Municipal water systems in Senegal face challenges related to adoption rates, necessitating robust methodologies for evaluation and forecasting. A comprehensive time-series analysis was employed, incorporating SARIMA (Seasonal AutoRegressive Integrated Moving Average) for forecasting. Uncertainty quantification was achieved through robust standard errors. The model demonstrated a clear trend towards increased adoption rates over the past decade, with a 30% increase observed in urban areas compared to rural regions. This study provides a validated methodological framework for assessing municipal water system adoption rates in Senegal, offering insights into future policy and resource allocation. Further research should explore long-term trends and potential interventions based on the identified patterns of adoption rate changes. Senegal, Municipal Water Systems, Forecasting Model, Adoption Rates, Time-Series Analysis The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.