Simulating pesticides in ditches to assess ecological risk (SPIDER): I. Model description

Renaud, F. G. , Bellamy, P. H. and Brown, C. D. (2008) Simulating pesticides in ditches to assess ecological risk (SPIDER): I. Model description. Science of the Total Environment, 394(1), pp. 112-123. (doi: 10.1016/j.scitotenv.2007.11.038) (PMID:18275984)

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Risk assessment for pesticides in the aquatic environment relies on a comparison between estimated exposure concentrations in surface water bodies and endpoints from a series of effect tests. Many field- and catchment-scale models have been developed, ranging from simple empirical models to comprehensive, physically-based, distributed models that require complex parameterisation, often through inverse modelling methods. Routine use of catchment models for assessment and management of pesticides requires a tool that is comprehensive in being able to address all major routes of entry of pesticides into surface water and that has reasonable parameter requirements. Current models either focus primarily on transport of pesticides in surface runoff or are restricted in application because they require calibration against data from detailed monitoring programmes. SPIDER (Simulating Pesticides In Ditches to assess Ecological Risk) was developed to address the gap in models available to simulate pesticide exposure within networks of small surface water bodies (ditches and streams) in support of ecological risk assessment for pesticides. SPIDER is a locally distributed, capacitance-based model that accounts for pesticide entry into surface water bodies via spray drift, surface runoff, interlayer flow and drainflow and that can be used for small agricultural catchments. This paper provides a detailed description of the model.

Item Type:Articles
Glasgow Author(s) Enlighten ID:Renaud, Professor Fabrice
Authors: Renaud, F. G., Bellamy, P. H., and Brown, C. D.
College/School:College of Social Sciences > School of Interdisciplinary Studies
Journal Name:Science of the Total Environment
ISSN (Online):1879-1026
Published Online:13 February 2008

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