Writing3 AMishra ASI UK DFID Nigeria Writing Sample 2014

Briefing Note Scoping Study for Resilient Northern Nigeria (Oct 2014)
STUDY OF A RESILIENT NORTHERN NIGERIA
FOR DFID NIGERIA
a. Context
Northern Nigeria faces a number of short and long term risks that threaten the regions peace and stability.
These risks include, but are not limited to, an inadequate power supply, the effects of climate change,
terrorism and changing patterns of development and growth. The risks are interrelated and compoundable:
the net impact of climate change on employment in Northern Nigeria will be more significant if agricultural
productivity declines alongside continued deindustrialisation, in which case a shrinking economic base will
have to support more dependants. Furthermore, decreasing economic prosperity is likely to fuel further
political instability and by extension a greater likelihood of terrorism.
Northern Nigeria is of pivotal importance given its size (approx. 84 million) compared to the rest of Nigeria
(53%) and West Africa (29%). The aforementioned risks will most likely increase poverty which at 77% of
the population in the North is already greater than the average of 64% for the rest of Nigeria. Instability in
Northern Nigeria could create further instability in the wider region by migratory flows, conflict and
alterations in material resource flows.
The overall objective for NIAF’s work on a Resilient Northern Nigeria is to identify a set of coherent policy
interventions that can be used to mitigate damaging or transformational future trends like changing
weather patterns and population growth. In particular the final outcome of the study is assess how DFID
can best support its Northern Nigerian partners facing complex regional climate vulnerabilities through
providing concrete recommendations for regional adaptive capacity and resilience strengthening-
measures.
Associated NIAF projects:
Project Code Project Name Description
UZ0009 Future Proofing Lagos Future proofing Lagos is an ongoing piece of
work examining the risks that Lagos faces
and potential mitigation strategies that
could be implemented.
Given the very different political and
economic situation the associated project is
only partially relevant.
b. Client request
DFID Nigeria requested NIAF to conduct a study on climatic change and its impact on Northern Nigeria.
This rapid assessment is the second of two study project stages. The main study phase aims to
analyse first and second order climate impacts in Northern Nigeria (NN). The report undertakes case
study analysis for rapid review of Northern Nigeria's existing and future potential for adapting
resilience strategy including its potential for climate proofing infrastructure (water, power, transport &
urban) development. Furthermore the study provides recommendations for resilience planning
frameworks through regional planning strategic frameworks and related regional institutional
strengthening and reforms needed to enable resilience planning. Finally the study explores the
potential for Northern Nigeria's states to adapt from existing climate vulnerability, to more resilient-
based regional development approaches, through medium-term climate proofing infrastructure
requirements and related requirements for regional resilience investment.

Aashish Mishra, Lead Consultant, Resilient Northern Nigeria Study, aash.mishra@nyu.edu Page 2 of 17
OBJECTIVES
c. Project objective(s)
For NIAF to enable a more Resilient Northern Nigeria through providing recommendations to support
Northern Nigeria's states existing climate impact vulnerabilities through implementing adaptive capacity
measures for resilience planning, institutional strengthening, potential for climate proofing infrastructure
and required regional resilience investments.
The study components and associated outputs include:
1. Developing climate scenario profiles and impact projections for Northern Nigeria and states rapidly
assessed in case study analysis;
2. Assessing Northern Nigeria critical infrastructure sectors of water, power, transport and urban
development, in terms of regional climate risks and climate proofing, with detailed analysis in case
studies;
3. Modelling and mapping of climate vulnerability for Northern Nigeria regional population and vulnerable
sectors, with detailed analysis in Case Studies;
4. Undertaking field based survey and data collection for three Case Studies in Northern Nigeria;
5. Providing recommendations for regional climate adaptation measures including regional planning,
institutional strengthening and resilience investments;
6. Presenting final report for submission to DFID.
d. Means of verification
Objectively Verifiable Indicator Date
Climate Impact and Vulnerability Maps for Northern Nigeria States
July 014
Preliminary Findings to NIAF
October 2014
Final Report Submitted to DFID
December 2014

1 RESILIENT NORTHERN NIGERIA (RNN) STUDY BRIEF
Resilient Northern Nigeria (RNN) Study Framework is the analytical construct for
assessing the Northern Nigerian (NN) States' potential vulnerabilities from and resilience
to adverse impacts from climate change scenarios, as determined by its 'adaptive
capacity' to protect diverse population and sectors from vulnerabilities to climate
impacts. Climate vulnerability and resilience are diametrically opposed and inter-related
ends of the climate impact continuum, and provide appropriate conceptual basis to
utilise inverse logic frameworks such as SWOT (Strength, Weakness, Opportunity, Threat)
to determine Northern Nigerian States' most significant climate threats to population and
sector vulnerability. In turn such regional vulnerability risks provide logical counter-
response to overcome resilience system weaknesses in regional planning, institutions
and investments, which should typically adapt to emerging risks, faced by vulnerable
population and core sectors in responsive regional systems.
The study framework utilises "adaptive capacity assessment" as overarching case study
survey method to rapidly assess select NN States' strength of existing 'regional resilience
systems' for adaptation and resilience planning, institutions and investment practices.
RNN framework measures Northern Nigerian States' "adaptive capacity" vis-à-vis
responsiveness of prevailing resilience systems to dampen climate vulnerability of at-risk
population groups and protect critical infrastructure sector investments. The RNN model
supported through SWOT-level assessment captures of NN regions' 'baseline resilience
scenario' and thus its "adaptive capacity" to dampen vulnerability. This 'baseline
scenario' of adaptive capacity provides comparative basis to generate further hypothesis
regarding potential array of strategic interventions to strengthen, for e.g., planning for
agriculture production.
The RNN study design establishes regional climate profiles and projection models as
prima-facie identification of disparate NN States' vulnerable population (agglomerations
of urban ands rural areas) and core sectors (water, power, transport, regional and urban
infrastructure) at-risk. Case study method is then utilised to investigate regional
vulnerability and "adaptive capacity" vis-à-vis rural and urban settlements and built-up
assets, water and power networks and transportation linkages; and assessed through
integrated case study analysis regarding on-ground workability for potential medium-term
NN resilience development interventions.
Finally, the expected outcomes of the RNN study include better supporting DFID and NN
States in SWOT assessment for regional climate proofing infrastructure development and
investments; supporting regional development infrastructure strategy through analysis of
bankable infrastructure project design, sector integration, financing options; and finally,
informing DFID’s medium-term NN aid strategy through study recommendations for
unlocking regional climate proofing infrastructure strategies, and furthermore highlight
tremendous scope for NN's socio-economic diversification through, for e.g., resilience
systems responding to shifts in urban-rural productivity by more strategic regional
development investment.

RNN Study Outputs
1. RNN Study Analytical Framework
1.1.Field based assessment in Northern Nigeria (NN) States analyses strength of NN
States' "Regional Resilience Systems" and thereby it's "Adaptive Capacity" for
dampening climate vulnerability of at-risk population groups and critical
infrastructure sector investments.
2. NN Climate Scenarios
2.1.Climate Impact Profile
2.1.1. Environmental Triggers
2.1.2. Climate Variability
2.1.3. Ecological Changes
2.1.4. Socio-economic Factors
2.2.Climate Impact Projections
2.2.1. Historic Events
2.2.2. Baseline Conditions
2.2.3. Projected Effects
3. NN Climate Vulnerability
3.1.Typology of Population At-Risk
3.1.1. Emerging City-Regions
3.1.1.1. Kano Metropolitan Area
3.1.1.2. Kaduna City-Region
3.1.1.3. Sokoto City-Region
3.1.2. State Capital Networks
3.1.2.1. Rural-urban scale economies
3.1.2.2. Rural industries in Capital Regions
3.1.2.3. Inter-State Capital Corridors
3.1.3. Regional Growth Corridors
3.1.3.1. Trade-Markets-Industrial Networks
3.1.3.2. Railway, Highway and Road Networks
3.1.3.3. Regional & International Crossing Boundaries
3.1.3.4. Pipeline-Powerline Networks to towns and cities
3.1.4. Rural Agglomerations
3.1.4.1. Shared natural resources or geography clusters
3.1.4.2. Historic or current markets and trading clusters
3.1.4.3. Ethnic, nomadic and local clusters
3.2.Sector Infrastructure At-risk

3.2.1. Climate Proofing Infrastructure
3.2.1.1. River/Lake/Reservoir Barriers
3.2.1.2. Emergency Services
3.2.1.3. Dam & Reservoir
3.2.1.4. Storm Water Drainage
3.2.1.5. Solid Waste Mgt.
3.2.1.6. Low GHG Regional Production
3.2.1.7. At-Risk Settlements
3.2.2. Water and Energy Resources
3.2.2.1. State Water and Power Provision
3.2.2.2. Informal Water and Power Markets
3.2.2.3. Agriculture-Water-Energy Linkages
3.2.2.4. Rainwater, Wastewater and Ground-water Harvesting
3.2.2.5. Renewable Energy
3.2.2.6. Agricultural/Industrial Consumption
3.2.3. Transportation Networks
3.2.3.1. National Highways
3.2.3.2. Rural Road Networks
3.2.3.3. Intra- Regional and
3.2.3.4. National Railways
3.2.3.5. International and Domestic Borders
3.2.3.6. Regional airports and
3.2.4. Regional & Urban Development
3.2.4.1. Human Settlement Infrastructure
3.2.4.2. Storm Drainage and Solid Waste Mgt.
3.2.4.3. Farming & Pastoral Activities
3.2.4.4. Rural & Urban Agriculture
3.2.4.5. Land-Water-Energy Linkages
3.2.4.6. Essential Trunk Infrastructure
4. Climate Adaptive Capacity Assessment for Regional Resilience Systems
5. NN Climate Resilience Systems
5.1.Resilience Planning
5.1.1. Land use and settlement planning
5.1.2. Resilient settlements & built-up structures
5.1.3. Water and energy resource management

5.1.4. Rural and urban productivity improvement
5.2.Resilience Institutions
5.2.1. Climate impact mapping & early warning systems
5.2.2. Regional emissions & environmental regulation
5.2.3. Regional climate risk pooling & insurance market
5.3.Resilience Investment
5.3.1. Climate risk adaptation and resilience investment loans
5.3.2. Resilient infrastructure bankability and private-sector financing
5.3.3. Rural & urban resilience investment credit facilities and co-financing
5.3.4.Intergovernmental and performance-based infrastructure subsidies

2 TYPOLOGY OF RISK
2.1 WHAT IS A TYPOLOGY?
A typology is the systematic grouping of entities or units of interest based on similarity and
potential pattern, and is commonly utlilised to build qualitative and quantitative relationships
among different variables in both the physical and social sciences.i A typology provides a casual
framework to organize data, detect patterns, aid decisions, prioritise and allocate resources, and
plan strategies and processes. An indicator-based typology for social science research, including
climate change assessments, generates grouping and framework to rank and categorise:
• People (households, communities, user groups);
• Places (cities, LGAs, districts, regions, countries);
• Relative level of physical vulnerability to climate change
There are several approaches to develop a typology including conceptual, empirical and
operational; and the later 'hybrid' approach integrates assessment of communities through
regional vulnerability profiles to better understand casual linkages of both climate risk and
resilience potential of communities. This study integrates elements of such 'Vulnerability Cube'
typologies to understanding how communities compare in vulnerability characteristics to one
another.ii The typology creates regional vulnerability profiles for distinct groupings of
communities' adaptive capacity requirements to better understand vulnerability of the
community profile group, provide basis for sub-regional comparison and assess the adaptation
potential of similar community groups.iii
2.1.1 CHARACTERISTICS OF A TYPOLOGY FOR CLIMATE RISK AND VULNERABILITY
Figure 2.1.1 illustrates the key characteristics of a typology of climate risk and vulnerability
include necessitate clarifying climate risk and vulnerability analytical concepts. The concept of
Hazard refers to physical manifestations of climatic variability or change, such as droughts,
floods, storms, and episodes of heavy rainfall. It also captures long-term changes or future trends
in the mean values of climatic variables. The empirical valuation of Hazard is based on its Hazard
Risk, which is defined as likelihood or frequency of occurrence of a hazard. In addition,
Vulnerability, comprised of both Biophysical and Socio-economic factors, is broadly defined as
the degree to which a system is susceptible to, or unable to cope with, adverse effects of climate
change, including climate variability and extremes.iv The concept of Exposure is defined the
nature and degree to which a system is exposed to significant climatic variations, such as
changes on population units (cities, farms) or sectors (urban, agriculture). Sensitivity is a key
component of Vulnerability, and in the broadest scope defined as the degree to which a system is
affected, either adversely or beneficially, by climate-related stimuli. Sensitivity is also referred to
as Social Vulnerability. Finally, the concept of Adaptive Capacity is captured in this typology as
resilience enabling factors of the 'exposed' system to adjust to climate change, including climate
variability and extremes; and to moderate potential damages, take advantage of opportunities, or
cope with the consequences.v

Figure 2.1.1 Characteristics of a Typology for Climate Risk and Vulnerability
2.1.1.1 WHY IS A CLIMATE RISK AND VULNERABILITY TYPOLOGY IMPORTANT FOR NORTHERN NIGERIA
Northern Nigeria's high sensitivity to climate impacts is summarised by three key facts regarding
the exposure of its agricultural sector: i) production is almost entirely rain-fed; ii) accounts for
about 40 percent of Nigeria’s GDP; iii) employs 70 percent of the nations' work force.vi One
cannot understate the need for dedicated Northern Nigeria climate resilience institutions at the
level that would enable policy makers to tackle climate change problems with the precision that
is critical to the region's stability.vii More importantly, comprehensive regional-level analysis of
climate impact vulnerability would provide the spatial linkages critical for Northern Nigeria to
better understand how and where climate change might constitute a threat to security in the
country.viii
2.1.2 HOW WILL A CLIMATE RISK AND VULNERABILITY TYPOLOGY HELP CREATE A RESILIENT NORTHERN NIGERIA?
Northern Nigeria's weak capacity for adapting climate resilient strategic planning, enabling
institutions, resilience infrastructure investment will undermine the entire nation's socio-
economic and political stability, unless these issues are systematically addressed through
regional resilience measures. Experts warn that weak climate resilience threatens the security
situation in Northern Nigeria through agricultural productivity failure, climate-induced
displacement and water, energy and food scarcity, which will deepen regional conflict and
insecurity through poverty malnutrition and disease.ix It is projected that crop yield in Nigeria may
fall by 10-20% by 2050 or even up to 50% is sensitive to climatic variability.x Moreover experts
want that Northern Nigeria's failure for regional adaptation and resilience in agricultural sector
and resultant forecasts of crop yield decline, could led to decline of 4.5 percent of Nigeria's GDP
by 2050!xi
Hazards
•Natural Events
•Socio-economic Events
•Climatic Outcomes
Exposure
•Sub-region Units
•Settlement Area
•Infrastructure Coverage
Vulnerability
•Risk Sensitivities
•Biophysical Outcomes
•Social Vulberabilities
Adaptive Capacity
•Resilience Investment
•LGA Adaptation Plans
•Climate Proofing Communities

In order to dampen, mitigate, or possibly avert these extraordinary welfare losses forecasted for
an un-resilient Northern Nigeria, the nation must undertake regional climate resilience
assessment for both its Biophysical and Socio-economic risks it faces. Undertaking this typology
for regional adaptive capacity assessment provides the strength of 'bottom up' perspective of the
of sub-regional, state and community needs for climate proofing infrastructure investment and
institutional strengthening for resilience adaptation. Figure 2.1.2 captures salient outcomes of
the study's Regional Adaptive Capacity Assessment framework, which include resilience
strategies for enabling community, sector and institutional mapping for regional adaptive
capacities, based typology for groupings of regional and sub-regional population and sector
vulnerabilities through similar resilience strengthening measures. Thus, physical, social,
economic, and institutional resilience building strategies are derived from the study analysis.
Figure 2.1.2 Strategies for a Resilient Northern Nigeria
2.1.3 HOW IS OUR TYPOLOGY SET OUT?
The study typology, set out in Figure 2.1.3, is proposed through "integrated assessment
approach" which combines both socioeconomic and biophysical vulnerability approaches to
integrate assessment of Northern Nigeria's exposed population and sectors through regional
vulnerability profiles that draw casual linkages of both climate risk and resilience potential of
communities.xii The typology conceptualizes vulnerability to climate as a function of adaptive
capacity, sensitivity, and exposure, which accommodates the integrated approach to vulnerability
analysis. In particular, the "integrated assessment approach" is similar to the indicator-based
"Vulnerability Cube" typology (refer to 2.1) which enables typological grouping of the sub-regional
community-specific adaptive capacity profiles, based on index grouping relative needs for social,
physical, economic and institutional capacity strengthening.
The advantage of using this typology is based on evidence that this approach has enabled other
regional vulnerability assessment researchers to integrate both physical and social vulnerability
perspectives into regional analysis, which has not proved as successful in other typology
designs.xiii Illustrated in Figure 3, the typology presupposes that vulnerability, in this context, is a
physical risk (Biophysical Risk) and a social response (Socio-economic Risk/Sensitivity), within a
defined geographic territory, and thereby distinctly captured and isolated for spatial and temporal
adaptive capacity assessment.

Figure 2.1.3 Integrated Assessment Approach for Regional Vulnerability
2.2 METHODOLOGY
The study method utilises climate risk and vulnerability typologies as the basis for "Regional
Adaptive Capacity" Assessment (Fig 2.2) which frames rapid assessment of the strength of
Northern Nigeria's existing systems for adaptation and resilience planning, institutions and
investment practices.
Figure 2.2 Analytical Framework for "Regional Adaptive Capacity" Assessment

Climate risk profiles and projections are undertaken for DFID-defined northern states within its
four Eco-climatic zones (Fig 2.2.1), which capture environmental, meteorological, hydrological,
and ecological indicators historical, baseline, and projected climate scenarios.
In addition, the study typology for Geo-spatial Vulnerability (Fig 2.2.1) is utilised for comparative
grouping of potential climate variability and emerging climate scenario patterns through sub-
regional key impact indicators -- climate projections, population and risk exposure, and sensitivity
(Fig 2.2).
Also regional urban and rural settlements exposed to potential climate risks within the eco-
climatic zones are further grouped through potential geo-spatial patterns for Northern Nigeria's
rural and urban LGA clustering and relationship typologies, such as shared natural resources or
common infrastructure networks (Fig 2.2.1).
Figure 2.2.1 Geo-Spatial Vulnerability Typology: Eco-climatic Zones & Human
Settlements
URBAN
ENVIRONMENT
CAPITAL
NETWORKS
REGIONAL
CORRIDORS
RURAL
AGGLOMERATIONS
Kano/Katsina
Metropolitan
Areas
State Capital
to peri-urban
networks
Regional
railway,
highway and
road centres
Shared natural
resources or
geography
clusters;
Kaduna/Zaria
Urban and
Peri-Urban
Intra-State
infrastructure
networks
Regional
trade-
markets-
industrial
centres
Historic or
current
markets and
trading
clusters;
Sokoto/Bernin
Kebbi Urban
and Peri-
Urban
Inter-State
infrastructure
networks
Regional &
International
Crossing
Boundary
Ethnic,
nomadic, and
local clusters.
Next, the study typology for sub-regional Infrastructure Vulnerability (Fig 2.2.2) captures both
climate adaptation deficiency and resilience building potential of key infrastructure sectors in
Northern Nigeria. Thus, it serves as key analytical framework for rapid sub-regional assessment
of current infrastructure risks to its infrastructure, and thereby its 'adaptive capacity' for regional
resilience building measures to projected infrastructure risks.
In addition, illustrated in Figure 2.2.2, Risk Sensitivity, or socio-economic factors can deepen
vulnerability or strengthen resilience, and include environmental, physical, social and economic.
These key "Social Vulnerability indicators' are further mapped into the Broader Study typology in
Fig 2.2

Figure 2.2.2 Typology for Sub-Regional Infrastructure Vulnerability and Risk Sensitivity
Finally the sub-regional typology of climate exposure, sensitivity vulnerability draws together key
resilience factors for Northern Nigerian to strengthen its "adaptive capacity" in order to weaken
the effects of risk exposure for its rural and urban population groups, and regional infrastructure
sector sustainability and investments.
In conclusion and summarised in Section 2.1.2, the Risk Vulnerability assessment typology
utilised in the study provides powerful strategic tools for investigating and recommending viable
medium-term resilience interventions to strengthen regional support systems in Northern Nigeria
which urgently require managing, mitigating and adapting to serious and credible threat of
projected regional ecological and socio-economic failures.
2.2.1 RNN STUDY VULNERABILITY INDICATORS
I. Vulnerability Typology Baseline Indicators
a) Framing analysis within Northern Nigeria Four Eco-Climatic Zones:
o Southern Guinea savannah
o Sudan savannah
o Sahei savannah
o Northern Guinea savannah
b) Compiling and analyzing all available regional data for RNN vulnerability measures within
the unit of these eco-climatic zones
o Basic Demographic;
o Population distribution;
o Sub-regional and local government units;
o Population density;
o Temperature variability index;
o Rainfall variability index;
o Land aridity, deforestation and de-vegetation measures;
o Desertification measures;
o Urban and rural settlement exposure;
o Transport network;
o Water resource network and pipeline infrastructure;

o Power access and energy network;
o Livelihoods index;
o Poverty index;
o Agricultural—farming and pastoral – land use;
II. RNN Population and Sector Vulnerability Measures
a) Social
o Poverty and inequality
o Proportion of rural and urban population
o Female literacy
o Distance to Conflict areas
o Malnutrition, disease and infant mortality mitigation
b) Economic
o Per-capita GDP
o Livelihoods and key economic activities
o Agricultural, industrial and regional productivity
o Basic service investments
c) Geo-Physical and Environmental
o Natural and man-made boundaries and vulnerabilities
o % forested, vegetated land
o % Crop and pastoral land cultivation
o Incidence of drought, flood, event, change in frequency
o Agriculture, industry, domestic GHG management
d) Regional Infrastructure and Sector Risk
o Regional resilience capacity: built-up settlements and infrastructure
o Water resource management -- %Reservoir storage, ground-water recharge etc.
o Regional networks: spatial, settlement and roads form/connectivity
o Investments for agriculture, industry, domestic production and GHG management
III. RNN Drought Vulnerability Measures
a) Meteorological drought profiled through "Rainfall Deficit" baseline indicators and
indirectly captured through well-accepted indexes such as Standardized Precipitation
Index (SPI) or other available datasets that analyze co-variables capturing:
o Low precipitation
o High temperatures
o Strong Winds
o Increased solar radiation
o Loss of soil moisture
o Supply of irrigation water declines
b) Hydrological drought profiled through "Stream flow Deficit" baseline indicators and
indirectly captured through well-accepted indexes such as Palmer Drought Severity Index
(PDSI) or other available datasets that analyze co-variables capturing:
o Reduced infiltration

o Low soil moisture
o Little ground-water recharge
o Reduced storage in lakes and reservoirs
o Less water for urban supply and power generation
o Poorer water quality
o Ecosystems threatened
c) Agricultural drought profiled through " Soil moisture deficit" baseline indicators and
indirectly captured through well-accepted indexes such as Vegetation Condition Index
(VSI) and Crop-Specific Drought Index (CSDI) or other available datasets that analyze co-
variables capturing:
o Low evapotranspiration
o Plant water stress
o Reduced biomass
o Fall in ground-water levels
o Poor yields from rain-led crops
o Irrigation systems start to fail
o Pasture and livestock productivity decline
o Rural industries affected
d) Famine drought profiled through "Food deficit" baseline indicators capturing likely all of
the following, and must be argued with well-accepted public policy measures such as
United Nations criterion for declaring famine (1/5 of population food insecure):
o Loss of natural vegetation
o Increased risk of wildfires
o Wind-blown soil erosion (i.e. dust storms)
o Desertification
o Widespread failure of agricultural systems
o Food shortages on seasonal scale
o Rural economy collapses
o Rural-urban migration
o Increased malnutrition and related mortality
o Humanitarian crisis
o Borderline food insecure
o Acute food and livelihoods crisis
o Humanitarian emergency
o Famine/catastrophe
o Disease pandemic
e) Potential Data Sources and Relevant Drought and agricultural warning and monitoring
systems
o Normalized Difference Vegetation Index (NDVI) as early indicator for both crop and
pasture failure
o U.N. Global Information and Early Warning System (GIEWS)
o USAID Famine Early Warning System (FEWS-NET) Africa Real Time Environmental
Monitoring Information System (ARTEMIS)
2.3 RNN STUDY SECOND PHASE
1. Climate Change Economist with expertise in agricultural/food drought and
migration assessment scenarios, and proficient in the following:

1.1. Climate impact assessment and adaptation modeling at sub-regional, state and local
levels;
1.2. Climate impact and multi-hazard (climatological, environmental, and socioeconomic)
probability and severity historic and projection modeling for cross-region and cross-state
comparison amongst different typologies of rural and urban agglomerations;
1.3. Designing and co-leading Northern Nigeria field-based surveys for climate impact
assessment and adaptation models;
1.4. Estimating financial costs from climate impact;
1.5. Regional, state and local asset inventory at risk modeling;
1.6. Urban and rural agglomeration exposure assessment;
1.7. Multi-sector exposure assessment (water, energy, roads, livelihoods, agricultural—
farming and herding, human settlements, health, education);
1.8. Undertaking Climate Vulnerability and Capacity Analysis (CVCA) methods:
1.8.1.1. Agricultural and famine drought vulnerability analysis;
1.8.1.2. Crop yield sensitivity analysis;
1.8.1.3. Migration and conflict vulnerability analysis;
1.8.1.4. Social vulnerability.
1.9. Experience with Erosion Productivity Crop Model (EPIC);
1.10. Cost-benefit analysis for climate proofing infrastructure investment;
1.11. Developing and integrating climate resilience conceptual models and applied
framework for intergovernmental and multi-stakeholder institutional and governance
capacity building;
1.12. Climate adaptation and resilience modeling, validity testing, field-based
surveying, integrating impact assessment frameworks.
2. GIS (Geo spatial Mapping) Specialist with expertise in integrating data-sets for
two-way data streaming and visualisation of climate impact assessment and
adaptation modeling;
2.1. GIS-based analysis and cartography proficiency in visually integrating multivariate data-
sets and imagery from different sources (satellite imagery, remote sensing, national and
sub-national, field-based survey) for the following:
2.1.1. Climate impact projections;
2.1.2. Regional and local demographic;
2.1.3. Human settlements;
2.1.4. Socio-economic indexes;
2.1.5. Physical and social infrastructure.
2.2. Creating two-way streaming geo spatial mapping from emerging climate impact and
adaptation data-sets including:
2.2.1. Population distribution;
2.2.2. Sub-regional and local government units;
2.2.3. Population density;
2.2.4. Temperature variability index;
2.2.5. Rainfall variability index;

2.2.6. Land aridity, deforestation and de-vegetation measures;
2.2.7. Desertification measures;
2.2.8. Urban and rural settlement exposure;
2.2.9. Transport network;
2.2.10. Water resource network and pipeline infrastructure;
2.2.11. Power access and energy network;
2.2.12. Livelihoods index;
2.2.13. Poverty index;
2.2.14. Agricultural—farming and pastoral – land use;
2.2.15. Crop and grazing productivity index.
2.3. Streaming and converging sub-sets of geo spatial mapping for intermediate and final
analysis;
2.4. Cartography of final mappings at conclusion of study.
3. Northern Nigeria Political and State Institutions Expert.
4. Professional Graphic Designer.
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Adaptation Flagship Working paper No. 7. http://www.csiro.au/resources/CAF-working-papers.html
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xii Y. T. Maru, J. Langridge and B. B. Lin (2011) Current and potential applications of typologies in vulnerability assessments and adaptation science. CSIRO Climate
xiii Y. T. Maru, J. Langridge and B. B. Lin (2011) Current and potential applications of typologies in vulnerability assessments and adaptation science. CSIRO Climate

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