LILONGWE WATER BOARD
Environmental and Social Impact Assessment for Lake Malawi Water Supply Project for Lilongwe City
VOLUME 2 – APPENDIX
Rpt_t17049/02 February-18
www.nemus.pt [email protected]
Government of Malawi Ministry of Agriculture, Irrigation and Water Development
ENVIRONMENTAL AND SOCIAL IMPACT ASSESSMENT FOR LAKE MALAWI WATER SUPPLY PROJECT FOR LILONGWE CITY
VOLUME 2
— APPENDIX —
LILONGWE WATER BOARD
February 2018
ENVIRONMENTAL AND SOCIAL IMPACT ASSESSMENT FOR LAKE MALAWI WATER SUPPLY PROJECT FOR LILONGWE CITY
VOLUME 1- ESIA REPORT
VOLUME 2 - APPENDIX
TABLE OF CONTENTS
1. Introduction 1
2. Geology, Topography and Hydrogeology 3
2.1. Introduction 3
2.2. Regional geomorphology 4
2.3. Geology 6
2.4. Geohazards 7
2.4.1. Neotectonics and seismicity 7
2.5. Economic geology 9
2.6. Hydrogeology: type of aquifer and other general aspects 13
2.7. Alluvial aquifer system 14
2.8. Weathered basement: aquifer properties 15
2.9. Groundwater quality 16
3. Soils 21
3.1. Introduction 21
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix i
3.2. Soil characterization 22
3.3. Soil suitability 31
3.4. Slopes 33
3.5. Soil erosion 35
3.6. Soil contamination 36
4. Climate and Meteorology 39
4.1. Climate of Malawi 39
4.2. Rainfall 43
4.3. Temperature 58
4.4. Extreme meteorological events 66
4.4.1. Floods 67
4.4.2. Extreme temperatures and rainfall 67
4.4.3. Droughts 67
4.5. Climate trends and expected evolution 70
4.5.1. Rainfall 70
4.5.2. Temperature 74
4.5.3. Extreme meteorological events 77
4.5.4. Summary of the climate projections for the region 80
5. Air Quality 82
5.1. Air quality standards 82
5.2. Sensitive receptors 84
5.3. Air pollution 84
5.3.1. Health 84
5.3.2. Ambient air quality 85
5.4. Air pollution sources 87
5.4.1. Road traffic 88
5.4.2. Biomass combustion 90
ii Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
5.4.3. Other sources 91
5.5. Atmospheric dispersion conditions 93
5.6. Air quality assessment 94
6. Surface Water Quality 97
6.1. Overview of the water resources in the project area 97
6.1.1. Water quality assessment methodology 102
6.1.2. Water uses 106
6.1.3. Pollution sources 107
6.1.4. Water quality assessment 109
7. Ecology, Flora and Fauna 119
7.1. Introduction 119
7.2. Habitats 120
7.3. Vegetation and flora 135
7.3.1. Vegetation 135
7.3.2. Flora 138
7.4. Fauna 140
7.4.1. Aquatic macro-invertebrates 140
7.4.2. Ichthyofauna 141
7.4.3. Herpetofauna 142
7.4.4. Avifauna 144
7.4.5. Mammals 146
8. Socioeconomics and Public Health 148
8.1. Political evolution, administrative and community structure 148
8.2. Population characteristics and dynamics 152
8.3. Education and literacy 157
8.4. Household and housing characteristics 161
8.5. Social conditions and public health 169
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix iii
8.6. Economic activity 173
8.7. Employment 180
8.7.1. Land Ownership 184
9. References 185
Annex 1 – ESIA Team Composition 193
Volume 1 Annex – Maps
Map PRJ1 – Administrative Framework (orthophoto map – 1:300 000)
Map PRJ2 – Pipeline alignment and projected infrastructures (topographic map – 1:25 000)
Map PRJ3 – Pipeline alignment and projected infrastructures (orthophoto map – 1:5 000)
Map GEO1 – Hypsometry (1: 50 000)
Map GEO2 – Slope Angles (1: 50 000)
Map GEO3 – Geological / Hydrogeological Map (1: 50 000)
Map SOL1 – Soil Types (Lowole, 1983) (1:300 000)
Map SOL2 – Soil Types (GeoNode, 2013) (1:300 000)
Map CLI1 – Average Annual Rainfall (1:300 000)
Map CLI2 – Average Annual Temperature (1:300 000)
Map FF1 – Habitat Map (1:15 000)
iv Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
LIST OF TABLES
Table 1 – Dominant lithology along the study area 6
Table 2 – Results from different monitoring campaigns held in the alluvial aquifer and near the pipeline project 15
Table 3 – Parameters from groundwater in the Lilongwe area (weathered basement aquifer) from 1997 and 1999 (N = 43) and drinking water quality standards and guidelines from MBS (2013) and WHO (2017) 17
Table 4 – Quality results from a monitoring well located in the alluvial aquifer, in the Kambwiri Sere Irrigation Scheme (Salima district) and drinking water quality standards and guidelines from MBS (2013) 18
Table 5 – Soil classification according to LREP system: characteristics and properties of soil types present in the pipeline area 25
Table 6 – KIA weather station total annual precipitation records, for the 1961-2011 period, and classification of hydrological year type 49
Table 7 – Parameters for each hydrological year type, according to data from the KIA station, for the 1961-2011 period 50
Table 8 – Chitedze weather station total annual precipitation records, for the 1997-2011 period, and classification of hydrological year type 52
Table 9 – Parameters for each hydrological year type, according to data from the Chitedze station, for the 1997-2011 period 53
Table 10 – Salima weather station total annual precipitation records, for the 1997-2011 period, and classification of hydrological year type 55
Table 11 – Parameters for each hydrological year type, according to data from the Salima station, for the 1997-2011 period 56
Table 12 – Drought classification according with the Percentile Drought Index method 68
Table 13 – KIA, Chitedze and Salima weather stations’ drought annual precipitation thresholds and years that threshold is verified, according with Percentile Drought Index (Gibbs, 1987) 69
Table 14 – GCM projections of wet season (November-March) precipitation changes in Central Malawi, for the period 2071-2100 71
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix v
Table 15 – GCM projections of wet season (November-March) temperature changes in Central Malawi, for the period 2071-2100 74
Table 16 – Summary of climate projections for the South African region 81
Table 17 – IFCs’ reference guidelines for ambient air quality 82
Table 18 – Ambient air quality standards limits for Malawi 83
Table 19 – Air quality standards for motor vehicles in Malawi 83
Table 20 – Carbon dioxide emissions for Malawi in the period 1990-2011 86
Table 21 – Assessment of air quality in South Africa 94
Table 22 – Concentrations of fine particulate matter (PM2.5) (μ/m3) in Malawi 95
Table 23 – Location and sampled parameters of LWB surface water quality monitoring sites 103
Table 24 – Water quality standards and guidelines 105
Table 25 – Lake Malawi (Leopard Bay area) major pollution sources and associated water quality impacts 108
Table 26 – Water quality standard/guidelines compliance assessment for Lake Malawi sample site 109
Table 27 – Water quality standard/guidelines compliance assessment for Lumbadzi sample site 110
Table 28 – Water quality standard/guidelines compliance assessment for Linthipe sample site 111
Table 29 – Turbidity results for monitoring sites 112
Table 30 – Suspended solids results for monitoring sites 113
Table 31 – Electrical conductivity results for monitoring sites 114
Table 32 – Total dissolved solids results for monitoring sites 115
Table 33 – Nitrates results for monitoring sites 116
Table 34 – Iron results for monitoring sites 117
Table 35 – Faecal coliforms results for monitoring sites 118
Table 36 – Areas of each habitat within the study area 120
Table 37 – Key demographic indicators (1998-2030) 155
vi Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
Table 38 – Internal Migration, in Malawi and at Districts, in 2008 156
Table 39 – Population distribution by religion, in 2008 156
Table 40 – Literacy status of persons aged 5 years and older by region, in 2008 157
Table 41 - Sex distribution of the literate population, in 1998-2008 157
Table 42 – Literacy rate by sex for districts, in 2008 158
Table 43 – Percent distribution of school going age population by sex and region, 2008 159
Table 44 – Percent distribution of persons 6 years and over by school attendance status for district, in 2008 160
Table 45 – Population aged 5 years and over by highest educational level attended and by district, in 2008 160
Table 46 – Number of persons and type of dwelling unit by district, in 2008 162
Table 47 – Population distribution of households according to main source of drinking water by districts, in 2008 164
Table 48 – Population distribution of households according to type of toilet facility used by district, in 2008 166
Table 49 – Population of households by main source of energy for cooking by district, in 2008 168
Table 50 – Population of households by main source of energy for lighting by district, in 2008 168
Table 51 – Population of households by type of assets by district, in 2008 169
Table 52 – Proportion of distribution of top most reported diseases (2016-2017) 172
Table 53 – Annual percentage growth rates, 2014-2018 174
Table 54 – Sectoral contribution to Malawi GDP, 2014-2018 175
Table 55 – Employment by sector, sex and region, in 2013 182
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix vii
LIST OF FIGURES
Figure 1 - Longitudinal survey of altimetry along the design trajectory 5
Figure 2 – The Afro-Arabian rift system (continental graben and depressions are shaded) 8
Figure 3 – Epicentre of 1989 Salima Earthquake, a magnitude 6.6 quake, occurred on March 10, 1989 in central Malawi 8
Figure 4 – Seismic hazard for Southeast Africa expressed as peak ground acceleration (PGA) 9
Figure 5 – Borrow pits located close to the main road (km 3+900 – Salima District/TA Maganga) 10
Figure 6 – Borrow pit located close to km3+900 – Salima District/TA Maganga 11
Figure 7 – Quarry located close to the study area (km 95+400 – Lilongwe District / TA Chimutu) 12
Figure 8 – Hydrogeological regions of Malawi 14
Figure 9 – Soil types of Malawi (extract) with projected pipeline implementation (in yellow) 28
Figure 10 – Soil types of Malawi with projected pipeline implementation course (in purple) 29
Figure 11 – Soil type (Salima area) 30
Figure 12 – Soil type (Dowa area) 30
Figure 13 – Soil type (Lilongwe area) 31
Figure 14 – Location of ADD areas in Malawi (pipeline implementation area projected in yellow) 32
Figure 15 – Soil slopes of Malawi (extract) with pipeline implementation 34
Figure 16 – Exposed soil in agricultural land 35
Figure 17 – Exposed soil in forest production area 35
Figure 18 – Exposed bare soil in flood land 36
Figure 21 – Burnt clay bricks kiln 38
Figure 22 – Chitedze, KIA and Salima weather stations location, with pipeline projected implementation (in yellow) 40
viii Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
Figure 23 – Historical climate monthly averages (temperatures and rainfall), measured at the Chitedze, Salima and KIA stations 42
Figure 24 – Seasonal rainfall anomalies (mm) over southern Africa from 1901 to 2014 with respect to the long-term average climatology 1961-1990; based on the gridded CRU TS 3.23 data set 43
Figure 25 – Projected change in distribution of rainfall throughout the year (statistical downscaling) 44
Figure 26 – Projected change in distribution of rainfall throughout the year (dynamical downscaling) 45
Figure 27 – Decadal anomalies in rainfall with respect to the long-term average climatology 1961-1990; based on CRU TS 3.23 data. 46
Figure 28 – Average annual rainfall across Malawi, with pipeline implementation 47
Figure 29 – Average annual rainfall in the pipeline implementation area 48
Figure 30 – Total annual precipitation measured at the KIA weather station, between 1961 and 2011 50
Figure 31 – Monthly average precipitation measured at the KIA weather station, between 1961 and 2011 51
Figure 32 – Total annual precipitation for hydrological years, measured at the KIA weather station, between 1961 and 2011, and annual precipitation values corresponding to dry and wet year average limits 51
Figure 33 – Total annual precipitation measured at the Chitedze weather station, between 1997 and 2011 53
Figure 34 – Monthly average precipitation measured at the Chitedze weather station, between 1997 and 2011 54
Figure 35 – Total annual precipitation for hydrological years, measured at the Chitedze weather station, between 1997 and 2011, and annual precipitation values corresponding to dry and wet year average limits 54
Figure 36 – Total annual precipitation measured at the Salima weather station, between 1997 and 2011 56
Figure 37 – Monthly average precipitation measured at the Salima weather station, between 1997 and 2011 57
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix ix
Figure 38 – Total annual precipitation for hydrological years, measured at the Salima weather station, between 1997 and 2011, and annual precipitation values corresponding to dry and wet year average limits 57
Figure 39 – Observed trends in annual average near-surface temperature (°C per decade) over Africa for the 1961-2014 period based on CRUTEM4v data 59
Figure 40 – Observed trends in seasonal average near-surface temperature (°C per decade) over Africa for the 1961-2014 period based on CRUTEM4v data. 60
Figure 41 – Minimum temperatures (left) and maximum temperatures (right) registered across Malawi, with pipeline implementation course 61
Figure 42 – Average annual temperature in the pipeline implementation area 62
Figure 43 – Regional temperature projections for December-January-February in Southern Africa under the RCP4.5 scenario 63
Figure 44 – Regional temperature projections for June-July-August in Southern Africa under the RCP4.5 64
Figure 45 – Projected mean annual maximum temperature change based on statistical downscaling 65
Figure 46 – Projected mean annual maximum temperature increase based on dynamical downscaling 65
Figure 47 – Number of recorded climate-related events over southern Africa since 1980 66
Figure 48 – Southeast Africa’s observed daily precipitation: wet season duration (left); frequency of days with precipitation (right) 71
Figure 49 – Projections of total monthly rainfall, at the Chitedze, Salima and KIA stations, for the period 2021-2041, under the RCP4.5 scenario 72
Figure 50 – Projected change in the Chitedze weather station’s precipitation for 2046- 2065 from empirical downscaling of seven GCM: a) total monthly precipitation; b) monthly number of days with precipitation above 2 mm 73
Figure 51 – Projected average maximum temperature, at the Chitedze, Salima and KIA stations, for the period 2021-2041, under the RCP4.5 scenario 75
Figure 52 – Projected average minimum temperature, at the Chitedze, Salima and KIA stations, for the period 2021-2041, under the RCP4.5 scenario 76
x Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
Figure 53 – Heat spell duration measured at the Chitedze, Salima and KIA stations, for the period 2021-2041, under the RCP4.5 scenario 78
Figure 54 – Average dry spell duration measured at the Chitedze, Salima and KIA stations, for the period 2021-2041, under the RCP4.5 scenario 79
Figure 55 – Representation of the increase of CO2 emissions for Malawi, in the period 1990-2011 86
Figure 56 – Relevant roads (yellow) in the vicinity of the pipeline route (red) 88
Figure 57 – Local movements made mainly on foot by pedestrians or by bicycle 89
Figure 58 – Dust re-suspension from road traffic 89
Figure 59 – Energy use in urban and rural Lilongwe City 90
Figure 60 – Vegetation/crop residues burning 91
Figure 61 – Burnt clay bricks kiln 91
Figure 62 – Charcoal sale at the roadsides 92
Figure 63 – Farming areas around Lake Malawi 93
Figure 64 – Livestock grazing around Lake Malawi 93
Figure 65 – Annual mean ambient PM2.5 (µg/m3) 95
Figure 66 – Annual mean concentrations of fine particulate matter (PM2.5) in urban areas of Malawi (μ/m3) 95
Figure 67 – Malawi Water Resource Areas (WRA) and Water Resource Units (WRU) 97
Figure 68 – Lake Malawi, near the abstraction point (raw water pipeline km 0+200) 98
Figure 69 – Lake Malawi, near the abstraction point (raw water pipeline km 0+800) 98
Figure 70 – Lilongwe river (near pipeline km 33+700) 99
Figure 71 – Mpatsanjoka River North, at pipeline km 2+200 (1) 100
Figure 72 – Mpatsanjoka River North, at pipeline km 2+200 (2) 100
Figure 73 – Mpatsanjoka River South, at pipeline km 9+400 (1) 100
Figure 74 – Mpatsanjoka River South, at pipeline km 9+400 (2) 100
Figure 75 – Lumbadzi River, at pipeline km 84+000 (1) 101
Figure 76 – Lumbadzi River, at pipeline km 84+000 (2) 101
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix xi
Figure 77 – Kofula River, at pipeline km 96+100 (1) 101
Figure 78 – Kofula River, at pipeline km 96+100 (2) 101
Figure 79 – Mchenzi River, at pipeline km 107+000 (1) 102
Figure 80 – Mchenzi River, at pipeline km 107+000 (2) 102
Figure 81 – LWB sampling sites used for water quality assessment 104
Figure 82 – Fishing at Lake Malawi (1) – near raw water pipeline km 0+500, Lifuwu village 106
Figure 83 – Fishing at Lake Malawi (2) – near raw water pipeline km 1+100, Lifuwu village 106
Figure 84 – Water collection from Lake Malawi (1) – near raw water pipeline km 1+000, Lifuwu village 106
Figure 85 – Water collection from Lake Malawi (2) – near raw water pipeline km 1+000, Lifuwu village 106
Figure 87 – Farming areas around Lake Malawi, near pipeline km 6+000, TA Maganga 108
Figure 88 – Livestock grazing around Lake Malawi, near pipeline km 4+000, TA Maganga 108
Figure 89 – Market of fresh products along the M14 road 121
Figure 90 – Vegetable selling along S122 road 121
Figure 91 – Cultivated lands in study area: tilled lands (km 21+670, near Salima) 122
Figure 92 – Cultivated lands in study area: untilled lands (km 40+620, Ta Karonga) 122
Figure 93 – Dambo (km 9+350, Ta Maganga) (1) 123
Figure 94 – Dambo (km 7+480, Ta Maganga) (2) 123
Figure 95 – Permanent swamps and marshes in study area (km 109+450, Lilongwe City) 124
Figure 96 – Phragmites mauritianus (km 67+900, Ta Chiwere) 124
Figure 97 – Floating species in a swamp (km 2+250, Ta Kuluunda) 124
Figure 98 – Brachystegia boehmii (1) 125
Figure 100 – Julbernardia spp. 126
Figure 101 – Combretum sp. 126
xii Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
Figure 102 – Piliostigma thonningii 126
Figure 103 – Piliostigma thonningii (leaf) 127
Figure 104 – Bauhinia sp. 127
Figure 105 – Terminalia sericea 127
Figure 106 – Khaya anthotheca 127
Figure 107 – Eucalyptus sp. 128
Figure 108 – Gmelina arborea 128
Figure 109 – Toona ciliata 128
Figure 110 – Woodlands within study area: high diversity and complexity (km 58+700, Ta Chiwere) 129
Figure 111 – Woodlands within study area: low diversity and size (km 2+650, Ta Kuluunda) (1) 129
Figure 112 – Woodlands within study area: low diversity and size (km 57+000, Ta Chiwere) (2) 129
Figure 113 – Woodlands’ vegetation as feedstock (1) 130
Figure 114 – Woodlands’ vegetation as feedstock (2) 130
Figure 115 – Woodlands’ vegetation as feedstock (3) 130
Figure 116 – Woodlands’ vegetation as feedstock (4) 130
Figure 117 – Graveyard 131
Figure 118 – Lake Malawi and shore (km 0+700 Intake Pipeline, Leopard Bay/Salima) 131
Figure 119 – Human uses of Lake Malawi (1) 132
Figure 120 – Human uses of Lake Malawi (2) 132
Figure 121 – Human uses of Lake Malawi (3) 132
Figure 122 – Human uses of Lake Malawi (4) 132
Figure 123 – Aquatic fauna occurring in the study area: bivalve molluscs 133
Figure 124 – Aquatic fauna occurring in the study area: avifauna 133
Figure 125 – Human settlements and infrastructure areas within the study area (km 0+400, Leopard Bay/Salima) (1) 134
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix xiii
Figure 126 – Human settlements and infrastructure areas within the study area (km 96+150, Ta Chimutu) (2) 134
Figure 127 – Planted garden areas in the study area (1) 134
Figure 128 – Planted garden areas in the study area (2) 134
Figure 129 – Macro-scale vegetation framework of the study area 135
Figure 130 – Erythrophleum africanum 136
Figure 131 – Acacia polyacantha 138
Figure 132 – Aquatic bivalve mollusc shell 140
Figure 133 – Engraulicypris sardella (Usipa) 142
Figure 134 – Sun drying of usipa 142
Figure 135 – Trachylepis sp. 143
Figure 136 – Ceryle rudis (Pied Kingfisher) 145
Figure 137 – Ardea melanocephala (Black-headed Heron) 145
Figure 138 – Egretta garzetta (Little egret) and Scopus umbretta (Hamerkop) 145
Figure 139 – Domesticated livestock identified in settlements within the study area: goats 147
Figure 140 – Domesticated livestock identified in settlements within the study area: cattle 147
Figure 141 – Domesticated livestock identified in settlements within the study area: poultry (1) 147
Figure 142 – Domesticated livestock identified in settlements within the study area: poultry (2) 147
Figure 143 – Malawi Territory 148
Figure 144 – Administrative areas where the project develops 151
Figure 145 – Total population by sex and region, in 2008 152
Figure 146 – Population by Urban and Rural areas and by Region, in 2008 153
Figure 147 – Population distribution of persons aged 18 years and above by region and by sex, in 2008 154
Figure 148 – Household size by Region, in 2008 161
xiv Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
Figure 149 – Examples of existing houses in the project area, in TA Chiwere 163
Figure 150 – Examples of existing houses in the project area, in TA Maganga 163
Figure 151 – Examples of sources of drinking water, in TA Chiwere 165
Figure 154 – Examples of type of toilet facility, in TA Chiwere 167
Figure 155 – Annual growth rates the Malawi GDP, 2011-2018 173
Figure 157 – Examples of area agricultural in the project area, in Mwansango (TA Chiwere, Dowa District) 177
Figure 158 – Example of area fishing in the project area, in TA Kaluunda (Salima District) 178
Figure 159 – Example of wood products in the project area, in TA Karonga (Salima District) 178
Figure 160 – Example of wood products in the project area, in TA Karonga (Salima District) 179
Figure 161 – Example of sale agricultural products in the project area, in TA Maganga (Salima District) 179
Figure 162 – Example of sale the buck products in the project area, in TA Chiwere (Dowa District) 180
Figure 163 – Unemployment rate by districts, in 2008 181
Figure 164 – Percentage distribution of the employment persons by occupation 182
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix xv
ACRONYMS
a.s.l. – Above Sea Level
ACR – African Chiroptera Report
ADD – Agricultural Development Division
AFOLU – Agriculture Forestry and Other Land Use
ALARP – as low as reasonably practicable
ART – Antiretroviral Therapy
BOD – Biochemical Oxygen Demand
CCAM – Conformal Cubic Atmospheric Model
CEC – Cation Exchange Capacity
CIP – Climate Information Platform
CITES – Convention on International Trade in Endangered Species of Wild Fauna and Flora
CRU TS 3.23 – Climatic Research Unit Time Series, version 3
CRUTEM4 – Climatic Research Unit Temperature, version 4
CSAG – Climate System Analysis Group
D-# – Deliverable (number)
DEAT – Department of Environmental Affairs and Tourism
DICL – Ductile Iron Cement Lined pipe
DJF – December-January-February
xvi Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
DoCCMS – Department of Climate Change and Meteorological Services
E – East
EAD – Environmental Affairs Department
EARS – East African Rift System
EC – Electrical Conductivity
ECD – Early Childhood Development
EHS – Environmental, Health, and Safety Guidelines
EIA – Environmental Impact Assessment
EMA – Environment Management Act
EMP – Environmental Monitoring Plan
EMSP –Environmental and Social Management Plan
ENSO – El Niño Southern Oscillation
EPA – Environmental Protection Agency
ESIA – Environmental and Social Impact Assessment
EuDASM – European Digital Archive of Soil Maps
FAO – Food and Agriculture Organization of the United Nations
GCM – Global Climate Model
GDP – Gross Domestic Product
GHG – Greenhouse gases
GPS – Global Positioning System
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix xvii
H – Horizontal
ha – hectare
ha – hectare
I&APs – Interested and affected parties
IARC – International Agency for Research on Cancer
IBA – Important Bird Area
ICOMOS – International Council of Monuments and Sites
IDA – International Development Association
IFC – International Finance Corporation
ILO – International Labour Organization
IPCC – Intergovernmental Panel on Climate Change
IR – Inception Report
ITCZ – Inter–Tropical Convergence Zone
ITN – Insecticide-treated Net
IUCN –International Union for Conservation of Nature
JJA – June-July-August
KIA – Kamuzu International Airport
km – kilometre
LREP – Land Resources Evaluation Project
LWB – Lilongwe Water Board
xviii Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
m – metre m2 – square metre m3/day | m3/sec– cubic metre per day | per second
MAM – March-April-May
MASDAP – Malawi Spatial Data Platform
MK – Malawian Kwacha
MLFS – Malawi Labour Force Survey mm – millimetres
MoEST – Ministry of Education Science and Technology
MOH – Ministry of Health
MS – Malawi Standard
MSB – Malawian Standards Board
NEAP – National Environment Action Plan
NEP – National Environmental Policy
NGO – Non-Governmental Organisations
NPK – Nitrogen, Phosphorus and Potassium
NSO – National Statistical Office
NSOER – National State of Environmental Report
ODA – Official Development Assistance
OP – Operational Policy (World Bank)
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix xix
PCP – Public Consultation Programme
PE – Primary Education
PGA – Peak Ground Acceleration
PM – Particulate Matter
RAMSAR – Convention on Wetlands of International Significant
RAP – Resettlement Action Plan
RCP – Representative Concentration Pathways
S – South
SADC – Southern African Development Community
SC – Senior Chief
SON – September-October-November
SPI – Standard Precipitation Index
SRTM – Shuttle Radar Topographic Mission
SST – Sea Surface Temperature
TA – Traditional Authorities
TDS – Total Dissolved Solids
TFR – Total Fertility Rate
ToR – Terms of Reference
TRMM – Tropical Rainfall Measuring Mission
UN – United Nations
xx Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
UNDP – United Nations Development Programme
UNESCO – United Nations Educational, Scientific and Cultural Organization
UTM – Universal Transverse Mercator
V – Vertical
VECEA –Vegetation and Climate Change in Eastern Africa
VOC – Volatile Organic Compound
WB – World Bank
WHO – World Health Organisation
WRU - Water Resources Units
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix xxi
Blank page
xxii Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
1. Introduction
The present appendix describes in further detail the environmental and social baseline of the Lake Malawi Water Supply Project for Lilongwe City, expanding upon the synthesis presented in section 5 of the ESIA Report (Volume 1). Support maps are presented in Volume’s 1 Annex.
The following biophysical and socio-economic issues were screened according to the type of project and the region it crosses:
• Geology, topography and hydrogeology • Soils; • Climate and meteorology; • Air quality; • Surface water quality; • Ecology, flora and fauna; • Socioeconomics and public health.
The Environmental and Social Baseline reports to a study area that comprises the project and intervention areas available at this stage, as well as their surroundings, specifically defined according to each environmental factor’s needs. However, a 12 m default buffer (6m to each side of the pipe centreline) was considered as the main directly affected area in the general case.
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 1
Blank page
2 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
2. Geology, Topography and Hydrogeology
2.1. Introduction
The characterisation of the current geomorphological, geological and hydrogeological setting is the baseline reference for the assessment of impacts in this study.
Since the potential impacts on geology, topography and groundwater are localised, not reflected in areas distant from the project site, the study area here considered refers to the 112 km of water pipelines and its immediate surroundings on a 100-m buffer zone (50 m per each side of the pipeline), except for those aspects of regional reach, needed to understand the study area (e.g. seismic hazard).
The present description of the geomorphological and geological aspects is based on sheets 23 (Lilongwe-Dowa Area, 1972) and 30 (Salima-Mvera Mission Area, 1970) of the geological map of Malawi at 1: 100,000 (Thatcher & Walter, 1968; Walter, 1972, respectively). However, other sources of information included fieldwork undertaken in the study area (December 2017) and specific studies such as those related to seismic hazard and geotechnical investigation.
This characterization includes descriptions of the following topics for the area:
• Geomorphology; • Geology; • Geohazards; • Geologic resources with economic and conservation interest; • Hydrogeology: type of aquifer; • Groundwater quality.
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 3
2.2. Regional geomorphology
The study area is in the gently undulating South Lilongwe Plain. Four major erosion surfaces have been recognised in this area (Lister, 1965):
• Post-Gondwana residuals; • African erosion surface; • Post-African erosion; • Quaternary erosion and deposition.
The oldest of these, the post-Gondwana surface of early and mid-Cretaceous age is now merely represented by residuals (inselbergs) which rise above the level of the surrounding plain.
The African cycle of erosion, which occurred in late Cretaceous – early Miocene formed an extensive plain in the Central Region of Malawi of which the South Lilongwe Plain is but a part. This surface reached a state of extreme old age, characterised by its monotonous flatness, before the post-African cycle of erosion was initiated in late- Miocene times.
The mature African surface is slightly downwarped in the vicinity of Lilongwe, this feature possibly being associated with Rift Valley faulting in the area to the east. Incipient post- African erosion has penetrated along the floor of the major river valleys and in places a composite surface results, the African and post-African surfaces merging gently and indiscernibly on the interfluves.
Quaternary surfaces of both an erosional and a depositional origin are found in Malawi although these generally of only limited extent, being largely confined to the floor and sides of the rift valley. The width of the Quaternary lakeshore plain which surrounds Lake Malawi varies considerably between less than 1.6 km and more than 16 km. In the study area it reaches some linear 30 km. In the wider parts this plain is generally covered by recent sands and alluvium which therefore represent Quaternary deposition. Youthful Quaternary erosion occurs along the crest of the rift valley escarpment wherever streams and rivers notch the crest and face of the scarp. This erosion sometimes continues headwards for several miles from the edge of the escarpment in the valleys of the larger rivers (Lister, 1965).
4 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
The area is drained by rivers flowing eastwards into the Lake Malawi. From the West to the East five river crossings were identified: Mchenzi river, Kofula river, Lumbadzi river and two crossings at the Mpatsanjoka river.
The study area spans from around 1310 m (a.s.l) in the West down to 476 m (a.s.l) in East by the Malawi Lake (See Volume 1 Annex – Map GEO1).
Figure 1 - Longitudinal survey of altimetry along the design trajectory
Slope angles may change dramatically along the study area. In general terms, the stretch can be divided in three sections (See Volume 1 Annex – Map GEO2):
• 1) All intake project + Pipeline project from km0 to km52+800 – The area is dominated by low slope angles (<10º); exceptions to this main trend occur in the intake project and in the first 6 km and between 39 km and 45 km of the pipeline project where there are areas nearby with slope angles above 15º; • 2) Pipeline project from km52+800 to km84+100 – stretches with slope angles higher than 15º are frequent in nearby areas; • 3) Pipeline project from km84+100 to km110+076 – The area is dominated by low slope angles (< 10º).
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 5
2.3. Geology
The South Lilongwe Plain and Dzalanyama Range are largely underlain by granulites, gneisses and schists of the Precambrian Basement Complex; on the lakeshore plain this basement complex is, for the most part, obscured by thick superficial deposits which include residual soils, alluvium and colluvium (Table 1 and Volume 1 Annex – Map GEO3). Table 1 – Dominant lithology along the study area Lithology Project Chainage (km+mmm) Biotite-granite and sandy soil Intake Pipeline km0+500 – km0+800 and colluvium Sandy soil and colluvium Intake Pipeline km0+800 – km1+936 Sandy soil and colluvium Treated Water Pipeline km0+000 – km0+800 Recent lakeshore and river alluvium including terrace Treated Water Pipeline km0+800 – km1+200 deposits Sandy soil and colluvium Treated Water Pipeline km1+200 – km9+200 Undifferentiated lakeshore Treated Water Pipeline km9+200 – km27+500 alluvium Red-brown sandy clay soil Treated Water Pipeline km27+500 – km37 + 500 Charnockitic gneiss and granulite + veins of graphitic Treated Water Pipeline km37 + 500 – km53 + 500 gneiss and granulite Biotite-gneiss, garnetiferous in Treated Water Pipeline km53 + 500 – km75 + 500 part and Graphitic biotite-gneiss Biotite-hornblende-gneiss Treated Water Pipeline km75 + 500 – Km81 + 500 Graphitic biotite-gneiss Treated Water Pipeline Km81 + 500 – km94 + 000 Quartzo-feldspathic granulite Treated Water Pipeline km94 + 000 – km98 + 200 and gneiss Biotite-gneiss, garnetiferous in Treated Water Pipeline km98 + 200 – km98 + 400 part Red-brown sandy clay soil Treated Water Pipeline Km98 + 400 – km101 + 000 Biotite-gneiss, garnetiferous in Treated Water Pipeline Km101 + 000 – km 101 + 800 part Red-brown sandy clay soil Treated Water Pipeline Km101 + 800 – km105 + 500 Biotite-gneiss, garnetiferous in Treated Water Pipeline Km105 + 500 – km 106 + 800 part Km 106 + 800 – km 110 + Red-brown sandy clay soil Treated Water Pipeline 076
6 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
2.4. Geohazards
2.4.1. Neotectonics and seismicity
Malawi is within the most seismically active belt of the East African Rift System (EARS). The EARS extends from the Red Sea/Gulf of Aden to Malawi and it is seismically active beyond. In its actual configuration it presents two main rift branches, the Western and the Eastern Rifts (Figure 2). The Western Rift of deep lakes and few volcanoes bends about the eastern edge of the Kenya dome from Uganda to Tanzania continuing south to Malawi (Figure 2).
The Western Rift is characterised by moderate magnitude earthquakes (M ≤ 6.0). Historical records show strongly felt earthquakes reported in various parts of Malawi, but no damage to property or loss of life has been recorded until the occurrence of the 1989 Salima Earthquake, a magnitude 6.6 quake, occurred on March 10, 1989 in central Malawi (Figure 3), which claimed a few lives and damaged some property.
An estimation of seismic hazard for hard rock sites shows that peak ground acceleration (PGA) for a 10% probability of exceedance in 50 years (475 years return period) for the entire country range from 180-240 gals. These values correspond to Modified Mercalli Intensity (IMM) of about VIII (Chapola, 2001). Such intensity would cause damage to ordinary brick buildings and completely destroy clay buildings. A 10% probability of exceedance in 100 years (950 years return period) gives PGA values ranging from 220- 320 gals which are equivalent to IMM of VII-IX. For a 50-year return period, PGA values range from 0.70 to 0.95 m/s2 (IMM of VI-VII). In principal cities of Mzuzu, Lilongwe and Blantyre, PGA values of 0.80 to 1.30 m/s2 corresponding to IMM of VI-VII are expected every 50-100 years (Chapola, 2001). These values are in accordance to those obtained by the USGS for the southeast Africa (Figure 4). According to these authors, PGA values in the study area span from 0.60 to 1.00 m/s2.
Since the building code of Malawi has no consideration of earthquake ground motion, the anticipated intensities, at all return periods considered, would cause tremendous damage to buildings and would have adverse social and economic impacts. Malawi is today under considerable development; hence it is expected that vulnerability to earthquakes will continue to increase with time.
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 7
Source: Baker et al. (1972) in Saemundsson (2010) Source: http://earthquake.usgs.gov/learn/today/ index.php?month=3&day=10&submit=View+Date
Figure 2 – The Afro-Arabian rift system Figure 3 – Epicentre of 1989 Salima Earthquake, (continental graben and depressions are shaded) a magnitude 6.6 quake, occurred on March 10, 1989 in central Malawi
8 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
Source: USGS (2006)
Figure 4 – Seismic hazard for Southeast Africa expressed as peak ground acceleration (PGA)
2.5. Economic geology
Graphitic biotite-gneiss occur in the study area [km53+500 – km75+500 (Dowa District/ TA Chiwere - SC Mkukula) and km81+500 – km94+000 (Dowa and Lilongwe Districts / SC Mkukula -TA Chimutu, respectively)], with different areas being signed in the geological map for the occurrence of graphite (See Volume 1 Annex – Map GEO3).
Sand suitable for building purposes is available along the major rivers (alluvial sands) and also along the lakeshore plain area (See Volume 1 Annex – Map GEO3).
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 9
Dambo clays and red-brown lateritic clay soils such as those found around the study area are often suitable for brick-making. As a result, several borrow pits were identified close to the main road (Figure 5 and Figure 6).
Source: NEMUS (2017)
Figure 5 – Borrow pits located close to the main road (km 3+900 – Salima District/TA Maganga)
10 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
Source: NEMUS (2017)
Figure 6 – Borrow pit located close to km3+900 – Salima District/TA Maganga
A quarry exploring quartzo-feldspathic granulite and gneiss was also identified near km95+400 (Figure 7).
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 11
Figure 7 – Quarry located close to the study area (km 95+400 – Lilongwe District / TA Chimutu)
Another geological resource is groundwater. For its importance and interest in this project this topic will be dealt separately in a following subchapter.
12 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
2.6. Hydrogeology: type of aquifer and other general aspects
The study area spans across different vast aquifer systems of Malawi (Figure 8), namely:
• Alluvial Aquifers that are situated along the lakeshore and the river flood plains. Depth to groundwater varies between 10 m to 30 m below ground surface, but may well be shallower. • Weathered Basement Aquifers that occur on the low relief plateau areas and at the base of the escarpments where a well-developed transitional zone between the bedrock and the top argillised layer constitutes the main groundwater-bearing horizon. The depth to groundwater varies between 15 to 25 m below ground surface.
Between these two hydrogeological regions there is also the fresh basement region (Figure 8). Areas composed of fresh basement normally do not define important hydrogeological regions as they are impermeable with little groundwater-bearing capacity. Nonetheless, in Walter (1972) some boreholes are reported to be tapping water in fracture zones, particularly in quartzites.
The entire intake project and the pipeline project roughly from 0km+000 to 38km+000 (Salima District / TA Kuluunda; TA Maganga; Salima Town; TA Karonga) is in alluvial aquifers. From 38km+000 to 103km+000 (Salima District / TA Karonga; Dowa District / TA Chiwere and SC Mkukula; Lilongwe District / TA Chimutu) the pipeline project runs over fresh basement. From 103km+000 to 110km+076 (Lilongwe District / TA Chimutu and Lilongwe City) the pipeline project runs over weathered basement aquifers (see Volume 1 Annex – Map GEO3).
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 13
Figure 8 – Hydrogeological regions of Malawi
2.7. Alluvial aquifer system
The pipeline project runs over the alluvial aquifer system for the first 38 km and also for the whole terrestrial portion of the intake project.
Groundwater table seems to be spatially variable going from at or very close to the surface at positions close to the river channels (Michael Pavlakis and Associates, 2017), to much deeper levels when away from river channels. For instance, these same authors did not find the water table at railway crossings where trial holes were excavated, which means that it is below the excavated depth (most of the time at 5 m). At the same time, monitoring of three boreholes reported in Aurecon (2011) indicate depths higher than 5 m to reach the water table in boreholes located more than 1.7 km away from a major river (Table 2) (See Volume 1 Annex – Map GEO3).
14 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
Table 2 – Results from different monitoring campaigns held in the alluvial aquifer and near the pipeline project
Borehole/ Static Depth of Trial water EC the pH T (ºC) Date holes level (μs/cm) borehole excavated depth GN214* 6.55 44.72 16200 7.5 28.8 Feb 2011 GN215* 5.72 40.70 2600 8.3 29.2 Feb 2011 GN164* 10.10 31.96 11900 7.7 28.2 Feb 2011 MR1-1** 0.60 - - - - Mar 2017 MR1-2** 1.00 - - - - Mar 2017 MR2-1** 0.60 - - - - Mar 2017 MR2-2** 0.70 - - - - Mar 2017 MR2-3** 0.70 - - - - Mar 2017 * Aurecon (2011); ** Michael Pavlakis and Associates (2017)
2.8. Weathered basement: aquifer properties
The last 7 km of the pipeline project runs over weathered basement aquifers. In this type of aquifer system, the alteration zone is 15 m to 30 m thick on the plateau and sometimes more. In the Lilongwe area for instance it can reach more than 40 m (see Appendix - Drawing 3). Normally, the alteration zone is thinner near rock outcrops and thicker in the faulted zones.
It is possible to distinguish from bottom to top:
• The fractured and unaltered substratum where water is found only in the fractures; • The dislocated substratum with impermeable blocks, where the water is found in the gaps. The size of blocks declines rapidly in the vertical direction and they acquire a sandy or gravely texture, with the original structure more or less preserved.
The formation becomes less consolidated from bottom to top. The upper layers consist mainly of sandy clays and argillaceous sands overlain close to the surface by compact clays.
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 15
The groundwater is usually under slight pressure beneath the clay strata. The available yields depend on the thickness of the water-bearing stratum. It is usually possible to count on an aquifer 10 m thick for rural boreholes equipped with hand pumps. If the water-bearing stratum is too thin or the depth to water too great, the available yields will probably be insufficient. In addition, the alteration formation must not be too argillaceous. Lateritic strata are often found, particularly when the aquifer is close to the surface, for fluctuations in the water level lead to their formation. The lateritic fossil crusts have very poor porosity and permeability and therefore do not facilitate infiltration.
The exploitation of rural wells is limited by the capacity of the hand pump with which they are equipped (0.25 to 0.50 l/s). Similar yields can be expected from all the alteration formations of the crystalline basement, provided that they are sufficiently thick, and it is probable that this result can be obtained without prior geophysical prospecting.
In fact, it is the thickness of the saturated alteration stratum rather than the depth of the borehole which determines a satisfactory yield. For example, at Lilongwe international airport yields of 1.5 to 5.0 l/s were obtained from alteration formations 20 to 29 m thick, under pressure beneath the compact clays.
2.9. Groundwater quality
From the limited information available, groundwater compositions in Malawi appear to be spatially variable and highly dependent on aquifer lithology (BGS, 2004).
In Chilton & Smith-Carington (1984), the authors refer that the chemical quality of groundwater in the plateau areas (weathered basement) is generally good, indicating that the weathered zone is highly leached of solute minerals, and groundwater is likely to be derived from relatively recent recharge. Although this paper is quite outdated in terms of what is the present-day quality of water in the aquifer, its interest lays on the fact that there seems to be no natural process affecting the quality of groundwater in a regional scale. These authors refer that water can be classified as predominantly calcium-bicarbonate type, although in some cases cation exchange may have occurred and magnesium or sodium may be dominant.
16 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
Table 3 summarises the results from quality analyses performed in 43 samples of groundwater from the Lilongwe area. From this summary, it appears that groundwater in selected areas may have high values of electrical conductivity (EC) (40% of the analysed samples) and high concentrations of total dissolved solids (TDS) (35%) and calcium (30%). Values of turbidity were also high in 28% of the analysed samples. High concentrations of fluoride, reaching concentrations of 4.5 mg/l, have been reported for the area of Nathenje (SE from Lilongwe city) (Msonda et al., 2007). Nonetheless, concentrations in the Lilongwe area seem to be lower and only two samples showed contents higher than 1.5 mg/l.
Table 3 – Parameters from groundwater in the Lilongwe area (weathered basement aquifer) from 1997 and 1999 (N = 43) and drinking water quality standards and guidelines from MBS (2013) and WHO (2017)
% of samples with Range MBS WHO Parameters concentrations (Groundwater) standard guidelines above guidelines
pH 6.3 – 8.8 - 5.0 – 8.5 6.5 – 8.5
EC (µS/cm) 81 - 2010 40 700 - 1500 -
TDS (mg/l) 72 - 1307 35 (> 450) < 500 < 1000
CO3 (mg/l) 0 - 67 - - -
HCO3 (mg/l) 35 - 586 - - -
Cl (mg/l) 4.0 – 58.1 - 100 - 200 < 200
SO4 (mg/l) 1.8 - 870 9 (> 200) 200 - 400 < 250
NO3 (mg/l) 0 – 11.3 - - < 50
38 (> 0.7); F (mg/l) 0.10 – 1.58 0.7 – 1.0 < 1.50 5 (> 1.5)
Na (mg/l) 7 - 210 7 (> 100) 100 - 200 < 200
K (mg/l) 0.7 – 8.1 - 25 - 50 -
100-300 (taste Ca (mg/l) 6.4 – 262.4 30 80 - 150 threshold)
Mg (mg/l) 4.0 – 62.2 9 30 - 70 -
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 17
% of samples with Range MBS WHO Parameters concentrations (Groundwater) standard guidelines above guidelines
Fe (mg/l) 0.01 – 0.35 9 - < 0.30
Turbidity 1 - 65 28 0.1 – 1.0 - (NTU) Source: adapted from WRDPS (2000)
Through scrutiny of the information and data in the WRDPS (2000) one concludes that groundwater in general can be classified as suitable for drinking purposes and only in few rather limited areas data indicates otherwise. It should be noted however that this data was collected between 1997 and 1999 and present-day conditions may have changed considerably. On the other hand, results of organic and bacteriologic analyses were not reported in the WRDPS (2000) and these parameters may well condition the suitability of groundwater for drinking purposes.
There is only one station in the alluvial aquifer, and close to the pipeline project (~580 m), for which recent data was found (Table 1). Considering drinking water quality standards from Malawi, water quality on this well is only fair to what concerns electrical conductivity, total dissolved solids and fluoride. The rest of the parameters for which MBS standards are defined indicate good quality of water.
Table 4 – Quality results from a monitoring well located in the alluvial aquifer, in the Kambwiri Sere Irrigation Scheme (Salima district) and drinking water quality standards and guidelines from MBS (2013)
Monitoring Well Parameters MBS standard (GN214)
pH value 6.95 6.5 – 8.5
Temperature (ºC) 25.7 -
Electrical conductivity 1164 700 - 1500 (µs/cm)
Total Dissolved Solids 597 <500 (mg/l)
18 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
Monitoring Well Parameters MBS standard (GN214)
Carbonate (as CO32-) (mg/l) 0.00 -
Bicarbonate (as HCO32-) 638 - (mg/l)
Chloride (mg/l) 36.2 100 - 200
Sulphate (as SO4) (mg/l) 17.2 200 - 400
Nitrate (as NO3) (mg/l) 0.061 -
Fluoride (mg/l) 0.74 0.7 – 1.0
Sodium (mg/l) 41 100 - 200
Potassium (mg/l) 3.4 25 - 50
Calcium (mg/l) 62.5 80 - 150
Magnesium (mg/l) 23 30 - 70
Total Iron (mg/l) <0.001 0.01
Manganese (mg/l) <0.001 0.05
Total Hardness (mg/l) 500 -
Total Alkalinity (mg/l) 523 -
Silica (as SiO2) 8.0 -
Turbidity (NTU) 4.0 0.1 – 1.0
Suspended Solids (mg/l) 2.0 -
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 19
Monitoring Well Parameters MBS standard (GN214)
Phosphate (as PO4) (mg/l) 1.630 <0.150
Lead (as Pb2+) (mg/l) 0.027 <0.01
Copper (Cu2+) (mg/l) 0.002 <1.0
Dissolved Oxygen (mg/l) 9.1 -
Biochemical Oxygen 10.9 - Demand (mg/l)
Chemical Oxygen Demand 43.1 - (mg/l)
Faecal coliform 0 10* (Counts/100 ml)
Faecal streptococci 0 0* (Counts/100 ml) Source: data provided by LWB (2018); Note: * 1% of sample as allowable compliance contribution
20 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
3. Soils
3.1. Introduction
Soil is a decisive natural resource, from which a variety of environmental and human processes depend, with trade-offs occurring with agricultural development, water availability, and extreme weather events.
In Malawi, as in other African countries, the challenge to address soil problems is of even more pressing needs, once the African region combines hunger and poverty, along with water limitations presented by extreme events – wildfires, storms, droughts, floods, heat and dry spells, as presented in “Climate and Meteorology”, section 4.
Soil, apart from being the support to ecosystems and habitats, in Malawi and in peri- urban/ rural areas, as the projected area for the pipeline implementation, agriculture presents itself as an essential soil use that cannot be neglected. In order to evaluate the component “Soils”, this assessment will proceed to the characterization and analysis of the study area soils capability and risks upon it.
The knowledge of its physical and chemical properties allows to determine its respective importance/aptitude to given soil uses or functions – nutrient exchange/retention, fertility, infiltration vs. surface runoff, etc.
Soils conservation and its management, namely by guaranteeing the most adequate and suitable uses, are two crucial aspects to assess the future availability of resources and to preserve all systems supported by them.
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 21
3.2. Soil characterization
The characterization of the soils present in the pipeline implementation area is based on the analysis of two soil maps:
• Soil map of Malawi compiled by M.W. Lowole1 (1983), for the Department of Agricultural Research; • Soil types in the country of Malawi (GeoNode, 2013, available at MASDAP), according to the FAO-UNESCO classification system.
According to the classification of soil types provided by GeoNode (2013), the future pipeline area fits several soil types, mainly due to its large coverage area. The most part of the pipeline sits on Chromic Luvisols and Eutric Cambisols (FAO, 1988), which are characterised by:
• Chromic Luvisols – The mixed mineralogy, high nutrient content, and good internal drainage of these soils makes them potentially suitable for a wide range of agricultural uses due to their moderate stage of weathering and high base saturation. Luvisols form on flat or gently sloping landscapes under climatic regimes that range from cool temperate to warm Mediterranean. This soil type appears in the landform “plains”, which is a deep, well drained, dark brown, medium over medium to fine textured soil of moderate chemical fertility. It is important to mention that Luvisols with high silt content are susceptible to structure deterioration if tilled in wet condition and/or with heavy machinery. In steep slopes, these soils, although structurally sound, require erosion control measures. • Eutric Cambisols – Cambisols are developed in medium and fine-textured materials derived from a wide range of rocks, mostly in alluvial, colluvial and aeolian deposits. They make good agricultural land and are intensively used. The Eutric Cambisols of the Temperate Zone are among the most productive soils on earth. This soil type appears in the landform “uplands”, which is a moderately deep soil, well drained, brown, coarse to medium over medium textured soil, with gravelly subsoil.
1 Based on the work of Young & Brown (1962), Brown and Young (1965), Stobbs (1975), Soil Survey Unit Reports, among others.
22 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
Other soil types with relevant presence in the projected pipeline implementation area are:
• Haplic Lixisols – the landform “ridges in uplands” is a very deep, well drained, red, coarse and medium over medium textured soil of moderate chemical fertility. • Haplic Luvisols – correspondence with the landform “foot slopes” which is a very deep, well drained, brown, medium textured soil of medium chemical fertility. • Eutric Fluvisols – the landform “outwash plains” is a very deep, imperfectly drained, dark brown soil with medium over fine texture, and with high chemical fertility. • Cambric Arenosols – the landform “beach ridges” is a very deep, well drained, coarse textured, yellowish brown soil of low chemical fertility. • Vertic Cambisols – the landform “bottom lands” is a very deep, poorly drained, of fine texture (mainly clay particles), with moderate chemical fertility, very low concentrations of N and P, but high concentrations of K. This type of soil is not susceptible to erosion, but does experience frequent flooding and severe ponding events. • Eutric Vertisols – the landform “depressions” is a very deep, poorly to imperfectly drained, of fine texture (sandy clay loam particles), with moderate chemical fertility, very low concentrations of N and P, but high concentrations of K. This type of soil is susceptible to slight erosion and severe ponding, but almost exceptionally does flooding occur.
The types of soils present in the pipeline area present two types of parent materials:
• A - Fluvial, colluvial and/or lacustrine sediments • X - Felsic and intermediate igneous and metamorphic rocks
The soil groups present in the project area are:
• a - Arenic soil group. Arenic soils have a sand or loamy sand texture throughout the upper 100 cm (or less if soil depth is less). • e - Eutric-fersialic soil group. Eutric-fersialic soils have a medium to high CEC- clay (>24 me/100g) in most of the upper 100 cm and a moderate to high base saturation (>50 percent) throughout the upper 50 cm. The relatively high CEC- clay indicates a limited advance of the ferrallitization process and the presence of weatherable minerals. The high base saturation indicates a low degree of
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 23
leaching and the presence of exchangeable bases, particularly calcium, magnesium and potassium. • f - Fluvic soil group. Fluvic soils are soils which are continuously rejuvenated through the deposition on the surface of sediments transported by water. They are derived from alluvium and are mostly very deep. There may be a considerable variation in particle size, both vertically in the profile (stratification) and horizontally. Gravelly layers can be observed in a minority of the profiles. • p - Paralithic soil group. Paralithic soils have highly weathered rock which starts at within a depth of 75 cm from the surface and continues to a depth of at least 150 cm from the surface. The soil above the weathered rock is often skeletal (>40 percent coarse mineral fragments). The weathered rock provides a foothold for roots, but only holds limited available moisture and nutrients. • x - Eutric-ferralic soil group. Eutric-ferralic soils have a low CEC-clay (<24 me/100g) in most of the upper 100 cm and a high base saturation (>50 percent) throughout the upper 50 cm. • v - Vertic soil group. Vertic soils have clayey topsoil’s (>30 percent clay) and deep, wide cracks when dry.
According to (Venema & Lorkeers, 1991), the various parent materials found in the survey area can be sub-divided according to the dominant slope. There are five classes covering the range of 0 to 55 % slopes, and are symbolized by the numbers 1 to 5:
• 1: 0-2%, flat to almost flat land • 2: 2-6%, gently sloping land • 3: 6-13%, sloping land • 4: 13-25%, moderately steep land • 5: 25-55%, steep land
Erro! Autorreferência de marcador inválida.Table 5 classifies the soil types present in the pipeline area according to the system used by LREP, designed specifically for use in Malawi (Venema, 1990).
An extract of the Malawi’s Soil Map compiled by Lowole (1983), with the projected pipeline implementation course highlighted in yellow is presented next, in Figure 9 and Map SOL1 (see Volume 1 Annex). Figure 10, and in detail the Map SOL2 (see Volume 1 Annex), shows Malawi’s soil types, focused on the projected area for the pipeline implementation course (in purple) and its vicinity, according to data by GeoNode (2013), available at MASDAP.
24 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
Table 5 – Soil classification according to LREP system: characteristics and properties of soil types present in the pipeline area
Cambic Eutric Haplic Vertic Chromic L Eutric Ca Eutric Fl Haplic Li Ar Ve Lu Ca Soil unit A1a1 X1e5 X2e5 X3e1 X4e4 X3p3 X4p2 A1f2 A1f4 A1f5 A1v2 X1x6 X2x3 A1e3 A1v1 Parent A X X X X X X A A A A X X A A material e - a - x - eutric- v - Group e - eutric-fersialic p - paralithic f - fluvic v - vertic eutric- arenic ferralic vertic fers. Slope 13- 13- 0-2% 0-2% 2-6% 6-13% 6-13% 0-2% 2-6% 0-2% (%) 25% 25% ridge outwas Landfor beach plain uplan upland hillside hillside flood depressi depressi s in uplan foot bottom uplands h m ridges s ds s s s plains ons ons uplan ds slopes lands plains ds Chemical mode moder low low low - low moderate high moderate fertility rate ate slight to moder Erosion slight slight none slight none moderate ate >150 >150 100- 50-100 100- Depth 100-150 >150 (very (very 150 (moderately >150 (very deep) 150 (cm) (deep) (very deep) deep) deep) (deep) deep) (deep
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 25
Cambic Eutric Haplic Vertic Chromic L Eutric Ca Eutric Fl Haplic Li Ar Ve Lu Ca Soil unit A1a1 X1e5 X2e5 X3e1 X4e4 X3p3 X4p2 A1f2 A1f4 A1f5 A1v2 X1x6 X2x3 A1e3 A1v1 Dark Dark Yellowis Reddish brown to Variabl Dark Dark Dark red to Colour brow Brown Red Brown Black h brown e grey brown grey brow n n Coar Medi Medi Coarse to Variabl se to Mediu Texture Coarse um to Coarse to fine Medium to fine Fine um to Fine medium e medi m fine fine um Topsoil sand to sandy sandy loam to variabl loamy sand to sandy loam to sandy part. size loamy loamy sand to sandy loam clay clay loam e sandy clay loam clay loam (0-30 cm) sand loam Subsoil sand to sandy loam to sandy sandy loam to sandy clay variabl sandy loam to sandy clay loam to part. size loamy sandy clay loam, clay clay loam e sandy clay loam sandy clay (>30cm) sand skeletal loam poorly to poorly to imperf Drainage well poorly imperfec imperfec well poorly ectly tly tly none to excepti freque Flooding none frequent exceptio none onal nt nal moder moder Ponding none severe severe none severe ate ate
26 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
Cambic Eutric Haplic Vertic Chromic L Eutric Ca Eutric Fl Haplic Li Ar Ve Lu Ca Soil unit A1a1 X1e5 X2e5 X3e1 X4e4 X3p3 X4p2 A1f2 A1f4 A1f5 A1v2 X1x6 X2x3 A1e3 A1v1 5.5 - 5.0 - 5.0 - 5.5 - 7.0 - pH 5.0 - 6.5 5.5 - 6.5 5.5 - 6.5 7.0 - 8.0 5.0 - 6.5 6.5 6.5 6.5 7.0 8.0 2-4 Salinity 0-2 (none) (slight) CEC <5 (very >10 (medium to 5-10 (low) >10 (medium to very high) 5-10 (low) (me/100g) low) very high) <0.08 0.08- <0.08 <0.08 N <0.08 (very 0.08-0.12 0.08-0.12 (low) (very 0.12 (very 0.08-0.12 (low) (very (%) low) (low) low) (low) low) low) >18 >18 <6 <6 P (mediu 6-18 6-18 (mediu <6 (very (very <6 (very low) 6-18 (low) 6-18 (low) (very (ppm) m - very (low) (low) m-very low) low) low) high) high) K >0.2 (medium to very high) (me/100g) Source: (Venema, 1990), (Venema & Lorkeers, 1991).
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 27
Source: Lowole (1983) with consultants’ work (2018)
Figure 9 – Soil types of Malawi (extract) with projected pipeline implementation (in yellow)
28 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
Source: GeoNode (2013) with consultant’s work (2018), available at: http://www.masdap.mw/layers/geonode%3Amw_soils
Figure 10 – Soil types of Malawi with projected pipeline implementation course (in purple)
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 29
The following figures (Figure 11, Figure 12 and Figure 13) show different soil types captured during the field works, in three distinct areas of the pipeline area of implementation – Salima, Dowa and Lilongwe, respectively.
Source: NEMUS (2017)
Figure 11 – Soil type (Salima area)
Source: NEMUS (2017)
Figure 12 – Soil type (Dowa area)
Source: NEMUS (2017)
30 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
Figure 13 – Soil type (Lilongwe area)
3.3. Soil suitability
In the Malawian context, the soil suitability for agriculture is the a very important indicator of soil use, especially considering the dependency of a great portion of the population from this activity for subsistence. The soils of the study area could be considered, in general, soils of good quality (especially in terms of structure and drainage), although marked by potential nutrient limitations.
In LREP classification (Venema & Lorkeers, 1991), a set of meteorological, hazardous, physical and chemical factors was pondered to evaluate the land quality and suitability for the Lilongwe ADD (which reaches part of the pipeline implementation area – Figure 14). These factors determine both the suitability and agricultural potential for a number of uses, such as rain-fed cultivation, wetland rice cultivation and forestry.
According to Venema & Lorkeers (1991), the soils in Lilongwe ADD are generally very deep, well drained, red to reddish brown and have a coarse to medium topsoil overlying a medium to fine textured subsoil. Poorly drained, regularly inundated soils occur in a few areas.
Reaction is acid to slightly acid (pH 5.0 to 6.5) for almost all soils. The nutrient status of most soils under cultivation is low with widespread deficiencies of nitrogen and phosphorus. The structure of most cultivated topsoil’s is weak, owing to the cultivation practices of intensive hoeing, and not returning enough organic matter to the soil. Topsoil’s are therefore highly erodible, and sheet erosion is taking place in most areas of Lilongwe ADD (Venema & Lorkeers, 1991).
According to the assessment of suitable uses for the Lilongwe ADD areas (provided by Venema & Lorkeers, 1991), the soils in the study area are moderately suitable for crops of maize, groundnuts and tobacco, as well as for most of the forest species (especially the Eucalyptus, Gmelina and Melia species).
A characterization of the soils in Salima ADD and Kasungu ADD was not found in bibliographic sources.
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 31
Source: (Venema & Lorkeers, 1991) with consultants’ work (2018)
Figure 14 – Location of ADD areas in Malawi (pipeline implementation area projected in yellow)
32 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
3.4. Slopes
As presented in subchapter “2.2” and in the Map GEO2 (see Volume 1 Annex), slope angles vary along the pipeline implementation area, although, in general terms, the area is dominated by low slope angles.
From a soils perspective, some sections can present a greater risk due to the nearby areas nearby with slope angles above 15º, such as, the section of intake project, in the first 6 km, between km 39-45 and from km 52 to km 84.
Near accentuated slopes, the most frequent risks to occur are landslides and increased surface runoff, especially if the soils are not well drained or have been compacted over its capacity (for example, due to heavy machinery traffic).
Despite some sections of nearby higher slope angles, the pipeline project implementation area is mostly dominated by low slope angles (< 10º).
Figure 15 presents an extract-view of the soil slopes of Malawi with the projected pipeline implementation area.
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 33
Source: SRTM data with consultant’s work (2018)
Figure 15 – Soil slopes of Malawi (extract) with pipeline implementation
34 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
3.5. Soil erosion
Regarding soil structure and soil use, soil erosion amounts effectively to a loss of natural resource, with consequences on the population’s subsistence capacity and ecological maintenance. Soil erosion is a function of several factors that may occur in the study area and its surroundings. Some of the factors that enhance the erosion phenomena are:
• Riverbanks with accentuated slopes, although steep slopes are not frequent in the project area; • Extensive cultivated areas and forest production areas, in which the post-harvest period implies the exposal of bare soil (Figure 16, Figure 17);
Source: NEMUS (2017)
Figure 16 – Exposed soil in agricultural land
Source: NEMUS (2017)
Figure 17 – Exposed soil in forest production area
• Exposure of bare soil in the dry season, in areas which are usually flooded in the wet season (Figure 18);
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 35
Source: NEMUS (2017)
Figure 18 – Exposed bare soil in flood land
• Hight intensity and erosive precipitation in short periods of time; • Extreme events, mostly precipitation, causing intense water runoff from upland; • High intensity winds during dry season (when the soils are dry and movable); • Drought periods.
It should be pointed that the susceptibility to water erosion is especially elevated during the beginning of the rainy season, where intense precipitation events concur with little or no ground cover on cultivated lands. Despite the exposed, some major erosion factors are not observed, such as frequent steep slopes, soil waterproofing (artificial paved areas) and use of heavy agricultural machinery.
The major concern to arise locally is the agricultural and forest production use, in riverbanks and immediately adjacent areas. The estimated erosion rate for the Lilongwe ADD (20t/ha/year) is higher than the national average (World Bank, 1992).
3.6. Soil contamination
While soil erosion directly affects the physical quality of the soil, soil contamination affects its chemical quality.
Soil contamination results from anthropogenic sources located in the area. Local conditions favour the infiltration of the pollutants into soil horizons instead of its runoff to
36 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
water streams and rivers, creating a context where significant pollution sources will impact the soil quality and its functions/supported land uses.
Considering the peri-urban/rural context of the project area, the following pollution sources are likely to occur:
• Fertilizer usage in agriculture – some smallholder farmers use fertilizers and animal manure to improve crop’s productivity, according to the undertaken fieldwork; • Farmyards and animal grazing (Figure 63 and Figure 64) – animal excretion is a diffuse soil pollution source. The existence of farming and livestock grazing areas around Lake Malawi and through the projected pipeline implementation area, indicates that this may be a potential source, though smallholders’ herds and other farm animals present a low quantitative potential for soil contamination;
Source: NEMUS (2017) Source: NEMUS (2017) Figure 19 – Farming areas around Lake Figure 20 – Livestock grazing around Lake Malawi Malawi
• Wastewater – the common use of latrines, along with other sorts of domestic sewage rural structures, represents an important source of direct soil contamination (especially in human settlements away from water streams and rivers); • Domestic waste combustion – the waste management system is very underdeveloped, causing the necessity for combustion of domestic waste produced in residential areas. Although the waste quantities are very limited and occur mainly on small roadside waste areas, the combustion of domestic waste is assumed to be responsible for the due soil contamination; • Burnt bricks kilns (Figure 61) – scattered near villages and over river margins are some kilns that support the local construction material’s market. These kilns, due
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 37
to the lack of care and the abandonment of the sites without proper cleaning or decontamination measures are responsible for local soil contaminated sites;
Source: NEMUS (2017)
Figure 21 – Burnt clay bricks kiln
• Finally, the vegetation/crop residues combustion associated with agricultural areas management and the setting/clearance for agricultural parcelling, is also a source of soil pollution.
38 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
4. Climate and Meteorology
4.1. Climate of Malawi
Southern Africa has been warming significantly over the last century. For the period 1961 to 2014, temperatures over the region have increased at a rate of 0.4°C per decade. Historical rain patterns are characterised by strong inter-annual and inter-decadal variability and there is little evidence for a substantial change in humidity and precipitation over the region (Davis-Reddy & Vincent, 2017).
Malawi has a sub-tropical climate, which is relatively dry and strongly seasonal, changing from wet to dry weather seasons. The warm-wet season stretches from November to April, during which 95% of the annual precipitation takes place. Annual average rainfall varies from 725 mm to 2.500 mm with Lilongwe having an average of 900 mm (DoCCMS, n.d.).
A cool, dry winter season is evident from May to August with mean temperatures varying between 17-27°C, and minimum temperatures falling between 4-10°C. In addition, frost may occur in isolated areas in June and July. A hot, dry season lasts from September to October with average temperatures varying between 25-37°C. Humidity ranges from 50% (for the drier months of September/October) up to 87% (for the wetter months of January/February) (DoCCMS, n.d.).
Wang et al. (2011) used data from the Chitedze weather station to conclude that relative air humidity typical values for the region are 72.6% in the wet season and 59.6% in the dry season. Regarding evaporation, studies show that it increases in line with temperature increases (Vincent, et al., 2014).
Bibliographic sources state that the dominant wind direction is from Southeast (Mandeville & Batchelor, 1990), although in the wet season the winds from Northeast are important (Pegado, 2000). The average wind intensity is higher in the dry season: 5.3 km/h, as contrasted with 4.4 km/h in the wet season, according to Chitedze weather station’s 1985-2004 data (Wang, et al., 2011).
The general climate pattern can be locally modulated by differences in altitude, relief and due to lake influence (Vincent, et al., 2014).
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 39
Since climate change is already occurring, it is important to assess the nature of observation records before looking at how they may be projected to change into the future. Recent climate trends are best observed by averaging observed station data over larger areas in order to minimize local effects (Vincent, et al., 2014).
The most accessible source of climate data on Malawi is the Climate Information Platform (CIP) hosted at the CSAG. This portal has historical records of TRMM satellite rainfall data, namely total monthly rainfall, total monthly rainy days, and total monthly heavy rain days (useful to identify particular climate events such as floods or droughts, as well as observing long term variability and trends and observed average seasonality) covering Malawi (Vincent, et al., 2014).
For the purpose of this study, the stations of Chitedze, Salima and KIA at Kamuzu International Airport (also known as Lilongwe International Airport) (represented in Figure 22) were analysed, due to their proximity to the proposed location for the construction of the pipeline.
Source: Station coordinates from CIP (University of Cape Town). Image retrieved from Google Earth, on January 2018.
Figure 22 – Chitedze, KIA and Salima weather stations location, with pipeline projected implementation (in yellow)
The following image (Figure 23) shows the historical climate monthly averages measured at these three stations: Chitedze, Salima and KIA, with data regarding rainfall and temperatures (maximum and minimum). The KIA station represents the station with the largest amount of available data, for the period ranging from 1961 to 2011.
40 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
As shown by the graphs below, the warm-wet season stretches from November to April, when most of the annual precipitation takes place. The rainiest month is January, with higher values of rainfall measured at the Salima station (recording values of rainfall above 300 mm).
Regarding temperatures, the hottest month is November, again with Salima presenting the highest values, with a maximum temperature of above 33.5°C. Minimum temperatures are usually below 10°C, with KIA station presenting the lowest value, of 8.4°C in the cold month of July.
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 41
Source: (University of Cape Town), accessed on November 2017
Figure 23 – Historical climate monthly averages (temperatures and rainfall), measured at the Chitedze, Salima and KIA stations
42 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
4.2. Rainfall
Changes in rainfall are typically harder to detect than changes in temperature because rainfall has a higher variability, both spatially and from year to year (Davis-Reddy & Vincent, 2017).
For southern Africa, the rainfall time series (Figure 24) is characterised by strong inter- annual and inter-decadal variability with periods of above and below average rainfall. The alternating patterns of above normal/below normal rainfall periods clearly illustrate the rainfall cycles prevalent in southern Africa where extreme wet and dry years have been recorded, which resulted both in floods and droughts. Note that trends have not been consistent across different observed precipitation data sets and any signals of change are weak and statistically insignificant (Davis-Reddy & Vincent, 2017).
Source: (Davis-Reddy & Vincent, 2017) Legend: Red represents positive anomaly and blue a negative anomaly in rainfall. Seasons are given as summer (December-January-February), autumn (March-April-May), winter (June- July-August), and spring (September-October-November).
Figure 24 – Seasonal rainfall anomalies (mm) over southern Africa from 1901 to 2014 with respect to the long-term average climatology 1961-1990; based on the gridded CRU TS 3.23 data set
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 43
Figure 25 presents the seasonal distribution of projected change in rainfall distribution. Malawi is likely to suffer an increase in rainfall of more than 45 mm per annum (and in some parts more than 60 mm). Whilst models do not confirm whether there will be an increase or decrease in winter and early summer, they do project an increase in rainfall in the second part of summer (January to May). This will have implications for rain-fed agriculture, for example, as planting may need to occur later than it does currently (Vincent, et al., 2014).
Source: Davis, 2011 as cited in Vincent, et al., 2014 Note: Red box highlights Malawi.
Figure 25 – Projected change in distribution of rainfall throughout the year (statistical downscaling)
Although there is uncertainty about winter rainfall, the second part of the summer (December-January-February) and then autumn (March-April-May) will likely have increases in rainfall. Whilst the statistical downscaling of the models is inconclusive on early summer, dynamical downscaling (Figure 26) shows a definite decrease in rainfall in the early part of summer (September-October-November), i.e. the traditional planting time (Vincent, et al., 2014).
44 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
Source: Davis, 2011 as cited in Vincent, et al., 2014 Note: Red box highlights Malawi.
Figure 26 – Projected change in distribution of rainfall throughout the year (dynamical downscaling)
According to the report by Davis-Reddy and Vincent (2017), the decade 1960-1969 was characterised by below-normal rainfall over most of the African region, except for Angola, Malawi, Zambia, Democratic Republic of Congo and Tanzania. Later in the 1970’s this rainfall anomaly pattern was reversed, with parts of southern Africa experiencing above- normal rainfall (see Figure 27).
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 45
Source: (Davis-Reddy & Vincent, 2017) Note: Red box highlights Malawi.
Figure 27 – Decadal anomalies in rainfall with respect to the long-term average climatology 1961-1990; based on CRU TS 3.23 data.
Generally, for southern Malawi, the rainy season normally lasts from November to February with between 150 mm and 300 mm in rainfall per month (Vincent, et al., 2014).
According to Vincent, et al. (2014), the intra-annual precipitation variability is due to the general migration of the Inter-Tropical Convergence Zone (ITCZ) which may vary slightly between different years, and is also strongly influenced by orography. The Lilongwe area, while located in a plateau area, receives comparatively less precipitation than the adjacent highlands and escarpment area (near Lake Malawi) which are directly exposed to the prevailing south-easterly winds transporting humid air (Glad, 2010). Precipitation’s daily variability is dominated by convective precipitation, which generally occurs in the afternoon through local thunderstorms.
Inter‐annual variability in the wet season rainfall in Malawi is influenced by the Indian Ocean Sea Surface Temperatures (SST), which vary from year to year, mainly due to the El Niño Southern Oscillation (ENSO) phenomenon (Vincent, et al., 2014).
Longer term trends in precipitation are more difficult to discern given the nature of the underlying variability. Observations of rainfall over Malawi do not show statistically
46 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
significant trends either in terms of total amount, the date of rainfall onset, or the length of the wet season (December-February) (Vincent, et al., 2014).
Figure 28 shows a representation of the average annual rainfall across Malawi, displaying a difference between the west side of the country (with lower values of rainfall) and the east side of the country (with higher values of rainfall), possibly due to the proximity to Lake Malawi.
Source: (DoCCMS), accessed on November 2017, with consultants’ work (2018)
Figure 28 – Average annual rainfall across Malawi, with pipeline implementation
Figure 29 presents a zoom overview over the pipeline implementation area, providing a more detailed insight of the average annual rainfall in the area. An A3 version of Figure 29 is presented in MAP CLI1 (see Volume 1 Annex).
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 47
Source: MASDAP (2013), with consultants’ work (2018), available at: http://www.masdap.mw/layers/geonode%3Arain2
Figure 29 – Average annual rainfall in the pipeline implementation area
The results of country-specific studies on rainfall trends show that Malawi has a very strong inter-annual rainfall variability, and studies have found no evidence from rainfall records (1960-2000) of a change in rainy season totals, season length or duration of dry or wet spells (Davis-Reddy & Vincent, 2017).
For the analysis of inter-annual precipitation changes, the meteorological stations of KIA, Chitedze and Salima were used due to their proximity to the project intervention area, through the analysis of the data provided by the CIP, hosted at CSAG.
In the following tables (Table 6, Table 8 and Table 10) and figures (Figure 30, Figure 31 and Figure 32 for KIA station; Figure 33, Figure 34 and Figure 35 for Chitedze; Figure 36, Figure 37, Figure 38 for Salima) the total annual and monthly averages rainfall station records are presented. The KIA station presents the largest availability of data, with records from 1961 to 2011, while the Chitedze and Salima stations only provide data for the period from 1997 to 2011. All stations were analysed and the hydrological years were categorized (in Table 7, Table 9 and Table 11) by year type, such as wet, dry, or mean, in comparison to historical averages.
48 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
• KIA station
Table 6 – KIA weather station total annual precipitation records, for the 1961-2011 period, and classification of hydrological year type
Total annual precipitation (mm) – Dry / Mean / Wet classification 1961 882.2 – Mean 1987 584.5 – Dry 1962 1086.32 – Wet 1988 721.9 – Mean 1963 574.79 – Dry 1989 1285.7 – Wet 1964 639.09 – Dry 1990 667.6 – Dry 1965 961.08 – Wet 1991 907.1 – Mean 1966 621.59 – Dry 1992 788.5 – Mean 1967 647.16 – Dry 1993 784.7 – Mean 1968 915.93 – Mean 1994 630 – Dry 1969 840.24 – Mean 1995 634.3 – Dry 1970 862.84 – Mean 1996 1306.7 – Wet 1971 873.42 – Mean 1997 867.1 – Mean 1972 778.99 – Mean 1998 717.8 – Mean 1973 508.75 – Dry 1999 853.1 – Mean 1974 1193.56 – Wet 2000 722.6 – Mean 1975 762.56 – Mean 2001 916 – Mean 1976 918.66 – Wet 2002 949.1 – Wet 1977 1051.81 – Wet 2003 1112.1 – Wet 1978 1001.27 – Wet 2004 884.8 – Mean 1979 830.64 – Mean 2005 546.3 – Dry 1980 796.75 – Mean 2006 783 – Mean 1981 909.8 – Mean 2007 779.8 – Mean 1982 744 – Mean 2008 762.1 – Mean 1983 705.4 – Dry 2009 810.6 – Mean 1984 893.9 – Mean 2010 706.2 – Mean 1985 1007.8 – Wet 2011 757.5 – Mean 1986 743.6 – Mean – – Nr. Years 51 Minimum 828.1 Average 508.8 Maximum 1306.7 Standard Deviation 175.4 Variation Coefficient 0.2 Asymmetry Coefficient 0.7
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 49
Total annual precipitation (mm) – Dry / Mean / Wet classification Dry Year (p=0.2) 705.4 Mean Year (p=0.5) 796.8 Wet Year (p=0.8) 918.7
Table 7 – Parameters for each hydrological year type, according to data from the KIA station, for the 1961-2011 period
Parameter Dry years Mean years Wet years Nr. Years 11 29 11 Minimum 508.8 706.2 918.7 Average 614.5 813.7 1079.5 Maximum 705.4 916.0 1306.7 Standard Deviation 56.3 67.4 133.1 Variation Coefficient 0.1 0.1 0.1 Asymmetry Coefficient -0.4 0.1 0.7
Source: Data from University of Cape Town, accessed on January 2018, with consultant’s work (2018)
Figure 30 – Total annual precipitation measured at the KIA weather station, between 1961 and 2011
50 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
Source: Data from University of Cape Town, accessed on January 2018, with consultant’s work (2018)
Figure 31 – Monthly average precipitation measured at the KIA weather station, between 1961 and 2011
Source: Data from University of Cape Town, accessed on January 2018, with consultant’s work (2018)
Figure 32 – Total annual precipitation for hydrological years, measured at the KIA weather station, between 1961 and 2011, and annual precipitation values corresponding to dry and wet year average limits
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 51
Amongst the dry years registered at the KIA station, the average precipitation is 614.5 mm, corresponding to 76% of the average annual precipitation.
On wet years the average precipitation at the KIA station is 1079.5 mm, corresponding to 133% of the average annual precipitation.
The minimum value of annual precipitation registered at the KIA station was 508.8 mm, in 1973, while the maximum value of annual precipitation was 1306.7 mm, registered in 1996.
• Chitedze station
Table 8 – Chitedze weather station total annual precipitation records, for the 1997-2011 period, and classification of hydrological year type
Total annual precipitation (mm) – Dry / Mean / Wet classification 1997 1094.2 – Wet 2005 573.4 – Dry 1998 949.5 – Mean 2006 818.9 – Mean 1999 1199.7 – Wet 2007 991.7 – Mean 2000 652.4 – Dry 2008 858.3 – Mean 2001 996.4 – Mean 2009 835.6 – Mean 2002 797.4 – Mean 2010 857.4 – Mean 2003 891.4 – Mean 2011 633.7 – Dry 2004 1046.3 – Wet – – Nr. Years 15 Minimum 508.8 Average 828.1 Maximum 1199.7 Standard Deviation 174.6 Variation Coefficient 0.2 Asymmetry Coefficient -0.1 Dry Year (p=0.2) 768.4 Mean Year (p=0.5) 858.3 Wet Year (p=0.8) 1006.4
52 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
Table 9 – Parameters for each hydrological year type, according to data from the Chitedze station, for the 1997-2011 period
Parameter Dry years Mean years Wet years Nr. Years 3 9 3 Minimum 573.4 797.4 1046.3 Average 619.8 888.5 1113.4 Maximum 652.4 996.4 1199.7 Standard Deviation 41.3 74.0 78.5 Variation Coefficient 0.1 0.1 0.1 Asymmetry Coefficient -1.3 0.5 1.0
Source: Data from University of Cape Town, accessed on January 2018, with consultant’s work (2018)
Figure 33 – Total annual precipitation measured at the Chitedze weather station, between 1997 and 2011
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 53
Source: Data from University of Cape Town, accessed on January 2018, with consultant’s work (2018)
Figure 34 – Monthly average precipitation measured at the Chitedze weather station, between 1997 and 2011
Source: Data from University of Cape Town, accessed on January 2018, with consultant’s work (2018)
Figure 35 – Total annual precipitation for hydrological years, measured at the Chitedze weather station, between 1997 and 2011, and annual precipitation values corresponding to dry and wet year average limits
54 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
Amongst the dry years at the Chitedze station, the average precipitation is 619.8 mm, corresponding to 70% of the average annual precipitation.
On wet years the average precipitation at Chitedze is 1113.4 mm, corresponding to 125% of the average annual precipitation.
The minimum value of annual precipitation registered at Chitedze was 573.4 mm, in 2005, while the maximum value of annual precipitation was of 1199.7 mm, measured in 1999.
• Salima station
Table 10 – Salima weather station total annual precipitation records, for the 1997-2011 period, and classification of hydrological year type
Total annual precipitation (mm) – Dry / Mean / Wet classification 1997 1803.8 – Wet 2005 569.5 – Dry 1998 1082.4 – Mean 2006 1730 – Wet 1999 1064.8 – Mean 2007 1463.9 – Mean 2000 1097.3 – Mean 2008 1361.3 – Mean 2001 1784.4 – Wet 2009 892.5 – Dry 2002 1368.3 – Mean 2010 1485.7 – Mean 2003 1410.1 – Mean 2011 838 – Dry 2004 1396.4 – Mean – – Nr. Years 15 Minimum 569.5 Average 1289.9 Maximum 1803.8 Standard Deviation 360.5 Variation Coefficient 0.3 Asymmetry Coefficient -0.3 Dry Year (p=0.2) 1030.3 Mean Year (p=0.5) 1368.3 Wet Year (p=0.8) 1534.6
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 55
Table 11 – Parameters for each hydrological year type, according to data from the Salima station, for the 1997-2011 period
Parameter Dry years Mean years Wet years Nr. Years 3 9 3 Minimum 569.5 1064.8 1730.0 Average 766.7 1303.4 1772.7 Maximum 892.5 1485.7 1803.8 Standard Deviation 172.9 171.3 38.3 Variation Coefficient 0.2 0.1 0.0 Asymmetry Coefficient -1.5 -0.7 -1.2
Source: Data from University of Cape Town, accessed on January 2018, with consultant’s work (2018)
Figure 36 – Total annual precipitation measured at the Salima weather station, between 1997 and 2011
56 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
Source: Data from University of Cape Town, accessed on January 2018, with consultant’s work (2018)
Figure 37 – Monthly average precipitation measured at the Salima weather station, between 1997 and 2011
Source: Data from University of Cape Town, accessed on January 2018, with consultant’s work (2018)
Figure 38 – Total annual precipitation for hydrological years, measured at the Salima weather station, between 1997 and 2011, and annual precipitation values corresponding to dry and wet year average limits
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 57
On dry years, the average precipitation in Salima is 766.7 mm, corresponding to 59% of the average annual precipitation.
On wet years the average precipitation in Salima is 1772.7 mm, corresponding to 136% of the average annual precipitation.
The minimum value of annual precipitation for Salima was of 569.5 mm, observed in 2005, while the maximum value of annual precipitation was 1803.8 mm, occurred in 1997 (the highest value among the three analysed stations).
4.3. Temperature
There is strong evidence that the average land-surface temperature has increased across Africa over the last century, and that this warming has been particularly marked since the 1970’s with the decade of the 2000’s being the warmest (Davis-Reddy & Vincent, 2017).
In Figure 39 the observed trends in annual average near-surface temperature over Africa, for the 1961-2014 period, are presented, displaying some areas with trends up to 4.0°C per decade. The country of Malawi itself shows trends of increases near 2.5-3.0°C per decade in annual average near-surface temperature.
The regional distribution of temperature increases is uneven and some regions have experienced greater changes than others. The largest trends, of 4.0°C per decade, are observed over subtropical southern Africa, subtropical North Africa and parts of central Africa.
58 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
Source: (Davis-Reddy & Vincent, 2017) Note: Crosses indicate grid boxes where the trend is statistically significant. White areas indicate incomplete or missing data. Blue box highlights Malawi.
Figure 39 – Observed trends in annual average near-surface temperature (°C per decade) over Africa for the 1961-2014 period based on CRUTEM4v data
Malawi shows an approximate seasonal trend of 0.3°C throughout the year, with a particular increase in the spring period (SON), reaching the 0.4°C per decade in average near-surface temperature (Figure 40).
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 59
Source: (Davis-Reddy & Vincent, 2017) Note: Crosses indicate grid boxes where the trend is statistically significant. Seasons are given as summer (December-January-February), autumn (March-April-May), winter (June- July-August), and spring (September-October-November). White areas indicate incomplete or missing data. Blue box highlights Malawi.
Figure 40 – Observed trends in seasonal average near-surface temperature (°C per decade) over Africa for the 1961-2014 period based on CRUTEM4v data.
Figure 41 shows maps of the minimum and maximum temperatures across Malawi, being visible that the west side of the country has lower extreme temperatures than the east side, given the temperature attenuation provided by the water body – Lake Malawi.
60 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
Minimum Temperatures Maximum Temperatures
Source: (DoCCMS), accessed on November 2017, with consultants’ work (2018)
Figure 41 – Minimum temperatures (left) and maximum temperatures (right) registered across Malawi, with pipeline implementation course
Figure 42 presents a zoom overview over the pipeline implementation area, providing a more detailed insight of the average annual temperature in the area. An A3 version of Figure 42 is presented in Map CLI2 (see Volume 1 Annex).
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 61
Source: EnsoImpact (2017), with consultants’ work (2018), available at: http://www.masdap.mw/maps/522
Figure 42 – Average annual temperature in the pipeline implementation area
In general, Malawi’s average temperatures range between 18°C and 27°C (Vincent, et al., 2014), between the months of October and July, having recorded an average maximum temperature of 34.4°C in October of 1995, and an average minimum temperature of 7.25°C in June of 1985.
When it comes to analysing future climate projections from GCMs, Figure 43 presents the regional temperature projections for Southern Africa under the RCP 4.5 scenario for December-January-February (i.e. summer). The top row of the diagram shows the period 2016-35; the middle row shows 2046-65; and the bottom row shows 2081-2100. The percentage figures (25%, 50% and 75%) are percentiles because these are combined from sets of models, known as ensembles, which all provide slightly different outputs when run under the same conditions. Malawi, like other southern African countries, is projected to get warmer in the summer; and the extent of warming is predicted to increase throughout the century, such that summer temperatures are likely to be more than 2°C warmer by the end of the century (Vincent, et al., 2014).
62 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
Source: IPCC, 2013 as cited in Vincent, et al., 2014
Figure 43 – Regional temperature projections for December-January-February in Southern Africa under the RCP4.5 scenario
In Figure 44, the future climate projections from GCMs shows the projected temperature changes in winter (June-July-August). The key regional dynamic is that winter temperatures will get warmer throughout the century, particularly in the interior of the sub-continent (including Malawi). By the end of the century an increase of over 2°C, compared to current winter temperatures, can be expected (Vincent, et al., 2014).
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 63
Source: IPCC, 2013 as cited in Vincent, et al., 2014
Figure 44 – Regional temperature projections for June-July-August in Southern Africa under the RCP4.5
Vincent et al. (2014) claims a 90% certainty that the annual maximum temperature change (projected in Figure 45) will exceed the 10th percentile, and a 90% certainty that it will be less than the 90th percentile. This means there is 90% likelihood that the average annual maximum temperatures in southern Malawi will have an increase of over 1.6-1.8°C (the far-left diagram), and 90% chance they will be less than 2.7-2.8°C (Vincent, et al., 2014).
64 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
Source: Davis, 2011 as cited in Vincent, et al., 2014
Figure 45 – Projected mean annual maximum temperature change based on statistical downscaling
Similarly, to statistical downscaling, dynamical downscaling also shows an increase in the mean annual maximum temperature throughout Malawi (Figure 46). Again, according to Vincent et al. (2014), there is a 90% chance that mean annual maximum temperature will exceed 1°C in the south of the country, and a 90% chance that the mean annual maximum temperature increase will be less than 2.4-2.6°C.
Source: Davis, 2011 as cited in Vincent, et al., 2014
Figure 46 – Projected mean annual maximum temperature increase based on dynamical downscaling
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 65
4.4. Extreme meteorological events
Climate change will cause drastic changes in the Malawian climate, causing more frequent and severe extreme weather events, with the most common being floods, large storms, droughts and wildfires, and these are likely to continue to increase into the 21st century.
Figure 47 presents a graph with the number of extreme weather events registered in the period of 1980 to 2016. Note that, in the graph, “wildfires” refers to any uncontrolled and non-prescribed burning of plants in a natural setting; “storms” refer to tropical, extra- tropical and convective storm events; “floods” refer to riverine, flash and coastal flood events; “extreme temperature” refers to both cold waves and heat waves; and “droughts” refer to extended periods of unusually low precipitation that produce a shortage of water (Davis-Reddy & Vincent, 2017).
Source: (Davis-Reddy & Vincent, 2017)
Figure 47 – Number of recorded climate-related events over southern Africa since 1980
66 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
4.4.1. Floods
One of the worst recorded floods in southern Africa occurred in southern Malawi, in 1991. The flash floods resulted in damages to houses, agricultural crops, and infrastructures. The floods and consequent landslides resulted in 500 deaths and thousands of people being displaced (Davis-Reddy & Vincent, 2017).
The low-lying areas such as Lower Shire Valley and some areas in Salima and Karonga present a higher vulnerability to floods than higher grounds (DoCCMS, n.d.).
4.4.2. Extreme temperatures and rainfall
Regarding extreme events, Malawi is very vulnerable to heat and dry spell events. A heat spell event is characterized as a period of excessively hot weather (which may, or may not, be accompanied by high humidity); and a dry spell event refers to a long period of time without rainfalls. Dry spells early in the wet season are particularly important given their impact on maize production (Vincent, et al., 2014).
There is strong evidence to suggest that the number of hot extremes have increased and the number of cold extremes have decreased, which is consistent with the global warming trend. Low temperatures, including the number of frost days, have decreased in frequency and are expected to become less frequent in the future (Davis-Reddy & Vincent, 2017).
Changes in extreme rainfall events are harder to detect because rainfall is subject to a high degree of spatial and temporal variability. Evidence suggests that the frequency of dry spells, as well as daily rainfall intensity, has been increasing (Davis-Reddy & Vincent, 2017).
4.4.3. Droughts
There is some evidence suggesting that droughts have become more intense and widespread over southern Africa. An increased frequency in droughts is expected due to the projected increases in temperature combined with a decrease in rainfall in parts of southern Africa (Davis-Reddy & Vincent, 2017).
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 67
In 1992, Malawi was one of the countries most affected by droughts in southern Africa. Meteorological droughts resulted in approximately 70% of crops failing and 11.4 million tonnes of cereal having to be imported. Large areas of southern Africa received 20-70% of normal rainfall totals, with the dry conditions amplified by excessively high temperatures (Davis-Reddy & Vincent, 2017).
The water balance analysis shows evidently that water deficiency is a common reality in the late winter and early summer months. Apart from this regular situation, the occurrence of meteorological drought, defined as a period of abnormal dry weather sufficiently prolonged for the lack of water, causes serious hydrological imbalance in the affected area (Huschke, 1959).
On dry years, the meteorological drought can be classified as serious or severe. The 1991/1992 drought, with more than 30% departure from normal annual precipitation, is considered as one of the most severe droughts in recent years affecting Malawi (Munthali, et al., 2003).
Following the work of Gibbs (1987) for Australia and Munthali, et al. (2003) for Malawi, the precipitation associated with drought in the Project intervention area is characterized through the Percentile Drought Index. This index relies on the assumption that the water user learns to adapt to the amount of available water and its supply variability except when it occurs within the 10th percentile. In this context, drought is classified as in Table 12.
Table 12 – Drought classification according with the Percentile Drought Index method
Percentile range Drought condition < 5th percentile Severe 5th percentile – 10th percentile Serious Source: Adapted from Gibbs (1987)
This index has an advantage over drought indexes based on average precipitation, such as the Standard Precipitation Index, in which the precipitation is ranked within frequency distributions, being more adequate when the precipitation distribution is not Gaussian. Important asymmetries are expected in highly seasonal precipitation climates (Glad, 2010), such as in the Lilongwe area. This is the case of the annual precipitation series for the Project intervention area, which show important asymmetries assumed as the result of several variability modes (orography effect, convective precipitation, and cyclone associated precipitation).
68 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
The Percentile Drought Index method has been considered, together with the SPI, superior relative to other indexes (Keyantash & Dracup, 2002). In addition to the advantages of the Percentile Drought Index presented before, the choice of index for the drought characterization in this report was made also considering that data time series length of more than 30 years is recommended for Standard Precipitation Index calculation (Hayes et al., 1999), and the data provided by the Chitedze and Salima stations only cover 15 years.
Table 13 presents the drought threshold precipitation values obtained for the KIA, Chitedze and Salima weather stations, that may have originated Serious and/or Severe Droughts, and the years that threshold was met.
Table 13 – KIA, Chitedze and Salima weather stations’ drought annual precipitation thresholds and years that threshold is verified, according with Percentile Drought Index (Gibbs, 1987)
Serious Drought Severe Drought (p=0.1) (p=0.05) Weather station Annual Years Annual Years precipitation threshold is precipitation threshold is threshold (mm) verified threshold (mm) verified 1966; 1987; 1963; 1973; KIA 630 579.6 1994 2005 Chitedze 641.2 2011 615.6 2005 Salima 859.8 2011 757.5 2005
Although the occurrence of Serious Droughts is not concurrent for all weather stations, it does occur both in the Chitedze and Salima stations on the year of 2011. In these two cases, the threshold considered for the year 2011 was an annual precipitation bellow 641.2 mm and 859.8 mm, which represents between 73% and 67% of the total average annual precipitation in Chitedze and Salima, respectively. The KIA station, despite not having presented a serious drought in 2011, is otherwise the station where the threshold was most frequently met.
As for Severe Droughts, the year of 2005 is concurrent for all three stations analysed, presenting itself as the most severe year, again, with the KIA station registering more years where the threshold was met. For severe droughts, the threshold considered for KIA was 579.6 mm and 615.6 mm for Chitedze (both counting 70% of the total average annual precipitation); for Salima the threshold was 757.5 mm (59% of total average annual precipitation).
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 69
The classification of 1994 as a drought year is also referred by World Bank (2009), which links this drought to the ENSO meteorological anomaly, as most droughts affecting Malawi are. The 1991/1992, 1993/1994 and 1999/2000 droughts are classified as extreme droughts using SPI method for Malawi as a whole (Glad, 2010). The 1991/1992 drought is also related to ENSO by (Hulme et al., 1995), who states that there is an historical connection between the occurrence of ENSO and droughts in Southern Africa. According to the World Bank (2009), a drought return period of 5,7 years was determined for the Lilongwe region.
4.5. Climate trends and expected evolution
Observed changes in climate presented in the previous chapter are projected to increase into the future. In the context of Climate Change due to anthropogenic activity, several studies indicate probable changes in the air temperature and precipitation regimes of Malawian climate.
4.5.1. Rainfall
Projections suggest that an increase in the frequency of extreme rainfall events (20 mm of rain falling within 24 hours) will occur over the eastern parts of southern Africa. More heavy rainfall events are expected in a warmer atmosphere, which can hold more water vapour (Davis-Reddy & Vincent, 2017).
Whilst Tadross et al. (2007)’s study of daily precipitation records since 1960 indicates, for the Lilongwe area, a reduction of the wet season duration, a reduction of the frequency of rainy days (Figure 48), as well as an increase in the average dry spell length, which is found connected with the occurrence of ENSO, a phenomenon that has become more often than usual in recent periods.
Overall, despite the expected frequency increase of extreme rainfall events, the frequency of “normal” rainy days is expected to be reduced, thus reducing the current duration of the wet season and prolonging the dry spells duration.
70 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
Source: (Tadross, et al., 2007)
Figure 48 – Southeast Africa’s observed daily precipitation: wet season duration (left); frequency of days with precipitation (right)
The projections of change of precipitation in November-March for 2071-2100 for Central Malawi, as provided by six GCM are presented in Table 14 (World Bank, 2009). According to these data, precipitation is expected to decrease by five of the analysed GCM, in a range of 0.1-2.0 mm/day relative to current levels.
Table 14 – GCM projections of wet season (November-March) precipitation changes in Central Malawi, for the period 2071-2100
HadCM CCSR- GFCL99- ECHAM CSIRO- CGCM 2 3 NIES R30 4 Mk2 Precipitation change -0.1 -1.4 -2.0 -0.7 0.9 -0.6 (mm/day) Source: Adapted from (World Bank, 2009)
In order to account for a future setting of climate projections, the graphs in Figure 49, collected from CIP, show projections of the total monthly rainfall according to meteorological data collected from the Chitedze, Salima and KIA stations, projected for the period of 2021-2041, under RCP 4.5 scenario conditions.
The graphics don’t reach a consensus, demonstrating a relevant variability with months presenting simultaneously an increase and a decrease of rainfall. However, it is possible to identify Salima as the most likely station to have the greatest changes when it comes to rainfall variability (possibly due to the proximity to Lake Malawi) reaching values of up to almost 50 mm in increase (as well as -50 mm of decrease) rainfall, in the months of December and January; while Chitedze is the station with the lowest variability,
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 71
projecting increases/decreases within a 20 mm interval. The greatest variations occur in the summer months (November to January/February) while the winter months (June to August) tend to maintain current tendencies, not showing significant increases/decreases in rainfall levels.
Source: (University of Cape Town), accessed on November 2017 Figure 49 – Projections of total monthly rainfall, at the Chitedze, Salima and KIA stations, for the period 2021-2041, under the RCP4.5 scenario
72 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
Considering the downscaled forecasts of seven GCM for the A2 emission scenario (high population growth, slower economic growth and technological changes), which better fits the Malawian expected evolution (World Bank, 2009), Tadross et al. (2007) indicates for the Chitedze weather station for 2046-2065 period an increase of total monthly precipitation between January and May (especially in April, with an increase of 30 mm) and a reduction in October to December (almost 10 mm in November). They also indicate a decrease of the number of days with precipitation above 2 mm, in November, although less consistently among downscaled estimates (Figure 50).
The results of the GCM downscaling are supported by the observed precipitation trends, meaning a later start of the wet season and an intensification of the late wet season precipitation.
Source: (Tadross, et al., 2007)
Figure 50 – Projected change in the Chitedze weather station’s precipitation for 2046-2065 from empirical downscaling of seven GCM: a) total monthly precipitation; b) monthly number of days with precipitation above 2 mm
The results, including those of Tadross et al. (2007), show a considerable variability between projections, especially in precipitation, which shows the uncertainty that must be considered for climate change forecasts. Nevertheless, the consistency in the qualitative change between projections provides confidence in the probability of a
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 73
decrease of early summer total precipitation and an increase of late summer precipitation.
4.5.2. Temperature
Global Climate Models (GCM) analysed in the IPCC AR5 project that mean annual global temperatures will increase by 0.3-2.5 °C by 2050, relative to the 1985-2005 climatological average (Davis-Reddy & Vincent, 2017).
Projections, based on CCAM downscaling, suggest that the annual frequency of very hot days (number of days with a maximum temperature above 35°C) will increase into the future. Even under the more conservative scenario – RCP 4.5 – increases are as high as 80 days per year by the end of the century. For sectors currently sensitive to extreme temperatures, exposure to such events will almost certainly pose an increased risk in the future (Davis-Reddy & Vincent, 2017).
Projections of change of air temperature (as average of maximum and minimum temperatures) provided by six GCM in November-March for the period 2071-2100, for Central Malawi, are presented in Table 15 (World Bank, 2009). According to these data, air temperature is expected to increase 1.9-5°C relative to today levels.
Table 15 – GCM projections of wet season (November-March) temperature changes in Central Malawi, for the period 2071-2100
CCSR- GFCL99- ECHAM CSIRO- HadCM3 CGCM2 NIES R30 4 Mk2 Mean temperature 3.6 5.0 2.1 1.9 2.4 3.3 increase (°C) Source: Adapted from (World Bank, 2009)
The following graphics, collected from CIP, show projections of the average maximum temperature (Figure 51) and the average minimum temperature (Figure 52), according to meteorological data collected from the Chitedze, Salima and KIA stations, projected for the period of 2021-2041, under scenario RCP 4.5 conditions. The projections for all three regions show an increase of temperature, being this increase more accentuated in KIA, followed by Chitedze. Salima will also suffer an increase of temperature, albeit bit more moderate, possibly due to Lake Malawi’s proximity and influence, serving as a mitigating factor for temperature extremes.
74 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
Maximum temperatures are more likely to increase during the summer months (November and December), but the increase will be assured throughout the whole year. In the modelled period (2021 to 2041), the increase in average maximum temperatures can reach values of up to 2.3°C in November (KIA station) and, the lowest increase will be around 1.3°C in June (Salima station). Even the lowest increase can represent significant impacts over local climate characteristics.
Source: (University of Cape Town), accessed on November 2017 Figure 51 – Projected average maximum temperature, at the Chitedze, Salima and KIA stations, for the period 2021-2041, under the RCP4.5 scenario
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 75
Regarding the average minimum temperatures, projections still show an increase, but in this case more dispersed throughout the whole year. Projected increases vary from 1.25°C up to 1.8°C over current temperatures, focusing on spring-summer time (September to November) to have the highest increases.
Source: (University of Cape Town), accessed on November 2017 Figure 52 – Projected average minimum temperature, at the Chitedze, Salima and KIA stations, for the period 2021-2041, under the RCP4.5 scenario
76 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
4.5.3. Extreme meteorological events
Climate change is expected to alter the magnitude, timing, and distribution of storms that produce flood events.
The occurrence of fires is also closely linked with climate changes. The increases in temperature combined with an increase in dry spells may result in wildfires affecting larger areas, and fires of increased intensity and severity. The frequency of high-fire danger days is projected to increase across southern Africa and is consistent with the increases in heat-wave days (Davis-Reddy & Vincent, 2017).
Droughts in southern Africa are often linked to strong El Niño conditions, so it’s very important to understand if a warmer climate will result in more frequent and more intense ENSO events or not. Researchers across the region are conducting ongoing research into climate dynamics and extreme events including ENSO in order to understand the mechanisms and consequences of climate dynamics in the region on short- to long-term time scales. So far, the conclusions are of low confidence in projections of changes in the behaviour of ENSO because of insufficient agreement between different model projections (Davis-Reddy & Vincent, 2017).
For the period of 2021-2041, it is expected that the heat spell duration will most likely increase throughout the year, having the largest increase in the summer months, specially November and December (Figure 53). Under the RCP 4.5 scenario, it is projected an increase of over 4 days in a heat spell duration, in the month of November, with data from Chitedze station.
KIA is the only station projecting a decrease in the heat spell duration, for the autumn/winter months, reaching the value of, approximately, -0.25 days of heat spell in the month of June.
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 77
Source: (University of Cape Town), accessed on November 2017
Figure 53 – Heat spell duration measured at the Chitedze, Salima and KIA stations, for the period 2021-2041, under the RCP4.5 scenario
For the projected period of 2021-2041, the variation of the average dry spell duration is not so well distinguished, although the majority of the year still presents an increase of duration for the dry spell events (in accordance with the expected shortness of rainfalls
78 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
and temperature increases). The largest increase is projected for the Salima station, adding nearly 28/29 days to the duration, and the largest decrease is projected for the Chitedze station, with a reduction of nearly 20 days, under the RCP 4.5 (Figure 54).
Source: (University of Cape Town), accessed on November 2017
Figure 54 – Average dry spell duration measured at the Chitedze, Salima and KIA stations, for the period 2021-2041, under the RCP4.5 scenario
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 79
The temperature increase should drive an evaporation and evapotranspiration increase, provided that sufficient precipitation is available. Together with the probable increase of the dry season length and of dry spells, this will tend to increase the frequency/severity of meteorological droughts (Hulme et al., 1995).
4.5.4. Summary of the climate projections for the region
Assuming that emissions of anthropogenic greenhouse gases continues to rise at current or higher levels, central southern Africa is likely to be drier in the future during mid- summer. Malawian climate can thus be expected to be more extreme.
Some of the most relevant results obtained from projections analysis were:
• Increase of air temperature (mean, maximum and minimum), heat waves and warm spell durations; • Increase in the frequency of very hot days; • Increase of evaporation and evapotranspiration; • Increase of dry season length and dry spells frequency; • Intensification of droughts; • Decrease of summer precipitation; • Increase in the frequency of heavy rainfall events.
Table 16 provides a summary of the most relevant climate projections for the South African region (Davis-Reddy & Vincent, 2017).
80 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
Table 16 – Summary of climate projections for the South African region
Source: (Davis-Reddy & Vincent, 2017)
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 81
5. Air Quality
5.1. Air quality standards
No national air quality/reference standards or limits are set for air pollution. Therefore, international guidelines are to be used in order to provide reference for ambient air quality goals, such as the guidance book on Air Quality by the World Health Organization (WHO), which includes revised guideline values for the four most common air pollutants – particulate matter, ozone, nitrogen dioxide and sulphur dioxide (WHO, 2005). These WHOs’ Air Quality Guidelines are referred by the IFC, a subsidiary of the World Bank Group, through its Environmental, Health, and Safety (EHS) Guidelines as follows, in Table 17.
Table 17 – IFCs’ reference guidelines for ambient air quality
Pollutant Averaging period Guideline value (μg/m3)
125 (Interim target-1) Sulphur dioxide 24-hour 50 (Interim target-2)
(SO2) 20 (guideline) 10 minutes 500 (guideline) Nitrogen dioxide 1-year 40 (guideline)
(NO2) 1-hour 200 (guideline) 70 (Interim target-1) 50 (Interim target-2) 1-year 30 (Interim target-3) Particulate matter 20 (guideline) (PM10) 150 (Interim target-1) 100 (Interim target-2) 24-hour 75 (Interim target-3) 50 (guideline) 35 (Interim target-1) Particulate matter 25 (Interim target-2) 1-year (PM2.5) 15 (Interim target-3) 10 (guideline) 75 (Interim target-1) Particulate matter 50 (Interim target-2) 24-hour (PM2.5) 37.5 (Interim target-3) 25 (guideline)
82 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
Pollutant Averaging period Guideline value (μg/m3)
160 (Interim target-1) Ozone 8-hour daily maximum 100 (guideline) Source: (WHO, 2005)
Besides ambient air quality standards, the guidelines specify maximum allowable concentrations for gaseous and particulate pollutants (Table 18). Most significant are the special guidelines on PM emissions limits and air quality standard limits for motor vehicles in Malawi (Table 19) (Mapoma & Xie, 2013).
Table 18 – Ambient air quality standards limits for Malawi
Source: (Malawi Standards Board, 2005), as cited in (Mapoma & Xie, 2013).
Table 19 – Air quality standards for motor vehicles in Malawi
Source: (Malawi Standards Board, 2005), as cited in (Mapoma & Xie, 2013).
The 2005 National Environmental Management: Air Quality Act provides the framework for a range of flexible air pollution prevention measures and requires municipalities to compile Air Quality Management Plans. The current ambient air quality guidelines will be replaced by air quality targets, in order to protect the health and wellbeing of people (DEAT, 2006).
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 83
A two-year study of major industries has been initiated that will identify the 50 biggest polluters and result in the rewriting of their air pollution permits. The Department of Trade and Industry is investigating market incentives and disincentives to restrict emissions. Cleaner production activities are gaining momentum, cleaner coal technologies are being investigated, and alternative fuels are being considered (DEAT, 2006).
5.2. Sensitive receptors
The strict analysis of the study area shows a progression of land occupation through urban suburbs from Salima, Senga and Lilongwe City limits up to Lake Malawi, with the expected decrease of population density, increase of agricultural land and more scarce and dispersed population settlements as distance from the urban centres increase.
See the following sub-chapter for a more detailed description of sensitive receptors in the local context of project area, including the location of the main settlements.
5.3. Air pollution
In general, the condition of the South African environment is deteriorating. Increasing pollution and the decline of air quality (counting high sulphur dioxide and particulate matter levels) are harming people’s health (DEAT, 2006).
5.3.1. Health
Air pollution is a major environmental risk to health. By reducing air pollution levels, countries can reduce the burden of disease from stroke, heart disease, lung cancer, and both chronic and acute respiratory diseases, including asthma (WHO, 2016).
The concentration of particulate matter is a key air quality indicator since it is the most common air pollutant that affects short and long-term health. The presence of particles with a diameter of less than 2.5 µm (PM2.5) is more concerning because their small size allows them to travel deeper into the cardiopulmonary system (IAMAT, 2016). Exposure
84 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
to particulate matter increases the risk of many chronic and acute respiratory and cardiovascular conditions in children and adults (WHO, 2016).
A 2013 assessment by WHO’s International Agency for Research on Cancer (IARC) concluded that outdoor air pollution is carcinogenic to humans, associating particulate matter to increased cancer incidence, especially lung cancer and cancer of the urinary tract/bladder. WHO estimates that in 2012, 72% of outdoor air pollution-related premature deaths were due to ischaemic heart disease and strokes, 14% were due to chronic obstructive pulmonary disease or acute lower respiratory infections, and other 14% due to lung cancer (WHO, 2016). Outdoor air pollution has also been associated with breathing problems, chronic diseases, increased hospitalization, and premature mortality (IAMAT, 2016).
Indoor smoke is another serious health risk for nearly 3 billion people who cook and heat their homes with biomass fuels and coal (WHO, 2016). Studies on indoor air quality have been carried out (although on very limited scales) showing that indoor air pollution in Malawian homes is high due to biomass fuel usage (Mapoma & Xie, 2013).
5.3.2. Ambient air quality
In Malawi, air pollution occurs countrywide. In all areas, air is a combination of dust, gases and car exhaust fumes that affects the air quality in both urban and rural settings. The use of large diesel vehicles, especially in the transport sector which are poorly maintained, as well as the large volumes of vehicles in the cities and the increased incidences of traffic congestions, contribute with significant amounts of CO, CO2, VOCs and secondary pollutants, promoting poor air quality (Mapoma & Xie, 2013).
The trend in CO2 emissions for Malawi is rising, as depicted by the results in Table 20 and Figure 55.
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 85
Table 20 – Carbon dioxide emissions for Malawi in the period 1990-2011
CO2 emissions CO2 emissions Year (thousand metric Year (thousand metric tons) tons) 1990 612,4 2001 905,7 1991 660,1 2002 883,7 1992 656,4 2003 957,1 1993 693,1 2004 975,4 1994 718,7 2005 916,8 1995 729,7 2006 953,4 1996 711,4 2007 953,4 1997 759,1 2008 1147,8 1998 828,7 2009 1056,1 1999 997,4 2010 1213,8 2000 905,7 2011 1206,4 Source: (UN, 2015)
Source: consultants’ work with data from UN (2015)
Figure 55 – Representation of the increase of CO2 emissions for Malawi, in the period 1990- 2011
86 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
Despite the efforts being made, the research and reporting of the issue is still far behind what’s necessary. Lack of monitoring equipment and systems hinder studies in air quality in Malawi, with very few places having monitoring systems; for example, the Lilongwe International Airport (KIA) has one monitoring system for Air Quality. However, this system has limited sensors available for SO2, NO2 and CO monitoring, making it difficult to extrapolate any usable results (Mapoma & Xie, 2013).
5.4. Air pollution sources
Inventory on greenhouse gases (GHG) show that Malawi is a net emitter, implying that the total emission levels exceed its’ sink capacity. The major sources of GHG are energy (combustion of fossil fuels and fugitive emissions), industrial processes and other products (mineral processes and solvents), agriculture forestry and other land use
(AFOLU) (Livestock, land use and non-CO2 emissions) and wastes (solid waste disposal, incineration/open burning and wastewater treatment). According to the National State of
Environment Report, Malawi emits on average about 22.708 Gigagrams (Gg) of CO2eq (with AFOLU counting for 95% of this value) (Mapoma & Xie, 2013).
Some studies show that urban and rural settings have localized air pollution issues due to various activities such as tire and waste burning, biomass burning (significant contributor to human health problems), firewood and charcoal use (Mapoma & Xie, 2013).
The use of wood fuel in rural homes contributes to significantly higher particulate matter
(PM) levels, while in urban setting CO2 is significantly higher due to the use of charcoal as fuel (Mapoma & Xie, 2013). As a transition area (from peri-urban residential areas to rural and dispersed small settlements), the project area’s characteristics define and reflect the main pollution sources:
• Road traffic, concentrated in the connection area between the city of Lilongwe and Salima, and residual traffic at local accesses; • Residential/rural combustion.
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 87
The emission of atmospheric substances is therefore mostly related with the burning of fossil fuels and biomass combustion, resulting in a local increase of pollutants such as carbon monoxide (CO), carbon dioxide (CO2), nitrogen oxides (NOx) and, especially, particulate matter (PM).
5.4.1. Road traffic
Traffic emissions can be discussed under different perspectives: gaseous emissions directly associated with traffic volume and circulation speed, and particulate emissions, related not only with incomplete combustion products, but also with the suspension of dust in unpaved surfaces.
Figure 56 highlights the relevant roads (in yellow) surrounding the pipeline route (in red).
Source: aerial image from Google Earth, retrieved on January 2018
Figure 56 – Relevant roads (yellow) in the vicinity of the pipeline route (red)
Based on in situ observations and contact with local village leaders and population, it was observed that the great majority of traffic flows occur between Salima and Lilongwe City, representing the typical commuting that reflects the dependency of peri-urban/rural suburbs on a major city (Lilongwe). The project area is otherwise served by local unpaved road accesses with very residual traffic volumes, as local movements are mainly pedestrian or made by bicycle (Figure 57).
88 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
Source: NEMUS (2017)
Figure 57 – Local movements made mainly on foot by pedestrians or by bicycle
Hence, the population along the study area and its surroundings is exposed to limited concentrations of traffic-associated gaseous emissions. Also, although the road accesses are unpaved roads, the scarce circulation of vehicles and the dominance of population movements made on foot or by bicycle decreases the significance of re- suspended particulate matter/dust.
Source: NEMUS (2014)
Figure 58 – Dust re-suspension from road traffic
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 89
5.4.2. Biomass combustion
An estimated 95% of the Malawian population uses biomass as their main source of domestic energy (Fullerton, et al., 2009). The use of fuelwood and charcoal as an energy source is spread out, especially in peri-urban and rural areas, posing a specific threat to indoor air quality.
A study developed in Malawi (rural Chikwawa and urban Blantyre) concluded that all sampled homes presented PM2.5 levels (24h period) above the recommended 25 μg/m3 limits and 80% had levels four times higher than the WHO level for outdoor air quality (Fullerton, et al., 2009).
The study area reflects the national trend for rural households, as fuelwood and charcoal are the main energy sources in households – cooking, with the use of paraffin as house lighting fuel, as shown in the following figure (Figure 59).
Fuelwood 100% Paraffin 90%
80% Fuelwood 70% Paraffin 60% Charcoal 50%
40% Electricity 30%
20% Charcoal Electricity 10%
0% Urban Rural
Source: Second Integrated Household Survey, 2004, in O’Sullivan&Fitzgerald (2006)
Figure 59 – Energy use in urban and rural Lilongwe City
90 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
5.4.3. Other sources
Considering the study area’s characteristics, other sources of air pollution were identified:
• Vegetation/crop residues combustion (Figure 60) – associated with agricultural areas management and the setting/clearance for agricultural parcelling;
Source: NEMUS (2014)
Figure 60 – Vegetation/crop residues burning
• Burnt bricks kilns (Figure 61) – near villages and over river margins there are some scattered kilns that support the local construction material’s market. These clay-brick structures are stacked, covered with mud and burnt using wood. The emissions are characteristic of biomass combustion – CO, NOx and PM;
Source: NEMUS (2017)
Figure 61 – Burnt clay bricks kiln
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 91
• Charcoal sale (Figure 62) – during the field visits for characterization of the study area it was noticed that the private roadside sale of charcoal is very common. Charcoal is used as an energy source but it produces several toxic emissions such as carbon dioxide, methane and heavy metals, with several concerns regarding global warming and acid rainfalls.
Source: NEMUS (2017)
Figure 62 – Charcoal sale at the roadsides
• Domestic waste combustion – as waste management is underdeveloped, domestic waste produced in residential areas is generally burnt in near surroundings or specified areas to that end. No landfill or waste concentration areas were identified, so domestic waste combustion is assumed as a local relevant practice and as such a local air pollution source, responsible for typical emissions of CO, PM, NMVOC, NOx and CH4; • Livestock grazing and farming areas (Figure 63 and Figure 64) – promotes residual emissions of NH3 from decomposing manure (in grazing and housing areas – stables, barns or stalls);
92 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
Source: NEMUS (2017) Source: NEMUS (2017)
Figure 63 – Farming areas around Lake Figure 64 – Livestock grazing around Lake Malawi Malawi
5.5. Atmospheric dispersion conditions
Pollutants’ dispersion in the atmosphere is based on turbulent air mass movements due to thermal and/or mechanical forces. A given pollutant’s concentration in the atmosphere depends not only on the pollution sources emissions but also from the combined action of diffusion and transport phenomena (wind regime and thermal stratification), chemical reactions (in the atmosphere and at ground/emission source level) and other removal mechanisms (such as precipitation and sinks).
The knowledge of the wind regime of a given region is a fundamental aspect to determine the pollutant dispersion conditions, given that it influences the horizontal transport patterns. The wind regime for Malawi, in general, indicates the prevalence of south- eastern winds, except for the period from September to November, as the rapid increase of temperature induces a wind direction change to east and northeast (Venema & Lorkeers, Land Resources Evaluation Project – Malawi: Land Resources Appraisal of Lilongwe Agricultural Development Division (Field Document No. 24), 1991).
The combination of the rainiest months with periods of higher average temperatures – November to March (see chapter 4.1 for more information) – leads to the increased probability of pollutants concentration (especially those related with combustion gases and biodegradable material digestion), although the increased rainfall probability and intensity provide unfavourable atmospheric conditions for particles dispersion (removal potential of suspended particulate matter increases – wash-effect).
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 93
5.6. Air quality assessment
The National State of Environmental Report (NSOER) provides an indication of the countries environmental state in terms of the 9 key environmental issues, including “Air Quality”, and it reports that air quality is still fairly good. However, urbanization, population growth, an increasing number of vehicles and the booming of industrial activity anticipate a degradation of the air quality, causing problems on human health, global climate changes and ozone depletion (Mapoma & Xie, 2013).
Since 1999, the number and sophistication of monitoring stations has grown substantially, and the monitoring networks of industry are sharing more data. Many provincial and local authorities are establishing monitoring networks to comply with new legislation (DEAT, 2006). However, progress still needs to be made.
The Department of Environmental Affairs and Tourism (DEAT) in its’ overall assessment of air quality has expressed its “cause for concern” regarding air quality in South Africa (Table 21), which is, in general, decreasing and raising concerns due to the increase of air pollution and higher incidence of human health problems.
Table 21 – Assessment of air quality in South Africa
= “cause for concern” Source: (DEAT, 2006)
Figure 65 shows that most of the area comprised by the pipeline project implementation is situated in an area that exceeds the values stipulated by the WHO Guidelines, varying from a concentration of 16 to 35 µg/m3 (annual means value for PM2.5 is up to 10 μg/m3).
94 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
Source: WHO (2016). Available at: http://maps.who.int/airpollution/
Figure 65 – Annual mean ambient PM2.5 (µg/m3)
The concentration of fine particulate matter in Malawi is higher in urban areas (reaching, approximately, 26 μ/m3), as shown in Table 22 and Figure 66.
Table 22 – Concentrations of fine particulate matter (PM2.5) (μ/m3) in Malawi
Concentrations of fine particulate matter (PM2.5) (μ/m3) Country Urban areas Total Malawi 25,6 22,0 Source: WHO (2016). Available at: http://apps.who.int/gho/data/node.main.152?lang=en Last update until report preparation: 2016-09-30.
Source: WHO (2016), with data from 2014. Available at: http://gamapserver.who.int/gho/interactive_charts/phe/oap_exposure/atlas.html
Figure 66 – Annual mean concentrations of fine particulate matter (PM2.5) in urban areas of Malawi (μ/m3)
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 95
No monitoring networks or data, public or private, are available in the study area. Hence, a qualitative assessment of the air quality baseline situation is based on all the considerations above, as well as on specialised perception of local air quality conditions during fieldwork. These issues point to a very limited ambient air quality degradation. Nonetheless, occasional combinations of high temperatures and stable atmospheric conditions (such as low intensity winds and no precipitation) may occur, increasing local accumulation of contamination, particularly in human settlements adjacent to roads (exposed to high traffic and dust emissions), and residential areas adjacent to biomass combustion hotspots.
96 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
6. Surface Water Quality
6.1. Overview of the water resources in the project area
The drainage system of Malawi has been divided into 17 Water Resources Areas (WRA) with each one either pertaining to one river basin or being composed by several small river basins. The WRA were sub-divided into Water Resources Units (WRU) as presented in Figure 67 (JICA, 2014).
Source: JICA (2014)
Figure 67 – Malawi Water Resource Areas (WRA) and Water Resource Units (WRU)
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 97
The study area is included in the Linthipe basin (WRA 4) and Nkhota-kota Lakeshore basin (WRA 15), integrating the following WRU:
• Linthipe basin:4E, 4C, 4F, 4B; • Nkhota-kota Lakeshore basin: 15A.
The abstraction point is projected to be located in Lake Malawi, on the Leopard bay area. Lake Malawi is the third biggest freshwater lake in Africa and the eighth all over the world. Its water surface area is about 29 000 km2 and its catchment area spreads to around 98 000 km2 consisting of 64 000 km2 in Malawi, 27 000 km2 in Tanzania and the remainder in Mozambique (JICA, 2014).
The lake is 570 km in length and 16-80 km in width, and the total volume is about 8 000 km3. The mean lake level is about 474 m above mean sea level. Lake Malawi has an important role not only from the viewpoint of water resources but also for the national tourism, transportation and fishery industries in Malawi (JICA, 2014).
The Figure 68 and the Figure 69 portrait Lake Malawi shore, near the intake point.
Source: NEMUS (2017) Source: NEMUS (2017)
Figure 68 – Lake Malawi, near the Figure 69 – Lake Malawi, near the abstraction point (raw water pipeline km abstraction point (raw water pipeline km 0+200) 0+800)
The Linthipe and its tributary Lilongwe are the major rivers in the surroundings of the pipeline route. The closest point between either of those rivers and a project site is approximately at pipeline km 33+700, where Lilongwe River is at 100 m (Figure 70).
98 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
Source: NEMUS (2017)
Figure 70 – Lilongwe river (near pipeline km 33+700)
The Lilongwe river flows from the Mountain Range of Dzalanyama, on the Western Malawi-Mozambique border, to the Linthipe River. Its main tributaries are the Lumbadzi and the Lingadzi rivers. The Lilongwe River catchment area is the largest subcatchment of the Linthipe River catchment. Dowstream, the Linthipe River flows into Lake Malawi.
Although major rivers like Linthiphe or Lilongwe aren’t crossed, five other rivers were identified in the pipeline route (Khato Civils & South Zambezi JV, 2017):
• Mpatsanjoka North – pipeline km 2+200; • Mpatsanjoka South – pipeline km 9+400; • Lumbadzi – pipeline km 84+000; • Kofula – pipeline km 96+100; • Mchenzi – pipeline km 107+000.
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 99
As observed during fieldwork, those rivers, identified in the project concept design, are dry (Mpatsanjoka North, Mpatsanjoka South, Lumbadzi and Kolufa) or show just a minor stream (Mchenzi). The figures below portrait the status of the river beds during fieldwork.
Source: NEMUS (2017) Source: NEMUS (2017)
Figure 71 – Mpatsanjoka River North, at Figure 72 – Mpatsanjoka River North, at pipeline km 2+200 (1) pipeline km 2+200 (2)
Source: NEMUS (2017) Source: NEMUS (2017)
Figure 73 – Mpatsanjoka River South, at Figure 74 – Mpatsanjoka River South, at pipeline km 9+400 (1) pipeline km 9+400 (2)
100 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
Source: NEMUS (2017) Source: NEMUS (2017)
Figure 75 – Lumbadzi River, at pipeline Figure 76 – Lumbadzi River, at pipeline km 84+000 (1) km 84+000 (2)
Source: NEMUS (2017) Source: NEMUS (2017)
Figure 77 – Kofula River, at pipeline Figure 78 – Kofula River, at pipeline km 96+100 (1) km 96+100 (2)
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 101
Source: NEMUS (2017) Source: NEMUS (2017)
Figure 79 – Mchenzi River, at pipeline Figure 80 – Mchenzi River, at pipeline km 107+000 (1) km 107+000 (2)
According to the first National Water Resources Master Plan (UN-DTCV, 1986), the rainy season extends from November to April, within which the Linthipe River (and its tributaries) catchment receives over 95% of its annual rainfall, on average. The fieldwork took place in late November and had coincided with the beginning of the rainy season, explaining the absence of streams or the minor flow in the case of the Mchenzi River.
6.1.1. Water quality assessment methodology
The surface water quality assessment includes the following steps:
• Water uses influencing and being influenced by the existing surface water quality on Lake Malawi and others water bodies in the pipeline route; • Description of the major surface water pollution sources for Lake Malawi and others water bodies in the pipeline route; • Surface water quality baseline assessment based on primary and available secondary data.
The assessment of the major pollution sources and relevant water uses was based on fieldwork and local interviews carried out in November/December 2017 for the present assignment.
102 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
Water quality assessment was based on regular monitoring data for Lake Malawi, in the catchment area (Leopard Bay), provided by Lilongwe Water Board (LWB), covering the December 2016 to May 2017 period. The location and sampled parameters for available LWB sampling sites with relevance for the assessment are presented in the Table 23.
Data from two other sampling sites was provided by LWB (2013). One from the Lumbadzi River, performed near the projected river crossing, and other in the Linthipe River, performed near the railroad bridge of Salima Town.
The Lumbadzi River sampling site is considered to be representative of water quality in water bodies crossed by the pipeline, which will likely be influenced by project induced changes, namely the increase of turbidity during construction works.
While no changes are expected at the Linthipe sampling site due to the project, its data was included for comparison purposes to the Lumbadzi/Lake sites.
The water quality sampling locations from LWB are presented in Figure 81.
Table 23 – Location and sampled parameters of LWB surface water quality monitoring sites
Site Description Lat(ºS) Long(ºE) Parameters Physical: Lake Malawi pH 1 (near the 13°40'54.32"S 34°35'49.78"E Suspended Solids (mg/l) Turbidity (NTU) intake area) Chemical: Electrical conductivity Lumbadzi (S/cm) River (at Total Dissolved Solids (mg/l) 2 13°47'46.44"S 33°59'19.74"E Salima Road Hardness (mg/l), Alkalinity (mg/l) Bridge) Na (mg/l), K (mg/l), Ca (mg/l) Mg (mg/l), Mn (mg/l), Fe Linthipe (mg/l) SO4 (mg/l), NO3 (mg/l), F River (at (mg/l) 3 Railway 13°47'24.00"S 34°27'6.00"E Cl (mg/l), HCO3 (mg/l), Bridge, PO4 (mg/l) Biological: Salima) Faecal coliforms (counts/100 ml) Source: data provided by LWB
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 103
Figure 81 – LWB sampling sites used for water quality assessment
The Malawian Standards Board (MSB) Drinking Water specification (MS 214:2013) and the World Health Organization Guidelines for Drinking-water Quality (WHO, 2017), presented in Table 24, were considered in water quality analysis. Although it isn’t expected that the raw water sampled meet the requirements of those standards/guidelines, used for treated/drinking water, in the absence of more suitable standards they were considered as a general reference to assess the environmental quality of surface water at the sampling sites.
The FAO guideline for irrigation water quality (FAO, 1985) was also considered.
104 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
Table 24 – Water quality standards and guidelines
Drinking water Irrigation water Parameter MSB WHO standard guideline FAO guideline (2013) (2017) (1985) pH 6.5-8.5 6.5-8.5 6.5-8.4 Suspended Solids (mg/l) - - - Turbidity (NTU) 0.1-1 - - <700 (no restriction on use) 700-3,000 (slight Electrical conductivity 700-1500 - to moderate (S/cm) restriction on use) >3,000 (severe restriction on use) <450 (no restriction on use) 450-2,000 (slight Total Dissolved Solids <500 <1000 to moderate (mg/l) restriction on use) >2,000 (severe restriction on use) Hardness (mg/l) - <500 - Alkalinity (mg/l) - - - Na (mg/l) 25-50 <200 - K (mg/l) 6-10 - - 100-300 (taste Ca (mg/l) 80-150 - threshold) Mg (mg/l) 30-70 - - Mn (mg/l) <0.05 <0.4 - Fe (mg/l) <0.01 <0.3 -
SO4 (mg/l) 100-200 <250 -
NO3 (mg/l) - <50 - F (mg/l) 0.7-1 <1.5 - Cl (mg/l) 100-200 <250 -
HCO3 (mg/l) - - -
PO4- (mg/l) - - - Faecal coliforms Not detected Not detected - (counts/100 ml)
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 105
6.1.2. Water uses
The main human water uses of water in Lake Malawi are (Leopard bay area):
• Fishing (domestic use and economic activity); • Domestic use (washing, personal hygiene, both on site and at home); • Recreational bathing (mainly associated with touristic facilities); • Collection for irrigating (in very small scale during the dry season); • Livestock consumption (in small scale, around the lake).
Source: NEMUS (2017) Source: NEMUS (2017) Figure 82 – Fishing at Lake Malawi (1) – near Figure 83 – Fishing at Lake Malawi (2) – near raw water pipeline km 0+500, Lifuwu village raw water pipeline km 1+100, Lifuwu village
Source: NEMUS (2017) Source: NEMUS (2017) Figure 84 – Water collection from Lake Figure 85 – Water collection from Lake Malawi (1) – near raw water pipeline km Malawi (2) – near raw water pipeline km 1+000, Lifuwu village 1+000, Lifuwu village
106 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
Source: NEMUS (2017)
Figure 86 – Recreational bathing in Lake Malawi, Senga bay
Although no evidence of direct human consumption for drinking was found, such use can occur sporadically, according to village leaders and contacted population. These uses occur at villages near the Lake (either using untreated water or boiling water) or in cases of groundwater problems (failure in pumps or other groundwater abstraction infrastructures).
The water resources identified throughout the pipeline route (section 6.1) show similar uses, with focus on domestic use, irrigation and livestock consumption.
Taking into account the surface water uses, water quality should be at least suitable for drinking, bathing/recreational use and irrigation.
6.1.3. Pollution sources
Major pollution sources and their likely water quality impacts, for water resources in the project area, are presented in Table 25. Although this analysis was focused on Lake Malawi (Leopard Bay area), similar pollution sources can be found for water resources along the pipeline route.
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 107
Table 25 – Lake Malawi (Leopard Bay area) major pollution sources and associated water quality impacts
Type of Water quality Pollution source pollution impact Major locations BOD Washing and Faecal coliform Nearest settlements Diffuse bathing (on lake) Turbidity around the lake Phosphates Farming (rice, maize, tobacco, groundnuts, beans, Phosphates and potatoes, nitrates enrichment Major rice production Diffuse vegetables), using Oxygen depletion area in Lifuwu, and small (fields manure as fertilizer. BOD areas near the runoff) Poor agricultural Faecal coliform settlements practices lead to Siltation/ Turbidity increased soil erosion Diffuse Settlements around the (solid BOD Human lake, namely Lifuwu waste/faecal Faecal coliform settlements village, which is located matter Turbidity near the intake runoff) Diffuse BOD Around the Lake, near (grazing Faecal coliform Livestock grazing the settlements. Usually areas Turbidity in small numbers runoff) Nutrient enrichment
Source: NEMUS (2017) Source: NEMUS (2017)
Figure 87 – Farming areas around Lake Figure 88 – Livestock grazing around Lake Malawi, near pipeline km 6+000, TA Malawi, near pipeline km 4+000, TA Maganga Maganga
108 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
In general, these pollution sources should have low impact on Lake Malawi water quality mainly because there is a huge dilution capacity given the lake’s scale. Nonetheless, diffuse pollution should be the most important type of pollution, especially following the first precipitation events of the wet season, which erode accumulated cattle manure from the dry season, as well as exposed soil from large uncultivated areas.
Runoff from settlement areas in the vicinity of the lake is also more important in the beginning of the wet season. The lack of organized sanitation and solid waste management is a major source of contaminants, such as coliforms, to the water resources.
Pollution sources for the rivers identified along the pipeline route are generally the same as described above.
6.1.4. Water quality assessment
6.1.4.1. Suitability for use
Considering the LWB sampling sites for the project area and the standards/guidelines presented before in Table 24, the following tables presents an assessment of the surface water. The requirements for drinking water were used as reference to assess the environmental quality of surface water. Although it isn’t expected that raw water meets those requirements (for treated/drinking water), this analysis can be seen as an indicator for suitability for future uses.
Table 26 – Water quality assessment for Lake Malawi sample site
Parameter above the requirement (percentage of total samples for each standard/guideline) Parameter MSB 2013 WHO 2017 FAO 1985 drinking drinking irrigation (%) water (%) water (%) Cl (mg/l) 100 0 -
SO4 (mg/l) 100 0 - F (mg/l) 100 0 - Na (mg/l) 53 0 - K (mg/l) 67 - -
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 109
Parameter above the requirement (percentage of total samples for each standard/guideline) Parameter MSB 2013 WHO 2017 FAO 1985 drinking drinking irrigation (%) water (%) water (%) Ca (mg/l) 100 0 - Mg (mg/l) 100 - - Fe (mg/l) 100 40 - Mn (mg/l) 100 33 - Electrical conductivity (S/cm) 100 - 0 pH (Sorensen Scale) 7 7 27 Turbidity (NTU) 93 - - Faecal Coliforms (counts/100 100 100 - ml)
Table 27 – Water quality assessment for Lumbadzi sample site
Parameter above the requirement (percentage of total samples for each standard/guideline) Parameter MSB 2013 WHO 2017 FAO 1985 drinking drinking irrigation (%) water (%) water (%) Cl (mg/l) 100 0 -
SO4 (mg/l) 100 0 - F (mg/l) 100 0 - K (mg/l) 100 - - Ca (mg/l) 100 0 - Mg (mg/l) 100 - - Electrical conductivity (S/cm) 100 - 0 pH (Sorensen Scale) 100 100 100 Turbidity (NTU) 100 - - Faecal Coliforms (counts/100 ml) 100 100 -
110 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
Table 28 – Water quality assessment for Linthipe sample site
Parameter above the requirement (percentage of total samples for each standard/guideline) Parameter MSB 2013 WHO 2017 FAO 1985 drinking drinking irrigation (%) water (%) water (%) Cl (mg/l) 100 0 - Na (mg/l) 100 0 - Ca (mg/l) 100 0 - Mg (mg/l) 100 - - Electrical conductivity (S/cm) 0 - 100* Turbidity (NTU) 100 - - Faecal Coliforms (counts/100 ml) 100 100 - Note: * - Sample result above 700 and below 3000 (Slight to moderate restriction on use).
While 15 samples were considered for the Lake Malawi sample site (December 2016 to May 2017), the Lumbadzi and Linthipe sites only showed a sample each (collected in 2013), affecting possible conclusions about suitability for use.
Considering MSB guidelines for drinking water, Chloride, Calcium, Magnesium, Turbidity and Faecal Coliforms shows results higher than the standards for all samples in all three locations. In the context of the WHO Guidelines, the only parameter showing non-compliance cases, in all three locations, is Faecal Coliforms.
The highest result for Faecal Coliforms was in Lake Malawi, of 5 500/100 ml on 03-04-2017, with the lowest result being 100/100 ml also in the Lake (04-01-2017).
Setting aside biological quality issues, some problems were detected concerning iron and manganese concentrations, especially for the Lake site, considering WHO Guidelines, that are already very demanding. pH showed results slightly above the standards for drinking water and irrigation, in the Lake and Lumbadzi sites.
Despite these standards aims to meet quality for human consumption, the analysis showed that some parameters already comply with drinking water quality, revealing in some extent, a good surface water quality.
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 111
6.1.4.2. Variability along monitoring sites
From all available LWB’s sampled parameters, Turbidity and Suspended Solids are assumed to be representative of general physical quality. Electrical Conductivity, Total Dissolved Solids, Nitrates and Iron were considered representative of general chemical quality and adequate for assessing existing pollution sources, such as runoff from agricultural areas. Finally, Faecal Coliforms is taken to be representative of general biological quality.
Turbidity results were generally low, except for two samples from Lake Malawi in March and April 2017 (31 NTU). Both were collected towards the end of the wet season, which could link the obtained values to strong storm runoff. Other wet season samples such as December 2016 and January 2017 presented much lower records.
Table 29 – Turbidity results for monitoring sites
Sampling Site Date Turbidity (NTU) 23/dec/2016 0.9 28/dec/2016 1.7 28/dec/2016 2.8 04/jan/2017 1.3 14/jan/2017 1.8 18/jan/2017 2.8 21/jan/2017 2.8 1 – Lake Malawi 29/jan/2017 1.2 29/mar/2017 31 3/apr/2017 31 19/apr/2017 10.1 26/apr/2017 7.2 3/may/2017 3 17/may/2017 2.2 31/may/2017 6.9 2 – Lumbadzi River --/--/2013 4.2 3 – Linthipe River --/--/2013 12 Source: data provided by LWB
112 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
Suspend solids concentration follows the same pattern as turbidity, with March and April 2017 samples showing higher values (35 mg/l). Samples collected in 19 and 26 April and 31 May also show higher results (16 – 20 mg/l) than the rest of the samples, namely those collected in December and January (0.5 – 5 mg/l).
Table 30 – Suspended solids results for monitoring sites
Sampling Site Date Suspended Solids (mg/l) 23/dec/2016 2 28/dec/2016 2.4 28/dec/2016 5.2 04/jan/2017 0.5 14/jan/2017 0.6 18/jan/2017 0.92 21/jan/2017 0.92 1 – Lake Malawi 29/jan/2017 - 29/mar/2017 35.2 3/apr/2017 35.2 19/apr/2017 19.6 26/apr/2017 17.2 3/may/2017 4 17/may/2017 1.6 31/may/2017 16.4 2 – Lumbadzi River --/--/2013 2 3 – Linthipe River --/--/2013 6 Source: data provided by LWB
Electrical conductivity (Table 31) showed higher values for the Lumbadzi and Linthipe Rivers, with a mean value around 720 μS/cm, than in the Lake site (mean value 220 μS/cm).
According to FAO irrigation water guidelines, all results present no restriction on use (<700 mg/l) except for the sample in for the Linthipe River, which implies a slight to moderate restriction on use (result between 700 and 3000 μS/cm). Most of the samples don’t comply with MSB drinking water standards for electric conductivity (700-1 500 μS/cm).
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 113
Table 31 – Electrical conductivity results for monitoring sites
Electrical Conductivity Sampling Site Date (µS/cm) 23/dec/2016 2.55 28/dec/2016 227 28/dec/2016 235 04/jan/2017 234 14/jan/2017 224 18/jan/2017 236 21/jan/2017 236 1 – Lake Malawi 29/jan/2017 234 29/mar/2017 223 3/apr/2017 223 19/apr/2017 235 26/apr/2017 255 3/may/2017 235 17/may/2017 237 31/may/2017 252 2 – Lumbadzi River --/--/2013 674 3 – Linthipe River --/--/2013 779 Source: data provided by LWB
Total Dissolved Solids data also shows higher values for the Lumbadzi and Linthipe Rivers, compared with the Lake site.
According to FAO irrigation water guidelines, all results present no restriction on use (<450 mg/l). Furthermore, samples comply with MSB/WHO drinking water standards for total dissolved solids.
114 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
Table 32 – Total dissolved solids results for monitoring sites
Total Dissolved Solids Sampling Site Date (mg/l) 23/dec/2016 162 28/dec/2016 159 28/dec/2016 165 04/jan/2017 152 14/jan/2017 157 18/jan/2017 165 21/jan/2017 165 1 – Lake Malawi 29/jan/2017 164 29/mar/2017 156 3/apr/2017 156 19/apr/2017 165 26/apr/2017 179 3/may/2017 165 17/may/2017 166 31/may/2017 176 2 – Lumbadzi River --/--/2013 318 3 – Linthipe River --/--/2013 383 Source: data provided by LWB
Nitrate concentrations are generally low in all sites (Table 33), widely complying with WHO drinking water standards for nitrates.
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 115
Table 33 – Nitrates results for monitoring sites
Sampling Site Date Nitrates (mg/l) 23/dec/2016 0.0 28/dec/2016 0.1 28/dec/2016 5.6 04/jan/2017 2.0 14/jan/2017 3.6 18/jan/2017 3.1 21/jan/2017 3.1 1 – Lake Malawi 29/jan/2017 4.3 29/mar/2017 0.8 3/apr/2017 0.8 19/apr/2017 0.5 26/apr/2017 1.6 3/may/2017 5.8 17/may/2017 4.9 31/may/2017 6.1 2 – Lumbadzi River --/--/2013 0.1 3 – Linthipe River --/--/2013 0.2 Source: data provided by LWB
According to these data, surface water nutrient enrichment, which typically results from diffuse pollution sources such as agriculture and is a common concern in lakes/reservoirs, does not seem to be a significant issue in the region. The scarce use of chemical fertilizers and the lake dilution capacity are probably the main reasons.
Iron results (Table 34) are generally higher than the MSB drinking water standard (<0,01 mg/l) for the Lake site. The comparison of those results with the WHO standard show peak values on December 2016 and between 26 April and 31 May 2017, surpassing 0,3 mg/l (WHO Standard).
116 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
Table 34 – Iron results for monitoring sites
Sampling Site Date Iron (mg/l) 23/dec/2016 2.55 28/dec/2016 0.06 28/dec/2016 0.32 04/jan/2017 0.06 14/jan/2017 0.05 18/jan/2017 0.03 21/jan/2017 0.03 1 – Lake Malawi 29/jan/2017 0.03 29/mar/2017 0.04 3/apr/2017 0.04 19/apr/2017 0.10 26/apr/2017 0.83 3/may/2017 0.59 17/may/2017 0.76 31/may/2017 0.65 2 – Lumbadzi River --/--/2013 <0.001 3 – Linthipe River --/--/2013 <0.001 Source: data provided by LWB
Faecal coliforms are good indicators of organic pollution sources, namely from human settlements and cattle grazing areas. Manure spreading as fertilizer on fields during wet periods can also be a local source.
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 117
Table 35 – Faecal coliforms results for monitoring sites
Faecal coliforms Sampling Site Date (counts/100 ml) 23/dec/2016 142 28/dec/2016 1800 28/dec/2016 1800 04/jan/2017 100 14/jan/2017 150 18/jan/2017 180 21/jan/2017 180 1 – Lake Malawi 29/jan/2017 1350 29/mar/2017 2600 3/apr/2017 5500 19/apr/2017 2300 26/apr/2017 2500 3/may/2017 350 17/may/2017 1840 31/may/2017 600 2 – Lumbadzi River --/--/2013 1065 3 – Linthipe River --/--/2013 2355 Source: data provided by LWB
As can be observed above (Table 35), this type of contamination affects all sites. The lake site is strongly influenced by the high values from March to April 2017. This can be due to cattle grazing in the vicinity of the lake, as observed during fieldwork, and the proximity of Lifuwu and other settlements, where no sanitation exists.
Contamination usually peaks in the beginning of the wet season, following the first rains, when accumulated faecal matter in the fields during the dry season (when cattle comes to graze near the water) is washed to the lake. 28 December 2016 samples for the Lake most likely shows this kind of situation, with a peak over 1 800 count/100 ml. The Lumbadzi and Linthipe sites also have higher results around this time, especially on Linthipe, were the result surpassed 2 000 counts/100 ml.
There is no clear pattern of spatial variation which likely means that pollutions sources, while similar in nature, have distinct ways (or seasons) of influencing water quality.
118 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
7. Ecology, Flora and Fauna
7.1. Introduction
In this section the occurring ecosystems in the study area will be characterised in terms of the existing habitats and flora and fauna communities; this analysis will allow the identification of sensitive ecological values.
The geographic scope of this ecological analysis includes approximately 112 km of water conveyance pipeline and its immediate surroundings on a 100 m buffer zone (50 m per each side of the pipeline). Some potential impacts may have a superior area of incidence due to ecosystems’ continuity; these cases will be properly pointed out in the impact assessment phase.
The Project’s site comprises terrestrial and aquatic ecosystems, therefore the following biological groups are expected to be potentially impacted:
• Flora and vegetation; • Aquatic macro-invertebrates; • Ichthyofauna; • Herpetofauna; • Avifauna; • Mammals.
The pipeline (and therefore the study area) surrounds the west limit of Senga Hills Forest Reserve. This forest reserve has a reported area of 14.2 km2 and was designated in 1958. There are no other national protected areas nor international conservation areas (like IBA or Ramsar sites) in the study area.
For the ecological characterisation of the study area, a rigorous bibliographic research focused on the biological resources of the area was first conducted, and afterwards, the gathered data was crossed with the data collected during a fieldwork campaign in December, 2017.
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 119
7.2. Habitats
The natural and semi-natural habitats that occur in the study area include terrestrial habitats (woodlands and cultivated areas), terrestrial habitats with aquatic affinities (wetlands) and aquatic habitats (Lake Malawi). Each habitat has its own intrinsic ecological value, mainly reflected on the occurring floristic and faunistic values.
There are also artificial areas, mainly human settlements and other humanized areas, which due to their non-natural origin are not considered real “habitats”.
The characterization of the habitats occurring in the area was achieved through the following tasks:
• Preliminary mapping of the habitats described for the area based on bibliographic references cross-referenced with orthophoto map interpretation; • Fieldwork to assess and validate the produced cartography; • Description of the identified habitats according to their ecological composition and human intervention level.
From this procedure resulted a cartographic representation of the several habitat types occurring within the study area (see Volume 1 Annex – Map FF1, Habitat Map). The areas occupied by each habitat in the study area are presented as follows.
Table 36 – Areas of each habitat within the study area
Study Area – buffer Study Area – buffer Habitat 50 m 6 m Area (ha) Area (%) Area (ha) Area (%) Cultivated areas 649.11 57.9 77.41 57.6 Wetlands – Dambos 13.68 1.2 1.63 1.2 Wetlands – Permanent swamps 5.00 0.4 0.71 0.5 and marshes Wetlands (total) 18.69 1.7 2.34 1.7 Open woodlands 93.88 8.4 10.14 7.5 Closed woodlands 4.70 0.4 0.46 0.3 Graveyards 6.12 0.5 0.31 0.2 Woodlands (total) 104.69 9.3 10.90 8.1 Lake Malawi and shore 7.56 0.7 0.95 0.7 Humanized areas 340.29 30.4 42.81 31.8 Total 1120.34 100 134.42 100
120 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
From the analysis of Table 36 it is possible to conclude that cultivated areas are the main habitat of the study area, occupying almost 58% of the total area considering both buffers (50 m and 6 m). Humanized areas are the second largest category, corresponding to 30% of the study area.
The study area was characterised according to the occurring macro-habitats. Each macro-unit may comprise one or more habitats that have the same ecological functioning and functions, and thus do not justify to be represented separately.
The identified habitats are described in the following topics.
Cultivated areas
This semi-natural biotope includes cultivated areas and areas that are being prepared for cultivation.
Some cultivated species are seasonal (like maize and rice), while others are cultivated all year round (mainly vegetables) typically for families’ subsistence and small-scale sales (Figure 89 and Figure 90).
Source: NEMUS (2017) Source: NEMUS (2017)
Figure 89 – Market of fresh products along the Figure 90 – Vegetable selling along S122 road M14 road
The fieldwork was developed immediately before the wet season (during end of November and beginning of December); several areas were already in preparation for cultivation, with the soil already tilled, whereas in other areas farmers were expecting the rainy season to ease the soil tillage (Figure 91 and Figure 92).
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 121
Source: NEMUS (2017) Source: NEMUS (2017)
Figure 91 – Cultivated lands in study area: Figure 92 – Cultivated lands in study area: tilled lands (km 21+670, near Salima) untilled lands (km 40+620, Ta Karonga)
In some areas, cultivated lands occur in small patches with human settlements and with remains of woodlands that used to be the original habitat in the area. Croplands of larger extent are usually occupied by maize or rice.
In this semi-natural habitat, the occurring fauna is typically human-tolerant. Opportunist species can occur, drawn by the high availability of food in these areas. Animal husbandry is common practice, so cattle, goats, pigs and poultry are frequent, usually raised under free range near the villages.
Cultivated areas represent a habitat of low ecological value, since the occurring flora and fauna are mainly anthropogenic and ubiquitous. Nevertheless, these areas are economically and socially relevant, since agriculture is the main subsistence activity in the area.
Wetlands
Wetlands is a macro-habitat which include a variety of biotopes that share between them both the conservation interest and the ecological vulnerability.
To distinguish the types of wetlands occurring in the study area, one followed Hughes & Hughes (1992) and identified: dambos and permanent swamps and marshes.
122 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
Dambos frequently intersperse within woodlands. These grassy depressions are permanently or temporarily flooded wetlands located along drainage lines with herbaceous vegetation, mainly grasses and sedges, and absence of trees (FAO, 1996) (Figure 93 and Figure 94).
Some grass species occurring are: Brachiaria humidicola, Echinochloa pyramidalis, Entolasia imbricata, Hyparrhenia nyassae, Monocymbium ceresiiforme (Kindt et al., 2011).
Cropping is very common in these systems because of the water availability and soil fertility, which provides them a high potential for agricultural use (Frenken & Mharapara, 2002; FAO, 1996). Livestock grazing is also common in these habitats.
Source: NEMUS (2017) Source: NEMUS (2017)
Figure 93 – Dambo (km 9+350, Ta Maganga) Figure 94 – Dambo (km 7+480, Ta Maganga) (1) (2)
In permanent swamps and marshes the presence of Phragmites mauritianus and Typha spp. is common, and sometimes associated with free floating species, like Azolla nilotica, Pistia stratiotes and Utricularia spp., depending on the water levels (Figure 95 to Figure 97).
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 123
Source: NEMUS (2017) Source: NEMUS (2017)
Figure 95 – Permanent swamps and Figure 96 – Phragmites mauritianus marshes in study area (km 109+450, (km 67+900, Ta Chiwere) Lilongwe City)
Source: NEMUS (2017)
Figure 97 – Floating species in a swamp (km 2+250, Ta Kuluunda)
Wetlands represent an important ecosystem to local communities and it is common to find human settlements near them, since they guarantee food (security against droughts), good grazing and hunting sites and water availability (Frenken & Mharapara, 2002). They are also ecologically relevant since they retain water levels in flood peaks, are responsible for the maintenance of riverbanks and for the organic matter input into the aquatic food web (through the leaves and branches) and regulate the water temperature and insolation of the river channel.
124 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
Faunistic species occurring in wetlands have ecological preferences that include proximity to water and in some cases some human tolerance, due to the frequent presence of cultivated lands, such as: amphibians and reptiles (as Natriciteres olivacea), aquatic avifauna (as Cisticola njombe and Bugeranus carunculatus), otters (Aonyx capensis and Lutra maculicollis) and some bats (like Laephotis botswanae) (Hughes & Hughes, 1992).
Human presence constitutes the main threat to these ecological systems, since it leads to habitat loss and fragmentation and biodiversity degradation (clearance for agriculture or settlement and introduction of invasive alien species) (EAD, 2006).
Woodlands
“Woodlands” is the designation for a type of forest-grassland formation. In the study area this biotope is represented by miombo, which is a particular type of forest dominated by the genera Brachystegia and Julbernardia (Figure 98 to Figure 100).
Source: NEMUS (2017) Source: NEMUS (2017)
Figure 98 – Brachystegia boehmii (1) Figure 99 – Brachystegia boehmii (2)
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 125
Source: NEMUS (2017)
Figure 100 – Julbernardia spp.
Other tree species occurring in the area include Combretum spp., Piliostigma thonningii, Bauhinia spp., Terminalia sericea and Khaya anthotheca (Figure 101 to Figure 106).
Source: NEMUS (2017) Source: NEMUS (2017)
Figure 101 – Combretum sp. Figure 102 – Piliostigma thonningii
126 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
Source: NEMUS (2017) Source: NEMUS (2017)
Figure 103 – Piliostigma thonningii (leaf) Figure 104 – Bauhinia sp.
Source: NEMUS (2017) Source: NEMUS (2017)
Figure 105 – Terminalia sericea Figure 106 – Khaya anthotheca
These woodlands have a sparse understory generally of medium height, with dominance of herbaceous strata, and less or none scrubs or scandent species. There is a relative dominance of Poaceae (particularly of the genera Hyparrhenia, Andropogon, Panicum and Digitaria), although Asteraceae, Fabaceae, Malvaceae and Acanthaceae are also well represented (Morris, 2009).
Exotic tree species can also be found like Eucalyptus spp., Gmelina arborea and Toona ciliata (Figure 107 to Figure 109).
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 127
Source: NEMUS (2017) Source: NEMUS (2017) Figure 107 – Eucalyptus sp. Figure 108 – Gmelina arborea
Source: NEMUS (2017)
Figure 109 – Toona ciliata
This biotope varies throughout the study area: areas with high diversity and density (Figure 110) contrast with areas less diverse, with a more sparse cover and young individuals, simplifying the existing vegetation strata (Figure 111 and Figure 112).
In the study area the largest areas of this habitat occur along: km 38+000 and km 39+800, km 43+900 and km 44+900, km 61+600 and km 62+600, km 97+600 and km 99+600 and along the limit of Senga Hills Forest Reserve (km 2+300 and km 6+100).
128 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
Source: NEMUS (2017)
Figure 110 – Woodlands within study area: high diversity and complexity (km 58+700, Ta Chiwere)
Source: NEMUS (2017) Source: NEMUS (2017)
Figure 111 – Woodlands within study area: Figure 112 – Woodlands within study area: low diversity and size (km 2+650, Ta low diversity and size (km 57+000, Ta Kuluunda) (1) Chiwere) (2)
Fauna occurring in these habitats may include avifauna (like Polemaetus bellicosus and Circus macrourus), terrestrial mammals (like Civettictis civetta), bats (such as Epomophorus anselli and Epomophorus labiatus) and several reptile species.
Natural woodlands provide a relevant ecological, social and economic role, since they are the preferential biotope of occurrence of several species of conservation concern and they provide feedstock to the well-being of human populations (construction material, biofuel, charcoal and fuelwood) (Figure 113 to Figure 116).
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 129
Source: NEMUS (2017) Source: NEMUS (2017)
Figure 113 – Woodlands’ vegetation as Figure 114 – Woodlands’ vegetation as feedstock (1) feedstock (2)
Source: NEMUS (2017) Source: NEMUS (2017)
Figure 115 – Woodlands’ vegetation as Figure 116 – Woodlands’ vegetation as feedstock (3) feedstock (4)
Human dependence of this habitat has led to its decrease and degradation. Slash-and- burn agriculture and intensive wood extraction (for timber, firewood and charcoal) result in the increasing of soil erosion and loss of habitat and biodiversity (Lowore, 2006).
Patches of pristine woodlands may still be found in graveyards (Manda), since these are forested areas of unspoiled vegetation due to their sacred value and communities’ beliefs (Mauambeta et al., 2010) (Figure 117).
130 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
Source: NEMUS (2017)
Figure 117 – Graveyard
In the study area woodlands sometimes occur in patches with cultivated lands, which limits their conservation status.
Lake Malawi and shore
The study area includes part of the Lake Malawi and its shore (or beach), in Leopard Bay area, where the abstraction works is to be constructed (Figure 118).
Source: NEMUS (2017) Figure 118 – Lake Malawi and shore (km 0+700 Intake Pipeline, Leopard Bay/Salima)
Lake Malawi includes a protected area – Lake Malawi National Park – that does not overlap with the study area. This area was created for the conservation of the occurring fish (most of them are endemic) and aquatic habitats.
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 131
Lake Malawi is of extreme importance to all biological populations, including human population. People use the lake for economic, social and cultural purposes (fishing, bathing, washing). Local villages on the shore of the lake live in close relation with this habitat, since it is their main source of food and commercial resources (Figure 119 to Figure 122).
Source: NEMUS (2017) Source: NEMUS (2017)
Figure 119 – Human uses of Lake Malawi (1) Figure 120 – Human uses of Lake Malawi (2)
Source: NEMUS (2017) Source: NEMUS (2017)
Figure 121 – Human uses of Lake Malawi (3) Figure 122 – Human uses of Lake Malawi (4)
The aquatic fauna includes invertebrate species, like aquatic insects and molluscs, and vertebrate species, such as fishes, amphibians, mammals and aquatic avifauna. African Fish Eagle, White Breasted Cormorant, Cape Clawless Otter, Spotted Neck Otter, monitor lizards, hippopotami, crocodiles, Klipspringer and Rock hyrax, are examples of the fauna occurring in this lake (Kaleke, 2015) (Figure 123 to Figure 124).
132 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
Source: NEMUS (2017) Source: NEMUS (2017)
Figure 123 – Aquatic fauna occurring in the Figure 124 – Aquatic fauna occurring in the study area: bivalve molluscs study area: avifauna
Humanized areas
In the study area humanized areas are represented by human settlements or other infrastructure areas (like roads and roadsides, the last ones frequently lacking vegetation), and areas that were profoundly altered from their original features through human intervention, like gardened areas with exotic ornamental species and/or edible fruit species (Figure 125 to Figure 128).
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 133
Source: NEMUS (2017) Source: NEMUS (2017)
Figure 125 – Human settlements and Figure 126 – Human settlements and infrastructure areas within the study area infrastructure areas within the study area (km 0+400, Leopard Bay/Salima) (1) (km 96+150, Ta Chimutu) (2)
Source: NEMUS (2017) Source: NEMUS (2017)
Figure 127 – Planted garden areas in the Figure 128 – Planted garden areas in the study area (1) study area (2)
Characterised by ruderal, opportunists and ubiquitous floristic and faunistic communities when occurring, the ecological value of these non-natural areas is null.
134 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
7.3. Vegetation and flora
7.3.1. Vegetation
Phitogeographically the study area is located in the North Zambezian unit, in the Zambezian Region, following White (1983).
The vegetation types of this Phytochoria that occur in the study area are “Miombo woodland” (that divides itself in the subclasses “wetter miombo”, “drier miombo” and “miombo on hills and rocky outcrops”), “North Zambezian undifferentiated woodland and wooded grassland” and “Edaphic wooded grassland on drainage-impeded or seasonally flooded soils/Freshwater swamp”, the last one in a small extent (Figure 129).
Source: adapted from VECEA Figure 129 – Macro-scale vegetation framework of the study area
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 135
The “Miombo woodland” is included on the Zambezian miombo woodland. Miombo is the prevalent vegetation, nearly always dominated by Brachystegia spp., Julbernardia spp. or Isoberlinia angolensis. In the study area the first two are the most common.
Due to agricultural practices, miombo’s structure and floristic composition have been altered and simplified (White, 1983).
Associated species may occur, like Diospyros batocana, Pterocarpus angolensis, Afzelia quanzensis, Erythrophleum africanum, Anisophyllea pomifera and Parinari curatellifolia (White, 1983) (Figure 130).
Source: NEMUS (2017)
Figure 130 – Erythrophleum africanum
The “Wetter miombo woodland” in particular is floristically rich and includes nearly all the miombo dominant species: Brachystegia floribunda, B. glaberrima, B. taxifolia, B. wangermeeana, Julbernadia globiflora and J. paniculata are widespread in this vegetation type. Associated vegetation includes species of dry evergreen forest and thicket, swamp forest evergreen riparian forest and wet dambos (White, 1983; Kindt et al., 2011).
Characteristic but not dominant species of this vegetation type are: Burkea Africana, Dombeya rotundifolia, Flacourtia indica, Parinari curatellifolia, Pericopsis angolensis and Terminalia sericea. Other species frequently found are: Antidesma venosum (riverine species), Combretum zeyheri, Dichrostachys cinerea, Kigelia Africana, Piliostigma thonningii and Vangueriopsis lanciflora (Kindt et al., 2011).
136 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
The “Drier miombo woodland” is associated with dry deciduous forest and thicket, riparian forest and dry dambos. Species like Brachystegia boehmii, B. spiciformis and Julbernadia globiflora are frequently the only dominants occurring (Kindt et al., 2011).
The “Miombo woodland on hills and rocky outcrops” is roughly characterized by Brachystegia species occurring in shallow pockets of soil over rock pavements (Kindt et al., 2011).
The “North Zambezian undifferentiated woodland and wooded grassland” is defined by the nonexistence of the dominant species of miombo and mopane woodlands, although it has more tree species than either miombo or mopane woodlands (White, 1983; Kindt et al., 2011).
This vegetation type is very variable floristically and several miombo associated species frequently occur: Afzelia quanzensis, Burkea africana, Kigelia africana, Pseudolachnostylis maprouneifolia, Pterocarpus angolensis and Terminalia sericea (White, 1983).
Undifferentiated woodlands in Malawi have numerous and overlapping species assemblages. Recent studies have proposed five subtypes on this vegetation type, with the major one occurring in the study area being “Combretum-Acacia-Piliostigma woodland and thicket” (Kindt et al., 2011).
Characteristic species of Combretum-Acacia-Piliostigma woodland and thicket include: Acacia polyacantha, Acacia sieberiana, Albizia amara, Albizia versicolor, Brachystegia bussei, Burkea africana, Combretum zeyheri, Ozoroa insignis, Piliostigma thonningii, Pseudolachnostylis maprouneifolia, Pterocarpus angolensis, Strychnos potatorum, Ziziphus abyssinica. Other species occurring are Cassia abbreviata, Combretum adenogonium, C. collinum, C. molle, Crossopteryx febrifuga, Flueggea virosa, Markhamia obtusifolia, Stereospermum kunthianum and Strychnos spinose (Figure 131; Kindt et al., 2011).
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 137
Source: NEMUS (2017)
Figure 131 – Acacia polyacantha
The subtype “Acacia-Adansonia-Hyphaene-Sterculia woodland and thicket of the shores of Lake Malawi” may also occur although nowadays only relics of large trees of those species remain. Species listed for this subtype include Acacia polyacantha, A. seyal and Boscia salicifolia (Kindt et al., 2011).
The “Edaphic wooded grassland on drainage-impeded or seasonally flooded soils/Freshwater swamp” is also present in the study area, in some particular areas. These floodplain grasslands have less than 10% cover of wooden species, being sometimes classified as “grasslands” instead of “wooden grasslands”. Species of this class include: Alloteropsis cimicina, Bothriochloa bladhii, Chloris gayana, Dactyloctenium aegyptium, Echinochloa pyramidalis, Eragrostis atrovirens, Hyparrhenia rufa, Oryza barthii, Panicum repens, Pennisetum purpureum, Setaria spp., Sorghum spp. and Sporobolus spp.; Hyphaene petersiana is a characteristic species occurring (Kindt et al., 2011).
7.3.2. Flora
More than 6000 plant species are recorded in Malawi; 122 of these species are endemic and 34 are assessed in a category different from “Low Concern” in the IUCN Red Data List (Government of Malawi, 2015; IUCN, 2018).
138 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
Malawi’s great flora diversity results from the diversity of the occurring habitats. The alteration of pristine areas due to habitat conversion and exploitation led to a decline of specialist species. In the study area the existing flora diversity reflects the prevailing habitats.
The main two vegetation types occurring in the study area are floristically rich units that include both ubiquitous and frequent species and species that have a more restrict distribution and/or exhibit some degree of threat.
Aquatic vegetation comprises many forms: vascular macrophytic species, filamentous attached algae, phytoplankton and unicellular demersal algae. The aquatic vascular species are classified according to their life-forms as: rooted emergent macrophytes (like Phragmites mauritianus), rooted macrophytes with floating leaves (like Eichhornia crassipes), rooted submerged with floating leaves (as Potamogeton spp.) and free- floating macrophytes (EAD, 2006).
In Malawi more than 75 species of edible fruits are described, like Uapaca kirkiana, Parinari curatellifolia, Strychnos cocculoides, Flacourtia indica, Diospyros mespiliformis and Azanza garkceana (Shackleton et al., 2010).
Other species are harvested for fuelwood or show potential for timber plantations, due to their fast growth and high-quality wood, like Afzelia quanzensis, Acacia nilotica and Pteleopsis myrtifolia (Malawi Government, 1995).
Some species are used for medical purposes, and most of them grow as wild plants (Baumann, 2005; Morris, 2009), like Flueggea virosa.
Alien plant species are frequently harmful agents that may compete or hybridize with native species, affecting the entire ecosystem. In the study area, Eucalyptus sp. and Gmelina arborea are common species occurring, frequently planted as fuel wood.
Alien species are registered in the country such as Acacia mearnsii (black wattle), Eichhornia crassipes (water hyacinth), Prosopis glandulosa (mesquite), Lantana camara (lantana), Rubus spp., Salvinia molesta (kariba weed) and Pistia stratiotes (water lettuce) (Macdonald et al., 2003; EAD, 2006).
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 139
7.4. Fauna
The implantation of the pipeline will directly affect the terrestrial environment in its surroundings and the aquatic environment in the connection of the abstraction tower (intake pipeline) and in the river crossings. This justifies the analysis of both aquatic and terrestrial fauna.
Existing information on fauna occurring in the study area is scarce. The analysis made was based on the carrying capacity of the existing habitats, cross-checked with the habitat preferences of the faunistic species described for the area, according to the consulted bibliographic references.
7.4.1. Aquatic macro-invertebrates
Aquatic macro-invertebrate fauna is a relevant food resource to other faunistic communities such as fishes and avifauna.
There is no certainty on the existing aquatic macro-invertebrates’ richness of Malawi. Several studies undertaken in the country have registered 280 species of non-insect aquatic invertebrates, distributed among Molluscs, Nematodes, Crustaceans, Annelids and others (Figure 132; EAD, 2006).
Source: NEMUS (2017)
Figure 132 – Aquatic bivalve mollusc shell
140 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
In Malawi, 33 species of invertebrates are assessed with a Red List category above “Least Concern” according to IUCN (2018): two species are “Critically Endangered”; five species are “Endangered”; nine species are “Vulnerable”, five species are “Near Threatened” and the other 12 species are assessed as “Data Deficient”. Some of these species are restricted to specific areas (like Allocnemis maccleeryi, Allocnemis montana and Oreocnemis phoenix), while others have montane or dense forest habitats as preferential sites of occurrence (like Chlorolestes elegans, Nepogomphoides stuhlmanni, Teinobasis alluaudi and Umma declivium); therefore their presence in the study area is unlikely.
7.4.2. Ichthyofauna
The total number of fish species estimated for Malawi is of 850 species, from which over 800 are described for Lake Malawi, 95% are cichlids and 99% are endemic to the Lake (EAD, 2014). In riverine habitats cyprinids and some species of catfish can occur and represent important fishing resources.
According to the IUCN Red List (2018), 119 fish species occurring in Malawi have a conservation status above “Least Concern”: nine species were assessed as “Endangered”, 89 as “Vulnerable” and three as “Near Threatened”; 18 species are “Data Deficient”. Many species are endemic to Lake Malawi (like Aulonocara ethelwynnae, Aulonocara nyassae, Buccochromis atritaeniatus, Cynotilapia zebroides and Labidochromis pallidus) or occur exclusively in lacustrine habitats, whilst other species have lotic habitat preferences (like Pangio filinaris) or a more ubiquitous distribution (like Megalops cyprinoides and Oreochromis mossambicus). Species potentially occurring in the study area include mainly lentic habitat preferences.
Oreochromis is a genus that includes native species like O. mossambicus and O. squamipinnis, and alien species like O. niloticus and O. leucostictus, already registered in the Lake Malawi according to Genner et al. (2013).
In the study area over Leopard Bay/Salima fish fauna of Lake Malawi is a relevant food resource to local human populations as well as an economic resource. In fact, fisheries are the main economic activity of the villages near Lake Malawi: chambo (Oreochromis
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 141
sp.) and usipa (Engraulicypris sardella) compose the majority of catches in these villages (Figure 133 and Figure 134).
Source: NEMUS (2017) Source: NEMUS (2017)
Figure 133 – Engraulicypris sardella (Usipa) Figure 134 – Sun drying of usipa
To prevent the overexploitation of fish species there are laws that regulate the seasonal closures of some species. Nevertheless, overfishing is one of the main causes of decline of the existing fish species.
Habitat degradation and introduction/proliferation of alien species are the other two main threats to native ichthyofauna. Hybridization of exotic species with native species leads to fish genetics’ erosion (EAD, 2006). Moreover, exotic species are usually aggressive and voracious and compete with native species for food and space resources.
7.4.3. Herpetofauna
There are no accurate numbers for the total number of amphibian species in Malawi but according to the last National Report to the Convention on Biological Diversity (EAD, 2014) about 83 amphibian species have been recorded in Malawi, of which six species are endemic and eight are assessed in the IUCN Red List in a category different from “Least Concern” (IUCN, 2018).
142 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
From the eight species assessed in the IUCN Red List (2018):
• Nothophryne broadleyi and Amietia johnstoni are “Endangered”; the first one is known only from Mount Mulanje (Malawi) and Mount Ribaue (Mozambique), while A. johnstoni is endemic to Malawi and recorded only for Mount Mulanje; • Arthroleptis francei, Hyperolius spinigularis and Hyperolius inyangae are assessed as “Vulnerable” and are native from Malawi and Mozambique and Malawi and Zimbabwe (H. inyangae); • Mertensophryne nyikae and Ptychadena broadleyi are “Near Threatened”, being the last species endemic to Malawi; • For the species Hyperolius friedemanni the lack of information does not allow a grounded assessment, thus this endemic species was assessed as “Data Deficient”.
The assessed species are described for a specific spatial range that does not include the study area, even though for some species the preferential habitats of occurrence are habitats similar to those found in the study area.
Concerning reptile species, 145 reptile species are described for Malawi, from which eight are endemic and four are identified with a relevant conservation status in the IUCN Red List (Figure 135; EAD, 2014; IUCN, 2018).
Source: NEMUS (2017)
Figure 135 – Trachylepis sp.
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 143
The chameleon Rhampholeon chapmanorum is “Critically Endangered” due to the intense pressure over its small and fragmented occurrence area. Nadzikambia mlanjensis and Rhampholeon platyceps are also chamaeleonidae species and are endemic to Mount Mulange; both are “Endangered”. Cycloderma frenatum, a freshwater tortoise, is also assessed as “Endangered” (IUCN, 2018).
7.4.4. Avifauna
According to the last National Report to the Convention on Biological Diversity (EAD, 2014) there are over 630 bird species in Malawi (comprising migrant species), but only one species is endemic for the country, Apalis flavigularis (EAD, 2014).
A total of 36 species are listed in the IUCN Red List (2018) with a category different from “Least Concern”: three species are assessed as “Critically Endangered”, eight species are listed as “Endangered”; eight species are listed as “Vulnerable”; and 17 species are listed as “Near Threatened”.
The species Ceryle rudis (Pied Kingfisher), Ardea melanocephala (Black-headed Heron), Egretta garzetta (Little egret) and Scopus umbretta (Hamerkop) were recorded during fieldwork (Figure 136 to Figure 138).
Other species can potentially occur in the study area, depending on the available habitats and species’ habitat needs and preferences: Anthreptes anchietae (Anchieta's Sunbird), Accipiter melanoleucus (Black Sparrowhawk), Bubo lacteus (Verreaux's Eagle-owl), Bugeranus carunculatus (Wattled Crane), Buteo buteo (Eurasian Buzzard), Circus macrourus (Pallid Harrier), Coracias caudatus (Lilac-breasted Roller), Motacilla aguimp (African pied wagtail), Platalea alba (African Spoonbill) and Polemaetus bellicosus (Martial Eagle).
144 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
Source: NEMUS (2017) Source: NEMUS (2017)
Figure 136 – Ceryle rudis (Pied Kingfisher) Figure 137 – Ardea melanocephala (Black- headed Heron)
Source: NEMUS (2017)
Figure 138 – Egretta garzetta (Little egret) and Scopus umbretta (Hamerkop)
The proximity of Senga Forest Reserve may complexify the avifauna cast for the study area, since it is a forested native habitat.
Habitat loss and degradation as a result of clearing, drainage and conversion to agro- pastoral systems are the major threats to bird species that occur in the study area. These threats restrict the preferential areas of occurrence of the species, which may lead to the decline in the occurring diversity.
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 145
7.4.5. Mammals
There are about 192 mammal species recorded for Malawi, according to the Malawi Report to the Convention of Biological Diversity (EAD, 2014). Several of these species with terrestrial and aquatic affinities may occur in the study area.
A total of 26 species have been assessed with a concern category in the IUCN Red List (2018). While some of these species are clearly not described for the area, like Diceros bicornis (black rhinoceros) (extinct but was recently reintroduced in some protected areas) (“Critically Endangered”), Acinonyx jubatus (cheetah), Panthera leo (lion) and Loxodonta africana (african elephant) (all as “Vulnerable” species), others may potentially occur in the study area or in its surroundings, since their habitat requirements match with the occurring biotopes in the study area: Aonyx capensis (african clawless otter), Eidolon helvum (african straw-coloured fruit-bat), Hipposideros vittatus (Commerson's leafnosed bat) and Smutsia temminckii (Temminck's ground pangolin).
The total number of bat species registered for Malawi is 69 species, according to the African Chiroptera Report (ACR, 2016). Several species have aquatic affinities since they use rivers and lakes as main hunting biotopes, like Laephotis botswanae; others are usually recorded from miombo woodlands, like Epomophorus anselli and Epomophorus labiatus (ACR, 2014); these species represent potential occurrences in the study area.
Domesticated livestock like goats, cattle and poultry represent a relevant economic and food resource to human populations (Morris, 2009). During the fieldwork livestock and farm animals were frequently seen under free range near the human settlements (Figure 139 to Figure 142). A mongoose was also spotted during fieldwork.
146 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
Source: NEMUS (2017) Source: NEMUS (2017)
Figure 139 – Domesticated livestock identified Figure 140 – Domesticated livestock identified in settlements within the study area: goats in settlements within the study area: cattle
Source: NEMUS (2017) Source: NEMUS (2017)
Figure 141 – Domesticated livestock identified Figure 142 – Domesticated livestock identified in settlements within the study area: poultry (1) in settlements within the study area: poultry (2)
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 147
8. Socioeconomics and Public Health
8.1. Political evolution, administrative and community structure
The Republic of Malawi has an area of 118,484 km2 located in sub-Saharan Africa. It is bordered to the north and northeast by Tanzania, to the south, east and southwest by Mozambique and to the west by Zambia.
In the fifteenth century, the central and southern parts of the present territory of Malawi, together with the Zambian and Mozambican territories were part of a strongly established political system under the Maravi Confederation. This Confederation fell into decay in the late eighteenth century with the slave trade.
The first contact with westerners took place in the 19th century, in 1859, with the arrival of explorer David Livingstone and the discovery of lake Nyasa. Later, with the arrival of the missionaries and the British occupation, the area became the Protectorate of the Districts of Nyasaland, integrating, two years later, the British Protectorate of Central Africa, and in 1907, adopting the name of Nyasaland. In
Source: NSO (2008) 1953, Nyasaland, Northern Rhodesia (now Zambia) and Southern Rhodesia (now Figure 143 – Malawi Territory Zimbabwe) came together to form the Federation of Rhodesia and Nyasaland.
148 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
The action of the colonial administration generated discontentment, leading to the birth of the nationalist movement, that under the leadership of Hastings Kamuzu Banda, provoked the dissolution of the federation in 1963 and the proclamation of independence of Malawi on July 6th 1964.
Hastings Banda adopted a pragmatic policy of maintaining relations with South Africa while the apartheid was in force, and, on the domestic front, established a single-party state, the Congress Party of Malawi, which led, in 1971, to the re-election of Banda as president for life.
A growing internal uneasiness coupled with pressure from the church and the international community led to a referendum on the continuation of one-party state that had been in place since the independence. On 14th of June 1993, the people of Malawi overwhelmingly voted in favour of multiparty democracy and on 17th of May 1994, national elections were called, from which Elson Bakili Muluzu and the United Democratic Front party emerge.
That same year, the devastating drought plaguing the country left the agriculture sector in miserable state, forcing the Government to call for emergency international aid to the World Food Program.
Mr. Bakili Muluzi was in power until 2004, when he lost the elections for Bing Wa Mutharika who died in 2012 after being re-elected in 2009. Joyce Banda, the vice president, took the leadership of Malawi until the national elections of 2014, when Peter Mutharika became President of the Republic of Malawi until nowadays.
Malawi is a democratic republic with two spheres of government: national and local. The local government system has 35 single-tier authorities: 28 district councils (which are predominantly rural), four city councils, two municipal councils and one town council. The council is responsible for collecting local taxes and user fees and charges. However, the majority of its revenue comes from central government. All councils have the same responsibilities, including primary education, primary health, forestry, natural resources and community services.
The Northern Region consists largely of high plateaus and is the least densely populated area, with a density of 63 persons per square kilometre. This region is divided in six districts, namely: Chitipa; Karonga; Likoma; Mzimba; Nkhata Bay and Rumphi.
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 149
The Central Region has a population density of 155 persons per square kilometre and has low as well as high plateaus. Its divided in nine districts, namely: Dedza; Dowa; Kasungu; Lilongwe; Mchinji; Nkhotakota; Ntcheu; Ntchisi and Salima.
The Southern Region has a mixture of extremely hot areas, the highest mountain in the country, and cool fertile shire highlands. It has a population density of 184 persons per square kilometre. The Southern Region is divided in thirty districts, namely: Balaka; Blantyre; Chikwawa; Chiradzulu; Machinga; Mangochi; Mulanje; Mwanza; Nsanje; Thyolo; Phalombe; Zomba and Neno.
Each district is further divided into traditional authorities, which are ruled by chiefs. The village is the smallest administrative unit and each village is under a traditional village headman. A group village headman oversees several villages.
The Lake Malawi Water Supply Project for Lilongwe City involves abstraction of water from Lake Malawi (Leopard bay, Salima) through a 2km long pipeline till Lifuwu Water Treatment Works and after that the transportation of treated water through a 110- km conveyance pipeline to Lilongwe City. It totalizes roughly 112 km of water pipelines, and it develops most of the way along the M14 Lilongwe – Salima Road, until LWB’s Kanengo reservoirs.
The project is developed in three districts of the Central Region and the following administrative areas (Figure 144):
• Lilongwe District - Lilongwe City and TA Chimutu; • Dowa District - SC Mkukula and TA Chiwere; • Salima District - Salima Town, Sub TA Bibi Salima, TA Karonga, TA Kuluunda and TA Maganga.
150 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
Figure 144 – Administrative areas where the project develops
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 151
8.2. Population characteristics and dynamics
The results from the last census (2008) state 13 066 320 million as the total population in Malawi. The population increased 32% in a ten years period, from 9 933 868 million in 1998 (1998 census) to 13 066 320 million in 2008. Out of this, 6 365 771 million (49% of the total population) are men and 6 700 549 million (51% of the total population) are women (Figure 145).
The population is unevenly distributed along the country’s regions. At region level, the results show that the Southern Region is the most populated, with 5 876 784 million as total population (45%), Central Region is a close second, with 5 491 034 million (42%) and, finally, the Northern Region has 1 698 502 million of people (13%) (Figure 145).
Comparing the last census (1998 and 2008), results show a change in the regional distribution pattern. A reduction in the population residing in the Southern Region was noted, but at the same time Central and Northern Regions have increased its population.
Figure 145 – Total population by sex and region, in 2008
Source: NSO (2008)
152 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
Source: NSO (2008)
Figure 146 – Population by Urban and Rural areas and by Region, in 2008
The population of Malawi lives predominantly in rural areas. Considering the 2008 census, more than 80% of the total population lived in rural areas. This pattern occurs in all regions of the country, but is higher in the Northern Region (Figure 146).
In Malawi, urban areas refer to the four major cities of Blantyre, Lilongwe, Mzuzu and Zomba. Urban population in Malawi has been increasing, from about 1,4 million of people in 1998 to 2,0 million of people in 2008 (National Statistical Office, 2018).
When analysing the age and sex distribution of the population, the results show that 2,8 million of people were aged under-five years and about 6,0 million were aged 18 years or more. At national level the census results reveal that about 7% of the total population in Malawi comprised infants aged less than 1 year, 22% were aged under-five years and about 46% were aged 18 years or older, while a further 4% were aged 65 years or older. The age and sex distribution on population shows that Malawi has a young population.
The Figure 147 shows population distribution of people who are 18 years and older, by region and by sex. The figure indicates that population aged 18 years or more is 6 216 432 million of people (48% of the total). Of this fraction, 2 972 335 million are males and 3 244 097 million are female. The population distribution of persons aged 18 and above across regions show that Southern Region has 45%, Central Region the 42% and 13% in the Northern Region.
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 153
7 000 000 6 000 000 5 000 000 4 000 000 3 000 000
2 000 000 TotalPopulation 1 000 000 0 Malawi Northern Region Central Region Southern Region
Male 18+ Female 18+ Total 18+
Source: NSO (2008)
Figure 147 – Population distribution of persons aged 18 years and above by region and by sex, in 2008
As stated earlier, the project area is integrated in the Central region, the second largest region of Malawi. Table 37 presents some demographic indicators of the three districts crossed by the Lake Malawi Water Supply Project for Lilongwe City.
Between 1998 and 2008, the population of Malawi increased by 32%, representing a 2,8%annual growth rate. The districts also increased their population, mainly the Lilongwe district, that has presented a 3,5% annual growth rate. The population projections for the coming years point out to a steady and positive growth and Malawi is expected to grow at an annual growth rate of more than 3% by 2030.
The global population density for Malawi, in 2008, was 139 persons per square kilometre in. As for the districts, there are more people per square kilometre in the Lilongwe district (1 695) than in the other two districts, 184 and 154 in the Dowa and Salima Districts, respectively.
154 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
Table 37 – Key demographic indicators (1998-2030)
Lilongwe Dowa Salima Variable Year Malawi District District District
1998 9 933 868 1 346 360 411 387 248 214 Population 2008 13 077 160 1 905 282 558 470 337 895
2018 17 931 637 2 791 581 866 218 458 357 Population (projected) 2030 26 090 975 4 318 525 1 365 292 649 836
1998- 2,8% 3,5% 3,1% 3,1% 2008
Annual Increase 2008- 3,2% 3,9% 4,5% 3,1% Rate 2018
2018- 3,2% 3,7% 3,9% 3,0% 2030
Land Area (Sq. 2008 94,276 6,159 3,041 2,196 Km.)
Population 2008 139 1 695 184 154 Density
Source: NSO (2008) Projected Population based on 2008 Malawi Population and Housing Census
Based in the 2015-16 Malawi Demographic and Health Survey (2015-16 MDHS) of National Statistical Office (NSO), there is recent information about the fertility. The total fertility rate (TFR) in Malawi is 4,4 children per woman. Women in rural areas have higher fertility, on average, when compared to women in urban areas. The age specific-fertility rates start at 136 births per 1000 women among women age 15-19, peak among women age 20-24 (2016 births per 1000 women), decline thereafter, and reach the lowest level among women age 45-49 (18 births per 1000 women).
The number of children per woman declines with a woman’s education level. A woman with no education has an average of 5,5 children compared with 2,3 children for a woman with more than secondary education.
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 155
As mentioned in the 2008 Population and Housing Census Malawi (NSO, 2008), lifetime inter-district migration refers to migration that has occurred between birth and the time of the census within the country.
The Lilongwe District attracted 188 084 inhabitants in 2008. The main origins of the new Lilongwe City inhabitants are: Lilongwe Rural (about 39 000 inhabitants), Dedza (about 36 000 inhabitants) and Ntcheu (about 29 000 inhabitants) (NSO, 2008) the Salima District attracted 4 103 new inhabitants. On the other hand, the Dowa District lost 41 775 inhabitants in 2008 (Table 38).
Table 38 – Internal Migration, in Malawi and at Districts, in 2008
Lilongwe Salima Variable Malawi Dowa District District District In migrants 2 111 181 420 813 52 063 52 995 Out-migrants 2 111 181 232 729 93 838 48 892 Net migration 0 188 084 -41 775 4 103 Source: NSO (2008)
The census classified the population by nationality. Based in the National Statistical Office (NSO, 2008), foreign population was representing less than one percent of the population (51 554 of people). Of the foreign population, Mozambicans represented the most part (37%), followed by Zambians, who accounted for 11% of the total foreign population.
Finally, the census classified the population by religion. Table 39 shows that from the 13 million usual residents, 10,8 million (83%) were Christians, 1,7 million (13%) were Muslims, 2% follow other religions and 3% did not follow to any religion.
Table 39 – Population distribution by religion, in 2008
Variable Number Percent Christian 10 770 229 82,7% Muslim 1 690 087 13,0% Other 242 503 1,9% None 326 679 2,5% Source: NSO (2008)
156 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
8.3. Education and literacy
Literacy is one of the main indicators of socioeconomic development in a society. Reduction in illiteracy is very much associated with various other indicators such as reduction of infant mortality rates, improvement in food security, wealth status. The reduction in illiteracy promotes the combat to poverty and might spur economic growth of a society.
The impact of literacy is not only on reading and writing, but also on personal dignity, the right to participate, the empowerment of the marginalized and excluded, and the opportunity to learn in a variety of ways and settings.
Table 40 gives literacy status of persons aged 5 years by region, in 2018. There were 10,7 million people aged 5 years and older. Out of this, 6,8 million were literate, representing a 64% literacy rate. The table also shows that there were 2,9 million literate people in Southern Region, 2,8 million in Central Region and 1,1 million in Northern Region.
Table 40 – Literacy status of persons aged 5 years and older by region, in 2008
Administrative Illiterate Literate Total division Malawi 3 844 575 6 831 770 10 676 345 Northern Region 322 062 1 058 993 1 381 055 Central Region 1 693 905 2 809 897 4 503 802 Southern Region 1 828 608 2 962 880 4 791 488 Source: NSO (2008)
One of the major goals to be achieved on literacy is gender equality. Table 41 shows that in regard to gender distribution of the literate population, the proportion of literate females increased from 51% in 1998 to 59% in 2008, thereby decreasing the gender gap among the literate population between the two censuses (NSO, 2008).
Table 41 - Sex distribution of the literate population, in 1998-2008
Variable Census of 1998 Census of 2008 Male (%) 65% 69% Female (%) 51% 59% Source: NSO (2008)
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 157
Table 42 – Literacy rate by sex for districts, in 2008
Administrative Literacy rate division Total Males Female Malawi 64% 69% 59% District Lilongwe 57% 63% 52% Dowa 63% 67% 59% Salima 57% 63% 51% Source: NSO (2008)
Table 42 gives literacy rate by sex for districts in project area. The Dowa district has the highest literacy rate (63%), compared to the other districts under analysis. The literacy rate is lower for women, in any district.
According to the National Education Sector Plan (2008-2017), education and training in Malawi is classified into four broad categories:
• Basic education (which includes early childhood development, non-formal education which includes adult literacy and out of school youth, and primary education); • Secondary education; • Tertiary education (which includes teacher training and technical and vocational training); • Higher/university education.
In general, basic education has three main components: early childhood development (ECD), adult literacy including out of school youth literacy and primary education (PE). In Malawi, however, basic education is synonymous with Primary Education, ECD is thought of as infant care and support, adult literacy and out school youth is non-formal education.
The formal education system in Malawi follows an 8-4-4 structure: 8 years of primary school, 4 years of secondary and typically 4 years of university level education. Primary, secondary, teacher training, tertiary and higher education levels are under the authority of the Ministry of Education Science and Technology (MoEST). Primary and secondary education is administered by the MoEST through its headquarters, the 6 education divisions and 34 districts education offices. University education is sub-vented by government, and university are autonomous.
158 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
Early Childhood Development (ECD) in Malawi involves programmes for children from birth to age five and its main purpose is to protect child rights and foster full cognitive, emotional, social and physical development. ECD services are categorized into two levels: the first level (baby care centres), for children aged 0-2 years, is usually offered by the private sector. The second level, for children aged 2-5 years, is either provided by the private (preschools/nurseries) sector or the public sector (community-based child care centres).
The official school going ages in Malawi are 6 to 13 years for primary school level, 14 to 17 years for secondary school level and 18 to 24 years for post-secondary school level.
Table 43 shows the distribution of school going age population by sex and region for persons aged 6 to 24 years. The results show that in 2008 the official school going age population constituted about 43% of the total population in Malawi. Out of these, the primary school age comprised 22% while the secondary school age comprised about 8% of the total population and about 13% were the post-secondary school populations.
Further, the results in Table 43 show small variations by sex in primary and secondary school ages. For primary school it was 22,3% for males and for females it was 21,6% while for secondary schools for males it was 8,6% and 8,1% for females. Similar observations are noted when the three regions are compared.
Table 43 – Percent distribution of school going age population by sex and region, 2008
Post- Primary Secondary Secondary Total School Indicator School Age School Age School Age Age (6-24) (6-13) (14-17) (18-24) Sex Male 22,3% 8,6% 12,3% 43,3% Female 21,6% 8,1% 13,9% 43,6% Region Northern 22,2% 8,7% 13,1% 44,0% Central 21,9% 8,5% 13,2% 43,6% Southern 22,0% 8,0% 13,1% 43,1% Total 22,0% 8,3% 13,1% 43,4% Source: NSO (2008)
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 159
Table 44 – Percent distribution of persons 6 years and over by school attendance status for district, in 2008
Never Currently Indicator Ever attended attended attending Malawi 21,6% 50,5% 27,9% Sex Male 16,4% 55,1% 28,5% Female 26,5% 46,2% 27,3% District Lilongwe 17,0% 55,8% 28,0% Dowa 22,1% 51,2% 26,6% Salima 28,5% 46,1% 25,5% Source: NSO (2018)
There is difference in the proportions of persons who have attended school by place of residence. Comparing the three districts, Salima district had the highest proportion (29%) of persons aged 6 years and older never attended school while the Lilongwe district had the lowest proportion (17%) and Dowa district had 22% (Table 44).
Table 45 – Population aged 5 years and over by highest educational level attended and by district, in 2008
Highest level attended Indicator Total Pre-school Primary Secondary University Malawi 10 676 345 33 609 2 692 029 249 019 8 877 District Lilongwe 1 567 872 4 474 372 952 44 343 2 115 Dowa 462 216 872 116 7 309 115 Salima 274 042 776 65 4 308 78 Source: NSO (2018)
Additionally, according to the Population and Housing Census Malawi (NSO, 2008), in the Lilongwe district there are more population with the major levels of education (Table 45). Comparing with two other districts, Dowa Salima had the highest population with the major levels of education while the Salima district. However, this analysis should take into consideration the relative proportion of populations.
160 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
The African Development Bank reported that the national literacy rate of Malawi was 71,3% in 2013 (African Union Commission and ECA, 2016), while the estimated adult literacy rate for the same year was estimated at 61,3%, disaggregated into 70,0% for female and 74,3% for males. This data represents significant improvement since the 2008 census, which recorded the national literacy rate at 63%, disaggregated into 69% and 58% for males and female, respectively. The report also highlights the significant progress and achievements made by the Government in reducing the education gender gaps and enhancing the countries’ human resource stock.
8.4. Household and housing characteristics
Housing and shelter are important indicators when it comes to assessing living conditions of a population. Housing is one of the basic human needs, and has a profound impact on health and welfare of an individual.
The average household size is calculated as the ratio of the total household population to the number of households in an area. The 2008 census shows that average household size of Malawi of 4,6. Average household size is higher in the Northern Region (5,2), followed by the Central Region (4,7) and finally by the Southern Region (4,4) (Figure 148).
Source: NSO (2008)
Figure 148 – Household size by Region, in 2008
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 161
A housing unit is classified as traditional if it is built with both thatched roof and mud walls. On the other hand, a house is classified as permanent if the house or block is generally built using modern or durable facilities. A semi-permanent house is the one that has generally been built using modern and partial lasting materials.
Table 46 – Number of persons and type of dwelling unit by district, in 2008
Lilongwe Salima Indicator Malawi Dowa District District District Persons in dwelling 12 615 298 1 847 836 541 227 327 117 Units Permanent 2 894 291 450 658 79 277 46 432 Semi- 4 306 883 593 091 105 805 122 229 Permanent Traditional 5 414 124 804 078 356 145 158 456 Source: NSO (2018)
There were 12 615 298 persons enumerated in regular households and 461 862 were in institutions and homeless (In 2008, the population of Malawi was of 13 077 160). According to the Table 46 the majority of persons (43%) were living in traditional dwelling units, 34% of persons lived in semi-permanent dwellings and 23% lived in permanent dwelling units.
The table further shows that at district level there is the same pattern. That is, in both districts, there are more people living in traditional dwelling units, followed by semi- permanent dwellings and finally permanent dwellings units.
Most people live in informal settlements, where the living conditions are underdeveloped and inhabitants have little or no access to social infrastructures and basic urban services. The houses, with their poor conditions, are also vulnerable to disasters (e.g., fire and flood).
Throughout the three districts (Lilongwe, Dowa and Salima) the houses are mainly built of temporary floors and in the majority of the dwellings units are made of earth or sand. The burnt and unburnt bricks are dominant wall materials and the roofing materials more commonly used in dwelling units are the grass thatch and iron sheets (Figure 149 and Figure 150).
162 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
Source: NEMUS (2017)
Figure 149 – Examples of existing houses in the project area, in TA Chiwere
Source: NEMUS (2017)
Figure 150 – Examples of existing houses in the project area, in TA Maganga
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 163
Sanitation and main source of drinking
As one of the most basic human necessities, the access to safe water and sanitation are important development goals. Increased access to safe drinking water results in improved health outcomes in form of reduced cases of water borne diseases and the availability of latrines is of utmost importance to basic health in a home.
The sources of drinking water in both the wet and dry seasons includes; piped water sources (piped into dwelling, piped into compound and communal stand pipes); boreholes, wells and springs.
Table 47 – Population distribution of households according to main source of drinking water by districts, in 2008
Main source of drinking water Piped Comm- Adminis- Piped Un- Pro- into unity Bore- trative into protected tected Spring River yard/ stand hole division dwelling well well plot pipe Lilongwe 109 294 146 093 282 090 418 436 212 108 613 265 3 643 54 493 District Dowa 4 583 6 372 8 549 180 729 50 240 220 016 4 449 64 603 District Salima 6 754 11 515 10 199 25 120 20 768 218 963 955 29 977 District Source: NSO (2018)
Table 47 shows that borehole is the main source of drinking water in the three districts. Almost half of the households in Malawi used borehole as a main source drinking water in 2008 while a quarter used the same source in 1998 (according the public resultants of 1998 census).
There are wide variations in the main drinking sources used between rural and urban households. Slightly above half of the rural households use boreholes as the main source of drinking water. Piped water sources (piped into dwelling, piped into compound and communal stand pipes) have remained a resource enjoyed only by the urban households (NSO, 2008).
164 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
Most of the drinking water is abstracted from boreholes in the study area and its immediate surroundings. Groundwater consumption is available at villages located in the study area and/or immediate surroundings especially thorough communal hand-pumps in villages or individual boreholes/wells.
Source: NEMUS (2017)
Figure 151 – Examples of sources of drinking water, in TA Chiwere
Source: NEMUS (2017) Figure 152 – Examples of sources of drinking water, in TA Chimutu
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 165
Source: NEMUS (2017)
Figure 153 – Examples of sources of drinking water, in Lilongwe City
Improved sanitation facilities are a key to environmental health, and availability of latrines is very important to basic health standards in a home. Poor sanitation facilities coupled with unsafe water sources pose a serious risk of water-borne diseases.
Table 48 – Population distribution of households according to type of toilet facility used by district, in 2008
Type of toilet facility Adminis- Traditional pit Improved pit trative Flush toilet No facility Other toilet (VIP) latrine division Lilongwe 114 060 1 482 112 23 459 205 542 22 663 District Dowa 4 239 453 936 11 050 62 333 9 669 District Salima 6 723 242 154 6 137 63 409 8 694 District Source: NSO (2018)
Table 48 show that traditional pit latrine has the principal toilet facility used in the three focused districts.
166 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
The 2008 census indicate that the traditional pit latrine is the most common type of toilet facility used by both rural and urban areas. There are more households without latrines in the rural areas, however, there has been a downward trend in the percent of households without latrines.
The use of pit latrines is very common, resulting in high levels of pollution of underground in these areas, as well as in the spreading of diseases.
Source: NEMUS (2017)
Figure 154 – Examples of type of toilet facility, in TA Chiwere
Main sources of energy
The use the paraffin was the most common used source of energy for lighting in Malawi, in 2008. For cooking, the majority of households used the firewood.
In the three districts houses, the main source of energy for cooking and for lighting is firewood and paraffin (Table 49 and Table 50), respectively. Nonetheless, in Lilongwe district and Salima district the charcoal is emerging as the main source of energy for cooking and electricity as the second source of energy for lighting. In Dowa district, the second source of energy for lighting is the firewood.
In the study area and its surroundings, firewood is the dominant source of energy for cooking, charcoal production is predominantly for sale purposes.
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 167
Table 49 – Population of households by main source of energy for cooking by district, in 2008
Main source of energy for cooking Adminis- trative Electricity Paraffin Gas Charcoal Firewood Straw Other division Lilongwe 109 803 19 248 480 268 015 1 432 826 14 888 2 576 District Dowa 2 867 6 252 21 13 503 517 095 1 065 424 District Salima 3 785 4 607 21 11 329 301 734 5 404 237 District Source: NSO (2008)
Table 50 – Population of households by main source of energy for lighting by district, in 2008
Main source of energy for lighting Administrative Electricity Paraffin Candles Firewood Other division
234 968 1 424 341 134 767 31 254 22 506 Lilongwe District
11 005 480 662 9 654 19 404 20 502 Dowa District
13 417 295 616 3 992 7 564 6 528 Salima District Source: NSO (2008)
Household assets and other facilities
The welfare of households also depends on the asset base as well as the economic activities undertake.
In the study area and its surroundings, radio is the most common asset owned by households, followed by bicycle (Table 51).
The ownership of radio and bicycles is an important indicator of the social and economic development of Malawian households.
168 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
Table 51 – Population of households by type of assets by district, in 2008
Administrative Owned a Radio Owned a bicycle Oxcart division Lilongwe District 1 210 613 833 993 66 938 Dowa District 333 548 222 936 27 293 Salima District 187 118 154 573 4 404 Source: NSO (2008)
8.5. Social conditions and public health
In the last ten years Malawi has seen some progress in non-monetary indicators of human development. However there have been persistent challenges with respect to progress in some health and education aspects, and due to large flows of Official Development Assistance (ODA). Malawi partially or fully achieved 4 of 8 of the Millennium Development Goals.
In the 2015 Human Development Report, the human development index for Malawi improved minimally to 0,445 (2014) from 0,439 in 2013. Its ranking also improved slightly, from 174th to 173rd out 188 countries.
Although Malawi has recorded robust economic growth rates since the mid-2000s, the country’s poverty levels have remained persistently high, improving only slightly. This is one of the country’s development challenges.
The results of the most recent Integrated Households Survey, showed that the poverty levels, namely the percentage of the population classified as poor, was 50,7%. The survey also showed that poverty levels are higher in the rural areas compared to the urban ones. Poverty levels were the highest in the Southern Region, followed by the Northern Region and Central Region. Despite alleviating poverty in recent years, it is a great concern that while national and urban poverty levels are decreasing, rural poverty levels are rising, mainly due to the high rural population, limited income generation activities, associated with the largely subsistence agriculture sector, and unavailability of basic public services.
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 169
Inequality in Malawi, unlike poverty, has worsened. Nationally, the Gini coefficient increased from 0,390 in 2005 to 0,452 in 2012. Although higher in urban area as compared to rural areas, it worsened more in rural areas. Geographically, the Southern Region has the highest Gini coefficient, which reflects higher income inequality. In terms of gender, female-headed households are poorer than their male-headed counterparts.
Inequality in Malawi, unlike poverty, has worsened. Nationally, the Gini coefficient increased from 0,390 in 2005 to 0,452 in 2012. Although higher in urban areas as compared to rural areas, it worsened more in rural areas. Geographically, the Southern Region has the highest Gini coefficient, which reflects higher income inequality. In terms of gender, female-headed households are poorer than their male-headed counterparts.
The majority of Malawians are vulnerable to social and economic shocks, which exacerbate poverty. According to the World Bank there are four major shocks that make households vulnerable to poverty. These include:
• Over reliance on rain fed agricultural production systems which are prone to climatic shocks; • Animal and plant diseases which lead to major crop and livestock losses; • Volatility of prices of maize, fertilizer and tobacco; • HIV/AIDS, malaria, tuberculosis and anaemia which are prevalent in Malawi.
The population of Malawi is projected to be more than triple of its current total in the next 30 years. If unchecked, this rapid growth would overwhelm the already struggling health care system, resulting in inefficiencies and failures.
The most recent Demographic and Health Survey (2015-2016 MDHS) shows that modern contraceptive use among married women rose from 7% in 1992 to 42% in 2010, and the fertility rate dropped from 6,7% to 5,7% during the same period (USAID, 2018). The health status of children and women was reflected in the results of interventions aimed at reducing child mortality and improving maternal health, corresponding to Millennium Development Goals. In this way, the under-five mortality rates declined from 112 per 1000 live births in 2010 to 85 in 2014, infant mortality declined 71,05 to 53 per 1000 live births and neo-natal mortality declined from 25,7 to 21,8. The maternal mortality declined from 675 per 100,000 live births in 2010 to 574 in 2014 (United Nations, 2018).
Nutritional health of children is a serious health and development problem in Malawi. The Demographic and Health Survey of 2015-2016 shows that 48% of children under 5 years
170 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
old were stunted and severely stunted, 3% were wasting and 15% were underweight and severely underweight.
Malaria is the leading cause of morbidity and mortality in children under five years and pregnant women in Malawi. The Ministry of Health (MOH) estimates that malaria accounts for 34% of all outpatient visits and 40% of all hospital admissions among children under five years. Four out of ten hospital deaths are reported to be due to malaria. The disease is endemic throughout Malawi and continues to be a major public health problem, with an estimated six million cases occurring annually.
The ownership and use of both treated and untreated mosquito nets is the primary prevention strategy for reducing malaria transmission in Malawi. The Malawi Ministry of Health adopted the distribution of insecticide-treated nets (ITNs) as one of the major malaria control interventions in 2005.
Malawi implemented a nationwide universal access campaign in 2012, during which 5,6 million nets were distributed countrywide. In December 2014, 1 158 968 ITNs were distributed during the first phase of the 2014-2015 national campaign. The 2015-2016 MDHS showed that 63% of households have at least one mosquito net and 57% have at least one ITN. On average, there are 1,1 ITNs per households.
Although the national HIV prevalence decreased from 12% in 2004 to 10,6% in 2010, Malawi continues to face a severe epidemic. Women are disproportionately affected, and there are approximately 770 000 children orphaned because of AIDS (USAID, 2018).
The joint United Nations Programme on HIV/AIDS in its 2015 HIV and AIDS estimates stated there were 980 000 adults and children living with HIV in Malawi. In 2015, Malawi developed the 2015-2020 National HIV and AIDS Strategic Plan (NSP) which provides a new framework for the implementation of HIV programs that align with the UNAIDS 90- 90-90 targets. The 2015-2020 NSP focuses on case identification and the promotion of access to antiretroviral therapy (ART), adherence, and retention (2015-2020 NSP). National efforts and investments from donors and other partners have also focused on HIV prevention, knowledge and behavioural interventions. In 2014, Malawi developed the 2015-2020 HIV Prevention Strategy that focused on delivering behaviour change interventions such as life skills education, promotion of faithfulness, use of male and female condoms and activities that addressed gender-based violence, stigma and discrimination and harmful cultural practices.
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 171
According to the 2015-2016 MDHS, about three-quarters of women and men age 15-49 know that using condoms can consistently reduce the risk of HIV infection. More than eight in ten women and men (86% of women and 89% of men age 15-49) know that limiting sexual intercourse to one uninfected partner who has no other partners can reduce the risk of HIV. Seventy percent of women and men know that both consistent condom use and only having sex with one uninfected partner can prevent HIV. The percentage of men and women with comprehensive knowledge about HIV/AIDS has only increased a few percentage points between 2010 and 2015-2016 moving from 41% to 42% among women and 45% to 48% among men.
Tuberculosis is a major public health problem in Malawi. In 2013, 20 335 new and relapse cases and 1 400 deaths were reported in Malawi. The World Health Organization estimates that only 78% of tuberculosis cases are diagnosed in Malawi. Six in ten people with tuberculosis are also infected with HIV. The number of tuberculosis cases in Malawi increased steadily from 1995 until 2003, when it reached its peak. Since 2003, there has been a downward trend to just over 20 000 cases recorded in 2013.
In the study area and its surroundings, fever and malaria was the highest reported illness followed by sore throat and headache.
At district level, Lilongwe district report the highest percentage of people who suffered from fever and malaria at 53,7%, followed by the Salima district at about 50,4% and then the Dowa district at 41,3% (Table 52).
Table 52 – Proportion of distribution of top most reported diseases (2016-2017)
Top most diseases suffered Adminis- Fever Respira- Sore Stomach trative and Headache Diarrhoea tory Other Throat Ache division Malaria Infection
Malawi 45,2% 14,5% 9,2% 7,0% 3,9% 0,8% 19,5%
Lilongwe 53,7% 6,9% 10,0% 9,3% 3,6% 0,6% 15,9% District Dowa 41,3% 24,2% 6,2% 7,7% 2,5% 0,4% 17,7% District Salima 50,4% 6,6% 12,0% 4,4% 4,4% 0,0% 22,1% District Source: IHS4 REPORT (2018)
172 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
8.6. Economic activity
Economic growth in 2016 remained sluggish at 2,7%, largely due to the El Niño2 induced drought, but is projected to improve to 6,1% in 2017 and further 5% in 2018 (Figure 157). Due to its poverty levels, increasing population, and advanced environmental degradation, Malawi is especially vulnerable to climatic shocks and hard-won development gains are fragile in the face of climatic shocks such as those caused by El Niño.
Source: Annual Economic Report (2017)
Figure 155 – Annual growth rates the Malawi GDP, 2011-2018
The modest growth of Malawi’s GDP in 2016 was mainly caused by weather related shocks and unstable macroeconomic conditions. The drought negatively affected the agricultural sector and led to a decline in production of major crops, such as maize, tobacco and tea.
2 El Niño occurs when the Pacific Ocean warms and disrupts weather around the globe. In Malawi, where the rains were delayed in places by up to two months, the ongoing El Niño has resulted in a severe drought, and led to failed crops for many subsistence farmers.
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 173
Improvements in some of the macroeconomic fundamentals such as availability of fuel and foreign exchange and stability of the domestic currency against the US Dollar, contributed to the growth of some sectors. Despite these positive outcomes, higher growth potential was undermined by high interest rates, the high inflation rate, intermittent power supply and high cost of inputs such as labour, electricity and raw materials.
According to the Annual Economic Report of 2017 (Ministry of Finance, Economic Planning and Development), the economy is recovering in 2017, following the favourable weather conditions. GDP growth is projected at 6,1% on account of the good performance in agriculture and fishing, which is estimated to grow by 6,8%, manufacturing, with a growth of 4,9%, construction, with a growth of 5,1%, wholesale and retail trade, with a growth of 6,6% and financial and insurance activities, with a growth of 7,3% (Table 53). In 2018, GDP growth is projected to remain strong, at 5%. The growth will mainly be driven by stability of the macroeconomic environment which is expected to promote private sector investment (AER, 2017).
Table 53 – Annual percentage growth rates, 2014-2018
Sector 2014 2015 2016 2017 ⃰ 2018 ⃰ GDP at constant market prices 6,2% 3,3% 2,7% 6,1% 5,0% Agriculture, forestry and fishing 6,3% -1,0% -0,2% 6,8% 3,4% Mining and quarrying -4,6% 1,1% 0,4% 1,6% 2,3% Manufacturing 6,3% 3,8% 1,4% 4,9% 6,0% Electricity, gas and water supply 3,0% 2,4% 0,4% 2,2% 4,5% Construction 4,8% 3,5% 3,4% 5,1% 5,9% Wholesale and retail trade 6,3% 4,9% 2,0% 6,6% 3,8% Transportation and storage 4,8% 4,3% 4,7% 6,3% 5,9% Accommodation and food services 5,9% 5,1% 5,7% 4,6% 3,9% Information and communication 12,2% 8,6% 4,8% 4,3% 3,5% Financial and insurance services 5,5% 5,6% 5,5% 7,3% 8,1% Real estate activities 3,7% 1,9% 3,1% 2,8% 2,7% Professional and support services 7,4% 5,0% 3,7% 5,8% 5,2% Public administration and defence 5,1% 6,3% 6,2% 4,6% 7,2% Education 4,0% 6,1% 7,9% 7,0% 6,7% Health and social work activities 4,2% 3,6% 7,2% 7,1% 6,2% Other services 5,4% 5,9% 5,5% 4,3% 5,3% Note: Values to constant 2010 prices (in Kwachas million) Source: Ministry of Finance, Economic Planning and Development (2017) Note: ⃰ projections
174 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
As indicated in Table 54 below, agriculture continues to dominate the economy, with its contribution to GDP of about 28% in 2016. Although the agriculture sector contracted, other sectors registered growth. Growth was registered in the following sectors: transportation and storage, accommodation and food services, information and communication, financial and insurance services, real estate and professional and support services. The growth of these sectors offset the registered contraction in agriculture.
Table 54 – Sectoral contribution to Malawi GDP, 2014-2018
Sector 2014 2015 2016 2017 ⃰ 2018 ⃰ Agriculture, forestry and fishing 29,9% 28,6% 27,9% 28,1% 27,7% Mining and quarrying 0,9% 0,9% 0,9% 0,9% 0,8% Manufacturing 9,5% 9,6% 9,4% 9,3% 9,4% Electricity, gas and water supply 1,3% 1,3% 1,2% 1,2% 1,2% Construction 2,8% 2,8% 2,8% 2,8% 2,8% Wholesale and retail trade 15,8% 16,0% 15,9% 16,0% 15,8% Transportation and storage 2,6% 2,7% 2,7% 2,7% 2,8% Accommodation and food services 1,9% 1,9% 2,0% 2,0% 1,9% Information and communication 4,1% 4,3% 4,4% 4,3% 4,3% Financial and insurance services 5,0% 5,2% 5,2% 5,5% 5,4% Real estate activities 7,8% 7,7% 7,7% 7,5% 7,3% Professional and support services 0,3% 0,3% 0,3% 0,3% 0,3% Public administration and defence 1,9% 2,0% 2,1% 2,0% 2,1% Education 2,5% 2,6% 2,7% 2,7% 2,8% Health and social work activities 2,6% 2,6% 2,7% 2,8% 2,7% Other services 4,8% 4,9% 5,1% 5,0% 5,0% Note: Values to constant 2010 prices (in Kwachas million) Source: Ministry of Finance, Economic Planning and Development (2017) Note: ⃰ projections
As can be conclude from Table 54, Malawi's economy is focused on three main sectors. These three sectors contribute to more than half of Malawi's GDP production and are responsible for the country’s growth and development of the economy. This structure and contribution of the sectors to the economy of the country has been verified over the years and is expected to continue. The three sectors that most contribution to Malawi GDP were:
• Agriculture, forestry and fishing (28%); • Wholesale and retail trade (16%);
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 175
• Manufacturing (9%).
Malawi’s economy is primarily driven by the agriculture sector. Land is the country´s most valuable resource considering its agro-based economy and highly dependence on rain- fed agriculture. Most land is used for food production, mainly maize, and tobacco, which is the main export commodity.
The sector is not resilient to climatic hazards such as drought and dry spells. Performance of the sector in 2016 was affected by dry spells, which hit most of the countries in Southern Africa, including Malawi. In particular, the crop sector was significantly affected by the drought. The major crops such as maize, tobacco and tea, registered a substantial decline.
In the 2016/2017 growing season, the sector recovered with a growth of 6,8%. Production of major crops has increased, maize by 35,9%, groundnuts by 22,2%, beans by 15,0% and pigeon peas by 19,7%. However, production of tobacco has dropped by 36,7% due to a decline in burley production. Most burley farmers switched to alternative crops because of the price disincentives that prevailed on the tobacco market during the previous growing season.
Activities in wholesale and retail trade are expected to improve. The improvement is mainly attributed to favourable weather conditions, which has resulted in increased disposable income. Being agro-based, the country is expected to see an increase in household incomes in 2017, following good agricultural production. In addition, stability of the Kwacha against the currency of major trading partners, is also expected to contribute to the growth of the sector.
In 2016, the manufacturing sector struggled due to energy challenges, declining aggregate demand and limited availability of raw materials for industrial production. The agricultural sector supplies most of the raw materials for industrial production. However, production of agricultural commodities decreased due to the poor weather conditions. As a result, activities in the manufacturing sector grew modestly. Nevertheless, due to favourable weather conditions in 2017, the manufacturing sector is projected to grow. The growth will mainly be due to increase in aggregate demand, availability of raw materials and stability and availability of foreign exchange. The expected stability in the macroeconomic environment and improvement in energy will promote activity in the sector.
176 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
The study area follows the national trend regarding agricultural activities. The majority of the rural populations relies on subsistence agriculture, with small holder farms based on rainfed maize production and tobacco. Other important planted crops are groundnuts and vegetables and other subsistence and consumption products within households (like Irish and sweet potatoes, green beans, soybeans, tomatoes, pumpkins, sugarcane, among others) (Figure 156 and Figure 157).
Source: NEMUS (2017) Figure 156 – Examples of area agricultural in the project area, in Kafumphe (SC Mkukula, Dowa District)
Source: NEMUS (2017) Figure 157 – Examples of area agricultural in the project area, in Mwansango (TA Chiwere, Dowa District)
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 177
Fishing and livestock grazing are common activities in the study area. They are important activities that complement the agricultural activity. Fishing is mainly important along the Lake in the Salima District, while grazing livestock activity is practiced a bit throughout the project area and surroundings villages. (Figure 158 and Figure 159).
Source: NEMUS (2017) Figure 158 – Example of area fishing in the project area, in TA Kaluunda (Salima District)
Also playing a very important role in rural economy are wood products and a charcoal production and the sale of several products mainly agricultural products.
Source: NEMUS (2017)
Figure 159 – Example of wood products in the project area, in TA Karonga (Salima District)
178 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
Source: NEMUS (2017)
Figure 160 – Example of wood products in the project area, in TA Karonga (Salima District)
Source: NEMUS (2017)
Figure 161 – Example of sale agricultural products in the project area, in TA Maganga (Salima District)
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 179
Source: NEMUS (2017)
Figure 162 – Example of sale the buck products in the project area, in TA Chiwere (Dowa District)
8.7. Employment
Malawi’s economy presents high levels of unemployment, particularly among the youth.
Table shows the unemployment rate by districts in the project area. The proportion of unemployed among females is higher than males and this is more pronounced in Dowa district. This is the trend that is seen in all the districts and in the country as a whole (Figure 163).
180 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
Source: NSO (2018)
Figure 163 – Unemployment rate by districts, in 2008
Informal employees are workers whose work is not regulated by labour laws and are without provisions for social security benefits, such as compensation services, pension scheme and sick leave. One of the driving forced for the growth in informal employment is the low capacity of the economy to create jobs and the lack of a clear framework of linking economic growth and job creation. It has become apparent that economic growth may not necessarily translate into an increase in the number of jobs being created.
The Figure 164 presents the percentage distribution of the employed population by occupation. The 2013 MLFS survey indicate that highest percentage of employed persons was involved in agricultural, forestry and fishery occupations (45%). There were also notable percentage of employed persons engaged in elementary occupations (22%) and in service and sales (19%).
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 181
Source: NSO (2014) - MLFS 2013
Figure 164 – Percentage distribution of the employment persons by occupation
Table 55 shows that 64% of the employed population works in agriculture, forestry and fishing. Nearly 20% of the employed labour force works in the wholesale and retail trade and repair of motor vehicles industry. Comparatively, more females than males are engaged in agriculture, forestry and fishing and wholesale and retail trade and repair of motor vehicles industries
At region level there is the same pattern. Agriculture, forestry and fishing sector and wholesale and retail trade and repair of motor vehicles are the industry that employed more persons.
Table 55 – Employment by sector, sex and region, in 2013
Sex Region Indicator Total Male Female Northern Central Southern Agriculture, forestry and fishing 64,1% 58,5% 69,9% 69,6% 67,7% 58,3% Mining and quarrying 0,3% 0,2% 0,3% 0,2% 0,2% 0,4% Manufacturing 4,1% 4,5% 3,6% 3,8% 3,6% 4,7% Electricity, gas 0,2% 0,3% 0% 0,2% 0,2% 0,2% Water supply, waste 0,2% 0,4% 0,1% 0% 0,3% 0,1% management Construction 2,6% 4,2% 1% 2,9% 2,3% 2,9%
182 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
Sex Region Indicator Total Male Female Northern Central Southern Wholesale and retail trade and 16,2% 15,1% 17,4% 15,3% 14,8% 18,3% repair of motor vehicles Transport, storage and 2% 3,8% 0,2% 1,4% 1,7% 2,6% communication Accommodation and food 0,7% 0,7% 0,8% 0,4% 0,7% 0,8% services activities Professional, scientific and 0,2% 0,3% 0,1% 0,1% 0,1% 0,3% technical Administrative and support 0,7% 0,8% 0,5% 0,2% 0,5% 1% services Public administration 2% 3,3% 0,7% 1,8% 1,7% 2,5% Education 2,2% 2,8% 1,6% 1,9% 2,4% 2,1% Human health and social work 1,4% 1,6% 1,1% 0,8% 0,9% 2,1% Other service 1,8% 2,6% 1% 1% 1,5% 2,3% Activities of households as 1,3% 0,8% 1,7% 0,3% 1,6% 1,3% employers Source: NSO (2018)
The International Labour Organization (ILO) defines informal employment as a job where the relationship between the employer and employee is not subject to national labour economy, income taxation or any social protection or employment benefits. Workers in informal employment include: own account workers and employers employed in their own enterprises; members of informal producer’s cooperatives and contributing family works irrespective of whether they work for formal or informal enterprises. Paid employees are considered in informal employment if they are without any benefit: no paid leave; no contribution to social security; no payment for leave days not taken; no paid sick leave; no medical benefit and no tax deduction from salary.
The 2013 MLFS data indicate that employed persons in Malawi are predominantly engaged in informal employment. Overall, 89% of working persons are in informal employment setups. Women are more likely to be in informal employment than men. There are marked differences in involvement in informal employment between rural areas, then percentage of employed persons in informal employment is 91% compared to 69% in urban areas. Men and women in urban areas are less likely to be engaged in informal employment than their counterparts in the rural areas. The informal employment rate in the Southern region is lower than for Central and Northern regions.
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 183
8.7.1. Land Ownership
There are various legal instruments that govern land administration and Management in Malawi. According to the Report of the Law Commission on the Review of the Land Related Laws (9th April, 2010), ownership of the land can be of three types:
• Public: land occupied and privately owned by the Government and dedicated to a specified national use or made available for private use at the discretion of the Government; • Private: land which is owned, held or occupied under a freehold title, or a leasehold title or a customary estate and is registered as such under the Registered Land Act of 1967; • Customary: land used for the benefit of the community as a whole and includes unallocated land within the boundaries of a Traditional Land Management Area.
The land tenure can be as follows:
• Freehold (application to private land): Private sector manages the rights, use and alienation of lands; • Leasehold (application to public, private and customary land): Lease conditions vary by the use – 21 years to agricultural land and 22 to 99 years to development properties and infrastructures. Public and customary lands are managed by the government or TA leader. When the leasehold time expires, the land reverts to the ownership; • Customary: Land held as a whole by a group or individual person or family. If the land has been held individually, it is a presumption that the use is exclusive and perpetual and that the land can be leased.
The information about land ownership, land tenure and use of land is scarce in the Lilongwe District, Dowa District and Salima District, where the study area is located.
The main characteristics in terms of land use, settlement and geographical distribution of population in the study area are dispersed settlements with low population density and interspersed with agricultural land.
184 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
9. References
ACR (2016). African Chiroptera Report 2016. AfricanBats, Pretoria. 7380 pp.
AFRICAN ECONOMIC OUTLOOK. Malawi 2017.
AURECON (2011). Borehole water monitoring census report: field review of 35 water monitoring boreholes. Final report March 2011. 28 pp.
BAKER, B.H., MOHR P.A., WILLIAMS, L.A.J. (1972). “Geology of the Eastern Rift System of Africa”. The Geol. Soc. of America. Special Paper, 136, 67 pp.
BAUMANN, G. (2005). Photographic Guide to Wildflowers of Malawi. Wildlife and Environmental Society of Malawi. 259 pp.
BENSON, T. (2008). Malawi: An Atlas of Social Statistics. National Statistical Office/Government of Malawi. August 2008.
BGS (2004). Groundwater quality: Malawi. WaterAid – British Geological Surveys. 6 pp.
CHAPOLA, L.S. (2001). “Seismology in Malawi”. Bull. Int. Inst. Seismol. Earthq. Eng., 35, 57-69.
CHILTON, P.J. & SMITH-CARINGTON, A.K. (1984). “Characteristics of the weathered basement aquifer in Malawi in relation to rural water supplies”. Challenges in African Hydrology and Water Resources (Proceedings of the Harare Symposium, July 1984). IAHS, 144, 57 – 72.
CONSTITUTION OF MALAWI (2010). Report of the Law Commission on the Review of the Land _Related Laws. March 2010.
DAVIS-REDDY, C. L., & VINCENT, K. (2017). Climate Risk and Vulnerability: A Handbook for Southern Africa (2nd Edition). CSIR, Pretoria, South Africa. Retrieved from https://www.csir.co.za/sites/default/files/Documents/SADC%20Handbook_Second% 20Edition_full%20report.pdf
DEAT. (2006). South Africa Environment Outlook. A report on the state of the environment. Executive summary and key findings. Department of Environmental Affairs and Tourism, Pretoria. Retrieved January 19, 2018, from http://soer.deat.gov.za/dm_documents/Executive_summary_5hHwD.pdf
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 185
DoCCMS. (n.d.). Malawi Climate. (Ministry Natural Resources, Energy and Environment, Editor, & Dep. of Climate Change and Meteorological Services, Producer) Retrieved November 14, 2017, from http://www.metmalawi.com/climate/climate.php
EAD (2006). National Biodiversity Strategy and Action Plan. Environmental Affairs Department Ministry of Energy, Mines and Natural Resources. Lilongwe, Malawi. 118 pp.
EAD (2014). Malawi Fifth Country Report to The Convention On Biological Diversity (CBD). Environmental Affairs Department Ministry of Energy, Mines and Natural Resources. Lilongwe, Malawi. 46 pp.
FAO (1985): Water Quality for Agriculture [January 2018]. Available at: http://www.fao.org/docrep/003/T0234E/T0234E00.htm.
FAO (1996). Socio-economic and production system study of wetland use. Main text and working papers 1 and 2.
FISHER, M.; SHIVELY, G. (2006). Agricultural Subsidies and Forest Pressure in Malawi’s Miombo Woodlands. 3rd World Congress of Environmental and Resource Economists. Kyoto, Japan.
FOOD AND AGRICULTURE ORGANIZATION OF THE UNITED NATIONAL. Review of food and agricultural policies in Malawi: Country Report 2014. May 2015.
FRENKEN, K.; MHARAPARA, I. (2002). Wetland Development and Management in SADC Countries. Proceedings of a sub-regional workshop, 19-23 November 2001, Harare, Zimbabwe. Food and Agriculture Organization of the United Nations. Harare, Zimbabwe. 190 pp.
FULLERTON, D. G., SEMPLE, S., KALAMBO, F., SUSENO, A., MALAMBA, R., HENDERSON, G., . . . GORDON, B. (August de 2009). Biomass fuel use and indoor air pollution in homes in Malawi. Occupational & Environmental Medicine, 66, pp. 777– 783.
GENNER, M.J.; CONNELL, E.; SHECHONGE, A.; Smith, A.; SWANSTROM, J.; MZIGHANI, S.; MWIJAGE, A.; NGATUNGA, B.P.; TURNER, G.F. (2013). Nile tilapia invades the Lake Malawi catchment. African Journal of Aquatic Science, 38: 85-90 pp.
GLAD, P. (2010). Meteorological and hydrological conditions leading to severe regional drought in Malawi. Master Thesis in Geosciences, University of Oslo.
186 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
GORMAN, L., MORANG, A. & LARSON, R. (1998). “Monitoring the coastal environment; Part IV: Mapping, shoreline changes, and bathymetric analysis”. J. Coastal Res. 14: 61-92.
GOVERNMENT OF MALAWI (2015). National Biodiversity Strategy and Action Plan II (2015-2025). United Nations Environment Program.
GOVERNMENT OF MALAWI http://www.malawi.gov.mw/ (November 2017)
HUGHES, R.H.; HUGHES, J.S. (1992). A Directory of African Wetlands. IUCN, Gland, Switzerland and Cambridge, UK/UNEP, Nairobi, Kenya/WCMC, Cambridge, UK. 820 pp.
HUSCHKE, R. (1959). Glossary of meteorology. Boston: American Meteorological Society.
IAMAT. (2016). General Health Risks: Air Pollution. Retrieved from https://www.iamat.org/country/malawi/risk/air-pollution
INTERNATIONAL MONETARY FUND (2017). Malawi: Economic Development Document. July 2017.
ISRIC. (1997). FAO-UNESCO Soil Map of the World - Revised Legend with corrections and updates. Technical Paper 20, International Soil Reference and Information Centre, Wageningen. Retrieved from http://www.fao.org/fileadmin/user_upload/soils/docs/isricu_i9264_001.pdf
IUCN (2018): IUCN Red List of Threatened Species. Version 2017.3 [January 2018]. Available at: www.iucnredlist.org.
JICA (2014). Project for National Water Resources Master Plan in the Republic of Malawi – Volume II: Main Report. Japan International Cooperation Agency. December 2014.
KALEKE, T.S. (2015). Evaluating community participation in the effective management of protected areas: a case study of Lake Malawi National Park. Master Thesis. Stellenbosch University. 107 pp.
KEYANTASH, J., & DRACUP, J. (2002). The Quantification of Drought: An Evaluation of Drought Indices. Bulletin of the American Meteorological Society, 1167-1180.
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 187
KHATO CIVILS & SOUTH ZAMBEZI JV (August 2017). Concept Design Report: Lake Malawi Water Supply Project for Lilongwe City (Project Rhino). Procurement No.: LM/LWB/2016. August.
KINDT, R.; VAN BREUGEL, P.; LILLESØ, J. B.; BINGHAM, M.; DEMISSEW, S.; DUDLEY, C.; FRIIS, I.; GACHATHI, F.; KALEMA, J.; MBAGO, F.; MINANI, V.; MOSHI, H.; MULUMBA, J.; NAMAGANDA, M.; NDANGALASI, H.; RUFFO, C.; JAMNADASS, R. & GRAUDAL, L. O. V. (2011). 63 ed. Forest & Landscape, University of Copenhagen. 176 p. (Forest & Landscape Working Paper; 63).
LISTER, L.A. (1965). “Chapter 2 - Erosion surfaces in Malawi” in Records of the Geological Survey of Malawi. Vol. VII. Malawi Ministry of Economic Affairs.
LOWORE, J. (2006). Miombo woodlands and rural livelihoods in Malawi. Center for International Forestry Research (CIFOR), Bogor, Indonesia. 18 pp.
MACDONALD, I.A.W., REASER, J.K.; BRIGHT, C.; NEVILLE, L.E.; HOWARD, G.W.; MURPHY, S.J. & PRESTON, G. (eds.). (2003). Invasive alien species in southern Africa: national reports & directory of resources. Global Invasive Species Programme, Cape Town, South Africa. 125 pp.
MALAWI GOVERNMENT (1995). Malawi: Country Report to the FAO International Technical Conference on Plant Genetic Resource. FAO.
MALAWI GOVERNMENT (2017). Annual Economic Report 2017. Ministry of Finance, Economic Planning and Development.
MALAWI GOVERNMENT (2017). National Agriculture Policy 2016. Ministry of Agriculture, Irrigation and Water Development. September 2016.
MALAWI GOVERNMENT (s.d.). Malawi: Country Report on the State of Plant Genetic Resources for Food and Agriculture. FAO. 44 pp.
MALAWI STANDARDS BOARD (2005). Malawi Standard: Industrial Emissions, Emissions Limits for Stationary and Mobile Sources-Specification, MS737:2005. Blantyre.
MALAWI STANDARDS BOARD (2013). MS 214:2013 – Drinking water Specification (second edition). Malawi Standards Board.
MANDEVILLE, A. N., & BATCHELOR, C. H. (1990). Estimation of actual evapotranspiration in Malawi. Institute of Hydrology, Report nº10, 81pp.
188 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
MAPOMA, H., & XIE, X. (2013). State of Air Quality in Malawi. Journal of Environmental Protection, 4(11), pp. 1258-1264. doi:10.4236/jep.2013.411146
MAUAMBETA, D.; CHITEDZE, D.; MUMBA, R.; GAMA, S. (2010). Status of Forests and Tree Management in Malawi. A Position Paper Prepared for the Coordination Union for Rehabilitation of the Environment (CURE). 51 pp.
MICHAEL PAVLAKIS AND ASSOCIATES (2017). Preliminary report - Geotechnical investigation for major river and railway crossings present along the proposed new bulk water pipeline (Project RHINO) – from Kanengo to Malawi Lake. 30 pp.
MORRIS (2009). Wildlife and Landscapes in Malawi. Selected Essays on Natural History. Trafford Publishing. 325 pp.
MSONDA, K.W.M.; MASAMBA, W.R.L.; FABIANO E. (2007). “A study of fluoride groundwater occurrence in Nathenje, Lilongwe, Malawi”. Physics and Chemistry of the Earth, 32, 1178–1184.
MUNTHALI, G. K., SAKA, J., KAMDONYO, D. R., KASULO, V., NKHOKWE, J. L., & KAINJA, S. (2003). Drought Case Study for Malawi. Ministry of Environment and Climate Change Management: Department of Meteorological Services.
NATIONAL STATISTICAL OFFICE http://www.nsomalawi.mw/ (December 2017)
NATIONAL STATISTICAL OFFICE. Malawi Demographic and Health Survey 2015- 16. February 2017.
NATIONAL STATISTICAL OFFICE. Malawi Labour Force Survey 2013. April 2014.
PEGADO, A. (2000). The Distribution of Cloud Cover Over Lake Malawi/Niassa/Nyasa. Thesis submitted to the Faculty of Graduate Studies in Partial Fulfillment of the Degree of Master of Arts, University of Manitoba, Department of Geography, Winnipeg.
SAEMUNDSSON, K. (2010). “East African Rift System – An Overview”. Short Course V on Exploration for Geothermal Resources, organized by UNU-GTP, GDC and KenGen, at Lake Bogoria and Lake Naivasha, Kenya, Oct. 29 – Nov. 19, 2010.
SAFEGE Consulting Engineers (2002). Engineering Studies for Lilongwe Water Board-New Water Sources Report.
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 189
SHACKLETON, S.; COCKS, M.; DOLD, T.; KASCHULA, S.; MBATA, K.; MICKELS- KOKWE, G.; VON MALTITZ, G. (2010). Non-wood Forest Products: Description, Use and Management In Gumbo, E.C.D.J. (ed.) The Dry Forests and Woodlands of Africa: managing for products and services. London: Earthscan 93-129.
TADROSS, M., SUAREZ, P., LOTSCH, A., HACHIGONTA, S., MDOKA, M., UNGA- NAI, L., . . . MUCHINDA, M. (2007). Changes in growing-season rainfall characteristics and downscaled scenarios of change over southern Africa: implications for growing maize. IPCC regional Expert Meeting on Regional Impacts, Adaptation, Vulnerability, and Mitigation, Nadi, Fiji.
THATCHER, E.C. & WALTER, M.J. (1968). The geology of the South Lilongwe plain and Dzalanyama range. Geological Survey Department. Malawi Ministry of Natural Resources. 77 pp.
UN. (2015). Millennium Development Goals Indicators: Carbon Dioxide Emissions (CO2), Thousand Metric Tons of Carbon Dioxide (CDIAC). United Nations Statistics Division. Retrieved January 19, 2018, from http://mdgs.un.org/unsd/mdg/SeriesDetail.aspx?srid=749
UNAIDS (2017). Country Profiles: Malawi. http://www.unaidsrstesa.org/regionalcountry-profileshome/country-profiles/malawi
UN-DTCV (1986). National Water Resources Master Plan. Report and Appendices. United Nations Department of Technical Cooperation for Development, November 1986.
UNITED NATIONS ECONOMIC COMMISSION FOR AFRICA (ECA). Malawi: Country Profile 2016. March 2017.
UNIVERSITY OF CAPE TOWN. (n.d.). Climate Information Portal - CIP. Retrieved November 15, 2017, from Climate System Analysis Group: http://cip.csag.uct.ac.za/webclient2/datasets/africa-merged-cmip5/#nodes/cmip5- anomalies?folder_id=33&extent=101514
USAID https://www.usaid.gov/malawi/fact-sheets/malawi-el-ni%C3%B1o-mitigation- fact-sheet
USGS (2006). M7.0 Mozambique Earthquake of 22 February 2006. United States Geological Survey. ftp://hazards.cr.usgs.gov
VECEA: Potential natural vegetation of eastern Africa [January 2018]. Available at: http://vegetationmap4africa.org/
190 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
VENEMA, J. (1990). Land Resources Evaluation Project – Malawi: Methods of Description, Classification and Mapping of the Physiography and Soils of Malawi (Field Document No. 3). Malawi Government Ministry of Agriculture/Land Husbandry Branch. Lilongwe: United Nations Development Programme, Food and Agriculture Organization of the United Nations. Retrieved from http://library.wur.nl/isric/fulltext/isricu_i17213_001.pdf
VENEMA, J., & LORKEERS, A. (1991). Land Resources Evaluation Project – Malawi: Land Resources Appraisal of Lilongwe Agricultural Development Division (Field Document No. 24). Malawi Government Ministry of Agriculture/Land Husbandry Branch; United Nations Development Programme; Food and Agriculture Organization of the United Nations. Retrieved from http://resources.bgs.ac.uk/sadcreports/malawi1991faolilongwelanduse.pdf
VINCENT, K., DOUGILL, A. J., MKWAMBISI, D. D., CULL, T., STRINGER, L. C., & CHANIKA, D. (2014). Analysis of Existing Weather and Climate Information for Malawi. University of Leeds, School of Earth and Environment. South Africa: Kulima Integrated Development Solutions (Pty) Ltd. Retrieved November 15, 2017, from http://www.futureclimateafrica.org/wp-content/uploads/2015/02/Malawi-existing- Analysis-of-existing-weather-and-climate-information-for-Malawi-final-with- disclaimer.pdf
WALTER, M.J. (1972). The geology of the Salima – Mvera Mission Area. Geological Survey Department. Malawi Ministry of Agriculture and Natural Resources. 29 pp.
WHITE, F. (1983). The vegetation of Africa: a descriptive memoir to accompany the Unesco/AETFAT/UNSO vegetation map of Africa. Natural Resources Research: 20. Paris: United Nations Educational, Scientific and Cultural Organization. 356 pp.
WHO (2017). Guidelines for drinking-water quality: fourth edition incorporating the firstaddendum. World Health Organization.
WHO. (2005). WHO Air quality guidelines for particulate matter, ozone, nitrogen dioxide and sulfur dioxide - Global update 2005 - Summary of risk assessment. Retrieved from https://www.iamat.org/assets/files/WHO_SDE_PHE_OEH_06.02_eng%281%29.pdf
WHO. (2016). Media centre - Fact sheets - Ambient (outdoor) air quality and health. Retrieved from http://www.who.int/mediacentre/factsheets/fs313/en/
WORLD BANK (2017). Malawi Economic Monitor: Land for Inclusive Development. World Bank – Office Malawi. November 2017.
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 191
WORLD BANK (1992). Malawi Economic Report on Environmental Policy (Volume I). Main Report (Report No. 9888-MAI), World Bank – Country Operations Division, Southern Africa Department.
WORLD BANK (2009). Malawi: Economic Vulnerability and Disaster Risk Assessment. Draft Final Report (Volume 1: Main report).
192 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
Annex 1 – ESIA Team Composition
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 193
Blank page
194 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix
ESIA Team Composition
The ESIA was conducted by a team of specialists with vast experience in environmental assessment and management. The team was led by Pedro Bettencourt (Project Manager), with the support of Project Coordinator Nuno Silva.
Name of Specialist Qualifications
• ISCED 7/ MSc in Geology; ISCED 7/ Post-graduation in Pedro Bettencourt Geologic Oceanography and Marine Sedimentology
Nuno Silva • ISCED 7/ MSc in Environmental Engineering
Gisela Sousa • ISCED 7/ MSc in Biology
• ISCED 8/ PhD in Environmental Engineering; ISCED 7/ Ângela Canas MSc. in Science in Engineering and Management of Technology; ISCED 7/ MSc in Environmental Engineering
• ISCED 8/ PhD in Geosciences; ISCED 7/ MSc Post- César Jesus graduation in Sciences of Coastal Areas; ISCED 7/ MSc in Geology and Biology
• ISCED 7/ MSc in Environmental Engineering; ISCED 7/ Maria Grade MSc in Geographic Information Systems
Cláudia Fulgêncio • ISCED 7/ MSc in Environmental Engineering
• ISCED 7/ BSc Social Sciences, Post graduate in Housing Mtafu Manda & Urban Development; Post graduate in Population and sustainable Development; MSc Development Planning
• ISCED 7/ MSc in Environmental Economics and Diogo Maia Management; BSc. in Economics
Carina Gonçalves • ISCED 7/ MSc in Economics; MSc International Economy
• ISCED 8/ PhD candidate; ISCED 7/ MA in Theoretical Menno Welling Archaeology; ISCED 7/ MA in Cultural Anthropology
• ISCED 7/ MSc Post-graduation in Environmental Studies Sofia Gomes and Land Management; ISCED 7/ MSc in Archaeology
• ISCED 7/ MSc Landscape Architecture; Post-graduation Elisabete Teixeira in Advanced Studies in Land, Environment and Sustainable Development
João Lopes • ISCED 7/ MSc in Environmental Engineering
Joana Santos • ISCED 7/ MSc in Environmental Engineering
Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix 195
Blank page
196 Rpt_t17049/02 ESIA for Lake Malawi Water Supply Project for Lilongwe City: Appendix