Small Grants Final Technical Report

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CPWF SG 503 FTR 2007

ENHANCE ADOPTION OF HIGH POTENTIAL INTERVENTIONS FORINCREASING AGRICULTURAL WATER PRODUCTIVITY

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ANNEX A

SSUUAA AALLEERRTT IIFFPPRRII

JULY, 2007


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CPWF SG 503 FINAL TECHNICAL REPORT

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EXECUTIVE SUMMARY

The Soil Water Management Research Group (SWMRG) of the Sokoine University of Agriculture(SUA) in collaboration with the Association for Land-use, Environmental care, Research and

Technology transfer (ALERT) and International Food Policy Research Institute (IFPRI) of

Washington DC, implemented the research project number CPWF SG 503 on Conditions for SustainableAdoption of Water and Moisture System Innovations in Nile River Basin: Case of Makanya Watershed in Tanzaniaunder a CPWF Small Grant Program on Enhance Adoption of High Potential Interventions forIncreasing Agricultural Water Productivity

The purpose of the research project was to improve adoption of agricultural water and moisture systeminnovations (WMSIs) among smallholder farmers for enhanced livelihood in semi-arid areas. Thedevelopment challenge abreast of this project is on how the rate and intensity of adoption of robustendogenous and novel WMSIs can be enhanced. The objectives of the research project were: (i) toestablish an inventory of smallholder water and moisture system innovations practiced in the study areaand their potential to improve household livelihoods; (ii) to identify biophysical and socio-economic

determinants of adoption of the WMSIs in the study area; (iii) to identify perceptions of the farmersand local communities on the WMSIs; (iv) to promote strategies and approaches that facilitate scalingup of WMSIs and (v) to produce and share policy recommendations for the adoption of water andmoisture system innovations to enhance uptake by key stakeholders.

This study was conducted in Makanya Catchment in Tanzania, covering five villages namely Chajo,Mhero, Malindi, Mgwasi and Makanya. Both participatory approaches and questionnaire interviews

were conducted to collect data and relevant information. A series of consultation meeting andworkshops with stakeholders were conducted to share knowledge and information generated as part ofthe implementation of communication plan.

The results showed that the current extent of use of water and moisture innovation systems (WMSIs),in the study area, is as follows:

WMSIs practiced in the study area

Most of the WMSIs practiced in the catchment can be categorised into storage and in-situ watercapture type. Storage structures include charco dams (malambo ), small ponds (ndiva ), wells and tanks(surface or subsurface). These are important WMSIs for domestic use, crop and livestock production.

This is mainly because the rains are erratic and sometime last for a short period. In-situ WMSIs,commonly known as soil-water conservation innovations, comprise a group of techniques forpreventing runoff and promoting infiltration. A number of cultural practices such as trees-on-farm,cover crops, mulching, ridging and addition of manure, fall under this category. Others include stone

and earth terraces, fanya juu/chini and contour ridges/bunds, borders/basins, deep tillage, trash lines,and ripping; run off diversion, valley bottom farming and large planting pits. A number of these

WMSIs practiced in the Makanya catchment are traditional while the others are introduced. Intensityand extent of adoption differ between the lowlands, midlands and uplands.

Potential of WMSIs to improve farmers livelihoods

The study revealed that WMSIs that involve supplementary irrigation had higher returns to land andlabour therefore have potential for improving household livelihood based on crop enterprises involved.For example, run-off diversion for spate irrigation had higher returns to land (TAS 222,266/ha US$176) and labour (TAS 202/person/day US$ 0.16/person/day) compared to over WMSIs in the

lowland under Lablab enterprise. In the midlands diversion of stream flows had returns to land (TAS451,655/ha US$ 358) under Lablab enterprise. In the uplands ndiva had higher returns to land (TAS2,908.125/ha US$ 2308) and labour (TAS 6,613/person/day US$ 5.2). On the other hand, tree-


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on-farm had high returns to land (TAS 1,301,425/ha US$ 1033) and labour (TAS 21,154/person/day US$ 16.8) in upland in coffee enterprise.

Biophysical and socio-economic determinants of adoption of the WMSIs

The results showed that determinants that positively and/or negatively influence adoption of

innovations are mainly biophysical and socio-economic. The biophysical determinants includetopography (control erosion), yield increase/productivity, reduce inconvenience in irrigation schedule,irrigation task is simplified by controlling water, conserve soil, fertility and moisture, good crop growth,shortage of enough water to conserve, land shortage, increased production, rainfall shortage, protect

water loss and poor working tools. The socio economic determinants include bye-laws for group theuse the same ndiva, cash crops, low education level, low income level, inadequate labour force, landtenure, cost involved, poor technology, unwillingness to take up the technology, having otheralternative activities, lack of expertise/technology, lack of collective action (kiwili), high cost toimplement, lack of information about technology, traditions and norms of using draught animals andlaziness, ignorance, jealousy, complacency. Between 62.5 and 70% of mentioned determinants thatpositively influence farmers to adopt WMSIs are of biophysical in nature. It was also found thatbetween 69.2 to 79% of all the factors negatively affect farmers to adopt WMSIs are socio-economic innature.

Determinants of technology adoption at household level include household capital endowments(capital assets - human, natural, physical, financial and social), land tenure and access to market andservices have influenced adoption of WMSIs in Makanya Catchment. Results show that there arepositive relationships between adoption of WMSIs with human capital (education level, training offarmers, household labour and age of farmers); natural capital (farm size); physical (ownership oflivestock and house type); financial capital (liquid asset - bank account) and social capital (farmerassociation sand networks). Other factors include access to market and policy environment. It is worthnoting that results showed negative relationship on adoption of most WMSIs for women except forcover crops. This is due to the fact that most women are dealing with leguminous crop which arecommonly use as cover crops, in their effort to provide food for their households.

Perceptions of the farmers and local communities on the WMSIs

Results showed that the need for conserving soil and water, improving food security, increasingproductivity, low rainfall and increasing income were perceived as most important reasons for adoptingmost WMSIs at farm level. On the other hand farmers perceived that inadequateknowledge/education/skills and low income are the most important reasons for them not adoptingsome innovations they perceive to be good for their farm households. There are significant correlationsamong reasons for adopting the innovations. During focus group discussions women groups perceivedadvantages of adopting some WMSIs differently from groups of men farmers. For example, women

farmers perceived that charco-dams and water tanks improved availability of water near homesteadswhich reduced their work load of walking long distances in search of water, therefore providing ampletime to do other households chores. On the other hand men emphasised that charco dams increased

water availability for livestock, thus protecting livestock from dying while moving them to the River insearch of water.

Strategies and approaches that facilitate scaling up of WMSIs

The project assessed current strategies and approaches for scaling up of WMSIs. Results show thatscaling-up of potential WMSIs entailed communication, interaction and interrelation amongst keystakeholders through social and institutional networks. Sharing of knowledge and information is donemostly within the family members and farming communities within in the villages and between village

to village. A few farmers learned about WMSIs in schools and colleges while other throughinterventions by the government and change or development agents like NGOs and developmentprojects. The farmers response shows that interactive methods like on-farm trials, field/exchange


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visits, demonstration plots, meetings and seminars were effective in knowledge sharing. Similarly,learning from parents, extension workers and village government leaders were also found to beeffective.

Policy issues for the adoption of WMSIs

Review of policies to assess their adequacy in promoting adoption of WMSIs revealed that mostpolicies and strategy papers have contain clauses related to conservation of water and moisture. Thesedocuments include National Water Policy of 2002, Tanzania Agricultural and Livestock Policy of 1997,the National Environmental Policy 1997; National Forestry Policy of 1998; and strategy papers like the

Agricultural Sector Development Strategy of 2001 and the National Strategy for Growth and Reductionof Poverty of 2005. There are major weaknesses in implementation of policies which make promotionand uptake of WMSIs difficult. These include policies documents not available and therefore not knowto most executives; limited understanding of the policies to both communities and extension officers;poor community involvement in policy making process; some cases where policies are interpretedpolitically in favour of a few or groups of individuals. In addition, there are conflicting policies and bye-laws which also create confusion among farming communities.

Conclusions and Recommendations

The study found out that most of the household in the Makanya Catchment are practicing at least oneWMSI. The WMSIs that involve supplementary irrigation had higher returns to land and labour, whichindicates that in semi-arid environment supplementation of rainfed agriculture, is important. Venturingin high value crops like vegetables under capital intensive WMSIs like ndivawould effectively reduceincome poverty in water constrained dry lands. Most of the constraints to adoption are related to socio-economic determinants. This implies that successful promotion of novel technologies to farm andcommunity levels should address socio-economic constraints for smooth uptake of technologies. Theneeds to conserve soil and water, improving food security and increasing income were perceived asmost important factors for adopting WMSIs. However, there are gender differences on perception of

advantages and disadvantages over adoption of WMSIs, which in-turn affects uptake of WMSIs.Furthermore, limited accessibility of policies and low understanding of policies, regulations and bye-laws limit promotion and uptake of WMSIs. Therefore it is recommended that availability of policydocuments at village, ward and division levels should be enhanced as well as education on policy, laws,principles and procedures for leaders and communities to foster smooth implementation.


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ACRONYMS AND DEFINITIONS

ALERT : Association for Land use, Environmental care, Research and Technology TransferCARITAS : Roman Catholic Agency for Community DevelopmentCBOs : Community Based OrganisationsCPWF : Geographical Information SystemDALDO : District Agricultural and Livestock Development OfficerDC : District CouncilFGD : Focus Group DiscussionIFPRI : International Food Policy Research InstituteKSPs : Knowledge Sharing ProductsNGOs : Non Government OrganisationsSAIPRO : Same Agricultural Improvement ProjectSG : Small GrantSSA : Sub Saharan AfricaSSI : Smallholder System InnovationsSUA : Sokoine University of AgricultureSWMRG : Soil Water Management Research Group

TIP : Traditional Irrigation Improvement Project VECO : Vredeseilanden Country Office VEO : Village Executive Officer WEO : Ward Executive Officer WDC : Ward Development Council WMSIs : Water and Moisture System Innovations WSIs : Water System Innovations


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TABLE OF CONTENTS

EXECUTIVE SUMMARY............................................................ ................................................................ .................. II

ACRONYMS AND DEFINITIONS....................................................... ............................................................... ........ V

TABLE OF CONTENTS ..............................................................................................................................................VI

LIST OF FIGURE .......................................................................................................................................................VIII

LIST OF TABLES ..........................................................................................................................................................IX

LIST OF APPENDICES ................................................................................................................................................IX

INTRODUCTION ............................................................. ................................................................ .............................. 1

1.1BACKGROUND............................................................. ................................................................ .............................. 1

1.2STUDYVILLAGES......................................................... ................................................................ .............................. 2

METHODOLOGY............................................................. ................................................................ .............................. 3

2.1DELIVERY OF OUTPUT 1 ......................................................... ............................................................... .................... 32.1.1 Review of literature on existing WMSIs...................................................................................................................... 3

2.1.2 Introducing the project in the selected village.................................................................................................................. 3

2.1.3 Participatory agro-ecosystem analysis.......................................................................................................................... 3

2.2DELIVERY OF OUTPUT 2 ......................................................... ............................................................... .................... 32.2.1 Review of different econometric adoption models............................................................................................................. 3

2.2.2 Identify determinantsof adoption............................................................................................................................... 3

2.3DELIVERY OF OUTPUT 3 ......................................................... ............................................................... .................... 42.3.1 Identification of farmers and community perceptions...................................................................................................... 4

2.4DELIVERY OF OUTPUT 4 ......................................................... ............................................................... .................... 42.4.1 Review and documentation of strategies and approaches for scaling up ................................................................................ 4

2.4.2 Development of the knowledge sharing and communication strategy and plan....................................................................... 4

2.5DELIVERY OF OUTPUT 5 ......................................................... ............................................................... .................... 52.5.1 Review and assessment of adequacy of water related policies............................................................................................. 5

2.5.2 Village level assessment of water policy........................................................................................................................ 5

2.6DATA COLLECTION................................................................ ............................................................... .................... 52.6.1 Sampling Procedure................................................................................................................................................ 5

2.6.2 Data Processing and Analysis.................................................................................................................................. 6

2.7LIMITATION OF THE METHODOLOGY.......................................................... .............................................................. 7

SMALLHOLDER WMSIS IN THE MAKANYA CATCHMENT............................................................ ................... 8

3.1OVERVIEW........................................................ ............................................................... ......................................... 83.2AGRO-ECOSYSTEMS IN MAKANYA CATCHMENT ............................................................... ......................................... 93.2.1 Uplands............................................................................................................................................................... 9

3.2.2 Mid lands............................................................................................................................................................ 9

3.2.3 Lowlands............................................................................................................................................................. 9

3.3WMSIS PRACTICED IN THE MAKANYA CATCHMENT......................................................... ......................................... 93.3.1 Uplands............................................................................................................................................................. 10

3.3.2 Midlands........................................................................................................................................................... 11

3.2.3 Lowlands........................................................................................................................................................... 12

3.4INTENSITY OFADOPTION OFWMSIS IN MAKANYA CATCHMENT ........................................................................... 123.5POTENTIAL OFWMSIS IN HOUSEHOLD LIVELIHOODS IMPROVEMENT AND POVERTY REDUCTION .......................... 13

3.5.1. Performance of crop enterprises under different WMSIs in lowland................................................................................. 13

3.5.2. Performance of crop enterprises under different WMSIs in the midland........................................................................... 14

3.5.3. Performance of crop enterprises under different WMSIs in the upland............................................................................. 17

DETERMINANTS OF ADOPTION OF WMSIS IN THE MAKANYA CATCHMENT ...................................... 20


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LIST OF FIGURE

Figure 1: Location of the study villages within the Makanya watershed ........................................................ 2

Figure 2: Yield of lablab under different WMSIs in masikaseason in the lowland.....................................13

Figure 3: Returns to land from lablab under different WMSIs in masikaseason in the lowland..............14

Figure 4: Returns to labour from lablab under different WMSIs in masikaseason in the lowland.......... 14

Figure 5: Yield of lablab under different WMSIs in masikaseason in the midland .................................... 14

Figure 6: Returns to land from lablab under different WMSIs in masikaseason in the midland ............. 15

Figure 7: Returns to labour from lablab under different WMSIs in masikaseason in the midland .........15

Figure 8: Yield of bean under different WMSIs in vuliseason in the midland............................................15

Figure 8: Yield of bean under different WMSIs in vuliseason in the midland............................................16

Figure 9: Returns to land from bean under different WMSIs in vuliseason in the midland.....................16

Figure 10: Returns to labour from lablab under different WMSIs in vuliseason in the midland............. 16

Figure 11: Yield of maize under different WMSIs in vuliseason in the midland........................................16

Figure 12: Returns to land from maize under different WMSIs in vuliseason in the midland................. 17

Figure 13: Returns to labour from maize under different WMSIs in vuliseason in the midland ............. 17

Figure 14: Yield of bean under different WMSIs in vuliseason in the upland ............................................ 17

Figure 15: Returns to land from bean under different WMSIs in vuliseason in the upland ..................... 18

Figure 16: Returns to labour from bean under different WMSIs in vuliseason in the upland .................18

Figure 17: Returns to land from vegetables under different WMSIs and seasons in the upland ............. 18

Figure 18: Returns to labour from vegetables under different WMSIs and seasons in the land .............. 18

Figure 19: Yield of coffee under different WMSIs in the upland..................................................................19

Figure 20: Returns to land from coffee under different WMSIs in the upland........................................... 19

Figure 21: Returns to labour from coffee under different WMSIs in the upland.......................................19


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LIST OF TABLES

Table 1: Category of the water and moisture system innovation in the catchment...................................... 8

Table 2: WMSIs in the Makanya Catchment.................................................................................................... 10

Table 3: Extent of practicing WMSIs in upland areas..................................................................................... 10

Table 4: Extent of practicing WMSIs in midland areas .................................................................................. 11

Table 5: Extent of practicing WMSIs in lowlands........................................................................................... 12

Table 6: Intensity of adoption of WMSIs in the Makanya catchment..........................................................12

Table 7: Family labour and adoption of water and moisture system innovations ...................................... 22

Table 8: Gender and adoption of water and moisture system innovations ................................................. 22

Table 9: Perceive reasons for adopting of first priority WMSIs .................................................................... 26

Table 10: Perceive reasons for adopting priority two WMSIs.......................................................................26

Table 11: Perceive reasons for adopting priority three WMSIs..................................................................... 27

Table 12: Reasons for not adopting innovation perceived to be good for the household........................27

Table 13: Correlations of the farmers perceptions on the reasons for adopting WMSIs.........................28

Table 14: Source of knowledge and information currently used as indicated by farmers ......................... 33

Table 15: Perception of farmers on the extent of adopting from trained farmers ..................................... 34

Table 16: Effectiveness of Knowledge and Communication methods in Makanya Catchment .............. 36

Table 17: Number of farmers adopting bench terraces and terraces established in Malindi village ........ 38

LIST OF APPENDICES

Appendix A: Table of results on the determinants of adoption.................................................................... 46

Appendix B: Most Significant Change Stories ................................................................................................. 57


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CHAPTER 1

INTRODUCTION

1.1 Background

From January 2006, the Soil Water Research Management Research Group (SWMRG) of the SokoineUniversity of Agriculture (SUA) in collaboration with a local NGO known as Association for Land-use,Environmental care, Research and Technology transfer (ALERT) and International Food PolicyResearch Institute (IFPRI) of Washington DC, has been implementing a research project numberCPWF SG 503 on Conditions for Sustainable Adoption of Water and Moisture SystemInnovations in Nile River Basin: Case of Makanya Watershed in Tanzaniaunder a CPWF SmallGrant Program on Enhance Adoption of High Potential Interventions for Increasing

Agricultural Water Productivity

The purpose of the research project is to improve adoption of agricultural water and moisture systeminnovations (WMSIs) among smallholder farmers for enhanced livelihood in semi-arid areas. Theproject was designed to contribute in improving the currently low adoption of water and moisturesystems innovations for increased productivity of agricultural water in the semi-arid areas. In the semi-arid areas scarcity and variability of agricultural water and moisture is a major constraint to improvedlivelihood of smallholder farmers in the semi-arid dryland areas.

Water Moisture System Innovations (WMSIs) are defined as any management technology or practicethat has the objective to reduce risks of rainfed-induced water stress and/or increase agriculturalproductivity. They include water harvesting, drip irrigation, precision agriculture and conservationfarming technologies aiming at improving water productivity while conserving resources (Rockstrom et

al., 2004). Most WMSIs are understood in a systems context where water management forms anintegral part of a production system, including interactions between soil, water and crop management(e.g., conservation tillage which aims to improve soil properties for water conservation).

The development challenge abreast of this project is on how the rate and intensity of adoption ofrobust endogenous and novel WMSIs can be enhanced. In this regard, this project (CPWF SG 503) isdesigned to meet this challenge by delivering its purpose after attaining the following outputs (stated inresults form):

1. Inventory of smallholder water and moisture system innovations practiced in the study areaand their potential to improve household livelihoods Established

2. Biophysical and socio-economic determinants of adoption of the WMSIs in the study areaIdentified

3. Perceptions of the farmers and local communities on the WMSIs Identified4. Strategies and approaches that facilitate scaling up of WMSIs Promoted5. Policy recommendations for the adoption of water and moisture system innovations

Produced and Shared for uptake by key stakeholders


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1.2 Study Villages

The study villages were selected by stakeholders during the project inception workshop held in Samefrom 22nd to 23rd March 2006. The selection process was guided by three criteria that: i) the target of theproject is only five villages, ii) the villages must represent the three biophysical locations of the

watershed landscape (upland, midland and lowland), and iii) the selected village should be the one really

manifesting non-existence or very low extent of adoption of WMSIs and not already researched interms of adoption of the same. In the first place 13 potential villages were identified entailing 7, 4, and1 from the upland, midland and lowland respectively. Based on the selection criteria two villages wereunanimously selected in the upland (Suji and Mhero), two in the midland (Chajo and Mgwasi) and onein the lowland (Makanya). Figure 1 presents the selected study villages.

Figure 1: Location of the study villages within the Makanya watershed


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CHAPTER 2

METHODOLOGY

2.1 Delivery of output 1

2.1.1 Review of literature on existing WMSIs

This activity was an entry point for establishing an inventory of smallholder WMSIs and theirunderlying potential to improve household livelihoods. The activity was implemented through in-depthreview of existing WMSIs at regional, national and watershed levels (Annex B1).

2.1.2 Introducing the project in the selected village

This activity was undertaken by a team of researchers who paid visits to the selected villages. Theproject was introduced to the village leader then to the group of selected farmers who attended FGD.

The process followed normal protocols involving paying a courtesy to village offices to introduce theproject to respective village executive officers. The village officers assisted to make arrangements forthe general meetings with farmers. In the meetings the research team introduced the projectbackground, objectives and expected community outcomes/impacts and the roles of the localcommunities in the research process stipulated by stakeholders during an inception meeting.

2.1.3 Participatory agro-ecosystem analysis

In this project, participatory agro-ecosystem analysis refers to application of participatory and quasi-participatory (mainly researcher based) methods in implementing research activities in the field. In thisstudy the term agro-ecosystem refers to a dynamic association of crops, pastures, livestock, other floraand fauna, atmosphere, soils, and water. Agro-ecosystems are contained within larger landscapes thatinclude uncultivated land, drainage networks, wildlife and rural communities(www.fao.org/ag/wfe2005/glossary_en.htm). This activity was done during FGD in the initial stages of theproject implementation and subsequent field visits during implementation of the project.


2.2.1 Review of different econometric adoption models

The basic intent of this activity was to establish and critique different adoption models from the viewpoints of adoption theories and models (Annex B2).

2.2.2 Identify determinants of adoption

Using participatory approaches (FGD, key informant interviews and observations) and questionnairesurvey, critical determinants of adoption of WMSIs, farmers perceptions on novel innovations anddissemination and information sharing methods were identified and assessed
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2.3.1 Identification of farmers and community perceptions

Perceptions on the preconditions and externalities for adoption of WMSIs were explored at farm andcommunity levels. Farm level data for perceptions were collected through a questionnaire administered

in the household survey while that for community level were collated through FGD and keyinformants interviews.

At community level, the preconditions and externalities were assessed through focused groupdiscussions to capture community wide perceptions on the adoption of WMSIs. In the analysis of farmlevel perception, the conventional attitudinal scale (Likert) was used evaluate different attributes ofpreconditions for adoption of different WMSIs. Attitudinal rating aspects on the Likert scale that wereloaded in factor analysis include very important; important; not so important; not important at all.


2.4.1 Review and documentation of strategies and approaches for scaling up

In this regard, it is imperative to review and critique different approaches and strategies for scaling upfor enriching the project communication plan (Annex B3).

2.4.2 Development of the knowledge sharing and communication strategy and plan

In the development of knowledge sharing and communication strategy, the first stage involvedcategorization of stakeholders and identification of their information needs. This was done through aknowledge sharing and communication strategy workshop. The stakeholders were categorized into

groups such as farmers, planners, district agricultural officers, trade officers and the private sectorsinvolved with handling farmers products or providing inputs. After categorization, through opendiscussions in the workshop among the stakeholders information needs, knowledge, attitude andpractice were analyzed. The ways of information brokerage and sharing were also elicited. Theframework was shared in the stakeholders consultation workshop.

The aims of the knowledge sharing and communication strategy in relation to the project purpose were:

To facilitate participation and commitment of stakeholders in the research process so as tofoster the sense of ownership of research outputs, which would propel uptake of researchresults

To ensure that farmers access and use best-bet WMSIs that would enable them to increaseproductivity of resources (land, water, capital and labour) in order to reduce poverty andincrease food security

Bridging the research and policy by brokering research results to policy and developmentpractitioners at district and national levels

Therefore, for successful and sustainable outcomes, the promotion of the research outputs andproducts of this project involved a process whereby a framework for knowledge sharing to differentstakeholders was developed as one of the project activities. The development and operationalization ofthe knowledge sharing and communication strategy involved dissemination of potential innovationsthrough study visits, agricultural exhibitions, training, informative stakeholders workshops and

lobbying and advocacy in order to pass the research knowledge across a range of stakeholders toensure scaling up/out.


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2.5.1 Review and assessment of adequacy of water related policies

The process involved collection material related to policies and institutional frameworks e.g.legislations, guidelines with a bearing to WMSIs adoption and access and undertake content analysis for

adequacy/potential and shortfall/caveats, and equate with local realities and priorities. Key extracts andstatements from the policy, strategy and legislation documents explicitly have been synthesized toconcretize strengths and weaknesses of the contents to highlight domains for robust reformations forefficient and sustainable adoption of WMSIs (Annex B4).

2.5.2 Village level assessment of water policy

At village level the project sought to evaluate awareness, attitudes and opinions of farmers on thepolicies and legislations related to water, land and other related natural resources such as catchmentforests. Such awareness has been evaluated with a major focus on how these policies affect(hinder/enhance) adoption of and access to WMSIs. The policies were further evaluated in relation to

the planning process and participation of local stakeholders and implications for policy efficacy at locallevel.

2.6 Data Collection

Data was collected through focus group discussions with key informants, and individual interviewsusing a structured questionnaire as detailed in Annex B5.

2.6.1 Sampling Procedure

Households

By design a minimum of 60 respondents from each of study village located in the three biophysicallocations on the watershed landscape (i.e. upland, midland and lowland). The overall sample size was300 respondents. Simple random sampling was used to select the respondents from an updated villageregister of all households. A few case studies were undertaken to track interesting field stories andprocesses related to adoption of WMSIs that were used to supplement or complement to the otherresearch findings.

Key informant interviews

Before each focus group interviews, short meetings were held with village leaders. Key informants werepeople that were knowledgeable in WMSIs in their village and sub-villages. For this reason,chairpersons of villages and sub-villages, elders and extension staff at ward and village levels constitutedthe key informant interviews.

Key informant interviews were held at village level that brought together village leaders and extensionstaff. The second session involved farmers. Researchers facilitated the discussion and started byexplaining the objective of the survey. The discussions focused on identification of the extent andperformance of WMSIs in the respective village or sub-village. This included information on types of

WMSIs found in the area, agro-ecosystem analyses, perception of the factors affecting wide adoption ofthe WMSIs and policies influencing the uptake of WMSIs. The WMSIs currently in use; areas andactivities where WMSIs are mostly practiced and areas suitable for WMSIs for various activities were

also discussed.


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Structured interviews

Development of the household questionnaire survey involved undertaking a series of tasks. Theseinclude design of the questionnaire, piloting the questionnaire in the field and post-pilotingincorporation of adjustments in the final questionnaire that was used to undertake a baseline survey.

The questionnaire was crafted to address basic strands embedded in all of the project outputs. This is

because only one household questionnaire survey was done in during project implementation. Thearchitecture of the questionnaire entailed four broad parts. First part comprised of introductoryinformation, the second part comprised of information of water and moisture system innovations, thethird part comprised of socio-economic aspects of water and moisture system innovations and the lastpart was on household development. In order to increase accuracy and efficiency in the interviewprocess the questionnaire was translated into Swahili which is the official language well understood byboth the interviewers and interviewees.

Selection and training of enumerators

The enumeration process was carried out by a team of local enumerators including village/wardextensionists, social workers, and primary school teachers. At least 3 local enumerators identified byrespective village leaders were appointed from each village. Use of local enumerators enables flexibilityin the time of undertaking the interviews as the enumerator and the respondent could agree on the timeof interview. Because one might have an ample time to revisit the farms to clarify some issues thatappear unclear during the interviews and get acquainted of field realities such as typologies of WMSIs.

Training of enumerators was done in two phases for two days. The first phase involved training on thetheoretical and practical insights into research in general and social survey in particular. Critical aspectsthat were introduced under the first phase included: the concept of research as a systematic enquiry, theart and science for establishing convenient interviewer-interviewee interface and probing, and theexternalities of leading questions. The second phase involved going through all the questions as tounderstand the construct and the intended purpose of each question and pre-testing the instrument inthe field. From the lessons acquired after pre-testing the questionnaire was amended to incorporatenecessary changes and establishing common of styles of asking some questions.

Arrangements for household survey were done in advance by formally informing the village and sub-village leaders to inform the selected households. Through collaboration between the research teamand local leaders, the letters specifying the date of visit to a particular village/sub-village cluster weredistributed some days before survey started. The household survey was conducted by visiting differentindividual heads of households at home or in the field. During the interviews, in case the household isabsent the spouse was the proxy respondent. Collection of data was done for two weeks. One ofresearchers based in the field monitoring the progress, collect filled questionnaire, review them and givefeedbacks to enumerators for redress.

2.6.2 Data Processing and Analysis

The collected primary data were analyzed in view of delivering the elements of project outputs across.For the first output, descriptive analysis aimed at eliciting a portfolio of WMSIs by different biophysical(e.g. location, farm characteristics such as slope/terrain, crop type etc) and socio-economic variables(e.g. gender, age, wealth, education, access to extension etc). The analysis was undertaken usingavailable spreadsheet and statistical packages such as Excel and SPSS.


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2.7 Limitation of the Methodology

Due to the project setting and implementation it was not possible to have physical data on cropenterprises therefore the data used to compute returns to land and labour for production enterprisesrelied from farmers recalls during household surveys which may be prone to over or under estimation.


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CHAPTER 3

SMALLHOLDER WMSIs IN THE MAKANYA CATCHMENT

3.1 Overview

Farmers in the Makanya catchment are aware that both crop and livestock production can be improvedsubstantially through concentration of scarce rainwater as well as provision of supplementary waterduring critical times. The following sections of this chapter cover the agro-ecosystems in the MakanyaCatchment, existing WMSIs and the extent and intensity of adoption at household level.

The WMSIS practiced in the catchment storage type and in-situ water capture type (Table 5). Storagestructures like small ponds (ndiva) are important WMSIs for crop production. This is mainly becausethe rains are erratic and sometime last for a short period. These small ponds (ndiva) are normallyconstructed at a relatively higher (upland) area are used to store water from streams during the night

that supplement irrigation during the day. Charco dams are mostly found in the lowlands and mainlypurposed for livestock but currently used also for domestic purposes. Ground/underground tanks havebeen promoted mainly for kitchen gardening. The tank surfaces are usually sealed with mortar toreduce seepage losses while covering the tanks, with iron sheet minimizes evaporation.

In-situ WMSIs, also known as soil-water conservation, comprises a group of techniques for preventingrunoff and promoting infiltration. They aim at retaining moisture that would otherwise be wasted asrunoff from the cropped area. The most common technology is conservation tillage which aims tomaximize the amount of soil moisture within the root zone. A number of cultural moisture practicessuch as mulching, ridging, addition of manure, etc. could fall under this category. In-situ waterconservation is also combined with runoff farming on farms with terraces, in which the terrace channel

(mainly fanya juu and contour ridges/bunds) collects and stores runoff from small external catchmentswhile the cropland between the channels harvest and conserve direct rainfall. However, excess runoffthat may be generated from the cropland between the terrace channels would be collected at thechannel.

Table 1: Category of the water and moisture system innovation in the catchment

Category WMSIs

Storage Storage ponds Ndiva Wells Charco dams Tanks - Ground/underground

In-situ Terraces fanya juu/chini, bench Mulching Contours Conservation of natural vegetation Border/basins Deep tillage Use of ripper


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3.2 Agro-ecosystems in Makanya Catchment

3.2.1 Uplands

The uplands are dominated by various farming systems with a network of furrows and storage pondsknown as ndivas. Crops grown includes horticultural crops, maize, coffee/banana system, sweet and

round potatoes, yams, beans, trees-on-farm (for fruits, timber and shade), sugarcane and cassava.Others crops are on small-scale such as wheat and flower gardens. Rainfed and irrigated cropproduction using the existing traditional irrigation system is widely practiced. Zero grazing is common

where animals are housed and stall fed. Local and crossbred cattle are kept. Other animals include goatsand local chickens..

3.2.2 Mid lands

Major farming system is rainfed crop production with an exception of a few horticultural crops servedby a traditional irrigation system. Cropping systems include sole maize, maize with sunflower, maize

with groundnuts, legumes and pulses (lablab bean/common beans/pigeon). Others are cassava, sweet

and round potatoes, bananas, groundnuts, sugarcane and vegetables such as amaranthus, cabbages,tomatoes, onions, sweet pepper, and the African egg plant (ngogwe ). Other cropping systems includesugarcane and coffee/ banana and cover crops like lablab. Livestock production is also practiced whereanimals are zero grazed or tethered. A mixture of cross bred and local breeds is common.

3.2.3 Lowlands

The farming systems in this area are purely rainfed with exception of horticulture which getssupplementary irrigation from water harvested and stored in charco dams. The systems include maizeand legume (beans and lablab) intercropping, horticulture where vegetables like amaranthus, tomatoes,cabbage, okra are grown. Others crops grown are sweet potatoes, water melons and cucumber. Agro-pastoralism is practiced in the lowlands, mainly extensive grazing for local cattle, sheep and goats. Localchickens are also kept.

3.3 WMSIs practiced in the Makanya Catchment

A number of WMSIs are practiced in the Makanya catchment as shown in Table 1. Mostly aretraditional while the others are introduced and vary according to the toposequence across thecatchment. Similarly the intensity and extent of adoption differ between the lowlands, midlands anduplands as shown on Tables 2 - 4.


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Table 2: WMSIs in the Makanya Catchment

Areas Water Conservation Innovations Moisture Conservation Innovations

Highlands Storage ponds (ndiva) Cisterns

Wells Small charco-ponds Wetlands Natural vegetation conservation Canals Tree planting at water sources Valley bottoms Terraces

Bench terraces, Fanya juu/Fanya chini Mulching (crop residues)

Cover crops ( potatoes, legume, lablab,legumes, pumpkins)

Contours Conservation of natural vegetation Deep tillage Large pits Use of FYM and compost

Midslopes Storage pond (ndiva) Tanks Wells Charco dams Conservation of natural vegetation & watersources

Bench terraces, Contours (Fanya juu/Fanya chini) Tied ridges Mulching and Cover crops Deep tillage through ripper

Lowlands Charco-dams Storage tanks Tanks underground/subsurface Basins/borders

Basins/borders Mulching Deep tillage Cover crops

3.3.1 Uplands

WMSIs mostly practiced in the uplands include mulching, traditional deep tillage, trees-on-farm and useof farm yard manure while the least practiced are rainwater harvesting, diversion of stream flow and

terraces as shown on Table 2.

Table 3: Extent of practicing WMSIs in upland areas

WMSIs Upland (n = 120)

n %Mulching 96 81

Traditional Deep Tillage 86 74 Trees-on-farm Application of FYM 82 69Cover crop 58 50

Ndiva System 55 46Post Irrigation Tillage 51 43Large Planting Pits 42 36Earth Terraces 35 30

Trash Lines 25 Stone Terraces 23 20Runoff Diversion Ditches 20 17Runoff Diversion 12 10

Valley Bottom Farming 12 10RWH Tank and Pipe 7 6Diversion of Stream Flow 4 3

Fanya Juu/Chini Terraces 3 3n = number of respondents


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Mulching is the most practiced innovation where 81% of the households are practicing. This is mainlydue to the coffee banana system where the coffee and banana farms are mulched. The other innovationis the traditional deep tillage and use of farm yard manure to conserve moisture due to shortage of rainsand irrigation water where 69% of the households apply farm yard manure and 71% plant trees onfarms. The technologies are adopted to increase crop productivity and income that accrue from cropsales and therefore improving the food security as reported by most of the respondents. Other reasons

for adoption are the steep slopes, by laws enforced to conserve the environment and the frequentshortages of rainfall. However non adoption of WMSIs for some of the households is due to labourand capital intensiveness of some of the innovations such as construction of water tanks and pipe, andstone terraces. Lack of income, working tools, resources and materials are other factors mentioned tolimit adoption of WMSIs.

3.3.2 Midlands

Midland farmers mostly practice the traditional deep tillage where 66% of the households make use ofit. The run off diversion, ndiva and mulching are also common as 43%, 35% and 31% of thehouseholds respectively, practice them. Table 3 shows more of the WMSIs and the extent of their

adoption in the midlands. The extent of adoption of Diversion of run-off and stream flows in themidlands is not as high as in the upland areas. Location disadvantage was mentioned by all respondentsin the midlands as the main reason for not adopting the diversion of stream flow innovation asabstraction is high in uplands limiting water flowing downstream. However, low income and lack oftechnical know-how contribute to low use of technological know-how to improve the structures formaximizing run-off diversion. Despite the need for use of farm yard manure to improve fertility andconserve moisture, 83% of farmers fail to use it due to lack of transport as it is bulky and difficult tocarry to farm sites. Other reasons for non adoption include lack of tractors for deep tillage, ndivasnotfunctioning, and negative effects of some tree species to crops. Ripping is a newly introducedtechnology that is still in pilot sites.

Table 4: Extent of practicing WMSIs in midland areas

WMSIs Midland (n = 120n %

Traditional Deep Tillage 78 66Runoff Diversion 51 43Ndiva System 42 35Mulching 37 31Diversion of Stream Flow 33 28Large Planting Pits 31 26Post Irrigation Tillage 29 24

Cover crop 29 24 Trees-on-farm Application of FYM 24 20Earth Terraces 19 16

Trash Lines 15 Stone Terraces 10 8Runoff Diversion Ditches 8 7Bordered Basins 8 7

Valley Bottom Farming 6 5RWH Tank and Pipe 4 3Fanya Juu/Chini Terraces 3 3

Ripping 2 2n = number of respondents


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3.2.3 Lowlands

Mostly, the WMSIs used in the lowlands include the runoff diversion, bordered basins, cover crops,traditional deep tillage and large planting pits. Diversions of runoff and bordered basins are common,practiced by 87% and 58% of the households respectively. These innovations are useful in collectingrun off water during occasional rainfall events that usually occur in the semi arid lowlands or run-off

from the surrounding mountains.

Compared to the uplands and midlands, the lowlands in the Makanya catchment practice fewer WMSIsand the mostly practiced are the runoff diversion used by 87% of the households and the borderedbasins by 58%. The need to conserve soil and water compelled farmers to adopt different innovationsin order to increase production and improve the food security. However, adoption of mulching, postirrigation, charco dams, FYM and ripping is still low due to various reasons including inadequateknowledge, labour constraints, lack of tools like ox-cart to fetch FYM to distant fields and low income.

Table 5: Extent of practicing WMSIs in lowlands

WMSIs Lowland (n = 60

n %Runoff Diversion 51 87Bordered Basins 34 58Cover crop 23 39

Traditional Deep Tillage 18 31Large Planting Pits 16 27Mulching 5 8Post Irrigation Tillage 5 8Charco Dams 5 8

Application of FYM 3 5Ndiva System 1 2

Ripping 1 2

n = number of respondents

3.4 Intensity of Adoption of WMSIs in Makanya Catchment

Table 6, shows the intensity of adoption of WMSIs. The intensity varies with the toposequence acrossthe Makanya catchment. Generally each household has adopted at least 2 innovations and most of thehouseholds do not go beyond 4 WMSIs per plot. The adoption intensity was found to be higher inlowlands whereby more than 68% of farmers in the lowlands have 4 innovations in their farms. This isdue to the fact that crop production in the lowlands is highly constrained to water and moisture

compared to the midlands and highlands where availability of water and moisture for crop productionis higher. Therefore farmers in the lowlands implement different innovation in the same farm plot tomaximise use of available water and moisture.

Table 6: Intensity of adoption of WMSIs in the Makanya catchment

Intensity of adoption WMSIs TotalCatchment position

2 3 4Lowlands (n = 60) 0 (0%) 18 (30.0%) 41 (68.3%) 59 (98.3%)

Midlands (n = 120) 20 (16.7%) 57 (47.5%) 37 (30.8%) 114 (95%)

Uplands (n = 120) 60 (50.0%) 42 (35.0%) 9 (7.5%) 111 (92.5%)

Total (n = 300) 80 (26.0%) 117 (39.0%) 87 (29.0%) 284 (94.7%)


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3.5 Potential of WMSIs in household livelihoods improvement and poverty reduction

The ultimate aim to adopt and practice improved WMSIs is to increase productivity and income offarmers, which in turn improves the livelihoods of farming households and reduce poverty. In thisstudy the economics of WMSIs entail the physical output (yield), and returns to land and labour frommajor income crops. Various crop enterprises were cited by farmers for income generation. The

economic analysis involved categorization of the yield, and returns to land and labour into respective WMSIs practiced in the production process and seasons. Computational and theoretical insightspertinent to these economic analyses are extensively presented in the methodology manual (Annex B5).Selected crop enterprises under WMSIs practiced in different toposequence in the Makanya Catchmentare analysed and discussed in the following sections. Worth noting, only WMSIs that farmers felt weremajor contributors of the realized income were considered in the economic analysis.

3.5.1. Performance of crop enterprises under different WMSIs in lowland

In the semi-arid lowland lablab is grown as cover crop but also as cash earner exported to Kenya.Results in Fig. 2 show that adoption was higher under runoff diversion system than under bordered

basins and mulching. Mulching and bordered basins WMSIs are in-field practices which do not bring inagricultural water from outside contrary to runoff diversion. The results have shown that in the semi-arid environment supplementation of direct rainfall with externally generated runoff is important.

0.46

0.57

0.69

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

Bordered bas ins Mulching Runoff diversion

Major Water and Moisture System Innovations

Y

ield

(ton/ha)

Figure 2: Yield of lablab under different WMSIs in masikaseason in the lowland

Figures 3 and 4 indicate that farmers earned up to TAS 222,266/ha (US$ 1761) and TAS 202/person-

day from lablab under runoff diversion system. Intermediate and lowest levels of returns were realizedfrom lablab enterprise under mulching and bordered basins. Runoff diversion appears to be mostpreferred over other WMSIs in terms of increased lablab yield and income generation to farmers.

1 1 US $ = 1260 (July 2007)


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116,250

139,500

222,266

0

50,000

100,000

150,000

200,000

250,000

Bordered bas ins Mulching Runoff divers ion

Water and Moisture Systems Innovations

Return

s

to

land

(TAS/ha)

113

154

202

0

50

100

150

200

250

Bordered basins Mulching Runoff divers ion

Major Water and Moisture Systems Innovations

Returns

to

la

bour(TAS/person-day)

Figure 3: Returns to land from lablab underdifferent WMSIs in masikaseason in the lowland

Figure 4: Returns to labour from lablab underdifferent WMSIs in masikaseason in the lowland

3.5.2. Performance of crop enterprises under different WMSIs in the midland

3.5.2.1. Lablab enterprise

In the midland, lablab is grown mainly duringmasikaseason under a range of WMSIs. Fig. 5 indicatesthat the highest yield level of lablab was realized under direct diversion of stream flow followed byndivasystem and under trees-on-farm. Diversion of stream flow through tradition furrow irrigation and ndivaare WMISs with sure and manageable supply of agricultural water. Traditional deep tillage andmulching which do not involve commanding in extra water, apart from the direct rain, recorded theleast yield level of all WMSIs practiced for lablab production. This means, moisture from rainfall ishighly inadequate unless farmers search for supplemental water like diverting run-off or stream flow.

0.44

0.63 0.63

0.86 0.89

1.2

0

0.2

0.4

0.6

0.8

1

1.2

1.4

Traditional

deep tillage

Mulching Runoff

diversion

Tree planting Ndiva Diversion of

stream flow


Yield

(ton/ha)

Figure 5: Yield of lablab under different WMSIs in masikaseason in the midland

Returns in terms of gross margins per unit land and labour were determined by considering the physicaloutput together with input and output prices involved in the production and exchange processes. In the

smallholder family farm, land and labour are key factors of production. Fig. 6 indicates that returns toland from lablab enterprise were the highest under furrow irrigation involving direct channelling ofwater from the stream followed byndivasystem. Although direct diversion of stream flow had higher


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return to land than ndivasystem, the latter recorded lower return to labour than the former (Fig. 7).This difference implies that diversion of stream flow through furrow irrigation practices is more labourintensive than ndiva system. Also ndiva assure more reliable water availability than flowing streamsduring irrigation. The crop fields are not strategically located relative to the position of the stream,always far from this water source hence requiring farmers to dig much longer furrows to direct the

water.

166,563140,812 159,375

256,156318,383

451,655

050,000

100,000150,000200,000250,000300,000350,000400,000450,000500,000

Traditionaldeeptillage

Mulching Runoffdiversion

Trees-on-farm

Ndiva Diversion

of stream

flow


Returnstoland(TAS/ha)

231

126

198 208

566

299

0

100

200

300

400

500

600

Traditional

deep

tillage

Mulching Runoff

diversionTrees-on-farm

Ndiva Diversion

of stream

flow


Returnstolabor(TAS/person-day)

Figure 6: Returns to land from lablab underdifferent WMSIs in masikaseason in the midland

Figure 7: Returns to labour from lablab underdifferent WMSIs in masikaseason in the midland

3.5.2.2. Bean enterprise

The bean legume gave higher yields under trash lines than the same crop under other WMSIs. It is

interesting to note that runoff diversion which involves supplementing the cropland with external waterdid not outsmart other WMSIs in terms of yield. Agronomically, bean legume is prone to water logginghence application of extra water might reduce the yield.

Figure 8: Yield of bean under different WMSIs in vuliseason in the midland

0.26

0.39

0.72

1.13

0.0

0.2

0.4

0.6

0.8

1.0

1.2

Runoffdiversion

Traditionaldeep tillage

Mulching Trashlines


Yie

ld(ton/ha)


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Figure 9: Yield of bean under different WMSIs in vuliseason in the midland

Trash lines recorded higher return to land and labour compared other WMSIs (Figures 9 and 10).Although traditional deep tillage had lower returns to land than that of runoff diversion in case ofreturns to labour the reverse was true. This suggests that runoff diversion is more labour demandingthan traditional deep tillage. Labour intensiveness of runoff diversion might be associated with regularmaintenance of runoff conveyance and distribution canals.

78117

76

457

0

50100

150

200

250

300

350

400

450

500

Runoff

diversion

Traditional

deep tillage

Mulching Trashlines


Returns

tolabor(TAS/person-day)

182,875

96,428144,603

345,625

0

50,000

100,000

150,000

200,000

250,000

300,000

350,000

400,000

Runoffdiversion

Traditionaldeep tillage

Mulching Trashlines



Figure 10: Returns to land from bean under differentWMSIs in vuliseason in the midland

Figure 11: Returns to labour from lablab underdifferent WMSIs in vuliseason in the midland

3.5.2.3. Maize enterprise

Large planting pits performed a bit higher by a difference of 0.08 ton of maize per ha compared totraditional deep tillage (Fig. 11). The two WMSI do not involve outsourcing of water supplementalirrigation. Large pits form depressions around the plants which holds water much longer compared tojust tillage.

0.26

0.34

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

Traditional deep tillage Large planting pits


Yield(ton/ha)

Figure 12: Yield of maize under different WMSIs in vuli season in themidland


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In a reversed trend as compared to yield, large planting pits resulted into lower returns to land andlabour compared to traditional deep tillage. Difference in returns might be attributed to variation ineither or both production costs and producer prices among respective farmers.

Figure 13: Returns to land from maize underdifferent WMSIs in vuliseason in the midland

Figure 14: Returns to labour from maize underdifferent WMSIs in vuliseason in the midland

92

75

0

10

20

30

40

50

60

70

8090

100

Traditional deep til lage Large planting pits


Returnstolabor(TAS/person-d

ay)65,938

61,459

0

10,000

20,000

30,000

40,000

50,000

60,000

70,000

Traditional deep tillage Large planting pits



3.5.3. Performance of crop enterprises under different WMSIs in the upland

3.5.3.1. Bean enterprise

Fig. 14 indicates that bean legume is normally grown under systems which do not involvesupplementation of the direct rain. These systems include stoned grass trash lines, mulching and atypical rainfed system that does not involve any soil and moisture conservation practices. In the

reference vuliseason, bean crop under rainfed system performed better than other WMSIs in terms ofyield. Factors that might contribute to reduced yield of bean legume under stoned grass trash lines andmulching in the sub-humid climate would be fungal disease and insect pests which are favoured thesesystems. Other farmers reported that they planted on steep slopes with stoned/grass trash lines but theperformance was also poor compared to other systems.

Figure 15: Yield of bean under different WMSIs in vuli season in theupland

0.54

0.69

1.49

0

0.2

0.4

0.6

0.81

1.2

1.4

1.6

Trashlines Mulching Rainfed system


Yield(ton/ha)


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The patterns of returns to land from bean enterprise in Fig. 15 resembled that of yield in Fig. 14.Implying that respective yields consistently translated into a similar pattern of returns to land. However,in the case of returns to land, mulching had higher return to labour than other WMSIs. This is becausemulching would tremendously reduce labour intensive operations such as weeding.

2,128

21,019

997

0

5,000

10,000

15,000

20,000

25,000



Returnstolabor(TAS/person-day)

161,667

243,625

621,875

0

100,000

200,000

300,000

400,000

500,000

600,000700,000




Figure 16: Returns to land from bean underdifferent WMSIs in vuliseason in the upland

Figure 17: Returns to labour from bean underdifferent WMSIs in vuliseason in the upland

3.5.3.2. Vegetable enterprise

Economic analysis of vegetables was restricted to returns leaving aside physical yield. This is because anumber of vegetable crops were reported by farmers in different units of weight measurement whichare incomparable in terms of a common average. Farmers involved in vegetables production underndivasystem in vuliseason realised higher returns to land and labour as shown in Figures 17 and 18.

This implies that choice of WMSIs should take into consideration other factors such as croprequirements. Development interventions by NGOs to improve the traditional irrigation systems likendivaencourage them to produce high value crops like vegetables. Results show that venturing in high

value crops like vegetables under capital intensive WMSIs involving storage like ndivawould effectivelyreduce income poverty in water constrained dry lands.

Figure 18: Returns to land from vegetables under

different WMSIs and seasons in the upland

Figure 19: Returns to labour from vegetables

under different WMSIs and seasons in the land

802,000

2,908,125

0

500,000

1,000,000

1,500,000

2,000,000

2,500,000

3,000,000

3,500,000

Stone terrace-masika Ndiva-vuliMajor Water and Moisture System Innovations

Returnstola

nd(TAS/ha)

739

6,613

0

1,000

2,000

3,000

4,000

5,000

6,000

7,000

Stone terrace-masika Ndiva-vuliMajor Water and Moisture System Innovations

Returnstolabor(

TAS/person-day)


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3.5.3.3. Coffee enterprise

Coffee is a perennial crop traditionally grown in the sub-humid highlands. In the sub-humidenvironment, once coffee has established it does not sternly require irrigation but performs better inmoist aerated soil conditions. In view of this, farmers tend to grow coffee under shed of woody trees(agro-forestry) and mulching systems. Yield analysis results in Fig. 19 show that the yield of coffee

under agro-forestry system was bit higher than that of the same crop under mulching.

1.29

1.46

1.2

1.25

1.3

1.35

1.4

1.45

1.5

Mulching Trees-on farm


Yield(ton/ha)

Figure 20: Yield of coffee under different WMSIs in the upland

Figures 20 and 21 indicate that integration of agro-forestry in coffee production resulted into highereconomic returns to land and labour. Apparently, mulching recorded much lower returns to labour

than agro-forestry system implying that the former is labour demanding than the latter. Mulchingrequires labour to collect grass much regularly whereas trees-on-farm is done once over a long time.

The common agro-forestry trees such as Grevilleain coffee farming system can persist in the farm overa decade.

Figure 21: Returns to land from coffee underdifferent WMSIs in the upland

Figure 22: Returns to labour from coffee underdifferent WMSIs in the upland

1,255

21,154

0

5,000

10,000

15,000

20,000

25,000

Mulching Trees-on-farm


Returns

to

labor

(TAS/person-

day)

981,944

1,301,425

0

200,000

400,000

600,000

800,000

1,000,000

1,200,000

1,400,000

Mulching Trees-on-farm


Returns

toland(TAS/ha)


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CHAPTER 4

DETERMINANTS OF ADOPTION OF WMSIs IN THE MAKANYA

CATCHMENT

Water stress is one of the major limitations to agricultural productivity in the Makanya catchment as itaffects both livestock and crop production which is the mainstay of the people in the catchment. Thissituation threatens generation of income, frustrates efforts to attain food security and improvedlivelihoods among rural households. As a coping strategy traditional WMSIs have been used for a longtime. Farmers have adopted different WMSIs at different levels as discussed in chapter 3. However thisadoption is influenced by a number of factors/determinants which either affects it positively thuspromote adoption of more WMSIs and by many farmers or have negative influences and limit it. Thesedeterminants are either natural, physical, human, social or financial related. This chapter will deal with

the different adoption determinants and the way they influence adoption of WMSIs in the Makanyacatchment.

4.1 Determinants of adoption of WMSIs at community level

During focus group discussions farmers mentioned several factors that influence adoption of WMSIs(Appendix A-Table A1). Results show that different innovations have different sets of factors thatinfluence their adoption both positively and negatively. It was also noted that these factors differ alongthe toposequence due to biophysical, socio-economic, cultural and technological aspects of thelocations, communities and innovations per se. Further analysis of the determinants as presented in thetable revealed that the WMSIs can be categorised into two major types: storage and in-situ watermanagement. The findings also showed that determinants that positively influence adoption ofinnovations are mainly biophysical and socio-economic. Between 62.5 and 70% of mentioneddeterminants that positively influence farmers to adopt WMSIs are of biophysical in nature. It was alsofound that between 69.2 to 79% of all the factors negatively affect farmers to adopt WMSIs are socio-economic in nature. These findings suggest that farmers are more motivated by biophysical factors toadopt innovation, but they are constrained by socio-economic circumstances. This implies thatsuccessful promotion of novel technologies to farm and community levels should address socio-economic constraints for smooth uptake of technologies.

4.2 Determinants of adoption of WMSIs at farm level in Makanya Catchment

A farm level analysis of the determinants of technology adoption has centered on the householdsurveys conducted in the study area. It is at the household where most farm level decisions onagricultural production are taken.2 The socio-economic determinants of adoption of agriculturaltechnologies can be grouped into major types as household capital endowments, land tenure, access tomarket and services, population density, government policies and regulation and characteristics of the

2 Some decisions are also taken at community level for management aspects that require implementation by the whole community. Studies oncollective action have analyzed the institutions and other factors that affect adoption of improved management practices at community level, e.g.planting trees, controlling soil erosion, community level irrigation, community grazing land management, etc.


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technology (Feder, et al., 19853; Reardon and Vosti, 19954; Franzel, 1999). This chapter deals with thefirst three types, while chapter 7 takes into account government policies and regulation issues.

4.2.1 Household Capital Endowments

4.2.1.1 Human Capital

This includes assets embodied in peoples knowledge and abilities, such as education, experience, andtraining, family labour, gender of household members, source of income and age of householdmembers. This part deals with education, extra training, labour, gender and the age of household heads.

a. Education of Head of HouseholdResults on the effect of education on adoption of WMSIs are presented in (Appendix A-Table A2). Itshows that there is a positive relationship between education levels and adoption of most innovations.

The most significant relationship was found for those who have basic primary education and more. ThePearson chi squares confirmed the relationship in different levels of significant between 1-10%. Mostsignificant relationship was found in trees-on-farm (P = 0.014). A significant positive relationship was

observed in the adoption of mulching, FYM, fanya juu/chini and charco dam technologies in the headsof households with amore than basic primary education (P < 0.1).

b. Training of the Head of HouseholdResults of additional training of the heads of household are presented in Appendix A-Table A3. Thetraining which the heads of household obtained was categorised in to three, those who did not have anyextra training after basic education, those who attended adult education and those who had vocationaltraining. The results showed that there have been positive significant relationships between kind ofextra training obtained and the adoption of various innovations at different levels between 1 - 10%.

There are some innovations like runoff diversion, mulching, direct diversion of stream flows, valley

bottom and borders that are home grown and have been passed onto from generation to generation asit is indicated in Table 14 (Section 6.1).

c. Family LabourThe major source of manpower in the Makanya catchment is the household members. The more familymembers working on the farm the more likelihood of adoption of WMSIs as it becomes possible toconstruct and maintain them.

The results of the cross tab between family labour and adoption of WMSIs indicate that there is a greatchance of finding adoption of WMSIs in the families with members up to 5 who are fully working on

the farm. This is the case with adoption of run off diversion, cover crop and traditional deep tillage andthe relationship is positive (Table 7). Innovation such as runoff diversion needs labour to maintain thediversion canals. In addition, 40% of household with between 1-3 family members involved in farmactivities have adopted run off diversion while 44.8% of households with 3-5 members involved infarming activities have adopted run off diversion. The same trend is observed with adoption of covercrop technology but a strong relationship is found in the runoff diversion (P = 0.01). A linear by linearassociation (P < 0.1) has revealed a possibility of adoption of traditional deep tillage by household(56%) with no family members who work fully on farm.

3 Feder, G., Just, R.E., Zilberman, D., 1985. Adoption of agricultural innovations in developing countries: A survey. Economic Developmentand Cultural Change 33, 255297.

4 Reardon, T. and S. Vosti. 1995. Links between rural poverty and the environment in developing countries: Asset categories and investmentpoverty. World Development 23(9): 1495-1506


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Table 7: Family labour and adoption of water and moisture system innovations

WMSIs Adoption Members working fully on the farm Pearson Chi-Square

None 1 - 3 3 5 > 5 Value Sig. (2-sided)Runoff diversion Yes N 1 99 13 1 11.290 0.010

% 5.0 40.0 45.0. 100.0

No N 18 146 16 0% 95.0 60.0 55.0 0.0Cover crop Yes N 2 96 12 0 6.340 0.096

% 11.0 39 41.0 0.0No N 16 151 17 1

% 89.0 61.0 59.0 100.0 Traditional deep tillage Yes N 10 149 22 1 2.990* 0.084

% 56.0 60.0 76.0 100.0No N 8 98 7 0

% 44.0 40.0 24.0 0.0* Linear by Linear association

d. Gender of Head of HouseholdGender of the head of household has a chance to influence adoption of certain innovations. Adifference was noted between the female headed households (FHH) and male headed households(MHH) in adoption of WMSIs across the catchment. MHH have adopted more innovations than theFHH. Results in Table 8 show that there are positive relationships between gender and adoption of afew innovations with male headed household having relatively high chances.

Table 8: Gender and adoption of water and moisture system innovations

WMSI Adoption Gender of HHhead

Pearson Chi-Square Fisher's Exact Test

Male Female Value Sig. (2-sided)

Sig. (2-sided)

Sig. (1-sided)

Earth terraces Yes N 45 9 4.080 0.043% 21.0 11.0

No N 168 73% 79.0 89.0

FYM yes N 85 24 0.137 0.074% 39.5 30.0

no N 130 57% 60.5 70.0

Cover crop yes N 74 36 0.138 0.077% 35.0 44.0

no N 140 45% 65.0 56.0

Trash line yes N 34 6 3.605 0.058% 16.0 7.0

no N 180 75% 84.0 93.0

Analysis of the innovations which revealed significant adoption relationships it was observed that

among the MHH, 21.0% of have adopted earth terraces, 39.5% have adopted FYM, 35.0% haveadopted cover crops and 16.0 have adopted trash lines. In the case of FHH, a positive relationship wasobserved in the adoption of cover crop (Fishers exact test for significance, P = 0.077) where by 44.0%


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e

of the FHH adopted the innovation. The likelihood of this finding to happen is based on the fact thatmost women are dealing with leguminous crop which are commonly use as cover crops, in their effortto provide food for their households.

. Age of Head of HouseholdThe age of household head has influence on adoption of WMSIs as indicated in Appendix A-Table A4.Mostly the head of households with more than 50 years of age showed a positive chance of adoptingmost innovations. The Pearson Chi Square statistic indicates that there is statistically significantdifference between the age groups in the likelihood of adopting trees-on-farm (50.0%) at P < 0.01;mulching (56%) at P = 0.031; ndiva (41.0%) at P = 0.012. On the other hand Linear by linearassociation has revealed that the age groups of > 50 has positive relationship in their likelihood toadopt post irrigation surface tillage (3.5%) at P = 0.072; and retention ditch (13.0%) at P = 0.055. Thegroup age of between 36 -50 has shown a positive significant relationship in adoption of post irrigationsurface tillage (29.0% at P = 0.072). Furthermore a positive relation was found between age groups 20

35 of age (23.0%) in adoption of borders at P = 0.060. These findings give a clue that age depicts theexperience a farmer has, though it may not be a direct proportional assumption. However it was found

that most innovations adopted by farmers of age > 50 are indigenous in nature while border, a newintroduction had a positive relationship with younger farmers.

4.2.1.2 Natural Capital

These are stocks of assets embodied in natural resources, including the quantity and quality of land,investment on land such as irrigation infrastructure, soil and conservation structures, trees, and accessto other resources physical assets (e.g., livestock and equipment). However, this part discusses land sizeonly.

a. Land SizeThere is a variation in the sizes of land owned by different households in the catchment. This variesfrom the 0.5 of an acre to about 5. The size also gets smaller, as one goes up the catchment from thelowlands. The size of land owned by a household influences the decision making on the number andkind of WMSIs to be adopted.

The results on the relationship between land size and adoption showed that majority of farmers withland size between 2.25 and 5.0 acres have positive relationship with adoption of WMSIs. The Pearsonchi squares affirm the strength of the relationship (Appendix A-Table A5). Highly significant positiverelationship (P < 0.01) was observed in the adoption of run off diversion (78.0%) for farmers with > 5acres while tree on farm (27.0%) and runoff diversion (46.5%) for farmers with 2.25 -5.0 acres.

Although results showed that RHW tanks and pipes are adopted by only 6.4% of the farmers with 2.25

5.0 acres, they are potential water system innovations in the study area in future. Stoned terraces arepreferred mostly with those who own between 0.75 to 5.0 acres of land. The WMSIs like trees-on-farm,mulching and FYM depicted positive relationship in their likelihood for adoption by households withshortage of land.

4.2.1.3 Physical Capital

This includes physical assets that are used for production of goods and services. They include livestock,buildings, machinery, tools, equipment, furniture, etc. Among these livestock and house type arecovered in this section.

a. Livestock


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Livestock ownership shows to have relationship with adoption of some innovations as presented inAppendix A-Table A6. Since the actual numbers of adoption of various innovations are greater thanexpected values, there is a positive relationship between adoption of innovation and types of livestock.

The Pearson Chi Square statistics indicate that there is a statistically difference between type oflivestock and adoption. The category of farmers owning cattle showed significant and positiverelationship with adoption of most WMSIs. However Sheep and goats owners experienced a good

relationship in run off diversion and borders. This is due to the fact that most livestock owners whopractice run off diversion and borders are located in the lower drier parts of the catchment which isfavourable for sheep and goats. The higher significant levels (P < 0.01) were found on trees-on-farm,mulching, ndiva, FYM, cover crops and retention ditches in relation to cattle owners. This confirmsthat the relationships were not by chance because the innovations are related to cattle production interms of supply of farm yard manure, fodder grass planted on contours, fodder grass left over utilisedas mulches and poles used for building cattle pens.

b. House Type The results on the relationship between house type and adoption of innovations are presented in

Appendix A-Table A7. These show strong relationships between people with houses built using burntbrick and adoption of innovation. However runoff diversion show a positive relationship with those

who own houses built using trees and mud (P < 0.01).

Having a good house gives an indication of well-being within the household. This household is likelyto be endowed with resources which could lead to adoption of desired innovations. The strongstatistical significant values (P 0.05) tell us that the difference in adoption of WMSIs seen betweenthose with good and poor wall type is likely not by chance and therefore house type has gainedevidence towards having a true association with adoption of innovations.

4.2.1.4 Financial Capital

a. Liquid AssetsAppendix A-Table A8 shows the relationship between liquid assets and adoption of WMSIs. A fewinnovations adopted showed positive relationship between having a bank account and their adoption.Higher significances were found in the use of valley bottoms and FYM.

This trend is attributed to the fact that most of the valley bottoms are utilised for vegetable productionwhich also encourage use of a lot of manure. Likely vegetable enterprise earns a lot of cash as shown inchapter 3 (section 3.5.3.2). Some innovations are capital intensive whose adoption needs cash. Forexample, RWH tanks and pipes were adopted by only 11.0% (P = 0.014) and stone terraces (19.0% at P= 0.097) which is likely attributed to availability of finance at a time of adoption.

4.2.1.5 Social Capital

This refers to social organizations such as farmer associations, networks, norms, and social trust thatfacilitate coordination and cooperation for mutual benefits.

b. Farmer Associations and NetworksThe analysis of group meeting the head of household attended has shown relationship with adoption ofinnovations (Appendix A-Table A9).

There has been a strong positive relation between using ofndivaand percentage of meeting attended.Pearson Chi Square statistics showed higher significant levels (P < 0.01) in the midland and uplandareas where ndiva is mostly practiced. The heads of households whose attendance to the meeting


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exceeded 75% showed a good chance of adopting the innovation. Run off diversion was also found tobe related to group networking especially in the midlands (P = 0.46) while post irrigation surface tillage

was significant different in both midland (P = 0.012) and upland (P = 0.000). Stone terraces wereobserved to have positiv

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