BIOMOVS II: An international test of the performance of environmental transfer models

The Biospheric Model Validation Study-Phase II (BIOMOVS II) was an international cooperative program that tested the accuracy of predictions of environmental assessment models. Model evaluation was based on calculations made by individual participants for 10 test scenarios that addressed both short- and long-term releases of radioactivity from facilities such as power reactors, solid waste disposal repositories and uranium mill tailings. Model predictions were compared with each other and, where possible, with independent field observations, and reasons were sought for any differences that arose. Qualitative topics were also considered, including development of systematic methodologies for radiological assessments. This paper addresses conclusions arising from the study as a whole. Confidence intervals on predictions and differences between predictions and observations were often less than a factor of 10, although there was much variability among models and scenarios. Model performance depended critically, not only on the formulation and parameter values of the model itself, but also on the experience and assumptions made by the user. The study demonstrated the need to better explain and justify all aspects of model structure and application and to assess all sources of uncertainty. A key recommendation was that assessments should not be undertaken in isolation by one individual using one model.     

Effect of user interpretation on uncertainty estimates: examples from the air-to-milk transfer of radiocesium

An important source of uncertainty in predictions of numerical simulation codes of environmental transport processes arises from the assumptions made by the user when interpreting the model and the scenario to be assessed. This type of uncertainty was examined systematically in this study and was compared with uncertainty due to varying parameter values in a code. Three terrestrial food chain codes that are driven by deposition of radionuclides from the atmosphere were used by up to ten participants to predict total deposition of ¹³⁷Cs and concentrations on pasture and in milk for two release scenarios. Collective uncertainty among the predictions of the ten users for concentrations in milk calculated for one scenario by one code was a factor of 2000, while the largest individual uncertainty was 20 times lower. Choice of parameter values contributed most to user-induced uncertainty, followed by scenario interpretation. Due to the significant disparity in predictions, it is recommended that assessments should not be carried out alone by a single code user.     

Model testing using data on 131I released from Hanford

The Hanford test scenario described an accidental release of 131I to the environment from the Hanford Purex Chemical Separations Plant in September 1963. Based on monitoring data collected after the release, this scenario was used by the Dose Reconstruction Working Group of BIOMASS to test models typically used in dose reconstructions. The primary exposure pathway in terms of contribution to human doses was ingestion of contaminated milk and vegetables. Predicted mean doses to the thyroid of reference individuals from ingestion of 131I ranged from 0.0001 to 0.8 mSv. For one location, predicted doses to the thyroids of two children with high milk consumption ranged from 0.006 to 2 mSv. The predicted deposition at any given location varied among participants by a factor of 5-80. The exercise provided an opportunity for comparison of assessment methods and conceptual approaches, testing model predictions against measurements, and identifying the most important contributors to uncertainty in the assessment result. Key factors affecting predictions included the approach to handling incomplete data, interpretation of input information, selection of parameter values, adjustment of models for site-specific conditions, and treatment of uncertainties.     

Radionuclide transfer to fruit in the IAEA TRS 364 Revision

Information on the transfer of radionuclides to fruits was almost absent in the former TRS 364 “Handbook of parameter values for the prediction of radionuclide transfer in temperate environments”. The revision of the Handbook, carried out under the IAEA Programme on Environmental Modelling for RAdiation Safety (EMRAS), takes into account the information generated in the years following the Chernobyl accident and the knowledge produced under the IAEA BIOMASS (Biosphere Modelling and Assessment) Programme in the years 1997–2000. This paper describes the most important processes concerning the behaviour of radionuclides in fruits reported in the IAEA TRS 364 Revision and provides recommendations for research and modelling.     

Radionuclide migration in forest ecosystems--results of a model validation study

The primary objective of the IAEA's BIOMASS Forest Working Group (FWG) was to bring together experimental radioecologists and modellers to facilitate the exchange of information which could be used to improve our ability to understand and forecast radionuclide transfers within forests. This paper describes a blind model validation exercise which was conducted by the FWG to test nine models which members of the group had developed in response to the need to predict the fate of radiocaesium in forests in Europe after the Chernobyl accident. The outcomes and conclusions of this exercise are summarised. It was concluded that, as a group, the models are capable of providing an envelope of predictions which can be expected to enclose experimental data for radiocaesium contamination in forests over the time scale tested. However, the models are subject to varying degrees of conceptual uncertainty which gives rise to a very high degree of divergence between individual model predictions, particularly when forecasting edible mushroom contamination. Furthermore, the forecasting capability of the models over future decades currently remains untested.     

Examination of model uncertainty and parameter interaction in a global carbon cycling model (GLOCO)

Simulation models play an important role in understanding the causes and consequences of climate change. In order to make full use of these models, it is necessary to establish the magnitude and sources of uncertainty associated with their predictions. This information can be used to achieve a better understanding of the simulated systems, to increase the reliability of model predictions, to guide field surveys and laboratory experiments, and to define realistic values that should be used in scientific, economic, and political discussions of future conditions. In this paper, a new tree-structured density estimation technique that extends the ability of Monte Carlo-based analyses to explore parameter interactions and uncertainty in complex environmental models was applied. The application of the technique is demonstrated using the GLOCO global carbon cycle model. The paper demonstrates that there are numerous distinct parameter combinations that can meet fairly stringent calibration criteria, and they are concentrated in relatively small subsets of the parameter space. These different subsets can be viewed as representing different ecological systems that achieve the same calibration or performance goals in fundamentally different ways. It is also shown that the simulated responses of these systems to future environmental change can lead to different conclusions regarding the interaction between factors affecting environmental processes, such as the growth of vegetation. Together, these results show how the tree-structured density estimation technique can be applied to gain a broader understanding of model performance and of ecosystem responses to change.     

Model testing using data on 137Cs from Chernobyl fallout in the Iput River catchment area of Russia

Data collected for 10 years following the Chernobyl accident in 1986 have provided a unique opportunity to test the reliability of computer models for contamination of terrestrial and aquatic environments. The Iput River scenario was used by the Dose Reconstruction Working Group of the BIOMASS (Biosphere Modelling and Assessment Methods) programme. The test area was one of the most highly contaminated areas in Russia following the accident, with an average contamination density of 137Cs of 800,000 Bq m-2 and localized contamination up to 1,500,000 Bq m-2, and a variety of countermeasures that were implemented in the test area had to be considered in the modelling exercise. Difficulties encountered during the exercise included averaging of data to account for uneven contamination of the test area, simulating the downward migration and changes in bioavailability of 137Cs in soil, and modelling the effectiveness of countermeasures. The accuracy of model predictions is dependent at least in part on the experience and judgment of the participant in interpretation of input information, selection of parameter values, and treatment of uncertainties.     

Modelling and experimental studies on the transfer of radionuclides to fruit

Although fruit is an important component of the diet, the extent to which it contributes to radiological exposure remains unclear, partially as a consequence of uncertainties in models and data used to assess transfer of radionuclides in the food chain. A Fruits Working Group operated as part of the IAEA BIOMASS (BIOsphere Modelling and ASSessment) programme from 1997 to 2000, with the aim of improving the robustness of the models that are used for radiological assessment. The Group completed a number of modelling and experimental activities including: (i) a review of experimental, field and modelling information on the transfer of radionuclides to fruit; (ii) discussion of recently completed or ongoing experimental studies; (iii) development of a database on the transfer of radionuclides to fruit; (iv) development of a conceptual model for fruit and (v) two model intercomparison studies and a model validation study. The Group achieved significant advances in understanding the processes involved in transfer of radionuclides to fruit. The work demonstrated that further experimental and modelling studies are required to ensure that the current generation of models can be applied to a wide range of scenarios.     

A validation study for the transport of 134Cs to strawberry

The paper presents results on model validation by field experiment for transport of 134Cs to strawberry. The transfer of 134Cs to herbaceous plants was investigated following a wet deposition after an acute release during 2000. Leaf-to-fruit, soil-to-fruit and direct fruit pathways were examined. The available meteorological and local soil information together with the experimental data were taken into account by the model RUVFRU. The processes are described by first order differential equations. In the case of foliar contamination scenarios measured and calculated results for fruit are in good agreement. However, the results of soil contamination scenarios provide large differences of up to three orders of magnitude between model predictions and experimental values for either fruit or other parts of the plant. The bias could be explained by the underestimation of the interception of the plant at the beginning of the season, in the soil contamination scenario. The model output permits prompt assessment of emergency situations and provides aid making decisions concerning mitigation of the consequences of the accident.     

Addressing uncertainties in the ERICA Integrated Approach

Like any complex environmental problem, ecological risk assessment of the impacts of ionising radiation is confounded by uncertainty. At all stages, from problem formulation through to risk characterisation, the assessment is dependent on models, scenarios, assumptions and extrapolations. These include technical uncertainties related to the data used, conceptual uncertainties associated with models and scenarios, as well as social uncertainties such as economic impacts, the interpretation of legislation, and the acceptability of the assessment results to stakeholders. The ERICA Integrated Approach has been developed to allow an assessment of the risks of ionising radiation, and includes a number of methods that are intended to make the uncertainties and assumptions inherent in the assessment more transparent to users and stakeholders. Throughout its development, ERICA has recommended that assessors deal openly with the deeper dimensions of uncertainty and acknowledge that uncertainty is intrinsic to complex systems. Since the tool is based on a tiered approach, the approaches to dealing with uncertainty vary between the tiers, ranging from a simple, but highly conservative screening to a full probabilistic risk assessment including sensitivity analysis. This paper gives on overview of types of uncertainty that are manifest in ecological risk assessment and the ERICA Integrated Approach to dealing with some of these uncertainties.     

Effects of model complexity on uncertainty estimates

In the Model Complexity working group of BIOMOVS II, models of varying complexity have been applied to a theoretical problem concerning downward transport of radionuclides in soils. The purpose was to study how uncertainty in model predictions varies with model complexity and how model simplifications can suitably be made. A scenario describing a case of surface contamination of a pasture soil was defined. Three different radionuclides with different environmental behavior and radioactive half-lives were considered: ¹³⁷Cs, ⁹⁰Sr and ¹²⁹I. A detailed specification of the parameters required by different kinds of models was given, together with reasonable values for the parameter uncertainty. A total of seven modelling teams participated in the study using 13 different models. Four of the modelling groups performed uncertainty calculations using nine different modelling approaches. The models ranged in complexity from analytical solutions of a 2-box model using annual average data to numerical models coupling hydrology and transport using data varying on a daily basis.     

"Reference Biospheres" for solid radioactive waste disposal: the BIOMASS methodology

The BIOMASS Theme 1 project has developed a methodology for the logical and defensible construction of 'assessment biospheres': mathematical representations of biospheres used in the total system performance assessment of radioactive waste disposal. The BIOMASS Methodology provides a systematic approach to decision making, including decisions on how to address biosphere change. The BIOMASS Methodology was developed through consultation and collaboration with many relevant organisations, including regulators, operators and a variety of independent experts. It has been developed to be practical and to be consistent with recommendations from ICRP and IAEA on radiation protection in the context of the disposal of long-lived solid radioactive wastes. The five main steps in the methodology are described in this paper. The importance of a clear assessment context, to clarify intentions and to support a coherent biosphere assessment process within an overall repository performance assessment, is strongly emphasised. A well described assessment context is an important tool for ensuring consistency across the performance assessment as a whole. The use of interaction matrices has been found to be helpful in clarifying the interactions between different habitats within the biosphere system and the significant radionuclide transfer pathways within the biosphere system. Matrices also provide a useful means of checking for consistency.     

Imprecision of dose predictions for radionuclides released to the environment: An application of a Monte Carlo simulation technique

An evaluation of the imprecision in dose predictions has been performed using current dose assessment models and present knowledge of the variability or uncertainty in model parameter values. The propagation of parameter uncertainties is demonstrated using a Monte Carlo technique for elemental ¹³¹I transported via the pasture-cow-milk-child pathway. The results indicate that when site-specific information is not available the imprecision inherent in the predictions for this pathway is potentially large. Generally, the 99th percentile in thyroid dose for children was predicted to be approximately an order of magnitude greater than the median value. The potential consequences of the imprecision in dose for radiation protection purposes are discussed.     

Radionuclide transfer to fruits: A critical review. Foreword

After completion of the (Validation of Environmental Model Predictions) (VAMP) and (BIOspheric Model Validation Study) (BIOMOVS II) Programmes, the Division of Radiation and Waste Safety of the IAEA decided to promote a new co-ordinated research programme to continue activities in the area of biosphere modelling. As a result, the BIOMASS Programme on BIOsphere Modelling and ASSessment was launched in Vienna in October 1996. The Programme is scheduled to finish in October 2000. The overall objective of BIOMASS is to provide an international focal point in the area of biosphere assessment modelling. There are 3 Themes and 11 working groups in BIOMASS. The objective of the Theme 3 Fruits Working Group is to improve understanding of the uptake and transfer of radionuclides from different sources to fruit. As part of the work programme, a review was undertaken of the experimental, field and modelling information on the transfer of radionuclides to fruit.     

Scenario-model-parameter: a new method of cumulative risk uncertainty analysis

The recently developed concepts of aggregate risk and cumulative risk rectify two limitations associated with the classical risk assessment paradigm established in the early 1980s. Aggregate exposure denotes the amount of one pollutant available at the biological exchange boundaries from multiple routes of exposure. Cumulative risk assessment is defined as an assessment of risk from the accumulation of a common toxic effect from all routes of exposure to multiple chemicals sharing a common mechanism of toxicity. Thus, cumulative risk constitutes an improvement over the classical risk paradigm, which treats exposures from multiple routes as independent events associated with each specific route. Risk assessors formulate complex models and identify many realistic scenarios of exposure that enable them to estimate risks from exposures to multiple pollutants and multiple routes. The increase in complexity of the risk assessment process is likely to increase risk uncertainty. Despite evidence that scenario and model uncertainty contribute to the overall uncertainty of cumulative risk estimates, present uncertainty analysis of risk estimates accounts only for parameter uncertainty and excludes model and scenario uncertainties. This paper provides a synopsis of the risk assessment evolution and associated uncertainty analysis methods. This evolution leads to the concept of the scenario-model-parameter (SW) cumulative risk uncertainty analysis method. The SMP uncertainty analysis is a multiple step procedure that assesses uncertainty associated with the use of judiciously selected scenarios and models of exposure and risk. Ultimately, the SMP uncertainty analysis method compares risk uncertainty estimates determined using all three sources of uncertainty with conventional risk uncertainty estimates obtained using only the parameter source. An example of applying the SMP uncertainty analysis to cumulative risk estimates from exposures to two pesticides indicates that inclusion of scenario and model sources.     

MUD: a Model to investigate the migration of 137Cs in the Urban environment and Drainage and sewage treatment systems

A model is presented for the migration of 137Cs in the urban environment, including the drainage systems and the sewage treatment plants, with flexibility to be adapted to different configurations common in urban areas. The dynamics of 137Cs is simulated both under natural evolution and in case of forced decontamination, which can have a direct impact on the radioactivity going to sewers. The model assesses the activity concentrated in sewage sludge and that discharged with the treated or untreated effluent to the receiving watercourse. Tests made for two post-Chernobyl contamination scenarios in Sweden show differences between model predictions and observed results within the range of the experimental uncertainties. An uncertainty and sensitivity analysis of the main model parameters indicates that some parameters may have a significant influence on the results of the model. Moreover, the model uncertainty is driven by a few parameters; therefore, additional research could be necessary into these parameters, aiming at simplifying the model without losing its predictive power.     

Uncertainty in the difference between maps of future land change scenarios

It is essential to measure whether maps of various scenarios of future land change are meaningfully different, because differences among such maps serve to inform land management. This paper compares the output maps of different scenarios of future land change in a manner that contrasts two different approaches to account for the uncertainty of the simulated projections. The simpler approach interprets the scenario storyline concerning the quantity of each land change transition as assumption, and then considers the range of possibilities concerning the value added by a simulation model that specifies the spatial allocation of land change. The more complex approach estimates the uncertainty of future land maps based on a validation measurement with historic data. The technique is illustrated by a case study that compares two scenarios of future land change in the Plum Island Ecosystems of northeastern Massachusetts, in the United States. Results show that if the model simulates only the spatial allocation of the land changes given the assumed quantity of each transition, then there is a clearly bounded range for the difference between the raw scenario maps; but if the uncertainties are estimated by validation, then the uncertainties can be so great that the output maps do not show meaningful differences. We discuss the implications of these results for a future research agenda of land change modeling. We conclude that a productive approach is to use the simpler method to distinguish clearly between variations in the scenario maps that are due to scenario assumptions versus variations due to the simulation model.     

Use of contaminated well water, example reference biospheres 1 and 2A

The BIOMASS programme's Theme 1 evaluated a number of scenarios, which assisted in the development of practical guidance. A total of four Example Reference Biospheres were fully developed, with the assumptions, data, and models thoroughly documented. These Examples display both the practicality and the transparency available through the use of the Reference Biosphere Methodology. While the methodology is designed to promote transparency and traceability, proper documentation and justification is still the responsibility of the user. The Examples can also be used as generic analyses in some situations. Although it is anticipated that each of the Reference Biospheres explored within BIOMASS Theme 1 should be a useful practical example, the quantitative results of the model calculations are not intended to be understood as prescribed biosphere 'conversion factors'. In choosing to implement an Example, careful consideration would need to be given to their relevance (including associated data) to the particular assessment context at hand. In general, the more complex the model is, the more limited applicability it has for generic purposes. For example, ERB1A (direct use of well water for drinking) can be used straightforwardly, with minor or no adjustments, at a number of generic sites. Example 2A, however, for which climatic conditions and agricultural practices need to be specified, would need to be implemented for each specific situation.