Robustness is being used increasingly for decision analysis in relation to deep uncertainty and many metrics have been proposed for its quantification. Recent studies have shown that the application of different robustness metrics can result in different rankings of decision alternatives, but there has been little discussion of what potential causes for this might be. To shed some light on this issue, we present a unifying framework for the calculation of robustness metrics, which assists with understanding how robustness metrics work, when they should be used, and why they sometimes disagree. The framework categorizes the suitability of metrics to a decision‐maker based on (1) the decision‐context (i.e., the suitability of using absolute performance or regret), (2) the decision‐maker's preferred level of risk aversion, and (3) the decision‐maker's preference toward maximizing performance, minimizing variance, or some higher‐order moment. This article also introduces a conceptual framework describing when relative robustness values of decision alternatives obtained using different metrics are likely to agree and disagree. This is used as a measure of how “stable” the ranking of decision alternatives is when determined using different robustness metrics. The framework is tested on three case studies, including water supply augmentation in Adelaide, Australia, the operation of a multipurpose regulated lake in Italy, and flood protection for a hypothetical river based on a reach of the river Rhine in the Netherlands. The proposed conceptual framework is confirmed by the case study results, providing insight into the reasons for disagreements between rankings obtained using different robustness metrics.

Multiple plausible future scenarios are being used increasingly in preference to a single deterministic or probabilistic prediction of the future in the long-term planning of water resources systems. These scenarios enable the determination of the robustness of a system-the consideration of performance across a range of plausible futures-and allow an assessment of which possible future system configurations result in a greater level of robustness. There are many approaches to selecting scenarios, and previous studies have observed that the choice of scenarios might affect the estimated robustness of the system. However, these observations have been anecdotal and qualitative. This paper develops a systematic, quantitative methodology for exploring the influence of scenario selection on the robustness and the ranking of decision alternatives. The methodology is illustrated on the Lake Problem. The quantitative results obtained confirm the qualitative observations of previous works, showing that the selection of scenarios is important, as it has a large influence on the robustness value calculated for each decision alternative. However, we show that it has a relatively small influence on how those decision alternatives are ranked. This implies that despite the difference in robustness values, similar decision outcomes will be reached in this case study, regardless of the basis on which the scenarios are obtained. It is also revealed that the impact of the scenarios on the robustness values is due to complex interactions with the system model and robustness metrics.

Strategies for monitoring the chemical and biological impacts of freshwater land-based and cage fish farms in the West of Scotland are described and the results of monitoring are presented. The compliance of landbased farms with discharge consents is discussed. The impact of fish farming on receiving water chemistry was found to be limited, but effects on benthic invertebrate communities in both running waters and lochs were more readily detectable, although generally localized in the immediate vicinity of the farm. The benthic fauna of a stream receiving wastes from a land-based farm recovered within 19 months of the discharge ceasing. At a vacated cage site in a loch, severe impact on the sediments was still evident after more than 3 years. Problems in monitoring for consent compliance are discussed and the need for closer liaison between the industry and regulatory bodies is emphasized.

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