**3.1 CA adoption in Chivi**

*Natural Hazards - Impacts, Adjustments and Resilience*

within the CA project.

**2. Methodology**

increase agricultural productivity under diverse climatic conditions. The same CA project in Chivi, was implemented in Zambia and increased crop yields by 240 to 400% [4]. In Kenya, Ghana and Malawi agricultural profitability increased [5–7]. Despite all this success CA project in Chivi has been characterized by conflict and contestations and its adoption has been very slow [8, 9]. It is within this breadth that this chapter seeks to assess CA adoption in Chivi and establish the weaker lines

IPCC's climate change projections predicting an increase in temperatures and acute rainfall shortages in southern Africa of between 1.5°C to 2.5°C under the 2.0°C GWL and 10 to 20% reduction in precipitation, it is crucial to draw sustainable adaptation strategies and improve resilience in rural communities, which are more vulnerable [10]. This research also unveils factors affecting the adoption of CA and

The effectiveness of a new technology depends on its adoption and also the project's adoption levels reflect on its strength thus convenience and usefulness in the user's interpersonal networks [11]. Adoption is defined "as the extent to which farmers put into practice a new innovation, given adequate information about the technology and the potential benefits" [12]. The Tradeoffs model inform that farmers are rational beings and only adopt a new system of agriculture if it's more

The data used in this chapter was elicited from 140 household questionnaires administered across 16 wards of Chivi District and focus group discussions held in six wards of Chivi district. This data was also supported by data from key informant interviews held with three Non-Governmental Organisations (NGOs) and 16

Data capturing was organized in Microsoft Excel 2013 and later transferred to Stastical Package for Social Science (SPSS). Prior to the analysis, captured data was coded according to the levels of measurement. This allowed for uni- and bivariate data analyses. Data analysis was done using SPSS version 22. Chi square and Cramer's V value were calculated and analysis was set at 0.05 confidence level. In order to describe and identify relationships that must be taken into account and characterise CA project in Chivi District, frequency tables and bar graphs were generated (univariate analysis). Frequency distributions described the number of times the different attributes of a variable were observed in a sample. This allowed for the comparison of different variables. Statistical tests of significance were conducted on the levels of awareness and general perceptions in order to explore independent variables e.g. gender; age; level of education differences. Chi-square tests was used to calculate significant differences in different demographic groups on their adoption and practices in the Conservation Agriculture project [14]. A 95% level of signifi-

viable [13]. This chapter sought to evaluate the adoption of CA in Chivi.

enhance its effectiveness as an adaptation strategy to drought.

Agricultural Research and Extension (AREX) officials.

cance was used, which is most commonly used in social research [15].

strength of the relationship is considered strong [16].

Cramer's V test was used to measure the strength of relationships. It measures the strength of relationship for any size of contingency table, and it offers good norming values from zero to one (0–1) for relative comparison of the strength of correlation regardless of the table size. For Cramer's V, 0.0 to 0.30, the strength is considered no relationship to weak; for Cramer's V, 0.31 to 0.70, the strength is considered moderate relationship; while for Cramer's V from 0.71 to 1.0, the

For qualitative data analysis, Archive of Technology, Life world and Language.

Text interpretation (Atlas.ti 8) was used to analyse data from the household

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The physical adoption of the CA project was measured based on project adoption records of NGOs operating in Chivi district.

Only 30% of households in Chivi are practicing CA, refer to **Figure 1**. AREX officials and Focus Group Discussants showed that CA started as early as 1995 in some wards such as Ward 10 but became more popular from 2008 when the government of Zimbabwe formalized it. This implies that the project has been long operating in the District, despite low adoption percentage. However, CA benefits are normally realized at least after 10 years of practice [17]. Hence a 30% adoption is not that low, considering that the project is formally slightly over a decade in most wards. After seeing the benefits more farmers are likely to adopt CA. However data on CA adoption trends did not support this. Key informants confirmed a decline in adoption trend over the years in all wards. In ward 21 of the 300 farmers who initially adopted CA in 2008 only 80 are currently practicing it. Of interest is that Ward 21 was listed as the third highest adopter of CA in the District by NGOs. This gives a gloomy picture to the sustainability of CA as a drought risk reduction tool in the District.

#### **3.2 Extension of CA plots**

To get an insight into the spatial adoption of CA and the long term plans of farmers on CA, plot sizes were also assessed. Key informants showed that farmers under the main NGO, CARE increased their demo plots from the 18 mother demo plots of 1 hectare to 180 baby demo plots across its 12 wards. However the questionnaire survey showed that 100% of CA farmers are still working on demonstration plots in groups and have not adopted the full CA package onto their individual

**Figure 1.** *CA adoption in Chivi.*

plots. However 100% admitted to have adopted at least one of the CA principles and are using them in their conventional agriculture system. 52% of these farmers adopted planting on time, 80% crop rotation and 38% use of small grains. No CA farmers have adopted planting basins and mulching onto their traditional systems. NGOs supported these findings and added that planting basins and mulching principles are the most unpopular. These two principles could be the hindrance to effective adoption of CA as a disaster risk reduction tool in Chivi.
