Sustainable Development Goals
Abstract/Objectives
This project focuses on the Touqian River Basin, integrating multi-source data from the Ministry of Environment’s National Water Quality Monitoring Network, the Central Weather Administration’s CODis climate data, and the Hsinchu Environmental Protection Bureau’s automatic river monitoring system to analyze the correlations and temporal variations of water pollution. Covering long-term monitoring data from 2005 to 2024, the study examines annual and seasonal changes in the River Pollution Index (RPI) and the influence of key parameters such as dissolved oxygen, biochemical oxygen demand, ammonia nitrogen, and suspended solids. Results indicate that since 2009, water quality in the Touqian River has significantly improved and remained stable, with suspended solids identified as the primary factor affecting RPI variation, showing weak correlation with rainfall. Furthermore, analysis of real-time monitoring data in 2024 reveals short-term pollution fluctuations not captured by monthly measurements. The project proposes integrating AI and big data analytics to develop a water quality early-warning system, enhancing real-time monitoring and supporting data-driven environmental governance.
Results/Contributions

This project, "Correlation Analysis of Water Pollution in the Touqian River," was conducted by the Data Analysis & Interpretation Lab at the Department of Engineering & System Science, National Tsing Hua University. It aims to deeply investigate the pollution characteristics and water quality variation patterns of the Touqian River, a vital water source in the Hsinchu area. The project's content first involves integrating diverse, cross-disciplinary data sources, including: 1) Long-term, manual monitoring data from the Ministry of Environment's "National Environmental Water Quality Monitoring Information Network," covering key pollution indicators such as Dissolved Oxygen (DO), Biochemical Oxygen Demand (BOD), Chemical Oxygen Demand (COD), and Ammonia Nitrogen (NH3-N); 2) Climate observation data from the Central Weather Administration, used to analyze the potential impact of climatic factors like rainfall; 3) High-frequency, real-time monitoring data from the Hsinchu City Environmental Protection Bureau's "River Water Quality Automatic Monitoring Network."

Project Results:

The core achievements of this project are reflected in the systematic data analysis performed using the aforementioned databases. Key results include:

  1. Pollution Index Trend Analysis: The team calculated the River Pollution Index (RPI) and conducted an in-depth analysis of its annual and quarterly correlations. This successfully depicted the long-term overall trends in Touqian River's water quality and identified pollution hotspots during specific seasons (e.g., wet and dry seasons).
  2. Real-time Dynamic Grasp: By analyzing real-time automatic monitoring data, the project captured instantaneous changes and short-term trends in water quality, helping to clarify the occurrence patterns of specific pollution events.
  3. Correlation Mining: The central objective of this research was to establish correlation models between various pollutant indicators (e.g., the relationship between DO, BOD, and Ammonia Nitrogen) and between pollution indicators and climatic factors. This lays the groundwork for subsequent pollution source tracing and water quality prediction.


Keywords
Touqian River, Water Quality Monitoring, River Pollution Index (RPI), Suspended Solids (SS), Real-time Monitoring and AI Analysis
References
Contact Information
分析與環境科學研究所
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