The project Aquisafe assesses the potential of selected near-natural mitigation systems, such as constructed wetlands or infiltration,zones, to reduce diffuse pollution from agricultural sources and consequently protect surface water resources. A particular aim is the attenuation of nutrients and pesticides. Based on the review of available information and preliminary tests within Aquisafe 1 (2007-2009), the second project phase Aquisafe 2 (2009-2012) is structured along the following main components: (i) Development and evaluation of GIS-based approaches for the identification of diffuse pollution hotspots, as well as model-based tools for the simulation of nutrient reduction from mitigation zones (ii) Assessment of nutrient retention capacity of different types of mitigation zones in international case studies in the Ic watershed in France and the Upper White River watershed in the USA under natural conditions, such as variable flow. (iii) Identification of efficient mitigation zone designs for the retention of relevant pesticides in laboratory and technical scale experiments at UBA in Berlin.The present study focused on (i) and aimed at testing GIS approaches for the localization of critical source areas (CSAs) of diffuse NO3- pollution in rural catchments with low data availability as a basis for the planning of mitigation measures. We tested a universal GIS-based approach, which is a combination of published methods. The five parameters land use, soil, slope, riparian buffer strips and distance to surface waters were identified as most relevant for diffuse agricultural NO3 - pollution. Each parameter was classified into three risk classes, based on a literature review. The risk classes of the five parameters were then averaged in a GIS overlay in order to find areas with highest risk. The Ic catchment in Brittany, France, served as a study site to test the applicability of the chosen approach. The result of the overlay was compared (a) with measured NO3 - loads in seven subcatchments of the Ic catchment and (b) with the results of a previous analysis by the numerical model Soil and Water Assessment Tool (SWAT). Regarding (a) it was found that higher mean risk classes in a subcatchment correspond with higher measured NO3- loads. However, due to the small number of data points a reliable statistical analysis was not possible. Regarding (b), the plotting of the loads predicted by SWAT against the mean risk class for the 32 SWAT subcatchments show a similar, but poorer relationship. The GIS approach was further analyzed regarding its sensitivity to each of the parameters. The analysis showed that the method is not very sensitive to most of the parameters, i.e. risk class distribution (or the choice of CSA) does not change greatly if one parameter is omitted. Nevertheless, if data quality for some parameters is known to be low, sensitivity of the result to the parameter should be considered in addition.In summary, it can be stated that the applied GIS overlay is a promising, easy to handle approach. First experiences on the Ic catchment indicate that GIS-based approaches can be robust, even for lower data availability. As a result, further work is suggested towards developing a universally applicable GIS method for nitrate CSA identification. Main points to be assessed are the number of classes, the necessary weighting of parameters and the best inclusion of different nitrogen pathways between field and surface water.