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Eutrophication, primarily caused by the discharge of untreated sewage, poses a significant threat to Lake Chapala in Mexico. This study utilized satellite imagery from Sentinel-2, ERA5, and Sentinel-1, combined with artificial intelligence techniques, to assess key water quality indicators: Chemical Oxygen Demand (COD), Total Phosphorus (TP), Total Suspended Solids (TSS), and chlorophyll-a (Chl-a) concentration. The results revealed coefficients of determination (r2) values of 0.67 for COD, 0.72 for TP, 0.58 for TSS, and 0.60 for chlorophyll-a, highlighting the potential of remote sensing and AI in identifying polluted surface water bodies. This integrated approach could strategically guide the placement of biodigesters, promoting sustainable wastewater management and energy recovery in the region.

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Estimation of Water Quality Parameters as Substrates for Energy Recovery Using Remote Sensing and Artificial Intelligence

  • 会议论文

  • 发表日期：

    2026年

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  • Freddy H. Villota González,
  • Kelly Joel Gurubel Tun,
  • Virgilio Zúñiga Grajeda,
  • Belkis Coromoto Sulbarán Rangel

摘要

Eutrophication, primarily caused by the discharge of untreated sewage, poses a significant threat to Lake Chapala in Mexico. This study utilized satellite imagery from Sentinel-2, ERA5, and Sentinel-1, combined with artificial intelligence techniques, to assess key water quality indicators: Chemical Oxygen Demand (COD), Total Phosphorus (TP), Total Suspended Solids (TSS), and chlorophyll-a (Chl-a) concentration. The results revealed coefficients of determination (r2) values of 0.67 for COD, 0.72 for TP, 0.58 for TSS, and 0.60 for chlorophyll-a, highlighting the potential of remote sensing and AI in identifying polluted surface water bodies. This integrated approach could strategically guide the placement of biodigesters, promoting sustainable wastewater management and energy recovery in the region.