The introduction of GIS has opened up new possibilities in combining different sources of geographical information. In Norway, an agro-meteorological decision system is under development which combines gridded weather information with soil and crop development data. The system is based on a daily scale soil moisture model driven by meteorological inputs. Weather information is based on in-situ observations, and spatial interpolation schemes are used to establish fine-mesh grids of these variables over the model domain. These interpolation schemes take advantage of geographical co-variables such as terrain information. The soil moisture model is used to estimate the soil water content, which is the determinant of soil suitability for tillage and sowing. The system also includes a phenological model for identification of suitable days when combine-harvesting of cereals can be satisfactorily undertaken.

Spatial interpolation of the meteorological elements is based upon all available in-situ observations. The different elements are interpolated by different interpolation techniques. Snow depth, cloud cover, relative humidity and wind are in this first version, interpolated by using inverse distance weighting. Precipitation is determined by triangulation with elevation adjustment. Temperature is interpolated by using a residual kriging approach that includes five independent predictors in the trend equation. Evaporation is estimated by using the Penman2 formula based on the estimates of the meteorological elements.

This approach is a good demonstration of the benefits of applying GIS and distributed geo-data in cross-disciplinary situations. The application is a valuable contribution to soil capability assessments.