Water pollution has recently emerged as one of the big global issues due to its impact on people’s lives and the environment, posing substantial human health risks. Geospatial methods, strategies, and technologies to collect or analyze spatial data are very important tools used for purposes in fields like water quality monitoring, wastewater management, hydrology applications in general (for example, rainfall), urban planning, and public health. Common methods for this type of approach include remote sensing, geospatial information systems (GIS), and spatial statistics. By leveraging such technologies, we gain valuable information on where and how pollution sources are distributed in space and time; the levels or concentrations of pollutants recorded by these devices also help us estimate incidences that may be detrimental to human health as well as the surrounding ecosystem. For example, remote sensing can be used to collect data on wastewater quality and pollution sources. Remote sensing can map the spatial distribution characteristics of water pollution, which can be realized by satellite and aerial imagery techniques for locating sources to determine the location and extent. Detection of the most polluted areas is an essential knowledge base for preventing some scenarios and minimizing others. Moreover, it may help in identifying sources of high pollution levels and evaluating the efficiency of any existing measures to control pollution. In conjunction with geospatial modelling, several frameworks of different types have been developed for pollution modeling. So those frameworks give you a way to build your models in a much more controlled way that should ensure they are all as consistent and accurate as possible. Working in conjunction with such frameworks, the use of geospatial approaches has been identified as a potentially useful method for evaluating pollution impacts on human health and the environment.