Remote sensing-based water quality assessment for urban rivers: a study in linyi development area

Area of Science:

• Environmental Science
• Water Resource Management
• Remote Sensing Applications

Background:

• Urban rivers are critical for city development and ecology, often serving as drinking water sources.
• Existing Chinese water quality assessment methods have limitations, potentially underestimating water quality.
• The Canadian Water Quality Index (CWQI) offers a more comprehensive and objective approach.

Purpose of the Study:

• To apply the CWQI method for assessing water quality in two major urban rivers in the Linyi development area.
• To develop remote sensing-based models for estimating CWQI scores to overcome the cost and scale limitations of traditional monitoring.
• To analyze the spatial and temporal distribution of water quality using the developed models.

Main Methods:

• Utilized water quality monitoring data from 2014-2017 for 24 parameters.
• Employed remote sensing techniques to correlate satellite data with CWQI scores.
• Applied linear regression analysis to identify the relationship between spectral bands and CWQI, and validated models with testing datasets.

Main Results:

• Red band satellite data showed the highest correlation with CWQI for both urban rivers.
• Remote sensing-based CWQI models were successfully validated, demonstrating good fit with testing datasets.
• Generated CWQI distribution diagrams enabled spatial and temporal water quality analysis.

Conclusions:

• The developed remote sensing approach effectively estimates CWQI, providing a robust and cost-efficient method for urban river water quality assessment.
• The approach accurately indicates actual water quality patterns, validated by field observations.
• This method supports improved urban river management and water resource conservation.