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ACKNOWLEDGEMENT
We give special thanks to all those who made this work possible, including the project staff and field
teams who fully supported us when we reached to them without fail. We also express our sincere
appreciation to the pastoral, agro-pastoral, IDPs and the peri-urban communities in the locations that
we reached during the assessment for their willingness, support and participation. Thank you to the
most important stakeholders and the consortium of seven international NGOs namely Action Against
Hunger (AAH), the Adventist Development and Relief Agency International (ADRA), Cooperative
Assistance for Relief Everywhere (CARE), Cooperazione Internazionale (COOPI), Danish Refugee
Council (DRC), Oxfam and World Vision Somalia, community leaders, farmer groups/cooperatives and
members, without their participation, this work would not have been possible.
Finally our sincere gratitude to the Federal Government of Somalia led by The Ministry of Planning,
Investment and Economic Development who actively supported sustained engagments to develop and
harmonise tools participate in the field assessments and support the inter-ministerial knowledge
synthesis and learning workshops in Mogadisho.
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Recommended Citation:
SomReP. 2020. Annual Resilience Measurement study World Vision Somalia. January 2021.
© 2021 World Vision Somalia on behalf of SomReP.
Notice:
• For any reuse or distribution, the license terms of this work must be made clear to others.
• Any of the above conditions can be waived if permission is obtained from the copyright holder.
• Nothing in this license impairs or restricts the author’s moral rights.
• Fair dealing and other rights are in no way affected by the above.
• The parts used must not misrepresent the meaning of the publication.
• World Vision would appreciate being sent a copy of any materials in which text, photos etc. have
been used.
Disclaimer:
This report has been produced under the auspices of the Somalia Resilience Program (SomReP). The
contents of the materials produced do not necessarily reflect the views of our donors or associated
governments.
Report prepared by:
Donald Otieno Ochieng – Head of Quality Assurance and M&E SomReP
Mohamed Ahmed Abdulle-Head of Performance Monitoring and Review Monitoring and Evaluation
Department - MoPIED, FGS
Sakariye Harbi- Research and Evaluation Monitoring and Evaluation Department - MoPIED, FGS
Abel Kavuta Monitoring and Evaluation Manager- Northern Somalia SomReP
Dennis Nyakeya, Monitoring and Evaluation Manager- Southern Somalia SomReP
Sandra Ndungu GIS and Knowledge Management Coordinator SomReP
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TABLE OF CONTENT ii
iv
ACKNOWLEDGEMENT v
TABLE OF CONTENT viii
LIST OF TABLES AND FIGURES ix
ACRONYMS AND ABBREVIATIONS xii
EXECUTIVE SUMMARY xii
SUMMARY FINDINGS OF KEY INDICATORS xii
1
Core indicators 2
Outcome Indicators 3
1.0 INTRODUCTION 3
2.0 ASSESSMENT SCOPE AND OBJECTIVES 3
3.0 ASSESSMENT APPROACH AND METHODS 3
3.1 Study Design 4
3.2 Sampling 4
3.3 Data collection 5
5
3.3.1 Literature Review 6
3.3.2 Household Survey 6
3.3.3 Key Informant Interviews 7
3.3.4 Focus Group Discussions 7
3.3.5 Field Observations and Project Activity Audit 9
3.4 Data Analysis and Reporting 10
3.5 Ethical Considerations 10
3.6 Limitations of the Study 11
4.0 PROJECT AREA MAP 11
5. FINDINGS AND DISCUSSIONS 13
5.1 Demographic Characteristics 13
5.2 Effectiveness of SomReP Programme 16
5.2.1 Income and Livelihood 19
5.2.2 Food security 21
5.2.2.1 Food Consumption Score (FCS) 24
5.2.2.2 Household Hunger Scale (HHS) 27
5.2.2.3 Household Dietary Diversity Score (HDDS) 31
5.2.2.4 Reduced Coping Strategy Index (rCSI) 33
5.2.3 Household and community assets 37
5.2.4 Livestock Ownership 40
5.2.5 Agriculture and Livestock Production 43
5.2.5.1 Crop Production 44
5.2.5.2 Good Agricultural Practices 44
5.2.5.3 Farmer Managed Natural Regeneration (FMNR)
5.2.5.4 Village Development Committee (VDC) Page | iv
5.3 Absorptive Capacity of the Communities Livelihoods
5.3.1 Common Hazards in the Project Areas
5.3.2 Household Contingency plans 52
5.3.3 Savings and access to credit facilities 53
5.3.4 Community Based Disaster Risk Management 55
5.4 Ecosystem Health and Natural Resource Management (NRM) 56
5.4.1 Natural Resource Management 56
5.4.2 Water Resource Management 57
5.4.3 Access to Land 60
5.5 Accountability, Research, Learning and Innovation 61
5.6 Resilience and Poverty index among SomReP beneficiaries 63
5.6.1 Resilience 63
5.6.2 Poverty levels among beneficiaries 67
5.7 SomReP Project Implementation Strategy 68
5.8 SomReP interventions Suitability and Relevance 69
5.9 Programme Reach/Intensity of activities across the districts 70
5.9 Effectiveness of the Project Interventions 71
5.10 Efficiency of the Project Interventions 74
5.11 Sustainability of the Project Interventions 74
6.0 Cross-cutting Issues 76
6.1 Gender Integration 76
6.2 Environmental Conservation 76
6.3 Human Welfare and Protection 77
6.4 Peace and Conflict Resolution 77
7.0 CHALLENGES AND LESSONS LEARNED 79
7.1 Key Challenges and Constraints 79
7.2 Lessons Learned and Way Forward 80
7.0 CONCLUSIONS AND RECOMMENDATIONS 83
7.1 Conclusion 83
7.1 Recommendations on SomReP ARM 83
8.0 BIBLIOGRAPHY 85
ANNEXES 87
LIST OF TABLES AND FIGURES
List of Tables
Table 1: Education level of the HH head across programme districts..........................................................10
Table 2: Main source of income across programme districts ......................................................................11
Table 3: Adoption of multiple source of income across the livelihoods zones ............................................12
Table 4: Household Dietary Diversity Score across livelihood zones ...........................................................20
Table 5: Reduced Coping Strategy Index across project districts .................................................................21
Table 6: Type of dwelling across project districts ........................................................................................25
Table 7: Type of dwelling across gender ......................................................................................................25
Table 8: Assets ownership by household across districts.............................................................................25
Table 9: Assets ownership across livelihood zones ......................................................................................26
Table 10: Livestock ownership across livelihood zones in the project areas ...............................................27
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Table 11: Type of livestock owned across project districts ..........................................................................29
Table 12: Type of livestock owned disaggregated by livelihood zone..........................................................30
Table 13: Average land size cultivated growing seasons..............................................................................33
Table 14: Average land size cultivated growing seasons..............................................................................33
Table 15: Choice of crops and mean acreage farmed during dry season (Hagga) .......................................34
Table 16: Choice of crops and mean acreage farmed during main cropping seasons (Gu) .........................34
Table 17: Choice of crops and mean acreage farmed during short rain cropping seasons (Deyr)...............35
Table 18: Choice of crops and mean acreage farmed during the dry seasons (Jilal)....................................35
Table 19: Perceived yield improvement by Households ..............................................................................36
Table 20: Households who have adopted GAP techniques in the project areas..........................................38
Table 21: Average land size allocated to FMNR ...........................................................................................41
Table 22: Awareness of the existence of community VDC...........................................................................43
Table 23: Type of hazard/shocks faced across the project districts .............................................................44
Table 24: Type of hazard/shocks faced across the livelihood zones ............................................................44
Table 25: Early warning information on hazard across the project districts ................................................45
Table 26: Percentage of HH using various source of information on hazard across the project districts....46
Table 27: Use of info to navigate through the shock/hazard .......................................................................47
Table 28: Use of info to navigate through the shock/hazard across livelihood zones .................................47
Table 29: Extend of preparedness upon receiving the info .........................................................................48
Table 30: Extend of preparedness upon receiving the info .........................................................................48
Table 31: Severity of effect of hazard on primary livelihood .......................................................................49
Table 32: Extent of community recovery from effects of the shocks/hazards.............................................49
Table 33: Likelihood of Beneficiary providing support or help to the community across livelihood zones .51
Table 34: Likelihood of community providing support or help to the Beneficiary across livelihood zones .51
Table 35: If you lost something of value, most people in this village would be honest enough to return it
to you across livelihood................................................................................................................................52
Table 36: Presence of contingency reserves at the community level ..........................................................52
Table 37: Access to financial services by the beneficiary communities .......................................................53
Table 38: Type of financial services..............................................................................................................54
Table 39: Effectiveness of the leaders/institutions in addressing issues related to livelihoods/shock risk
reduction (DRR)/conflict management/NRM...............................................................................................56
Table 40: household’s primary source of water during the Dry season.......................................................58
Table 41: Project staff from SomReP project respectful when working with beneficiaries ........................62
Table 42: Resilience and capacities across districts .....................................................................................65
Table 43: Poverty analysis across livelihood zones .....................................................................................67
Table 44: Poverty analysis across districts ...................................................................................................68
Table 45: SomReP participation in various multiple intervention ................................................................70
List of Figures
Figure 1: FCS across livelihood zones............................................................................................................14
Figure 2: Comparison of food consumption score 2017, 2019 and 2020 .....................................................15
Figure 3: Household Hunger Scale across project districts ...........................................................................17
Figure 4: Comparison of Household Hunger Scale 2017, 2019 and 2020 ....................................................17
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Figure 5: Comparison of Household Hunger Scale across livelihoods 2017, 2019 and 2020: .......................18
Figure 6: Average Household Dietary Diversity Score across livelihoods ......................................................20
Figure 7: Reduced Coping Strategy Index across livelihood zones ................................................................22
Figure 8: Reduced Coping Strategy Index 2015, 2017, 2019 and 2020 ........................................................23
Figure 9: Type of farming practiced across project districts ........................................................................32
Figure 10: Trainings provided on Good Agricultural Practices (GAPs) ..........................................................38
Figure 11: Primary livelihood affected by the hazard across livelihood zones.............................................49
Figure 12: Extent of recovery from effects of the shocks/hazards across livelihood zones.........................50
Figure 13: Type of contingency reserves at the community level................................................................53
Figure 14: Natural Resource Management (NRM)/Rangeland Committee across livelihood ......................57
Figure 15: Access to water all year round across livelihood zones ..............................................................58
Figure 16: Absorptive capacity across livelihood zones ...............................................................................63
Figure 17: Adaptive capacity across livelihood zones ..................................................................................64
Figure 18: Transformative capacity across livelihood zones .......................................................................64
Figure 19: Resilience Index across livelihood zones .....................................................................................65
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ACRONYMS AND ABBREVIATIONS
ACF Action Contre la Faim
ADRA Adventist Development and Relief Agency
ARM Annual Resilience Measurement
ASALs Arid and Semi Arid Lands
CbEWS Community-based Early Warning System
CFW Cash for Work
COOPI Cooperazione Internazionale
CRM Conflict Resolution Mechanism
DRC Danish Refugee Council
DRR Disaster Risk Reduction
EU European Union
EW/EA Early Warning/Early Action
EWS Early Warning System
FCS Food Consumption Score
FS&L Food Security and Livelihoods
GAP Good Agricultural Practices
HH Household
HHH Household Head
HHS Household Hunger Scale
HoA Horn of Africa
IDP Internally Displaced Person
IGA Income Generating Activity
ISFM Integrated Soil Fertility Management
IWM Integrated Weed Management
KII Key Informant Interviews
M&E Monitoring and Evaluation
MoA Ministry of Agriculture
NGO Non-Governmental Organization
NRM Natural Resources Management
ODK Open Data Kit
rCSI Reduced Coping Strategy Index
sCSI Simple Coping Strategy Index
SLA Sustainable Livelihoods Approach
SomReP Somali Resilience Program
STATA Data Analysis and Statistical Software
TVET Technical and Vocational Education and Training
UCT Unconditional Cash Transfer
USD US Dollar
VDC Village Development Committees
VSL Village Savings and Loans
VSLA Village Savings and Loans Associations
WFP World Food Programme
WV World Vision
Page | viii
EXECUTIVE SUMMARY
This is an external Annual Resilience Measurement study for Somalia Resilience Programme (SomReP).
The assessment aims to contribute to providing information on the progress made so far by the
programme in increasing the envisioned improvement of the resilience of chronically vulnerable
households among the pastoral, agro-pastoral, IDPs, urban and peri-urban dwellers as well as the fisher
folks. The programme seek to strengthen the adaptive capacity, absorptive capacity, natural
ecosystem health and strengthen the capacity of the civil society to manage natural resources, support
resilience of communalities and promote community learning, research and adoption of appropriate
production practices.
SomReP programme is funded by Danida, Sida, DFAT, SDC, and European Union/European Aid and
implemented by a team of International Non-Governmental Organizations led by WVS with the
Consortium members being COOPI, DRC ACF, ADRA, CARE and Oxfam. The Consortium members are
the main implementers in their lead regions with the coordination of WVS through the programmes
Steering Committee.
The methods used in the ARM evaluation included a literature review, household individual survey,
Key Informant Interviews (KII), Focus Group Discussions (FGD) and field observation with key
stakeholders, including project beneficiaries. During the assessment, the project plans were assessed
against the criteria of planned implementation strategy, activities suitability, expected impacts,
observed outcomes and sustainability of the interventions. In addition, key indicators were computed
including food security, resilience indexes and poverty. Finally, the assessment provides lessons
learned, conclusions, recommendations and way forward for better implementation of the planned
activities.
The implementation strategy planned by the consortium is adequate in achieving the outcomes of the
project intervention. The programs has fully benefited from partnerships with implementation being
done by partners working in areas of long experience and strong established working relationships
with the communities, and thus ease of acceptance and build up from their past intervention’s. The
planned use of beneficiary community and focus in diverse livelihood zones was an important
consideration for all the interventions. This has increased the acceptance and instilled ownership of
the project activities by the beneficiaries. The project has also been implemented through partnership
with relevant authorities, local government institutions at all levels ranging from national, regional and
districts administration. The ministries involved include the Ministry of Agriculture, Ministry of water,
Ministry of Environment/Forestry/Natural resources, with other partners from the community
representatives and stakeholders who have been adequately consulted.
The annual resilience measurement found that 43.8% of the entire responded are exposed to shocks
and hazard such as COVID 19, conflict and drought as well as Desert locusts and flood. A high level of
exposure is reported in Bossaso (86.5%), Luuq (85.4%), Afgooy (83.9%), Xudur (80.2%), while a low
level of exposure was reported in Lughaye, Eyl and Baidoa, with 4.8%, 8.8% and 15.7% respectively.
Page | ix
Male-headed households have had a higher exposure level as compared to their female-headed
household counterpart.
The findings on food consumption scores show a lower scores compared to the baseline which was at
76% Peri-Urban/ Urban to 47 %, 69% for IDPs to present 29.5% and 62% for Agro-Pastoral to 44.3%
in this assessment. On the other hand, the Household Hunger Scale for the project districts showed
that majority (73.2%) of the households have little or no hunger, with moderate hunger 24.4% and
severe hunger at 2.4%. There is an increase of HH with little or no hunger from 32% in 2017, 52% in
2019 and presently at 73.2%. Three out of the seventeen districts of SomReP were dominate by
households who are facing moderate hunger, this include Laas Caanood, Bossaso and Burao with
62.8%, 54.8% and 46.8% respectively. Other districts were all facing little to no hunger.
In addition, the survey found that 60% of the sampled households are within the medium Dietary
Diversity (DD) level. The average HHDDs score was 5.88 across the project area. Moreover, the average
score for the male-headed households was 6.03 while for female-headed households was 5.71. Most
of districts fall within medium DD and thus slightly having better diversity of food sources expect for
Hargeysa and Salahley and to some extend Burao where the majority reported to be having low DD
with 64.5%, 50% and 46.5% respectively. The study also reported 30.3% of the respondents in the
SomReP areas have little or no food insecurity across the areas. Majority of the HH are stressed (58%)
and only 11.7% are in crisis in regard to food security status. Majority of the districts are within the
category of phase 2 (stressed) except for Owdweyne, Hargeisa and Bossaso where the majority of
household fall under the little to no food insecurity with 81.3%, 64.5% and 47.1% respectively.
Overall, the average Absorptive capacity index was 21.4, while the adoptive capacity index was 34, the
transformative capacity index was also reported to be 29. On the other hand the overall resilience
index was 30. Furthermore, the absorptive capacity index was highest among pastoral communities
with an average of 23.7 followed by agro-pastoralists with 21.6. The lowest was among peri-urban and
urban population with 18. The average absorptive capacity index was 21.4. Similarly, the adaptive
capacity index was higher among agro-pastoralists followed by pastoralists while IDPs and peri-urban
population. The transformative capacity index was highest among agro-pastoralists (31) and pastoralist
(29) and lowest among IDPs (18). Likewise, agro-pastoral areas have the highest resilience index with
32, followed by pastoralists with 30. Peri-urban and IDPS had an average of 24 and 23 respectively.
To improve the absorptive capacity focus should be directed more to enhance animal health and water
projects as well as VSLA and cash for work. On the other hand, any improvement in adaptive capacity
index should be based on investment on NRM, crop production as well as TVET, VSLA, EWEA. Similar
to absorptive capacity, transformative capacity index is highly dependent on animal health and water
project, in addition to TVET, EWEA and NRM. The resilience index was linked predominantly to animal
health and water projects as well as NRM, TVET, crop production and VSLA. Key intervention emerged
across the indexes are mostly animal health and water projects among others.
The greatest lessons learned from the SomReP project is the use of community and partner’s
participation in the interventions selection, and implementation in the target project areas. This has
Page | x
enhanced the implementation and achievement of the outcomes. The project was planned on critical
need basis with consultations between partners, government and the community; this has enhanced
synergy by the implementing partners and reduced the past duplication of activities by different
partners. Notably also, the openness in communication between the partners and the beneficiaries is
a good lesson for future projects, with the reported complain and conflicts mitigation structures by
the project team fully in use by the beneficiaries. From this assessment, the future projects should
support more the livestock sector and agro-pastoralism to increase household livelihoods and food
security and incomes. The study also notes great potential for rain fed agriculture through proper
onsite water harvesting technologies and proper agronomic practices in many of the project areas, an
opportunity that will increase productivity if considered. Due to the vastness of the project areas,
continued support to reach the wider population and the communities should be considered for
support. Last, the programme should strengthen the post interventions implementation follow-up and
impact tracing from the training activities and document the contributions to livelihoods, food security
and resilience of the communities.
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SUMMARY FINDINGS OF KEY INDICATORS
Core indicators
Indicator ARM 2017 Results
Not computed
% households who are structurally non-poor [1] as measured
by stochastic and structural poverty. Not computed
Resilience index 1 32%
% of targeted households with little to no hunger as measured 54% (livelihood disaggr
by Household Hunger Scale was not computed)
SoI1: % of households having acceptable food consumption
scores (disaggregated by household head gender, and Not computed
vulnerability type)
SoI2: % of communities who report to utilize EWEA Not computed
information to make risk informed decisions (disaggregated
by livelihood zone)
SoI3: % increase in community asset score (disaggregated by
livelihood zone) in programme areas
So14: % of people in targeted districts (gender disaggregated) Not computed
who view local governments as accountable and responsive to Not computed
community priorities in providing equitable services and
promoting resilience interventions
So15: % of innovations piloted through SomRIL and adopted
for scale up
`
Outcome Indicators ARM 2017 R
Indicator
1 https://www.fsnnetwork.org/sites/default/files/Methodology_Guide_Nov201850
ARM 2019 Results ARM 2020 Results
Not computed 37.5%
Not computed 30
52% 73.20%
regation 63% (Peri-Urban/ Urban 80%, 44.9% (Peri-Urban/ Urban 47 %,
Pastoral49%, IDP 68% ,Agro- Pastoral 46.2%, IDP 29.5% ,Agro-
Pastoral 60%) Pastoral 44.3%)
12.5% (livelihood disaggregation 22.1% (Peri-Urban/ Urban 12.3%,
was not computed) Pastoral 18.5%, IDP 7.4%, Agro-
Pastoral 30.3%, Fisher-folk 33.3%)
HH 41 (Pastoral community 32, HH 24.3 (Peri-urban/urban 37,
Agro-pastoral community 42 Pastoral 23.7, IDP 9.1, Agro-pastoral
19.5, Fisher fork 8.2)
10.5% (Male 7.9%, Female 1.3%)/ 66.8% (Male 64.6%, Female 66.9)/
(Peri-Urban 10%, Pastoral 9%, Agro- (Peri-Urban/ Urban 67.4%, Pastoral
pastoral 18%, IDP=5% 63.3%, IDP 61.1%, Agro-Pastoral
64.6%, Fisher-folk 66.7%)
Not computed TBD
Results ARM 2019 Results ARM 2020Results
08.pdf
Page | xii
Io111: % of target households who have positive coping strategies as Not comput
measured by the reduced coping strategy index (rCSI) (disaggregated by
household head gender, vulnerability type, and livelihood zone).
Io211: % reduction in households who are in need of humanitarian Not comput
assistance during shocks and stress
Not comput
Io212: % increase in household incomes (data disaggregated by 15%
household head gender, vulnerability type, and livelihood zone).
Io213: % of the targeted populations with all year access to multi-use Not comput
water (for irrigation agricultural production & domestic use) as a result Not comput
of investment in large scale water infrastructure and small scale water Not comput
infrastructure disaggregated by men and women household head 20% (Gende
gender, vulnerability type and livelihood zones livelihood
Io214: #of hectares under soil and water conservation measures disaggregat
not comput
Io215: % of households experiencing yield improvements (by gender and Not comput
livelihood zone)
Io216; % Increase in yield per unit hectares
Io3I1: % of HHs engaging in multiple income generating activities as
measured by participation index[1]. (disaggregated by household head
gender, vulnerability type, and livelihood zone)
Io3I2: % increase in household asset diversification score (disaggregated
by household head gender, vulnerability type, and livelihood zone)
Io313: % increase in households who realize improved profit gains from Not comput
their sales
Io314: % increase in households who reports easy access to markets Not comput
Io315: % increase in households who report improved $ sales volume per Not comput
season Not comput
Io316: % increase in households who have access to formal financial
services (e.g. those able to open accounts /access loans from formal Not comput
banks, mobile money providers)
Io317: % point increase in proportion of women that engage in jobs in
sectors of sustainable livelihoods (diversified production related
incomes) and economic growth (business development services like
transport, milling, bulking, and input supply)
ted 60% ( Peri-Urban/ Urban 30.3% ( Peri-Urban/ Urban (28.0%)
(75%) Pastoral (85%) IDP Pastoral (27.3%) IDP (30.5%) Agro-Pastoral
(68%) Agro-Pastoral (69%) (33.5%) Fisher-folk (0.0%)), (Male (31.9%),
Female (28.5%))
ted Not computed 26.80%
ted Not computed N: 2700 Minimum 0.0, Maximum 5,245,
60% Mean 140.4522, Std. Deviation 263.09463
77.50%
ted 5 Hectare 28.9 Hectare
ted
ted 40% (Gender disaggregation 28.3% (Male 31.3%, Female 23.7%)
er and was not computed) Not computed
tion was Not computed
ted)
ted 35.3% (Gender and 40.1% (Male 41.8% Female 38.1%), (Agro-
livelihood disaggregation was Pastoral 44.7%, Pastoral 31.6%, Fisher-folk
ted not computed) (0.0%), IDP 35.8%, Peri-Urban/ Urban
42.6%)
ted HH 41 (Pastoral community 24.3 (Peri-urban/urban 37, Pastoral 23.7,
32, Agro-pastoral community IDP 9.1, Agro-pastoral 19.5, Fisher fork
42 8.2)
Not computed 63.9% (Agro-Pastoral 76.3%, Fisher-folk
66.7%, IDP, 35.8%, Pastoral 68%, Peri-
Not computed Urban/ Urban 36.6%), (female 68.6%,
58.6%)
66.5
ted Not computed 63.90%
ted Not computed 36.40%
ted Not computed 56.50%
Page | xiii
Io411: Extent to which targeted communities are satisfied with delivery Not comput
of basic services by local government (measured on a scale from 1 to 5) Not comput
Io412: % increase of participation of women and other disadvantaged
groups in decision-making at the district level in the determination of
development priorities and CAAP financing
Io5I1. Extent to which local government annual development plans have Not comput
incorporated priorities from communities identified through CAAPS Not comput
(Measured on a scale from 1 to 5)
Io5I2. . % of the targeted government staff who are able to lead CAAPs
monitoring and evaluation processes at community level (PMERL)
ted Not computed 3 (64.8%)
ted Not computed
46.2% Women, 37.4% of disabled
ted Not computed household head (Peri-Urban/ Urban
ted Not computed 45.4%, Pastoral 54.9%, IDP 23.2%, Agro-
Pastoral 45.7%, Fisher-folk 66.7%)
Not computed
42.90%
Page | xiv
1.0 INTRODUCTION
The Somali Resilience Programme (SomReP) was designed to effectively mitigate the effects of
recurrent shocks and stressors and alleviating the chronic vulnerability among pastoralists, agro-
pastoralists, and peri-urban households across Somalia. The programme addresses communities’
unique needs by building resilient livelihoods. Limited alternative livelihood opportunities through
agriculture or other employment has resulted in higher poverty rates making it one of the most
vulnerable regions. The programme is managed largely by a consortium of seven international NGOs
namely Action Against Hunger (AAH), the Adventist Development and Relief Agency International
(ADRA), Cooperative Assistance for Relief Everywhere (CARE), Cooperazione Internazionale (COOPI),
Danish Refugee Council (DRC), Oxfam and World Vision Somalia. The long-term consortium is managed
by World Vision Somalia where a steering committee guide the implementation processes. The
SomReP receive funding from Danida, Sida, DFAT, SDC, and European Union/European Aid.
Generally, the Programme contributes to the resilience of vulnerable communities in Somalia by
bringing communities at the center of cross-border policy and investment discourse and actions; not
only as beneficiaries but also as key stakeholders defining the agenda of their future. To achieve this,
SomReP programming supports resilience through:
a) Livelihoods & food security: HHs in targeted communities have improved access to productive
livelihoods for enhanced food access and diversity;
b) Social Safety Nets: HHs in target communities have their livelihoods and assets protected
during shocks and stressors through the establishment and strengthening of social safety nets,
including the use of crisis modifier mechanisms such as Savings Group Schemes;
c) Natural resource management: Eco–system health improved through promotion of equitable
and sustainable natural resource management;
d) Local governance capacity building: Communities, civil society and local institutions are better
equipped with resilience strategies and response capacities to cope with recurrent shocks and
stressors.
The program targeted 83,694 households and was implemented in the districts of: Belet Xaawo,
Dollow, Luuq, El Barde, Odweyne, Baidoa, Badhan, Bossaso, Burao, Eyl, Hargeisa, Lughaya, Rabdhure,
Afgooye, Dinsor, Waajid, Xudur, Laas Caanood, Salahley and Qansadhere. The implementation of the
above intervention was expected to eventually result in positive changes in well-being indicators,
which implicitly is indicative of enhanced adaptive, absorptive and transformative capacity as
ultimately the resilience status of the beneficiaries. This is thought to be delivered through key
interventions comprising animal health, cash for work, crop production, early warning early action,
natural resource management, Technical and Vocational Education and Training (TVET), Village Saving
and Loan Associations (VSLA) and water projects. In addition, to active engagement with government
agencies at national, regional and district levels in order to mainstream SomReP approach,
interventions and lasting impact.
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2.0 ASSESSMENT SCOPE AND OBJECTIVES
The scope and focus of the SomReP ARM study was to explore the outcomes and impact of the
programme, in order to facilitate an understanding amongst the consortium and stakeholders and
measuring the extent to which the envisaged change within the program design has been realized.
Specifically, the assessment aimed to:
a) Assess the relevance, and effectiveness of the program strategies and interventions in relation
to the context and the programme strategic framework, documenting the lessons learnt and
best practices to inform future programming;
b) Establish the extent to which the programme achieved its purpose and delivered on intended
outputs, and whether the intended outcomes were met in relation to resilience programming;
c) Assess the impact of the programme with particular focus on establishing changes that have
occurred as measured by resilience and wellbeing indicators (provided for in SomReP master
logical framework) - food security and coping strategies indicators (i.e. HHS, FCS, rCSI, and
HDDS), ownership of household and community productive assets (climate sensitive and non-
climate sensitive assets), income and expenditures among others; and
d) Assess sustainability of the project interventions beyond donor funding.
e) Assess the effectiveness and efficiency of programme interventions in strengthening the
response capacity of various shocks and stresses including COVID-19 effects, Desert Locust,
Conflict and Floods.
Page | 2
3.0 ASSESSMENT APPROACH AND METHODS
3.1 Study Design
A combination of information gathering and analysis techniques was used for undertaking the
assignment. The data collection, analysis and writing of the report were guided by the following
criteria:
1. Voice and inclusion of the project beneficiaries.
2. Appropriateness of the methods and techniques in collecting the required data to answer the
assessment questions.
3. Triangulation to ensure various perspectives are captured and mixed methods and techniques
are used in the data collection.
4. Contribution was assessed by focus on showing what change happened and providing a clear
explanation of how the change happened.
5. Transparency in terms of methods used, limitation of the methods and challenges with the
process and a reflection of the same in this final assessment report.
3.2 Sampling
The assessment used non-experimental pre-test and post-test research to measure the causal changes
brought about by the programme allowing for comparison of resilience and wellbeing outcomes.
Random sampling was used for the household quantitative survey to ensure that all subjects of the
population get an equal opportunity to be selected as respondents. For the qualitative data, a
purposive sampling method was used to select study respondents, based on the role they played in
the programme. The quantitative data collection targeted households in the selected project areas
who participated in the programme. The methodology was designed to collect data from household
heads or their spouses, based on the demographic, socio-economic characteristics of the households
and determine achievement against response performance indicators.
3.3 Data collection
The assessment involved a holistic approach in assessing all the implemented activities. The study
employed participatory assessment techniques to gather both quantitative and qualitative data. The
methods used were; literature review, household survey questionnaire, focus group discussion (FGDs),
key informant interviews (KII), observation and project activity audit.
The Quantitative Primary data collection was done using a structured household questionnaire
programmed into mobile data collection application. The qualitative data collection was done from
target key stakeholders of the programme and the information gathered were used to supplement
and triangulate the quantitative data collected from the household interview.
Page | 3
Secondary data and information was assessed from existing relevant documents and publications held
by SomReP Consortium members particularly the Technical Unit (TU) and other partners and sources.
The data collection process used in the study is described below.
3.3.1 Literature Review
Secondary data was gathered from various sources in addition to what has been shared by the project
team which include; annual reports, past concluded Annual Resilience Measurement report, project
log-frame & theory of change, annual and mid-term project evaluation reports were also evaluated.
Relevant district level reports and documents for background information and establishing the socio-
economic context in which the project took place were also collected from the relevant institutions.
The review focused also on other relevant sources of information including the Food Security and
Nutrition Analysis Unit for Somalia (FSNAU)-FSNAU-FEWS NET Food Security and Nutrition reports and
publications for the region and Somalia. These documents were assessed and used to interpret the
project implementation and impacts during the assessment.
3.3.2 Household Survey
Semi-structured questionnaire was developed to capture all the pertinent sections of the project
activities with the consideration of all the inputs from the SomReP project staff and project partners.
The tool was arranged into different thematic areas, including sections that gather relevant project
information at the household level this include household demographics, agriculture, income and
expenditure, food security, access to various aspect of support, NRM, conflict and level of community
engagement and satisfaction to help establish baseline values for new indicators and comparison
values for already existing indicators. The tool was thereafter coded and loaded into KOBOToolbox.
The assessment was conducted across 17 project districts in Somalia. The project participants were
used as the sampling frame. For quantitative survey, a random sampling technique was used to sample
direct beneficiaries of the SomReP program. To determine the sample size for quantitative survey,
three important statistical parameters were considered: the survey’s margin of error, response
distribution and confidence level. A margin of error of 8% and confidence interval of 95% were used
to arrive at the total number of respondents per district. The sample size was determined using the
formula below given by Krejcie and Smith19792. As follow:
2 (1 − )
= 2( − 1) + 2 (1 − )
X2 = the table value of chi-square for 1 degree of freedom at the desired confidence level (3.841)
N = the population size
2 Krejcie, R. V. and D. W. Smith. (1970). Determining Sample Size for Research Activities. Educational and
Psychological Measurement. Vol 30, Issue 3. Pp. 607-610. Sage Publications Inc.
Page | 4
P = the population proportion (assumed to be .50 since this would provide the maximum sample size).
d = the degree of accuracy expressed as a proportion (.08).
The sampling process will be a mixture of purposive and random sampling. The team targeted all the
17-project district since this was pre-determined by the ToR and detailed in the project proposal. The
number of households to be interviewed per district and per livelihood zone was subjected to the
following parameters
1. CF 95%
2. ME 8%
3. RD 73%
Using the pre-calculated tables of the same formula and a target population of 83,694 the total sample
size was 3,164 household across the 17 districts3. This includes Las Canood (199), Odweyne (154), El
Barde (287), Eyl (209), Dollow (340), Badhan (304), Beled Hawa (196), Luuq (75), Baidoa (276), Afgoye
(118), Xudur (114), Hargeisa (101), Lughaya (262), Burco (305), Bossaso (108), and Ceel Afweyne (116).
3.3.3 Key Informant Interviews
Key Informant Interviews were conducted with key project staff, key leaders from the community
groups/partners involved in project implementation, representatives for implementing Partners, local
administration officers and government departments involved in project implementation. A checklist
of issues pertinent to the project, particularly community participation, project implementation
strategy, project relevance, effectiveness and efficiency, as well as project impacts, sustainability and
gender inclusivity was be developed and used4. Key question guides were used as presented in Annex
3.
3.3.4 Focus Group Discussions
This was used to gather evidence in support of project relevance, effectiveness, efficiency, impact and
sustainability. This was used to enrich the understanding of the change and its significance, the
collaboration of others, and the contribution of the project. Focus Group Discussions with the
community project beneficiaries was conducted in the project sites. The FGDs meetings were held with
community groups and committees in areas of natural resource management, early warning
committees, social affairs, village development, VSLAS among others. The meetings considered
inclusivity of all gender groups (adult women, adult men, youth girls and boys where appropriate). The
FGDs were done with adherence to all the COVID 19 prevention protocols including all participants
were healthy and not sick in anyway, all wearing masks and the meetings provided hand sanitizers and
ensured social distancing during the interactions. All the FGDs had a max number of participants
between 8-10 respondents. During the discussions, checklists of key questions were used Annex 3.
3 See annex 1 for the number of household per district and per livelihood zone.
4 See Annex 3 for the list of key Informant (KI) interviewed.
Page | 5
3.3.5 Field Observations and Project Activity Audit
The assessment team visited a cross-section of project field sites/ groups (randomly selected) to assess
project interventions implemented. This was done after conducting the FGD to make the link between
the infrastructure and the meetings outcomes. The observation included water infrastructure, power
energy infrastructure, agricultural infrastructure and health infrastructure. Among the factors to
consider during the visits was infrastructure operation and condition, present management and use,
maintenance plan by the communities, a site discussion on how the community are benefiting from
the infrastructure, any challenges facing the management and use and how that can be addressed by
the program or community. In addition, detailed audit of implemented activities was made through
scoring of the project targets to date as outlined in the project logical framework and outlined in the
terms of reference using information collected from the interviews within the community, project
partner’s reports, key stakeholders and quarterly, midterm and annual project reports5.
3.4 Data Analysis and Reporting
Data analysis involved the identification of patterns and processes among clusters of outcomes, and
key project deliverables. Data from semi-structured questionnaire was subjected to SPSS and Stata for
detailed analysis. The data analysis primarily targeted to measure progress across all project indicators
using variety of analytical technique. These techniques include descriptive statistics and generation of
means as well as computing various indexes to enable measure and assess progress against log-frame
indicators. The analysis includes computation of Resilience Index6 (Adaptive capacity index, absorptive
capacity index and transformation index as well as resilience index) as well as food security index7,8,
which comprise Food Consumption Score (FCS), Household Hunger Scale, Household Dietary Diversity
Score (HDDS), Reduced Coping Strategies Index (rCSI). The food security analysis was guided by the
Food and Nutrition Security Conceptual Framework to ensure that food security is measured across
the individual, household and at community levels.
Other index measured included the participation index9 to measure the change of percentage in
households engaging in multiple income generating activities. All the analysis was disaggregated by
household head gender, vulnerability type, and livelihood zone where appropriate. The assessment
also used stochastic and structural poverty measurement to measure the percentage of households
who are structurally non-poor. Other indictors in the log-frame were directly extracted/computed
from the data collected from the Household Survey.
Data from FGDs and KIIs (Qualitative data) were used to complement the data from the household
interviews as well as aid in extractions of quotes used in shaping the case studies/success stories across
5 See Annex 4 for the observation guide
6 https://www.fsnnetwork.org/sites/default/files/Methodology_Guide_Nov2018508.pdf
7 https://fscluster.org/handbook/assets/images/project/FSL%20Indicator_handbook_17.03.2020.pdf
8 https://documents.wfp.org/stellent/groups/public/documents/manual_guide_proced/wfp271449.pdf
9 http://www.fao.org/fileadmin/user_upload/riga/pdf/ai197e00.pdf
Page | 6
the various intervention and geographical locations. Given the limited time and resources, a
comprehensive qualitative data analysis was not attainable.
The analysis results from the assessment are presented in the most appropriate format to allow
comparison and measure of change or impacts from the baseline and other assessment done
throughout the program. The report provides stories and quotes from the programme activities that
provide outstanding impacts.
3.5 Ethical Considerations
In carrying out the Annual Resilience Measurement for the SomReP, the following guideline and ethical
consideration were provided by the humanitarian standard and those of SomReP implementing
partners and donors at all levels of the exercise were followed. This includes:
1. Do no harm principles were applied throughout the processes. This was critical to ensure and
observe human rights, respect, diversity and cultural sensitivity as well as child rights. This was
applied during the site visits for all interventions during the assessment.
2. The evaluation team ensured all the relevant authorities in the project areas were aware of
the assignment and all the laid down government process and procedures adhered to in the
process.
3. We ensured accuracy, reliability, sound application of research methods and high quality
control in all aspects. This was done by thorough and continuous consultation with the
research team and close monitoring of all processes.
4. The participation in the data collection and information provision was a participatory and
voluntary and free from external pressure. This was done by clearly seeking the respondent
consent after explaining what we intended to achieve and how the response will help in design
better interventions for their benefit.
5. Confidentiality of information, privacy and anonymity of study participants was assured. This
was done by clearly declaring to them the respect, the right of institutions and individuals to
provide information in confidence and ensure that sensitive data will solely be for the task and
will not be shared for other purposes and their source is confidential.
6. Honesty, integrity and accountability were key ethical considerations that guided the
assessments processes.
7. The safety of all respondents was ensured following all the control measures and protocols of
the COVID 19 Pandemic.
3.6 Limitations of the Study
The study was faced with some limitation, this include:
1. During the evaluation, being an election year with political impacts, some areas were not safe
for collection the information. The teams were very flexible and worked at convenient times
Page | 7
for data collections with guidance of field teams from the partner organizations and the
security team also supported the process.
2. Time needed to reach out to all the areas and security was also a major limitation to
assessment processes. This was addressed by working closely with the local partner and also
the consulting team was very flexible with field plans.
3. The capacity of the enumerators was also a limitation for the study but this was addressed by
provision of intensive training on the tools and the exercise as well as close monitoring of the
data collection process.
Page | 8
4.0 PROJECT AREA MAP
Page | 9
5. FINDINGS AND DISCUSSIONS
This chapter presents the Annual Resilience Measurement (ARM) survey findings presented in tables
and figures based on the analysis of quantitative data and corroborated with the analysis of the
qualitative findings. The chapter discusses the results and the implications to the project based on
progress so far in a quest towards resilient communities among the SomReP beneficiaries. The
conclusions are thereafter drawn from the findings. All the findings are presented as statements of
facts that are based on analysis of the data and the survey findings focusing on the key ARM
assessment questions and thereafter the key indicators.
5.1 Demographic Characteristics
The household heads respondent in the Survey was represented by 47.1% female and 52.9% male.
The average age of the household head was 43 (Std. Deviation 12.923) years. The majority of the
household head (85.7%) are in the category of 18 – 55 years of age, while 14.2% of the household
heads are in the category of above 55 years of age. Whereas the married household heads represented
67.0%. The average household size was four members. This is an indication unlike in the past where
men dominated as household heads; women are increasingly taking the roles of household heads in
the project areas. This has implication on the need to increase interventions that also empower
women as leads in the community. The ARM 2019 indicated a similar finding where the 60% of the
respondents were women. We also know the women are responsible in making some major decision
on food security, household dietary diversity and hence should be well represented in any food
security income generation activates interventions. Most of the HH had only attained the Qur'anic
School as the highest level of education (55.9%) followed by majority who had no any formal education
28.6%. Among the HH only 11% had primary education and 3.5% with secondary level (Table 1).
Table 1: Education level of the HH head across programme districts
Level of education Frequency Percentage
Certificate, Diploma, Vocational Accreditation 3 0.1
Master's Degree or Doctorate 3 0.1
Bachelor's Degree or equivalent 14 0.5
Secondary School Diploma 99 3.5
Primary School Diploma 318 11.3
No formal education 805 28.6
Qur'anic School 1574 55.9
Total 2816 100
Source: Assessment Survey
Furthermore the study found that about 49.4% of the male-headed households having attended only
Qur’anic School level of education while their female headed household’s counterpart was 63.3%
attended Qur'anic School. A similar trend was observed across livelihood zones where the majorities
were having Qur'anic School education with 51.3%, 65.1%, IDPs 62.1% and 51.8% for peri-urban,
pastoral, IDPs and agro-pastoral for males and females respectively. Qur'anic School education and no
formal education categories were dominant across all the districts expect for Bossaso, Hargeysa, Luuq
Page | 10
and Salahley where 41.3%, 37.1%, 26.7% and 23.3% of the respondents indicated that they have
attained primary educations10.
These findings represent major challenges facing many pastoral communities in the Horn of Africa. The
education level of HHH is still low and this may reduce the adoption levels of technologies that seek to
adapt them to the changing climatic condition11. This is evidence as indicated by the disaggregated
data across the project districts. However, we noted that for increased benefits of any interventions,
the use of Quranic schools as part of the extension avenue may increase benefits to the communities
in the project areas. The level of education also demands the extension approaches to be done in the
local languages and should be as practical as possible for increase adoption.
5.2 Effectiveness of SomReP Programme
5.2.1 Income and Livelihood
The SomReP programme aimed to strengthen the communities’ capacity to the changing climatic
conditions, reduce vulnerability of the household to climate related shocks as well as working towards
increased food and nutritional security. The approach to achieving these result areas was community
capacity enhancement in GAP, animal husbandry, dryland farming, animal health management,
community savings and access to credit, community early warning, preparedness, and interventions
that increase livelihood diversifications. The outcome was to increase household income and diversify
the livelihoods. The survey noted household to be making an average income of 140.5 USD across the
17 districts within six months. The survey also notes that agricultural crops income includes sales of
sorghum, maize, melon, onion and vegetables among other crops while the major Agriculture Livestock
incomes for the communities comes from the sales of Goats and Sheep. We noted that being a
dominant pastoral community, livestock was still the main source of livelihood and income ?2). We
also noted that there has been an improvement on incomes from farming activities where past annual
resilience measurement had 14% in 2017, 21% in 2019 and the present 2020 noting 25%. Non-farm
related business accounted for 13.8%. These findings further show that the need to support livestock
and agriculture activities contributes to household incomes. SomReP consortium identified these
activities as critical for increasing community resilience in the project areas, which was also reported
by the communities during the FGDs and KIIs.
Table 2: Main source of income across programme districts Percentage
Source 3.1
3.4
Agriculture wage employment 10.1
Agriculture related business 13.8
Non-farm wage employment 17.0
Non-farm related business
Transfers
10 For district-based analysis refer to annex 2
11 Mahamoud Habane, M. (2017). Factors Affecting Adoption of Improved Bread Wheat Varieties by Smallholder
Farmers in Awbare District, Somali Regional State, Ethiopia (Doctoral Dissertation, Haramaya University).
Page | 11
Agriculture crops 25.3
Agriculture livestock 47.3
Source: Assessment Survey
The source of income was further disaggregated by gender and districts across the project areas. The
dominant source of income among the male-headed households were agriculture livestock (48%)
agriculture crop (30.3%), transfer (14), non-farm related business (12.4%) and non-farm wage
employment (11.7%). On the other hand, the dominant source of income among the female-headed
households were agriculture livestock (46.5%) agriculture crop (19.8%), transfer (20.4) and non-farm
related business (15.5%). Agriculture livestock was the dominant source of income for peri-urban and
pastoral with 32.5% and 64.7% respectively. While agro-pastoral drives their income from agriculture
crops (48%) and agriculture livestock (44.5%). IDPS indicated that their income comes majorly from
transfer (30%) and agriculture livestock (29.5%). Similar to the livelihood zones the main source across
most of the district are agriculture crops and livestock with an exception of Baidoa and Lughaye where
the dominant source of income is transfer with 43.4% and 50.9% respectively. On the other hand, non-
farm related business was the major source of income across Salahley (50%), Luuq (46.7%) Hargeysa
(45.2%) and Xudur (36.6%)12.
The findings show 40.1 % of the households are engaging in multiple income generating activities with
the proportion for Male household headed having 41.8% and Female 38.1%. The highest adoption of
multiple source of income was found in Baidoa (69.3%) while the lowest was found in Hargeysa (1.6%).
Other districts with fewer households reporting to have multiple incomes include Lughaye (16.2%) and
Ceel Afweyne (16.7%). Out of the 17 districts there were nine district with 50% and above reported to
have multiple income sources.
When this is measured by participation index disaggregated by livelihood zone, it is noted that 44.7%
of pastoral are engaged in multiple livelihoods, 35% of IDPs and 31.6% of Pastoral households as shown
in Table 3. Agro- pastoral households seem to have diversified their income sources from the
integration of crops and livestock keeping. Dryland farming that has been known to be one of the
means that agro-pastoralists use to adapt to the changing climatic conditions is most embraced by
pastoral dropouts, most who were reported to have been devastated by livestock losses during
droughts. The study noted 56.5% of women are engaged in livelihood options that support sustainable
livelihoods with diversified incomes to areas like kitchen gardens, transport, milk bulking and inputs
supply to farming and livestock as reported by FGDs in Las-caanod and Oodwayne Districts.
Table 3: Adoption of multiple source of income across the livelihoods zones Percentage
Livelihood zone 00.0
31.6
Fisher-folk 35.8
Pastoral 42.6
IDPs
Peri-urban/urban
12 For livelihood and district based analysis refer to annex 2
Page | 12
Agro-pastoral 44.7
Source: Assessment Survey
The economic investments and engagement into business by women in value chains that support
agriculture in a sustainable way is also supportive to the SomReP program vision of incomes
diversification. The study finds a strong support by VSLAs in enabling the women diversify into other
livelihood options. This was noted in Owdweyne and Beerato areas where VSLAs groups were saving
and re-investing in farming activities as a group, where cash crops (Onion, Tomatoes, watermelon,
chilies and green paper) were observed within the group farms. The households reported this to have
increased their household food and nutritional security, with also being an important source of
income.
5.2.2 Food security
This section presents the findings of food security analysis. This is based on the four key indicators as
stated in the SomReP Logical framework. The indicators include food consumption score, household
hunger scale, and household dietary diversity score and reduced coping strategy index. The section
further linked selected food security indicators to the SomReP intervention in order to determine the
contribution and the direction of the relationship to guide future programming.
5.2.2.1 Food Consumption Score (FCS)
The Food consumption score (FCS) is a score calculated using the frequency of consumption of
different food groups consumed by a household during the 7 days before the survey13. Households
were asked to recall the foods they consumed in the previous seven day on the day of household
survey. Using the WFP (2008) the standard Food Groups and Standard weights, the types of foods
were categorized as a basis of conducting the FCS analysis in which a calculated profile of 0-28 was
considered to be poor; and in the range of 28.1-42 was considered to be borderline while above 42
was considered to be acceptable. The findings also indicate that 44.9% of the HH in the study area are
having acceptable FCS, while 34.6% are at the borderline and 20.6% are poor. This shows the majority
of the study populations are having acceptable food consumption score as the result of adequate food
intake, which is attributed to increased productivity and diversity of food stuff at household level.
The FCS is further disaggregated by gender; we found that the majority of both male-headed
households and female-headed households are having an acceptable FCS with 46% and 43.7%
respectively. Similarly, those within the borderline are 34.4% male-headed households and 34.8%
female-headed households. The survey reveals that there is an improvement on households who have
acceptable food consumption score for pastoral livelihoods with baseline being 34% and presently
46.2% (Figure 1). The other livelihoods have lower food consumption scores compared to the baseline
13 https://www.wfp.org/publications/meta-data-food-consumption-score-fcs-indicator
Page | 13
whereas 76% Peri-Urban/ Urban to 47 %, 69% for IDPs to present 29.5% and 62% for Agro-Pastoral to
44.3% in this assessment.
80 46.2 66.7 50.5 47
33.3
70 31.9 29.5 29.8
22 20 23.1
60
0
50 44.3
40 37.4 Pastoral Fisher-folk IDPs Peri-urban/urban
Borderline (%)
30
20 18
10
0
Agro-pastoral
Poor (%) Acceptable (%)
Figure 1: FCS across livelihood zones
Source: Assessment Survey
This is a worrying trend that indicates the households are presently worse off than during the baseline,
a situation reported during GGDs to have been due to the present COVID 19 impacts and the last
droughts that affected the productivity and the economic activities by the communities. This was
reported during the FGDs and KII where communities reported there was reduced food supply during
the period of COVID, maybe due to fear and movement restrictions across the borders. Thus, the
SomReP targets may have been negatively impacted in terms of gains made. When these figures are
compared to The ARM 2019, we see that pastoral HH who also had acceptable FCS with proportion of
49%, indicating a decline in the ARM 2020. Therefore, we see households have shown a declining FCS
across all the livelihood zones.
Across the districts the majority of the household fall under the acceptable food consumption score
which include, Owdweyne (76.8%), Ceel Barde (67.7%), Ceel Afweyne (63.3%), Eyl (57.7%), Lughaye
(57.5%), Laas Caanood (49.7%), Bossaso (48.1%), Afgooye (43.2%), Baidoa (39.4%) and Xudur (38.7%).
The other districts are mainly within the poor category with the highest in Hargeisa (100%), followed
by Salahley (93.3%), Luuq (68%), Belet Xaawo (53.5%), Dollow (49.9%) and Badhan (42.3%)14.
When we compare the FCS across the three periods i.e. 2017, 2019 and 2020 we noticed that the
percentage of households who have acceptable FCS are slightly less in 2020 (54%) as compared to
2019 (63%). The study also finds those who are at the borderline have increased from 13% to 35%,
while those who are poor have decreased from 24% to 12% as shown in Figure 2.
14 For district-based analysis refer to annex 2
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70.0% 63% 54%
60.0% 44.9%
50.0%
40.0% 34.6% 35%
30.0%
20.0% 24%
10.0% 20.5%
0.0% 13% 12%
Acceptable Borderline Poor
2020 2019 2017
Figure 2: Comparison of food consumption score 2017, 2019 and 2020
These findings were also elaborated during the KII and FGDs where communities reported the ongoing
dry periods during the assessment to have contributed to food insecurity. The communities also noted
that remittance, which has been an important part of their income source, had declined in the recent
past since COVID 19 challenges began, with reasons that even their relatives abroad were struggling
with life after job losses and slowed business opportunities. To this end, we see that the future support
amidst the pandemic will need a recovery strategy to support the resilience of the communities, since
we do not know when the pandemic will end. Thus, the project partners should work on strengthening
resilience of during the pandemic scenarios. During the discussion, the pastoral communities reported
even the trade in live animals had declined during the pandemic, which was attributed to slow down
in movement and this could have resulted in decline shipping of live animal though the Berbera port.
It was also reported that SomReP as a consortium has not given effort on supporting livestock trade
and value chain, except on the tremendous work on addressing animal health. The communities
requested this to be considered in the future, especially with trainings specifically for market linkages,
trade in livestock productions, value addition trainings through the Technical and Vocational Education
and Training (TVETs) as well as market infrastructure support like the sale yards equipped with loading
rumps, loading bays among others within community identified potential market areas. These were
the issue from Las-anod, Owdweyne -Gatiliilei areas.
From the field observations, FGDs and KIIs, the study also relates that areas that had activities relating
to agricultural support which included Good Agricultural Practices (GAP) trainings and water supply
support like Owdweyne, Cee barde showed positive response with most household reporting to have
acceptable FCS. This is attributed to the diversification of livelihoods opportunities brought about by
the supported agro-pastoralists by SomReP. When we compare this with highly pastoral livelihood
zones like Luuq, Belet Xaawo, and Salahley, most household reported to be in emergency or crisis
Page | 15
phase (borderline and poor). This clearly links to the highly fragile and vulnerable pastoral livelihood
most prone to the droughts and climate change impacts. During the assessment, the present situation
is dry season and this was reported to be increasing the severity of food insecurity among the
households. Most of these areas, livestock had migrated and the remaining families were depending
on savings, donor support or remittance. The discussions noted that these pastoral communities were
willing to engage in alternative livelihoods, but the options were limited, like some areas have serious
water access for multiple uses, and if this could be addressed, then the communities can diversify their
activities into farming.
The FCS correlate15 with most of the current interventions of SomReP. Weak correlations were
observed with animal health (0.1905*), crop production (0.1476*), TVET (0.1449*), water projects
(0.1140*), and EWEA (0.1106*). This indicate that in order to improve FCS particularly within the
districts where the majority of household fall within the poor category, there is need to invest more in
these significant correlating intervention, specifically in animal health and crop production as well as
other supporting interventions.
5.2.2.2 Household Hunger Scale (HHS)
The Household Hunger Scale is an individual indicator; it is a household food deprivation scale based
on the idea that the experience of household food deprivation causes predictable reactions that can
be captured by a survey and summarized in a scale16. To measure the food deprivation as part of the
food security assessment, the ARM used the Household Hunger scale.
The Household Hunger Scale for the project districts showed that majority (73.2%) of the households
have little or no hunger, with moderate hunger 24.4% and severe hunger at 2.4%. We noted that there
is an increase of HH with little or no hunger from 32% in 2017, 52% in 2019 and presently at 73.2%
(Figure 3). Further, there was a decline on household categorized as severe hunger from 6% in 2019
to 2.4 in 2020 (Figure 4). This positive changes based on this outcome indicator is attributed to increase
in food production and land productivity that the SomReP may have implemented in the project areas.
The communities are also presently better in terms of food security and hence an increase in
household nutrition. This could also be explained from the relatively better seasons in 2019/2020 with
regards to rainfall amounts in the Horn of Africa (IGAD 2020).
15 See Annex 4 for correlation matrix
16 https://www.spring-nutrition.org/sites/default/files/publications/tools/spring_context_assessment_tools_all.pdf
Page | 16
Severe hunger 2.4
Moderate hunger 24.4
Little to no hunger 73.2
0 10 20 30 40 50 60 70 80
Figure 3: Household Hunger Scale across project districts
Source: Assessment Survey
80 73.2 46 22
70 42 2.4 6
24.4
60 52 Severe hunger
50 Moderate hunger
2020 2019 2017
40 32
30
20
10
0
Little to no hunger
Figure 4: Comparison of Household Hunger Scale 2017, 2019 and 2020
Source: Assessment Survey
The Household hunger scale across the different livelihood zones shows that there has been
tremendous increase for all the livelihood zones. The change has been growing positive with
proportion with little or no hunger under Peri-urban changing from 2017 - 29%, 2019 – 56% and
presently 2020 68%. Similar trend observed in Pastoral with 2017-35%, 2019 57% and 2020 at 75%.
Agro pastoral has also seen an increase from 50% in 2019 to 73.3% in present 2020 ARM study. The
IDP HHS has also tremendously changed from 12% 2017, 43% in 2019 and now stands at 91%.
Page | 17
120
100 2.1 4 8 3.2 7 2.1 8 1.1 11
24.6 21.8 16 7.7
22
80
29.8 41
46 38 36 38
60 49 47
50
40 73.3 91.6
75 68 48
20 50 54 57 56 43
35 29
12
0
2020 2019 2017 2020 2019 2017 2020 2019 2017 2020 2019 2017
Agro-pastoral Pastoral Peri-urban/urban IDPs
Little to no hunger Moderate hunger Severe hunger
Figure 5: Comparison of Household Hunger Scale across livelihoods 2017, 2019 and 2020:
Source: Assessment Survey
The HHS was further disaggregated by districts and the same trend as livelihood zone was observed.
Three out of the seventeen districts of SomReP were dominate by households who are facing
moderate hunger, this include Laas Caanood, Bossaso and Burao with 62.8%, 54.8% and 46.8%
respectively. Other districts were all facing little to no hunger with Baidoa having the highest
percentage of households (98%) followed by Ceel Afweyne (97.7%) and Lughaye (97%)17.
The findings indicate 26.8% HH in the project areas are in need of humanitarian assistance at phase 3
crisis, 4 emergencies and 5 famines. Importantly, majority of the households (64.7%) are at the
minimal phase 1 of no hunger, an improvement from the baseline data that had 52%. This finding can
be attributed to the interventions that supported food production through dryland farming, income
generating activities, animal husbandry and health as well as income diversification by SomReP. The
programme was reported to have contributed a lot through GAP trainings that has seen households
engage in farming activities with increased food production. The communities had also received
trainings on postharvest handling, food and feed preservation that has increased their ability to
prepare for periods of deficits due to climatic challenges. Among the interventions was also early
warning and early action trainings that the community noted to be useful in preparing them for
predictable challenges and hence support their livelihoods better as reported during FGDs in
Oodwayne district.
These positive trends can be attributed to the interventions by the SomReP together with other
partner’s activities and programs in the project areas. When there is an increase in incomes,
17 For district-based analysis refer to annex 2
Page | 18
productivity and diversification of livelihoods, this trend is expected for the different livelihood zones.
However, we also noted that some household still reported severe hunger; these is attributed to the
vulnerable household that had lost their livelihoods from past droughts and are yet to recover from
the shocks. From the FGD meetings, it was reported in all the districts that some households are still
struggling to recover after losing all their livestock in the past drought periods, still with some areas
having IDPs who are also in need of humanitarian support. This study also only focused on SomReP
project beneficiates, which excluded others and whom we do know could be having more challenges
as reported during FGDs, that the scope of the programme should consider reaching wider areas and
support other villages beyond the present target areas.
5.2.2.3 Household Dietary Diversity Score (HDDS)
The Household Diversity Score (HDDS) measure household food access. To better reflect a quality diet,
the number of different food groups consumed is calculated, rather than the number of different foods
consumed. This measures the nutritional quality of the households. It is also used as a proxy measure
of the socio-economic status of the household18. This score range from 0 to 12 and divided equally
into three category, 0 – 4 low DD, 5 – 8 medium DD, and 9 – 12 High DD. The survey found that 60%
of the sampled households are within the medium DD, 26.2% low DD while 13.8% are with high DD.
The average HDDs score was 5.88 across the project area categorized as medium dietary diversity. On
the other hand, the average score for the male-headed households was 6.03 while for female-headed
households was 5.71. Furthermore, the average score across the livelihood zone is given in figure 6.
The highest score was peri-urban (6.73) while the lowest was for Fisher Fork (4). IDP average score was
5.93, while pastoral and agro-pastoral were 5.24 and 5.89 respectively as shown in Figure 6.
6.73 5.93 5.89 5.88
7
5.24 4
6 Pastoral
IDP Agro-Pastoral Fisher Fork Total Average
5
4
3
2
1
0
Peri-Urban/
Urban
18 https://www.spring-nutrition.org/sites/default/files/publications/tools/spring_context_assessment_tools_all.pdf
Page | 19
Figure 6: Average Household Dietary Diversity Score across livelihoods
Source: Assessment Survey
The findings shown majority of households across the livelihoods zones have medium DD with 64.1%,
60.8, 60% and 57% for pastoral, peri-urban, IDPs and agro-pastoral respectively. Highest livelihood
with high HDD (high DD) are peri-urban (20.7%) followed Agro-pastoral (16.1) and IDPs (14.7) as shown
in Table 7. This finding collaborates that peri-urban livelihoods may be having wider access to diverse
food sources based on urban life and access to markets. The pervious ARM did not computed HDDS
thus this make the baseline and should be compared during the future ARMs.
Table 4: Household Dietary Diversity Score across livelihood zones
HDDS socre Low DD Medium DD High DD
20.7
Peri-Urban/ Urban 18.5 60.8 5.2
Pastoral 30.8 64.1 14.7
IDP 25.3 60.0 16.1
Agro-Pastoral 27.0 57.0
Source: Assessment Survey
Looking at the HDDS across the districts, the study revealed that most districts falls within medium DD
and thus slightly having better diversity of food sources except for Hargeysa and Salahley and to some
extend Burao where the majority reported to be having low DD with 64.5%, 50% and 46.5%
respectively19. This is a clear indication that SomReP intervention are contributing better to the
household well-being. On the other hand, the districts with low DD require further attention and better
investment to move to better phases.
With the implementation of agricultural support activities and income generating activities as well as
focus on diversification of the production systems by SomReP, this moderate increase in HDDS was
realized. However, from the discussions with communities, it emerges that diversity of food sources is
only high during better seasons, but tremendously declines when dry and drought periods set in. The
communities noted that during favorable periods, there is better trade, better and stable income
sources as well as good prices for food commodities in the markets. From the finding, we still noted
that there is much need to improve on HDDS across all the districts since most are still below 60%.
This is a challenge that was also observed during the field study, with the present dry seasons
continuing, most households reported to have challenges in accessing diverse foods, except for the
few areas supported with farming activities. But, still, even the areas where farming is done, the water
is quickly depleting, and most farms have been affected with crop wilting and scale of production
reduced, and thus if the situations persist, the food sources are going to be further stressed. The case
example is Somaliland where Arapsio area and Owdwayne dam site farming areas dams and wells have
19 For district-based analysis refer to annex 2
Page | 20
dried and cropping activities greatly reduced. Gatiililey area has a dam without liner and already the
water has depleted, with cropping activities halted, presently eater trucking is only done for domestic
uses.
The communities in these areas are having diverse income sources from off farm activities and hence
able to buy foodstuff (mostly with more than 50% adoption of multi-source of income). Agro-
pastoralism as an integrated system may also have increased the HDDS than pastoralism with an
increase to crop products access and an added income from farming activities. The IDPs reported to
have access to food from the market, with some areas having IDPs engage in some level of Farming
like Ceel-Same farmers garden who are IDPs supported by community and SomReP programme with
individual farms. In addition, from the KII, most IDPs have some remittance support that allows them
access food from the market areas, and thus this could explain the observed HDDS. We also noted that
SomReP programme gave some special focus to IDPs especially with trainings and support that must
have contributed to livelihoods diversification.
5.2.2.4 Reduced Coping Strategy Index (rCSI)
This indicator is strategic in understanding the household coping strategies and behaviors when faced
with food crisis. The HH activities engaged in and behaviors will always determine their food security
status. Normally, the higher the rCSI score, the worse the level of food security. The rCSI score also
measures the impact of food security and coping strategy in programmes, and as an indicator of
impending food crisis. The tool can also be used as an indicator of food security at household level.
The study reports that 30.3% of the respondents in the SomReP areas have high coping strategies
across the areas. Majority of the HH are medium coping level (58%) and only 11.7% are in low coping
(Table 5). This result shows that majority of the HH at present still need interventions that can increase
their coping strategies to be food secure as envisioned in the SomReP Log-frame. There is needed to
increase the communities’ ability to employ the coping strategies that will enhance their food security
at Households level.
Table 5: Reduced Coping Strategy Index across project districts Percentage
rCSI 30.3
58.0
High Coping 11.7
Medium Coping 100.00
Low Coping
Total
Source: Assessment Survey
The rCSI across the livelihood zones (Figure 7) show that most of the household are still at the medium
coping phase 2, and 11.7% at low coping phase indicating that there is still much need for support to
communities to help increase their coping strategies to get them out of food insecurity at HH level.
When the rCSI for the household is compared with the 2017/2019 ARM, we that noted there has been
a decline in 2020, with low coiping phase leading compared to the two years where 2019 had over
Page | 21
60% of HH having little to no food insecurity. This could be attributed to the recent many climatic
impacts from droughts, locusts’ invasions and the recent pandemic from Covid 19. The impacts of this
may have left households with limited coping strategies that increase their food security, with the
much-reported decline in economic activities because of limited movements and decline on
international trade that may have affected trade.
120
100 13.6 5.3 12.2
9.2 54.3
80 33.5
Agro-Pastoral
60 62.8 59.1 64.2
40
20 27.3 30.5
28
Pastoral IDP
0 None Stressed Crisis - Catastrophe
Peri-Urban/ Urban
Figure 7: Reduced Coping Strategy Index across livelihood zones
Source: Assessment Survey
Looking across the years in regards to rCSI we found that the average index for 2020 (9.25) is more
than what was recorded in 2019 (8.77) (Figure 8). This indicates that the programme beneficiaries
demonstrate better coping strategies over years and are less food insecure. The slight increase in the
status of the food security for the beneficiary group’s could be attributed to the extent of involvement
of the households with the project. These strategies include, changing diet, increase their food
supplies using short-term strategies that are not sustainable over a long period (borrowing, or
purchasing on credit; more extreme examples are begging or consuming wild foods, or even seed
stocks), reduce the number of people that they have to feed by sending some of them elsewhere.
Fourth, and most common, households can attempt to manage the shortfall by rationing the food
available to the household.
Page | 22
18 16.57 11.4 8.77 9.25
16 2017 2019 2020
14
12
10
8
6
4
2
0
2015
Figure 8: Reduced Coping Strategy Index 2015, 2017, 2019 and 2020
Source: Assessment Survey
When we examine the reduced Coping Strategy index across the districts, we found that the majority
of the districts are still having low coping strategies20 except for Owdweyne, Hargeisa and Bossaso
where the majority of household are within the medium coping and high coping strategies with 81.3%,
64.5% and 47.1% respectively. Just like with the FCS and HDDS, we also see that regions that are more
of agro-pastorals seem to be medium coping level and hence minimal food stress as with the case of
Owdwayne and Hargeysa. Even though, the trends also show that most of the regions are still under
low coping strategies from the rCSI scores, with this probably a reflection of the prevailing dry seasons
in all the districts that has affected the productions systems both for crops and livestock keeping.
As much as the programme has supported the communities on adaption to shocks and contributed to
enhancing their resilience, the areas are vast, with most household being poor, and this has limited
the adoption of many useful technologies like farming technologies that can use the little available
water efficiently. The observation was that most are still doing canal irrigation within the water
deficient areas. Also, the support on animal health was an excellent intervention, but access to
sustainable services for all the regions is still a challenge, donor support has limits and the local
governments have not taken up this roles fully, with the little support by the programme ending up
being diluted over time, especially on how sustainable this interventions can be achieved. The
programme has really enhanced the capacity of farmers, but most of the farmers are asking for
continued support with inputs like seeds, fertilizer, drugs and health kits. Still also, it emerges that the
mobility that prevails during dry seasons also limits service delivery, since most of the people get
scattered in search for survival, and the few trained support teams cannot reach all the areas,
especially during prolonged dry seasons and droughts.
20 For district-based analysis refer to annex 2
Page | 23
Generally, the ARM 2020 showed that the food security situation was stable as measured by food
consumption score, household hunger scale, and household dietary diversity score and reduced coping
strategy index. This is with an exception of internally displaced persons and returnees without
sustainable livelihood strategies as they are somehow among the most food insecure groups. As
discussed in the above sections more is needed to be done to further improve the food security across
the livelihoods zones particularly the introduction of a district and livelihood based intervention to
ensure all the four aspects of the food security.
5.2.3 Household and community assets
The household assets are critical in determining the well-being and resilience of a household. This has
been critical in determining the resilience of a household and has been an important consideration
when looking at resilience frameworks. Assets have always provided a safety net and also as source
of income that helps communities to bounce back after shocks. When looking at the assets average
assets diversification score for this study, different types of assets: Financial, Natural Capital, Physical
Capital, and Social Capital were factored in the assessment. The study noted an average asset
diversification score of 24.3 for the HH in the whole project areas. The average asset score for male-
headed households was 13.8, while for the female headed households was 33.4. When this was
segregated per livelihood zone, we have Peri-urban/urban 37, Pastoral 23.7, IDP 9.1, and Agro-pastoral
19.5, and Fisher fork 8.2. The more diversified a household is, the higher the chances of being resilient
and adapt to shocks. We noted that the study shows that the peri-urban households were more
diversified in their assets than the IDPs and Fisher folks. Pastoral are the second followed by agro-
pastoral households. As expected, most of peri-urban are diversified, and most still have assets in the
rural set up and hence the observed higher values, with added advantage of business opportunities
still as well as urban lifestyle that increases the need to have more assets like cars, shops, TVs, bicycles
etc. Pastoral communities may have much of their assets in livestock with little other source of
investment to other asset types and hence the lower values compared to the agro-pastoralists. The
finding show that there is an increase in Average asset diversification score when livelihoods are
diversified.
Table 6 show that within the project areas, traditional houses (56.4%) are still common a clear
indication that the project areas are more of pastoral setup, with still low cost and adapted structures
preferred for shelter. We also noted that concrete private building is owned by 18.7 of the HH followed
by 16.1 who own the Galvanized iron sheet. The type of house indicates the social status and financial
wellbeing of the household. Concrete houses represent households who have better incomes and as
represented in these findings very few households are in this class.
Page | 24
Table 6: Type of dwelling across project districts Percentage
House Structure type
Concrete shared building 7.0
Galvanized iron sheet 16.1
Concrete private building 18.7
Traditional shelter 56.4
Others 1.9
Source: Assessment Survey
A similar trend was observed when comparing the overall type of dwelling with those disaggregated
by gender. Among the male headed households and female headed households the majority are using
traditional shelter with 53.1% and 52.3% respectively. This is followed by concrete private building
with 21% (male) and 19.4% (female) as shown in Table 7.
Table 7: Type of dwelling across gender Male (%) Female (%)
House Structure type 6.2 8.6
17.9 17.3
Concrete shared building 21 19.4
Galvanized iron sheet 53.1 52.3
Concrete private building 1.7 2.4
Traditional shelter
Others
Source: Assessment Survey
The findings also noted that across all the livelihood zones in the SomReP areas, livestock was still the
main assets owned with Goats being asset to 53.3% and sheep 18.8% of the household assets (Table
8). This is an indication that pastoralism is still the main economic activities in the study areas.
Importantly also, radio was owned by 13.5%, giving an indication that for communication of extension
service, the ownership is still low, though better than TV sets at 1%. Cattle was also lowly owned by
households, which indicates that small stocks are the most preferred livestock species, a situation than
could be attributed to the changing climatic conditions that affect feed resources, low capital needed
for starter stock and also ease of disposing for cash need at the household level.
Table 8: Assets ownership by household across districts Percentage
Asset 5.1
1.2
Automobile 1.1
Bicycles 13.7
Boats 6.9
Buul 3.7
Camel 8.3
Cattle 2.8
Donkey 0.1
Donkey Cart 0.6
Fish Ponds 0.2
Fruit Trees 53.3
Generator 0.2
Goats
Granary
Page | 25
Hard roof house 3
Horses 0.0
Jewellery 0.3
Kiosk 1.6
Motorbike 0.1
Oxen 1.0
Phones 29
Ploughs 0.1
Poultry 5.4
Radio 13.5
Seeds 1.9
Shed 0.1
Sheep 18.8
Solar Panels 0.7
Traditional House 11.7
TV 1.7
Water Pump 0.3
Wheelbarrow 4.4
Source: Assessment Survey
Asset ownership across the livelihood zones shows that Goats and Sheep were still the dominant assets
by households, this was also reported by Tempia eta al (2010). Interestingly, even within the peri-
urban and urban livelihood zones, the two still emerge as important assets by the households. This is
a confirmation that despite the urbanization and livelihoods diversification efforts, livestock keeping
activities are still the preference of the communities in Somalia (Table 9).
Table 9: Assets ownership across livelihood zones
Asset Peri-Urban/ Urban Pastoral IDP Agro-Pastoral (%) Fisher-folk
(%)
(%) (%) (%)
33.3
Automobile 4.1 1.4 8.4 7.7 0.0
0.0
Bicycles 2.6 0.8 3.2 0.6 0.0
0.0
Boats 1.1 0.5 1.1 1.5 0.0
0.0
Buul 14.6 14.9 11.6 12.8 0.0
0.0
Camel 5.2 6.2 8.4 7.9 0.0
0.0
Cattle 2.3 3.0 2.1 4.9 33.3
0.0
Donkey 8.9 5.4 14.7 9.4 0.0
0.0
Donkey Cart 2.0 2.4 3.2 3.4 0.0
0.0
Fish ponds 0.0 0.0 2.1 0.0 0.0
0.0
Fruit trees 0.3 0.1 8.4 0.4
Generator 0.3 0.0 0.0 0.3
Goats 45.9 63.3 23.2 52.5
Granary 0.2 0.1 0.0 0.2
Hard roof House 1.6 5.5 0.0 2.2
Jewelry 1.3 0.1 0.0 0.0
Kiosk 3.3 1.3 3.2 0.8
Motorbike 0.0 0.0 0.0 0.2
Phones 47.2 23.2 52.6 22.3
Ploughs 0.3 0.0 0.0 0.1
Page | 26
Poultry 9.2 2.2 8.4 5.5 0.0
Radio 26.4 8.5 13.7 10.7 0.0
Seeds 0.7 0.4 1.1 3.5 0.0
Shed 0.0 0.0 0.0 0.2 0.0
Sheep 16.4 22.8 7.4 18.3 0.0
Solar Panels 1.6 0.7 0.0 0.4 0.0
Traditional House 14.3 12.4 5.3 10.6 0.0
Oxen 0.5 0.2 0.0 1.9 0.0
TV 4.1 0.0 0.0 1.8 33.3
Water Pump 0.2 0.4 0.0 0.4 0.0
Wheelbarrow 10.2 2.5 9.5 2.6 0.0
Source: Assessment Survey
From the above results, interventions targeting at improving livelihoods and incomes, still need to
consider the livestock sector as an important component. The FGDs also noted a strong emphasis by
the communities with support in animal health, more training needs also with CAHWs as well as timely
and adequate supply of veterinary drugs. Technological development in communication seems to have
also impacted on communities’ livelihoods in the project areas where among all the assets, phones
have emerged to be the second assets owned across all the livelihood zones. This may have
revolutionized communications, increased ties and also economic activities from mobile money
transfers for business, remittance and also trade and marketing. Another important benefits from
mobile phone owners as reported during the FGDs was use in fodder and feed tracking during the dry
seasons. The communities also reported the provided phone by SomReP has also increased
communication with regards to EWEA communications by communities and committees.
5.2.4 Livestock Ownership
The study notes that 67.1% of the respondents across all the livelihood zones kept livestock, which is
an increase from the 21% reported by the ARM of 2019. We also not that 70.5% of the male-headed
household indicated to have livestock, while 63.3% of the female-headed household indicated to have
livestock as their assets. When livestock ownership is disaggregated per livelihood zones, we noted
that agro-pastoral and pastoral having over 70% of ownership (Table 10). Interestingly also, a
significant proportion of peri-urban HH own livestock. This could be an indication of strong ties to
pastoral way of life or an increasing peri-urban livestock keeping. The FGDs also reported that livestock
keeping is a fast and easier way to bounce back a household from food insecurity if situations change
and support provided to increase productivity.
Table 10: Livestock ownership across livelihood zones in the project areas
Livelihood zone Frequency Percentage
Pastoral 2236 79.4
Agro-pastoral 1994 70.8
Peri-urban/urban 1495 53.1
Fisher-folk 0 0.0
IDPs 0 0.0
Source: Assessment Survey
Page | 27
The communities commended the SomReP interventions on CAHWs as an important approach that
cushioned households from losses of livelihood options, and healthy animals had higher chances of
surviving the dry seasons and drought. They also noted a declining trend of losses from livestock
diseases, a trend achieved from the well-trained CAHW who have continued to support the
communities. However, the communities asked for further trainings, refresher training to CAHWs, with
need for support with animal health kits and drugs. From the field visits, CAHW has showed
tremendous success, with below a success story from one of the female beneficiary, surprising she has
found passion in male dominated areas in livestock health, thanks to SomReP empowering
intervention.
Page | 28
SUCCESS STORY
CAHW support in Yagoori Village
Miss Najma Abdi Hersi is a 22-year-old trained as CAHW by SomReP.
She was trained in January 2020 for 14 days.
SomReP provided the training and the required equipment and drugs. She was provided
with drugs twice by the programme. To date, she has treated and vaccinated around
200 camels, 460 sheep and 320 goats, this include various diseases that broke out in
the year 2020. She mostly does not charge any money as most of the clients are her
community members within the village and occasionally she only charges for the drug
used and not her services. She said- If someone bring like 2 camels, 6 sheep and 12
goats, I do my job and then they just give me what they feel like or have at that moment.
In her service delivery since training, she makes an average of 25USD profit after every
drug stock that she buys and currently she has about 180 dollars as capital for
repurchasing of the drugs she uses. She supports a family of four people (husband and
2 kids).
Najma notes the most challenges she faces include, some people not paying her for the
jobs she do or the drug she use especially some people still believe the drugs are
supplied by donors and thus should be free. She also notes that frequent droughts
make the livestock move away from the village, even though sometimes she follows the
animals out of village when called upon by owners, and she may spend several nights
out of her home and thus the huge risk as she is a lady and a mother of two.
Her biggest dream is to be able to open an ago-vet/drug store in the village or the nearby
small town of Ainabo. Her plan now is to keep working and join VSLA in the village to
access capital for her planned business. She mentioned that she need a refresher
training and more training on the same, as well support with more modern equipment
like Automatic syringes. She is very grateful to have gained the experience from
SomReP.
Box 1: Success story from Yagoori - Laas Caanood
Goat ownership still emerged as an important (60% of HH) livestock species kept by household in the
project areas across the livelihood zones, followed by Sheep (25.4%). Cattle ranks lower than camel in
proportion of ownership still from the findings. Similarly, among male-headed household and female-
headed household ownership of Goats were the dominant type of livestock with 63.4% and 57.2%
respectively followed by Sheep 29.4% (male-headed households) and 21% (female-headed household)
as shown in Table 11.
Table 11: Type of livestock owned across project districts
Page | 29
Livestock Species Overall (%) Male-headed HH (%) Female-headed HH (%)
Goat 60.5 63.4 57.2
Sheep 25.4 29.4 21
Camel 9.6 12.8 5.9
Donkey 8.7 10.1 7.1
Cattle 6.9 7.3 6.4
Poultry 5.1 5.7 4.4
Oxen 1.4 1.9 0.8
Source: Assessment Survey
Goats were also dominant across the livelihood zones with 73.7% 63% and 46.9% for pastoral, agro-pastoral
and peri-urban households. Similar to gender disaggregation, the Sheep was second in terms of ownership.
The survey also shown more cattle are owned by agro-pastoralist (10.3%) as compared to pastoral (5.2%)
and peri-urban (3.3%) as shown in Table 12. This is likely because agro-pastoral environment are more
favorable for cattle as compared to pastoral and urban environment21. The same trend was also observed
when disaggregating livestock ownership by districts where the majority of households kept Goats and
Sheep with fewer cattle and camels. Camels presence was reported in all districts expect for Afgooye and
Luuq Districts. On the other hand, cattle presence were recorded in most districts expect in Bossaso,
Hargeysa, Laas Caanood and Salahley22.
Table 12: Type of livestock owned disaggregated by livelihood zone
Livestock Species Peri-Urban/ Urban Pastoral Agro-Pastoral
Goat 46.9 73.7 63
Sheep 19.3 30.9 26.7
Camel 6.9 8.9 11.9
Donkey 6.6 12.1
Poultry 3.6 6 7.8
Cattle 3.3 2.8 10.3
Oxen 0.2 5.2 2.7
Source: Assessment Survey 0.6
The small stock (Shoats) seem to have taken the day in livestock ownership and hence the most
preferred species that interventions in the project areas should consider. In many pastoral
communities across the regions, there is increasing shift to small stock keeping for the reasons of easy
management, low feed and water demands, easy market access and convenient for provision of
household meat demands. In addition, in most cases, women ownership of livestock is always likely
for the small stock. Donkey is still appreciated as an important animal species for the roles in transport
and draft power for the communities. Despite the camel being a very hardy and well adapted species
in the drylands, its adoption is still low; partially this could be attributed to the high cost involved in
acquiring it as starter stock.
From the survey, we noted that majority (58%) of the respondents who owned livestock indicated that
they have experience an increase in their livestock numbers, while 28% indicated a decrease in the
21 https://www.lrrd.cipav.org.co/lrrd19/12/tole19177.htm
22 For district-based analysis refer to annex 2
Page | 30
numbers of livestock due to destocking and shocks (shocks include conflict, drought, disease outbreak,
theft and floods). The observed increase may be partly attributed to the SomReP intervention to
animal husbandry, animal health, and restocking and land management for increased feed resources
to the livestock keepers. We also know that, many pastoralists always invest in livestock production
when incomes improve, and hence increase in the numbers reported. The reported decline by over
25% of the respondents is still a gap that needs to be addressed. The major contributing factors
identified like droughts, feed shortage, conflicts and diseases is still an area that development partners
need to support in the future programming.
Plate 1 Camel browsing in FMNR site Owdweyne; Goats going for grazing in Dollow district
5.2.5 Agriculture and Livestock Production
The study found that 24.6% of the respondents across all the livelihood zones are practicing farming
activities. Across the districts, the majority of households practice farming expect for Ceed Barde, Eyl,
Hargeysa and Salahley where 78.7%, 100%, 88.9% and 80% indicated that they don’t practice farming
respectively23. Most of the farming activities are done under rain-fed conditions, which should be
seasonal farming activities, and rain-fed farming in drylands is the most vulnerable to climatic change
impacts. Irrigation accounts for 32.3% of the household respondents while mixed farming is done by
25.8% (Figure 9).
23 For district-based analysis refer to annex 2
Page | 31
32.3
41.9
25.8
Irrigated Irrigated and rain fed Rain fed
Figure 9: Type of farming practiced across project districts
Source: Assessment Survey
Among the farmers who use irrigation, 44% are using canal (particularly Earth canal) to deliver water
to their farms while other are using Bucket, Drip, Gravity, Mechanical and Sprinkler. These findings
indicate that the efficiency of irrigation, especially for earth canal is wanting due to water losses. This
can be improved by enhancing the canal by paving for reduced water seepage. Still, there is an
opportunity to increase support with efficient irrigation technologies like drip irrigation for better
water use efficiency and increase in acreage under farming. The study found out that most of the
farmlands supported by the programme are still using canal irrigation with most villages like Beerato,
Ceelefwein, Arapsio in Somaliland having water deficits and hence reduced crop productivity and
seasonal production. Even though, we find the villages to be very productive if sustainable water
source like dams coupled with water saving irrigation technologies like drip kits could be adopted in
the future support.
The main source of irrigation water is from rivers (21.7%), Borehole (9.6%), water kiosk (7%),
unprotected well (4.9%), rain water (4.6%) and Hand pump well (2.8%), as the main source of farming
water. Other sources of water for farming include dams, shallow wells and springs that account for
0.8%, 1.1% and 1.2% respectively. The interventions by SomReP in support to farming have
contributed to access for irrigation water, this includes; dams construction, Rehabilitation and upgrade
of multi-use water structures (berkads, boreholes, surface water pans, sand dams, water reservoirs &
shallow wells for multiple water uses (household, agriculture and livestock consumption). The study
finds that some communities like Gatililey village in Owdwayne are still having challenges with
sustainable water source for multiple uses, with the current dam having not been lined and hence high
water losses. The village was reported during FGDs and KII to be still under water stress with the
present dry period relying on water trucking for both domestic and livestock uses. This is achieved at
high costs of about three dollars per barrel of 200 litres.
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The Somalia farming activities depend mainly on seasonality calendars with four main seasons (Ogallo
et al. 2018). The region has four main seasons in a year. Main dry season known as Jilaal (January and
March), main rain seasons known as Gu (April and June), dry season Hagaa (July–September) and short
rain seasons known as Deyr (October–November). This season determines the extent of farming
activities, with impacts on acreage of crops based on across productivity risks expected. Main farming
activities are carried during Gu and Deyr, and thus the observed high number of acreage of average
13 hectares cultivated in this periods (Table 16). Jilal had the lowest farming acreage due to the long
dry periods with the expected crop failures. Hagga period sometimes receives some moisture that
allows cropping of drought tolerant crops like sorghum. Comparing the average hectares across male
and female headed households, the survey revealed that female-headed households cultivated more
hectares across the growing season expect for the Deyr compared to their male-headed households
as shown in Table 14.
Table 13: Average land size cultivated growing seasons
Source Average land size (hectare) Std. Deviation
Gu 13.33 51.244
Deyr 13.08 40.130
Jilal (Dry season) 1.27 6.289
Hagga 8.63 39.314
Source: Assessment Survey
Table 14: Average land size cultivated growing seasons
Source Male-headed HH Average land size Female-headed HH Average land size
(hectare)
(hectare) 7.79
10.68
Deyr 9.96 9.45
6.40
Gu 8.89
Hagga 6.23
Jilal (Dry season) 5.87
Source: Assessment Survey
5.2.5.1 Crop Production24
Crop production during the Hagga period
The dry season of Hagga has many farmers doing maize (N=201) followed by melon and Sorghum as
first priority crops. This season has a lot of uncertainties and most farmers usually get crop failures,
except the farmers who do more of drought tolerant varieties of maize and sorghum, of which from
the FGDs the farmers are challenged in accessing better varieties of the same, and most use farmer
own saved traditional seeds. Most of the farmers seem not to have many other crops for second and
third priority. Importantly the farmers still do vegetable farming due to the always high demand in the
markets. Melon being among the first priority crop has high acreage (17 Ha) due to the high demand
24 The data collection used various measures for yield that are difficult to amalgamate hence the difficulty to obtain
crop yield. The tables below show the average land size allocated to various crops.
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2020 Annual Resilience Measurement Study Report
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