<![CDATA[Domestic wastewater management is a long-term systems problem shaped by population growth, water use, sanitation coverage, treatment capacity, infrastructure deterioration, institutional performance, finance, pollutant generation, and receiving-water conditions. This review synthesizes the use of System Dynamics (SD) for integrated domestic wastewater planning, with emphasis on causal-loop structures, stock–flow models, policy scenarios, pollutant-load estimation, and river-water-quality responses. A structured narrative search covering 2010 to June 2026 was used to identify peer-reviewed studies that applied explicit SD concepts to wastewater, sanitation, water pollution, or coupled water-quality management. The literature shows that most models represent population, wastewater generation, treatment capacity, and pollution control, but fewer integrate on-site sanitation, faecal-sludge pathways, microbiological pollutants, river hydrology, climate stress, finance, and institutional behavior in one model. Scenario analysis is widely used, particularly business-as-usual, capacity expansion, service-coverage improvement, treatment-efficiency enhancement, and combined-policy scenarios. The evidence indicates that isolated infrastructure expansion often underperforms when household connections, operation and maintenance, financing, or treatment efficiency remain constrained. More robust models combine service coverage and capacity dynamics with pollutant mass balance, receiving-water dilution, validation tests, and sensitivity or uncertainty analysis. Coastal and data-limited cities require additional representation of shallow groundwater, infiltration and inflow, flooding, tidal backwater, sea-level rise, and the dominance of on-site sanitation. The review proposes an integrated framework linking socio-demographic, service, infrastructure, treatment, pollutant, river-quality, financial, institutional, and climate subsystems. Future development should priorities spatial SD, participatory modelling, global sensitivity analysis, adaptive policy pathways, real-time monitoring, and hybridization with GIS, hydrological models, optimization, and machine learning.]]>
