1. Testing and comparison of three pesticide risk indicator models under Norwegian conditions A case study in the Skuterud and Heiabekken catchments Marianne Stenrød, Heidi E. Heggen, Randi I. Bolli, Ole Martin Eklo Materials and Methods The NERI-model was initially tested and evaluated in comparison with the Environmental Impact Quotient (EIQ) model [2]. These two models were further evaluated in relation to modelling risk of pesticide transport in soil using the SWAT (Surface Water ATtenuation) model [4]. Model characteristics NERI and EIQ-models Simple and easy to use Integrate –Physical/chemical pesticide properties –Biological effects (toxicity) –General models for dispersion processes Yields relative risk numbers for specific pest management strategies Focus on trends with time and comparison of pest management strategies No regard given to site specific data on soil characteristics and weather conditions SWAT-model Estimate potential leaching –Physical/chemical pesticide properties –Site specific data on soil and weather conditions Yields leached concentrations and a leaching risk classification for each pesticide used in a field Focus on risk of exposure in surface waters due to leaching No regard given to environmental effects (e.g. toxicity to terrestrial and aquatic organisms) Our main focus in this work has been the farmer and his need to evaluate the environmental impact of alternative pest management strategies. We have used actual reported use of pesticides on different crops when evaluating the models to achieve this. Results and Discussion Evaluation of integrated models (Figure 1 and 2): EIQ-model risk estimates are largely governed by amount of pesticide used. NERI-model gives much weight to substances of long persistence in soil and/or high risk of bioaccumulation,  NERI-model more in accordance with goals of risk reduction – but gives insufficient weight to mobile pesticides Model suitability as farmer guidance tools The increasing focus on risk reduction and need for implementation of BMPs for pest control, leaves the farmer in need of reliable and easy-to-use risk evaluation tools. The simplicity and ease of use of the integrated models NERI and EIQ give some serious lacks when it comes to use for farmer guidance. They do not include any site specific data on soil characteristics and weather conditions, factors of great importance for pesticide leaching and, hence, governing the risk of exposure. Map presentations of leaching risk of individual pesticides or other tools giving the opportunity to ‘hands-on’ compare the environmental impact of different plant protection strategies, have a large potential when based on pre-simulated model results under some representative environmental conditions. SWAT-results summarized over the 10 year simulation period implemented in a GIS-application (Figure 3 and 4).  Site specific evaluation of leaching risk based on knowledge of the soils, climate (amount and time of rainfall episodes) and previous use of pesticides (dose, timing of application)  Easy interpretable farm maps of leaching risk for the individual pesticide. Initially an extensive data table had to be established; a time-consuming process with SWAT-model runs and reorganization of data before further use. Concluding remark Achievement of practical solutions for harmonized and user friendly tools for pesticide risk evaluation and management from ongoing research projects within Europe (i.e. EU FP6- projects HAIR and FOOTPRINT), will be of great importance for further development within this field. Acknowledgements This work was funded by the Norwegian Research Council. Co-workers of the INTRA-project are acknowledged for their contribution. Thanks to J.M. Hollis for help with classification of the soil types according to the HOST- system. Literature [1] Spikkerud et al., 2005. Guidelines for a Banded Pesticide Tax Scheme, Differentiated According to Human Health and Environmental Risks. Norwegian Food Safety Authority, National Centre of Plants and Vegetable Foods, Ås, Norway, 14 pp. [2] Kovach et al., 1992. A method to measure the environmental impacts of pesticides. New York’s Food and Life Sciences Bulletin 139, 1-8. [3] Turpin et al., 2005. AgriBMPWater: systems approach to environmentally acceptable farming. Environmental Modelling and Software 20, 187-196. [4] Brown & Hollis, 1996. SWAT – a semi-empirical model to predict concentrations of pesticides entering surface waters from agricultural land. Pesticide Science 47, 41-50 Introduction In recent years, there has been an increased concern for the risk of non-target impacts of pesticides. It has been widely acknowledged that weight and volume measures are not adequate proxies for assessing this risk. This is reflected in governmental policies by the focus on risk reduction rather than reduced amounts used for plant protection purposes. Many pesticide risk indicator models, all having their strengths and weaknesses, have been developed as tools to assess the environmental risk from spraying with pesticides, and are in use throughout the world. The National Food Safety Authorities in Norway have developed a pesticide risk indicator model for tax banding of pesticides (the NERI-model) [1] and trend analysis within the Norwegian market. The aim of the present investigation was to evaluate the performance of this pesticide risk indicator model on catchment and farm level. www.bioforsk.no Corresponding author: marianne.stenrod@bioforsk.nomarianne.stenrod@bioforsk.no Bioforsk Plant Health and Plant Protection Division Høgskoleveien 7, N-1432 Ås, NORWAY plantehelse@bioforsk.no Norwegian Institute for Agricultural and Environmental Research Figure 1. The (four) most used pesticide active ingredients in the Skuterud catchment 1994-2003 (a) and the Heiabekken catchment 1996-2002 (b) Figure 4: SWAT-simulation results, based on input data of pesticide use, climatic conditions and soil type (Rk8 = silty clay loam, Je3 = sandy soil) and drainage, summarized for 10 years. The leaching risk for the pesticide ioxynil is shown for a particular farm. Figure 3: SWAT-simulation results, based on input data of pesticide use, climatic conditions and soil type and drainage, summarized for 10 years. All pesticides used on the field x soil type (here: silty clay loam) in question are shown with an associated leaching risk. Figure 2. The (four) most hazardous (as estimated by the NERI- and EIQ-models) pesticide active ingredients used in the Skuterud catchment 1994-2003 (a) and Heiabekken catchment 1996-2002 (b). Marianne StenrødHeidi E. HeggenRandi I. BolliOle Martin Eklo Azoxystrobin: High Cyprodinil: Low Cyproconazole: Medium Dichlorprop: High Diquat dibromide: Low Ethephon: Low Fenpropimorph: Low Glyphosate: Medium Ioxynil: High Iodosulfuron: Low Chlormequat chloride: High Chlorsulfuron: Low Mancozeb: High MCPA: High Metalaxyl: High Prochloraz: Low Propiconazole: Low Tribenuron-methyl: Low Trinexapac-ethyl: Low Pesticide leaching risk on selected field: