Uncertainty and sensitivity analysis provide powerful means to enhance the performance of the models, to increase the transparency and credibility of the model results, and to allow the decision-maker to judge whether the model results are sufficiently accurate and precise to support decision-making or not. Uncertainty and sensitivity analysis of numerical models usually require hundreds, thousands, or even more, repeated model runs (e.g., in Monte Carlo simulation) as well as access to change the model parameters and variables on each model run. Consequently, many model codes, although widely used and well-formulated, are not well-suited for uncertainty and sensitivity analysis due to too long model execution time or due to lack of suitable interface to change model parameters and variables in an automated way. In this paper, we describe in details a lake model code, which aims to combine good simulation capabilities with efficient model execution time and easy application of numerical uncertainty and sensitivity analysis techniques. This model code is called MyLake (Multi-year Lake simulation model) and it is a one-dimensional process-based model code for simulation of daily vertical distribution of lake water temperature and thus density stratification, evolution of seasonal lake ice and snow cover, sediment-water interactions, and phosphorus-phytoplankton dynamics. After giving a detailed technical description of the different processes and algorithms included in the current version 1.2 of the MyLake model code, we present some results from a model application example including an Extended Fourier Amplitude Sensitivity Test (Extended FAST) sensitivity analysis and a simple Monte Carlo simulation based uncertainty analysis. Finally we discuss the performance of the MyLake code, especially in connection with numerical uncertainty and sensitivity analysis techniques.
