Abstract: Non-Revenue Water (NRW) remains a major challenge to water conservation, financial sustainability, and service delivery in Kenya. This study evaluated NRW reduction strategies employed by Homa Bay Water and Sanitation Company Limited (HOMAWASCO) across four water supply schemes in Homa Bay County. A mixed-methods descriptive design was adopted, guided by the Theory of Competitive Advantage and Natural Resource Use Theory. Data were collected from staff and customers through questionnaires, focus group discussions, field observations, and operational records, and analyzed using descriptive statistics, weighted means, chi-square tests, and thematic analysis. Findings showed that NRW consistently exceeded 40% across all schemes. Among 27 respondents, 55.56% rated real losses as moderate, 29.63% as high, and 7.41% as very high, with 92.59% rating them moderate to very high. Apparent losses were rated moderate by 55.56%, high by 18.52%, and very high by 11.11%. Major causes included ageing infrastructure, leakages, bursts, meter inaccuracies, billing errors, overflows, and illegal connections. Infrastructure rehabilitation was the most effective strategy. The study recommends integrated technical, commercial, and institutional interventions for sustainable NRW reduction.

Hezron O. Agili – Faculty of Biological and Physical Sciences, Tom Mboya University, Kenya

Josephat Okuku Oloo – Department of Geography and Environmental Studies, Moi University, Kenya

Email: njairovirginia@gmail.com / hagili@tmu.ac.ke/ josokuku@mu.ac.ke

Abstract: Drought is a recurring environmental hazard in Homa Bay County, Kenya, affecting agriculture, water resources, and community livelihoods. Despite its impacts, there is limited spatially explicit information on drought-prone areas within the county. This study aimed to map drought vulnerability in Homa Bay County using remote sensing and GIS techniques. The study was anchored on two theories; Disaster risk reduction theory and Vulnerability theory. The study used MODIS NDVI data (2020–2023) to map drought severity, while ESA World Cover land use and CHIRPS rainfall data were integrated as vulnerability factors. A weighted overlay analysis was run in QGIS to combine three factors: drought severity (50%), land use (30%), and rainfall (20%). The final vulnerability map was classified into four classes: low, moderate, mild, and severe. The results show that 0.91% of the county falls under severe vulnerability, concentrated in Mbita and Karachuonyo sub-counties. Moderate vulnerability dominates 53.69% of the county, followed by mild (31.22%) and low (14.18%). The study provides spatially explicit information to support county-level drought planning and intervention strategies. The paper recommends development in severe vulnerable counties; Mbita and Karachuonyo with carefully drought planning and intervention strategies.