MODELING OF SEASONAL-VARIATION IN NITROGEN-RETENTION AND IN-LAKE CONCENTRATION - A 4-YEAR MASS-BALANCE STUDY IN 16 SHALLOW DANISH LAKES

The mass balance for total nitrogen (N) was studied over a four-year p eriod in 16 shallow mainly eutrophic Ist order Danish lakes. Water was sampled in the main inlet of each lake 18-26 times annually, and from the outlets and the lake 19 times annually. Water was also sampled fr om minor inlets, although less frequently. N input and output were cal culated using daily data on discharge (Q), the latter being obtained e ither from the Q/H relationship based on automatic recordings of water level (H) for the main in- and outlet, or by means of Q/Q relationshi ps for the minor inlets. Annual mean N retention in the lakes ranged f rom 47 to 234 mg N m(-2) d(-1), and was particularly high in lakes wit h high N loading. Annual percentage retention (N-ret-y%) ranged from 1 1 to 72%. Non-linear regression analysis revealed that hydraulic reten tion time and mean depth accounted for 75% of the variation in annual mean N-ret-y% and, in combination with inlet N concentration, accounte d for 84% of the variation in the in-lake N concentration. N-ret% vari ed according to season, being higher in the second and third quarter t han in the first and fourth quarter(median 18-19%). A simple model was developed for predicting monthly nitrogen retention (N-ret-m) on the basis of external N loading, the lake water pool of nitrogen N-pool, h ydraulic loading and lake water temperature. Calibration of only two p arameters on data from the randomly selected 8 out of 16 lakes rendere d the model capable of accurately simulating seasonal dynamics of the in-lake N concentration and N-ret-m in all 16 lakes. We conclude that with regard to shallow, eutrophic lakes with a relatively low hydrauli c retention time, it is now possible to determine not only annual mean nitrogen retention, but also the seasonal variation in N-ret-m. Predi ction of seasonal variation in N loading of downstream N-limited coast al areas is thereby rendered much more reliable.