Understanding Heterogeneity in Adaptation to Intermittent Water Supply: Clustering Household Types in Amman, Jordan

2025-08-04

AI Summary

Over one billion people globally experience intermittent water supply (IWS), exacerbating intra-urban inequality. While existing studies predominantly focus on income-based disparities, they overlook the multidimensionality and nonlinear heterogeneity of household characteristics. This paper addresses this gap by developing a standardized analytical framework—integrating hierarchical clustering analysis (HCA) with Welch’s t-test—applied to multidimensional survey data from Amman, Jordan. The method identifies statistically distinct household adaptation clusters, moving beyond unidimensional income metrics to reveal how social networks, perceived water quality, and other factors jointly shape heterogeneous coping strategies. Three qualitatively distinct household groups emerge, differing significantly in interruption response patterns, financial burden, and underlying vulnerability mechanisms. The framework is transferable across contexts, offering a novel paradigm for analyzing structural inequities under IWS.

Technology Category

• Application Domains: Humanities & Computational Social Science
• Data Mining & Knowledge Management: Anomaly/Outlier Detection
• Constraint Satisfaction and Optimization: Distributed CSP/Optimization

Application Category

• Social Networks and Social Media: Social media analysis through the lenses of networks
• Web Mining and Content Analysis: Bridging structured and unstructured data
• Systems and Infrastructure for Web, Mobile and WoT: Web performance, measurement, and characterization

Abstract

More than a billion people around the world experience intermittence in their water supply, posing challenges for urban households in Global South cities. An intermittent water supply (IWS) system prompts water users to adapt to service deficits which entails coping costs. Adaptation and its impacts can vary between households within the same city, leading to intra-urban inequality. Studies on household adaptation to IWS through survey data are limited to exploring income-based heterogeneity and do not account for the multidimensional and non-linear nature of the data. There is a need for a standardized methodology for understanding household responses to IWS that acknowledges the heterogeneity of households characterized by sets of multiple underlying factors and that is applicable across different settings. Here, we develop an analysis pipeline that applies hierarchical clustering analysis (HCA) in combination with the Welch-two-sample t-test on household survey data from Amman, Jordan. We identify three clusters of households distinguished by a set of characteristics including income, water social network, supply duration, relocation and water quality problems and identify their group-specific adaptive strategies such as contacting the utility or accessing an alternate water source. This study uncovers the unequal nature of IWS adaptation in Amman, giving insights into the link between household characteristics and adaptive behaviors, while proposing a standardized method to reveal relevant heterogeneity in households adapting to IWS.

Problem

• Analyzing household adaptation to intermittent water supply heterogeneity
• Identifying multidimensional factors influencing water adaptation strategies
• Developing standardized clustering method for cross-setting IWS analysis

Innovation

• Hierarchical clustering analysis for household classification
• Welch-two-sample t-test to validate cluster differences
• Multidimensional survey data analysis for adaptive strategies