Browsing by Subject "Risk analysis"

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Climate change adaptation to increasing isk of glacial lake outburst floods : decision making methodology for risk management applied to Imja Lake in Nepal and Lake Palcacocha in Peru
(2016-08) Cuéllar, Amanda Dulcinea; McKinney, Daene C.; Stahl, Dale O; Passalacqua, Paola; Webber, Michael E; Gilbert, Robert
Glacial retreat around the world, accelerated by climate change, has led to the formation of glacier lakes that present a risk of a glacial lake outburst flood (GLOF). GLOFs are sudden, catastrophic events that are impossible to predict. Communities in the path of a potential GLOF are now attempting to implement adaptation projects, yet no quantitative data or guidance is available to understand the benefits of adaptation projects or how to weigh these benefits against the cost of project implementation. The objective of this work is to develop a rational decision making methodology for GLOF risk management that incorporates available scientific information and the uncertainty surrounding the understanding of GLOF events. The decision making methodology consists of 1) identifying flooding scenarios, 2) evaluating the consequences of flooding scenarios, and 3) a nuanced (in terms of the inclusion of intangibles and probabilistic events) economic analysis of flood consequences and adaptation options. The methodology is applied to Lake Palcacocha in Peru and Imja Lake in Nepal to demonstrate the robustness of the methodology in light of different sources of uncertainty and data gaps. For Imja Lake it is concluded that lowering the lake 10 m is the best decision, from an economic standpoint. Nonetheless, the decision is sensitive to changes in the decision tree variables, which should be assessed for accuracy. At Lake Palcacocha it was determined that a GLOF would result in substantial damage to the city of Huaraz and the best decision is to lower the lake 30 m and install an emergency warning system (EWS). This decision is robust to large changes in the uncertain variables.
Optimization of production allocation under price uncertainty : relating price model assumptions to decisions
(2011-08) Bukhari, Abdulwahab Abdullatif; Jablonowski, Christopher J.; Lasdon, Leon S.; Dyer, James S.
Allocating production volumes across a portfolio of producing assets is a complex optimization problem. Each producing asset possesses different technical attributes (e.g. crude type), facility constraints, and costs. In addition, there are corporate objectives and constraints (e.g. contract delivery requirements). While complex, such a problem can be specified and solved using conventional deterministic optimization methods. However, there is often uncertainty in many of the inputs, and in these cases the appropriate approach is neither obvious nor straightforward. One of the major uncertainties in the oil and gas industry is the commodity price assumption(s). This paper investigates this problem in three major sections: (1) We specify an integrated stochastic optimization model that solves for the optimal production allocation for a portfolio of producing assets when there is uncertainty in commodity prices, (2) We then compare the solutions that result when different price models are used, and (3) We perform a value of information analysis to estimate the value of more accurate price models. The results show that the optimum production allocation is a function of the price model assumptions. However, the differences between models are minor, and thus the value of choosing the “correct” price model, or similarly of estimating a more accurate model, is small. This work falls in the emerging research area of decision-oriented assessments of information value.
Risk analysis in tunneling with imprecise probabilities
(2010-08) You, Xiaomin; Tonon, Fulvio; Rathje, Ellen M.; Gilbert, Robert B.; Manuel, Lance; Smirnoff, Timothy P.
Due to the inherent uncertainties in ground and groundwater conditions, tunnel projects often have to face potential risks of cost overrun or schedule delay. Risk analysis has become a required tool (by insurers, Federal Transit Administration, etc.) to identify and quantify risk, as well as visualize causes and effects, and the course (chain) of events. Various efforts have been made to risk assessment and analysis by using conventional methodologies with precise probabilities. However, because of limited information or experience in similar tunnel projects, available evidence in risk assessment and analysis usually relies on judgments from experienced engineers and experts. As a result, imprecision is involved in probability evaluations. The intention of this study is to explore the use of the theory of imprecise probability as applied to risk analysis in tunneling. The goal of the methodologies proposed in this study is to deal with imprecise information without forcing the experts to commit to assessments that they do not feel comfortable with or the analyst to pick a single distribution when the available data does not warrant such precision. After a brief introduction to the theory of imprecise probability, different types of interaction between variables are studied, including unknown interaction, different types of independence, and correlated variables. Various algorithms aiming at achieving upper and lower bounds on previsions and conditional probabilities with assumed interaction type are proposed. Then, methodologies have been developed for risk registers, event trees, fault trees, and decision trees, i.e. the standard tools in risk assessment for underground projects. Corresponding algorithms are developed and illustrated by examples. Finally, several case histories of risk analysis in tunneling are revisited by using the methodologies developed in this study. All results obtained based on imprecise probabilities are compared with the results from precise probabilities.
Vulnerability and decision risk analysis in glacier lake outburst floods (GLOF). Case studies : Quillcay sub basin in the Cordillera Blanca in Peru and Dudh Koshi sub basin in the Everest region in Nepal
(2014-08) Somos-Valenzuela, Marcelo A.; McKinney, Daene C.
Glacial-dominated areas pose unique challenges to downstream communities in adapting to recent and continuing global climate change, including increased threats of glacial lake outburst floods (GLOFs) that have substantial impacts on regional social, environmental and economic systems increasing risk due to flooding of downstream communities. In this dissertation, two lakes with potential to generate GLOFs were studied, Imja Lake in Nepal and Palcacocha Lake in Peru. At Imja Lake, basic data was generated that allowed the creation of a conceptual model of the lake. Ground penetrating radar and bathymetric surveys were performed. Also, an inundation model was developed in order to evaluate the effectiveness of a project that seeks to reduce flooding risk by lowering the lake at least 3 meters. In Peru, a GLOF inundation model was created. Also, the vulnerability of the people living downstream in the City of Huaraz was calculated, and the impacts of an early warning system were evaluated. The results at Imja indicated that the lake deepened from 98 m in 2002 to 116 m in 2012. Likewise, the lake volume increased from 35.8 to 61.6±1.8 million m3 over the past decade. The GPR survey at Imja and Lhotse-Shar glaciers shows that the glacier is over 200 m thick in the center of the glacier. The modeling work at Imja shows that the proposed project will not have major impacts downstream since the area inundated does not reduce considerably unless the lake is lowered by about 20 m. In Huaraz, the results indicate that approximately 40646 people live in the potentially inundated area. Using the flow simulation and the Peru Census 2007, a map of vulnerability was generated indicating that the most vulnerable areas are near the river. Finally, the potential number of fatalities in a worst case GLOF scenario from Lake Palcacocha was calculated to be 19773 with a standard deviation of 1191 if there is no early warning system and 7344 with a standard deviation of 1446 people if an early warning system is installed. Finally, if evacuation measures are improved the number reduces to 2865 with a standard deviation of 462.