An approach for decomposing river water-quality trends into different flow classes.

Area of Science:

• Environmental Science
• Hydrology
• Water Quality Analysis

Background:

• Existing statistical methods often fail to report separate water quality trends for different flow conditions.
• The Weighted Regressions on Time, Discharge, and Season (WRTDS) method provides a basis for flow normalization but needs enhancement for flow-condition-specific analysis.

Purpose of the Study:

• To introduce and demonstrate the utility of the novel FN2Q approach for quantifying river water quality trends under distinct low-flow and high-flow conditions.
• To analyze total nitrogen trends in the South Fork Shenandoah River using the FN2Q method and identify contributing factors.

Main Methods:

• The study proposes the FN2Q approach, an extension of flow-normalization (FN) from WRTDS, to generate daily time series of low-flow and high-flow FN flux estimates.
• The method was applied to a dataset of 632 total nitrogen concentration samples from the South Fork Shenandoah River (1985-2018).
• Daily estimates were summarized to identify trends over the period of record.

Main Results:

• The overall flow-normalized (FN) flux of total nitrogen declined between 1985 and 2018, largely due to a decrease in the low-flow class.
• The decline in low-flow conditions correlated with reduced wastewater effluent loads, suggesting treatment upgrades improved water quality.
• High-flow FN flux showed a spike around 2007, linked to increased particulate nitrogen from sediment transport.

Conclusions:

• The FN2Q approach effectively characterizes river water quality changes under different flow regimes.
• The method aids in identifying underlying drivers of water quality dynamics, such as wastewater treatment efficiency and sediment-related nutrient delivery.
• FN2Q is a valuable tool for analyzing widely available river monitoring data to enhance understanding of water quality dynamics.