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Concepts like the 100‐year flood event can be misleading if they are not updated to reflect significant changes over time. Here, we model observed annual maximum daily streamflow using a nonstationary approach to provide the first global picture of changes in: (a) the magnitudes of the 20‐, 50‐, and 100‐year floods (i.e., flows of a given exceedance probability in each year); (b) the return periods of the 20‐, 50‐, and 100‐year floods, as assessed in 1970 (i.e., flows of a fixed magnitude); and (c) corresponding flood probabilities. Empirically, we find the 20‐/50‐year floods have mostly increased in temperate climate zones, but decreased in arid, tropical, polar, and cold zones. In contrast, 100‐year floods have mostly decreased in arid/temperate zones and exhibit mixed trends in cold zones, but results are influenced by the small number of stations with long records, and highlight the need for continued updating of hazard assessments. Plain Language Summary: Here, we provide the first global examination of recent changes in the size, frequency, and probability of extreme river floods using historical river records. Since the 1970s, the 20‐year and 50‐year extreme river floods have mostly increased in temperate zones but decreased in arid, tropical, polar, and cold zones. In contrast, the 100‐year floods have decreased in arid and temperate zones, and show mixed results in cold zones, but at a smaller sample of sites with long records. Descriptions of changes in extreme flooding depend largely on site selection, and are constrained by availability of long‐term data. Overall, our findings highlight the importance of regularly updating flood hazard assessments under nonstationarity. Key Points: We provide the first global nonstationary assessment of changes in the magnitude, return period, and probability of observed extreme floodsWe find increasing 20‐year and 50‐year floods in temperate climate zones but mostly decreases in arid, tropical, polar, and cold zonesFor the 100‐year floods, at a smaller sample of sites, we find decreases in arid and temperate zones and mixed results elsewhere [ABSTRACT FROM AUTHOR]

This paper examines marginal-risk behavior in a decision-theoretic setting that is sufficiently general to accommodate any decision-making model representable by a certainty equivalent. The analysis shows that risk aversion in its usual sense is a special case of marginal-risk aversion associated with mean-preserving changes in gambles. Thus, marginal-risk behavior and risk behavior are not inherently different. Rather, they manifest similar behavior evaluated at different gambles. The paradox of marginal-risk-loving risk averters arises from mixing definitions of an "increase in risk". [ABSTRACT FROM AUTHOR]

Animals can shape their timed behaviors based on experienced probabilistic relations in a nearly optimal fashion. On the other hand, it is not clear if they adopt these timed decisions by making computations based on previously learnt task parameters (time intervals, locations, and probabilities) or if they gradually develop their decisions based on trial and error. To address this question, we tested mice in the timed-switching task, which required them to anticipate when (after a short or long delay) and at which of the two delay locations a reward would be presented. The probability of short trials differed between test groups in two experiments. Critically, we first trained mice on relevant task parameters by signaling the active trial with a discriminative stimulus and delivered the corresponding reward after the associated delay without any response requirement (without inducing switching behavior). During the test phase, both options were presented simultaneously to characterize the emergence and temporal characteristics of the switching behavior. Mice exhibited timed-switching behavior starting from the first few test trials, and their performance remained stable throughout testing in the majority of the conditions. Furthermore, as the probability of the short trial increased, mice waited longer before switching from the short to long location (experiment 1). These behavioral adjustments were in directions predicted by reward maximization. These results suggest that rather than gradually adjusting their time-dependent choice behavior, mice abruptly adopted temporal decision strategies by directly integrating their previous knowledge of task parameters into their timed behavior, supporting the model-based representational account of temporal risk assessment. [ABSTRACT FROM AUTHOR]

In this paper, we propose a new formulation for the 'price duration curve' (PDC) using probability considerations and provide a procedure for constructing it. This curve is expected to be useful in the long-term prediction of market prices and is similar in spirit to the load duration curve. It shows the proportion of time over a given time horizon during which the real-time market price of electricity is expected to exceed specified dollar amounts. The price over a long term is a stochastic quantity that depends on physical factors such as production cost, load, generation availability, unit commitment, and transmission constraints. It also depends on economic factors such as strategic bidding and load elasticity. We illustrate a procedure for constructing a stochastic system-based model for the PDC, taking into account the randomness associated with load and generator outages. The effects of unit commitment, transmission congestion, and transmission outages are not considered. We use two economic models. One is due to Bertrand and represents perfect competition. The other model is due to Rudkevich et al. who have given a closed-form expression for the market-clearing price in an oligopoly consisting of several identical firms. Index Terms--Deregulation, electricity price, method of cumulants, oligopoly, price duration curve (PDC), reliability, risk analysis.

Different risks are associated with the operation and maintenance of wind farms in cold climate regions, mainly due to the harsh weather conditions that wind farms experience in that region such as the (i) increased stoppage rate of wind turbines due to harsh weather conditions, (ii) limited accessibility to wind farms due to snow cover on roads, and (iii) cold stress to workers at wind farms. In addition, there are risks that are caused by wind farms during their operation, which impact the surrounding environment and community such as the (iv) risk of ice throw from wind turbines, (v) environmental risks caused by the wind farms, and (vi) social opposition risk to installing wind farms in cold climate regions, such as the Arctic. The analysis of these six risks provides an overall view of the potential risks encountered by designers, operators, and decision makers at wind farms. This paper presents a methodology to quantify the aforementioned risks using fuzzy logic method. At first, two criteria were established for the probability and the consequences of each risk; with the use of experts' judgments, membership functions were graphed to reflect the two established criteria, which represented the input to the risk analysis process. Furthermore, membership functions were created for the risk levels, which represented the output. To test the proposed methodology, a wind farm in Arctic Norway was selected as a case study to quantify its risks. Experts provided their assessments of the probability and consequences of each risk on a scale from 0–10, depending on the description of the wind farm provided to them. Risk levels were calculated using MATLAB fuzzy logic toolbox and ranked accordingly. Limited accessibility to the wind farm was ranked as the highest risk, while the social opposition to the wind farm was ranked as the lowest. In addition, to demonstrate the effects of the Arctic operating conditions on performance and safety of the wind farm, the same methodology was applied to a wind farm located in a non-cold-climate region, which showed that the risks ranked differently. [ABSTRACT FROM AUTHOR]

A durable asset is sold in a sealed-bid first price auction. The seller sets an undisclosed reservation price. The seller has no prior information respecting the private valuations of the bidders. If no bid exceeds the reservation price, the asset is sequentially auctioned until it is sold. A rational seller will design an intertemporal series of reservation prices that maximize the discounted value of the transaction price. To accomplish this, the seller uses the history of unsuccessful bids to estimate the probability density functions governing the maximum bids at each hypothetical future auction date. [ABSTRACT FROM AUTHOR]

Abstract: We suggest CCS risk assessment should extend beyond the primary container to address a wide range of safety, economic, social, political and engineering issues. In New Zealand, for example, past experiences of large engineering projects suggests that failure to gain public support or to allocate appropriate resources to navigate through legislative process could provide significant barriers to successful CCS implementation. We have developed a modularized and probabilistic based logic tree which encompasses the main components of CCS (capture, transport, injection and storage) and is built upon the five issues mentioned above. [Copyright &y& Elsevier]