Impact of data quality and model complexity on prediction of pesticide leaching

Accurate input data for leaching models are expensive and difficult to obtain which may lead to the use of "general" non-site-specific input data. This study investigated the effect of using different quality data on model outputs. Three models of varying complexity, GLEAMS, LEACHM, and HY...

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Bibliographic Details
Published in:	Journal of environmental quality Vol. 35; no. 2; pp. 628 - 640
Main Authors:	Dann, R.L, Close, M.E, Lee, R, Pang, L
Format:	Journal Article
Language:	English
Published:	Madison American Society of Agronomy, Crop Science Society of America, Soil Science Society 01-03-2006 Crop Science Society of America American Society of Agronomy
Subjects:	Adsorption Agronomy Agronomy. Soil science and plant productions Applied sciences Biological and medical sciences Bridged Bicyclo Compounds - analysis Bridged Bicyclo Compounds - chemistry Carbon - analysis Chemicals Complexity Computer Simulation Copyrights data analysis Degradation Documents Drinking water Earth sciences Earth, ocean, space Engineering and environment geology. Geothermics Environmental management Environmental quality Exact sciences and technology Fundamental and applied biological sciences. Psychology GLEAMS model Glycolates - analysis Glycolates - chemistry Half-Life hydrologic models HYDRUS-2D model Leaching LEACHM model Loams Mathematical models model validation Models, Theoretical New Zealand Optimization Particle size distribution Pesticides Pesticides - analysis Pesticides - chemistry Physical properties Picloram Picloram - analysis Picloram - chemistry Pollution Pollution, environment geology prediction Regional Research Design Silt loam Silts simulation models Soil (material) Soil - analysis soil transport processes Sorption Studies Surface water Triazines - analysis Triazines - chemistry Water Pollutants, Chemical - analysis water pollution Water Supply New Zealand Oceania Soil quality Partition coefficient Solutes Forecast model Modeling Optimization Degradation Transport process Site specificity Site selection Database Lixiviation Phase partition Half life Pollutant behavior Pesticides Prediction Leaching Physical properties Sorption Particle size distribution Picloram Silt loam soil Simulation Observation data Field study
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Summary:	Accurate input data for leaching models are expensive and difficult to obtain which may lead to the use of "general" non-site-specific input data. This study investigated the effect of using different quality data on model outputs. Three models of varying complexity, GLEAMS, LEACHM, and HYDRUS-2D, were used to simulate pesticide leaching at a field trial near Hamilton, New Zealand, on an allophanic silt loam using input data of varying quality. Each model was run for four different pesticides (hexazinone, procymidone, picloram and triclopyr); three different sets of pesticide sorption and degradation parameters (i.e., site optimized, laboratory derived, and sourced from the USDA Pesticide Properties Database); and three different sets of soil physical data of varying quality (i.e., site specific, regional database, and particle size distribution data). We found that the selection of site-optimized pesticide sorption (K(oc)) and degradation parameters (half-life), compared to the use of more general database derived values, had significantly more impact than the quality of the soil input data used, but interestingly also more impact than the choice of the models. Models run with pesticide sorption and degradation parameters derived from observed solute concentrations data provided simulation outputs with goodness-of-fit values closest to optimum, followed by laboratory-derived parameters, with the USDA parameters providing the least accurate simulations. In general, when using pesticide sorption and degradation parameters optimized from site solute concentrations, the more complex models (LEACHM and HYDRUS-2D) were more accurate. However, when using USDA database derived parameters, all models performed about equally.
Bibliography:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 ObjectType-Article-2 ObjectType-Feature-1
ISSN:	0047-2425 1537-2537
DOI:	10.2134/jeq2005.0257