A NEW, SIMPLE, GENERAL TECHNIQUE TO PREDICT SEASONAL VARIABILITY OF RIVER DISCHARGE AND LAKE TEMPERATURE FOR LAKE ECOSYSTEM MODELS

The aim of this work is to present a new technique to predict seasonal variability in tributary water discharge, lake water retention rate a nd lake temperature (surface and deep water temperature and stratifica tion) when empirical data are missing, and the basic objective is to m odel ecosystem rather than hydrological processes. The main features o f the technique are the curves (called the norms) describing the maxim um (monthly) variability and the smoothing functions (the moderators) to change the maximum variability of the norms. The smoothing function s are calculated from readily available ''map parameters'' (latitude, longitude, altitude, mean annual precipitation, catchment area and lak e volume). The norms apply to all lakes of a given type. The aims of t his work are to present: (1) the new technique to predict seasonal var iability in tributary water discharge (Q); the basic aim is to give an account of the construction of a norm and a seasonal variability mode rator; (2) a model based on the same technique to predict seasonal var iabilities in surface and bottom water temperature; (3) a model for th e retention rate of lake water; (4) sensitivity tests illustrating how these models work, (5) examples how to use these models within the fr amework of a larger lake ecosystem model; and (6) examples showing tha t by accounting for the seasonal variability in this way, one can impr ove the behaviour and predictive accuracy of dynamic lake models. The seasonal moderator technique gives dimensionless expressions that may be used in dynamic models wherever one would like to account for seaso nal variability in rates and coefficients. This paper is a technical a ccount of the method. It has, however, been outside the scope to provi de thorough empirical calibrations.