A novel mathematical template for developing fDOM probe fluorescence signal correction models for freshwaters

Area of Science:

• Environmental Chemistry
• Water Quality Monitoring
• Spectroscopy

Background:

• Field-deployable fluorescent dissolved organic matter (fDOM) probes offer real-time water quality data.
• Probe accuracy is compromised by environmental factors like temperature, pH, turbidity, and inner filter effects.
• Accurate compensation models are crucial for reliable fDOM measurements and dissolved organic carbon (DOC) estimation.

Purpose of the Study:

• To develop and validate correction models for temperature, pH, turbidity, and inner filter effects on a commercial fDOM probe (fDOMs).
• To assess the effectiveness of these models in improving DOC predictions across diverse Australian water bodies.
• To integrate the correction models into user-friendly software for practical application.

Main Methods:

• Laboratory-based Model Calibration Experiments (MCEs) were conducted using Australian waters with varying DOC, UV absorbance, and turbidity.
• A model template was utilized to develop four discrete factor correction models by determining specific coefficient (α) values.
• The consistency of derived α values across different water qualities was evaluated.

Main Results:

• Generic α values were identified for each of the four correction factors, indicating broad applicability.
• Applying the four-factor compensation models significantly improved the correlation between fDOMs and DOC (r = 0.96, p < 0.05).
• Average bias between predicted and actual DOC decreased from 60.9% to 16.7% after applying the correction models.

Conclusions:

• The developed four-factor compensation models effectively correct fDOM probe signals for key environmental influences.
• These models enhance the accuracy of DOC estimation from fDOM measurements in diverse aquatic environments.
• The incorporation into EXOf-Correct software provides a practical tool for improving field-based water quality monitoring.