Democracy at its Best? The Consensus Conference in a Cross-national Perspective

Over recent decades, public participation in technology assessment has spread internationally as an attempt to overcome or prevent societal conflicts over controversial technologies. One outcome of this new surge in public consultation initiatives has been the increased use of participatory consensus conferences in a number of countries. Existing evaluations of consensus conferences tend to focus on the modes of organization, as well as the outcomes, both procedural and substantial, of the conferences they examine. Such evaluations seem to rest on the assumption that this type of procedure has universally agreed goals and meanings, and that therefore consensus conferences can readily be interpreted and applied across national boundaries. This article challenges this approach to consensus conferences. The core of the article is a study of national differences in ideas about what constitutes legitimate goals for participatory arrangements. The study looks at three consensus conferences on GMOs, which took place in France, Norway, and Denmark. Drawing on this study, the article discusses the ways in which interpretations of the concept of participation; the value attributed to lay knowledge vs. technical expertise; as well as ideas about the role of the layperson, are all questions that prompt entirely different answers from country to country. Further, the article analyses these national differences within a theoretical framework of notions of democratic legitimacy.     

COMPARATIVE EVALUATION OF THREE URBAN RUNOFF MODELS1

ABSTRACT: Three urban runoff models, namely, the Road Research Laboratory Model (RRLM), the Storm Water Management Model (SWMM) and the University of Cincinnati Urban Runoff Model (UCURM), were examined by comparing the model simulated hydrographs with the hydrographs measured on several instrumented urban watersheds. This comparison was done for the hydrograph peak points as well as for the entire hydrographs using such statistical measures as the correlation coefficient, the special correlation coefficient and the integral square error. The results of the study indicated that, when applying the three selected non-calibrated models on small urban catchments, the SWM model performed marginally better than the RRL model and both these models were more accurate than the UCUR model. On larger watersheds, the comparisons between the SWM model and the other two models would be likely even more favourable for the SWM model, because it has the most advanced flow routing scheme among the studied models.     

Simulation modeling and resource management

Simulation models are becoming increasingly important as tools for synthesizing and applying information in almost all aspects of land management. They are particulary valuable for predicting and comparing outcomes of alternative decisions and assumptions. Models also permit managers to consider and integrate the potential influences of a large number of variables.     

ACCURACY OF IMPERVIOUS AREA VALUES ESTIMATED USING REMOTELY SENSED DATA1

ABSTRACT: Remote sensing offers an attractive alternative to conventional data collection employed in the estimation of certain hydrologic model parameters. In this investigation, the standard error of parameters estimated from Landsat data are examined. Relationships between the standard error and the size of the spatial-modeling units are developed that allow extending results to larger areas. Based upon the investigations conducted, a generalized model of the error relationships could not be developed.     

REDUCING THE COST OF CONTINUOUS HYDROLOGIC-HYDRAULIC SIMULATION1

ABSTRACT: The use of continuous hydrologic-hydraulic-water quality models is inhibited by their large computer run costs relative to cost incurred with discrete event models. The fixed recurrence interval transfer (FRIT) technique is a means of achieving substantial reductions in computer costs associated with continuous models while retaining their technical advantages. The FRIT technique is applicable where it is reasonable to assume that the recurrence interval of the response of a watershed to a causative meteorologic event is the same for both “before” and “after” conditions. Example applications of the FRIT technique to the hydrologic-hydraulic modeling of floodwater storage, land use changes, and channel modifications are presented to demonstrate the procedure, to suggest the expected accuracy, and to illustrate how computer run costs might be reduced by 99% or more. The FRIT technique is intended for preliminary assessment of the impact of alternative land use conditions and structural water control measures.     

THE EFFECT OF DATA INDEPENDENCE IN MODEL CALIBRATION AND MODEL TESTING1

ABSTRACT: With the increased use of models in hydrologic design, there is an immediate need for a comprehensive comparison of hydrologic models, especially those intended for use at ungaged locations (i.e., where measured data are either not available or inadequate for model calibration). But some past comparisons of hydrologic models have used the same data base for both calibration and testing of the different models or implied that the results of model calibration are indicative of the accuracy at ungaged locations. This practice was examined using both the regression equation approach to peak discharge estimation and a unit hydrograph model that was intended for use in urban areas. The results suggested that the lack of data independence in the calibration and testing of regression equations may lead to both biased results and misleading statements about prediction accuracy. Additionally, although split-sample testing is recognized as desirable, the split-samples should be selected using a systematic-random sampling scheme, rather than random sampling, because random sampling with small samples may lead to a testing sample that is not representative of the population. A systematic-random sampling technique should lead to more valid conclusions about model reliability. For models like a unit hydrograph model, which are more complex and for which calibration is a more involved process, data independence is not as critical because the data fitting error variation is not as dominant as the error variation due to the calibration process and the inability of the model structure to conform with data variability.     

OPTIMAL RESERVOIR MANAGEMENT AND CROP PLANNING UNDER DETERMINISTIC AND STOCHASTIC INFLOWS1

ABSTRACT: This study analyzes planning under deterministic and stochastic inflows for the Mayurakshi project in India. Models are developed to indicate the optimal storage of reservoir water, the transfer of water to the producing regions, and the spillage of water from the reservoir, if needed. A deterministic programming model was first formulated to represent the existing situation. A chance-constrained model then was constructed to evaluate potential violations of the deterministic model. Both models were quantified for the command area. Data were collected from surveys of the area and from government agencies. Both the deterministic and change-constrained models suggest a more intensive cropping program in the region. Both emphasize more dependence on rabi and less on kharif crops. The chance-constrained especially suggests use of more water in the rabi season. Important chances in cropping programs and labor use take place under the chance-constrained model.     

COMPARISON OF TWO AUTOREGRESSIVE MODELS FOR MONTHLY STREAM FLOW GENERATION1

ABSTRACT: Two autoregressive models for monthly stream flow generation are compared based on the reproduction of the historical record in terms of several important statistics such as the mean, standard deviation, skewness coefficient, correlation coefficient, and the reservoir storage components. In the comparison, both theoretical considerations and practical applications are employed to evaluate the performance of each model.     

STOCHASTIC MODELING OF MONTHLY AND DAILY RAINFALL SEQUENCES1

ABSTRACT: A monthly model and two daily models (I and II) are presented for the purpose of generating monthly and daily rainfall sequences in the Quae Yai river basin in Thailand. Performance of the models are evaluated by comparing the statistical parameters of the generated sequences with those from historical data. For monthly generation, Thomas-Fiering model worked satisfactorily in spite of the monthly correlations being weak, if any. Daily Model I, which assumes no persistence between daily rainfall amounts within the wet spells, could not preserve some important parameters regardless of the simplicity in model construction. Application of multi-state transition probability matrix model gave good results, although the user has to modify some parameters looking at the performance of the model for each historical record.