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Wastewater characteristics vary significantly across regions due to a combination of climatic, socioeconomic, and infrastructural factors. Understanding these variations is important for accurate influent characterization and the development of region-specific guidelines. This study investigates geographical and regional differences in wastewater characteristics by analyzing influent data from multiple locations, including a detailed comparative analysis between two distinct regions with contrasting environmental and socioeconomic conditions. A comprehensive dataset spanning several years was utilized to examine key wastewater parameters, including BOD, COD, TSS, total Kjeldahl nitrogen, and total phosphorus. To ensure data reliability, preprocessing techniques incorporating machine learning models such as principal component analysis were applied. Statistical methods, including descriptive analysis, ANOVA, and correlation analysis, were applied to assess the variability and relationships between parameters. The results highlight significant differences in wastewater characteristics, not only between geographically distant locations but also within the same country. Whereas climatic conditions influence wastewater characteristics indirectly, socioeconomic factors such as water consumption patterns, industrial activities, and waste disposal practices play a significant role in shaping influent characteristics. These findings highlight the limitations of applying standardized design criteria and regulatory frameworks to wastewater treatment systems without accounting for local conditions. The study emphasizes the necessity of adaptive approaches that integrate regional variability, ensuring more precise influent characterization and enhancing overall system efficiency.