School of Agriculture, Environment, Water and Natural Resources Management (JA)

Spatial and statistical analysis of groundwater chemical composition in Mui basin block C, Kitui County, Kenya: Relationships among ph, nitrates, and total dissolved solids

2026-07-09T07:37:46Z

Spatial and statistical analysis of groundwater chemical composition in Mui basin block C, Kitui County, Kenya: Relationships among ph, nitrates, and total dissolved solids Kibos, Nurh K.; Ogondo, Julian A.; Kerandi, Noah M. Groundwater quality assessment is critical for sustainable water resource management in arid and semi-arid regions. This study investigated the spatial distribution and interrelationships among pH, nitrate concentrations, and total dissolved solids (TDS) in groundwater from Mui Basin Block C, Mwingi Central, Kitui County, Kenya. Water samples were collected from all existing 32 sampling points comprising boreholes, shallow wells, and earth dams, representing shallow (1 - 10 m), moderate (10 - 30 m), and deep (>30 m) aquifer systems. Physicochemical analysis was conducted following standard methods, and spatial distribution patterns were mapped using Inverse Distance Weighting (IDW) interpolation in ArcGIS. Statistical analyses, including descriptive statistics, one-way ANOVA, and Pearson correlation, were performed to examine relationships among parameters. Results revealed mean values of pH 7.84 ± 0.89, TDS 964.74 ± 893.76 mg/L, and nitrate 56.11 ± 44.52 mg/L. ANOVA indicated no significant variation in these parameters across different aquifer depths (p > 0.05), suggesting uniform hydrogeochemical processes throughout the basin. Strong positive correlations were observed between electrical conductivity and TDS (r = 0.99, p < 0.01), and moderate correlations between nitrate and salinity parameters. Spatial analysis revealed elevated TDS and nitrate concentrations in the central and southeastern portions of the basin, likely influenced by geological formations, agricultural activities, and limited recharge. The findings indicate that groundwater quality in Mui Basin Block C is primarily controlled by water-rock interactions and anthropogenic inputs rather than aquifer depth, with implications for targeted water quality management strategies in similar semi-arid environments. DOI: 10.4236/gep.2026.146005

Litho-structural mapping via machine learning and geodata on remotely sensed data in the Tharaka-Kanzungo, Kitui-Kenya

2026-05-19T09:09:06Z

Litho-structural mapping via machine learning and geodata on remotely sensed data in the Tharaka-Kanzungo, Kitui-Kenya Odek, Jerald; Boitt, Mark; Thiong’o, Kuria; Kariuki, Patrick C. Litho-structural mapping is critical for resource exploration and hazard assessment, supporting economic development. This study applies Planetscope and ALOS Palser DEM data to conduct lithological and structural mapping in the Tharaka-Kanzungo region of Kenya's Northern Kitui County. The approach integrates support vector machine classification with manual (shaded relief) and automatic (PC Line module) lineament extraction. Planetscope’s high spatial resolution enabled effective rock unit discrimination, while ALOS Palser DEM data enhanced linear-structural analysis. SVM classification achieved 76.24% accuracy and a kappa of 70%, successfully identifying lithologies such as granitoid gneiss, semi-pelitic, calc-silicate, sillimanite-biotite, hornblendite, and crystalline limestone. Comparative results showed automatic methods detected more, shorter lineaments sensitive to texture and vegetation, whereas manual extraction captured fewer, longer, and distinct orientations. Stereographic projections further revealed tectonic features including shear foliations and lineations, aiding tectonic interpretation. The dominant NE-SW and NW-SE trends indicate structural influence on fluid pathways and potential mining zones. The integration of remote sensing techniques with ground-based validation produced a high-accuracy geological map, consistent with existing data. This approach demonstrates strong potential for updating maps and guiding mineral exploration in remote or inaccessible regions. DOI: 10.7176/JEES/15-5-02

Role of Women Farmer Groups in the Adoption of Climate-Smart Agricultural Practices Under Private Sector-Led Extension in Kitui West Sub-County, Kitui County, Kenya

2026-05-05T09:22:28Z

Role of Women Farmer Groups in the Adoption of Climate-Smart Agricultural Practices Under Private Sector-Led Extension in Kitui West Sub-County, Kitui County, Kenya Kilonzo, Boniface K.; Kiruki, Harun M.; Mbala, Simon; Akuja, Thomas E. Smallholder farmers in Kitui West Sub-county, Kitui County, rely heavily on rain-fed agriculture, making them highly vulnerable to climate variability and change. Climate-Smart Agriculture (CSA) provides a sustainable approach to enhance productivity, resilience, and environmental conservation. However, adoption of CSA practices remains uneven, particularly among women farmers, despite their significant role in agricultural production. This study examined the role of women farmer groups in facilitating the adoption of climate-smart agriculture practices under private sector-led extension systems in Kitui West Sub-county. A mixed-methods approach was adopted, involving 196 smallholder farmers selected using Cochran’s sampling formula. In addition, purposive sampling was used to select women farmer groups, extension agents, and key stakeholders for interviews and focus group discussions. Data were analysed using chi-square tests and binary logistic regression in SPSS. The findings revealed that 75.1% of respondents belonged to women farmer groups, and group membership was significantly associated with CSA adoption (χ² = 10.842, p = 0.001). Frequency of meetings, perceived benefits, and discussiontopics were also significantly associated with CSA uptake (p < 0.05). A majority (81.5%) of respondents perceived women farmer groups as critical drivers of CSA adoption. The study concludes that women farmer groups are effective platforms for promoting CSA through knowledge sharing, collective learning, and access to extension services. The study recommends strengthening private sector partnerships, enhancing access to training and financial services, and promoting gender-responsive extension systems DOI: https://doi.org/10.37284/2707-4307

Factors driving the adoption of climate-smart Agriculture Practices Promoted by the Private Sector among Women Farmer Groups in Kitui West Subcounty, Kitui County, Kenya

2026-04-28T06:08:54Z

Factors driving the adoption of climate-smart Agriculture Practices Promoted by the Private Sector among Women Farmer Groups in Kitui West Subcounty, Kitui County, Kenya Kilonzo, Boniface K; Kiruki, Harun M.; Mbala, Simon; Akuja, Thomas E. Climate-smart agriculture (CSA) has been promoted as a smart way of improving farm productivity. However, adoption levels have been low despite concerted efforts by both public and private sector actors. This has been attributed to reduced access to extension services, credit, and markets, especially by women farmer groups who make a significant contribution to the adoption of CSA. By actively involving women, the private sector-led model has far-reaching benefits in that women are usually organised into farmer groups, learn easily, and therefore adopt sustainable agricultural practices with ease. Guided by Diffusion of Innovation Theory, this study explored the potential of women farmer groups in driving the uptake of private sector-led adoption of climate-smart agriculture practices. A mixed-method approach was used, where qualitative research entailed data collection through interviews with 19 women farmer groups, private sector representatives, and stakeholders, while the quantitative method involved administering questionnaires to 196 farmers. Collected data was analysed using the Statistical Package for Social Sciences (SPSS) software. Results indicated that women farmers belonging to organised groups were more likely to adopt CSA practices than non-members (p < .05). The findings also revealed that women farmer groups play a facilitative role by enabling peer learning, resource pooling, and collective engagement with private sector actors. Results showed that women with access to institutional support, particularly extension and credit services, were more likely to adopt CSA practices than those without such support (p < .05). The study recommends strengthening private sector–led training and extension initiatives with a deliberate focus on women farmer groups. Second, policies should prioritise the formation and strengthening of women farmer groups as a strategy for scaling CSA practices. Third, government and development partners should enhance access to affordable credit and inputs through gender-responsive financing mechanisms to address key institutional barriers. DOI: https://doi.org/10.37284/eajab.9.1.4880