in the above processes, especially with regards to the primary production and the types of algae growing in lakes.

As concern the presence of Fe in the lake, the survey conducted by Asimbolarimalala (2008) on the lake’s physical and chemical quality provided informative data on the level of concentration and the part of the lake where Fe seems to be at higher concentration. In this way, he found that Fe concentrations ranged from 26.25 mg L -1 to 1737.5 mg L -1, with a mean value of 338.41 ± 487.87 mg L -1. Higher concentrations were found from the eastern and northern part of the lake.

Few data were available as regards Si. A survey conducted, as complementary of this study, in June 2010 showed that dissolved silica within the lake varied between 29 mg L -1 to 51 mg L-1, with a mean value of 37.5 ± 6.76 mg L -1. The highest value was found at station 1 and 3 and the lowest at station 2.

It is noteworthy that the lake’s water contained very high concentrations of magnesium and calcium that could reach the level of 2580 mg L -1 and 5850 mg L -1. The composition of spring water with high mineral contents is affecting the lake water composition as well.

After doing the analyses of the variation pattern of nutrients in the lake, it would be logic to ask question as to what extent organic compounds would affect the lake’s chemical characteristics and status. The following sub chapter refers to organic compounds pattern of variation and behaviour.

3.2.2.7. Level and variation of organic compounds in the lake

From point of view limnology there is no need of analysing and assessing the level of organic matter in lakes as an indication of the degree of pollution, rather limnologists are much more interested in the decomposition of organic matter as source of carbon since dissolved and colloidal organic matter is utilized by aquatic animals directly, whereas organic matter of a given size range may be a major food source (Wetzel and Likens, 2000). Assessment of organic matter in this subchapter is being carried out owing to the fact that effluents from urbanized watershed are discharged into the lake. As such, our interest is rather in rough estimates of remaining organic matter, representing organic pollution, which is susceptible to biodegradation or oxidation. This is done for the purposes of seeking a better way of cleaning the lake.

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3.2.2.7.1. Biochemical oxygen demand (BOD)

BOD tests on collected samples over the monitoring period showed concentration levels that -1 varied from minimum mean value of 8.01 mg O 2 L to a maximum mean value of 47.65 mg -1 -1 O2 L , with a mean value of 21.67 ± 5.25 mg O 2 L . Figure 41 shows the pattern of variation of BOD according to location of stations, period, and time of sampling.

-1 -1 By station mean values varied between 19.45 ± 4.80 mg O 2 L to 25.04 ± 7.37 mg O 2 L , with the lowest mean value being localised at station 1 and the highest at station 5. According to CV calculation (29.4%) station 5 showed more variable concentrations both monthly and daily. The ANOVA test provided very significant evidence of differences between stations measurements as mean values (P = 0.019).

According to monthly variation February showed the lowest mean value (17.60 ± 3.78 mg O 2 -1 -1 L ) whereas November showed the highest mean value (25.55 ± 8.20 mg O 2 L ). The general trend of variation seemed to have relatively lower mean values between February up to May and higher mean values from August to December. Probably the effect of rain bringing about dilution but also organic matter through storm runoff was playing significant role in the shape of BOD variation. More variable concentrations were seen in November, with a CV of 32.1%. Strong evidence of differences between period mean values was provided by ANOVA test, with P << 0.05.

-1 The highest mean value was found in the afternoon (22.94 ± 4.44 mg O 2 L ) compared to -1 that in the morning (20.40 ± 5.72 mg O 2 L ). However, morning samples showed more variable concentration, with a CV of 28.04%. The ANOVA test provided strong evidence of differences between sampling in the morning and in the afternoon, with P = 0.021.

Morning 30,00

25,00

) Station 1

-1 20,00 L

2 2 Station 2 15,00 Station 3

10,00 Station 4 BOD (mg BOD O Station 5 5,00

0,00 Feb Mar Apr May Aug Sep Oct Nov Dec

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Afternoon 40,00 35,00 30,00

) Station 1 -1

L 25,00 2 2 Station 2 20,00 Station 3 15,00 Station 4 BOD (mg BOD O 10,00 Station 5 5,00 0,00 Feb Mar Apr May Aug Sep Oct Nov Dec

Figure 41: Variation of Biochemical oxygen demand as a function of station location, period, and time of sampling

3.2.2.7.2. Chemical oxygen demand (COD)

Irrespective of the location of stations, season, and time of sampling the overall COD values varied -1 between a minimum mean value of 21.67 ± 5.25 mg O 2 L and a maximum mean value of 67.63 -1 ± 30.46 mg O 2 L . The pattern of variation according to sites location, season, and time of sampling is presented in Figure 42.

Range of mean values according to location of stations varied from a minimum of 60.59 ± -1 -1 29.84 mg O 2 L to a maximum of 71.61 ± 33.00 mg O 2 L , with the lowest mean value from station 5 while the highest was found at station 2. Station 5 followed by station 2 showed more variable concentrations over the monitoring period, with CV of 49.25% and 46.10% respectively. However, the ANOVA test did not provide acceptable evidence of significant differences between stations mean values, with P = 0.852.

The variation of mean values according to period of sampling alike previous parameters was more striking. Indeed, the general pattern of monthly variation consisted of having lower mean values during rainy season, from December to April, and higher mean values during dry season starting from May to November. Range of COD mean values varied from 35.63 ± -1 -1 10.77 mg O 2 L to 108.31 ± 22.78 mg O 2 L . The lowest mean value was found in March and the highest in October. According to CV values December showed more variable concentrations, with a value of 41.51%. Furthermore, the ANOVA test provided strong evidence of significant differences between any of monthly mean values, with P << 0.05.

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Morning 160,00 140,00

120,00 Station 1 ) -1 L 100,00 2 Station 2 80,00 Station 3 60,00 Station 4 COD (mgCOD O 40,00 Station 5 20,00 0,00 Feb Mar Apr May Aug Sep Oct Nov Dec

Afternoon 140,00

120,00

100,00 Station1 ) -1 L 2 2 80,00 Station 2 Station 3 60,00 Station 4 COD (mgCOD O 40,00 Station 5 20,00

0,00 Feb Mar Apr May Aug Sep Oct Nov Dec

Figure 42: Variation of chemical oxygen demand as a function of sites location, period, and time of sampling

-1 The COD mean value from sample collected in the afternoon (71.60 ± 27.88 mg O 2 L ) was -1 found higher compared to that in the morning (63.66 ± 32.67 mg O 2 L ). Concentrations found from samples collected in the morning were more variable as confirmed by CV value of 51.32%. However, the ANOVA test did not provide enough evidence of significant differences between sampling in the morning and sampling in the afternoon, with P = 0.22.

Generally, there is close relationship between organic compounds and suspended or dissolved solids in surface water, so the next subchapter will be focused on detail analyses of solids in suspension or dissolved.

3.2.2.8. Variation of total solids and suspended solids

Analysis of solids as such is not properly relevant to the characterisation of lakes, however, it is not only one of the most common assessments of water quality, but also turbidity is

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associated with suspended solids concentrations (Droste, 1997). For the purpose of restoring the lake characterising solids in the lake water and their variations would not be less relevant for the study.

3.2.2.8.1. Total solids

In light of the data over the monitoring period of the lake it appears that one of the important charges having significant impact on the status of the lake is the high level of concentrations in TS. The overall concentrations ranged from a minimum value of 456.67 mg L-1 to a maximum value of 2706.67 mg L -1, with a mean value of 921.96 ± 354 mg L -1. The pattern of variation according to sites location, season, and time of sampling is presented in Figure 43.

The variation by station of sampling did not show striking pattern as between these stations, mean values ranged from 895.41 ± 296.79 mg L -1 at station 5 to 996.88 ± 537.52 mg L -1 at station 1. Stations 4 and 3 also showed higher concentrations, with 922.71 ± 314.26 mg L -1 and 916.46 ± 296.81 mg L -1 respectively. The most variable concentrations were found at station 1 having the highest CV of 53.9%. However, no enough evidence was provided by the ANOVA test regarding differences between stations mean values, that is, the whole area of the lake seems to be heavily charged with solids, unless slight decrease of mean concentration at station 5 pointed out this zone as sinking zone. Also, the deepest area is being localised around station 5.

By contrast the seasonal variation showed clear pattern of lower concentrations during very wet season, that is, between February and March, whereas higher concentrations started earlier as April up to December. The lowest mean value was found in March (490.67 ± 28.01 mg L -1) while the highest in October (1371.33 ± 50.68 mg L -1). December showed more variable concentration, probably because of the storm runoff influence. The ANOVA test provided very strong evidence of significant differences between any of period of sampling measured values, with P << 0.05.

Samples collected in the morning proved to have higher mean concentration of TS compared to that in the afternoon, with mean values of 932.17 ± 411.10 mg L -1 against 911.75 ± 293.22 mg L -1. Furthermore, concentrations from samples collected in the morning presented higher CV of 44.10%, which indicates more variable concentrations. However, the ANOVA test did not provide strong evidence of significant differences (P = 0.799) between sampling in the morning and sampling in the afternoon, although, generally, wind rises in the afternoon.

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Morning 3000,00

2500,00 Station 1 2000,00

) Station 2 -1 1500,00 Station 3

TS (mg TS L Station 4 1000,00 Station 5 500,00

0,00 Feb Mar Apr Aug Sep Oct Nov Dec Afternoon 1600,00

1400,00

1200,00 Station 1

) 1000,00 Station 2 -1 800,00 Station 3

TS (mg TS L 600,00 Station 4 Station 5 400,00

200,00

0,00 Feb Mar Apr Aug Sep Oct Nov Dec Figure 43: Variation of Total solids as a function of sampling stations, period, and time of sampling

3.2.2.8.2. Nature of total solids in the lake water

Total solids contents and concentrations in the lake water varied rather seasonally than by sampling location. In this way, between February and March, TS was mostly made up of volatile solids (TVS), with mean values ranging from 54.08 ± 13.21% to 72.85 ± 8.81%, and to lesser extent of non volatile solids (ITS) varying between 24.68 ± 9.44% and 43.3 ± 13.32%, regardless of time of sampling either in the morning or in the afternoon. Slowly the pattern of composition of TS changed from volatile predominance to non volatile predominance. So, between April up to December, TS consisted mostly of non volatile components and to lesser extent of volatile components. Non volatile contents varied between 45.59 ± 5.71% and 78.48 ± 3.41%, with the lowest value found in April and the highest value in October. By contrast the volatile part showed the highest value in April (52.97 ± 5.96%) and the lowest in October (19.73 ± 3.82%). The pattern of variation of solids composition is shown in Figure 44.

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Morning Afternoon 80,00 90,00 80,00 70,00 70,00 Station 1 60,00 Station 1 Station 2 60,00 Station 2 50,00 50,00 Station 3 Station 3 40,00 40,00 TVS (%) TVS Station 4 TVS (%) TVS Station 4 30,00 30,00 Station 5 Station 5 20,00 20,00 10,00 10,00 0,00 0,00 Feb Mar Apr Aug Sep Oct Nov Dec Feb Mar Apr Aug Sep Oct Nov Dec Morning Afternoon 90,00 90,00 80,00 80,00 70,00 Station 1 70,00 Station 1 60,00 Station 2 60,00 Station 2 50,00 50,00 Station 3 Station 3 40,00 40,00 ITS (%) ITS Station 4 (%) ITS Station 4 30,00 30,00 Station 5 Station 5 20,00 20,00 10,00 10,00 0,00 0,00 Feb Mar Apr Aug Sep Oct Nov Dec Feb Mar Apr Aug Sep Oct Nov Dec Figure 44: Variation of Total solids composition as a function of season of sampling

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3.2.2.8.3. Total suspended solids

Over the period of monitoring the lake, samples were collected for testing total suspended solids (TSS), which again is a relevant parameter determining the turbidity of the lake water, but also the nature of suspended matter by continuing the test through volatile suspended solids (VSS). The global level of TSS ranged from 22 mg L -1 to 182 mg L -1, with a mean value of 70.5 ± 35.74 mg L -1 irrespective of site location, season, and time of sampling.

When mean concentrations were compared between stations, the lowest value was found at station 4 (61.75 ± 26.33 mg L -1) while the highest at station 1 (81.50 ± 45.57 mg L -1) followed by station 3 (77.56 ± 42.51 mg L -1). In view of the stations having high level of TSS one is attempted to link the proximity of effluent inputs to these two stations (1 and 3). Also, station 1 had more variable concentrations amongst stations, with CV of 55.91%. Insufficient evidence was provided by the ANOVA test (P = 0.440) as far as differences between stations mean values are concerned, that is, the location of the sampling sites does not really influence the level of TSS concentrations.

By contrast, the monthly variation of TSS level of concentrations followed the same pattern as for TS previously, that is, lowest values were found in February and March, whereas the level started to increase from April up to December. Mean values ranged between 28.90 ± 4.61 mg L -1 (March) and 105.30 ± 13.07 mg L -1 (September). On the other hand December showed more variation of concentrations with CV of 59.39%. Naturally, with P << 0.05, strong evidence of differences between sampling periods was provided by the ANOVA test. Figure 45 shows the variation of TSS concentrations.

TSS mean values were found higher in the afternoon compared to that in the morning, with values of 84.53 ± 40.70 mg L -1 and 56.47 ± 22.99 mg L -1 respectively. Furthermore, concentrations measured in the afternoon seemed to be more variable according to CV of 48.15%. The ANOVA test provided strong evidence of differences between mean values of samples collected in the morning and those from samples collected in the afternoon, with P << 0.05.

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Morning 120,00

100,00 Station 1 80,00 )

-1 Station 2 60,00 Station 3 Station 4 TSS (mg TSS L 40,00 Station 5 20,00

0,00 Feb Mar Apr Aug Sep Oct Nov Dec Afternoon 200,00 180,00 160,00 Station 1 140,00 )

-1 120,00 Station 2 100,00 Station 3 80,00 Station 4 TSS (mg TSS L 60,00 Station 5 40,00 20,00 0,00 Feb Mar Apr Aug Sep Oct Nov Dec Figure 45: Variation of Total suspended solids as a function of sites location, season, and time of sampling

3.2.2.8.4. Nature of Total suspended solids in the lake

Mostly used in the selection and function of wastewater treatment processes the ratio between various substances is of big help for a better appreciation of the nature of effluents. The same ratio was being used hereafter to appreciating the nature of TSS in the lake water. According to Henze, Harremoës and al (2002) the ratio of volatile suspended solids (VSS) to suspended solids (SS) indicates the level of fraction of organic matter in the suspended solids. So, with a ratio between 0.4 and 0.6, fraction of organic matter is low, while between 0.6 and 0.8, that fraction is typical, and between 0.8 and 0.9, the fraction of organic matter is high.

The organic content pattern of the lake TSS varied, generally, between low and typical. Higher organic fraction in TSS was found in April, August, and September, while decrease

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started from October. However, higher fraction also was observed in January. Figure 46 shows the pattern of VSS/TSS variation over the monitoring period.

Morning 0,90 0,80 0,70 Station 1 0,60 Station 2 0,50 Station 3 0,40 VSS/TSS Station 4 0,30 Station 5 0,20 0,10 0,00 Feb Mar Apr Aug Sep Oct Nov Dec Afternoon 1,20

1,00 Station 1 0,80 Station 2 0,60 Station 3

VSS/TSS Station 4 0,40 Station 5 0,20

0,00 Feb Mar Apr Aug Sep Oct Nov Dec Figure 46: Variation of organic fraction in the suspended solids of the lake water as a function site, period, and time of sampling

3.2.2.8.5. Total dissolved solids

Another important variable which determines the chemical properties of water such as hardness, acidity, conductivity, which in turn affect the physical properties of water such as colour, taste and odour, as well as the capacity of the water to support life (Droste, 1997), is the total dissolved solids (TDS).

The whole TDS values over the monitoring period ranged from a minimum value of 428.67 mg L -1 to a maximum value of 2604.67 mg L -1, with a mean value of 851.45 mg L -1. Figure 47 shows the variation of TDS and the total dissolved volatile fraction (TDVS) content as a function of sites location, period, and time of sampling.

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The range of mean values by station is relatively narrow since the lowest mean value was of 812.17 ± 278.20 mg L -1 (station 5) and the highest was 915.58 ± 517.28 mg L-1 (station 1). TDS mean values seemed to decrease from station 1 to station 5. Even so, the ANOVA test did not provide strong evidence of significant differences between any stations mean values (P = 0.928). More variable concentrations of TDS were found at station 1, with a CV of 56.5%.

As illustrated in Figure 44 there was striking pattern of variation of TDS when mean values were compared according to sampling period. In this way, very wet season (February and March) showed lower values compared to those from dry season, commencing from April up to December. Highest mean value was found in October. Mean values ranged from 462.27 ± 27.23 mg L -1 to 1281.40 ± 31.13 mg L -1. The ANOVA test provided very strong evidence of significant differences between monthly mean values, with P << 0.05. December was found to show more variable TDS concentrations, with a CV of 57.6%.

As per station range of mean values according to time of sampling is narrow, with the lowest value of 827.22 ± 265.26 mg L -1 (afternoon) and the highest of 875.69 ± 393.99 mg L -1 (morning). More variable concentrations were found in the morning, with a CV of 45%, even so the ANOVA test provide no evidence of significant differences between samples in the morning compared to those in the afternoon (P = 0.520).

In light of the dissolved volatile content (Figure 44) one can remark that the more TDS concentrations increased, the more dissolved volatile fraction decreased, that is, the dilution of TDS was accompanied by higher content in presumed organic fraction, whereas more concentrate TDS went along with higher inorganic fraction. Dilution, naturally, did happen during rainy season in February, March, and a little bit in April.

Morning 3000

2500 Station 1 2000 )

-1 Station 2 1500 Station 3 Station 4 TDS (mg TDS L 1000 Station 5 500

0 Feb Mar Apr Aug Sep Oct Nov Dec

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Morning 80

60 Station 1 50 Station 2 40 Station 3

TDVS (%) TDVS 30 Station 4 Station 5 20

0 Feb Mar Apr Aug Sep Oct Nov Dec Figure 47: Variation of Total dissolved solids (TDS) as a function sites location, period, and time of sampling, and variation of Total dissolved volatile solids (TDVS) content

3.2.2.8.6. Alkalinity

Alkalinity is not a pollutant. It is a total measure of the substances in water that have “acid- neutralizing” ability. So, it gives an indication of the buffer capacity of water, therefore protecting it from pH easy change from any acidic substances addition.

Alkalinity, in the case of Lake Ranomafana, was not intensively tested over the monitoring period. However, few available data may give appreciable indication of the lake’s buffer capacity. According to Asimbolarimalala (2008) the lake’s alkalinity varied between 48.6 mg -1 -1 -1 L CaCO 3 and 113.7 mg L CaCO 3, with a mean value of 88.13 ± 21.61 mg L CaCO 3.

Complementary survey carried out in June 2010 showed a minimum alkalinity of 40 mg L -1 -1 -1 and a maximum of 100 mg L CaCO 3, with a mean value of 61.14 ± 18.68 mg L . These values seem normal since the water is mainly composed of spring water having high concentration in bicarbonate. However, low alkalinity also may be related to high nitrification activities, with a surplus of proton in the water. Indeed, nitrification has the largest impact on alkalinity and cause excessive decrease; if total alkalinity falls below about -3 -3 50 g m as calcium carbonate (CaCO 3) (1 mol total alk. m ), then the pH becomes unstable and can fall to values well below 6 (IAWPRC citing WRC, 1984)

In order to have a better picture of the lake status adding some information regarding the biological characteristics would be worthwhile. These will be presented in the next subchapter.

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3.2.3. Characterisation of Lake Ranomafana biological condition

As per physical and chemical conditions characterising the current biological conditions of the lake would give insight into the impact of physical and chemical characteristics changes the lake have been subjected to.

3.2.3.1. Variation of the chlorophyll a

Chlorophyll a is the primary photosynthetic pigment of all oxygen-evolving photosynthetic organisms and is present in all algae and cyanobacteria (Wetzel, 2001).From point of view limnology chlorophyll a is generally used to characterise the level of primary production and to what extent this latter varies temporally and spatially. Indeed, chlorophyll provides an indirect measure of algal biomass and an indication of the trophic status (Chapman, 1992). So, Figure 48 displays the pattern of variation of chlorophyll a over monitoring period and from different sites location, both in the morning and in the afternoon.

Over the whole monitoring period the level of concentrations in chlorophyll a of the lake water varied from a minimum value 88.74 mg m -3 to a maximum value of 416.99 mg m -3, with a mean value of 212.74 ± 76.37 mg m -3, regardless of the sites location, the period, and the time of sampling.

The mean values according to sites locations ranged from 200.53 ± 70.47 mg m -3 to 222.57 ± 70.44 mg m -3, with a tendency to have more or less lower values at stations 1 and 2, whereas relatively higher concentrations were found at stations 3, 4, and 5. The highest mean concentration was measured from sample collected at station 4, without any consideration of period, and time of collecting samples. However, the ANOVA test did provide no strong evidence of significant differences between any stations mean values (P = 0.919). Furthermore, station 5 showed more variable concentrations over monitoring period, with a CV of 40.50%.

Chlorophyll a variation was more striking through seasonal level of concentration. In such a way, the trend was to see lower mean values during very wet and likely more cloudy season, that is, in February and March. By contrast, higher mean values started from April up to December. The monthly mean values varied between 113.87 ± 16.14 mg m -3 (March) and 295.90 ± 43.08 mg m -3 (September). So naturally, the highest means values were obtained during the driest period, that is, in August, September, and November. Surely, the ANOVA test provided strong evidence of significant differences between any monthly mean values, with P << 0.05. October having the highest CV (45.39%) showed more variable concentrations.

Striking difference of mean concentrations according to time of sampling was less visible, probably this was due to the interval of time between first and second samples collections, both during sun rising. Samples collected in the afternoon showed relatively higher mean

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values (223.75 ± 72.01 mg m -3) compared to that in the morning (201.57 ± 79.75 mg m -3). More variation of concentrations was found from measurement carried out in morning samples, with a CV of 39.56%. The ANOVA test provided non strong evidence of significant differences between mean values any samples collected in the morning compared to that in the afternoon, with P = 0.170.

Morning 450 400 350

) Station 1

-3 300 250 Station 2 200 Station 3 150 Chl. a (mg m Chl. Station 4 100 Station 5 50 0 Feb Mar Apr May Aug Sep Oct Nov Dec

Afternoon 450 400 350 )

-3 300 Station 1 250 Station 2 200 Station 3 150 Chl. a (mg m Chl. Station 4 100 Station 5 50 0 Feb Mar Apr May Aug Sep Oct Nov Dec

Figure 48: Variation of chlorophyll a concentration as a function of sites location, period, and time of sampling

The biological communities of Lake Ranomafana are made up of plant and animals. So, although no detailed study has been carried on these communities, it is noteworthy to present the relevant members of them roughly.

3.2.3.2. Other phytoplanktonic communities

According to the data from survey along the littoral zone of the lake, carried out by IHSM/NUFU PhD candidate, Rasoamananto I. in 2008, representatives of the two major

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groups of diatoms were founds associated with littoral substrates as for example stones. Indeed, the group is commonly divided into the centric diatoms (Centrales), which have radial symmetry, and the pinnate diatoms (Pennales), which exhibit essentially bilateral symmetry (Wetzel, 2001).

The only specie from the centric group that Rasoamananto found associated with substrates along the littoral zone was Cyclostella atomus , whereas representatives from three out of the four groups of pennate diatoms were identified as follow: - The Araphidineae: Fragialaria sp Tabellaria sp ; - The Monoraphidineae: Cocconeis placentula, Achnanthes sp; - The Biraphidineae: Navicula cuspidate, Pinnularia pseudogibba, Pinnularia mesolepta, Pinnularia viridis, Gomphonema pseudoaugur, Gomphonema olivaceum, Nitzschia tryblionella, Amphora ovalis, Surirella brebissonii. In short, Rasoamananto I., during her survey of sessile diatoms associated with substrates along the lake littoral zone, found between 4 and 22 species of diatoms varying probably in function of physiological requirements and the constraints of the environment (Wetzel, 2001).

With regards to cyanobacteria, Rasoamanato identified few representatives such as the genus Merismopedia sp, and Eudonia sp.. Naturally, she underline the presence of unidentified zooplankton. It is worthwhile noting that both phytoplankton and zooplankton are highly sensitive to changes in the lake ecosystem and that the effects of environmental disturbances can be detected through changes in species composition, abundance, and body size distribution (USEPA, 2010). Also, it is important to note that no sign of massive presence of cyanobacteria (presence of algae scum on the water surface) was remarked during any of the monitoring campaign.

3.2.3.3. Fish and crayfish

Lake Ranomafana is subjected to intensive pressure from local population using different kind of material for catching fish such as big homemade basket, traditionally used to catch fish larvae scientifically called Gambusia sp , and nets to catch medium size Tilapia, probably from Tilapia nilotica specie , the one which can accommodate disturbed environment. Nets are installed in the afternoon and recovered, generally, in the morning (see Figure 9).

New coming specie of crayfish has been remarked during a campaign of monitoring to the lake. As mentioned in previous chapter it is about one invasive crayfish specie, locally known as “Fozaorana” and scientifically called Procambarus sp (Figure 49). This specie of marbled crayfish has been recently introduced in the country, and yet biologists have warned people about the danger they represent as to dominating the local origin crayfish while, as potentially invasive, represent a danger for fish. In effect, they are female and reproduce via parthenogenesis (http//theaquariumwiki.com/Procambarus_sp). The Conservation

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International (CI, 2011) Madagascar in its quarterly newsletter warned farmers about the potential damage they can bring about on the other species of fish and crayfish. They can multiply extremely quickly and have capacity to breed early and often with no males needed. Huge number of eggs is usually produced. They may eat sleeping and dead fish. Originally suspected from North America, their alarming invasion in the country has been observed during the rainy season in 2007. However, survey reported their presence since 2004 and 2005. Very keen to compete with fresh water other species, most regions of the country have been invaded by this fast multiplying crayfish.

Figure 49: "Foza orana" ( Procambarus sp ) collected nearby north-eastern effluent inlet, into the littoral vegetation

3.2.3.4. Macrovegetation

Different species of plant grow along the littoral zone of the lake, including grass and isolated invasive plant, mainly made up of water hyacinth (Eichornia Crassipes ). This latter used to invade and cover the whole lake area when chemical and biological conditions in the lake met the nutrient need of the plant. Lack of natural enemies, an abundance space, and adequate temperature are indeed required conditions to prolific growing of water hyacinth (Wikipedia citing Opande et al, 2004). Water hyacinth is a free-floating plant that gets its nutrients from the water from dandling roots. The plant reproduces by seeds and vegetatively by through daughter plants that form on rhizomes and produces dense plant beds. From one study, two plants produced 1,200 daughter plants in four months, while a single plant can produce as many as 5,000 seeds (www.ecy.wa.gov/programs/wq/plants/ weeds/hyacinth.html). The presence of water hyacinth poses not only aesthetical problem, but also, when not controlled, water hyacinth, by covering the whole surface of lakes, impacts water flow, blocks sunlight from reaching native aquatic plants, and starves the water of oxygen. The plants also create a prime habitat for mosquitoes, and a species of snail known to host a parasitic flatworm which causes schistosomiasis (snail fever) (www.en.wikipedia.org/wiki/water hyacinth ).

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The results of few tests carried out in June 2010, when the whole lake was covered by impenetrable mats of vegetation of water hyacinth, is shown in Table 30 and demonstrated that the quality of water changed dramatically from that without water hyacinth. There was striking decrease of dissolved oxygen (DO), pH decreasing to neutral, undetected ammonium

(NH 4), and particularly very low concentration of reactive phosphate (R-PO 4), and slight decrease of total Kjeldahl nitrogen. Furthermore, the depth of the lake decreased as well.

Table 30: Quality of the lake water during invasion of water hyacinth Station pH DO NO 3-N NH 4-N PO 4-P TKN COD TSS -1 -1 -1 -1 -1 -1 -1 (mg L ) (mg L ) (mg L ) (mg P L ) (mg L ) (mg O 2 L ) (mg L ) 1 7.22 2.44 0.12 Undetected 0.016 3.03 0 91 2 7.07 0.83 0.09 Undetected 0.017 2.53 5 78 3 7.27 1.12 1.10 0.02 0.017 6.57 10 65 4 7.00 0.89 0.41 Undetected 0.014 4.29 15 16 5 6.95 2.59 0.05 undetected 0.017 4.80 0 32

Figure 50 shows water hyacinth capacity to invade the whore open area of the lake.

Figure 50: Water hyacinth covering the whole lake surface

Lakes water physical, chemical, and biological conditions are closely related to the sediment conditions. So, the next subchapter will provide information about the current condition of Lake Ranomafana sediment.

3.2.4. Characterisation of Lake Ranomafana sediments chemical conditions

Sediments interact with lake water and soluble constituents in such a manner that they give many unique insights into limnological processes (Chapman, 1992). In order to have on hand more completed information about the suspected eutrophication problem affecting the lake and their cause few chemical testing were carried out on sediment samples collected from each station in parallel with water analyses. Nutrients, total solids (TS), and other nutrients as iron (Fe) and manganese (Mn) were analysed from these samples. Furthermore, the sediment composition and particle distribution also were determined.

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3.2.4.1. Nutrients

Overseas studies have shown that investigation of lake sediments can give valuable information on eutrophication (McColl citing Bortlesson 1971, 1977). In effect, limnological study is used to examining recent sediments in lake or reservoir system through chemical and biological characteristics, so as to get insight into processes that have induced changes in productivity of the systems (Wetzel and Likens, 2000). On the other hand, sediments play significant role in storing and reintroducing nutrients and other pollutants in overlying water when the condition fits to such processes to occur.

3.2.4.1.1. Total nitrogen

Total nitrogen (TN), in samples of sediment from surface layer level, was monitored from September to December 2009. Over this period TN range values varied between 0.68 mg g -1 and 2.88 mg g -1, with a mean value of 1.89 ± 0.53 mg g -1 irrespective of season and stations location. The pattern of TN variation is presented in Figure 51.

When compared by station, TN mean values varied between 1.83 ± 0.95 mg g -1 (Station 4) and 2.35 ± 0.27 mg g -1 (Station 5). Higher mean value found at Station 5 seems to indicate this latter as a sink zone. Station 4 showed more variable concentration, with a CV of 51.9%. However, the ANOVA test did not provide enough evidence of significant differences between stations mean values (P =0.616).

Maximum TN mean value was found in November (2.51 ± 0.32 mg g -1) while minimum mean value resulted from September measurements (1.63 ± 0.28 mg g-1). More variable concentrations were obtained in December, with a CV of 39.2%. The ANOVA test provided relatively strong evidence of significant differences between any of the monthly mean values (P = 0.044). In light of the obtained data, rainfall season and storm runoff is suspected to increase the accumulation of TN in sediment surface layers. TN in this case includes inorganic and organic fractions, and monitoring data is presented in Table 31, page 123.

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3,5

2,5 Station 1 ) -1 2 Station 2 Station 3 1,5

TN (mg g TN Station 4 1 Station5

0,5

0 Sep Oct Nov Dec Figure 51: Variation of Total nitrogen in sediments surface layers as a function of stations location and sampling period

3.2.4.1.2. Soluble reactive phosphate

Soluble reactive phosphate (SRP) and total phosphorus (TP) were monitored from August to December 2009. Over the monitoring period and regardless of sites location and sampling month, SRP values ranged between 5.16 µg g -1 and 59.91 µg g -1, with a mean value of 19.55 ± 10.84 µg g -1. Figure 52 presents SRP pattern of variation.

Station 2 showed the lowest mean value (16.46 ± 5.91 µg g -1) and station 3 the highest (28.11 ± 19.17 µg g -1). Apparently, the proximity of the latter station to the most polluted inlet (northwest effluent) seems to exercise influence on SRP concentration level of surface layers sediment. In effect, the concentration mean value at this station is about 1.5 more than that found at the other stations. So, it privileges the thesis of phosphorus from domestic effluent. On the other hand, more variable concentrations were measured from Station 3, with a CV of 68.2%. However, the ANOVA test produced no strong evidence of significant differences between any of the stations mean values (P = 0.419).

Lower mean values were found in December (9.66 ± 2.53 µg g -1) and August (13.29 ± 5.03 µg g-1) while November showed the highest mean value (28.43 ± 18.03 µg g -1), followed by October, and then September. According to CV value (63.4%) still November showed more variable concentrations. The ANOVA test provided strong evidence of significant differences between monthly mean values, with P = 0.017. Higher mean value found in November might be from high polluting charge accompanying storm water and urban runoff during the beginning of the rainy season, whereas relatively high mean values in September and October may originate from the combination of planktonic decomposition and effluent supply. Summary of SRP concentrations is presented in Table 31, page 123.

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50 Station 1 ) -1 Station 2 40 Station 3 -P (µg -P g 30 4 Station 4 PO 20 Station 5

0 Aug Sep Oct Nov Dec Figure 52: Variation of Soluble reactive phosphate in sediments surface layers as a function of sites location and sampling period

3.2.4.1.3. Total phosphorus

The overall TP concentrations ranged from 34.80 µg g -1 to 171.32 µg g -1, with a mean value of 75.20 ± 27.72 µg g -1. Figure 53 displays TP pattern of variation according to sites location and sampling period.

The comparison of mean values by station showed that mean values varied between 61.73 ± 12.42 µg g -1 (Station 2) and 91.32 ± 14.86 µg g -1 (Station 5) followed by Station 3 and 1. However, the ANOVA test provided no strong evidence of significant differences between stations mean values (P = 0.581). Station 1 showed more variable concentration having a CV of 76.3%. The thesis of station 5 being a zone of sink for pollutants is again questioned here.

By contrast, September showed the highest mean value (110.60 ± 37.26 µg g -1) against the lowest found November (56.80 ± 19.03 µg g -1). Highest More variation in concentration values also were found during September measurements. Furthermore, the ANOVA test produced enough evidence of significant differences between sampling period mean values, with P = 0.010. TP values are summarised as well in Table 31, page 123.

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180 160 140 Station 1 120

) Station 2 -1 100 Station 3 80

TP (µg TP g Station 4 60 Station 5 40 20 0 Aug Sep Oct Nov Dec Figure 53: Variation of Total phosphorus as a function of sites location and sampling period

Variation of TN, SRP, and TP according to sampling period is summarised in the following table.

Table 31: Means and ranges (in parentheses) nutrients content of surface sediments from the 5 stations Period TN (mg/g) SRP (µg g -1) TP (µg g -1) 13.29 ± 5.03 70.44 ± 16.46 August n.d (5.16 – 19.03) (50.62 – 92.89) 1.63 ± 0.28 21.66 ± 3.82 110.6 ± 37.26 September (1.37 – 2.07) (15.28 – 25.21) (80.71 – 171.32) 1.95 ± 0.33 24.72 ± 5.02 73.82 ± 12.89 October (1.49 – 2.28) (19.59 – 31.04) (56.20 – 89.14) 2.51 ± 0.32 28.43 ± 18.03 56.20 ± 19.36 November (2.07 – 2.88) (16.64 -59.91) (34.80 – 84.63) 1.86 ± 0.73 9.66 ± 2.53 59.17 ± 12.73 December (0.68 – 2.56) (7.20 – 12.47) (43.11 – 85.01)

3.2.4.1.4. Other inorganic compounds

Considered as micronutrients in lakes water column, Iron (Fe) and manganese (Mn) are inorganic elements that usually play relevant role in the mobilization of phosphorus from sediments to upper water layer. In order to get additional information about the environmental condition associated to the probable movement of phosphorus, concentrations of Fe and Mn in sediment samples, collected from the 5 stations, were analysed and hereafter presented.

Two sets of sediment samples collected in August and October 2009 were analysed by using Atomic Absorption Spectrophotometer (See Analyses of sediment samples). So, Table 32

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gives the different concentrations (dry weight) of Fe and Mn over two different sampling periods. Table 32: Iron and Manganese contents of Lake Ranomafana sediments Period Element 1 2 3 4 5 Average Fe (mg/g) 52.25 55.22 61.56 56.61 61.50 57.43 ± 4.06 August Mn (mg/g) 1.13 1.13 1.08 1.08 0.99 1.09 ± 0.06 Fe (mg/g) 56.80 54.26 57.82 55.95 58.98 56.76 ± 1.80 October Mn (mg/g) 1.24 1.32 1 1.17 0.91 1.13 ± 1.7

In August, Fe concentrations in sediment samples ranged from 52.25 mg g -1 to 61.56 mg g -1, with the lowest concentration found at Station 1 while the highest at station 3. The average concentration was of 57.43 ± 4.06 mg g -1. In light of these data, one would be attempted to suspect an enrichment of sediments from discharged effluents without neglecting sediments transport from watershed erosion, as Malagasy soil is being generally lateritic. Concentration levels did not really show great changes, in October, apart from the fact that highest concentration was found at Station 5 while the lowest at Station 2, with an average concentration of 56.76 ± 1.80 mg g -1. Furthermore, station being the deepest seems to be the sink zone for iron as well.

Appreciable concentrations of Mn were found in sediments either in August or October. Ranges of concentrations were relatively narrow between the lowest values and the highest. In August, Stations 1 and 2 showed higher concentrations (1.13 mg g -1) while Station 5 the lower (0.99 mg g -1), with an average concentration of 1.09 ± 0.06 mg g -1. No striking difference of concentrations was obtained in October, with the highest found at Station 1 (1.24 mg g -1) and the lowest at Station 5 (0.91 mg g -1). The average concentration was of 1.13 ± 1.7 mg g -1).

3.2.4.2. Total Solids and total volatile solids

Huge amount of sediments has been accumulating within Lake Ranomafana since its creation. It is very difficult, due to lack adequate material, to have an approximate volume of sediments accumulated in the whole area of the lake. Although sediment detailed study was not the main subject of this project, attempt to measure at least the depth of sediments by using hydrological expandable probe handle (1 to 3m) has been realised, but failed to get an estimate depth of the accumulated sediments, since the sediment layers were more than 3m deep. However, sediments nature was monitored over seven months by testing total solids (TS) and total volatile solids (TVS). Figure 54 displays the seasonal variation of TS and TVS content as percentages.

TS ranged between 261.20 mg g -1 and 386.85 mg g -1, with a mean value of 309.39 ± 32.07 mg g -1. Station 3 showed the highest mean TS value while Station 2 had the lowest, with values of 339.71 ± 26.39 mg g -1 and 286.80 ± 24.42 mg g -1 respectively. Note that Stations 4

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and 5 also showed relatively higher TS values. In spite a very low CV (14.5%) Station 4 showed variable values. This probably suggests relatively low fluctuation of TS throughout all stations. However, the ANOVA test produced strong evidence of significant differences between stations TS mean values (P = 0.017).

By contrast, monthly average TS varied between relatively narrow ranges of values. The lowest value was found in September (292.31 ± 27.97 mg g-1), whereas November showed the highest value (332.74 ± 32.53 mg g -1). December showed variable value, with a CV of 13.3%, compared to the other monthly values. But as per stations, the low CV value suggests relatively low fluctuation of TS over the monitoring period. And the ANOVA test provided no strong evidence of significant differences between monthly TS mean values (P = 0.358).

As regards TVS, the overall values varied between 46.93 mg g -1 and 66.11 mg g -1, with a mean value of 54.72 ± 5.15 mg g -1. In terms of percentage the volatile fraction, which is supposed to be of organic origin, was relatively low, ranging between 16.8% and 20.58%. This seems to be consistent with solids data from water column, suggesting high content of inorganic matter.

The variation of concentration levels between stations ranged from 51.82 ± 5.46 mg g -1 to 59.30 ± 4.44 mg g -1, with the lowest mean value localised at Stations 1 and the highest at Stations 3, the one at proximity of the most charged inlet. Station 4 showed more variable values, with a CV of 12.4%. Again, the low CV value suggests very little fluctuation of organic content between stations, although the ANOVA test produced enough evidence of significant differences between them, with P = 0.029.

The monthly variation was not very significant as the ANOVA test provided no strong evidence of significant differences between mean values, with P = 0.142. However, the lowest value was found in September (51.86 ± 4.32 mg g -1) and the highest in October (60.08 ± 4.79 mg g -1). More variable values were found in December (CV = 12.7%), probably due to rainfall influence with storm water and urban runoff accompanying each occurrence. However, low CV values suggest relatively little fluctuation of concentrations over the monitoring period.

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450 400 350 Station 1 300 )

-1 Station 2 250 Station 3 200

TS (mg TS g Station 4 150 Station 5 100 50 0 Mar Apr Aug Sep Oct Nov Dec

20 Station 1 15 Station 2 Station 3 TVS (%) TVS 10 Station 4 Station 5 5

0 Mar Apr Aug Sep Oct Nov Dec Figure 54: Variation of Total solids and percentages of Total volatile solids in sediments according to season and sites location

3.2.4.3. Characteristics and nature of Lake Ranomafana sediments at surface

In general, sediments classification ranges between silty, clayey, or sandy according to sediment contents in these elements. Indeed, the nature of sediments will be determined as a function of each of these 3 elements by using the ternary diagram base on relative percentage of sand, silt, and clay. The size distribution is important because smaller particles have greater specific surface area for pollutants adsorption (Kim, Choi et al (2003) citing Das, 1990). Therefore, the clay fraction, as the finest component, plays fundamental role with respect to the sediments characteristics inherent to sediments texture, that is, clay possesses more capacity to absorb ions. Table 33 below presents the clay, silt, and sand contents of sediment samples collected in March 2009 (practically at the end of rainy season) from the 5 stations and one from the middle of the lake.

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Table 33: Texture of Lake Ranomafana sediments at surface as a function of clay, silt, and sand contents Station Clay (%) Silt (%) Sand (%) Texture 1 20 33 47 Silty sand 2 18 35 47 Silty sand 3 21 32 47 Silty sand 4 20 34 46 Silty sand 5 19 36 45 Silty sand Middle 29 32 39 Sand-silt-clay

Fig 55 presents a ternary diagram, based on relative percentages of sand, silt, and clay, that was used for the determination of sediment particle distribution. Sediment samples from the 5 stations show relatively homogenous compositions and are classified as silty sand, whereas in the middle of the lake (around the islet), percentage of clay is more pronounced, to the detriment of sand. So, sediments in this area are classified as sand-silt-clay. Surely, these characteristics of sediments within the lake is playing important role in capturing and storing pollutants as phosphorus and nitrogen, but also in releasing and reintroducing back to the water column these compounds when redox condition fits to the process to happen, so that those nutrients can take part in the growth process of planktonic algae.

Figure 55: Sediments at surface particles distribution (diagram according to US Department of Agriculture Textural Classification, Kim, Choi et al, 2003 )

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3.2.5. Discussion

In order to have required data (physical, chemical, and to less extent biological) for a better understanding of Lake Ranomafana current status, campaigns of monitoring and analysis of those data were carried out. The aim of this exercise was not only to identify the key problems, but also to find out valid explications about the past and ongoing processes leading to the current status of the lake. A clear diagnostic of the visible eutrophication problem also would help understand the source or origin of the problem and propose the adequate solution for managing the lake towards its restoration. In this way, physical, chemical, and biological characteristics of the lake were previously presented, but need to be related from each other, so as to be useful for the management purposes.

3.2.5.1. Determinants of the physical shape of the lake

Obviously, the physical shape of the lake keeps changing from the original shape, which was, unfortunately, not well characterised since any data is unavailable. However, since the opening of the spa to the public, tons of suspended solids have been discharged into the lake through effluents from the spa, in addition to suspended solids from watershed erosion. Simple estimate from TSS mean values from Northwest and Northeast effluents gives an approximate of suspended solids conveyed annually by effluents, representing about 278.6 tons y -1. Irrespective of how important is the part which settles and the part which is being removed from flushing, it is obvious that the lake keeps accumulating important amount of sediments from suspended solids transported by effluents either in rainy or dry season. In other word, the lake is subjected to sedimentation or siltation, and the spa activities, by using mud bath, are one of the main sources of the sedimentation problem through its discharged effluents. On the other hand, it is likely that one part is flushed out of the lake through the outlet by the action of the wind, which keeps solids in suspension, while the wind action as well contributes to disperse suspended solids throughout the lake. Previously, it was stated that expandable hydrological probe of 3 m was not enough to reach the bottom strata of the sediment within the lake, so, surely, managing these sediments is amongst the other issues to be really taken into consideration for restoring the lake.

With respect to the transparency of the lake Figure 56 shows the seasonal variation of the average Secchi depth and the slight difference between the lake’s transparency in the morning compared to that in the afternoon. So, in general, transparency was better during rainy season, probably due to the effect of dilution by storm runoff, whereas the level decreased up to average values of 0.15 m and 0.11m in morning and afternoon, respectively, during dry season. This was probably due planktonic algal bloom during dry and sunny season. Likely exacerbated by the wind-induced resuspension of sediments, transparency was even worst in the afternoon. It is stated in training material touching lake concepts in the modelling software Pamolare 3 (United Nation Environmental Program) that lakes with Secchi-depth lower than 1m are usually heavily loaded with nutrients.

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0,4

0,35

0,3

0,25 Morning 0,2 Afternoon 0,15 Secchi depthSecchi (m) 0,1

0,05

0 Feb Mar Apr May Aug Sep Oct Nov Dec Figure 56: Seasonal variation of average Secchi depths

It is obvious and visible from Figure 57 that transparency is affected by total suspended solid irrespective of their origins either from sediment particles or planktonic algal cells. So, the more particles in suspension, the more transparency of lake water decreases. Definitely, combination of anthropogenic pressure from within the lake watershed and natural action (wind) is affecting transparency of the lake.

0,35

0,3

0,25

0,2

0,15 y = -0,121x + 0,673 R² = 0,752 0,1

0,05 Monthlyaverage Secchi depth(m) 0 0,00 1,00 2,00 3,00 4,00 5,00 LN TSS (mg l -1)

Figure 57: Correlation between Secchi depth and logarithm of average Total suspended solids

Temperature of the lake water also is amongst important physical characteristics that also determine ongoing predominant chemical and biological processes. As far as the lake Ranomafana is concerned the monitored temperature values never dropped below 15°C, even during freezing winter time, and because of very shallow depth no thermal stratification did occur as confirmed by relatively uniform temperature from surface to near bottom water column. Probable explication seems to be provided by the combination of warmer effluent from northwest with colder effluent from northeast. At least, Stations 1, 2,

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and 3 are more affected by this combination. This is also reflected by the lake water temperature that was always above ambient temperature as shown in Figure 58, in spite the influence of shallow depth of the lake, which generally favours rapid equilibrium of temperature with ambient temperature.

Because of the influence of temperature on decomposition of organic compounds at sediment level, it is noteworthy that in the shallower lake, absorption of solar energy by sediment is greater (Wetzel, 2001), shall it be even greater for Lake Ranomafana for being affected by both solar energy and thermal heat from used hot spring water from the spa. The question that will be treated in the next sub chapter concerns the extent to which these physical factors are affecting the chemical and biological characteristics of the lake.

Average ambient temp. Average morning temp. Average afternoon temp.

30 27,72 27,28 28,06 26,12 25,84 24,14 25 21,22 21,22 26,32 26,12 25,06 24,87 20,76 24,78 20 22,32 20,26 18,06 15 17,12

Temperature(°C) 10 19,7 19,7 19,2 17,8 17,8 19,2 19,4 15,3 15,5 13 12,8 13,3 5

0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Figure 58: Seasonal variation of average ambient temperature, average morning, and afternoon lake water temperature

3.2.5.2. Determinants of the lake chemical characteristics

Due to the impact of anthropogenic pressure from within its watershed Lake Ranomafana chemical characteristics, alike its physical status, are subjected to significant changes towards degraded status, that is, changes leading to eutrophication. Explanation about main chemical stressors patterns are believed to bring clarification to the lake health condition.

3.2.5.2.1. Conductivity

Conductivity of the lake varied according to season as slightly decreasing during rainy season and kept increasing during dry and sunny season. Over the monitoring period the average conductivity values measured in the morning and afternoon, were of 1193.84 µS cm -1 and of 1185 µS cm -1, respectively. The average maximum and minimum values were of 1709 µS cm -

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1 and of 686.8 µS cm -1. The lower values were likely caused by the storm runoff dilution, whereas higher values during dry and sunny season seem to reflect the hot spring water-fed origin of important part of lake water. However, one should not underestimate the effect of evaporation during sunny season when the lake is likely to function like a closed system. Wind-induced resuspension of sediments might favour interaction water-sediment, which influences conductivity. It is important to note that the lake is not saline, with salinity ranging from 0.6 to 0.7. According to Asimbolarimalala work (2008) cationic proportions determined heavy presence of magnesium and calcium followed by sodium and potassium as follow: Mg > Ca > Na > K. However, chemical test long time ago carried out on the hot spring source (source Perrier de la Bathie) detrmined cationic proportions as follow: Na > k >

Ca > Mg, whereas anionic proportions were HCO 3 > Cl > SO 4.

As micronutrients, calcium and the other cations are likely to influence photosynthesis process within the lake. Calcium is most likely required by green algae and is considered an essential inorganic element of algae, while magnesium is required universally by chlorophyllous plants (Wetzel, 2001). The same author also, in his limnology book treating “Lake and River ecosystems”, mentioned the importance of the ratio of monovalent to divalent cations in relation to the distribution and dynamic of algae.

3.2.5.2.2. Turbidity

Turbidity is a measure of light scattering. Higher turbidity values were measured in November but generally during dry season, and particularly in the afternoon. According to Wetzel (2001) turbidity usually consists of inorganic particles and originates by erosion of soil of the catchment basin and from resuspension of the bottom sediment. A particularly common suspensoid in hardwater lakes (case of Lake Ranomafana) is associated with colloidal and particulate calcium carbonate (CaCO 3). Wind-induced resuspension of clay and silt sediments is likely to cause higher turbidity compared to suspended solids brought by storm runoff, which mainly consist of sandy sediments readily more prone to settling. Wind, generally, rises in the afternoon causing more turbid water compared to that in the morning. Moreover, Figures 40 and 41 shows increased level of total solids and inorganic total solids during dry period so as to relate and also explain higher turbidity. Higher turbidity increase backscattering of light (Wetzel, 2001). So, it is probable that low Secchi depth values measured within the lake were also related to turbid lake water. On the other hand, the Environmental Protection Agency (2010) report on National lakes assessment underlined the impact of increased turbidity resulting in changing algae growth patterns.

3.2.5.2.3. pH and alkalinity

Lake Ranomafana, unlike most lakes that are basic (alkaline) when they are first formed and become more acidic with time due to the build-up of organic materials ( www.h2ou.com /h2wtrqual.htm#top), is a slightly basic lake having its pH ranging from 6.64 to 9.02. Actually,

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the lake pH is generally above 7.2 up to 9. The range of values between pH in surface and those from the bottom (about 10 cm above sediment surface layer) is relatively narrow being a shallow depth lake. Furthermore, pH values tended to be slightly higher in the afternoon and at Stations 4 and 5. As shown in Figure 59 higher pH values were measured during dry and very sunny day, that is, from September up to November. The explanation of the lake pH pattern is closely related to photosynthesis. Indeed, it is well known that photosynthesis causes pH to rise, whereas respiration causes pH to decline (Lewis Jr. and Mccutchan Jr., 2009). It is noteworthy that the hot spring water pH, measured long time ago by a team from Geophysics department of Antananarivo, was of 7.60, and high level of bicarbonate was found in the sample (3646 mg l -1). Relatively higher alkalinity was also measured by Asimbolarimalala (2008) within the lake, which is reflective of the origin of the lake water, but particularly demonstrating the lake‘s buffer capacity. The pH of Lake Ranomafana would likely be around more or less 7.60 in the absence of any influence other than presence of the bicarbonate ion that is delivered to it from the hot spring water. However deviation slightly below and above 7.60 seems to be caused by respiration accompanied by production and release of free CO 2 and photosynthesis consuming CO 2. As stated by Lewis Jr. and McCutchan Jr. (2009), inorganic carbon, through the carbonic acid- bicarbonate-carbonate equilibrium, is central to the control of pH in most lakes, and it is likely the case for Lake Ranomafana rich in bicarbonate while known to contain as well CO 2. pH between 7 and 8 occurred generally during rainy season and cold period (cloudy and less light) probably because of the pH being responsive to the rate of net photosynthesis of algae, not to algal biomass specifically (Lewis Jr. and McCutchan Jr., 2009). So, net growth during rainy and cloudy period likely lower algae net growth and therefore slightly decreasing pH (see Figure 56). In contrast, pH increased during dry season (from September) likely boosted by higher growth using more CO 2. On the other hand, lower pH values, although intense respiration process with release of CO 2, stabilise around 7 owing to the buffer capacity of the lake, provided by its appreciable alkalinity. It is important to remark that pH value between 7.5 and 8.4 seems to be the best range for the growth of algae (www.h2ou.com /h2wtrqual.htm#top), which is the case of Lake Ranomafana.

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Chl. a pH Surface pH Bottom 10 350,00 9 300,00 8 7 250,00 ) -3 6 200,00 5 pH 4 150,00 Chl. a (mg m Chl. 3 100,00 2 50,00 1 0 0,00 Feb Mar Apr May Aug Sep Oct Nov Dec Figure 59: Seasonal variation of average pH values as a function of sampling level (morning)

3.2.5.2.4. Dissolved oxygen

Alike pH, dissolved oxygen in Lake Ranomafana water is closely related to the presence of phytoplanktonic algae. The role of plant, in the lake case represented by phytoplanctonic algae, as oxygen generators through photosynthesis is well documented by numerous research in aquatic ecology area. So, the explanation of dissolved oxygen dynamic in lake water is just governed by micro-algae photosynthesis. The basic requirements are the presence of rapidly growing micro-algae, sufficient light, time and nutrients, and a moderate temperature (Oswald, 1988). Figure 60 shows the variation of oxygen in surface and at bottom layer. In general, the level of oxygen follows the shape of chlorophyll a, which, somehow, represents the micro-algae biomass and also reflective of the growth. Level of oxygen in the afternoon tended to be slightly higher compared to those in the morning due to the fact that maximum growth, therefore maximum production of oxygen was surely reached in the afternoon. During rainy and cold period, generally cloudy, level of oxygen tended as well to be lower than in the afternoon, after micro-algae likely got enough light, although reduced, to produce more oxygen compared to that in the morning. In contrast, during dry and sunny period from September, maximum conditions such as among other light and likely nutriments were present for optimum photosynthesis process to happen and oxygen production to reach the maximum as proportional to the micro-algae growth. The probable limiting factor for higher oxygen production would likely be the light penetration and the effect of temperature on oxygen solubility. It is recognized that high temperature decreases oxygen solubility, therefore decreases dissolved oxygen. This might be the case from November when temperature of water was generally high (between 26 to 28°C) due to relatively hot ambient air long with warm effluent from the spa. According to Wetzel (2001) solubility of oxygen in pure water in relation to temperature in equilibrium with air standard pressure saturated with water vapour starts to decrease from 17°C (9.870 mg L -1), and may

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reach 7.827 mg L -1 at 28°C. More important, to be taken into consideration, in the lake case also is the amount of oxygen that is being used by bacteria according to oxygen demand for biodegrading organic compounds from wastewater discharge into the lake. So, the level of oxygen measured in the lake is mainly determined by the intensity of photosynthesis against respiration process by heterotrophic bacteria degrading biodegradable organic compounds. It is important to note that oxygen level near surface sediment is relatively low as between 0.5 to 2 mg L -1.

Chl. a DO Surface DO Bottom 350,00 25

300,00 20 250,00 ) -3 )

15 -1 200,00

150,00

10 (mgDO L Chl. a (mg m Chl. 100,00 5 50,00

0,00 0 Feb Mar Apr May Aug Sep Oct Nov Dec Chl. a DO Surface DO Bottom 350,00 20 18 300,00 16 250,00 14 ) -3 )

12 -1 200,00 10 150,00 8 DO (mgDO L Chl. a (mg m Chl. 100,00 6 4 50,00 2 0,00 0 Feb Mar Apr May Aug Sep Oct Nov Dec

Figure 60: Variation of Dissolved oxygen and Chlorophyll a generated by phytoplanktonic algae (Morning and Afternoon)

On the other hand, as presented in Figure 61 pH might have indirect control on dissolved oxygen. According to Oswald (1988) in his study of micro-algae capacity for treating wastewater, during the day, when there was an abundance of oxygen, the pH was too high

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for optimum bacterial oxidation and at night, when the pH was sufficiently low to permit rapid oxidation, there was a dearth of oxygen. On the figure below, lower pH corresponded to lower dissolved oxygen, whereas higher pH was accompanied by increase of dissolved oxygen during dry and sunny period from September. The daily monitoring data and figures in Appendix C seems to confirm Oswald statement.

DO Surface DO Bottom pH Surface pH Bottom 25 10 9 20 8 7 )

-1 15 6 5 pH 10 4 DO (mgDO L 3 5 2 1 0 0 Feb Mar Apr May Aug Sep Oct Nov Dec

Figure 61: Variation of oxygen and pH in surface and bottom levels (Morning)

3.2.5.2.5. Nutrients

Phosphorus and nitrogen are main nutrients required for plants and algal growth. In appropriate quantities, these nutrients support the primary algal production necessary to support lake food webs (USEPA, 2010). Since 1970s, nutrients enrichment of lakes has become a source of headache for managing fresh water, particularly lakes. This is why the importance attributed to these two main nutrients when touching lakes management issues.

Lake Ranomafana, likewise many other lakes in the world, is, according to available data, subjected to nutrients enrichment from discharged effluents and other tributaries (rainy season), but also from internal loading, that is, from sediments release of nutrients. The relationship between algal production and available nutrients are central to resolving lake management issues since most chemical and biological processes are related to the effect of this relationship. As eutrophication is the main issue this project is trying to handle, Jørgensen (1980) reported that the growth of phytoplankton is the key process of eutrophication and it is therefore of great importance in understanding the interacting factors regulating the growth. Figure 62 presents how chlorophyll a varied seasonally with phosphate and nitrate available (average values).

Over the monitoring period level of nitrate available was always exceeding available phosphate both in the morning and in the afternoon. Probable explanation would be

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continuous supply of nitrate from spa effluent, as hot spring is naturally rich in nitrate according to Réland (1905). On the other hand, the surplus of nitrate would likely be caused by the presence of ammonium from domestic effluents, as the nitrate uptake is inhibited by the presence of ammonium (Jørgensen, 1980). It is worthwhile as well noting that lower level of nitrate generally corresponded to higher level of phosphorus (April, August), but the reason seems to be unknown. During highly sunny and dry period (from August or September) level of nitrate really decreased following the decrease of phosphate level, which seems to indicate that, during high growth reflected by higher level of chlorophyll a, both nitrate and phosphate are used , although nitrate to less extent compared to phosphate. For both nitrate and phosphate this lower level of concentration, that is, from September, might represent intracellular nutrients released from algae cells autolysis.

With regards to phosphate it was less available than nitrate in spite the fact that internal loading from sediments may supplement phosphate supply for phytoplankton growth. In contrast, the uptake of phosphate, which concentrations over monitoring period were below nitrate concentrations without being a limiting factor, seems to sustain the growth of phytoplankton, both during rainy season (February and March) and dry sunny season (from September to November). The uptake of phosphorus was even more pronounced during dry and sunny period. The reason could have been enough available reactive phosphate in water to support growth, so, the phenomenon called “luxury uptake” is prevailing as the phosphorus concentration in the water is high, then the phytoplankton will take up relatively more phosphorus (Jørgensen, 1980). Chorus and Mur (1999) added that if SRP is found above detection limits, this means that it is surplus to the requirement of cyanobacteria and algae. Nutrients, even during maximum growth (from August to November), were not completely depleted (See Figure 62). As per nitrate, local people practicing hand washing near the outfall of north eastern effluent are likely supplying phosphate continuously to the lake , in addition to others sources.

Assuming that organic nitrogen represents 5% of volatile suspended solids (VSS), ammonium may be calculated from difference between total Kjeldahl nitrogen and organic nitrogen. As one can see from Figure 62 ammonium, likewise nitrate and soluble phosphate were largely above the required level for maximum algal maximum growth. Ammonium concentrations were even higher than those of nitrate and phosphate. So algae likely have choice between ammonium and nitrate as source of nitrogen. But in general ammonium is preferred to nitrate for algal growth, however, shift between ammonium and nitrogen may happen as depend on algae communities’ composition. Anyway, drop of ammonium level was remarked during higher growth period (May to October).

It is noteworthy that concentration of soluble reactive phosphate (SRP) in sediment surface layer increased from September to October during maximum growth. The probable explanation would either be SRP in sediment was less available being bounded to iron and clay or SRP from intracellular decomposition was high following higher algal growth.

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According to Jørgensen (1980) the loss after 24 h of planktonic green algae is as much as 33%.

On the other hand, complementary sediment cores analyses on nutrients (see results in Appendix D) carried out in 2010 seems to show that the sediments appeared to be storage of nutrients such as NO 3, and PO 4, although concentrations generally decreased from surface layer sediment to much deeper layer. However, these stored nutrients would be released from sediment to water column by wind-induced turn over, leading to resuspension of layer sediments. Samples of 30 cm core sediments were analysed from every 10 cm. According to Søndergaard, Peder Jensen, and Jeppesen (1999) when studying internal phosphorus loading in shallow Danish lakes, the intensity and duration of internal loading may have a very significant impact on lake water phosphorus concentrations and subsequently on lake water quality.

Higher concentration levels of both nitrate and phosphate during rainy season (February to April) was mentioned, but as less light is available during this period because of cloudy sky, so, instead of either phosphorus or nitrogen being the limiting factor, it seems likely that light would be finally the limiting factor. Furthermore, light penetration might also be limited by high density of algae during higher growth season (from August to November) leading to algae growing in surface shading algae growing downward, and so, preventing incident light from penetrating a bit deeper. This phenomenon is known as, according to Wetzel, 2001), the self-shading effects of dense algal populations.

Chl. a PO4 NO3 NH4 6,00 350,00

5,00 300,00 )

-1 250,00 4,00

(mg l 200,00 4 3,00 NH

3, 3, 150,00 NO

4, 2,00 100,00 PO

1,00 50,00

0,00 0,00 Feb Mar Apr May Aug Sep Oct Nov Dec

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Chl. a PO4 NO3 NH4 6,00 350,00

5,00 300,00 )

-1 250,00

4,00 ) -3 (mg l

4 4 200,00 3,00 150,00

2,00 A Chl. (mg m 100,00 PO4, NO3, NO3, PO4, NH

1,00 50,00

0,00 0,00 Feb Mar Apr May Aug Sep Oct Nov Dec Figure 62: Variation of nutrients concentrations with chlorophyll a (Morning and Afternoon)

Figure 63 seems to confirm that neither phosphorus nor nitrogen is the limiting factor since the ratios TN/TP, over the monitoring period, never fell below about 4, and this lower ratio was in March, that is, likely when phytoplankton growth began and probably less supply from internal loading accompanied by high phosphorus demand by phytoplankton. It could be as well due to denitrification in column water (Wetzel, 2001). On the other hand, the ratio (N/P) around 7 seems to show relatively nutrient-sufficient growth conditions according to Redfield ratio of 7:1. However, the ratio decreased slightly in the afternoon as to reflect less availability of nitrogen, which might be due to less effluent from the spa because of reduced activities, but also internal recycling of phosphorus would likely supplement phosphorus from effluent input.

Chl. a TN/TP

10,00 350,00 9,00 300,00 8,00 7,00 250,00

6,00 200,00 5,00 CHl. a CHl. TN/TP 4,00 150,00 3,00 100,00 2,00 50,00 1,00 0,00 0,00 Feb Mar Apr Aug Sep Oct Nov

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Chl. a Série1

9,00 350,00 8,00 300,00 7,00 250,00 6,00 5,00 200,00 Chl. a Chl. TN/TP 4,00 150,00 3,00 100,00 2,00 50,00 1,00 0,00 0,00 Feb Mar Apr Aug Sep Oct Nov Dec Figure 63: Variation of TN/TP ratio with chlorophyll a (Morning and Afternoon)

As far as SRP is concerned sediment nutrients flux experiments did not show any conclusive results that would have showed any better condition for significant SRP to be released from sediments storage. It is, however, important noting that instability and extreme fluctuation in water quality characterising shallow lakes are to a large extent due to rapid changes in the internal supply rates of nutrients, and that resuspension of the surface sediments favoured by its morphometry and sediment granulometry, intense organic matter mineralization due to the labile nature or the organic settles matter (planctonic), and physical constraint (i.e. wind-induced resuspension), could play significant role in supplying reactive phosphate to lakes water (De Vicente, Amores, et al , 2006). The question that remains unanswered concerns the extent to which this recycling of nutrients (internal) supplement allochthonous sources from drainage basin and atmosphere (Wetzel, 2001).

3.2.5.2.6. Organic compounds

Biodegradable fraction of organic compounds in the lake was more or less variable over the monitoring period. The reason might be the low biodegradable charges from effluents were rapidly degraded by heterotrophic bacteria having largely sufficient oxygen, but also rapidly replaced by dead algae. There is slight increase of BOD from May (see Figure 41). In contrast, COD kept increasing from April to November. The storm water runoff might dilute non biodegradable fraction, mainly made up of mud residue from the spa. In this way, ration COD/BOD is seldom below 2. The ratio kept increasing from March up to November and may reach as high as 6. According to Henze, Harremoës et al (2002) a high COD/BOD ratio indicates organic matter difficult to degrade. However, COD in the lake is slightly low than combined COD from both Northeaster and Northwest effluents, which means that small part, even refractory, is being degraded or slight decrease of COD might also be due to settling of solids in suspension.

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Figure 64 displays variation of COD/VSS ratio, which may provide information about the variation of difficult to degrade organic compounds related to the content in easy to degrade organic compounds mostly from algae as VSS. In general, ratio tended to increase from August, and higher ratios were mainly found in the morning. This was probably due to higher supply of inorganic compounds from the spa in the morning in addition to wind-induced sediment resuspension, whereas in the afternoon organic compounds from algae decreased ratios around 1 to 1.5. The ratios find their importance in selection and function of treatment processes (Henze, Harremoës, et al, 2002).

3,5

2,5

2 Morning 1,5 COD/VSS Afternoon

0,5

0 Feb Mar Apr Aug Sep Oct Nov Dec Figure 64: Variation of COD/VSS ratios as function of season and time (average values)

After doing the characterisation of the lake, which has been very helpful in identifying the main issues leading to its current degraded status, it is also for the management purpose to evaluate the carrying capacity of the lake.

3.2.5.2.7. Carrying capacity of Lake Ranomafana

According to Chorus and Mur (1999) the concept of carrying capacity of the resources in a given ecosystem to sustain a population has proved very helpful in planning measure to control the size of that population. Applied to phytoplankton in Lake Ranomafana, this leads to asking questions related to potential biomass that could be sustained by available nutrients. In light of available data on nutrients and as already discussed previously, nutrients concentrations are so high that likely there is no nutrient limiting condition, but rather light would probably play this role of limiting factor. Indeed, if nutrient concentrations are excessively high, phytoplankton may reach a density that causes such a high level of turbidity that light availability limits any further growth, and in these situations populations will be light- rather than nutrient-limited (Chorus and Mur, 1999).

By using algae stoichiometric formula as C 106 H181 O45 N16 P, with molecular weight of 2429, and by assuming, in oxidizing system as Lake Ranomafana, that ammonium is the main source of

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nitrogen, carbon dioxide the source of carbon, phosphate the source of phosphorus and water the source of oxygen (Oswald, 1988) one can write the photosynthesis equation as follow: Light, Algae + 2- 106 CO 2 + 236 H2O + 16 NH 4 + HPO 4 C106 H181 O45 N16 P + 118 O 2 + 171 H 2O + 14 H + (Equation 3.7)

From the above stoichiometric equation and by using molecular weight of biomass, one can calculate the potential biomass (herein taken as volatile suspended solids or VSS) that would be sustain or supported by the maximum value of total phosphorus (TP) or the maximum value of total nitrogen (TN) found in the lake, regardless of that from sediments as internal loading. By using the above equation 31 mg L-1 P may support the growth of 2429 mg L -1 algae, that is, 0.012 mg L -1 P supporting 1mg L -1 algae. In this way, 1 mg P will support 83.3 mg L -1 algae, whereas, following similar way of reasoning, 14 x 16 mg L -1 N may sustain as well the growth of 2429 mg L -1 algae, that is, 1 mg L -1 N is believed to support 11 mg L -1 algae. So, the maximum TP in the lake of 4 mg P L-1 will then potentially support 333.2 mg L -1 algae, while the maximum TN of 12.19 mg N L -1 would sustain 134.1 mg L -1 algae. It is noteworthy that cyanobacteria and many other phytoplankton organisms have developed storage mechanisms for phosphate (known as luxury uptake). They enable them to store enough phosphate for 3 – 4 cell divisions. Therefore one cell can multiply into 8 – 16 cells without requiring any further phosphate uptake and biomass can increase by a factor of 10 or more in a complete phosphate depleted condition. Chorus and Mur (1999), the authors the above statement, are more reticent about using phosphate as way of predicting potential biomass likely to grow in any phosphate level condition.

Besides, one cannot overlook the fact that whatever estimated biomass will sooner or later die and settle to the bottom to be rapidly degraded by bacteria. This degradation will consume oxygen, which roughly corresponds to the algae chemical oxygen demand (COD). From the same above equation the degradation (decay) of 1 mg L -1 algae will generate 1.55 mg COD (3776/2429). So, the degradation of 333.2 mg L -1 algae will bring about oxygen -1 -1 consumption equivalent to 516.5 mg O2 L , whereas 134.1 mg L algae will generate oxygen -1 demand equivalent to 207.9 mg O 2 L . Managers have to think about the whole lake volume.

When using result of OECD models (Chorus and Mur, 1999) citing Vollenweider and Kerekes, 1982), roughly per microgram of TP, an annual mean phytoplankton biomass corresponding to 0.25 µg of chlorophyll a, and a maximum of up to 1 µg of chlorophyll a, may be expected. So, from the lake water maximum TP of 4 mg L -1 is being expected a maximum of up to 4000 µg of chlorophyll a, which may lead to the estimate of the lake carrying capacity in terms of chlorophyll a by multiplying by the volume of the lake.

The same above authors underline the importance, for planning and management purposes, of being able to estimate which of the key resources (light, nitrogen or phosphorus) is likely

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to control phytoplankton biomass in any given system, that is, to give answer to the following question:

- Which resource determines the carrying capacity for phytoplankton?

This question would have response from Figure 63 showing the variation of TN/TP in function of chlorophyll a concentrations. To confirm related interpretation of Figure 60, one is going to use the above equation to estimate concentration of intracellular nutrients by using average values of VSS over monitoring period. Table 34 presents N and P concentrations from VSS and N/P ratios. In view of the ratios calculated, it seems that relatively higher use of phosphorus prevails over the monitoring period so as to support the algae growth as ratios are over 7.

Table 34: Concentrations of phosphorus, nitrogen in VSS and N/P ratios Feb. Mar. Apr. Aug. Sep. Oct. Nov. Dec. P 0.26 0.18 0.37 0.61 0.79 0.50 0.44 0.41 Morn. P 0.35 0.20 0.63 0.76 0.86 0.56 0.58 0.58 Aftn. N 1.96 1.38 2.80 4.66 6.03 3.81 3.37 3.16 Morn. N 2.68 1.53 4.84 5.81 6.58 4.30 4.43 4.48 Aftn. N/P 7.5 7.7 7.6 7.6 7.6 7.6 7.7 7.7 Morn. N/P 7.7 7.7 7.7 7.6 7.7 7.7 7.6 7.7 Aftn. Morn. = Morning, Aftn. = Afternoon

Carrying capacity is closely related to trophic status of the lake. This is why it is important to characterise this trophic status according to worldwide used criteria.

3.2.5.3. Characterisation of Lake Ranomafana trophic status

Still within the approach to assessing the condition of the lake through the assessment of the primary production, trophic status is being used to depict biological productivity in the lake (USEPA, 2010). Few criteria based on chlorophyll-a, Secchi transparency depth, total nitrogen, and total phosphorus. Table 35 presents criteria values from Lake Ranomafana so as to define its trophic status.

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Table 35: Trophic state of Lake Ranomafana Total Total Chlorophyll- Secchi depth phosphorus nitrogen a (m) (mg m -3) (mg m -3) (mg m -3) Mean 1480 7520 212.66 0.20 Range 630 - 4000 4070 - 12190 88.74 – 417 0.11 -0.38 Comments Extremely Very high Worst case Very low high (Table extracted from General Trophic Classification of Lakes and Reservoirs in Relation to Phosphorus and Nitrogen, Wetzel, 2001)

According to different values set up for evaluating lakes trophic status (Wetzel, 2001) Lake Ranomafana is classified as Hypereutrophic Lake, with total phosphorus above eutrophic range of values (16 – 386 mg m -3), total nitrogen above eutrophic range of values (393 – 6100 mg m -3), chlorophyll a above eutrophic range values (3 – 78 mg m -3), and Secchi transparency depth above eutrophic range of values (0.8 – 7.0 m). Furthermore, hypereutrophic status of the lake also is confirmed by calculated Carlson’s Trophic State Index (TSI) (Mayhew (1991) citing Carlson, 1977) according to the following formulae:

- 60 14.41 ln , (Equation 3.8)

- 9.81 30.6 (Equation 3.9) Where, - SD: Secchi disk transparency (m), - CHL: Chlorophyll a (mg m -3).

In Table 36 are presented the trophic state index (TSI) calculated from Secchi dept transparency, chlorophyll a, and total phosphorus. All TSI values calculated from Secchi depth, chlorophyll a, and total phosphorus are above 70, which is characteristic of hypereutrophic conditions (Wetzel, 2001). TSI changes over the monitoring period and also between morning and afternoon TSI values from either Secchi depth or chlorophyll a increases from May up to December and to be higher in the afternoon. Probable explanation is from increased algal growth during dry and sunny season, but also increased turbidity during this period due to frequent wind-induced resuspension of sediments, particularly in the afternoon.

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Table 36: Carlson’s trophic State Index calculated from Secchi depth and Chlorophyll a, and Total phosphorus TSI Feb. Mar. Apr. May Aug. Sep. Oct. Nov. Dec. TSI(SD) 79.4 76.4 86.2 83.9 86.9 84.6 85.5 84.6 86.4 morning TSI(SD) 79.4 77.3 83.9 83.2 86.1 86.1 88.4 91.9 86.4 Afternoon TSI(CHL) 78.3 76.7 81.6 82.8 84.3 86.5 80 86.2 79.9 morning TSI(CHL) 81.4 77.4 83.1 82 86.2 86.3 83.6 84.1 83.9 Afternoon TSI(TP) 104.3 105.8 110.1 121.3 102.4 106.1 104.7 102.2 101.3 morning TSI(TP) 105.1 113.8 117.0 120.6 104.3 107.5 105.1 102.1 103.5 Afternoon

According to Wetzel (2001) deviations of the TSI relationships can be clarified by graphical expression as shown in Figure 65. Values, represented by name of the month, above the zero X-axis and below zero Y-axis indicate the likelihood of phosphorus limitation or small particles. With respect to Lake Ranomafana the latter is more probable than P limitation as there is relatively sufficient available P. Points to the right of the Y-axis and above the zero X- axis indicate transparency is greater than predicted from chlorophyll index.

If the three TSI values are not similar to each other, it is likely that algal growth may be light- or nitrogen-limited instead of P-limited, or that Secchi disk transparency is affected by erosional silt particles rather than by algae or something else (Pavluk and De Vaate, 2008).

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Figure 65: Potential nutrient-limited and non-nutrient-limited causes for deviation of biomass- based trophic state index, in the morning and afternoon (Wetzel, 2001)

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3.3. Partial conclusion

The preliminary surveys carried out in 2005 and in 2008 although incomplete helped not only design the monitoring campaign over 2009, but also helped find out the main focus of the monitoring campaign in order to achieve the different objectives cited previously. The monitoring conducted for less than one year has offered a unique opportunity to frame scientifically-based alternatives to the restoration of Lake Ranomafana in Antsirabe. It serves as a first step in the evaluation of any restoration project feasibility taking into consideration relevant local prevailing context: social, economical, municipality sustainable funding, agricultural irrigation, health and recreational benefit.

Better knowledge and understanding about the lake’s current status and conditions (physical, chemical, biological a bit less) not only can serve as a guide to the identification of the main problems leading to the actual conditions of the lake, but also constitute a useful background to creating a worldwide-used powerful tool for facing similar problem affecting aquatic environment, that is, modelling for lakes management, which is the second step towards finding site specific approaches to Lake Ranomafana restoration.

Taken together, the results of the lake’s characterization also provide a broad range of information necessary to understand the actual condition of the lake and some of the key stressors likely to be affecting it. The results are particularly important as they establish for the first time a baseline data for future monitoring having objective of tracking the trend in lake conditions. Whenever one restoration project will be implemented then these stressors would be placed in context of their relative importance for maintaining the lake integrity.

3.3.1. Current condition of Lake Ranomafana

The results of the survey and the monitoring provide information relating to the fundamental question of “what is the actual and current condition of Lake Ranomafana”. The study reports on the lake current health status according to the following 3 conditions: physical, chemical, and biological.

3.3.1.1. Physical conditions.

The current physical condition of the lake is definitely affected by the dynamic of its watershed as refer to surrounding urban settlement, spa activities, receptor of solid waste, and domestic wastewater. So, it seems that the original role of the lake as a counterbalance of gases pressure loss seems to be put in the middle distance, whereas the dumping site role seems now to prevail. Consequently, the lake’s morphometry keeps changing along with its physical condition deteriorating. This latter is characterized by the lake becoming shallower, with only an average depth of 0.5 m and a maximum depth between 0.8 and 0.9 in function of the season. This is mainly due to intensive sedimentation generated by important transport of suspended solids into the lake from watershed erosion during heavy storm in 146

addition to heavy load of mud residue from the spa. The littoral zone is expending to the detriment of profundal zone. Reduced depth not only hastens exchange and equilibrium of column water temperature to ambient temperature, which, in general, is beneficial to algal growth and other biological processes leading to eutrophication status, but also facilitates wind-induced sediment resuspension, with the upper layer, particularly rich in potential nutrients ready to be released back in water.

Even shallow, suspended solids and algae growth inhibit deeper penetration of light as transparency is much reduced. Consequently, light extinction tends to be higher favouring heat absorption by the lake water. Lack of previous monitoring data prevent from any physical status comparison, but a visual comparison with the photo of the lake shot in 1946 (see Figure 5) seems to be enough to declare the bad physical condition affecting Lake Ranomafana now.

The external factors affecting the physical condition of the lake also concern precipitation and evaporation of the lake water. This latter represents about 59% of the average annual precipitation.

3.3.1.2. Chemical conditions

Chemical conditions have been assessed for both external loading going to the lake and in- lake water.

3.3.1.2.1. Chemical characteristics of external loading

The present chemical conditions of the lake are a logic consequence of the physical degradation, but particularly of the nature of influents discharges into the lake.

The external loading to the lake comes permanently from two influents (northeast and northwest) in addition to about 8 small canals for storm and urban runoff drainage purpose. All inlets convey solid waste (plastic bag, paper,etc) and suspended solids into the lake. The northeast inlet is actually clean from its source located downward the Norwegian missionary, but becomes polluted by poor dwellers practicing hand washing before its entry to the lake.

From point of view organic compounds the external loading may be classified as very diluted domestic wastewater according to Henzel, Harremoës et all (2002), with BOD < 150 and COD -1 -1 < 210 mg O 2 L . The average gross annual organic loading is about 231 575 kg y as COD.

Both permanent inlets convey appreciable level of nutrients, but still they are classified as from dilutes wastewater. They are mainly composed of phosphorus, nitrogen (organic, ammoniacal, and oxidized). The gross annual average of nutrients external loading could reach 2395 kg y -1 of soluble reactive phosphate (SRP), 15 676 kg y -1 of nitrate nitrogen.

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One of the main stressor of the lake is total suspended solids (TSS), which mainly come from the northwest influents. They are composed of volatile suspended solids (VSS) for 54 to 71% and inorganic suspended solids for 29 to 46%. Mud residue and urban and storm runoff influence the nature of total suspended solids conveyed by influents to the lake. It was estimated about 279 tons y -1 were conveyed by influents to the lake.

As part of spring water influents have very high conductivity, with maximum 6 mS cm -1 (based on 2005 and 2008 surveys) depending on the season. Relatively higher conductivity is measured during raining season.

The average chemical characteristics of external loading as being equivalent to a very diluted domestic wastewater takes nothing away from being potentially harmful to the quality and trophic status of the lake. On the other hand, although relatively unstable with respect to polluting charge according to season, these influents do not comply at all with the national standards for wastewater discharge, particularly concerning temperature, total suspended solids, turbidity, and nitrate. Finally, it is worthwhile noting that they are hardly biodegradable, with the ratio 2.5

Based on influents discharged estimated to be 507 m3 h-1 (may be overestimated), pollutants conveyed into the lake seems to be important from point of quantity and volume. However, lack of sufficient data on influents discharge and outflowing water would suggest that rather the duration of such discharge since few decades ago has worsened the effect.

3.3.1.2.2. Chemical characteristics of the lake water

Apparently since the preliminary survey 2005, the lake water quality has continued to get degraded by the pollutants external supply, but also by intensive physical, chemical, and biological processes taking place in the lake.

The results of the monitoring show that nutrients and suspended solids are the most important stressors to the lake physical, chemical, and biological health.

The present health status of the lake is being characterized by the following chemical and biological parameters:

Temperature: due to shallow depth the lake does not have any thermal stratification and generally tends to have two to 3 units degree of temperature above ambient temperature. In this way, the highest minimum and maximum temperatures being reached in the afternoon, and they turn around 21°C and 28°C respectively. Three factors are believed to determine prevailing temperature: temperature of influents, rapid exchange air ambient/water column, heat absorption.

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Conductivity: the results showed that in-lake water conductivity is lower than influents conductivity. The dilution from urban and storm runoff seems to decrease conductivity up to one third of the maximum value. This latter could reach 1790 µS cm -1. The mineral content of the lake water is following: Mg>Ca>Na>K and HCO 3>Cl>SO 4.

Turbidity: the lake water showed higher turbidity mainly in the morning compared to that in the afternoon, with maximum values of 62 FTU and 55FTU, respectively. pH: according to season the lake water pH varied between 6.64 and 9.02. October witnessed the highest mean value of 8.61 ± 0.25, whereas March showed the lowest mean value (7.35 ± 0.22)

Dissolved oxygen (DO): the concentration level of dissolved oxygen was closely related to algae growth. In this way, DO levels increased from May up to November, i.e. during dry period usually beneficial to higher algae growth. The highest value was measured in September (about 16 mg L 1). Higher values were measured in surface compared to those from bottom. On the other hand, the occurrence of rainfall seems favour the decrease of DO. The average concentration was of 10.5 mg L -1 throughout the lake.

Daily variation pattern was relatively striking, with DO variation in surface and at bottom ranging from 0.42 to 34.99 mg L -1 and 6.87 to 30.62 mg L -1, respectively. Mean values measured in surface and at bottom were of 25.4 and 22 mg L -1. Accordingly, the saturation in

O2 was generally below the 100% saturation in the early morning and kept increasing up to water becoming supersaturated in oxygen at midday, with maximum up to 580%.

Nutrients: the lake suffered from nutrients enrichment from external and internal loadings from sediment release due to resuspension induced by wind rise. Nitrate (NO 3) could be found at relatively higher concentration up to more than 6 mg L -1. Higher values were measured at Stations 2 and 3 likely because of proximity to inlet. Also higher values were characteristic of rainy season mainly in the afternoon. In contrast, NO 3 level decreased during dry season.

Ammonia was found at relatively high level over the monitoring period. There is little difference between morning and afternoon average value, with 4.2 and 4.1 mg L -1, respectively.

Phosphate, the most important component for growth either for algae or bacteria, could reach a maximum value of less than 4 mg L -1, but the mean value is rather low around 0.5 mg L -1. Station 3 located at proximity of northwest inlet showed usually higher values compared to the other stations. The general trend was to get higher values during rainy season and lower values during dry season.

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This general trend of being lower level during dry season, for all three nutrients, reflected their support for growth during this period of the year. It is worthwhile noting that other nutrients, such as iron (Fe), silica (SI), calcium (Ca), and magnesium (Mg), have been found at appreciable level in the lake so as to offer optimum conditions for algae growth.

Organic compounds: the COD/BOD ratio ranged from 2 to 5 indicating organic matter difficult to degrade similar to organic compounds found in influents. The only difference was that a part of biodegradable organic matter was degraded likely by heterotrophic bacteria and algae. It was also observed that BOD increased during rainy season, whereas COD value decreased. The latter was high during dry season.

Total solids and total suspended solids: most important stressor of the lake, relatively heavy solids loading up to 2700 mg L -1 has been measured in the lake, particularly at proximity of northeast inlets (Stations 3). The general trend is lower during very wet season (February and March) and higher during dry season. The nature of total solids (TS) shifted from higher part of volatile solids (assimilated as organic matter) during wet season to higher inorganic total solids during dry season.

Total suspended solids (TSS), likewise TS, are affecting heavily the lake status. TSS higher values could reach 182 mg L -1, particularly at stations at proximity of inlets. Similar trend was observed concerning TSS concentration in the lake water, i.e. being lower during wet season while higher during dry season. According to VSS/SS ratio indicating organic content of TSS, higher ratios were found during dry season.

Total dissolved solids: up to 2600 mg L -1 could be found in the lake water. The volatile part as total dissolved volatile solids decreased whenever total dissolved solids increased.

Alkalinity: in view of few alkalinity measurements one can conclude that the lake water has enough buffer capacity to mitigate the effect CO 2 production, main cause of pH decrease.

3.3.1.2.3. Biological conditions

The biological conditions of the lake may be characterized by three components: high concentration of chlorophyll a, presence of new invading specie of crayfish, and frequent invasion of floating macrovegetation.

The lake presented optimum conditions for algae growth, and that is reflected from chlorophyll a concentration. Maximum value could reach more than 400 mg m -3. Level of chlorophyll a was lower during wet and cloudy season, while higher during dry season.

On the other hand, fast growing and colonizing specie of crayfish ( Procambarus sp ) was observed in the littoral zone of the lake (north eastern part) as they are subjected to poor dwellers capture. That presence would surely change ecosystem balance in the near future.

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Invasive floating macrovegetation, Eichornia crassipes , constitutes one major problem for the lake that frequent removal to prevent invasion is carried out by “Service technique” every year. The only positive point of such invasion is that water hyacinth has capacity to remove COD, nutrients, and TSS from the invaded aquatic system.

3.3.1.2.4. Sediment characteristics

Due to lack of data and also to important volume of accumulated sediment in the lake, no accurate estimate of sediment volume is available. However, the results showed their potentiality as important storage and supply of nutrient to the lake water. Indeed, total nitrogen at the upper layer of sediment could reach 3 mg g -1, while soluble reactive phosphate (SRP) concentration might turn around 60 mg kg -1. Sediments are generally rich in Fe and Mn, important elements for SRP reintroduction to water column at favourable redox conditions. The texture of sediments ranges from silty sand to sand-silt-clay.

3.3.1.2.5. Trophic status and carrying capacity

According to TP, TN, chlorophyll a, and Secchi depth values the lake is classified as hypereutrophic lake. That status is confirmed by the Carlson’s trophic state index over monitoring period, which is above 70, indicating hypereutrophic status.

On the other hand, the results showed that there is not limiting factor in view of the TN/TP ratios of about 7. The carrying capacity evaluation rather led to suspecting light as limiting factor.

In view of the trophic status and the availability of nutrients, it seems that the trend as regards the fate of the lake is towards more sedimentation, which, if nothing is done, directly leads the lake back to the initial nature of the area, i.e. a swampy area.

So, the most important question to be resolved after characterising the lake concerns the ability to identify the major stressor of the lake that can most easily be made to limit the algal growth. In order to find out different alternative approaches modelling was being used, taking into consideration relevant processes.

Finally, the results of chemical and biological analyses showed similarity of the lake behaviour and a wastewater pond, in which pollutants loading is being slightly removed.

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CHAPTER 4 Modelling Lake Ranomafana management scenarios

As per primary objective model was developed in order to simulate and predict the likely behaviours of the lake according to difference pre-assumed conditions.

4.1. Simulation of the lake behaviour under current conditions

As previously stated in the subchapter reporting on the development of Lake Ranomafana model, the model developed for the management of the lake will focus on the dynamic of the following component of the lake ecosystem: dissolved oxygen (DO), soluble reactive phosphate (PO 4), dissolved organic matter (COD), algae (phytoplankton), autotrophic bacteria, heterotrophic bacteria, accumulation of sediment.

The simulation of lake behaviour without any external or internal intervention is being performed using data from monitoring campaign over 2009 and measured volume of the lake. This could be taken for calibrating the model. Indeed, the one way ANOVA test for most parameters did not show any significant difference between stations.

4.1.1. Growth of algae and oxygen production

The conditions of simulation of algae growth and oxygen production were based on the following data input: - Volume of reactor is 56300 m 3; -1 - Maximum growth rate of algae (µ maxAl ) is of 2 d ;

- Phosphorus content of biomass (f P) is of 0.02 g/g biomass;

- Nitrogen content of biomass (f N) is of 0.1 g/g biomass;

- Oxygen production (O 2) is of 1.5 g O 2/g biomass;

- Half saturation for ammonia (K N) is of 0.02;

- Half saturation for phosphorus (K P) is of 0.02;

- Initial condition of biomass (X Alg ) is of 10 mg/l: Also the nutrient inputs of the mixed reactor were assumed to come from northeast and northwest influents according to the following formulae: Equation (4.1) _ _ and Equation (4.2) Where,

- CNH4 is the concentration of ammonia (mg/l); -1 - CNH4_ine is the concentration of ammonia in northeast influents (mg l ); -1 - CNH4_inn is the concentration of ammonia in northwest influents (mg l )

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3 -1 - Qe_in is the northeast influents flow rate (m d ); 3 -1 - Qn_in is the northwest influents flow rate (m d ); -1 - CP is the concentration of soluble reactive phosphate (SRP) (mg l ); -1 - CP_ine is the concentration of SRP in northeast influents (mg l ) ; -1 - CP_inn is the concentration of SRP in northwest influent (mg l ); and -1 - PSO4_Sed is the concentration of SRP released from sediments ((g d ).

Figure 66 shows the result of the simulation of algae growth and the production of oxygen under current condition without any intervention from either external or internal loadings of nutrients. The striking point, regarding algae growth, that is important to underline according to the result of the simulation are following: - Without supply from sediment algae can grow normally although less than with SRP sediment supply; - Up to certain extent additional supply of SRP from sediment would bring about further growth, however too much supply from sediment wouldn’t have anymore effect on algae growth, but rather less growth than without supply from sediment; - Curves showing alga_3 and alga_4 seems actually to show that algae abundance is positively correlated with phosphorus concentration at moderate levels of nutrient loadings, but becomes increasingly less responsive at higher phosphorus concentrations (Wetzel, 2001); - Algae assimilate phosphorus at rate more rapid than used for growth, so, as a result cells accumulate phosphorus and steady-state growth is saturated by concentrations much lower than half saturation constant (Wetzel, 2001); - Due to storage mechanism that allow algae to store enough phosphate (luxury uptake) for 3-4 cell division, the amount of biomass that can grow in addition to the biomass present cannot be predicted from the concentration of dissolved phosphate (Chorus and Mur, 1999). With respect to oxygen production the following remark would prevail in the simulated conditions: - Higher growth rate (see curves alga_1 and alga_2) would produce oxygen but likely rapidly depleted by algae respiration but probably also by the oxidation of organic matter in the lake, and the aerobic growth of autotrophic and heterotrophic bacteria; - Higher growth of algae would consume more dissolved carbon dioxide and rise the pH, which becomes limiting to algal activities, and therefore reducing production of oxygen (case O2_1 and O2_2; - Lower growth rate would produce more oxygen available for the entire lake ecosystem;

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- Oxygen produced by algae may be sufficient to oxidise organic matter with the help of heterotrophic bacteria.

Figure 66: Simulation of algae growth and oxygen production under current conditions

4.1.2. Growth of autotrophic bacteria

The simulation for the growth of autotrophic bacteria was performed by using the same input as for algae growth, but, with the following different stoichiometric coefficients and initial conditions:

-1 - Autotrophic bacteria yield (Υ_ A) (0.2 mgCOD mg NH4);

- Concentration of nitrate (1/Υ_ A);

- Half saturation for oxygen for autotroph (K_ OA ) is of 0.5; -1 - X_ B_A: 10 mg l as initial condition. Figure 67 shows the result of the autotrophic bacteria growth simulation under assumed normal and current conditions. One can remark that under supply of nutrient from external loading, algae would have higher growth rate but less oxygen because of what has been previously explained. Consequently, autotrophic bacteria would hardly grow in such condition of very less oxygen, which as well indicates that autotrophic bacteria could only grow in aerobic condition.

On the other hand, autotrophic bacteria growth would still be limited under aerobic condition; this is probably caused by competition between algae and autotrophic bacteria for substrate as ammonia. So, less algae growth would produce better autotrophic bacteria, while higher algae growth rate would be unfavourable to autotrophic bacteria growth.

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Figure 67: Simulation of autotrophic bacteria growth under current conditions

4.1.3. Growth of heterotrophic bacteria

Similar conditions were used for simulating heterotrophic bacteria growth, with the following additional inputs and initial conditions:

-1 - Heterotrophic bacteria growth yield (Υ _H ) (0.66 mg COD mg COD); - COD at initial condition is of 80 mg l -1;

- Half saturation for oxygen for heterotrophy (K_ OH ) is of 0.1; -1 - Concentration of heterotrophic biomass (X_ BH ) is of 10 mg l . Figure 68 presents the result of the heterotrophic bacteria growth simulation under assumed current conditions. The following remark deserves to be noted according to the figure below: - Heterotrophic bacteria can grow under either aerobic or anaerobic conditions; - Curve X_B_H1 shows growth under very limited oxygen conditions, but heterotrophic bacteria were showing higher growth; - Curve X_B_H2 shows decrease of growth after rapid growth even with additional supply of phosphorus from sediment internal loading, with more or less oxygen; - Higher growth immediately followed by growth decrease was noted under well aerobic conditions (see curves X_B_H3 and X_B_H4), and even if there is growth, it is less than under limited oxygen; the reason might be limiting substrate as COD; - Heterotrophic bacteria growth is less dependent of oxygen compared to autotrophic bacteria

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Figure 68: Simulation of heterotrophic bacteria growth under current conditions

4.1.4. Dissolved organic matter as COD

Figure 69 displays the result of the simulation of COD use as soluble substrate for heterotrophic bacteria. One can remark the following points: - COD was not completely depleted under limited oxygen condition, but small quantity would still remain,; - COD was completely used or oxidized under aerobic condition (see COD_2, 3, and 4); - Oxygen demand for oxidizing COD was met by less algal growth, but with higher rate of oxygen production.

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Figure 69: Simulation of chemical oxygen demand (COD) under current conditions

4.1.5. Nutrients as PO 4, NH 4, and NO 3

Figure 70 show the result of the simulation of the above nutrients consumption by algae, bacteria either autotrophic or heterotrophic. Both algae and bacteria are consuming nutrients for growth and maintenance but the conditions of assimilation would determine the difference, but also the presence of sufficient or limited oxygen would play important role. According the below figure soluble phosphate (PO 4) is rapidly used, and under the current condition, even additional supply of PO 4 from sediments seems rapidly used as well.

So, at reduced quantity of PO 4 from supply from both external and internal loadings, phosphorus would surely become a limiting factor.

Besides, the components ammonia (NH 4) and nitrate (NO 3) are a bit different. According to the figure and widely confirmed from laboratory assays NH 4 is being preferred than NO 3. Ammonia is preferred whenever oxygen is present, while nitrate is taken up whenever oxygen is limited or even absent. So, would it be related to the role nitrate plays as electron acceptor under anoxic condition during denitrification? But on the other hand, curves NH 4_3 and NH 4_4 variations might be explain by the fact that NH 4 is also used by autotrophic bacteria for growth under aerobic condition.

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Figure 70: Simulation of nutrients (PO4 and NH4/NO3) consumption under current conditions

4.1.6. Accumulation of sediment and Particulate organic matter (slowly biodegradable COD)

Figure 71 shows the potential accumulation of sediments from non-biodegradable matter that is assumed to be a biologically inert organic matter (particulate), and herein expressed as X_i, but also the accumulation of biodegradable organic matter that is assumed to be slowly biodegradable particulate, and herein expressed as X_s.

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Under current conditions accumulation of particulate inert matter as sediment would be relatively high under aerobic condition (see curves X_i3 and X_i4) and relatively low under limited oxygen condition (see X_i1 and X_i2). By contrast, slow biodegradable particulate would be rapidly consumed under whatever condition, either aerobic or in a limited oxygen condition (see curves X_s1, X_s2, X_s3, X_s4). Only heterotrophic bacteria would perform this process under such conditions.

The importance of accumulation of biologically inert organic matter in addition to the accumulation of inorganic matter such as clay, sand, and silt, from the spa wastewater constitutes, over longer time, a very damaging stressor for the lake, particularly for its physical status. And that was highlighted by the results of the diagnostic for characterizing the lake trophic status.

Figure 71: Simulation of production and accumulation of inert and particulate organic matter under current conditions

4.1.7. Partial conclusion

The simulations under current condition by using AQUASIM platform have provided additional explanation about the result of the diagnostic phase leading to the characterization of the lake status. In this way, the development of the Lake Ranomafana model and simulation of the current condition by using data from field monitoring has confirmed key findings related to the lake trophic status. So, from the results of the different simulations of the relevant parameters of interest, input of nutrient from external loading would be already enough for algal bloom and growth since the concentration levels are well above the half saturation. Additional release from sediment would exacerbate the

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phenomenon up to certain extent due to probably light (self shading) and/or pH limiting factors leading to algae being less responsive to more supply of nutrients.

On the other hand, the result of simulation indicated that PO 4 would be less available compared to nitrogen compounds for algae and bacteria consumption. Therefore it could be the component that, under control, might prevent algal bloom.

The potential stress that accumulation of sediments represents for the lake status was also a key finding of the simulation. So, any actions towards the restoration of the lake shouldn’t disregard and overlook this sedimentation issue.

For the moment under current conditions organic matter could be degraded without any shortage of oxygen for such process.

Finally, last but not least, the model developed for the lake may be used to evaluate alternative management strategies for the restoration of the lake so as to recommend the appropriate actions.

4.1.8. Limitation of the model

As previously stated in the subchapter treating “development of Lake Ranomafana model”, a model is a simple representation is a simple representation of a complex phenomenon. It is an abstraction, and therefore does not contain all features of the real system. However, a model does comprise all the characteristics ones, those essential to the problem to be solved or described. The model for the lake has been developed for describing and reflecting the reality but these are not the true reality. Indeed, for example the algal biomass growth, certain factor that determines algal biomass growth in reality were not included such as light, temperature, and even pH in addition to zooplankton grazing. So, the model is limited by such factor that simply has not been taken into consideration, but also by certain, probably important, features that might improve the accuracy of the model, while making it more complex and difficult to handle.

It is very difficult also to calibrate the model for all state variables in view of the available data that some are specific for the each station and the season of sampling, but effort has been made to run the model with available data from monitoring as much as possible.

4.2. Simulation with external loading treatment by reducing 50% of pollutants loading

In light of the pollutants removal capacity of nowadays available wastewater treatment technology (physical, chemical, and biological), particularly the different biological treatment capable of reducing nitrogen, phosphorus, and organic matter loads simultaneously, the simulation with external loading treatment was performed by assuming that inputs of NH 4,

PO 4, and COD would be reduced to 50% from current conditions.

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4.2.1. Growth of algae and oxygen production

Figure 72 shows the result of simulating 50% reduction of nutrients and dissolved organic matter as COD on algae growth and production of oxygen from photosynthesis. The following remark can be done: - More pronounced decrease of growth is obtained with 50% reduction, without any supply of phosphorus from sediments internal loading, and therefore no visible production of oxygen; - Reduced growth of algae would also happen when external loading (50%) is supported by internal loading from sediment, but still production of oxygen is not enough but just visible; - Sediments internal loading of phosphorus would play important role in supporting algae growth in case of 50% reduction of external loading; - Higher organisms such as fish would not grow in such condition.

Figure 72: Simulation of algae growth and oxygen production under reduction of 50% of external pollutants

4.2.2. Growth of autotrophic bacteria

Figure 73 presents the result of the autotrophic bacteria growth simulation under condition of 50% reduction of external loading. There is no doubt that autotrophic bacteria would not grow in such condition of practically anaerobic condition although sediment internal loading would supply additional phosphorus.

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Figure 73: Simulation of autotrophic bacteria growth under 50% reduction of external loading

4.2.3. Growth of heterotrophic bacteria

Figure 74 displays the result of heterotrophic bacteria growth simulation under 50% reduction of external loading. The below figure is just the opposite of what is displayed on Figure 68. And the following comments could be done: - Growth decreases with no additional supply of phosphorus from internal loading and no oxygen; - More or less similar growth could happen with additional supply of phosphorus but no oxygen; - Growth is reduced compared to normal condition, but still heterotrophic bacteria would grow and show no dependency to oxygen for their growth although relatively reduced.

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Figure 74: simulation of heterotrophic bacteria growth under 50% reduction of external loading

4.2.4. Dissolved organic matter as COD

Figure 75 presents the result of the COD simulation under 50% reduction of external loading. The fate of COD is more or less similar to that of normal and current condition, that is, no further reduction of COD up to zero would be possible. Would this remaining represent the slowly biodegradable fraction or inert fraction?

Figure 75: Simulation of the fate of dissolved organic matter as COD under 50% reduction of external loading

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4.2.5. Nutrients as PO 4, NH 4, and NO3

Figure 76 shows the result of the simulation of nutrients availability under 50% reduction of external loading. As far as phosphorus is concerned it would be completely consumed with or without any additional supply from sediment internal loading. By contrast, ammonia would still be available even at reduced concentration levels, whereas nitrate is also fully consumed.

Figure 76: Simulation of nutrients availability under 50% reduction of external loading

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4.2.6. Accumulation of sediments and slowly biodegradable organic matter

Figure 77 presents the result of the simulation of the accumulation of inert organic matter as sediments and slowly biodegradable organic matter. According to the figure below the accumulation of inert matter as sediment would be dramatically reduced, whereas the accumulation of slow biodegradable organic matter, although would decrease, before stabilising at appreciable level.

Figure 77: Simulation of the accumulation of sediments and slow biodegradable organic matter under 50% reduction of external loading

4.3. Simulation with external loading treatment by reducing 50% of phosphorus loading

Due to not only its diverse sources (point or diffuse source), but also to the capacity of certain planktonic algae (cyanobacteria) to fix atmospheric nitrogen for growth, many lake restoration experiences reported on the difficulty to control nitrogen supply to lakes. So, control and reduction of nutrients loading usually focuses on phosphorus, but measures addressing phosphorus may be designed to reduce nitrogen input simultaneously (Chorus and Mur, 1999). For the sake of addressing controllable component entering to Lake Ranomafana, the following simulations were focused on reducing phosphorus external loading by 50%.

4.3.1. Nitrogen compounds After running the model, the following comments should be made: - The algae growth decrease and oxygen production pattern is practically similar to

that of simulating 50% reduction of NH 4, PO 4, and COD (see Figure 72);

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- Autotrophic bacteria, likewise under 50% reduction, would have no growth pattern probably due to very limited oxygen condition (see Figure 73); - Phosphorus, as under 50% reduction, would be rapidly depleted in spite any supply from sediment internal loading (see Figure 76); - By contrast, ammonia would be even more available than under 50% reduction condition (Figure 78), while nitrate is rapidly consumed;

Figure 78: Simulation of inorganic nitrogen availability under 50% reduction of phosphorus external loading

4.3.2. Dissolved organic matter as COD The result of simulating heterotrophic bacteria growth shows similar growth variation pattern as that under 50% reduction (see Figure 74). However, the simulation of COD under 50% reduction of phosphorus external loading shows slightly different pattern compared to previous simulation scenario (see Figure 75) , with 50% reduction of NH 4, PO 4, and COD. In fact, COD would be slowly degraded compared to previous simulation scenario. Figure 79 presents the result of simulation of COD.

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Figure 79: Simulation of the fate of dissolved organic matter as COD under 50% reduction of phosphorus external loading

4.3.3. Accumulation of inert organic matter as sediment and slow biodegradable organic matter With respect to accumulation of inert organic matter as sediment and slow biodegradable organic matter the accumulation of slow biodegradable organic matter would be slightly higher compared to the result of previous simulation, while decrease of accumulation of inert matter would remains similar. Figure 80 shows the result of the simulation of the accumulation of inert matter as sediment and slow biodegradable organic matter.

Figure 80: Simulation of the accumulation of inert matter as sediment and slow biodegradable organic matter under 50% reduction of external phosphorus loading

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4.4. Simulation with external loading treatment by reducing 50% of dissolved organic loading (COD)

The control of organic matter related to lakes management is not widely practiced as in such case prevention at source rather than end of pipe treatment is much more recommended.

4.4.1. Algae growth and oxygen production

As far as Lake Ranomafana is concerned removal of external loading as COD would present no big achievement for restoring the lake status, but rather nutrients would remain available for algae growth to stabilise, while production of oxygen would be higher than under current condition. However, as under current condition, no sufficient production of oxygen would be possible without any supply of nutrients from sediment internal loading. Figure 81 shows the algae growth and oxygen production result of simulation under 50% reduction of organic matter as COD condition.

Figure 81: Simulation of algae growth and oxygen production under 50% reduction COD external loading

4.4.2. Growth of autotrophic bacteria Figure 82 shows the autotrophic bacteria growth result of simulation. In such condition of limited dissolved organic from external supply autotrophic bacteria would produce very limited growth quite similar to that of current condition (see Figure 67). It is likely probable that the same condition of oxygen production would be the main factor, which determines the growth pattern of autotrophic bacteria under 50% reduction of external COD.

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Figure 82: Simulation of autotrophic bacteria growth under 50% reduction of dissolved organic matter (COD)

4.4.3. Growth of heterotrophic bacteria

Figure 83 presents the result of simulating heterotrophic bacteria growth, with limited dissolved organic substrate. Under such condition heterotrophic bacteria would have an interrupted growth followed by a rapid decrease before the growth being stabilised at different levels likely influenced by nutrients availability. Despite available and increasing supply of phosphorus from sediment internal loading heterotrophic bacteria would decrease even more than without any additional supply.

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Figure 83: Simulation of heterotrophic bacteria growth under 50% reduction of external dissolved organic loading

4.4.4. Dissolved organic matter as COD

Figure 84 displays the result of the COD simulation after reducing loading from external source. Already less under current condition, reduction of COD by 50% would obviously lead to complete and rapid depletion of all COD entering to the lake. And that would happen under full nutrients supply from external and internal loadings.

Figure 84: Simulation of dissolved organic degradation under 50% reduction of COD external loading

4.4.5. Nutrients

No management of nutrient supply was assumed in this simulation with 50% reduction of COD. Figure 85 shows the result of such simulation. Available phosphorus from external loading in addition to sediments internal loading would be rapidly and completely consumed. By contrast, nitrogen compounds would be differently consumed. In this way, ammonia would be much preferred and effectively consumed. However, under no sediment internal supply of phosphorus condition, availability of ammonia would decrease up to certain level of concentration. Nitrate seems left aside and to have its concentrations increasing before stabilization. The availability of oxygen is likely influencing the nitrate consumption.

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Figure 85: Simulation of nutrients under 50% reduction of dissolved organic matter external loading

4.4.6. Accumulation of inert organic matter and slow biodegradable organic matter

Figure 86 presents the result of the accumulation of inert and slow biodegradable organic matter under 50% COD reduction. Inert organic matter assumed to become sediment would accumulate, particularly when internal supply of phosphorus is available. By contrast, slow biodegradable organic matter would be rapidly and completely degraded either with or without internal phosphorus addition supply.

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Figure 86: Simulation of the accumulation of inert and slow biodegradable organic matter under 50% COD reduction

4.4.7. Available applied wastewater treatment methods

The results of different simulation scenarios highlight the generated issues related to nutrient enrichment of the lake, either from external or internal loading. But the suspended solids loading also should not be disregarded. So, the main question that needs answer is the following: - How to solve the problems associated with influents loading? A review of different methods to solve the problem is presented in Table 37. However, in light of the actual social and economical situation of the country and at the municipality level, particularly regarding the question related to cost (affordable) and financial sustainability, “soft” technological and most cost-moderate methods, which are directly applicable to developing countries (UNEP, 2002), will be underlined.

Table 37: Generally applied wastewater treatment methods (UNEP, 2002) Efficiency Cost Method Pollution Problem (maximum 1.0) ($100m 3) Mechanical Suspended matter 0.75 – 0.90 3 - 8 treatment BOD 5 reduction 0.20 - 0.35

Biological treatment BOD 5 reduction 0.70 – 0.95 25 – 40 Phosphorus removal 0.30 - 0.60 Flocculation 6 – 9 BOD 5 reduction 0.40 - 0.60 Chemical Phosphorus removal 0.65 - 0.95 10 - 18 precipitation Al 2(SO 4) Reduction of heavy metals 0.40 - 0.80

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or FeCl 3 concentrations 0.50 - 0.65

BOD 5 reduction Phosphorus removal 0.85 - 0.95 Chemical Reduction of heavy metal 0.80 - 0.95 12 - 18 precipitation Ca(OH) 2 concentrations 0.50 – 0.65

BOD 5 reduction Chemical Phosphorus removal 0.90 - 0.98 precipitation and BOD 5 reduction 0.60 - 0.75 12 - 18 flocculation Ammonia stripping Ammonia removal 0.70 - 0.95 25 – 40 Nitrification Ammonium → nitrate 0.80 – 0.95 20 – 30 Active carbon COD (toxic substances) 0.40 – 0.95 60 – 90 adsorption BOD 5 reduction 0.40 – 0.70 Denitrification Nitrogen removal 0.70 – 0.90 15 – 25

BOD 5 reduction (proteins, e.g.) 0.20 – 0.40 40 – 60 Phosphorus removal 0.80 – 0.95 70 – 100 Ion exchange Nitrogen removal 0.80 – 0.95 45 – 60 Heavy metals 0.80 – 0.95 10 -25 Chemical oxidation Oxidation of toxic compounds 0.90 – 0.98 60 – 100 (e.g., with Cl 2) Heavy metals and other toxic 0.50 – 0.95 Extraction 80 – 120 compounds Removes pollutants with high Reverse 0smosis 100 – 200 efficiency, but is very expensive Microorganisms High, cannot be Disinfection methods 6 -30 indicated Microorganisms High Waste stabilization Reduction BOD 70 – 85% 2 – 8 pond 5 Nitrogen removal 50 – 70%

Reduction of BOD 5 20 – 50% Constructed wetland Nitrogen removal 70 – 90% 5 – 15 Phosphorus removal 0 - 80% Extracted from Planning and Management of Lakes and Reservoirs: An integrated Approach to Eutrophication

From point of view efficiency the listed methods are often used in combinations of two or more steps to obtain the overall removal efficiency required by the most cost-moderate solution (UNEP, 2002). In order to provide more detailed information about each type of treatment efficiency Table 38 presents matrix relating pollution parameters and wastewater treatment methods.

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Table 38: Efficiency ratio (0.0 - 1.0) matrix relating pollution parameters and wastewater treatment methods (after Jansen and Jørgensen, 1988) (UNEP, 2002) + Susp. BOD 5 COD P- NH 4 N- Heavy E. Colour Turbid- matter total total metals coli ty Mechanical 0.75 – 0.20 - 0.20 - 0.05 - 0.10 - 0.80 - ~0 0.20 - 0.25 treatment 0.90 0.35 0.35 0.10 0.40 0.98 Biological 0.75 - 0.65 - 0.10 - 0.05 - 0.10 - 0.30 - ~0 Fair ~0 - Treatment 0.95 0.90 0.20 0.10 0.25 0.65 Chemical 0.80- 0.50- 0.50- 0.80- 0.10- 0.80- 0.30- 0.80- precipita- ~0 Good 0.95 0.75 0.75 0.95 0.60 0.98 0.70 0.98 tion Ammonia 0.70 - 0.60 - ~0 ~0 ~0 ~0 ~0 ~0 ~0 ~0 stripping 0.96 0.90 0.80 - 0.80 - Nitrification ~0 ~0 ~0 ~0 ~0 Fair ~0 ¨0 0.95 0.95 Active 0.40- 0.40- 0.10- 0.70- 0.60- carbon - ~0.1 High* High* Good 0.70 0.95 0.70 0.90 0.90 adsorption Denitrifica - 0.70- tion after ~0 - - ~0 - ~0 Good ~0 - 0.90 Nitrification Ion 0.20 - 0.20 - 0.80 - 0.80 - 0.80 - 0.80 - Very 0.60 - 0.70 - - exchange 0.50 0.95 0.95 0.95 0.95 0.95 good 0.90 0.90 Chemical Corresp. 0.60- 0.50- oxidation - to ~0 ~0 ~0 ~0 ~0 ~0 0.90 0.80 oxidation Corresp. extraction 0.50- Extraction - of toxic ~0 ~0 ~0 ~0 ~0 ~0 ~0 0.95 compounds Desinfec - Correspond to application of chlorine , Very 0.50- 0.30- Tion ozone, etc. High 0.90 0.60 methods See Reverse Tab. Osmosis 37 Extracted from Planning and Management of Lakes and Reservoirs: An integrated Approach to Eutrophication

4.4.7.1. Waste stabilisation ponds (WSPs)

Traditionally, waste stabilisation ponds (WSPs) are built as a flow-through systems with an anaerobic, a facultative, and one or more maturation ponds (UNEP, 2002). According to Senzia et al. (2002) waste stabilisation ponds remain the most suitable and appropriate wastewater treatment technique because the capital, operation, and maintenance costs are

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generally low compared to conventional treatment techniques. Furthermore, operation is simple and manageable with low skilled personnel and the climatic factors are also favourable for biological reaction. The WSPs does not require mechanical mixing, needing only sunlight to supply most of its oxygenation. Their main constraint is land requirements (Kayombo et al., 2005).

The following processes are utilized in the pond system: settling and anaerobic decomposition of organic matter (mainly in the first ponds), aerobic decomposition of organic matter (mainly in the last ponds, where algae are present and produce oxygen), uptake of phosphorus and nitrogen by algae (facultative and maturation ponds), evaporation of ammonia (mainly where pH is high, i.e., in the last ponds), settling of algae, denitrification (in the anaerobic zones) (UNEP, 2002).

The same report stated that high removal efficiencies of BOD 5, COD, microorganisms, nitrogen, and phosphorus may be obtained provided that the guidelines for design and maintenance are followed. Removal of phosphorus is between 20 -50% depending on algae removal before effluent discharge. Certain specialists recommend the combination with constructed wetland after waste stabilisation ponds for very high efficiency. One major problem associated with WSPs is the sludge removal. The performance of the system might be jeopardised by accumulated sludge volume. This latter may cause an undesired internal loading.

Constructed wetland also seems a more attractive wastewater treatment for developing countries, particularly for those having sufficient areas for building such system.

4.4.7.2. Constructed wetland

Constructed wetland (CWs) are planned systems designed and constructed to employ wetland vegetation to assist in treating wastewater in a more controlled environment than occurs in natural wetland (Kayombo et al., 2005). Constructed wetland, likewise wastewater stabilization ponds, is known as alternative technology compared to conventional technology. They are also called “ecotechnology”. The pollutants removed by CWs include organic materials, suspended solids, nutrients, pathogens, heavy metals and other toxic or hazardous pollutants. CWs, for more efficiency, may be used in combination with other type of treatment as alternative to secondary and tertiary treatment, and can treat both municipal and industrial wastewater. It is noteworthy that CWs should not be used to treat raw sewage and, in industrial situations, the wastes may need to be pre-treated so that the biological elements of the wetlands can function effectively with the effluent (Kayombo et al., 2005).

CWs for wastewater treatment can be categorized as either Free Water Surface (FWS) or Subsurface Flow (SSF) systems (Kayombo, 2005). The main difference between these two

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systems is related to the flow of water. In FWS systems, the flow of water is above the ground, and plants are rooted in the sediment layer at the base of water column compared to water flowing through a porous media such as gravels or aggregates, in which plants are rooted (Kayombo et al., 2005). Figures 87 and 88 illustrate the two main types of constructed wetland.

Figure 87: emergent macrophyte treatment system with horizontal sub-surface flow (Kayombo et al. (2005) citing Brix, 1993)

Figure 88: emergent macrophyte treatment system with surface flow (Kayombo et al. (2005) citing Brix, 1993)

Table 39 shows the type of wetlands, vegetation type and water column in constructed wetlands.

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Table 39: Vegetation type and water column contact in constructed wetlands (Kayombo et al., 2005) Constructed wetland type Type of vegetation Section in contact with water column Free water surface (FWS) Emergent Stem, limited leaf contact Root zone. some Floating stem/tubers Photosynthetic part, possibly Submerged root zone Sub-surface flow (SSF) Emergent Rhizome and root zone Extracted from Waste stabilization ponds and Constructed wetlands design manual

In light of the above treatment possibilities the following question should be taken into consideration when selecting one or combined methods: - Which removal efficiencies are feasible from an economic point of view? and, - Which efficiencies are needed to obtain the desired effect in the ecosystem? While the former question is very important from financial sustainability point of view, the latter question is usually what modelling is developed for. Since internal loading was found out as significant stressor it is important to simulate its management.

4.5. Simulation of in-lake treatment

As previously reported sediment internal loading of phosphorus constitutes a significant supply for algae growth, and therefore is an additional stressor for the trophic status of the lake. In order to find out possible scenarios of restoration of Lake Ranomafana reduction of phosphorus internal loading from sediments was performed, while maintaining external loading unchanged.

4.5.1. Algae growth and production of oxygen

Figure 89 shows the result of simulating algae growth and production of oxygen under condition of sediment internal loading reduction by 50 to 100% phosphorus. There would be decrease of algae under condition of no supply from sediment internal loading. However, the concentration level, even decreasing, would stabilize a bit above the initial condition. The same pattern would happen for the different reduced supply cases. On the other hand, the production of oxygen would be very limited and would happen only with reduced internal loading.

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Figure 89: Simulation of algae growth and production of oxygen under no and reduced sediments internal loading

4.5.2. Growth of heterotrophic bacteria

Obviously, there would be no autotrophic bacteria growth in the absence or under very limited oxygen condition. So, in that case nitrification process by autotrophic bacteria could not take place. By contrast, heterotrophic bacteria, as less dependent to oxygen, would grow even without any sediment internal loading. In case of reduced supply of sediment internal loading heterotrophic bacteria would grow, but rapidly followed by growth decreasing before stabilisation of the concentration level still above the initial condition. Figure 90 illustrates the results of heterotrophic bacteria growth under no and reduced supply of sediment internal loading.

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Figure 90: Simulation of heterotrophic bacteria growth under no and reduced sediments internal loading

4.5.3. Dissolved organic matter as COD

Dissolved organic matter under no and reduced sediment internal loading would continue to be degraded. The degradation would not be complete under no supply of sediment internal loading, whereas degradation would be complete under reduced supply of phosphorus from internal loading. Figure 91 shows the result of simulating COD.

Figure 91: Simulation of organic matter as COD degradation under no and reduced internal loading

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4.5.4. Nutrients

Phosphorus would be completely consumed either under no internal supply or reduced internal supply. By contrast, nitrogen compounds would have different fate. As illustrated in Figure 92 nitrate would be completely consumed under no internal supply, while the concentration levels would increase under reduced internal supply of phosphorus. On the other hand, ammonia, due to limited or absence of nitrification process, would tend to accumulate, particularly under no internal supply of phosphorus.

Figure 92: Simulation of nutrients availability under no and reduced internal supply of phosphorus

4.5.5. Accumulation of inert organic matter as sediment and slow biodegradable organic matter

Inert organic matter assumed to be sediment would less accumulate under no internal supply of phosphorus, whereas accumulation would increase in case of reduced supply from sediment internal loading. By contrast, slow biodegradable organic matter would accumulate but rapidly degraded, particularly with reduced internal supply. The degradation would not be complete under condition of no internal supply of phosphorus from sediments, that is, degradation of slow biodegradable organic matter would probably be slow. Figure 93 shows the result of the simulation of sediments and slow biodegradable organic matter accumulation.

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Figure 93: Simulation of accumulation of inert organic matter and slow biodegradable organic matter under no and reduced internal loading

4.5.6. Internal measures for nutrient and algal control

Sediment has a profound role in the eutrophication of lakes (UNEP, 2002). Internal measures for nutrient reduction, likewise external measure for loading reduction, are amongst lake management restoration techniques. Sometimes, substantial positive change of the trophic status might be difficult to achieve because of significant supply from sediment internal loading. Therefore, in order to obtain more visible positive change certain appropriate measures ought to be carried out within the lake itself, and those measure must imperatively be accompanied by the elimination or at least the reduction to minimum of external input of nutrients and other pollutants. Otherwise any effort to restoring the lake would be waste of money and time as the positive change will be short-lived and limited in time. Sediments with high concentrations of available phosphorus or toxic elements and compounds usually consist of fine-grained silt- and clay-size particles enriched in organic matter (UNEP, 2002). There are two main approaches to sediments remediation: in situ methods and removal of the sediment from the bottom of the lake. Table 40 is summarizing the different techniques usually applied in sediment management:

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Table 40: Available techniques used for sediments remediation Methods Principle Appreciation and comments Pumping and releasing air or Could be very effective for a mixture of air and oxygen small area of treated at sediment-water interface sediment. Pure oxygen or to eliminate anoxia in the oxidizing agent are less Aeration bottom water; pure oxygen efficient due to loss of or strong oxidizing agents gaseous oxygen and partial (permanganates or sterilization of the sediment peroxides) are sometimes surface used Precipitation of phosphorus Success as unsuccessful cases by using flocculants: have been experienced but aluminium sulphate, ferric lasting success requires low salts (chlorides, sulphates), external loading. Certain In-lake phosphorus ferric aluminium sulphate, chemical are difficult to precipitation clay particles and lime (as handle as very acid (ferric

Ca(OH) 2 and as CaCO 3) salt). Some chemical would be locally expensive and hardly available Deposition of a top layer of Rarely used as placing non-polluted (i.e., clean) uniform cover is very sediment (30 – 40 cm thick) difficult; the cap should Capping over the polluted sediment consist of a material slightly coarser to prevent mixing or disruption of cover by wind, wave or current action Could be costly if for wide area. Effective if carried out up to sediment layer with a lower or less mobile phosphorus content. Phosphorus-rich interstitial Removal of polluted Sediment dredging water should be handled in sediment such manner to prevent further pollution of the water column. Safe disposal of dredge sludge to prevent them from becoming source of external loading. Reduction by flushing Flushing with water of low May accelerate recovery

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phosphorus concentration from internal loading by removing in-lake phosphorus. Needs sufficient water Manipulation of parts of the Can be helpful to diminish food web (Examples removal algal growth. Chance of of planktivorous and success may be relative, and benthivorous fish population, intervention may need to be Biomanipulation to enhance zooplankton, repetitive introducing submerged aquatic plants to compete with phytoplankton for nutrients)) It is possible to accelerate accumulation of the Sediment is left alone sediment on the bottom of provided that reduction of Do nothing the lake by the addition of external input has been sediment of the correct grain accomplished size to the external discharge going into the lake

4.6. Simulation of combined reduction of external and internal loadings

The last case of simulation combines the treatment of effluents from external loading and reduction of sediment internal loading. It is obvious that the result of the different simulations of relevant variables would not provide different patterns from the previous simulation with reduced inputs but likely the difference would lie on the effect of the combine intervention being more pronounced than lonely practiced.

4.6.1. Growth of algae and production of oxygen

The combine reduction would rapidly decrease the growth up to half the initial condition before stabilizing. The growth decrease generated by reduced external loading along with no internal supply would be more pronounced than with reduced both external and internal supply. Obviously, there would not be enough production of oxygen and therefore no possible growth of autotrophic bacteria.

Figure 94 shows the result of algae growth and production of oxygen simulation.

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Figure 94: Simulation of algae growth and oxygen production under combine external and internal loading reduction

4.6.2. Growth of heterotrophic bacteria

Heterotrophic bacteria would be less affected by the reduction of external and internal loadings. The growth would rather stabilize above the initial condition. The different conditions of simulation would produce less effect to heterotrophic bacteria. Figure 95 illustrates the result of simulating heterotrophic bacteria growth under combine reduction of external and internal loadings.

Figure 95: Simulation of heterotrophic bacteria growth under combine reduction of external and internal loadings

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4.6.3. Dissolved organic matter

The degradation of dissolved organic matter would not be complete for the combine reduction of loading. That would likely mean that degradation would proceed slowly. Figure 96 presents the result of simulating COD degradation under combine reduction of loading.

Figure 96: Simulation of dissolved organic matter degradation under combine reduction of external and internal loadings

4.6.4. Nutrients

Since no growth of autotrophic bacteria would be possible, it seems normal that ammonia would tend to accumulate and stabilize. By contrast, nitrate probably playing the role of electron acceptor would be completely consumed. Figure 97 shows the result of nutrients as nitrogen compounds simulation. Phosphorus would be as well complexly consumed.

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Figure 97: Simulation of nitrogen compounds availability under combine reduction of external and internal loadings

4.6.5. Accumulation of inert organic matter and slow biodegradable organic matter

There would be no or very limited accumulation of inert organic matter but rather accumulation of slowly biodegradable organic matter under combine reduction of loading. Slow biodegradation process of biodegradable organic matter would be probably the cause of such accumulation. Figure 98 shows the result of simulating the accumulation of inert and slow biodegradable organic matter.

Figure 98: Simulation of inert and slow biodegradable organic matter accumulation under combine reduction of external and internal loadings

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4.6.6. Partial conclusion presenting the different alternatives

The development, testing, and application of Lake Ranomafana model have been introduced and presented in the present document. This lake model, although simplified and probably very incomplete (e.g. light, temperature, and pH were not taken into consideration), has been used and has helped testing the different management scenarios, assumed to be site specific, to restoring the lake. These simulations were performed in order to satisfy the primary objective of this study, but particularly the desired output of the primary objectives: a generic computer model capable of predicting Lake Ranomafana behaviour according to different scenario alternatives, and restoration alternative approaches capable of reversing the ongoing visible eutrophication.

To find out the key components that could affect positively and effectively the trophic status of the lake, different scenarios ranging from reduction of external loading through simulated treatment of the influents to reduction of sediment internal loading were tested. The variable subject to concentration level reduction was PO 4, NH 4, and COD from the inputs.

4.6.6.1. Reduction of external loading by 50% reduction of PO 4, NH 4, and COD simultaneously

The results of simulating influents treatment leading to reduction of external loading by 50%

PO 4, NH 4, and COD, suggest that: - Pronounced decrease of algal growth and therefore of algal biomass occurs provided that sediments do not release back any phosphorus for growth uptake, whereas slight decrease of algal biomass does occur when sediments internal loading continues to supply algal growth; - Autotrophic bacteria growth is very limited due to very limited production of oxygen. Therefore, nitrification process is going to be limited and that ammonia tends to accumulate; - Heterotrophic bacteria, being less dependent to oxygen, grows, with then increase of biomass, but solely with sediments internal loading. Otherwise, biomass decreases but still above the initial condition; - COD is being reduced, but not completely as probably very low concentration of slow biodegradable organic matter remains; - Phosphorus is completely consumed with or without any sediments internal loading, whereas ammonia tends to accumulate, with the highest reached level of concentration under no internal loading supply. By contrast, nitrate in consumed; - Inert organic matter tends to be reduced, while slow biodegradable organic matter remains present either with or without any internal loading.

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4.6.6.2. Reduction of phosphorus as phosphate by 50%

By reducing phosphorus concentration level from external loading by 50%, similar effects, as under simultaneous reduction, are produced on algal biomass, autotrophic and heterotrophic bacteria biomass, that is, algal biomass decreases, autotrophic bacteria growth do not take place due to limited oxygen, whereas heterotrophic bacteria biomass decreases solely without any supply from internal loading and increases with different levels of internal loading supply; the results of the simulation also suggest that: - Phosphorus is completely consumed, while ammonia tends to accumulate, with or without any internal loading supply; - Dissolved organic matter as COD is degraded but not completely, with low level of residue remaining to be degraded; - There is no accumulation of inert organic matter as sediment, but rather tendency to slow biodegradable organic matter accumulating.

4.6.6.3. Reduction of COD external loading by 50%

If solely dissolved organic matter as COD is being reduced, then the following is expected to happen: - Algal biomass increases, but rapidly followed decrease up to initial condition. Meanwhile, production of oxygen increases, particularly with internal loading supply; - Autotrophic bacteria biomass is very limited with more supply from internal loading; - Biomass of heterotrophic bacteria decreases but still remains above initial condition; - Dissolved organic matter as COD is completely degraded as phosphorus is completely consumed; - Level of ammonia decreases, while nitrate tends to accumulate; - Inert organic matter accumulates, whereas slow biodegradable organic matter is consumed.

4.6.6.4. In-lake treatment by reduction of internal loading

The results of simulating reduction of internal loading suggest that: - Algal biomass decreases and production of oxygen is quite limited; - Autotrophic bacteria growth does not take place, whereas heterotrophic bacteria biomass increases without any supply from internal loading and rapidly decreases with reduced internal loading;

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- Dissolved organic matter (COD) is completely degraded solely with reduced supply from internal loading, while residue still remains without internal loading supply; - Phosphorus is completely consumed, whereas ammonia might accumulate, particularly without internal loading, and decreases, with reduced supply from internal loading; - Inert organic matter less accumulates, without internal supply of phosphorus, whereas rapid accumulation is taking place with reduced internal loading. By contrast, accumulation of slow biodegradable organic matter does not take place;

4.6.6.5. Combine reduction of external and internal loadings

The combine reduction of both external and internal loadings requires intervention at external level and within the lake. The results of simulations suggest that: - Algal biomass rapidly decreases as to stabilize at initial condition level, but the production of oxygen is being limited; - Biomass of heterotrophic bacteria increases and stabilizes, whereas autotrophic bacteria is practically very limited; - Dissolved organic matter as COD is not completely degraded; - Ammonia tends to accumulate and stabilize, whereas nitrate is completely consumed; - Inert organic matter as sediment is very limited to minimum, whereas slow biodegradable organic matter rather tends to accumulate and stabilize.

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CHAPTER 5 Cost-benefit analysis of Lake Ranomafana remediation

The cost-benefit analysis is a tool that usually economists use for addressing environmental related questions. Therefore, cost-benefit analysis might be a useful tool for the Lake Ranomafana main stake holder in charge of managing the lake, and herein assumed to be the municipality of Antsirabe, for assessing the economic effects of any remediation project with respect to the lake. In other word, cost-benefit analysis entails comparing all possible benefits and costs of a given policy or management objective (UNEP, 2002). The purpose of such analysis is just to provide a kind filter to eliminate project proposals that might be deleterious to the social and economical development of local population.

5.1. Remediation of the Lake Ranomafana

As far as Lake Ranomafana is concerned the main question that should be addressed is: should the water quality or the trophic status of Lake Ranomafana be improved and to what extent?”. To address such a question the team from the municipality of Antsirabe should think of using such a helpful tool as cost-benefit analysis since it provides important information into the decision making process. The analysis can be used at different level, municipal, region, province if needed.

The principle is based on comparison of the benefit of implementing any remediation project against the cost of implementing such project. While the estimation of costs seems relatively simple, estimating benefits could be somehow tricky, particularly for certain aspect that cannot be given any value. In general the costs are more or less monetary expenditure related to material, labour, treatment plant, operating cost, dredging costs, and monitoring and evaluation costs, whereas the benefit for having improved the aesthetic of the site is relatively difficult to estimate as there is no price that could be associated with that. On the other hand, the environmental costs should not be overlooked, such as reducing eutrophication may reduce yield of Tilapia for poor dwellers used to catch fish in the lake. Biodiversity is also difficult to estimate, but the lake is less concerned about loss, while rather would benefit from introducing variety of biodiversity in the clean lake. So, for valuable costs or benefits there are market-based method to estimate their values, whereas aspect such environmental quality might be estimated from hypothetical market, i.e. how much people are willing to pay for the good represented by environmental quality.

Some of the economic effects of the lake eutrophication and the type of benefit derived from reducing eutrophication are presented in Table 41.

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Table 41: Economic effects of eutrophication and benefits of reducing eutrophication (adapted from UNEP, 2002) Benefits of reducing How benefits can be Effect of eutrophication eutrophication measured Loss of water depth, surface • Reduced need for • Avoided costs for area, and storage capacity alternative irrigation dredging and substitute water; water for irrigation; • Values of shoreline • Avoided losses in property property preserved; values; • Continued viability of • Value of fish catches, fishery; which would not have • Continued viability of taken place; recreation; • Recreational expenditures which would have been lost; • Public willingness to pay for existence of the lake, apart from use values Increased possibility of toxins • Increased commercial • Increased value and in water fishing; number of fish caught; • More diverse biota; • Public willingness to pay • Increased water contact for improved ecosystem; • Increased expenditures on recreation; Increased odour problems in • Lower costs of treating • Treatment cost saving; water uses (irrigation) water; • Increased use of water • Walkers happier; (difference between using water and using substitute one9 Frequent invasion of water • Enhance aesthetic of the • Water hyacinth removal hyacinth side without water cost saving; hyacinth; Reduced visual and tactile • Happier nearby residents; • Increased value of quality of water body • Increased development property; around water body; • Increased development of • Increased recreation; land; • More diverse biota • Increased expenditure on recreation; • Prices for different species caught; • Public willingness to pay

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for improved ecosystem; Increased risk for public • Reduced risk for public • Expenditure for treating health health (diarrhoea, water related diseases; parasite and worm) Loss of tourism value • Increased attraction for • Price of any tickets for the site by tourists entry; • Public willingness to pay for improved site.

It is worthwhile noting that in performing cost-analysis exercise all stake holders’ interest should be taken into consideration so as to make the project more sustainable.

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CHAPTER 6 Synthesis of modelling results

Lake Ranomafana study was based on diagnosing the main problems leading to its current trophic status. In this way, diagnostic commenced from evaluating external loading, identifying the main components, their nature, the main stressors for the lake, and their potential sources. Then diagnostic continued within the lake at different compartment: water column and sediment. Chemical and biological tests were used to quantify and qualify the different components, so as to find out the main stressors for the lake status. The data collected from diagnosis were used to characterize the lake status to confirm the visual appreciation of the lake.

On the other hand, the above data were used to develop a computer model for the lake, but also used to supply somehow the inputs of the model developed. The model was designed in such a way that all lake behaviour submitted to studied conditions would be reproduced probably not very accurately, but at least the trend was palpable and roughly reflected.

6.1. The main stressors of the lake

According to the results of the diagnostic the main pressure for the lake comes from the following stressors: - Suspended solids from watershed erosion and from the spa wastewater leading to sedimentation; - Solid waste that is intentionally or unintentionally dumped into the stream going into the lake; and - Nutrients enrichment from effluent loading even diluted but the longer duration of such loading since few decades ago has worsen the situation; - Nutrient enrichment from sediment internal loading leading to continuous event of algal growth; Dissolved and biodegradable organic matter is discharged into the lake but they are less important than the above components. However, the diagnostic demonstrated that the lake trophic status is Hypereutrophic and that its physical status is in advance degradation, which is characterized by loss of depth, loss of surface.

In order to propose different scenarios of remediation the platform AQUASIM was used for building a model. Then different remediation scenarios were simulated.

6.2. Scenarios of Lake Ranomafana remediation

According to the different results of management strategies simulation Table 42 presents the different scenarios or alternative approaches to remediating the lake.

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Table 42: Synthesis of management scenarios for the remediation of Lake Ranomafana Scenario Method used Effects on the lake Do nothing • Leave the lake as now • Continued algal bloom; without any • Continued sedimentation intervention; leading to reduced surface and depth; • Continued accumulation of inert organic and inorganic matter; • Aquatic food web is likely changing to terrestrial food web (see Figure 99) Reduction of polluting charge • Wastewater treatment; • Reduced algal biomass (nitrogen, phosphorus, • Diversion of the most provided that sediment dissolved organic matter) polluted influent (from internal loading is from external loading northwest); eliminated; • Limited Phosphorus for algae growth • Reduced accumulation of inert organic as sediment • Reduced dissolved organic matter as COD; • Increased heterotrophic bacteria biomass; • Increased level of ammonia; Reduction of phosphorus • Waste water treatment • Reduced algal biomass; charge from external loading • Diversion of the main • Limited phosphorus for source of phosphorus algae growth; • Reduced heterotrophic bacteria biomass provided that no sediment internal loading; • Reduced dissolved organic matter as COD; • Reduced accumulation of inert organic matter; Reduction of dissolved • Waste water treatment • Increased rapidly followed organic matter as COD by decreased algal biomass;

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• Limited increase of autotrophic bacteria biomass provided that phosphorus is supplied from internal loading; • Slightly decreased of heterotrophic bacteria biomass, • Decreased level of ammonia; • Increased level of nitrate; • Increased accumulation of inert organic matter; Reduction of sediments • Dredging • Decreased algal biomass internal loading • Chemical precipitation; and oxygen production; (phosphorus) • Caping • Decreased autotrophic • Biomanipulatiom bacteria biomass; • Increased heterotrophic bacteria biomass; • increased degradation level of dissolved organic; • limited phosphorus loading for algae growth; • decreased accumulation of inert organic matter provided that internal loading is eliminated; Combine reduction of • wastewater treatment • Decreased algal biomass; external and internal combine with dredging • Limited production of polluting charge or caping; oxygen; • Diversion of the most • Increased heterotrophic polluting influent bacteria biomass; combine with dredging • Increased degradation or caping level of dissolved organic matter; • Increased accumulation of ammonia; • Limited accumulation of inert organic matter;

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Figure 99 below illustrates the likely future possible fate of Lake Ranomafana if the degradation of its trophic status is not considered.

Figure 99: Possible fate of the lake without any management strategy

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CHAPTER 7 General conclusions

7.1. Final conclusion

One would be tempted to believe that the fate of Lake Ranomafana (for some the lake which badly smells) was fixed since the functioning of the spa around the 1940s. Actually, only the French hydrogeologist Pierre de la BATHIE is well placed person to give the most accurate answer. However, due to anthropogenic pressure from surrounding watershed including from the spa, for which the hydrogeologist is less concerned, the lake is in an advanced degradation state. So, the main objective of the study was to find out alternative approaches for reversing the current situation, and to answer whether it is feasible or not taking into consideration the actual existing conditions.

To provide scientific-based explanation about the degradation of the lake status, the study approach was based on diagnosing the focal problems of the lake from external to internal. A worldwide tool, modelling, used for similar problem was developed and used to find out at low cost the likely site specific and appropriate restoration alternatives. Then, series of alternative solutions were proposed taking into consideration different aspects such as social and economical, funding sustainability, costs and benefits for the main stake holders. It is indeed worthwhile noting that two projects to restore the lake were submitted for funding, but they were, at that time too expensive, that the municipality failed to find any financial support. This is probably due to lack of scientific-based diagnostic, which should have permitted more realistic proposal. This failure to materialize these project proposals once again highlight the importance and the value of scientific-based proposal that could be easily justified by the key findings.

Based on the different results one can say that the key findings are serious enough to predict the likely future fate of the lake without anything done. Just for the sake of repeating the main problem, the lake has suffered from a series of problem: sedimentation, nutrients enrichment from external and internal loading leading to algal bloom, and accumulation of inert organic material. One should always take into consideration the fact that in shallow lakes one issue (for example the collapse of algal bloom) can spark a devastating chain of events.

These problems could be resolved but at what price since the cost depends on how early the intervention is being implemented. So the more these problems are disregarded the more expensive will be the cost. However, the good news is that the beauty of the lake taken in photo in 1946 might be seen again depending on stakeholder’s willingness to resolve the degradation problem. This could be a challenge for the municipality of Antsirabe, but the stakes (public health and tourism) might be worthwhile for taking up the challenge.

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The model could be used for selecting any of the proposed solution to better focus on resolving specific issue leading to the lake degradation without unbearable related cost for the municipality. It is worthwhile noting that the model represents an important tool for urban lakes management, and this model is the first of its kind as far as urban lakes receiving municipal wastewater is concerned. Important to note that Madagascar are rich in wetland including those located in urban agglomeration.

Last but not least is the impact of global warming on the lake. This latter is being affected by rise of temperature, and deficit of rainfall. So, evaporation is being enhanced while supply of water to the lake will also be likely jeopardized.

7.2. Further research

As has been noted and mentioned throughout this report, there are few studies that deserve to be completed as these would be useful for the management of the lake. They concern biological data about the nature and structure of phytoplankton communities (species), the characterisation of the output from point of chemical and biological characteristics. Further study on internal loading would be worthwhile for any management project proposal since important supply of phosphorus comes from sediment. Finally, a laboratory treatment test is also of big interest before selecting any remediation scenario. Treatment test should be performed on both influents and lake water.

On the other hand, a very interesting research could be in the future conducted at the level sediments with respect to ongoing anaerobic biological process transforming organic matter to gases, but also regarding removal of nutrients from sediment by simulating flushing with clean water at laboratory level.

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References

Anderson C., Lafontaine N., et al., 2007. Prendre son lac en main : Guide d’élaboration d’un plan directeur de bassin versant de lac et adoption de bonnes pratiques. Minirtère du Développement durable, de l’Environnement et des Parcs, Québec CANADA.

Asimbolarimalala, W.L., 2008. Analyse physico-chimique de l’eau du Lac Ranomafana d’Antsirabe en vue de sa remediation. Mémoire pour l’obtention du Diplôme d’Etudes Approfondies (DEA) en Chimie, Option : Chimie Minérale et Chimie Appliquée. Université d’Antananarivo, Faculté des Sciences.90p.

Bartram, J., Ballance, R., 1996. Water quality monitoring: A practical guide to the design and implementation of freshwater quality studies and monitoring programmes. E&FN Spon, London. 383p.

Chapman, D., 1992. Water quality assessments: A guide to the use of biota, sediments and water in environmental monitoring. First edition, E&FN Spon, London. 565p.

Chorus, I., Mur, L., 1999. Preventative measures. In Chorus I. and Bartram J. (WHO), Toxic Cyanobacteria in Water: A guide to their public health consequences, monitoring and management.

Commune Urbaine d’Antsirabe, 2003. Plan d’urbanisation (2 ème ) : Schéma d’assainissement urbain.

Commune Urbaine d’Antsirabe, 2006. Plan communal de développement. Rapport élaboré par la Structure Communale pour le Développement.51p.

Conservation International, 2011. Songadina. Bulletin trimestriel, N°8.

Dahl, Ø., 2010. Lovasoa the good heritage. Powerpoint presentation of the history of the Norwegian school in Antsirabe. First Antsirabe network conference (Lovasoa Antsirabe Cross-cultural Competence Centre, 6-8 decembre 2010).

De Vicente, I., Amores, V., Cruz-Pizarro, L., 2006. Instability of shallow lakes: A matter of the complexity of factors involved in sediment and water interaction?. Limnetica, 25(1-2):253- 270.

Drosde, Ronald. L., 1997. Theory and practice of water and wastewater treatment. John Wiley & Sons, Inc, New York. 789p.

199

Fish, G.R., 1970 (Online 2010). A limnological study of four lakes near Rotorua. New Zealand Journal of Marine and Freshwater Research, 4:2, 165 - 194.

Gray, N.F., 1999. Water technology: An introduction for environmental scientists and engineers. Arnold, London. 538p.

Henze, M., Harremoës, P, et al., 2002. Wastewater treatment: Biological and chemical processes. Third edition. Springer-Verlag Berlin Heidelberg New York. 421p.

International Association on water pollution Research and Control, undated. Activated sludge model n°1.

International Atomic Energy Agency Marine Environment Laboratory, Undated. Training workshop on the analysis of trace metals in biological and sediment samples: Laboratory Procedure book. 45p.

James, A., 1984. An introduction to water quality modelling. A Willey-Interscience publication. 231p.

Jørgensen, S.E., 1980. Lake management. Water development, supply and management, vol 14. 146p. Pergamon press, University of Copenhagen, Danmark.

Jørgensen, S.E., undated. The eutrophication problem.

Jørgensen, S.E., 1999. State-of –the art of ecological modelling with emphasis on development of structural dynamic models. Ecological modelling 120 (1999) 75 – 96.

Kayombo, S., Jørgensen,S.E., et al., 2005. Waste stabilization ponds and Constructed wetlands design manual. United Nation Environment Program - Division of Technology, Industry and Economics and Danish International Development Agency (Danida) Edition.

Kim, L.H., Choi, E., Stenstrom, M. K., 2003. Sediment characteristics, phosphorus types and phosphorus release rates between river and lake sediments. Chemosphere 50, 53 61.

Le Progrès de l’Imerina, 1890. Les eaux minérales de Madagascar. Magazine scientifique du 31 Décembre 1890 et 1 er janvier 1891.

L’Express de Madagascar, 2011. Andranomafana: Fermeture des eaux thermales. Les dépôts calcaires dans la tuyauterie nécessitent des entretiens annuels. La période de fermeture est choisie de façon à ne pas gêner les curistes. Quotidien d’information et d’analyse, Magazine régions du 17 Mai 2011.

200

Lewis Jr.W.M., McCutchan Jr., J. H., 2009. Factors affecting pH of water in Barr Lake and Milton Reservoir.

Magadza, C.H.D., 1979 (Online 2010). Physical and chemical limnology of six hydroelectric lakes on the Waikato River, 1970-72. New Zealand Journal of Marine and Freshwater Research, 13:4, 561 -572.

Mayhew, E., Mayhew, M., 1991. The trophic state of Lake Sidney Lanier. Proceedings of the 1991 Georgia Water Resources Conference, held March 19 and 20, 1991, at The University of Georgia.

McColl, R.H.S., 1977 (Online 2010). Chemistry of sediments in relation to trophic condition of eight Rotorua Lakes. New Zealand Journal of Marine and Freshwater Research, 11:3, 509 – 523.

Novics, V., 2009. Eutrophication of lakes and reservoirs.

Oswald, W.J., 1988. Micro-algae and waste-water treatment. In Borowitzka M. A., Borowitzla L. J. (eds), Micro-algal Biotechnology. Cambridge U. P., Cambridge, 305 -398.

Pavluk, T., De vaate, A., 2008. Trophic index efficiency. Ecological indicators 3602.

Peng, J.F., Wang, B.Z., Song, Y.H., Yuan, P., 2007. Modeling N transformation and removal in a ducweed pond: Model development and calibration. Ecological modelling 206, 147 – 152. Phlips, E.J., undated. Eutrophication and Algae.

Reichert, P., 1998. AQUASIM 2.0 – User manual: Computer program for the identification and simulation of Aquatic systems. 188p.

Réland, 1905. Les eaux thermales et minérales d’Antsirabe. Bulletin économique de Madagascar 1 er trimestre.

Rodier, J., 2001. L’analyse de l’eau, eau naturelle, eau use, eau marine. Seventh edition, pp. 198-203.

Ruley, J.E., Rusch, K.A., 2004. Development of simplifies phosphorus management model for a shallow, subtropical, urban Hypereutrophic lake. Ecological engineering 22, 77 – 98.

Sagehashi, M., Sakoda, A., Suzuki, M., 2001. A mathematical model of a shallow and eutrophic lake (The Keszthely basin, Lake balaton) and simulation of restorative manipulations. Water Resources, Volume 35, N° 7, pp. 1675 -1686. .

201

Seidl, M., 1997.Caractérisation des rejets urbains de temps de pluie et de leurs impacts sur l’oxygénation de la Seine. Thèse de Doctorat de l’Ecole Nationale des Ponts et Chaussées, Sciences et Techniques de l’Environnement. 169p.

Senzia, M.A., Mayo, A.W., Mbwette, T.S.A., et al., 2002. Modelling nitrogen transformation and removal in primary facultative ponds. Ecological Modelling 154, 207 – 215. .

Simonsen, J., Dahl-Madsen, K.I., 1978. Eutrophication models for lakes. Hydrology, 9, 131- 142.

Soetaert, K., Herman, P.M. J., 2001. Ecological modelling lectures notes. Netherlands Institutte of Ecology – Centre for Estuarine and marine ecology, Yerseke, the Netherlands.92p.

Soetaert, K., Herman, P.M.J., 2009. A practical guide to ecological modelling. Using R as a simulation platform. Springer Science+Business Media B.V.. 367p.

Søndergaard, M., Peder Jensen, J., Jeppesen, E., 1999. Internal loading in shallow Danish lakes. Hydrobiologia 408/409: 145-152.

Spears, B.M., Carvalho, L., Perkins, R., Paterson, D. M., 2008. Effect of light on sediment nutrient flux and water column nutrient stoichiometry in a shallow lake. Water research 42, 977-986.

Tchobanoglous, G., Burton, F. L., Stensel, H. D., 2003. Wastewater Engineering, Treatment and reuse. 4 th edition. Metcalf & Eddy, Inc.McGraw-Hill, New York. 1771p.

Tebbutt, T.H.Y., 1998. Principles of water quality control. Fifth edition. Butterworth- Heinemann, Oxford. 279p.

Udy, J., Gall, M., et al ., 2005. Water quality monitoring: A combined approach to investigate gradients of change in the Great Barrier Reef, Australia. Marine pollution bulletin, 51, 224- 238.

United Nations International Children’s Emergency Fund Madagascar, 2010. Boîte à outils: Partenariat Public-Privé pour les enfants.

United Nations Environment Programme-Division of Technology, Industry and Economics, 1999. Planning and management of lakes and reservoirs: An integrated approach to eutrophication. Technical publications, Series 11.

202

United Nation Environment Programme-Division of Technology, Industry and Economics- International Environmental Technology Centre, 2002. Planning and Management of Lakes and Reservoirs focusing on Eutrophication or Pamolare 2.

United States Environmental Protection Agency, 2010. National lakes assessment: A collaborative survey of the nation’s lakes. EPA 841 –R-09-001. U.S. 100p.

Wentzel, M.C., Ekama, G.A., undated. Principles in the modelling of biological wastewater treatment plants.

Wetzel, R.G., Likens, G.E., 2000. Limnological analyses. Third edition. Springer Science+Business Media, Inc, New York. 425p.

Wetzel, R.G., 2001. Limology: Lake and river ecosystems. Third edition. Academic Press, California, London. 985p.

White, E., Downes, M. T., 1977 (Online 2010). Preliminary assessment of nutrient loads on lake Taupo, New Zealand. New Zealand Journal of Marine and Freshwater Research, 11:2, 342 – 356.

203

Web sites http:// www.ecy.wa.gov/programs/wq/plants/ weeds/hyacinth.html http:// www.en.wikipedia.org/wiki/water hyacinth http://www.h2ou.com /h2wtrqual.htm#top http:// www.sante.gov.mg/vakinankaratra_ssd_antsirabeI http//theaquariumwiki.com/Procambarus_sp http://www.unicef.org/french/infobycountry/madagascar_statistics.html http://www.wateraidamerica.org/what_we_do/where_we_work/madagascar/ http://www.who.int/docstore/water_sanitation_health/toxicyanobact/ch16.html http://www.waterencyclopedia.com/Hy-La/Lakes-Chemical-Processes.html

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Appendices

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Appendix A.

National wastewater standards (Extract from Decree N° 2003/464 of 15/04/03 concerning Classification of surface waters and regulation of discharge of liquid effluents) PARAMETERS UNIT STANDARDS Organoleptic and physical factors pH 6.0 – 9.0 Conductivity µs cm -1 200 Suspended solids mg L -1 60 Temperature °C 30 Colour Scale Pt/Co 20 Turbidity NTU 25 CHEMICAL FACTORS -1 Total hardness as CaCO 3 mg L 180.0 Ammonium nitrogen mg N L -1 15.0 Nitrate mg L -1 20.0 Nitrite mg L -1 0.2 TKN (Total Kjeldahl nitrogen) mg N L -1 20.0 - - -1 Phosphates as PO 4 mg L 10.0 - - -1 Sulfates as SO 4 mg L 250 Sulfide as S - - mg L -1 1.0 Oil and grease mg L -1 10 Phenols and cresols mg L -1 1.0 Polyaromatic hydrocarbons mg L -1 1.0 Surface agent (ionic or non) mg L -1 20 Free chlorine mg L -1 1.0 chloride mg L -1 250 BIOLOGICAL FACTORS Chemical demand in oxygen (COD) mg L -1 150 -1 Biological demand in oxygen (BOD 5) mg L 50 UNDESIRABLE FACTORS METALS Aluminium mg L -1 5.0 Arsenic mg L -1 0.5 Cadmium mg L -1 0.02 Hexavalent Chromium mg L -1 0.2 Total Chromium mg L -1 2.0 Iron mg L -1 10.0 Nickel mg L -1 2.0

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Lead mg L -1 0.2 Tin mg L -1 10 Zinc mg L -1 0.5 Manganese mg L -1 5.0 Mercury mg L -1 0.005 Selenium mg L -1 0.02 OTHER SURBSTANCES Cyanide mg L -1 0.2 Aldehyde mg L -1 1.0 Aromatic solvent mg L -1 0.2 Nitrogen solvent mg L -1 0.1 Chlorinated solvent mg L -1 1.0 Organochlorinated pesticides mg L -1 0.05 Organophosphorus pesticides mg L -1 0.1 Pyrethrinoides mg L -1 0.1 Phenylpyrrazoles mg L -1 0.05 Total pesticides mg L -1 1.0 Antibiotics mg L -1 0.1 Polychlorinated biphenyls mg L -1 0.005 RADIOACTIVITY Bq 20 MICROBIOLOGICAL FACTORS Total coliforms 500 Escherichia coli 100 Colony Fecal streptococcus 100 Clostridium sulphite reducotrs 100

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Appendix B. Physical characteristics of Lake Ranomafana

B.1. Relationship between Secchi depth and coefficient of light extinction (Morning)

0,5 10 0,36 6,0 ) ) -1 -1 0,4 8 0,34 5,5 0,3 6 0,32 5,0 0,2 4 0,3 4,5 Secchi dept (m) dept Secchi

0,1 2 (m) depth Secchi 0,28 0 0 0,26 4,0 Light extinction coef (m coef extinction Light 1 2 3 4 5 (m coef. extinction Light 1 2 3 4 5

Secchi Feb Extinction Coef Feb Secchi Mar Extinction coef Mar

0,25 15 0,21 10,5 ) ) -1 -1 0,2 0,2 10 10 0,19 9,5 0,15 0,18 9 0,1 5 0,17 8,5

Secchi dept (m) dept Secchi 0,05 Secchi depth (m) depth Secchi 0,16 8 0 0 0,15 7,5 Light extinction coef (m coef extinction Light (m coef extinction Light 1 2 3 4 5 1 2 3 4 5

Secchi Apr Extinction Coef Apr Secchi May Extinction Coef May

0,25 15,0 0,21 10,5 ) ) -1 -1 0,2 0,2 10,0 10,0 0,19 9,5 0,15 0,18 9,0 0,1 5,0 0,17 8,5

Secchi depth (m) depth Secchi 0,05 (m) depth Secchi 0,16 8,0 0 0,0 0,15 7,5 Light extinction coef (m coef extinction Light (m coef extinction Light 1 2 3 4 5 1 2 3 4 5

Secchi Aug Extinction coef Aug Secchi Sep Extinction Coef Sep

0,25 12,0 0,25 12,0 ) ) -1 -1 0,2 10,0 0,2 10,0 8,0 8,0 0,15 0,15 6,0 6,0 0,1 0,1 4,0 4,0

Secchi depth (m) depth Secchi 0,05 2,0 (m) depth Secchi 0,05 2,0 0 0,0 0 0,0 Light extinction coef (m coef extinction Light (m coef extinction Light 1 2 3 4 5 1 2 3 4 5

Secchi Oct Extinction Coef Oct Secchi Nov Extinction Coef Nov

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0,25 12,0 ) -1 0,2 10,0 8,0 0,15 6,0 0,1 4,0

Secchi depth (m) depth Secchi 0,05 2,0 0 0,0 Light extinction coef (m coef extinction Light 1 2 3 4 5

Secchi Dec Extinction Coef Dec

B.2. Relationship between Secchi depth and coefficient of light extinction (Afternoon)

0,6 10 0,4 6 ) ) -1 0,5 5 -1 8 0,3 0,4 4 6 0,3 0,2 3 4 0,2 2 0,1 Secchi dept (m) dept Secchi 0,1 2 (m) depth Secchi 1 0 0 0 0 Light extinction coef (m coef extinction Light 1 2 3 4 5 (m coef. extinction Light 1 2 3 4 5

Secchi Feb Extinction Coef Feb Secchi Mar Extinction coef Mar

0,25 12 0,25 10 ) ) -1 -1 0,2 10 0,2 8 8 0,15 0,15 6 6 0,1 0,1 4 4

Secchi dept (m) dept Secchi 0,05 0,05 2 2 (m) depth Secchi 0 0 0 0 Light extinction coef (m coef extinction Light (m coef extinction Light 1 2 3 4 5 1 2 3 4 5

Secchi Apr Extinction Coef Apr Secchi May Extinction Coef May

0,25 15,0 0,25 15,0 ) ) -1 -1 0,2 0,2 10,0 10,0 0,15 0,15 0,1 0,1 5,0 5,0

Secchi depth (m) depth Secchi 0,05 (m) depth Secchi 0,05 0 0,0 0 0,0 Light extinction coef (m coef extinction Light (m coef extinction Light 1 2 3 4 5 1 2 3 4 5

Secchi Aug Extinction coef Aug Secchi Sep Extinction Coef Sep

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0,25 20 0,25 40 ) ) -1 -1 0,2 15 0,2 30 0,15 0,15 10 20 0,1 0,1 5 10

Secchi depth (m) depth Secchi 0,05 (m) depth Secchi 0,05 0 0 0 0 Light extinction coef (m coef extinction Light (m coef extinction Light 1 2 3 4 5 1 2 3 4 5

Secchi Oct Extinction Coef Oct Secchi Nov Extinction Coef Nov

0,25 12,0 ) -1 0,2 10,0 8,0 0,15 6,0 0,1 4,0

Secchi depth (m) depth Secchi 0,05 2,0 0 0,0 Light extinction coef (m coef extinction Light 1 2 3 4 5

Secchi Dec Extinction Coef Dec

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Appendix C. Daytime variation of Dissolved oxygen, Saturation of oxygen, Temperature, and pH

03.09.2009 Surface O2 Bottom O2 Sat Sat Time Temp (%) O2 (mg/l) (%) O2 (mg/l) 8:30 19.3 170.8 14.01 162.6 12.95 10:00 19.6 223 18.6 220.4 17.85 12:00 20.9 315.4 25.39 285.6 20.94 14:00 23 350.5 27.29 335 25.08 16:00 20.8 298.1 20 276.5 18.01 17:30 20 354 28.07 327.9 25.07

O2 O2 04.09.2009 Temp Sat (%) (mg/l) Sat (%) (mg/l) 6:00 16.4 149 12.64 148.4 12.37 8:00 18.1 162.4 14.26 165.9 13.27 10:00 20.9 274.9 22.78 257.8 19.8 12:00 22.2 348.6 27.29 333.4 25.08 14:00 23 369.9 31.02 356 25.93 16:00 20.9 414.8 34.64 378.5 30.62 17:30 22.4 407.7 34.99 369.2 28.51

O2 O2 18.09.2009 Temp pH Sat (%) (mg/l) Sat (%) (mg/l) 6:00 21.3 7.93 10.4 0.74 11.6 0.9 8:00 21.5 8.01 51.5 4.29 45.9 3.67 9:00 22.5 8.07 70.9 5.43 59.1 4.65 10:00 23.3 8.05 79.6 5.8 24.6 1.2 12:00 26.6 8.16 162.6 12.38 107.7 7.75 14:00 25.6 8.2 155 12.11 146.6 12.15 16:00 26.2 8.35 184.1 14.48 159.4 11.7 17:30 25.8 8.4 215.8 16.59 210.4 15.19

O2 O2 22.09.2009 Temp pH Sat (%) (mg/l) Sat (%) (mg/l) 6:00 21.2 7.99 3.4 0.42 3.9 0.32 8:00 21.2 8 12.8 0.92 6.2 0.74 9:00 22.3 8.01 18.2 1 0.3 0.07 10:00 24.2 8.07 60.2 4.76 3.9 0.32 11:00 24.7 8.09 69.3 5.75 28.6 2.52 12:00 25.4 8.16 97.9 6.71 70.4 4.66 14:00 25.3 8.19 156.6 12.89 124.3 10.03 16:00 24.4 8.06 51.6 4.93 62.6 5.41 17:30 24 8.01 20.1 2.75 42.1 3.39

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O2 O2 29.09.2009 Temp pH Sat (%) (mg/l) Sat (%) (mg/l) 6:00 20.8 8.11 18.4 1.65 24.7 2.15 8:00 21.4 8.16 64.4 5.24 59.4 4.58 9:00 22.2 8.16 68.8 4.96 72.2 5.43 10:00 23.5 8.19 102.5 7.86 98.5 7.18 11:00 24.7 8.23 115.3 7.96 112.6 8.65 12:00 25.7 8.28 157.2 11.96 150.9 11.08 14:00 26.8 8.4 206.2 15.6 203.2 14.15 16:00 27.3 8.39 226.7 17.65 189 14.17 17:30 26.8 8.49 214.3 16.94 186.7 13.39

O2 O2 09.10.2009 Temp pH Sat (%) (mg/l) Sat (%) (mg/l) 6:00 23.5 8.22 70.6 5.47 76 5.56 8:00 23.9 8.36 141 10.89 153.8 11.73 9:00 25 8.48 197.1 14.53 125.8 9 10:00 26.5 8.57 261.8 19.23 242.3 15.75 11:00 26.7 8.4 185.5 13.12 173.7 12.39 12:00 28.2 8.58 267.7 19.45 205.7 14.75 14:00 29 8.81 380 27.34 366.9 25.45 16:00 28.9 8.87 374.2 26.85 363.2 25.96 17:30 28.3 8.92 375.3 28.53 329.4 23.73

O2 O2 23.10.2009 Temp pH Sat (%) (mg/l) Sat (%) (mg/l) 6:00 23.5 8.23 40.1 3.09 45.1 3.43 8:00 23.2 8.32 41.4 3.29 37.5 3.08 9:00 23.2 8.4 57.2 4.5 53 4.08 10:00 23.2 8.4 87.1 6.92 83.2 6.54 12:00 25 8.44 124.4 9.39 130.7 9.78 14:00 26.6 8.51 170.3 12.44 189.1 13.7 16:00 26.4 8.43 n.d n.d n.d n.d 17:30 n.d n.d n.d n.d n.d n.d

O2 O2 02.11.2009 Temp pH Sat (%) (mg/l) Sat (%) (mg/l) 6:00 n.d 8.2 0.65 10 0.79 8:00 n.d 39.1 3.09 39.9 3.16 9:00 22.5 n.d 64.4 4.92 58 4.44 10:00 23 n.d 68.4 5.26 60.6 4.61 12:00 24.9 n.d 95.6 7.04 85.3 6.26 14:00 22.9 n.d 99.4 7.58 93.4 6.87 16:00 22.6 (rain)n.d 62.7 4.86 62.6 4.82 17:30 22 n.d 56.6 4.46 54.3 4.2

O2 O2 27.11.2009 Temp pH Sat (%) (mg/l) Sat (%) (mg/l) 6:00 22.2 7.99 61.3 4.85 50.1 3.89 8:00 22.1 8 64.3 5.03 61.1 4.72 9:00 22.8 8.08 84.8 6.58 76.6 5.76 10:00 23.4 8.17 101.4 7.67 92.1 6.9

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12:00 26 8.43 150.3 10.96 141.9 10.16 14:00 25.3 8.31 99.3 7.53 99.5 7.24 16:00 24.3 8.16 82.4 6.29 106.9 7.72 17:30 24.1 8.29 88.2 7.09 100.7 7.57

O2 O2 17.12.2009 Temp pH Sat (%) (mg/l) Sat (%) (mg/l) 6:00 21.6 7.52 17 1.32 21 1.61 8:00 22.2 7.76 86.1 6.6 70.6 5.38 9:00 23.8 7.94 111.8 8.47 109 8.15 10:00 24.1 7.77 85.9 6.48 65.5 4.89 12:00 23.6 7.75 89.5 6.84 63.5 4.85 14:00 23.5 8.42 137.8 10.26 106.6 7.8 16:00 24.9 8.4 137.6 10.55 105.8 7.97 17:30 n.d n.d n.d n.d n.d n.d n.d: not determined

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Appendix C. Daytime variation of Dissolved oxygen, Saturation of oxygen, Temperature, and pH (continued)

214

Variation of DO with Temperature (03.09.09) Variation of DO with Temperature (04.09.09) 24 30 25 40 35 23 25 20 30 22 )

20 ) 25 -1

-1 15 21 Temp Temp 15 20 20 Surf O2 10 15 Surf O2

10 (mgDO l 19 (mgDO l Bott O2 10 Bott O2 Temperature(°C)

Temperature(°C) 5 18 5 5 17 0 0 0 06:00 08:00 10:00 12:00 14:00 16:00 17:30 8:30 10:00 12:00 14:00 16:00 17:30

Time (h:mn) Time (h:mn)

Variation of DO with Temperature (18.09.2009) 18 30 16 25 14

) 12 20

-1 Temp 10 15 Surf O2 8

DO (mgDO l 6 10 Bott O2 Temperature(°C) 4 5 2 0 0 06:00 08:00 09:00 10:00 12:00 14:00 16:00 17:30

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Appendix D. Variation of Nitrogen-nitrate, Phosphorus-Phosphate, Total nitrogen, and Total phosphorus contents in sediment cores (30 cm)

Sample Depth Humidity N-NO 3 TN P-PO 4 TP (%) (g/kg) (g/kg) (g/Kg) (g/kg) 10 cm 34.96 0.058 0.715 0.024 0.089 1 20 cm 34.04 0.016 0.766 0.036 0.095 30 cm 36.58 0.017 0.640 0.027 0.046 10 cm 36.91 0.036 0.843 0.037 0.050 2 20 cm 60.25 0.032 1.202 0.032 0.101 30 cm 40.92 0.019 0.514 0.028 0.043 10 cm 54.91 0.074 0.599 0.027 0.030 3 20 cm 52.01 0.044 0.656 0.015 0.027 30 cm 50.95 0.018 0.715 0.011 0.026

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