Review of methodologies to assess and evaluate the climate resilience of rural community-managed drinking-water supply systems in low-income contexts
Abstract
In 2024, approximately 1.37 billion people worldwide living in rural and peri-urban areas remain without safely managed drinking water, with rural populations in Least Developed Countries (LDCs) being disproportionately affected, where 69.7% lack access. In these contexts, water supply is predominantly provided through self-supply systems, household- and community-managed, due to the absence of consistent government service provision. While these systems play a critical role in ensuring access, they are particularly vulnerable to climate change. Ensuring water safety and security in developing countries therefore requires the promotion of resilient water supply systems and empowered communities. Water system resilience depends not only on technological solutions but also on social, institutional, environmental, economic, and anthropological dimensions. Although a variety of tools and methodologies have been developed to assess and enhance the resilience of drinking water systems, few are specifically designed for rural, community-managed systems in low-income countries or adequately address the skills and enabling environments required for their effective implementation. This study presents a critical review of peer-reviewed literature, published guidance, and case studies focused on rural drinking water systems in developing countries. The review systematically organizes and analyses existing resilience frameworks and tools, highlighting significant gaps in contextual relevance. The findings underline the need for tailored, context-specific approaches that integrate elements from multiple methodologies and are grounded in an in-depth socio-cultural understanding of rural communities. These insights provide practical guidance for researchers, practitioners, and decision-makers seeking to move beyond risk diagnostics toward resilient, community-centered water service transformation.
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