scholarly journals Climate uncertainty in flood protection planning

2017 ◽  
Author(s):  
Beatrice Dittes ◽  
Olga Špačková ◽  
Lukas Schoppa ◽  
Daniel Straub
Keyword(s):  
Joint Probability ◽  
Life Time ◽  
Decision Makers ◽  
Flood Protection ◽  
Joint Probability Distribution ◽  
Damage Potential ◽  
Protection Measures ◽  
Practical Applications ◽  
Historic Record

Abstract. Technical flood protection is a necessary part of integrated strategies to protect riverine settlements from extreme floods. Many technical flood protection measures, such as dikes and protection walls, are costly to adapt after their initial construction. This poses a challenge to decision makers as there is large uncertainty in how the required protection level will change during the measure life time, which is typically many decades long. Flood protection requirements should account for multiple future uncertain factors: socio-economic, e.g. whether the population and with it the damage potential grows or falls; technological, e.g. possible advancements in flood protection; and climatic, e.g. whether extreme discharge will become more frequent or not. We focus here on the planning implications of the uncertainty in extreme discharge. We account for the sequential nature of the decision process, in which the adequacy of the protection is regularly revised in the future based on the discharges that have been observed by that point and that reduce uncertainty. For planning purposes, we categorize uncertainties as either visible, if they can be quantified from available catchment data, or hidden, if they cannot be quantified from catchment data and must be estimated, e.g. from literature. It is vital to consider the hidden uncertainty, since in practical applications only a limited amount of information (e.g. through projections, historic record) is available. We use a Bayesian approach to quantify the visible uncertainties and combine them with an estimate of the hidden uncertainties to learn a joint probability distribution of the parameters of extreme discharge. The methodology is integrated into an optimization framework and applied to a pre-alpine case study to give a quantitative, cost-optimal recommendation on the required amount of flood protection.

scholarly journals Managing uncertainty in flood protection planning with climate projections

2018 ◽  
Vol 22 (4) ◽  
pp. 2511-2526 ◽  
Author(s):  
Beatrice Dittes ◽  
Olga Špačková ◽  
Lukas Schoppa ◽  
Daniel Straub
Keyword(s):  
Joint Probability ◽  
Decision Makers ◽  
Flood Protection ◽  
Joint Probability Distribution ◽  
Climate Projections ◽  
Damage Potential ◽  
Protection Measures ◽  
Practical Applications ◽  
The Impact

Abstract. Technical flood protection is a necessary part of integrated strategies to protect riverine settlements from extreme floods. Many technical flood protection measures, such as dikes and protection walls, are costly to adapt after their initial construction. This poses a challenge to decision makers as there is large uncertainty in how the required protection level will change during the measure lifetime, which is typically many decades long. Flood protection requirements should account for multiple future uncertain factors: socioeconomic, e.g., whether the population and with it the damage potential grows or falls; technological, e.g., possible advancements in flood protection; and climatic, e.g., whether extreme discharge will become more frequent or not. This paper focuses on climatic uncertainty. Specifically, we devise methodology to account for uncertainty associated with the use of discharge projections, ultimately leading to planning implications. For planning purposes, we categorize uncertainties as either “visible”, if they can be quantified from available catchment data, or “hidden”, if they cannot be quantified from catchment data and must be estimated, e.g., from the literature. It is vital to consider the “hidden uncertainty”, since in practical applications only a limited amount of information (e.g., a finite projection ensemble) is available. We use a Bayesian approach to quantify the “visible uncertainties” and combine them with an estimate of the hidden uncertainties to learn a joint probability distribution of the parameters of extreme discharge. The methodology is integrated into an optimization framework and applied to a pre-alpine case study to give a quantitative, cost-optimal recommendation on the required amount of flood protection. The results show that hidden uncertainty ought to be considered in planning, but the larger the uncertainty already present, the smaller the impact of adding more. The recommended planning is robust to moderate changes in uncertainty as well as in trend. In contrast, planning without consideration of bias and dependencies in and between uncertainty components leads to strongly suboptimal planning recommendations.

scholarly journals Probability elicitation using geostatistics in hydrocarbon exploration

2021 ◽  
Author(s):  
André Luís Morosov ◽  
Reidar Brumer Bratvold
Keyword(s):  
Value Creation ◽  
Decision Process ◽  
Conceptual Models ◽  
Joint Probability ◽  
Decision Makers ◽  
Hydrocarbon Exploration ◽  
Joint Probability Distribution ◽  
Proof Of Concept ◽  
Geological Information ◽  
Decision Supporting

AbstractThe exploratory phase of a hydrocarbon field is a period when decision-supporting information is scarce while the drilling stakes are high. Each new prospect drilled brings more knowledge about the area and might reveal reserves, hence choosing such prospect is essential for value creation. Drilling decisions must be made under uncertainty as the available geological information is limited and probability elicitation from geoscience experts is key in this process. This work proposes a novel use of geostatistics to help experts elicit geological probabilities more objectively, especially useful during the exploratory phase. The approach is simpler, more consistent with geologic knowledge, more comfortable for geoscientists to use and, more comprehensive for decision-makers to follow when compared to traditional methods. It is also flexible by working with any amount and type of information available. The workflow takes as input conceptual models describing the geology and uses geostatistics to generate spatial variability of geological properties in the vicinity of potential drilling prospects. The output is stochastic realizations which are processed into a joint probability distribution (JPD) containing all conditional probabilities of the process. Input models are interactively changed until the JPD satisfactory represents the expert’s beliefs. A 2D, yet realistic, implementation of the workflow is used as a proof of concept, demonstrating that even simple modeling might suffice for decision-making support. Derivative versions of the JPD are created and their effect on the decision process of selecting the drilling sequence is assessed. The findings from the method application suggest ways to define the input parameters by observing how they affect the JPD and the decision process.

An integrated fuzzy SWARA and fuzzy AD approach for outsourcing provider selection

2019 ◽  
Vol 30 (2) ◽  
pp. 531-552 ◽  
Author(s):  
Selçuk Perçin
Keyword(s):  
Evaluation Criteria ◽  
Decision Makers ◽  
Ratio Analysis ◽  
Functional Requirements ◽  
Content Type ◽  
Practical Applications ◽  
Chemical Company ◽  
Order Preference ◽  
Practical Implications

Purpose Unlike previous literature, this study offers a novel integrated fuzzy approach to the field of outsourcing decisions. The purpose of this paper is to use design ranges of evaluation criteria that satisfy the functional requirements (FRs) of decision makers to solve the outsourcing provider selection problem. Design/methodology/approach In this study, considering the expected significance of outsourcing evaluation criteria, and the FRs of decision makers expressed in linguistic terms, a robust multi-criteria decision-making (MCDM) tool based on the integrated use of fuzzy Step-wise Weight Assessment Ratio Analysis and weighted fuzzy axiomatic design methods is proposed for use in decision process. Findings The proposed method is applied to a Turkish chemical company. A sensitivity analysis is performed and the outcomes of the proposed integrated framework are compared with those of other MCDM methods such as fuzzy-based Technique for Order Preference by Similarity to Ideal Solution, fuzzy Vise Kriterijumska Optimizacija I Kompromisno Resenje and fuzzy Multi-Objective Optimization on the basis of Ratio Analysis. This validates the usefulness and practicality of the proposed methodology. Practical implications The main contribution of this study is that it defines specific requirements that will assist company managers in eliminating alternatives that do not satisfy the needs and expectations of their company. Originality/value This paper compares the present study with other studies in the field of manufacturing. Additionally, it provides a well-documented case study, which makes the paper of value to researchers interested in the practical applications of MCDM methods.

scholarly journals A Perishable Inventory System with Postponed Demands and Multiple Server Vacations

2012 ◽  
Vol 2012 ◽  
pp. 1-17 ◽  
Author(s):  
R. Jayaraman ◽  
B. Sivakumar ◽  
G. Arivarignan
Keyword(s):  
Steady State ◽  
Joint Probability ◽  
Life Time ◽  
Inventory System ◽  
Inventory Level ◽  
Joint Probability Distribution ◽  
Single Server ◽  
Cost Rate ◽  
Stochastic Inventory ◽  
Number Of Customers

A mathematical modelling of a continuous review stochastic inventory system with a single server is carried out in this work. We assume that demand time points form a Poisson process. The life time of each item is assumed to have exponential distribution. We assume(s,S)ordering policy to replenish stock with random lead time. The server goes for a vacation of an exponentially distributed duration at the time of stock depletion and may take subsequent vacation depending on the stock position. The customer who arrives during the stock-out period or during the server vacation is offered a choice of joining a pool which is of finite capacity or leaving the system. The demands in the pool are selected one by one by the server only when the inventory level is aboves, with interval time between any two successive selections distributed as exponential with parameter depending on the number of customers in the pool. The joint probability distribution of the inventory level and the number of customers in the pool is obtained in the steady-state case. Various system performance measures in the steady state are derived, and the long-run total expected cost rate is calculated.

scholarly journals Theoretical and methodological reflection of a case study on the Deblínsko landscape project

Envigogika ◽  
2015 ◽  
Vol 10 (1) ◽  
Author(s):  
Alois Hynek ◽  
Břetislav Svozil ◽  
Jakub Trojan ◽  
Jan Trávníček
Keyword(s):  
Primary School ◽  
Regional Development ◽  
Tertiary Education ◽  
Field Work ◽  
Decision Makers ◽  
Civic Society ◽  
Practical Applications ◽  
Education Practice ◽  
Community Centre

Full text of the article is available both in English and Czech.The case study is based primarily on long-standing collaboration of two public sector institutions: the MU in Brno and the Deblín Primary School and Kindergarten, with cooperation of experts in numerous other institutions. The MU in Brno and the Deblín Primary School and Kindergarten focus on research, teaching and, above all, practical applications of sustainability/security. The objective of the study is to revise the theoretical and methodological frameworks influencing approaches to teaching sustainability in primary education and, through it, to open a discussion of civic society topics and formation starting at the level of children/pupils/students. The vehicle for achieving the objective is a thorough critical view of the “Deblínsko landscape project”. The authors’ experience concerns development of dialogue between the world of science and its applications and needs of those on whom its consequences impact. They are collected as part of activities aimed primarily at intensive field and project teaching, which reflects the sustainability discourse in the primary, secondary and tertiary education practice and is also connected with establishment of international collaboration. The focus of the field work is based on the understanding of each of the institutions as regional education centres (Deblín Primary School and Kindergarten = community centre), focused on solving issues of sustainability, involving owners, users, decision-makers, shareholders and stakeholders within public territorial administration, represented by means of goals and measures of regional development schemes along with micro-regional development programmes and local action group (LAG) activities.

The joint probability distribution function of structure factors with rational indices. V. The estimates

1999 ◽  
Vol 55 (3) ◽  
pp. 525-532
Author(s):  
Carmelo Giacovazzo ◽  
Dritan Siliqi ◽  
Cristina Fernández-Castaño ◽  
Giuliana Comunale
Keyword(s):  
Probability Distribution Function ◽  
Joint Probability ◽  
Experimental Tests ◽  
Joint Probability Distribution ◽  
Integral Index ◽  
Acta Cryst ◽  
Reliability Factor ◽  
Practical Applications ◽  
Structure Factors ◽  
Joint Probability Distribution Function

The probabilistic formulae [Giacovazzo, Siliqi & Fernández-Castaño (1999). Acta Cryst. A55, 512–524] relating standard and half-integral index reflections are modified for practical applications. The experimental tests prove the reliability of the probabilistic relationships. The approach is further developed to explore whether the moduli of the half-integral index reflections can be evaluated in the absence of phase information; i.e. by exploiting the moduli of the standard reflections only. The final formulae indicate that estimates can be obtained, even though the reliability factor is a constant.

scholarly journals SIMULATION OF SEA STORMS INCLUDING MULTIVARIATE STORM EVOLUTION

2018 ◽  
pp. 35
Author(s):  
Sebastián Solari ◽  
Miguel A. Losada
Keyword(s):  
Probability Distribution ◽  
Autoregressive Model ◽  
Joint Probability ◽  
New Method ◽  
Joint Probability Distribution ◽  
Northern Coast ◽  
Vector Autoregressive Model ◽  
Vector Autoregressive ◽  
Storm Evolution

A new method for the simulation of storms is proposed which takes into account the multivariate evolution of the storms, allowing to innovate in the form of each simulated storm, for all the variables involved. The method is based on two novel aspects: (a) measured storms are grouped using clusters techniques and a set of average evolution forms is defined for each cluster, one for each of the variables involved, and (b) a Vector Autoregressive model is fitted to the differences between the average evolution of each variable and the actual measured evolutions. The ability of the methodology to properly reproduce the joint probability distribution of all the variables involved is demonstrated for a case study at the mid Rio de la Plata northern coast.

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