cpwf pn 17 workshop, johannesburg, south africa 15-18 june 2009
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Biophysical and socio-economic factors affecting the use of in-situ water harvesting technologies in the semi arid Limpopo Basin: Experiences from Gwanda district, Zimbabwe. CPWF PN 17 Workshop, Johannesburg, South Africa 15-18 June 2009 I. Nyagumbo, M. Munamati, E. Chikwari and D. Gumbo - PowerPoint PPT PresentationTRANSCRIPT
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Biophysical and socio-economic factors affecting the use of in-situ water harvesting
technologies in the semi arid Limpopo Basin: Experiences from Gwanda district, Zimbabwe
CPWF PN 17 Workshop, Johannesburg, South Africa15-18 June 2009
I. Nyagumbo, M. Munamati, E. Chikwari and D. Gumbo Department of Soil Science and Agricultural Engineering
University of Zimbabwee-mail: [email protected]
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1. Introduction
• In-situ water harvesting structures have been promoted in Southern Africa as a solution to drought mitigation in semi-arid regions and are an option to improved agricultural water management by resource constrained smallholder farmers.
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Increasing investment costs
Use of improved seed eg hybrids
Use of organic and inorganic fertilizers
In-situ water conservation & harvesting technologies
e.g. dead level contours, fanya juus, CAtied ridging/ furrows
Supplementary irrigation technologies
eg wetlands, surface irrigation
Hi- tech irrigation TechnsEg dripCostly
Upper limit for shf without capital
Options for improved agricultural water management
Options for improving green water productivity in rainfed systems
Options for bluewater productivity
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1. Introduction continued• In several situations the standard graded mechanical
conservation structures such as contour ridges have been found to be inappropriate due to excessive run-off disposal
• Promotion by NGOs and others particularly in Zimbabwe, has tended to be indescriminate i.e – All soil types (texture, soil depth)?– Topographic conditions?– Rainfall conditions?– All farmers?
• In Gwanda various organizations such as Practical Action, ORAP, ICRISAT and World Vision have promoted their use
• Not much is known about their effectiveness in terms of water conservation and drought mitigation. No hard data!
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1. Introduction continued
• However various options have developed in the last decade eg dead level contours with infiltration pits, fanya juus, deepened contours etc.
• The systems require extra labour compared to standard contours.
• Can we justify these huge labour investments by farmers!
• Could we probably fine tune recommendations for use of such structures?
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1. Fanya juu contour (Chivi, Zim)
• Structures placed at horizontal intervals of 20-30 m depending on slopes• Bank on upper side of slope• May be graded or on true contour
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2. Deepened contours can help to reduce the rate of disposal of excess water
Zvishavane, Southern Zimbabwe
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Contour bank
Infiltration pit
3. Infiltration Pits dug along a standard contour ridge channel
Buhera, Manicaland, Zimbabwe
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4. Dead level contours reinforced with covered infiltration pits
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Farmers believe covering the pits can help to reduce evaporation water losses!
But there is no quantitative data to support this view….!
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2. Study Objectives• To explore biophysical conditions (soil type,
depth, slope and topographic conditions) that characterise successful in-situ water harvesting
• To explore preconditions for success based on farmers experiences
• Refine recommendations for applying in-situ WH systems so as to justify scarce labour investments.
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3. Methodology
• Study carried out in Gwanda district of Zimbabwe (Mat South Province).
• Key partners: Gwanda Rural District Council, Practical Action, Agritex, students
• Studies carried out in Wards 17 & 18 of Gwanda district
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3. Methodology
• Meetings held at ward centres with farmers and community leaders– Key informants identified
• Farmers classified into 3 groups by own peers through group work by village– Very successful– Medium – Poor performers
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3. Methodology
1. Key informant survey: 14 respondents (general constraints and factors, information about users of in-situ WH farmers or respondents
2. Formal survey (55 respondents): socioeconomic characteristics
3. Biophysical survey: 14 sites investigated detailed soil studies of sites : Soil texture, depth, drainage, existence of impermeable bed rock, slopes
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Calculation of resource status• Respondents were classified into 3 resource categories
(wealthy, medium rich, resource constrained) based on 3 criteria
• Range of implement types• livestock value,• land size.
Livestock value • Market prices of livestock prevailing at time of study were used
in the formula (300D+250C+20G+5P)/575T where • figure is price in USD, • D = number of donkeys, C= number of cattle, G= number of goats, P=
number of poultry owned per hhd, • T is total price of individual livestock types
• Range of Implement types referred to the different types of implements owned
• The values from the 3 criteria were then used to classify the respondents into 3 groups.
3. Classification into Resource Categories
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3. Methodology cont’d
Relationships between performance of WHT and the following factors were investigated;– Sex– Resource status– Land size– Field location– Labour numbers– Age– Experience
• Data analysed using various SPSS statistical tools on the 55 respondents data
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4. RESULTS
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Biophysical issues
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4.1 Perceptions of key informants on WHTs
Dead level contours with pits perceived to be most effective (72%)
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4.2 Location and Slopes of WHT fields• Field Location: 50% key informants considered
location as unimportant, 36 % =>homestead fields, 21 % =>far fields. Stats (N=55) showed insignificant correlation bwt success and location of fields. So location was not an important success factor!
• Slope did not seem to matter much (all slopes studied <4%) .However 64 % key informt farmers felt gentle to moderate slopes were prime. Stats based on a small sample of 14 analysed sites suggested slope was insignificant.
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4.3 Area of WHT fields and relationship with total arable area
• A significant linear relationship betwn total arable area and area under WHT (p = 0.000, r=0.84) , see figure below– The bigger the arable area the bigger the proportion put to
WHT
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Relationship between total arable area and that under WHTs (ha)
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• Resource status significantly influenced total arable area (p=0.000) and that put to WHT (p=0.001). Wealthy farmers had the highest total arable area followed by medium rich and lastly resource constrained farmers
• Avg area WHT=1.83 ha
• Avg total area= 4.49 ha
Resource status vs Total arable and Area under WHT
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4.4 Effects of soil typesFarmer class
Geology Soil texture Slope %
Soil depth (cm)
Soil depth limiting material
Inference
Highly successful
(N=7)
Mafic gneiss and dolerite
Coarse Sandy Loam to Sandy Clay loam / Sandy Clay (60 %)
<3 >70(71 %)
Slightly indurated (cemented) to moderately indurated in some cases(71%)
Deep soils hold more water . Limiting material causes bucket effect. Heavy texture enhancing water storage
Medium (N=3)
Mafic and siliceous gneiss
Predominantly Sandy Loam and some Sandy Clay loam(100% medium texture)
<2 <60 Moderately to slightly indurated
Medium texture close to surface. Shallow depth contributing to increased evaporation
Poor performers
(N=4)
Mafic gneissand granite
Loamy Sand to Sandy Loam on surfaces, Sandy Clay Loam in subsoils
<2 <60(100% shallow)
Well to moderately indurated, some slightly indurated
Excessive water loss by evaporation due to shallowness. Light texture not holding much water
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4.4 Effects of Soil types • Most of the best farmers had heavier textured soils
while the poor farmers had light textured soils. 83 % of the respondents key inf. felt deep soils were more effective.
• Shallow depth <60 cm also characterized the poor performers while deep soils >70 cm were more apparent among successful farmers.
N.B.The existence of a slightly indurated parent material seems to enhance the bucket effect but at the same time allowing drainage to take place in excessively wet periods!
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Socio-economic issues
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• Generally there is significant correlation between performance and resource status, at p=0.004
• Within the wealthy category,42.1% are successful, while 14.3% and 13.8% are average and poor performers respectively
• Within the medium rich category, the majority were average performers(57.1%) compared to 42.1% and 34.1% successful and poor performers respectively
– Reason; innovative, capitalise on new opportunities to acquire knowledge and other resources accessible within the community
• Within the resource constrained category, the majority (75.0% ) were poor performers
– Results suggest that wealth status contributes to success or failure in use of WHT
– Medium wealthy people could be best bet investment targets for technology! Drivers of change
4.5 Resource status vs Perfomance
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Sex vs Perfomance• Performance rating was
significantly correlated (p=0.007) to sex of household head.
• Eg Within the most successful group 94.7 % were men compared to 5.3 % women
• In the average performance category, 71.4% men and 28.6% women
• Within sex, 82.4% of women were poor performers compared to 17.6 % in the other categoriess. Only 39.5% men were in the poor cat.
4.6 Links between performance and sex
N.B Widows, hhd with absent husbands disadvantaged, targeting?
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Sex vs Resource status• Sig Pearson correlation
between resource status and sex (p=0.039).
• Within the wealthy category, 69.2% of respondents were men compared to 30.8% women.
• In the medium rich category 86.4 % were men compared to 13.6% women.
• Within sex category most women (58.8%) were resource constrained compared to men (26.3%)
4.7 Correlation btw sex and resource status
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Experience vs Perfomance
• No significant difference in mean years of experience across performance ratings,– Although data tended to
show a decline in performance with decrease in number of years.
– Increasing experience also tended to reflect increase in performance
4.8 Does experience have anything to do with performance?
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4.9 Labour and resource status/ performance
• No significant difference between labour numbers and performance and resource status. Avg per household=6.3 (n=55). However, the majority (93% KI) of the farmers felt labour was a key factor for success.
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4.10 Other issues• The most successful farmers had made
modifications to their systems which included: plastering the bottom of pits, covering the pits to reduce evaporation, altering the depth etc.
• Education and social status did not have any bearing on performance
• A sig. difference (p<0.05) in age between successful and poor performers with the elderly being more successful.
• Average age was 51 years
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5. Any Conclusions?
• Performance of WHTs dependent on soil type:– Best performance is obtainable from deep, heavy
textured soils with some underlying semi-permeable bedrock
• There was no apparent preference in allocation of land for WHTs between homestead and far fields.
• Slope had no apparent effects but could be because study area had limited slope ranges
• The proportion of land under WHTs increased with land ownership and so well resource farmers had more choices.
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5. Conclusions• Resource ownership could be a key factor in farmers ability to scale out WHTs. Performance was
significantly linked to resource status.• Medium wealthy people could be best bet investment targets for technology! • Women headed households were performing rather poorly in WHTs suggesting the need for special
attention to gender in the promotion of WHTs
• The influence of labour on performance was not apparent from the study (methodological limitations!)
• Resource ownership could be a key factor in farmers ability to scale out WHTs. Performance was significantly linked to resource status.
• Women headed households were performing rather poorly in WHTs suggesting the need for special attention to gender in the promotion of WHTs
• Sex, labour and land size are also key factors
• Performance of WHTs dependent on soil type:
• Best performance is obtainable from deep, heavy textured soils with some underlying semi-permeable bedrock
• Study area had limited slopes and so slope had no apparent effects
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6. Next Step!
• Use of GIS tools and Remotely sensed data to assess historical performance of WHTs still to be done but limited by resources
• There is need for more resources for more in-depth studies to demystify performance variation across locations and conditions particularly in Phase 2!
• Department has the zeal!
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Thanks!!