On-site sanitation systems (OSS), such as pit latrines, are an important source of methane (CH₄), with emissions increasing when they are wet, and this occurs when anaerobic conditions dominate. This paper presents the development of a model, which uses seasonal changes in groundwater to account for the fluctuating inundation of pit latrines, and, therefore, the associated CH₄ emissions from varying degrees of anerobic conditions are examined. Given that observed timeseries of groundwater table depth at high enough spatial and temporal resolutions are often difficult to obtain in low- and middle-income countries (LMICs), inverse distance weighted (IDW) interpolation is used to generate values for a whole region, which is then used, alongside average pit latrine depth, to determine areas of pit latrine inundation. Outcomes are further informed with open-source contextual data, covering population, urban/rural split, and sanitation facility data, before using methodologies from the Intergovernmental Panel on Climate Change (IPCC) to generate CH₄ emissions data. As a case study, we use data from Senegal to illustrate how this model works. Results show total CH₄ emissions for the month of January to be ~1.69 kt CH₄. We have also discussed the potential use of satellite remote sensing data in regions where access to historical groundwater data is limited. Understanding when the pit conditions are most likely to change could lead to incentives for better management strategies, as well as a reduction in CH₄ production.