Measures of flow variability for great lakes tributaries

Area of Science:

• Environmental Science
• Hydrology
• Water Quality Monitoring

Background:

• Designing effective water quality monitoring programs for load estimation is challenging due to limited chemical data for flux variance analysis.
• Detailed flow data are often available for tributaries, and flow variability can correlate with pollutant flux, especially for non-point sources.

Purpose of the Study:

• To evaluate measures of flow variability as proxies for pollutant flux variability.
• To determine if flow variability can inform sampling program design for tributaries lacking sufficient chemical data.

Main Methods:

• Explored three types of flow variability measures: ratio measures (q x/qy), spread measures ((q x-qy)/qm), and coefficient of variation of log-transformed flows.
• Evaluated these measures using data from 120 Great Lakes tributaries and compared flow variability with flux variability for suspended solids, total phosphorus, and chloride in a subset of rivers.

Main Results:

• Measures of flow variability for Great Lakes tributaries were highly intercorrelated, often non-linearly.
• The coefficient of variation of log flows correlated well with the coefficient of variation of fluxes for key pollutants.
• Abnormal flow distributions were identifiable as outliers when plotting different variability measures against each other.

Conclusions:

• Flow variability measures can serve as effective proxies for pollutant flux variability, particularly in data-scarce watersheds.
• This approach can optimize the design of water quality monitoring programs, ensuring adequate sampling for accurate load estimation.