Articles | Volume 6, issue 3
30 Jun 2002
30 Jun 2002

Hydrological application of the INCA model with varying spatial resolution and nitrogen dynamics in a northern river basin

K. Rankinen, A. Lepistö, and K. Granlund

Abstract. As a first step in applying the Integrated Nitrogen model for CAtchments (INCA) to the Simojoki river basin (3160 km2), this paper focuses on calibration of the hydrological part of the model and nitrogen (N) dynamics in the river during the 1980s and 1990s. The model application utilised the GIS land-use and forest classification of Finland together with a recent forest inventory based on remote sensing. In the INCA model, the Hydrologically Effective Rainfall (HER) is used to drive the water flow and N fluxes through the catchment system. HER was derived from the Watershed Simulation and Forecast System (WSFS). The basic component of the WSFS is a conceptual hydrological model which simulates runoff using precipitation, potential evapotranspiration and temperature data as inputs. Spatially uniform, lumped input data were calculated for the whole river basin and spatially semi-distributed input data were calculated for each of the nine sub-basins. When comparing discharges simulated by the INCA model with observed values, a better fit was obtained with the semi-distributed data than with the spatially uniform data (R2 0.78 v. 0.70 at Hosionkoski and 0.88 v. 0.78 at the river outlet). The timing of flow peaks was simulated rather well with both approaches, although the semi-distributed input data gave a more realistic simulation of low flow periods and the magnitude of spring flow peaks. The river basin has a relatively closed N cycle with low input and output fluxes of inorganic N. During 1982-2000, the average total N flux to the sea was 715 tonnes yr–1, of which 6% was NH4-N, 14% NO3-N, and 80% organic N. Annual variation in river flow and the concentrations of major N fractions in river water, and factors affecting this variation are discussed.

Keywords: northern river basin, nitrogen, forest management, hydrology, dynamic modelling, semi-distributed modelling