The development and use of models for predicting exposures are increasingly common and are essential for many risk assessments of the United States Environmental Protection Agency (EPA). Exposure assessments conducted by the EPA to assist regulatory or policy decisions are often challenged to demonstrate their "scientific validity". Model validation has thus inevitably become a major concern of both EPA officiMs and the regulated community, sufficiently so that the EPA's Risk Assessment Forum is considering guidance for model validation. The present paper seeks to codify the issues and extensive foregoing discussion of validation with special reference to the development and use of models for predicting the impact of novel chemicals on the environment. Its preparation has been part of the process in formulating a White Paper for the EPA's Risk Assessment Forum. Its subject matter has been drawn from a variety of fields, including ecosystem analysis, surface water quality management, the contamination of groundwaters from high-level nuclear waste, and the control of air quality. The philosophical and conceptual bases of model validation are reviewed, from which it is apparent that validation should be understood as a task of product (or tool) design, for which some form of protocol for quality assurance will ultimately be needed. The commonly used procedures and methods of model validation are also reviewed, including the analysis of uncertainty. Following a survey of pe~st attempts at resolving the issue of modeI validation, we close by introducing the notion of a model having maximum relevance to the performance of a specific task, such as, for example, a predictive exposure assessment.Key words. Model validation; analysis of uncertainty; model verification; quality assurance; system identification; model calibration. I n t r o d u c t i o nThe construction and use of m a t h e m a t i c a l models are essential in predicting the possible consequences of releasing chemicals, some of which m a y be quite novel, into new environments. Substantial costs, and substantial damages to the environment, m a y attach to the regulatory decisions that are informed and thus guided by the predictions derived from a model. T h e risk of making a wrong decision will be strongly dependent on the reliability of these predictions, in just the same way as it
This paper presents an analytical model for predicting contaminant transport from a Gaussian vertical strip source in a three‐dimensional uniform ground‐water flow field. The model takes account of hydrodynamic dispersion, adsorption, and decay. In addition, the effects of partial penetration of the contaminant source and finite aquifer thickness are accounted for. Dimensional analysis and type curve procedure are developed for evaluating steady‐state (or maximum attainable) concentration along the plume center line. Application of the type curve procedure is demonstrated. Also included in the presentation is a method for evaluating the effective decay constant of a nonconservative chemical, based on an assumption of simple hydrolysis. The proposed model has been compared with three other analytical models given in the literature. Two simulation examples are presented. Results of the comparison indicate certain advantages of the present model over its previous counterparts.
An aggregate model was employed to study the effects of aggregate size distribution (ASD) on solute transport in a column. Instantaneous local sorption equilibria and nondegradation were assumed. The aggregate model was solved using an effective new iterative numerical scheme. Three ASDs from the literature were used in the calculations. The effects of aggregate size and size distribution can not be separated and are influenced by the flow regimes of the system. A mean variance radius was derived. This mean variance radius depends on the internal diffusion and mass transfer coefficient of the aggregates. It provided the best approximation among other types of mean aggregate radii used in the literature. Multiple mean variance radii should be used to represent the ASDs.
Three nonpoint source runoff models were tested and compared for their abilities to predict the movement of the pesticides toxaphene and atrazine (2‐chloro‐4‐(ethylamino)‐6‐(isopropylamino)‐1,3,5‐triazine) from a 15.6‐ha watershed in the Mississippi Delta region and a smaller watershed in the Southern Piedmont. The three models are the Agricultural Runoff Management (ARM), Continuous Pesticide Simulation (CPS), and the Chemical, Runoff, and Erosion from Agricultural Management Systems (CREAMS). Published data on runoff, erosion, toxaphene, and atrazine runoff were used to test the models. Testing exercises indicated that all models accurately reproduced field data. For the total period of study, model predictions of total runoff differed from field observations by 15% or less. For the CPS and ARM models, predictions of total erosion differed from observations by 6%, whereas CREAMS underpredicted erosion by 25%. All models are within 10% of observations in overland toxaphene loss predictions. Five‐year simulations indicated that the models can differ in their predictions of peak events. Sensitivity analysis indicated that ARM can predict higher losses of soluble chemicals than CPS or CREAMS, due to an interflow component unique to the ARM model. Similarly, estimation of a sediment enrichment in the CREAMS model resulted in higher toxaphene loss predictions than the other two models.
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