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

Department of Soil Science and Agricultural Engineering University of Zimbabwe e-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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Options for improved agricultural water management Hi- tech irrigation Techns Eg drip

Costly

Upper limit for shf without capital Supplementary irrigation technologies eg wetlands, surface irrigation In-situ water conservation & harvesting technologies e.g. dead level contours, fanya juus, CA tied ridging/ furrows

Options for blue water productivity

Use of organic and inorganic fertilizers Use of improved seed eg hybrids

Options for improving green water productivity in rainfed systems

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Increasing investment costs

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 6

2. Deepened contours

can help to reduce the rate of disposal of excess water

Zvishavane, Southern Zimbabwe

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3. Infiltration Pits dug along a standard contour ridge channel

Contour bank Infiltration pit

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 harvesting

in-situ

water • 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 12

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 14

3. Classification into Resource

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 . 15

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

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 21

Relationship between total arable area and that under WHTs (ha) 16,00 14,00 12,00 10,00 8,00 6,00 4,00 2,00 0,00 0,00 2,00 4,00 y = 0,8032x + 0,1817 R² = 0,786 6,00 8,00 10,00 12,00 Total arable land area (ha) 14,00 16,00

Resource status vs Total arable and Area under WHT •

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

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Farmer class Highly successful

(N=7)

4.4 Effects of soil types

Geology Soil texture

Mafic gneiss and dolerite Coarse Sandy Loam to Sandy Clay loam / Sandy Clay

(60 %)

Slope %

<3

Soil depth (cm)

>70 (71 %)

Soil depth limiting material

Slightly indurated (cemented) to moderately indurated in some cases (71%)

Inference

Deep soils hold more water . Limiting material causes bucket effect. Heavy texture enhancing water storage

Medium (N=3) Poor performers (N=4)

Mafic and siliceous gneiss Mafic gneiss and granite Predominantly Sandy Loam and some Sandy Clay loam (

100% medium texture)

Loamy Sand to Sandy Loam on surfaces, Sandy Clay Loam in subsoils <2 <2 <60 <60 (

100% shallow

) Moderately to slightly indurated Medium texture close to surface. Shallow depth contributing to increased evaporation Well to moderately indurated, some slightly indurated Excessive water loss by evaporation due to shallowness. 24 holding much water

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

4.5 Resource status vs Perfomance

• 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

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targeting?

• 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.

• Sig Pearson correlation between resource status and sex (

p=0.039

).

• • Within the wealthy category,

69.2

compared to % of respondents were men

30.8

% women. • In the medium rich category

13.6

86.4

% women.

% were men compared to

Within sex category most women (58.8%) were resource constrained compared to men (26.3%)

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performance?

• 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 30

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.

7,0 6,8 6,6 6,4 6,2 6,0 5,8 5,6

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Wealthy Medium rich Resource status resource constrained

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 32

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

. 33

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!) 34

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!!

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