An inquiry into the potential of scenario analysis for dealing with uncertainty in strategic environmental assessment in China

Strategic environmental assessment (SEA) inherently needs to address greater levels of uncertainty in the formulation and implementation processes of strategic decisions, compared with project environmental impact assessment. The range of uncertainties includes internal and external factors of the complex system that is concerned in the strategy. Scenario analysis is increasingly being used to cope with uncertainty in SEA. Following a brief introduction of scenarios and scenario analysis, this paper examines the rationale for scenario analysis in SEA in the context of China. The state of the art associated with scenario analysis applied to SEA in China was reviewed through four SEA case analyses. Lessons learned from these cases indicated the word “scenario” appears to be abused and the scenario-based methods appear to be misused due to the lack of understanding of an uncertain future and scenario analysis. However, good experiences were also drawn on, regarding how to integrate scenario analysis into the SEA process in China, how to cope with driving forces including uncertainties, how to combine qualitative scenario storylines with quantitative impact predictions, and how to conduct assessments and propose recommendations based on scenarios. Additionally, the ways to improve the application of this tool in SEA were suggested. We concluded by calling for further methodological research on this issue and more practices.     

A Comparison of Bayesian Methods for Uncertainty Analysis in Hydraulic and Hydrodynamic Modeling

We evaluate and compare the performance of Bayesian Monte Carlo (BMC), Markov chain Monte Carlo (MCMC), and the Generalized Likelihood Uncertainty Estimation (GLUE) for uncertainty analysis in hydraulic and hydrodynamic modeling (HHM) studies. The methods are evaluated in a synthetic 1D wave routing exercise based on the diffusion wave model, and in a multidimensional hydrodynamic study based on the Environmental Fluid Dynamics Code to simulate estuarine circulation processes in Weeks Bay, Alabama. Results show that BMC and MCMC provide similar estimates of uncertainty. The posterior parameter densities computed by both methods are highly consistent, as well as the calibrated parameter estimates and uncertainty bounds. Although some studies suggest that MCMC is more efficient than BMC, our results did not show a clear difference between the performance of the two methods. This seems to be due to the low number of model parameters typically involved in HHM studies, and the use of the same likelihood function. In fact, for these studies, the implementation of BMC results simpler and provides similar results to MCMC. The results of GLUE are, on the other hand, less consistent to the results of BMC and MCMC in both applications. The posterior probability densities tend to be flat and similar to the uniform priors, which can result in calibrated parameter estimates centered in the parametric space.     

Toward quantifying the effectiveness of water trading under uncertainty

This paper presents a methodology for quantifying the effectiveness of water-trading under uncertainty, by developing an optimization model based on the interval-parameter two-stage stochastic program (TSP) technique. In the study, the effectiveness of a water-trading program is measured by the water volume that can be released through trading from a statistical point of view. The methodology can also deal with recourse water allocation problems generated by randomness in water availability and, at the same time, tackle uncertainties expressed as intervals in the trading system. The developed methodology was tested with a hypothetical water-trading program in an agricultural system in the Swift Current Creek watershed, Canada. Study results indicate that the methodology can effectively measure the effectiveness of a trading program through estimating the water volume being released through trading in a long-term view. A sensitivity analysis was also conducted to analyze the effects of different trading costs on the trading program. It shows that the trading efforts would become ineffective when the trading costs are too high. The case study also demonstrates that the trading program is more effective in a dry season when total water availability is in shortage.     

An inventory of N(2)O emissions from agriculture in China using precipitation-rectified emission factor and background emission

Fertilized agricultural soils are a major anthropogenic source of atmospheric N₂O. A credible national inventory of agricultural N₂O emission would benefit its global strength estimate. We compiled a worldwide database of N₂O emissions from fertilized fields that were consecutively measured for more than or close to one year. Both nitrogen input (N) and precipitation (P) were found to be largely responsible for temporal and spatial variabilities in annual N₂O fluxes (N₂O–N). Thus, we established an empirical model (N₂O–N = 1.49 P + 0.0186 P · N), in which both emission factor and background emission for N₂O were rectified by precipitation. In this model, annual N₂O emission consists of a background emission of 1.49 P and a fertilizer-induced emission of 0.0186 P · N. We used this model to develop a spatial inventory at the 10 × 10 km scale of direct N₂O emissions from agriculture in China. N₂O emissions from rice paddies were separately quantified using a cropping-specific emission factor. Annual fertilizer-induced N₂O emissions amounted to 198.89 Gg N₂O–N in 1997, consisting of 18.50 Gg N₂O–N from rice paddies and 180.39 Gg N₂O–N from fertilized uplands. Annual background emissions and total emissions of N₂O from agriculture were estimated to be 92.78 Gg N₂O–N and 291.67 Gg N₂O–N, respectively. The annual direct N₂O emission accounted for 0.92% of the applied N with an uncertainty of 29%. The highest N₂O fluxes occurred in East China as compared with the least fluxes in West China.     

Applied tracer tests in fractured rock: Can we predict natural gradient solute transport more accurately than fracture and matrix parameters?

Applied tracer tests provide a means to estimate aquifer parameters in fractured rock. The traditional approach to analysing these tests has been using a single fracture model to find the parameter values that generate the best fit to the measured breakthrough curve. In many cases, the ultimate aim is to predict solute transport under the natural gradient. Usually, no confidence limits are placed on parameter values and the impact of parameter errors on predictions of solute transport is not discussed. The assumption inherent in this approach is that the parameters determined under forced conditions will enable prediction of solute transport under the natural gradient. This paper considers the parameter and prediction uncertainty that might arise from analysis of breakthrough curves obtained from forced gradient applied tracer tests. By adding noise to an exact solution for transport in a single fracture in a porous matrix we create multiple realisations of an initial breakthrough curve. A least squares fitting routine is used to obtain a fit to each realisation, yielding a range of parameter values rather than a single set of absolute values. The suite of parameters is then used to make predictions of solute transport under lower hydraulic gradients and the uncertainty of estimated parameters and subsequent predictions of solute transport is compared. The results of this study show that predictions of breakthrough curve characteristics (first inflection point time, peak arrival time and peak concentration) for groundwater flow speeds with orders of magnitude smaller than that at which a test is conducted can sometimes be determined even more accurately than the fracture and matrix parameters.     

Life cycle assessment of active and passive groundwater remediation technologies

Groundwater remediation technologies, such as pump-and-treat (PTS) and funnel-and-gate systems (FGS), aim at reducing locally appearing contaminations. Therefore, these methodologies are basically evaluated with respect to their capability to yield local improvements of an environmental situation, commonly neglecting that their application is also associated with secondary impacts. Life cycle assessment (LCA) represents a widely accepted method of assessing the environmental aspects and potential impacts related to a product, process or service. This study presents the set-up of a LCA framework in order to compare the secondary impacts caused by two conceptually different technologies at the site of a former manufactured gas plant in the city of Karlsruhe, Germany. As a FGS is already operating at this site, a hypothetical PTS of the same functionality is adopted. During the LCA, the remediation systems are evaluated by focusing on the main technical elements and their significance with respect to resource depletion and potential adverse effects on ecological quality, as well as on human health. Seven impact categories are distinguished to address a broad spectrum of possible environmental loads. A main point of discussion is the reliability of technical assumptions and performance predictions for the future. It is obvious that a high uncertainty exists when estimating impact specific indicator values over operation times of decades. An uncertainty analysis is conducted to include the imprecision of the underlying emission and consumption data and a scenario analysis is utilised to contrast various possible technological variants. Though the results of the study are highly site-specific, a generalised relative evaluation of potential impacts and their main sources is the principle objective rather than a discussion of the calculated absolute impacts. A crucial finding that can be applied to any other site is the central role of steel, which particularly derogates the valuation of FGS due to the associated emissions that are harmful to human health. In view of that, environmental credits can be achieved by selecting a mineral-based wall instead of sheet piles for the funnel construction and by minimising the steel consumption for the gate construction. Granular activated carbon (GAC) is exclusively considered as the treatment material, both in-situ and on-site. Here it is identified as an additional main determinant of the relative assessment of the technologies since it is continuously consumed.     

Adaptive management intentions with a reality of evaluation: Getting science back into policy

In Australia’s Murray-Darling Basin water reform has been contentious as government attempts to reconcile historical over allocation of water to irrigation with the use of water for environmental outcomes. However, in many aspects, scientific knowledge of the environment is either imperfect, incomplete or environmental responses are unpredictable, with this uncertainty preventing definitive policy and closure of political arguments. In response to uncertainty and knowledge gaps, adaptive management has been written into the legislation, along with provisions for periodic evaluation.This research ascertains how adaptive management is understood by policy makers, with this indicative of future implementation of adaptive management. The way in which adaptive management is constructed by policy makers is determined through legislation, public speeches, government reports and semi-structured interviews. The findings demonstrate that adaptive management has been subsumed by evaluation. The loss of adaptive management as a distinct concept is seen as a loss of science and discovery from the policy process, with the dominance of evaluation discussed as limiting innovation and reinforcing a ‘muddling through’ of policy.     

Uncertainty,complexity and controversy in dolphin threat management: A role for post-normal science?

Managing fishing threats to populations of endemic, threatened Hector’s and Māui dolphins around New Zealand is a complex and controversial issue, underpinned by uncertain scientific knowledge. As such, it can be argued that it falls into the realm of post-normal science, which advocates transparency about uncertainties and stakeholder peer review of knowledge feeding into decision-making. This paper focuses on selected examples of modelling and risk assessment research relating to Hector’s and Māui dolphin threat management. It explores how knowledge is developed, shared and utilised by decision-makers, finding that uncertain scientific knowledge may be shared in ways that make it appear more certain, with some of the subjectivities involved in knowledge production hidden from view. Interviews with stakeholders illustrate how some stakeholders are aware of the subjectivities involved when uncertain knowledge underpins decision-making, so a lack of transparency may be leading to erosion of social trust in decisions made. This in turn can lead to a lack of support for dolphin conservation measures from key stakeholders such as the commercial fishing industry. The paper concludes that while moves towards increasing transparency and stakeholder involvement are apparent, a deeper embrace of post-normal science approaches to knowledge production and dissemination would contribute to effective dolphin threat management in New Zealand.     

Assessing the efficiency of Chilean water and sewerage companies accounting for uncertainty

Efficiency assessment of water and sewerage companies (WaSCs) has attracted considerable attention both for water company managers and water regulators. Within the methodological approaches that can be applied to estimate efficiency scores, data envelopment analysis (DEA) is the most widely applied technique. In spite of the positive features of DEA, it presents a major drawback which is its deterministic nature. In other words, conventional DEA models do not account for uncertainty in the data. To overcome this limitation, we assess, for the first time, the efficiency of a sample of Chilean WaSCs by using a DEA model with statistical tolerance in the data. Hence, 81 efficiency scores are estimated for each WaSC rather than a single score as with conventional DEA models. The results illustrate that outputs exhibit larger uncertainty than inputs. Moreover, WaSCs efficiency scores change significantly under the best-case and worst-case scenarios. The ranking of the WaSCs allows for the identification of which of them has the highest performance based on their efficiency scores. This information is essential to enhance efficiency and innovation in the water industry. Moreover, the introduction of uncertainty in the efficiency assessment allows for the prediction and ranking of future performance of WaSCs.     

Uncertainty Assessment for Management of Soil Contaminants with Sparse Data

In order for soil resources to be sustainably managed, it is necessary to have reliable, valid data on the spatial distribution of their environmental impact. However, in practice, one often has to cope with spatial interpolation achieved from few data that show a skewed distribution and uncertain information about soil contamination. We present a case study with 76 soil samples taken from a site of 15 square km in order to assess the usability of information gleaned from sparse data. The soil was contaminated with cadmium predominantly as a result of airborne emissions from a metal smelter. The spatial interpolation applies lognormal anisotropic kriging and conditional simulation for log-transformed data. The uncertainty of cadmium concentration acquired through data sampling, sample preparation, analytical measurement, and interpolation is factor 2 within 68.3 % confidence. Uncertainty predominantly results from the spatial interpolation necessitated by low sampling density and spatial heterogeneity. The interpolation data are shown in maps presenting likelihoods of exceeding threshold values as a result of a lognormal probability distribution. Although the results are not deterministic, this procedure yields a quantified and transparent estimation of the contamination, which can be used to delineate areas for soil improvement, remediation, or restricted area use, based on the decision-makers probability safety requirement.