Three-dimensional lake water quality modeling: sensitivity and uncertainty analyses.

Abstract

Two sensitivity and uncertainty analysis methods are applied to a three-dimensional coupled hydrodynamic-ecological model (ELCOM-CAEDYM) of a morphologically complex lake. The primary goals of the analyses are to increase confidence in the model predictions, identify influential model parameters, quantify the uncertainty of model prediction, and explore the spatial and temporal variabilities of model predictions. The influence of model parameters on four model-predicted variables (model output) and the contributions of each of the model-predicted variables to the total variations in model output are presented. The contributions of predicted water temperature, dissolved oxygen, total phosphorus, and algal biomass contributed 3, 13, 26, and 58% of total model output variance, respectively. The fraction of variance resulting from model parameter uncertainty was calculated by two methods and used for evaluation and ranking of the most influential model parameters. Nine out of the top 10 parameters identified by each method agreed, but their ranks were different. Spatial and temporal changes of model uncertainty were investigated and visualized. Model uncertainty appeared to be concentrated around specific water depths and dates that corresponded to significant storm events. The results suggest that spatial and temporal variations in the predicted water quality variables are sensitive to the hydrodynamics of physical perturbations such as those caused by stream inflows generated by storm events. The sensitivity and uncertainty analyses identified the mineralization of dissolved organic carbon, sediment phosphorus release rate, algal metabolic loss rate, internal phosphorus concentration, and phosphorus uptake rate as the most influential model parameters.