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The issue of whether models developed for current conditions can yield correct predictions when used under changed control, as is often the case in environmental management, is discussed. Two models of different complexity are compared on the basis of performance criteria, but it appears that good performance at the calibration stage does not guarantee correctly predicted behavior. A requirement for the detection of such a failure of the model is that the prediction uncertainty range is known. Two techniques to calculate uncertainty propagation are presented and compared: a stochastic first-order error propagation based on the extended Kalman filter (EKF), and a newly developed and robust Monte Carlo set-membership procedure (MCSM). The procedures are applied to a case study of water quality, generating a projective forecast of the algal dynamics in a lake (Lake Veluwe) in response to management actions that force the system into a different mode of behavior. It is found that the forecast from the more complex model falls within the prediction uncertainty range, but its informative value is low due to large uncertainty bounds. As a substitute for time-consuming revisions of the model, educated speculation about parameter shifts is offered as an alternative approach to account for expected but unmodelled changes in the system. KEY WORDS Uncertainty Prediction Parameter estimation Water quality modelling Lake eutrophicationAmong the incentives for modelling an environmental system, perhaps the most tempting is the desire to predict its future behavior. Yet while the literature on model construction is large, only very few convincing accounts are given of model verification, and reports on actual prediction performance are rare. The study of the requirements and peculiarities of the prediction process itself seems to be in its infancy. This is quite an unfortunate situation, because environmental systems are poorly understood and usually badly monitored, yet decisions regarding control measures will have a lasting impact in the years to come, and cannot easily be changed should they appear to be defective. The subject discussed therefore in this paper is: why do models, carefully constructed and calibrated on the basis of present information, sometimes perform so badly when used to predict the system's response to future management actions? Also, closely associated with this:Present address:
The issue of whether models developed for current conditions can yield correct predictions when used under changed control, as is often the case in environmental management, is discussed. Two models of different complexity are compared on the basis of performance criteria, but it appears that good performance at the calibration stage does not guarantee correctly predicted behavior. A requirement for the detection of such a failure of the model is that the prediction uncertainty range is known. Two techniques to calculate uncertainty propagation are presented and compared: a stochastic first-order error propagation based on the extended Kalman filter (EKF), and a newly developed and robust Monte Carlo set-membership procedure (MCSM). The procedures are applied to a case study of water quality, generating a projective forecast of the algal dynamics in a lake (Lake Veluwe) in response to management actions that force the system into a different mode of behavior. It is found that the forecast from the more complex model falls within the prediction uncertainty range, but its informative value is low due to large uncertainty bounds. As a substitute for time-consuming revisions of the model, educated speculation about parameter shifts is offered as an alternative approach to account for expected but unmodelled changes in the system. KEY WORDS Uncertainty Prediction Parameter estimation Water quality modelling Lake eutrophicationAmong the incentives for modelling an environmental system, perhaps the most tempting is the desire to predict its future behavior. Yet while the literature on model construction is large, only very few convincing accounts are given of model verification, and reports on actual prediction performance are rare. The study of the requirements and peculiarities of the prediction process itself seems to be in its infancy. This is quite an unfortunate situation, because environmental systems are poorly understood and usually badly monitored, yet decisions regarding control measures will have a lasting impact in the years to come, and cannot easily be changed should they appear to be defective. The subject discussed therefore in this paper is: why do models, carefully constructed and calibrated on the basis of present information, sometimes perform so badly when used to predict the system's response to future management actions? Also, closely associated with this:Present address:
A storm surge barrier was constructed in 1987 in the Oosterschelde estuary in the south-western delta of Holland to provide protection from flooding, while largely maintaining the tidal characteristics of the estuary. Despite efforts to minimize the hydraulic changes resulting from the barrage, it was expected that exchange with the North Sea, suspended sediment concentration and nutrient loads would decrease considerably. A model of the nutrients, algae and bottom organisms (mainly cockles and mussels) was developed to predict possible changes in the availability of food for these organisms. Although the model is based on standard constructs of ecology and hydraulics, many of its parameters are known with but low accuracy, being expressed as a range of possible values only. Running the model with all possible values of the parameters gives rise to a fairly wide range of model output responses. The calibration procedure used herein does not seek a single optimal value for the parameters but a decrease in the parameter range and thus a reduction in model prediction uncertainty. The field data available for calibration of the model are weighted according to their relationship with the model's objective, i.e. to predict food availability for shellfish. Despite the considerable physical changes resulting from the barrier food availability for shellfish is predicted to remain largely unchanged, due to the compensating effects of several other accompanying changes. There appears to be room for the extension of mussel culture, but at an increased risk of adverse conditions arising.
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