Governor Bond Lake TMDL
Final Report 28 September 2002
7.0 SEASONAL VARIATION
It is often essential to account for seasonal variations in the concentrations of contaminants addressed in
the TMDL. However, while seasonal variation is important for reservoir and lake systems, climate
conditions and climate history can have a great effect on transport and transformation processes. Runoff
and transport will be affected by previous year climate as well as current climate conditions. Flushing or
storage in the reservoir will be affected by the climate (amount of precipitation and runoff) and amount of
Seasonal variation was addressed by using an averaging program, FLUX, to determine yearly flow-weighted
average pollutant concentrations, which integrate the effects of seasonal variation and flow
measured in-stream concentrations. This model can be adjusted to account for these effects by stratifying
the data into related categories (e.g., early spring and late fall, high flow and low flow). The resulting
average and associated error terms incorporate seasonal effects.
The Generalize Watershed Loading Function model was run for 13 continuous years, 1987 through 1999.
This time frame was chosen in order to provide each simulated year (1989, 1993, 1996, and 1999) with at
least three years of antecedent conditions for characterizing the build up of soil moisture, runoff,
groundwater, and other transport factors.
Finally, the BATHTUB model was run for four climate conditions in order to bracket the effects of
variations in climate. BATHTUB is a steady-state, equilibrium model that models both a single season or
single year conditions and does not include build up and storage components. Simulations for changing
watershed characteristics or climatic conditions were performed by first modeling the changed conditions
in GWLF and using that program’s output as input values for BATHTUB. Seasonal variation is modeled
implicitly by including coefficients of variation for measured in-lake water quality parameters, which are
descriptive of seasonal variations.
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