For decades, there has been ongoing discussion about whether centralized or decentralized wastewater management systems are better. Decision-makers need to define the best option but do not always have the necessary tools to develop, compare, and identify the most appropriate solution. To address this, studies have been conducted on a settlement level. In this study, the main focus was to develop and optimize wastewater management scenarios for a region containing rural areas, where data scarcity was an issue, by extracting scenario-relevant information from the region using a satellite image and its calibration using locally available data. We selected a study region in India containing 184 villages with a total population of around 210,000 and covering an area of around 400 km². The study considered three different scenarios for the study area: centralized, decentralized, and an optimized scenario, which consists of a hybrid system involving partly decentralized and partly semi-centralized (clustered) infrastructure. The study developed a systematic approach for defining an optimized cluster of villages by considering the cost trade-off between the wastewater treatment plant (WWTP) capacity and sewer network layout. The results showed that the clustered and decentralized scenarios were nearly equal in terms of cost (around EUR 118 million), while the centralized scenario showed a relatively high cost of EUR 168 million. Potential applications and further development of the method were also considered. The proposed methodology may aid global wastewater management by estimating and optimizing infrastructure costs needed to fulfill Sustainable Development Goal 6 (SDG#6) in rural regions.