1. Impact of Sampling Frequency on Annual Load Estimation Amber Spackman Jones Utah Water Research Lab Nancy Mesner Watershed Science Jeff Horsburgh Utah Water Research Lab Ron Ryel Wildland Resources David Stevens Utah Water Research Lab

2. Environmental processes can have fine scale. Low frequency samples are unrepresentative. Omits important events. Requires complex load calculations. Limitations of “Traditional” Sampling

3. High Frequency Monitoring Advantages: overall cost reduction minimization of human error improved turnaround time additional sites extended time periods Are loads calculated from high frequency monitoring superior to those from intermittent sampling?

4. Study Area: Little Bear River Paradise: less impacted by human activity. Mendon: influenced by reservoir releases, agricultural return flows, wastewater treatment plant, and greater agricultural activity.

5. Study Area: Sampling Sites Paradise Higher peaks, flashier flow regime Coarse sediments Phosphorus content: 60% particulate 40% dissolved Mendon Higher baseflow Fine, lacustrine sediments Phosphorus content: 40% particulate 60% dissolved

6. Study Area: Sampling Sites Paradise Mendon

7. Methods Surrogate relationships with turbidity used to generate high frequency estimates of TP and TSS concentration. Concentration paired with discharge to estimate annual loads- reference loads.

8. Methods Half hourly concentration and discharge were subsampled to represent various sampling frequencies: -Hourly -Daily randomized -Weekly randomized -Monthly randomized -Daily by hour -Weekly by day Annual loads were compared to the reference loads.

9. Results Paradise (upper)Mendon (lower)

10. Results

11. Results: Hour of Day

13. Results: Day of Week

14. Conclusions Using high frequency data to calculate loads provides increased resolution and accuracy. Bias from the reference loads varied between sites. Daily sampling may approximate reference loads, but is usually infeasible. Weekly and monthly sampling were inadequate. The hour of the day and the day of the week of sampling can impact load estimation.

15. Why We Care Water quality monitoring -higher resolution data -improved concentration and load estimation (regulations) -compare between sites or time periods -additional settings (WWTP, beaches, etc) Water quality models -better ability to estimate and calibrate parameters -testing underlying assumptions of models Environmental observatories -logistically and economically feasible -extended time periods -at many locations

16. Acknowledgments Field and Lab Support Sandra Guerrero Emily Saad Eric Peterson Michael Stevens Su Anderson USU Aquatic Biogeochemistry Lab USU Analytical Lab Landowners on the Little Bear River National Science Foundation (CBET 0610075) US Department of Agriculture (UTAW-2004-05671) Questions?