farmers’ willingness to pay for irrigation water system as a mechanism for sustainable watershed...
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FARMERS’ WILLINGNESS TO PAY FOR IRRIGATION WATER SYSTEM AS A MECHANISM FOR SUSTAINABLE WATERSHED
MANAGEMENT AND ENHANCED FOOD PRODUCTION IN KERIO VALLEY BASIN KENYA
By
Jonah Kipsaat Kiprop, Job Lagat and Patience Mshenga
9 th EGERTON UNIVERSITY INTERNATIONAL CONFERENCE
25 th -27 th March 2015
EGERTON UNIVERSITY, KENYA
Kiprop et al .,2015
Outline
Background InformationResearch issue/ Statement of the ProblemObjectives of the studyStudy areaMethodologyResultsConclusions and Recommendations
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Background Information
Water is a vital resource in enhancing agricultural production in Kenya
However, given the unreliable rains, irrigation is critical in increasing and sustaining agricultural productivity
With climate change projected to account for 20 percent of the global increase in water scarcity (FAO-COAG, 2007). There is need to formulate policies that ensures efficient allocation of water.
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Background Information
Kenya is classified as a water deficit country with water resources unevenly distributed in space and time (ASDS, 2010-2020)
Only 17 % of the land area is high potential thus receiving adequate rainfall the remaining land is arid and semi-arid and cannot support crop production without irrigation
The Government has acknowledged the relevance of irrigated agriculture, in this regard it is a key component of Agricultural Sector Development Strategy of 2010-2020 towards achieving Vision 2030.
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Background Information
Irrigation in Kenya is mainly carried out in irrigation schemes with smallholder schemes accounting for 42% while government managed schemes account for 18% (RoK, 2010)
Only a small fraction 1.8% of crop land in Kenya is under irrigation while there lies a great potential of 1.3 million hectares (NIB, 2012) as illustrated in the figure below.
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Irrigation potential in Kenyan basins
Tana Athi Lake Victoria Kerio Valley Ewaso Ngiro0
50,000
100,000
150,000
200,000
250,000
Kenyan basins
Are
a in
Ha
Source: National Irrigation Board (NIB), 2012
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Policy efforts In the past a lot of efforts and funds were directed in
expanding smallholder irrigation schemes, however most schemes failed due to lack of self-sustaining systems
The Draft Water Policy of 2010 emphasized the need for enhancing the capacity of farmers to own, manage, and finance irrigation schemes through formation of Irrigation water users’ associations (IWUA’S)
Water pricing as an economic instrument that has been used worldwide to improve water allocation and to enhance sustainability in management of irrigation schemes (Bazza, 2002).
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Water Policy: Treating water as an economic goodDublin Principles and IWRM—approach recommended
for MDGs
2002 World Summit on Sustainable Development in Johannesburg
2003 Third World Water Forum
2006 World Water Development Report
Human Development Report 2006 Beyond scarcity: power, poverty and the global water crisis
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What do we mean by ‘economic value?’
A commodity has an economic value when people are willing to pay for it, rather than go without it is a monetary measure of the intensity of individual preferences (needs, wants, desires)
Market goods
◦ Observed equilibrium market prices represent the willingness-to-pay
Non-market goods
◦ Benefits are based on individual values in the form of willingness-to-pay (WTP) and their aggregation across all affected individuals
◦ Costs are the value of the opportunities forgone because of the commitment of resources to a project, or the willingness-to-pay to avoid detrimental effects (damages).
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What do we mean by ‘economic value?’
Water’s value is the willingness to pay for water
It is observed when people make a choice between different products• How much will a household pay for
drinking water?• How much will a farmer pay for
irrigation water?• How much will a factory pay for
clean water? Kiprop et al 2015
Most commonly used water valuation techniques
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Frequency of water valuation studies Most common methods used
Residual value (and variations)Production functionCVM, programming models
Manufacturing UncommonProduction function, programming
Hydroelectric power CommonProgramming models, opportunity cost
Waste assimilation services Common
Cost of prevention, Benefits from damages averted
Agriculture Most common application
Research Issue
Elgeyo Marakwet County has a long history of traditional furrow irrigation being practiced on the Kerio basin dating back to 400 years ago (Kipkorir, 1983).
Despite the traditional system bringing development in the past, it was inefficient in water use (Chepkonga et al., (2002).
Currently the traditional systems are being upgraded to modern systems, under this new arrangement water users will pay a fee under the management of the irrigation water users associations.
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Research Issue
Being a new system little is documented on how farmers will react to introduction of water pricing
.
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Transition from Traditional Irrigation system to Modern system
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Research objectivesGeneral objective
To contribute to the sustainable management of irrigation water in community managed smallholder irrigation schemes, by establishing an effective water pricing mechanism
Specific objectives
1. To determine the socio-economic factors which influence the farmers’ willingness to pay for irrigation water in the Kerio valley basin
2. To assess how much farmers’ are willing to pay for irrigation water in the Kerio valley basin
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Conceptual framework
Institutional factors• Access to credit• Membership in IWUA• Land tenure system• Access to extension
service Farm and
farmers characteristics’• Age of
farmer• Education
level• Farm size• Occupation • income
Attributes of the new system of irrigation
• Minimal repair costs• Irrigation land coverage
Outcome• Improved management of water
resources.• Reduced water conflicts• Reduced water wastage• Increased land under irrigation• Enhanced food production
Not willing to pay
Farmers’ willingness to pay for irrigation water
Farmers’ perceptions on paying for irrigation water
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MethodologyStudy area
The study was undertaken in Elgeyo Marakwet County.
216 smallholder irrigation farmers were sampled from
Arror irrigation scheme
The major crops food grown are maize, mangoes bananas,
sorghum, millet and cowpeas. Cotton is grown cash crop
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Map of the Study Area
Source: www.wri .org
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Analytical frameworkObjective 1: To identify the factors which influence
farmers’ willingness to pay for irrigation water.
The classical Probit model was used to identify the socio-economic factors that influence farmers’ decision to pay or not to pay for irrigation water.
The outcome equation was;
Willingness to pay(Yi) = β0+ β1Agehh+ β2Edulevelhh+ β3Farmsize+ β4Croptype+ β5Perc-mai+ β6Distmkt+ β7Famlysize+ β8Tlu-own+ β9Crd-acc+ β10Ext-ctc+ β11Income-irr+ β12Tot-income+ β13Traing+ β14Expr-irr+ β15Memb-iwua+ β16Prox-water+ β17Perc_mai+ ε
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Analytical framework
Objective 2: To determine the farmers’ mean willingness to pay for irrigation water in the Kerio Valley basin.
The double bounded contingent valuation method was used to value the water resource since there is no market for irrigation water in the area.
Once the farmer made the choice to pay, the next decision was to determine the amount of payment (intensity) in Kenyan Shillings.
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If the respondent replies “no’’ for the first bid, then further discussions on the payment are terminated.
On the other hand if the respondent’s choice is ‘’yes’’ then a second question is posed with a starting bid value. If the payment choice for Kshs, is ‘’yes’’ then the respondent will face another level of bid choice, which would be higher or lower amount, respectively.
This second amount (bid) is based on the response of the first bid (if the response for the first is yes, then the following bid will be double the first one and half if otherwise).
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The probabilities of the outcomes can be represented by p (yy); p (nn); P (yn); and p (ny) for “yes”, “yes’’, “no”, “no’’, “yes”, “no’’ and “no”, “yes’ ’outcomes respectively. Following Hanemann et al. (1991), these likelihoods can be represented mathematically as;
The probability of “ no, no” outcome is represented as: Pnn(Bi
1,Bi1) = P (Bi
L >Max.WTP and BiL >Max.WTP) = G(Bi
L,ɵ)
The probability of “yes, yes” will be: Pyy(Bi
1,BiU) = P (Bi
L >Max.WTP and BiU >Max.WTP) = G(Bi
U,ɵ)
When a “yes” is followed by “no” we have:
Pyn(Bi1,Bi
U) = P (BiL <Max.WTP ≤ Bi
U ) =G(BiU, ɵ) − G(Bi
L, ɵ)
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When a no is followed by a yes response the probability is :
Pny(BiI,Bi
L) = P (BiI >Max.WTP≥ Bi
L ) =G(BiI, ɵ) − G(Bi
L, ɵ)
With a sample of N observations where B is the various bid values the outcome equation is;
L(ɵ) = Ʃ diyy .Pyy (Bi
1,BiU) +di
nn.Pnn(BiI,Bi
L) + diyn .Pyn (Bi
1,BiU)
+diny.Pny(Bi
I,BiL)
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Variable Variable Code
Types of variable
Unit of Measurement of the Expected sign
Dependent variables
Willingness to pay for irrigation water WTP Dummy 1 for those willing to participate and 0 other wise
Independent variables
Education level of household head EDULHH Continuous Years -
Age of household head AGEHH Continuous Years -
Type of crop Grown CROP-TYP Dummy 1 if cash crops are produced,0 otherwise
+
Perception about operation and maintenance PERC-MAI Dummy 1 if perceived,0 otherwise +
Distance from the market DIST-MKT Continuous Kilometre -
Household family size FAMSIZE Continuous Number of persons in a household +/-
Livestock ownership TLU-OWN Continuous Number of livestock owned +/-
Access to credit service CRD-ACC Dummy 1 if accesibles,0 otherwise +/-
Access or contact with extension service EXT-CTC Dummy 1 if accessible , 0 otherwise +
Income from irrigated farm INCOME-IRR
Continuous Kenyan Shillings +
Access to training TRAING Dummy 1 Trained,0 otherwise +
Membership in irrigation water users association
MEMB-IWUA
Dummy 1 Member, 0 otherwise +
Proximity to water source PROX-WS Continuous Kilometre -
Perception and observation about maintenance problem
PERC_MAI
Dummy
1 if perceived, 0 otherwise
+/-
Description of variables and the expected Signs to be used in the models
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Results
Approximately 91.4% of the smallholder farmers were willing to pay for irrigation water with a mean Willingness to pay of Ksh 938 per production season.
This represents about 9.6% of the average total farm income.
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Factors Influencing farmers decision on WTP
Variables Coefficient Std. Err. z
Education level 2.88 1.34 2.14**
Age of farmer -0.017 0.023 -0.74
Participation in construction 1.50 0.75 2.01**
Household size 0.25 0.18 1.42
Gender of household head -0.74 0.71 -1.03
Distance to the market -0.35 0.12 -2.76
Total livestock ownership 0.008 0.015 0.54
Access to credit service -0.064 0.90 -0.07
Access to extension service -1.64 0.83 -1.97**
Total income from irrigated farm 5.80 1.53 3.79**
Access to agricultural training 1.88 0.71 2.62
Membership in (IWUA) 1.72 0.81 2.10**
Distance to water source -0.352 0.12 -2.88*
Constant 4.18 1.62 2.58*
N 216
LR χ2 95.10
Prob> χ2 0.000
Pseudo R2 0.7707
Log likelihood -14.143*, **, *** significant at 10, 5 and 1 percent level, respectively
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Factors influencing farmers mean willingness to pay for irrigation water
Variable Coefficient Std. Err. z
Age of farmer -30.27558 6.061803 -4.99**
Household size 109.3838 33.70524 3.25*
Membership in IWUA 76.38428 238.9641 0.32
Access to credit 2.598333 174.4956 0.01
Access to extension -423.3809 230.2513 -1.84
Access to training -136.5829 186.0542 -0.73
Participation in construction 282.9909 220.926 1.28
Distance to water source -97.71583 38.67595 -2.53**
Distance to the market -68.43047 28.59172 -2.39
Total livestock owned 0 .0151607 2.556768 0.01
Income from irrigation 53064 .0020247 2.62*
Constant 938.4346 560.7905 1.67***
Number of observations 197
F(14, 120) 15.78
Prob >F 0.000
R-squared 0.6461
Adjusted R-squared 0.6081
*, **, *** significant at 10, 5 and 1 percent level, respectively
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Conclusions and Recommendations
More capacity building initiatives such as training and field days should be undertaken to enhance the farmers’ willingness to pay
Establishing a feasible water charging system in the schemes such as the volumetric basis of water charging will be helpful.
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Conclusions and Recommendations
The water users associations should be strengthened through training of technical staff such as plumbers who will ensure water systems are properly maintained
Adequate extension support should be delivered more specifically on irrigation farming so that farmers would be able to make efficient use of their irrigated land
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Conclusions and Recommendations
Implementing an irrigation water management system that ensures equitable water distribution and effective enforcement of existing rules and regulations, would not only enhance the farmers’ willingness to pay but also the amount they would commit
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Acknowledgements
African Economic Research Consortium (AERC) for their funding the research through the CMMAE program
Department of Agricultural Economics and Agribusiness Management Egerton University
KVDA field staff
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THANK YOU
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