A metabolism-based whole lake eutrophication model to estimate the magnitude and time scales of the effects of restoration in Upper Klamath Lake, south-central Oregon
A whole lake eutrophication (WLE) model approach for phosphorus and cyanobacterial biomass in Upper Klamath Lake, south-central Oregon, is presented here. The model is a successor to a previous model developed to inform a Total Maximum Daily Load (TMDL) for phosphorus in the lake, but is based on net primary production (NPP), which can be calculated from dissolved oxygen, rather than scaling up a small-scale description of cyanobacterial growth and respiration rates. This phase 3 WLE model is a refinement of the proof-of-concept developed in phase 2, which was the first attempt to use NPP to simulate cyanobacteria in the TMDL model. The calibration of the calculated NPP WLE model was successful, with performance metrics indicating a good fit to calibration data, and the calculated NPP WLE model was able to simulate mid-season bloom decreases, a feature that previous models could not reproduce.
In order to use the model to simulate future scenarios based on phosphorus load reduction, a multivariate regression model was created to simulate NPP as a function of the model state variables (phosphorus and chlorophyll a) and measured meteorological and temperature model inputs. The NPP time series was split into a low- and high-frequency component using wavelet analysis, and regression models were fit to the components separately, with moderate success.
The regression models for NPP were incorporated in the WLE model, referred to as the “scenario” WLE (SWLE), and the fit statistics for phosphorus during the calibration period were mostly unchanged. The fit statistics for chlorophyll a, however, were degraded. These statistics are still an improvement over prior models, and indicate that the SWLE is appropriate for long-term predictions even though it misses some of the seasonal variations in chlorophyll a.
The complete whole lake SWLE model, with multivariate regression to predict NPP, was used to make long-term simulations of the response to 10-, 20-, and 40-percent reductions in tributary nutrient loads. The long-term mean water column concentration of total phosphorus was reduced by 9, 18, and 36 percent, respectively, in response to these load reductions. The long-term water column chlorophyll a concentration was reduced by 4, 13, and 44 percent, respectively. The adjustment to a new equilibrium between the water column and sediments occurred over about 30 years.
Wherry, S.A., and Wood, T.M., 2018, A metabolism-based whole lake eutrophication model to estimate the magnitude and time scales of the effects of restoration in Upper Klamath Lake, south-central Oregon: U.S. Geological Survey Scientific Investigations Report 2018–5042, 43 p., https:/doi.org/10.3133/sir20185042.
ISSN: 2328-0328 (online)
Table of Contents
- Significant Findings
- Whole Lake Eutrophication Model for Simulating Historical Conditions
- Multivariate Regression Model of Net Primary Production
- Whole Lake Eutrophication Model for Simulating Future Conditions
- Implications of Model Results for Restoration
- References Cited
Additional publication details
|Publication Subtype||USGS Numbered Series|
|Title||A metabolism-based whole lake eutrophication model to estimate the magnitude and time scales of the effects of restoration in Upper Klamath Lake, south-central Oregon|
|Series title||Scientific Investigations Report|
|Publisher||U.S. Geological Survey|
|Publisher location||Reston, VA|
|Contributing office(s)||Oregon Water Science Center|
|Description||vii, 43 p.|
|Other Geospatial||Upper Klamath Lake|
|Online Only (Y/N)||Y|
|Google Analytic Metrics||Metrics page|