Explore the Monitoring Status of Black and Odorous Water

Black and odorous water bodies caused by industrial pollution, agricultural runoff and urban wastewater pose environmental and public health risks. Traditional monitoring methods are both time and labour consuming limitations, which is unsuitable for large-scale assessments. Remote sensing has emerged as a new monitoring technology using spectral analysis and machine learning techniques to detect polluted water bodies with accuracy of 87.5%. This study examines the formation mechanisms of black-odorous water based on odorzing and blackening process. It also compares advantages and limitations of both traditional monitoring techniques and modern remote sensing methods. Challenges on remote sensing monitoring including atmospheric effect and ground effect decrease its accuracy, but future advancements in high-resolution satellite imaging, cloud-masking techniques and next generation machine learning model have potential to overcome those challenges. Stricter pollution regulations are also necessary to enhance water quality management. Strengthening these efforts is essential for sustainable urban development and environmental protection.

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Publication Details

Journal
MATEC Web of Conferences
Published
2025-01-01
DOI
https://doi.org/10.1051/matecconf/202541002007
Primary Topic
Water Quality Monitoring and Analysis
Type
article
Field-Weighted Citation Impact
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article

Explore the Monitoring Status of Black and Odorous Water

Zhihao Wang
1 links
MATEC Web of Conferences
Water Quality Monitoring and Analysis
article

Explore the Monitoring Status of Black and Odorous Water

Zhihao Wang
article en

Abstract

Black and odorous water bodies caused by industrial pollution, agricultural runoff and urban wastewater pose environmental and public health risks. Traditional monitoring methods are both time and labour consuming limitations, which is unsuitable for large-scale assessments. Remote sensing has emerged as a new monitoring technology using spectral analysis and machine learning techniques to detect polluted water bodies with accuracy of 87.5%. This study examines the formation mechanisms of black-odorous water based on odorzing and blackening process. It also compares advantages and limitations of both traditional monitoring techniques and modern remote sensing methods. Challenges on remote sensing monitoring including atmospheric effect and ground effect decrease its accuracy, but future advancements in high-resolution satellite imaging, cloud-masking techniques and next generation machine learning model have potential to overcome those challenges. Stricter pollution regulations are also necessary to enhance water quality management. Strengthening these efforts is essential for sustainable urban development and environmental protection.

MATEC Web of ConferencesVol. 410
University of Toronto (CA)
Openalex Percentile: Top 78%
Water Quality Monitoring and Analysis
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Explore the Monitoring Status of Black and Odorous Water — Zhihao Wang · MATEC Web of Conferences (2025) | TGRS Research Map | TGRS