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The HYPE model is a hydrological model for small-scale and large-scale assessments of water resources and water quality, developed at the Swedish Meteorological and Hydrological Institute during 2005–2007. In the model, the landscape is divided into classes according to soil type, land use and altitude. In agricultural lands the soil is divided into three layers, each with individual computations of soil wetness and nutrient processes. The model simulates water flow and transport and turnover of nitrogen and phosphorus. Nutrients follow the same pathways as water in the model: surface runoff, macropore flow, tile drainage and outflow from individual soil layers. Rivers and lakes are described separately with routines for turnover of nutrients in each environment. Model parameters are global, or coupled to soil type or land use. The model was evaluated both by local calibrations to internal variables from different test basins and to data on discharge and nutrients from a large number of small basins. In addition, the estimated parameters were transferred to two larger basins in southern Sweden: River Rönneå and River Vindån. The resulting simulations were generally in good agreement with observations.

The Swedish regional climate modelling programme, SWECLIM, started in 1997 with the main goal being to produce regional climate change scenarios over the Nordic area on a time scale of 50 to 100 yr. An additional goal is to produce water resources scenarios with a focus on hydropower production, dam safety, water supply and environmental aspects of water resources. The scenarios are produced by a combination of global climate models (GCMs), regional climate models and hydrological runoff models. The GCM simulations used thus far are 10 yr time slices from 2 different GCMs, UKMO HadCM2 from the Hadley Centre and the ECHAM4/OPYC3 of the Max Planck Institute for Meteorology. The regional climate model is a modified version of the international HIRLAM forecast model and the hydrological model is the HBV model developed at the Swedish Meteorological and Hydrological Institute. Scenarios of river runoff have been simulated for 6 selected basins covering the major climate regions in Sweden. Changes in runoff totals, runoff regimes and extreme values have been analysed with a focus on the uncertainties introduced by the choice of GCM and routines for estimation of evapotranspiration in the hydrological model. It is further shown how these choices affect the statistical return periods of future extremes in a design situation.

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A dynamic water quality model, HYPE, was applied to a large, data-sparse region to study whether reliable information on water quantity and water quality could be obtained for both gauged and ungauged waterbodies. The model (called S-HYPE) was set up for all of Sweden (∼450 000 km 2), divided into sub-basins with an average area of 28 km 2. Readily available national databases were used for physiographic data, emissions and agricultural practices, fixed values for representative years were used. Daily precipitation and temperature were used as the dynamic forcing of the model. Model evaluation was based on data from several hundred monitoring sites, of which approximately 90% had not been used in calibration on a daily scale. Results were evaluated using the Nash-Sutcliffe efficiency (NSE), correlation and relative errors: 92% of the spatial variation was explained for specific water discharge, and 88% and 59% for total nitrogen and total phosphorus concentrations, respectively. Day-today variations were modelled with satisfactory results for water discharge and the seasonal variation of nitrogen concentrations was also generally well captured. In 20 large, unregulated rivers the median NSE for water discharge was 0.84, and the corresponding number for 76 partly-regulated river basins was 0.52. In small basins, the NSE was typically above 0.6. These major achievements relative to previous similar experiments were ascribed to the step-wise calibration process using representative gauged basins and the use of a modelling concept, whereby coefficients are linked to physiographic variables rather than to specific sites.

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