236
have become interested in the uptake and scaling of climate-smart agriculture (CSA).
Many of the studies to date have focused on the production end of the value chain—i.e.,
ways to help farmers grow more food. This limited focus neglects the importance of the
harvesting, storage, processing and marketing stages. More researchers now are recognizing that food security is not just an issue of production but also of distribution, access
and affordability (Ericksen 2008; Ingram 2011) CSA studies must follow suit.
This study argues that successful adaptation requires consideration of how climate
change will affect all aspects of the value chain. It draws upon the county climate risk
profiles (CRPs), a project of the International Center for Tropical Agriculture (CIAT)
in collaboration with the Government of Kenya through the Ministry of Agriculture,
Livestock and Fisheries and with funding through the World Bank. Addressing different stages of the value chain—input provision, on- farm production, harvesting, storage, processing and marketing—these CRPs assess actual and potential climate risks.
The project’s aim is to provide county governments and stakeholders with localized
evidence of climate vulnerabilities and possible adaptation responses.
Each climate risk profile is framed around six key analytical stages: (i) overview
of the agricultural context in the county; (ii) assessment of climate vulnerabilities
across agricultural value-chain commodities; (iii) overview of on- and off-farm
adaptation strategies specific to each selected value chain; (iv) analysis of available
policies and programs to address climate change impacts on agriculture; (v) assessment of governance, institutional resources and capacity to incentivize uptake of
adaptation strategies; and (vi) recommendations for addressing gaps that hinder
effective institutional operation and collaboration. To date, profiles of 31 Kenyan
counties have been developed.
This chapter presents a case study conducted in Nyandarua County. Our goal is
to demonstrate the necessity of including value-chain perspectives in the design and
scaling of CSA interventions.
20.2 Methodology
This paper draws on data collected and analyzed for Nyandarua County between June
and September 2016. Nyandarua is located in the central area of the country and has
a population of 596,268 (2009) over a land area of 3245 km
2
. Temperatures range
from 12 °C (July) to 25 °C (December), and annual rainfall ranges between a minimum of about 700 mm and a maximum of about 1700 mm spread over two seasons,
mostly in the first wet season (January–June), but also in the second (short) wet season
(September–December) (GOK 2014). The rainfall decreases from East to West.
Agriculture is the main income-earning activity, employing 69% of the people, with
crop production (estimated at 17 billion KES) and livestock keeping (7 billion KES)
contributing 73% to the household incomes (MoALF 2016). Crop production in the
county is mostly rain-fed, small-scale and for subsistence purposes. Malnutrition is a
key challenge in the county, with 39% of the population estimated to be affected by
food insecurity and 35% of children below 5 years stunted.
C. Mwongera et al.
have become interested in the uptake and scaling of climate-smart agriculture (CSA).
Many of the studies to date have focused on the production end of the value chain—i.e.,
ways to help farmers grow more food. This limited focus neglects the importance of the
harvesting, storage, processing and marketing stages. More researchers now are recognizing that food security is not just an issue of production but also of distribution, access
and affordability (Ericksen 2008; Ingram 2011) CSA studies must follow suit.
This study argues that successful adaptation requires consideration of how climate
change will affect all aspects of the value chain. It draws upon the county climate risk
profiles (CRPs), a project of the International Center for Tropical Agriculture (CIAT)
in collaboration with the Government of Kenya through the Ministry of Agriculture,
Livestock and Fisheries and with funding through the World Bank. Addressing different stages of the value chain—input provision, on- farm production, harvesting, storage, processing and marketing—these CRPs assess actual and potential climate risks.
The project’s aim is to provide county governments and stakeholders with localized
evidence of climate vulnerabilities and possible adaptation responses.
Each climate risk profile is framed around six key analytical stages: (i) overview
of the agricultural context in the county; (ii) assessment of climate vulnerabilities
across agricultural value-chain commodities; (iii) overview of on- and off-farm
adaptation strategies specific to each selected value chain; (iv) analysis of available
policies and programs to address climate change impacts on agriculture; (v) assessment of governance, institutional resources and capacity to incentivize uptake of
adaptation strategies; and (vi) recommendations for addressing gaps that hinder
effective institutional operation and collaboration. To date, profiles of 31 Kenyan
counties have been developed.
This chapter presents a case study conducted in Nyandarua County. Our goal is
to demonstrate the necessity of including value-chain perspectives in the design and
scaling of CSA interventions.
20.2 Methodology
This paper draws on data collected and analyzed for Nyandarua County between June
and September 2016. Nyandarua is located in the central area of the country and has
a population of 596,268 (2009) over a land area of 3245 km
2
. Temperatures range
from 12 °C (July) to 25 °C (December), and annual rainfall ranges between a minimum of about 700 mm and a maximum of about 1700 mm spread over two seasons,
mostly in the first wet season (January–June), but also in the second (short) wet season
(September–December) (GOK 2014). The rainfall decreases from East to West.
Agriculture is the main income-earning activity, employing 69% of the people, with
crop production (estimated at 17 billion KES) and livestock keeping (7 billion KES)
contributing 73% to the household incomes (MoALF 2016). Crop production in the
county is mostly rain-fed, small-scale and for subsistence purposes. Malnutrition is a
key challenge in the county, with 39% of the population estimated to be affected by
food insecurity and 35% of children below 5 years stunted.
C. Mwongera et al.