Non-point source critical area analysis in the Gisselo¨ watershed using GIS

In the southeast in Norrko¨ping, Sweden, is a small fjord-like bay called Sla¨tbaken. The water quality in Sla¨tbaken—with its narrow outlet to the Baltic Sea—depends highly on the water quality of the streams that flow in it. While point pollution sources can be identified easily in general, the non-point sources are harder to find. The most important sources for non-point pollution are agricultural areas, and the pollutants are mostly nutrients like phosphorus, which come from the fertilisation of the fields. One important catchment area for Sla¨tbaken is the 57.7 km2 Gisselo¨ river basin (part of the topographic map 8GNO), which contains large agricultural areas. The transport of water pollutants is based on the same hydrological processes as erosion and sediment transport. The implementation of such a model in a GIS allows the analysis of a large area with a high resolution. When choosing the model, special attention was paid to the possibility of using a verified model that is easy to implement in a commercial GIS without the need of too much expert knowledge. This may allow its widespread use in many administrative applications that need non-point source information. A feasibility test for an enhanced GIS USLE model was done in the Gisselo¨ drainage basin before it was implemented for all river basins in the whole administrative area of Norrko¨pings kommun. It is possible to use the suggested simplified USLE model to estimate the load of both pollutants and sediments, and it is able to show the areas that are critical for the water quality at the outlet of the water basin. The model has been evaluated in three studies [Int. J. Geogr. Inf. Syst. 2 (4) (1988) 365; A GIS to target critical areas for non point source management, in: Proceedings of the International Non Point Source Management Symposium, Austin, TX, November 7, 1989; Vatten 48 (1992) 117]. Then, implemented in a very simple GIS that allowed only rough estimates of terrain models and distances, the model was able to estimate the total suspended solids (TSS) and total phosphorus (TP) loads in the Svarta° river basin of 1539 km2 in the same region as Gisselo¨ and the Bornsjo¨ river basin outside Stockholm. Besides an estimated R2 of 0.91–0.98 (verified by a more than one year measurement from manual and automated sampling stations in the whole river basin), the benefit with the GIS implemented USLE was the possibility to identify the risk areas with high spatial accuracy. During the last decade, both available databases and software have changed the possibilities to identify areas at risk of nutrient leakage. Schein [GIS Methods for Monitoring Sustainable Development by Analysis of Land-use and Land Cover Changes in the Surroundings of Linko¨ping (Sweden), Institut fu¨r Photogrammetrie und Fernerkundung, Technische Universita¨t Dresden, Germany] and Schein and Sivertun [Method and models for sustainable development monitoring and analyses in GIS, in: Proceedings of the International Workshop on Geo-Spatial Knowledge Processing for Natural Resource Management, University of Insubria, Varese, Italy, June 28–29, 2001] show that the enhanced land use data available through the European Union agricultural support program can be used together with remote sensing data to fine tune the modified GIS USLE model. The problems with the new 50 × 50 m digital elevation data now available are also pointed out here. Obvious errors in the data and possibilities to enhance the model by introducing a better terrain model were two important suggestions in these works. In this article, two modifications to the original model are suggested. One is enhancement of the digital terrain model by using height curves from the digital 1:50 000 scale topographic map, and the other is a smooth distance function that better reflects the impact of nutrients on water bodies.Because of its easy implementation on standard low cost systems, the GIS USLE model is suitable for analysing huge areas for critical places. The results can lead to more detailed studies in the risk areas thus identified or to investigations on the effect of land use changes, or can be used simply for taking care in the use of fertilisers and other chemicals in the critical agricultural areas.