Analysing the sensitivity behaviour of two hydrology models

Recently, the New Morris Method has been presented as an effective sensitivity analysis tool for mathematical models. The New Morris Method estimates the sensitivity of an output parameter to a given set of input parameters (first-order effects) and the extent these parameters interact with each other (second-order effects). This method requires the specification of two parameters (runs and resolution) that control the sampling of the output parameter to determine its sensitivity to various inputs. The criteria for these parameters have been set on the analysis of a well-behaved analytical function (see Cropp and Braddock, Reliab. Eng. Syst. Saf. 78:77–83, 2002), which may not be applicable to other physical models that describe complex processes. This paper will investigate the appropriateness of the criteria from (Cropp and Braddock, 2002) and hence the effectiveness of the New Morris Method to determine the sensitivity behaviour of two hydrologic models: the Soil Erosion and Deposition System and Griffith University Representation of Urban Hydrology. In the first case, this paper will separately analyse the sensitivity of an output parameter on a set of input parameters (first- and second-order effects) for each model and discuss the physical meaning of these sensitivities. This will be followed by an investigation into the sampling criteria by exploring the convergence of the sensitivity behaviour for each model as the sampling of the parameter space is increased. By comparing these trends to the convergence behaviour from Cropp and Braddock (2002), we will determine how well the New Morris Method estimates the sensitivity for each model and whether the sampling criteria are appropriate for these models. It will be shown that the New Morris Method can provide additional insight into the functioning of these models, and that, under a different metric, the sensitivity behaviour of these models does converge confirming the sampling criteria set by Cropp and Braddock.     

Energy-dispersive X-ray fluorescence systems as analytical tool for assessment of contaminated soils

To determine the heavy metal content in soil samples at contaminated locations, a static and time consuming procedure is used in most cases. Soil samples are collected and analyzed in the laboratory at high quality and high analytical costs. The demand by government and consultants for a more dynamic approach and by customers requiring performances in which analyses are performed in the field with immediate feedback of the analytical results, is growing. Especially during the follow-up of remediation projects or during the determination of the sampling strategy, field analyses are advisable. For this purpose four types of ED-XRF systems, ranging from portable up to high performance laboratory systems, have been evaluated. The evaluation criteria are based on the performance characteristics for all the ED-XRF systems such as limit of detection, accuracy and the measurement uncertainty on one hand, and also the influence of the sample pretreatment on the obtained results on the other hand. The study proved that the field portable system and the bench top system, placed in a mobile van, can be applied as field techniques, resulting in semi-quantitative analytical results. A limited homogenization of the analyzed sample significantly increases the representativeness of the soil sample. The ED-XRF systems can be differentiated by their limits of detection which are a factor of 10 to 20 higher for the portable system. The accuracy of the results and the measurement uncertainty also improved using the bench top system. Therefore, the selection criteria for applicability of both field systems are based on the required detection level and also the required accuracy of the results.     

An evaluation of in situ microcosms for validating aquatic fate and transport models

The fates of two compounds, 2,4 Dichlorophenoxy Acetic Acid Butoxyethyl Ester (2,4-DBEE) and 1,4 Dichlorobenzene (1,4-DCB), were examined in in situ microcosms placed in a pond and compared with the fates in the pond itself. Results also were compared with predictions of an aquatic fate and transport model (EXAMS). Decay rates of 2,4-DBEE were not significantly different among the microcosms, pond and model predictions. The decay rate of 1,4-DCB in the microcosms was significantly lower than the rate for the pond, and lower than the rate predicted by the model. The low volatility of 1,4-DCB in the microcosms is attributed primarily to lack of water surface turbulence in the microcosms.     

An Integrated Assessment of Climate Change and the Accelerated Introduction of Advanced Energy Technologies - An Application of MiniCAM 1.0

We report results from the application of an integrated assessment model, MiniCAM 1.0. The model is employed to explore the full range of climate change implications of the successful development of cost effective, advanced, energy technologies. These technologies are shown to have a profound effect on the future magnitude and rate of anthropogenic climate change. We find that the introduction of assumptions developed by a group of ‘bottom-up’ modelers for the LEESS scenarios into a ‘top-down’ model, the Edmonds-Reilly-Barns Model, leads to ‘top down’ emissions trajectories similar to those of the LEESS. The cumulative effect of advanced energy technologies is to reduce annual emissions from fossil fuel use to levels which stabilize atmospheric concentrations below 550 ppmv. While all energy technologies play roles, the introduction of advanced biomass energy production technology is particularly important. The consideration of all greenhouse related anthropogenic emissions, and in particular sulfur dioxide, is found to be important. We find that the consideration of sulfur dioxide emissions coupled to rapid reductions in carbon dioxide emissions leads to higher global mean temperatures prior to 2050 than in the reference case. This result is due to the short-term cooling impact of sulfate aerosols, which dominates the long-term warming impact of CO₂ and CH₄ in the years prior to 2050. We also show that damage calculations which use only mean global temperature and income may be underestimating damages by up to a factor of five. Disaggregating income reduces this to a factor of two, still a major error. Finally, the role of the discount rate is shown to be extraordinarily important to technology preference.