Monitoring water at high spatial and temporal resolutions is important for maintaining water quality because the cost of pollution remediation is often higher than the cost of early prevention or intervention. In recent decades, the availability and affordability of satellite images have regularly increased, thus supporting higher-frequency and lower-cost alternative methods for monitoring water quality. The core step in satellite remote sensing detection is inverse modeling, which is used to calibrate model parameters and enhance the similarity between the model and the real system being simulated. The reflectance values measured at water quality stations are extracted from atmosphere-corrected satellite imagery for analysis. However, various external environmental, hydrological, and meteorological factors affect the evaluation results, and the results obtained with different parameters can vary. This literature review shows that nonpoint-source pollution caused by stormwater runoff can also be monitored using satellite imagery. To improve the accuracy of satellite-based water quality prediction, the temporal resolution of field measurements can be increased, thus better considering the influence of seasonality. Then, the atmospheric correction module can be improved by using available atmospheric water content products. Moreover, because water surface ripples affect reflectance, wind speed and direction should be considered when comparing water quality scenes.
Keywords: Atmospheric correction; Eutrophication; Land cover; Nonpoint source; Remote sensing; Stormwater.
© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.