Managing water supply systems is essential for developing countries to face climate variability in dryland settings. This is exacerbated by high energy costs for pumping, water losses due to aging infrastructures, and increasing demand driven by population growth. Therefore, optimizing the available resources using a water–energy nexus approach can increase the reliability of the water distribution network by saving energy for distributing the same water. This study proposes a methodology that optimizes the Water Distribution Network (WDN) and its management that can be replicated elsewhere, as it is developed in a data-scarce area. Indeed, this approach shows the gathering of WDN information and a model to save energy by optimizing pump schedules, which guarantee water distribution at minimal operational costs. The approach integrates a genetic algorithm to create pumping patterns and the EPANET hydraulic simulator to test their reliability. The methodology is applied for a water utility in the dryland urban setting of Lodwar, Turkana County, Kenya. The results indicate a potential reduction in energy costs by 50% to 57% without compromising the supply reliability. The findings highlight the potential of WEN-based solutions in enhancing the efficiency and sustainability of data-scarce water utilities in dryland ecosystems.

Water scarcity, climate variability, and increasing water demands are placing growing pressure on water supply and distribution systems, particularly in water-scarce environments. Optimization-based approaches have become central to improving system design, planning, and operation. This study presents a structured review of optimization techniques applied to water distribution systems under conditions of scarcity, intermittency, or aridity, and introduces a context-aware classification framework incorporating system scale, population, and scarcity severity. PRISMA (“Preferred Reporting Items for Systematic Reviews and Meta-Analyses”) principles are adopted. Relevant studies are identified through Scopus and Google Scholar, screened using criteria focused on system type, optimization relevance, and explicit consideration of scarcity, intermittency, or aridity, and classified by optimization stage, methodological approach, geographical context, and main findings. The review is dominated by benchmark network studies under water scarcity, while real-world applications in arid regions, such as Sub-Saharan Africa and parts of the Middle East, remain underrepresented. Deterministic least-cost designs are inadequate under water scarcity, whereas multi-objective approaches deliver more reliable systems. The review shows a mismatch between the optimization focus of the benchmark studies, which is mainly in the design phase, and the real-world applications, which mainly focus on optimization of the operations of the existing systems.