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A smallholder farmer leveldecision
support systemfor climate resilient
farming practices improves community
levelresilience to climate change
Submitted by Erna Kruger (Director Mahlathini Development Foundation - MDF)
Ph: 0828732289, Email: info@mahlathini.orgWeb: www.mahlathini.org
Partners: Erna Kruger, Mazwi Dlamini, Samukelisiwe Mkhize, Temakholo Mathebula, Phumzile
Ngcobo, Betty Maimela, Sylvester Selala and Lulama Magenuka(MDF)
Palesa Motaung, Nonkanyiso Zondi,Sandile Madlala,Khetiwe Mthethwa, Andries Maponya,
Nozipho Zwane, Lungelo Buthelezi, and Zoli Gwala (students and interns)
Mr Lawrence Sisitka (Research Associate- Environmental Learning Research Centre- Rhodes
University)
Mr Nqe Dlamini (StratAct)
Mr Chris Stimie (Rural Integrated Engineering)
Mr Jon Mc Cosh, Ms Brigid Letty (Institute of Natural Resources)
Mr Hendrik Smith (CA coordinator for GrainSA)
Ms Sharon Pollard (AWARD)
Ms Lindelwa Ndaba (Lima RDF)
Ms Catherine van den Hoof (formerly of WITS Climate Facility, now the United Nations World
Food Programme)
Summary
The more extreme weather patterns with increased heat, decreased precipitation and more extreme rainfall
events; increase of natural hazards suchas floods, droughts, hailstorms and high windsthat characterise climate
change place additional pressure on smallholder farming systems and has already led to severe losses in crop
and vegetable production and mortality in livestock.A significant proportion of smallholders have abandoned
agricultural activities and this number is still on the increase. Smallholders are generally not well prepared for
these more extreme weather conditions and experience high levels of increased vulnerabilityas a consequence.
It is becoming clear thatclimate change will have drastic consequences for low-income and otherwise
disadvantaged communities. Despite their vulnerability, these communities will have to make the most climate
adaptations. It is possible for individual smallholders to manage their agricultural and natural resources better
and in a manner that couldsubstantially reduce their risk and vulnerability generally and more specifically to
climate change. Through a combination of best bet options in agro-ecology, water and soil conservation, water
harvesting, conservation agriculture and rangeland management a measurable impact on livelihoods and
increased productivity can be made.
Processes such as collaborative, participatory research that includes scientists and farmers, strengthening of
communication systems for anticipating and responding to climate risks, and increased flexibility in livelihood
options, which serve to strengthen coping strategies in agriculture for near-term risks from climate variability,
provide potential pathways for strengthening adaptive capacities for climate change.
Mahlathini Development Foundation and our partners and collaborators (Universities, NGOs, CSI initiatives,
District and Local Municipalities and Government Departments),have been working within the socio-
ecological and social learning space to assist smallholder farmers in KZN, Limpopo and the Eastern Cape to
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improve their resilience and adaptive capacity to climate change by designing and testing a participatory
smallholder level decision support system for implementing climate resilient agricultural practices.
Within this process smallholder farmers explore and analyse their understanding of climate change and the
impacts of these changes on their livelihoods and agricultural systems. They explore adaptive strategies and
measures (local and external), prioritize appropriate practices for individual and group experimentation and
implementation, assess the impact of these new practices and processes on their livelihoods and re-plan their
actions and interventions on a cyclical basis.
This allows them to make incremental changes over time in soil and water management practices, cropping
and livestock management and natural resources management, within the limits of their own resources, vision
and motivation. This provides a viable model for CCA implementation and financing at smallholder level.
Recent participatory impact assessments have shown remarkable improvements in resilience in the space of
just one to two years of focussed local action.
Introduction
A current Water Research Commission adaptive research process entitled “Collaborative knowledge creation
and mediation strategies for the dissemination of Water and Soil Conservation practices and Climate Smart
Agriculture in smallholder farming systems”is exploring best practice options for climate resilient agriculture
for smallholders and evaluating the impact of implementation of a range of these practiceson the resilience of
agriculture based livelihoods. Alongside this, a decision support methodology and system has been designed to
assist smallholders and the facilitators who support them to make informed and appropriate decisions about
choices of a ‘basket of options’ for implementation at a local level.
The research process is broadly divided into three elements for purposes of clarity, although all three elements
are tackled concurrently:
1. Community climate change adaptation process design
2. Climate resilient agricultural practices and
3. A decision support system.
Community climate change adaptation process design
This consists broadly of
1. Situation and vulnerability assessments; baselines and farmer typologies
2. Climate Change dialogues; Exploration of climate change impacts, adaptive strategies and
prioritization of adaptive measures and
3. Participatory impact assessments: Resilience snapshots
1. Situation and vulnerability assessments
The model for vulnerability assessments used in this process provides for a combination of socio-economic
(livelihood) and socio-ecological (access and utilization of natural capital)indicators,in a climate change
context (wellbeing, adaptive capacity and governance). This is a new process design, built from elements of
existing international best practice options.
The process consists of focus groups discussions, individual interviews (baselines) and household visits, or
walkabouts as we call them –as they include a broad and initial assessment of the “lay of the land”.
This information is pulled together into a database that has been put together to provide for a farmer
segmentation/ farmer typology approach. Farmer typologies allow for differentiation between different levels
of vulnerability in a community to target interventions/ practices more specifically
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The three typologies developed within this process are shown in the figure below
Figure 1: Smallholder typology for climate resilient farming decision support system
A typical participant is thus:
These typologies are one of the input categories
into the decision support system.
Climate change dialogues
A participatory methodology has been developed to allow groups of farmers to explore the impacts of climate
change, potential adaptive strategies and to prioritize local adaptation measures. Seven community level
workshops have been conducted across three provinces, involving around 250 participants. The table below
provides a summary of this community level analysis
Table 1: Summary of climate change impacts from community level workshops (2018)
Climate change impacts on livelihoods and farming
KZN
EC
Limpopo
Water
Less water in the landscape;
streams and springs dry up,
borehole run dry, soils dry out
quickly after rain
Less water in the landscape; streams
and springs dry up, borehole run dry,
soils dry out quickly after rain
Less water in the landscape; streams
and springs dry up, borehole run dry,
soils dry out quickly after rain
Dams dry up
Dams dry up
Dams dry up
Typology A (2,5 million)
•Female headed,
•Farm for food only,
•Very low incomes –mostly
unemployed,
•Access to small plots of land
(<0,1ha),
•No household level access to
water,
•Lower education levels (Primary
school)
•No access to formal markets,
•Belong to village savings and loan
associations and
•Engage in other livelihood
activities
Typology B (250 000)
•Male and female headed,
•Farm for food and sell surplus,
•Slightly higher incomes,
•Access to larger plots of land
(0,1-1ha)
•Some access to hh level
water,
•Somewhat higher education
levels (High school),
•No access to formal markets
and
•Belong to village savings and
loan associations
Typology C (10 000)
•Male headed, Ffarm mainly for
income,
•Much higher incomes from
employment in the household,
•Good access to water at
household and field level,
•Higher education levels (Matric
nad post scholl qualifications),
•Acess to formal markets.
•Belong to cooperatives or farm
individually
A 51 year old woman, who is the head
of her household, has Grade 9-11 level
of education, is unemployed, has an
average monthly income of R2170,
engages in field cropping, gardening
and livestock husbandry, has no
access to water in her household,
engages in local markets only and
belongs to a savings group
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Municipal water supply becoming
more unreliable
Municipal water supply becoming
more unreliable
Municipal water supply becoming
more unreliable;
Need to buy water for household use
–now sometimes for more than 6
months of the year
RWH storage only enough for
household use.
Soil
More erosion
More erosion
More erosion
Soils becoming more compacted
and infertile
Soils becoming more compacted and
infertile
Soils becoming more compacted and
infertile
Soils too hot to sustain plant growth
Cropping
Timing for planting has changed-
later
Timing for planting has changed-
later
Can no longer plant dryland maize
All cropping now requires irrigation –
even crops such as sweet potato
Drought tolerant crops such as
sorghum and millet grow- but severe
bird damage
Heat damage to crops
Heat damage to crops
Heat damage to crops
Reduced germination and growth
Reduced germination and growth
Reduced germination and growth
Seeding of legumes becoming
unreliable
Seeding of legumes becoming
unreliable
Seeding of legumes becoming
unreliable
Lower yields
Lower yields
Lower yields
Winter vegetables don’t do well -
stress induced bolting and lack of
growth
More pests and diseases
More pests and diseases
More pests and diseases
Loss of indigenous seed stocks
Loss of indigenous seed stocks
Livestock
Less grazing; not enough to see
cattle through winter
Less grazing; not enough to see cattle
through winter
Less grazing; not enough to see cattle
through winter
More disease in cattle and heat
stress symptoms
More disease in cattle and heat
stress symptoms
More disease in cattle and heat
stress symptoms
Fewer calves
Fewer calves
Fewer calves
More deaths
More deaths
More deaths
Natural
resources
Fewer trees; too much cutting for
firewood
Fewer trees; too much cutting for
firewood
Fewer trees; too much cutting for
firewood
Decrease in wild animals and
indigenous plants
Decrease in wild animals and
indigenous plants
Decrease in wild animals and
indigenous plants
Increased crop damage from wild
animals such as birds and
monkeys
Increased crop damage from wild
animals such as birds and monkeys
Increased crop damage from wild
animals such as birds and monkeys
Availability of indigenous
vegetables has decreased
No longer able to harvest any
resources due to scarcity
Increased population puts pressure
on resources
Social
More diseases
More diseases
More diseases
Increased poverty and hunger
Increased poverty and hunger
Increased poverty and hunger
Increased crime and reduced job
opportunities
Increased crime and reduced job
opportunities
Increased crime and reduced job
opportunities
Increased food prices
Increased conflict
Inability to survive
Although the impacts discussed were similar across the three provinces, the severity of these changes are a lot
more obvious in Limpopo.
From these impact diagrams community members discuss adaptive measures and strategies; what they have
already tried and what they would like to try. Here the new ideas or innovations can then be introduced by
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facilitators, as they are requested by the community members. The table below is illustrative and are the
adaptive measures suggested by the participants in Turkey village (Lower Oliphant’s’ Basin – Limpopo)
Table 2: An example of potential adaptive measures from the Turkey (Limpopo) climate change dialogue
process
Turkey CC workshop; December 2017
Impacts
Description and linkages
Outcomes
Potential adaptive measure
Reduced water
availability
Dams dry out, boreholes provide
less water, rivers dry out, less
rain
Reduced
production, hunger,
diseases, no jobs,
poverty, crime,
death
More boreholes, more dams, water
management, irrigation in evenings and
early morning, mulching, trench beds
(keep moisture in and soil cool)
Drying of
environment
Soils are hotter and drier,
drought, plants wilt, increased
pests
Save plant residues for animals, buy
fodder, control pests on animals
Reduction of
resources
Deforestation, Fruit trees die,
livestock, wild animals die
Planting of trees after they have been
cut down; make use of paraffin stoves
and electricity, government involvement
in solving the problem,
Extreme heat
Early fruiting, trees wilt
Poor crop health
Shade netting
Shortage of
water
Rivers dry out, municipal supply
only once per week. Boreholes
dry out
Lack of education
towards saving
water
NGOs and government to assist
Trench beds, mulching, save water in
dams, drip irrigation, irrigate in evening,
boreholes, greywater
Reduction of
resources
Less grazing, seed shortage, trees
are removed, indigenous animals
are no longer there
Increased
vulnerability of the
people, forced to
move to urban
areas
Donations for/of seed
Rather use paraffin stoves than
firewood. Only chop down mature trees
to allow others to grow, planting trees,
government intervention
Taking care of indigenous plants
Plant fodder for livestock
Soils
Poor cultivation practices, soil
erosion, dry soils, sandy soils
Using crop residues and manure,
conservation agriculture, mixed
cropping
Social
repercussions
Less or no food, health problems,
no jobs
Burning of buses,
divorce, separation
of families, poverty,
crime
Getting access to health care, parents
must work
Shortage of
implements
Setting up cooperatives for government
support, use animal drawn traction-
oxen and donkeys, improvise, make our
own tools, make use of hand hoes
A list of specific practices is summarised from these discussions and categorized into the five climate resilient
agriculture themes. An example is given below of this process conducted for a learning group from Ezibomvini
Village in Bergville, KZN.
The following table outlines the practices and their categories
Table 3: Suggested practices for farmers, categorised into the 5 primary themes.
Natural RM
Soil
Water
Crops
Livestock
Shade cloth Tunnels
Bed design
Mulching
Natural pest and diseases
Rainwater harvesting
Trench bed
Composting
Conservation Agriculture
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Fodder crops
Underground water tank
Mixed cropping
Conservation of wetlands and streams
Burying of disposable pampers
Reducing burning of grazing veld
Greywater use
Participants then prioritize these practices in order of
importance for implementation and change as a group.This
depends on local conditions such as drought, harsh weather
conditions and the like.The preference ranking for this
group was as follows:
1. Underground rainwater harvesting tanks
2. Shade cloth tunnels
3. Trench beds
4. Mulching
5. Natural pest and disease control
6. Mixed cropping(fields and gardens)
7. Compost
8. Fodder crops
9. Conserving wetlands and streams
Right: Sylvester and Temakholo from MDF, facilitating the
prioritization of practices
It is also possible here to do
a matrix ranking exercise
where you elucidate from
the groups their criteria for
prioritization of practices,
which is a very important
step in the community level
decision making process.
Right: A group level matrix
using community defined
criteria for prioritizing climate
smart/resilient agricultural
practices to be tried out
(Thabamhlophe village,
Estcourt, KZN, 2018)
This provides a broad action plan for implementation, which is developed further into an individual farmer
level experimentation plan. Participants choose from these prioritized practices which ones they will try out in
their own homesteads and devise a broad plan of how to intervene in the communal activities such as
conservation of wetlands. This process also provides a good agenda for securing external support from role
players in the development sector (government Departments, Municipalities, CSI and NGO funded projects)
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3. Participatory Impact Assessments
After a cycle of experimentation with the basket of CRA practices (one season/ 6 months), the
process is reviewed and a participatory impact assessment process is conducted with the learning
group members. Again, it is important for community members themselves to develop the impact
indicators/criteria
The diagram below provides a summary of all the practices that were tried out for the KZN learning
groups for the 2018-2019 season
1: Tower garden; using greywater for irrigation, planted to kale, spinach and tomatoes
2: Eco-circle with a 2litre bottle (with holes) used forin situ irrigation and planted to a mixture of herbs and vegetables
3: Bucket drip kits inside a shade cloth tunnel
4: raised bed with mixed cropping planted as a “normal practice control” when comparing with trench beds
5: A Shade cloth tunnel with 3 5x1m trench - beds
6: Inspection of a locally protected spring
7: A shallow trench bed planted to a mixture of green peppers,
chillies and marigolds
8: A deep trench bed planted to a mixture of kale, rape, mustard
spinach and Chinese cabbage
9: A maize and cowpea intercropped conservation agriculture
(CA) plot
10: A CA plot planted to summer cover crops; sunflower, millet
and sunnhemp
11: A CA plot planted to Dolichos beans
12: Making bales of hay with a small manual baler
Community members worked in small groups to analyse for
themselves the impact of the climate resilient agricultural
practices they have been implementing.
Right: Participants from 4 learning groups work together in
assessing the impact of their implementation
2
3
4
5
6
7
8
9
10
11
12
1
8
Below is the result of a matrix ranking exercise conducted during this session. The research team were
incredibly impressed with the depth of analysis participants undertook and with the impact indicators
participants developed. It also indicates that smallholder farmers use integrated and systemic indicators to
make their decisions and not just production and income data, commonly used in agriculture.
Table 4: Participatory impact assessment of CRA practices by Ezibomvini participants, March 2019.
IMPACT
INDICATORS
PRACTICES
Soil;
health
and
fertility
Money;
income
and
savings
Productivity;
acceptance
of practice,
saving in
farming –
equipment,
labour
Knowledge;
increased
knowledge
and ability
to use
Food;
how
much
produced
and how
healthy
Water;
use
and
access
Social agency;
Support,
empowerment
Total
Conservation
Agriculture
22
21
26
28
18
23
18
156
Savings
6
15
14
15
12
11
15
88
Livestock
19
11
18
7
5
12
11
83
Gardening
14
15
12
13
15
17
21
107
Crop rotation
16
12
13
12
12
15
10
90
Intercropping
12
13
15
12
11
11
9
83
Small
businesses
11
17
15
10
20
11
9
93
The resilience snapshot put together from individual interviews of these same participants, gives a very strong
indication of the benefit of CRA to the livelihoods of the rural poor. Climate change adaptation for these
participants has resulted in increased availability of food, incomes and social agency and has provided hope for
a more positive future for these participants.
Table 5: Resilience snapshot for Ezibomvini participants, March 2019.
Resilience indicators
Rating for increase
Comment
Increase in size of farming
activities
Gardening –18%
Field cropping –63%
Livestock –31%
Cropping areas measured, no of livestock assessed
Increased farming activities
No
Most participants involved in gardening, field cropping
and livestock management
Increased season
Yes
For field cropping and gardening- autumn and winter
options
Increased crop diversity
Crops: 12 new crops
Practices: 8 new practices
Management options include; drip irrigation, tunnels,
no-till planters, JoJo tanks, RWH drums,
Increased productivity
Gardening –72%
Field cropping –79%
Based on increase in yields
Positive impact of CRA and associated practices in order of
importance: Conservation Agriculture, gardening (tunnels,
agroecology), small businesses (farmer centres, poultry),
savings, livestock (integration –fodder, health)
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Livestock –25%
Increased water use efficiency
25%
Access, RWH, water holding capacity and irrigation
efficiency rated
Increased income
13%
Based on average monthly incomes
Increased household food
provisioning
Maize- 20kg/week
Vegetables –7kg/week
Food produced and consumed in the household
Increased savings
R150/month
Average of savings now undertaken
Increased social agency
(collaborative actions)
2
Villages savings and loan associations and learning
groups
Increased informed decision
making
5
Own experience, local facilitators, other farmers,
facilitators, extension officers
Positive mindsets
2-3
More to much more positive about the future: Much
improved household food security and food availability
Climate resilient agriculture practices for smallholders
The approach is to work directly with smallholders in local contexts to improve practices and synergise across
sectors. The emphasis is thus at farm/household level. Here CSA aims to improve aspects of crop production,
livestock and pasture management, natural resource management, as well as soil and water management as
depicted in Figure 2 below.
Figure 2: Household level implementation of CSA integrates across sectors (adapted from Arslan, 2014)
A database of 66 different practices falling into the categories mentioned in the figure above has been
compiled, based on local suggestionsand best bet options from experience and literature.
SYNERGIES
Soil
and water
conservation
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For each practice, a 1-page summary has been put together, that can be presented to smallholders in the
climate change adaptation workshops, for consideration by the smallholder farmers as a new idea or
innovation to experiment with. Below are two illustrative examples
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This database provides a resource to farmers and facilitators to choose appropriate climate resilient
agricultural practices for their area and their particular situation. It is one of the input parameters for the
decision support process.
In addition, qualitative and quantitative indicators have been explored to Physically assess the impact of these
practices. These have included for example run-off, infiltration, water holding capacity in the soil profile, and
water productivity as well as a number of soil based parameterssuch as organic matter content, soil fertility
and microbial activity.
As an example, a farmer level experimentation process consisting of production in trench beds, inside and
outside of shade cloth tunnels was conducted. The control for this experiment was the farmer’s ‘normal’
gardening practice –in this case raised beds.
Above left to right: Spinach grown in a trench bed inside a tunnel, in a trench bed outside atunnel and in a
control bed (raised bed), by Phumelele Hlongwane
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Farmers kept careful records of the amount of water applied (irrigation) and their harvests (yields), alongside
the research team who worked with local weather stations and soil moisture measurements to assess the
water productivity of these practices.
The table below outlines the resultant water productivity calculation for this experiment. Both conventional
WP calculations and a simpler format suggested by farmers that only uses their water applied were used.
Table 1: Water productivity for production of spinach inside and outside shade cloth tunnels for 2
smallholder farmers in KNV, Bergville
Bgvl June-Sept 2018
Simple scientific method (ET)
Farmers' method (Water applied)
Name of famer
water use
(m3)
Total weight
(kg)
WP
(kg/m3)
water use
(m3)
Total weight
(kg)
WP
(kg/m3)
Phumelele Hlongwane trench
bed inside tunnel
1,65
21,06
12,76
1,85
21,06
11,38
Phumelele Hlongwane; trench
bed outside tunnel
0,83
5,32
6,45
1,75
5,32
3,04
Ntombakhe Zikode trench bed
inside tunnel
1,65
17,71
10,73
2,37
17,71
7,47
Ntombakhe Zikode; trench bed
outside tunnel
0,50
3,35
6,76
0,53
3,35
6,33
The control plots are not included here, as the two farmers realised quite early in the season that their normal
production methods required too much water and opted to focus only on the trench beds. Water productivity
is 60-100% higher for trench beds inside the tunnels when compared to trench beds outside the tunnel –using
the more scientific approach that also takes into account evapotranspiration and leaching. This is a highly
significant result, indicating the potential of micro-climate control in adaptation.
Water productivity calculate only from yields compared to water applied, shows a larger variation in results for
the two participants. They both applied more water to their trench beds outside their tunnels, than inside;
working on the assumption that the reduced growth for the crops outside the tunnel was due to water stress.
This experimentation process assisted in their learning that plant stress also includes other factors such as
temperature, wind and insect damage.
The smallholder climate change adaptation decision support process
The decision support process focusses on a bottom -up approach, where individual farmers in a locality make
decisions regarding the ‘basket’ of CSA/CRA approaches and practices most suited to their specific situation.
To do this in a way that also includes the concepts of social learning, innovation and agency the following
decision support concept has been developed.
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The process is designed to also support and assist the facilitator in their decision making, in support of the
smallholder farmers; meaning that the facilitator accessesinformation such as the basic climate change
predictions for the area, the agroecological characteristics including rainfall, temperature, soil texture etc) and
an initial contextualised basket of CSA practices from which to negotiate prioritized practices with farmers.
Practices are thus chosen by both facilitators and farmers.
Figure 3: The smallholder CSA/CRA decision support model
The model is designed primarily as a participatory and facilitated process at community level. In support of this
process, a computer-based model can be used alongside this methodology to provide further information and
decisions support to the facilitator. It is also possible for a farmer to access this model independently to derive
an initial basket of CSA practice options for themselves.
The computer model information flow is designed asshown in the figure below –and follows the same basic
steps as the facilitated model shown in Figure 4 below.
PHYSICAL ENVIRONMENT: Climate and geographical
parameters; GPS coordinates, agroecological zones,
soil texture, slope and soil organic carbon content
PRACTICES: Database of CSA practices including; managing available
water, improving access to water, controlling soil movement, improving
soil health and fertility, crop management, integrated crop-livestock
management, veld management and veld rehabilitation
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Figure 4: The computer-based model for the smallholder DSS
In our case the set of criteria (proxies used as indicators for the complex reality) that helpsto make informed
decisions on management practices are:
➢The current farming systems; gardening, field cropping, livestock production and natural resource
management (NRM) (including trees),
➢The physical environment: agroecological zone, soil texture, slope and organic soil carbon and
➢The socio-economic background of the farmer; demographic information (gender HH head, age,
dependency ratio), level of education, sources of income (unemployment vs. external employment,
own business, grants, farm, etc.), total income, access to services, infrastructure, technology
(Electricity, water (tap, borehole, rainwater harvesting, etc.), irrigation (buckets, standpipes, etc.),
fencing and farming tools (hand vs traction/other), social organisation, market access (formal vs.
informal), farm size andfarming purpose (food vs. selling).
Besides this, the resources and related management strategies as well as a list of practices need to be
provided as input to the system. All information, except the physical environment; i.e. climate, soil and
topography, and the resources and management strategies, are derived through the use of a range of
participatory processes. Data on the physical environmental conditions have been taken from datasets freely
available online. This information can however be customised by the DSS user, in case more appropriate
information is available for the specific farmer concerned.
For the Facilitator-Farmer DSS the resources and related management strategies are discussed and negotiated
in the participatory process. For the computer based or Individual Farmer DSS these are provided as an input
into the model using the following framework:
FARMING SYSTEMFARMER SOCIO-ECONOMIC
BACKGROUND
RESOURCES TO MANAGE
SUGGESTED PRACTICES
CONSTRAINED BY
TYPOLOGY, SYSTEM
AND ENVIRONMENT
RANKED PRACTICES
BASED ON FACILITATORRANKED PRACTICES
BASED ON FARMER
FARMER BASED
PRIORITIES
FACILITATOR
BASED PRIORITIES
PHYSICAL ENVIRONMENT
DSS PROCESS FLOW
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Figure 5: Resources to manage and their associated managements strategies
Once all the information is inputted into the model an initial list of practices is suggested for each individual
farmer. The model has been tested and refined, through comparison of this computed based process with the
participatory process and assessing how closely these two processes are aligned.
Below is an example for 1 farmer in each of the three provinces where the model has been tested.
Table 6: Basket/list of practices recommended for version 2 of the DSS
Province
KZN
Limpopo
EC
Village
Ezibomvini
Sekororo
Mxumbu
Name and Surname
Phumelele Hlongwane
Chenne Mailula
Xolisa Dwane
Drip irrigation
0
0
0
Bucket drip kits
0
0
0
Furrows and ridges/ furrow irrigation
0
0
0
Greywater management
1
1
0
Shade cloth tunnels
1
1
0
Mulching
1
1
0
Improved organic matter (manure and crop
residues)
1
1
1
Diversion ditches
1
0
0
Grass water ways
0
0
0
Infiltration pits / banana circles
1
1
0
Zai pits
1
0
0
Rain water harvesting storage
1
1
1
Tied ridges
0
0
0
Half- moon basins
0
0
1
Small dams
0
0
0
Contours; ploughing and planting
1
0
0
Gabions
0
0
1
Stone bunds
0
0
0
Check dams
0
0
1
Cut off drains / swales
0
0
1
Terraces
0
0
0
Stone packs
1
0
0
Strip cropping
1
0
0
Pitting
1
1
0
Woodlots for soil reclamation
1
0
0
16
Targeted application of small quantities of
fertilizer, lime etc
1
0
0
Liquid manures
1
1
0
Woody hedgerows for browse, mulch, green
manure, soil conservation
1
0
0
Conservation Agriculture
1
0
0
Planting legumes, manure, green manures
1
0
0
Mixed cropping
1
0
0
Planting herbs and multifunctional plants
1
0
0
Agroforestry (trees + agriculture)
1
0
0
Trench beds/ eco circles
1
1
0
push-pull technology
1
0
0
Natural pest and disease control
1
0
0
Integrated weed management
1
1
1
Breeding improved varieties (early maturing,
drought tolerant, improved nutrient
utilization),
1
1
1
Seed production / saving / storing
1
1
1
Crop rotation
1
1
1
Stall feeding and haymaking
0
0
0
Creep feeding and supplementation
1
0
0
Rotational grazing
1
0
1
De-bushing and over sowing
1
0
1
Rangeland reinforcement
1
0
1
Bioturbation
1
1
1
Tower garden
1
1
0
Keyhole beds
1
1
0
No of practices recommended
35
16
14
For the KZN participant, this means that around 88% of thefull list of practices have been recommended for
her. She has a wide range of recommendationsbeing a farmer in Typology B (fewer restrictions) and engaging
in gardening, cropping and livestock production. Although this is quite high, it is understood that the farmer
level ranking is still to take place and these practices can then be prioritized and narrowed down further. For
the Limpopo and EC participants, around 1/3 of practices have been recommended in their basket of options.
Ranking can be undertaken first by the facilitator, or can be done directly by the farmer depending on the
circumstances. Below is the ranking exercise undertaken for Phumelele Hlongwane (Ezibomvini, KZN).The
practices shown in green are those that Phumelele are already implementing. This ranked list then provides
options for inclusion of further ideas and practices
Table 7: Ranking of CRA practices recommended for Phumelele Hlongwane
(KZN; Bergville)Phumelele Hlongwane: List of practices scored by facilitator
Practices
Field
cropping
Vegetable
gardening
Livestock
Natural
resources
and trees
Shade cloth tunnels
8
Mulching
9
Improved organic matter
11
11
11
Diversion ditches
9
9
9
Infiltration pits
10
Zai pits
10
10
RWH storage
9
9
9
9
17
Stone packs
9
9
9
Strip cropping
11
Pitting
11
11
11
Woodlots for soil reclamation
9
9
9
Targeted fertilizer application
8
Liquid manure
7
Woody hedge rows
10
10
10
Conservation agriculture
11
11
11
11
Planting legumes, manure, green manures
8
8
8
Mixed cropping
9
9
Planting herbs and multifunctional plants
9
9
Agroforestry (trees + agriculture)
11
11
11
11
Trench beds/ eco circles
9
push-pull technology
7
Natural pest and disease control
7
7
7
Integrated weed management
7
7
7
Breeding improved varieties (early maturing,
drought tolerant, improved nutrients),
7
7
7
7
Seed production / saving / storing
6
6
6
Crop rotation
9
9
Stall feeding and haymaking
Creep feeding and supplementation
7
Rotational grazing
9
De-bushing and over sowing
9
Rangeland reinforcement
9
Bioturbation
9
9
9
9
Tower garden
10
Keyhole beds
10
Below are a few indicative photographs of Phumelele’s CRA practices.
18
Above clockwise from top left: A view of Phumelele Hlongwane’s vegetable garden, a newly
constructed tower garden, trench beds planted to a mixture of vegetables in her shade cloth
tunnel, a plot of Dolichos in her CA field and a plot of summer cover crops- sunnhemp and millet.
Conclusion
The decision support system for climate resilient agriculture implementation by smallholder farmers is an
important new innovation in the field of community-based climate change adaptation and can be scaled up as
a framework in research, learning and implementation in this field.