A coupled physical-biochemical lake model for forecasting water quality: Application to the Northern Basin of Lake Lugano

Abstract

A new one-dimensional numerical model that includes physical and biochemical processes has been developed. The biochemical processes, influenced by the lake dynamics, are required for forecasting water quality. The model is used to investigate the effects of different internal restoration measures, such as artificial mixing, input of oxygen and drainage of deep water. The model is applied to the Northern Basin of Lake Lugano, a Swiss-Italian border lake. The lake is highly eutrophic and chemically stratified throughout the year. The model was calibrated over one year and validated over a period of several years. The results agree well with the measured data. The coupled model reproduces the observed depth dependency of conductivity even during long simulation times. Due to the predominant mixing, decoupled physical models cannot maintain such gradients. The forecasting capabilities of the model are demonstrated for different case studies. The impact of restoration measures on water quality is rather small. Best results are achieved by reducing the external nutrient loading. Caution is recommended for internal measures as these have to be studied in greater detail.