Multi-criteria decision making under uncertainty for flood mitigation

Designs of flood mitigation infrastructural systems are decision-making which are often made under various uncertainties involving multiple criteria. Under the condition of uncertainties, any chosen design alternative has the likelihood to perform inferior to other unselected designs in terms of the adopted performance indicators. This paper introduces a quantitative risk measure based on the concept of expected opportunity loss (EOL) for evaluating the consequence of making the wrong decision. The EOL can be used to assess the relative performance of multiple decision alternatives and is extended to deal with decision problems involving multiple criteria. In particular, the probabilistic features of the consequences associated with a design alternative is considered and used in the Preference Ranking Organization Method of Enrichment Evaluation (PROMETHEE) MCDM technique. The integration of PROMETHEE and decision making under uncertainty is demonstrated through an example of flood damage mitigation planning.     

Stochastic-fuzzy multi criteria decision making for robust water resources management

All realistic Multi Criteria Decision Making (MCDM) problems in water resources management face various kinds of uncertainty. In this study the evaluations of the alternatives with respect to the criteria will be assumed to be stochastic. Fuzzy linguistic quantifiers will be used to obtain the uncertain optimism degree of the Decision Maker (DM). A new approach for stochastic-fuzzy modeling of MCDM problems will be then introduced by merging the stochastic and fuzzy approaches into the Ordered Weighted Averaging (OWA) operator. The results of the new approach, entitled SFOWA, give the expected value and the variance of the combined goodness measure for each alternative, which are essential for robust decision making. In order to combine these two characteristics, a composite goodness measure will be defined. By using this measure the model will give more sensitive decisions to the stakeholders whose optimism degrees are different than that of the decision maker. The methodology will be illustrated by using a water resources management problem in the Central Tisza River in Hungary. Finally, SFOWA will be compared to other methods known from the literature to show its suitability for MCDM problems under uncertainty.     

Multi-criteria decision making for seismic intensity measure selection considering uncertainty

Seismic intensity measure (IM) selection is associated with consideration of multiple criteria, and there are uncertainties within the selection process. In this paper, a novel multi-criteria decision making (MCDM) approach by incorporating stochastic multi-criteria acceptability analysis (SMAA) with technique for order preference by similarity to ideal solution (TOPSIS) is proposed to solve the stochastic decision making problem of IM selection. TOPSIS provides an alternative rank function, and the SMAA is used to address the uncertainties within the IM selection. The performance criteria (e.g., efficiency, proficiency, practicality, sufficiency, and correlation) are evaluated for the investigated structural components, and the decision matrix is formulated based on the criteria of each IM alternative. Furthermore, the importance of the component to system reliability is quantified in a probabilistic manner using nonlinear time history analysis and serves as the weighting factors in MCDM stage. The holistic acceptability indices indicating the overall acceptability levels of IM alternatives are computed by the proposed approach. Additionally, the effects of different IMs (e.g., average spectral acceleration, peak ground velocity, and spectral acceleration) on probabilistic seismic loss and resilience are investigated to further support the IM selection. The proposed approach is illustrated on a highway bridge, and the results are presented.     

道路网络抗震功能失效空间决策支持方法研究

地震作用后桥梁的破坏是导致道路网络功能失效的主要原因。在进行道路网络抗震功能失效分析这一决策过程中,不仅要应用空间分析模型对空间数据进行分析,而且也要对属性数据进行有效的决策分析,因此本文结合了G IS(地理信息系统)与DSS(决策支持系统),形成了以模型库为驱动核心的道路网络抗震功能失效分析空间决策支持,本文着重对数据库及模型库的构建进行了深入研究。     

Incorporating probabilistic approach into local multi-criteria decision analysis for flood susceptibility assessment

Flood risk management can be enhanced by integrating geographic information system (GIS) with multi-criteria decision analysis (MCDA). However, the conventional, deterministic MCDA methods ignore uncertainty in the decision-making process and fail to account for local variability in criteria values and preferences. Therefore, a spatially explicit MCDA model which effectively incorporates spatial heterogeneity is required. In this paper, a probabilistic or stochastic MCDA method which incorporates the uncertainty into a local weighted linear combination (WLC) was utilized to evaluate flood susceptibility; and an application case in Gucheng County, Central China, was developed. A GIS database of geomorphological and hydro-meteorological criteria contributing to flood susceptibility analysis was constructed using six conditioning factors: digital elevation model (DEM), slope (SL), maximum three-day precipitation (M3DP), topographic wetness index (TWI), distance from the river (DR), and Soil Conservation Service Curve Number (SCS-CN). The results of local WLC were compared with those of the global WLC. It shows that the local WLC model can provide much more valuable information about the spatial patterns of criterion values, ranges, weights, trade-offs and overall scores, whereas the global WLC can only depict the spatial distribution of criterion values and overall scores. The local WLC can also help to prioritize the most susceptible locations within a neighborhood when navigating the disaster assistance process. Moreover, the uncertainty analysis of criteria weights increases the degree of confidence in the model output. It is concluded that the presented approach can provide more insights and understanding of the nature of the flood susceptibility than global WLC.     

Risk-based environmental decision-making using fuzzy analytic hierarchy process (F-AHP)

Environmental risk management is an integral part of risk analyses. The selection of different mitigating or preventive alternatives often involve competing and conflicting criteria, which requires sophisticated multi-criteria decision-making (MCDM) methods. Analytic hierarchy process (AHP) is one of the most commonly used MCDM methods, which integrates subjective and personal preferences in performing analyses. AHP works on a premise that decision-making of complex problems can be handled by structuring the complex problem into a simple and comprehensible hierarchical structure. However, AHP involves human subjectivity, which introduces vagueness type uncertainty and necessitates the use of decision-making under uncertainty. In this paper, vagueness type uncertainty is considered using fuzzy-based techniques. The traditional AHP is modified to fuzzy AHP using fuzzy arithmetic operations. The concept of risk attitude and associated confidence of a decision maker on the estimates of pairwise comparisons are also discussed. The methodology of the proposed technique is built on a hypothetical example and its efficacy is demonstrated through an application dealing with the selection of drilling fluid/mud for offshore oil and gas operations.     

A maritime decision support system to assess risk in the presence of environmental uncertainties: the REP10 experiment

The aim of this work is to report on an activity carried out during the 2010 Recognized Environmental Picture experiment, held in the Ligurian Sea during summer 2010. The activity was the first at-sea test of the recently developed decision support system (DSS) for operation planning, which had previously been tested in an artificial experiment. The DSS assesses the impact of both environmental conditions (meteorological and oceanographic) and non-environmental conditions (such as traffic density maps) on people and assets involved in the operation and helps in deciding a course of action that allows safer operation. More precisely, the environmental variables (such as wind speed, current speed and significant wave height) taken as input by the DSS are the ones forecasted by a super-ensemble model, which fuses the forecasts provided by multiple forecasting centres. The uncertainties associated with the DSS’s inputs (generally due to disagreement between forecasts) are propagated through the DSS’s output by using the unscented transform. In this way, the system is not only able to provide a traffic light map (run/not run the operation), but also to specify the confidence level associated with each action. This feature was tested on a particular type of operation with underwater gliders: the glider surfacing for data transmission. It is also shown how the availability of a glider path prediction tool provides surfacing options along the predicted path. The applicability to different operations is demonstrated by applying the same system to support diver operations.     

The contribution of spaceborne SAR and optical data in monitoring flood events: examples in northern and southern France

This paper demonstrates the utility of satellite remote sensing data in water management, and particularly, for flood monitoring and impact analysis. Satellite-derived data can provide timely geographical data from which water body extent in normal and flood regimes can be ascertained. Combined with exogenous and historical data, within a GIS, these can provide information useful for flood prevention decision making. The recent French Alsation, Camargue and Vaison la Romaine floods are taken to illustrate the utility of satellite remote sensing. © 1997 John Wiley & Sons, Ltd.     

Contaminant remediation decision analysis using information gap theory

Decision making under severe lack of information is a ubiquitous situation in nearly every applied field of engineering, policy, and science. A severe lack of information precludes our ability to determine a frequency of occurrence of events or conditions that impact the decision; therefore, decision uncertainties due to a severe lack of information cannot be characterized probabilistically. To circumvent this problem, information gap (info-gap) theory has been developed to explicitly recognize and quantify the implications of a severe lack of information in decision making. This paper presents a decision analysis based on info-gap theory developed for a contaminant remediation scenario. The analysis provides decision support in determining the fraction of contaminant mass to remove from the environment. An info-gap uncertainty model is developed to characterize uncertainty due to a lack of information concerning the contaminant flux. The info-gap uncertainty model groups nested, convex sets of functions defining contaminant flux over time based on their level of deviation from a nominal contaminant flux. The nominal contaminant flux defines a best estimate of contaminant flux over time based on existing, though incomplete, information. A robustness function is derived to quantify the maximum level of deviation from nominal that still ensures compliance for alternative decisions. An opportuneness function is derived to characterize the possibility of meeting a desired contaminant concentration level. The decision analysis evaluates how the robustness and opportuneness change as a function of time since remediation and as a function of the fraction of contaminant mass removed.     

地震应急对策决策支持软件的设计与开发

基于空间决策支持技术,设计与开发了地震应急对策软件,在软件的总体设计、功能模块、数据库建设、地震应急对策模型及接口设计与模块集成等方面进行了研究与开发,并在“青岛市地震应急指挥决策支持软件系统”中得到实际应用和检验。实践证明,该软件能够实现城市地震灾害信息的科学管理,智能制定各种地震应急对策和生动的可视化,从而有效提高地震应急的效率和响应速度,为城市地震应急工作提供了有效的辅助决策手段;建成的“青岛市地震应急对策系统”对全国大中城市地震应急指挥技术系统的建设具有示范意义。     

A network of knowledge on applying an indicator‐based methodology for minimizing flood vulnerability

Flood vulnerability assessment plays a key role in the area of risk management. Therefore, techniques that make this assessment more straightforward and at the same time improve the results are important. In this briefing, we present an automated calculation of a flood vulnerability index implemented through a web management interface (PHP) that enhances the ability of decision makers to strategically guide investment. To test the applicability of this methodology using this website, many case studies are required in order to cover the full range of cases in terms of scale such as river basin, subcatchment and urban area. This requires prompt solutions with large amounts of data and this has led to the development of this automated tool to help organize, monitor, process and compare the data of different case studies. The authors aim to create a network of knowledge between different institutions and universities in which this methodology is used. It is also hoped to encourage collaboration between the members of the network on managing flood vulnerability information and also promoting further studies on flood risk assessment at all scales. Copyright © 2009 John Wiley & Sons, Ltd.     

An inexact fuzzy-chance-constrained two-stage mixed-integer linear programming approach for flood diversion planning under multiple uncertainties

In this study, an inexact fuzzy-chance-constrained two-stage mixed-integer linear programming (IFCTIP) approach is developed for flood diversion planning under multiple uncertainties. A concept of the distribution with fuzzy boundary interval probability is defined to address multiple uncertainties expressed as integration of intervals, fuzzy sets and probability distributions. IFCTIP integrates the inexact programming, two-stage stochastic programming, integer programming and fuzzy-stochastic programming within a general optimization framework. IFCTIP incorporates the pre-regulated water-diversion policies directly into its optimization process to analyze various policy scenarios; each scenario has different economic penalty when the promised targets are violated. More importantly, it can facilitate dynamic programming for decisions of capacity-expansion planning under fuzzy-stochastic conditions. IFCTIP is applied to a flood management system. Solutions from IFCTIP provide desired flood diversion plans with a minimized system cost and a maximized safety level. The results indicate that reasonable solutions are generated for objective function values and decision variables, thus a number of decision alternatives can be generated under different levels of flood flows.     

河网水质管理决策支持系统在引江济太中的应用

利用太湖流域河网水质管理决策支持系统（TAIHU DSS）,对2000年夏季望虞河应急调水进行了技术方案比较,论证,重点对望虞河引江应急调水过程中,常熟枢纽泵站运用,望虞河东岸分流与否及望虞河立交开闸前对底水的处理等不同条件下的望虞河入湖水量,水质等进行多方案比较,为望虞河启用泵站调水、东岸适当分流,先打开蠡河船闸处理望虞河底水的方案提供了决策的技术依据,并引发了对太湖流域引江济太工作的进一步深入研究和实践,是决策支持系统在实际工作中的成功应用之一。     

Capturing flood-risk dynamics with a coupled agent-based and hydraulic modelling framework

ABSTRACT

Two-way interactions and feedback between hydrological and social processes in settled floodplains determine the complex human–flood system and change vulnerability over time. To focus on the dynamic role of individual and governmental decision making on flood-risk management, we developed and implemented a coupled agent-based and hydraulic modelling framework. Within this framework, household agents are located in a floodplain protected by a levee system. Individual behaviour is based on Protection Motivation Theory and includes the options to (1) not react to flood risk; (2) implement individual flood protection measures; or (3) file a complaint to the government. The government decides about reinforcing the levee system, compromising between a cost-benefit analysis and filed complaints from households. We found that individual decision making can significantly influence flood risk. In addition, the coupled agent-based and hydraulic modelling framework approach captures commonly observed socio-hydrological dynamics, namely levee and adaptation effects. It provides an explanatory tool for assessing spatial and temporal dynamics of flood risk in a socio-hydrological system.     

Information system for emergence decision on the protection against earthquake and disaster reduction in Shanghai City

IntroductionGeographic information System (GIS) is the technique Which has been developed and moremature in recent last 10 years. It is being eXtensively used tO build applied information system ormanagement system by corresponding departmentS, which brings remarkable benefit for societyand economy in scientific research and production. GIS may collect analyZe, manage and outputspace data expediently. And it has functions of regional analysis, analysis of various factors anddynamic predic…     

A dual two-stage stochastic model for flood management with inexact-integer analysis under multiple uncertainties

This study introduces a hybrid optimization approach for flood management under multiple uncertainties. An inexact two-stage integer programming (ITIP) model and its dual formation are developed by integrating the concepts of mixed-integer and interval-parameter programming techniques into a general framework of two-stage stochastic programming. The proposed approach provides a linkage to pre-defined management policies, deals with capacity-expansion planning issues, and reflects various uncertainties expressed as probability distributions and discrete intervals for a flood management system. Penalties are imposed when the policies are violated. The marginal costs are determined based on dual formulation of the ITIP model, and their effects on the optimal solutions are investigated. The developed model is applied to a case study of flood management. The solutions of binary variables represent the decisions of flood-diversion–capacity expansion within a multi-region, multi-flow-level, and multi-option context. The solutions of continuous variables are related to decisions of flood diversion toward different regions. The solutions of dual variables indicate the decisions of marginal costs associated with the resources of regions’ capacity, water availability, and allowable diversions. The results show that the proposed approach could obtain reliable solutions and adequately support decision making in flood management.     

Multi-objective optimal design for flood risk management with resilience objectives

In flood risk management, the divergent concept of resilience of a flood defense system cannot be fully defined quantitatively by one indicator and multiple indicators need to be considered simultaneously. In this paper, a multi-objective optimization (MOO) design framework is developed to determine the optimal protection level of a levee system based on different resilience indicators that depend on the probabilistic features of the flood damage cost arising under the uncertain nature of rainfalls. An evolutionary-based MOO algorithm is used to find a set of non-dominated solutions, known as Pareto optimal solutions for the optimal protection level. The objective functions, specifically resilience indicators of severity, variability and graduality, that account for the uncertainty of rainfall can be evaluated by stochastic sampling of rainfall amount together with the model simulations of incurred flood damage estimation for the levee system. However, these model simulations which usually require detailed flood inundation simulation are computationally demanding. This hinders the wide application of MOO in flood risk management and is circumvented here via a surrogate flood damage modeling technique that is integrated into the MOO algorithm. The proposed optimal design framework is applied to a levee system in a central basin of flood-prone Jakarta, Indonesia. The results suggest that the proposed framework enables the application of MOO with resilience objectives for flood defense system design under uncertainty and solves the decision making problems efficiently by drastically reducing the required computational time.     

空间决策支持技术在城市地震应急指挥软件系统中的应用

将空间决策支持技术SDSS引入城市地震应急指挥技术领域,利用决策支持技术DSS的多模型组合建模方法和地理信息系统的空间分析技术,建构了城市地震应急指挥空间辅助决策支持软件系统。详细讨论了该系统的整体规划与功能实现,并对系统数据库、模型库、方法库和知识库及其管理子系统的设计与开发作了详细阐述,以期为城市灾害与突发事件的防御与应急提供技术支持。     

Mapping groundwater recharge potential zones in arid region using GIS and Landsat approaches,southeast Tunisia

The rapid growth of population and agricultural and industrial activities has caused an increase in demand on the Jeffara aquifers of Gabes (southeast Tunisia). In fact, the over-pumping of this aquifer system has resulted in water-level declines ranging from 0.25 to 1 m/year during the past three decades. The aim of this study is to identify favourable artificial recharge sites of this aquifer system based on the combined use of remotely sensed data, a geographic information system (GIS), the Shuttle Radar Topography Mission (SRTM) product and a multiple criteria decision making (MCDM) technique. The delineation of artificial recharge zones shows high to moderate potential for groundwater recharge (40%) in the Gabes region, with high precision of good potential proposed sites. Recharge processes need to account for natural conditions and ecosystems.     

Improving at-site flood frequency analysis with additional spatial information: a probabilistic regional envelope curve approach

Extreme flood events have detrimental effects on society, the economy and the environment. Widespread flooding across South East Queensland in 2011 and 2013 resulted in the loss of lives and significant cost to the economy. In this region, flood risk planning and the use of traditional flood frequency analysis (FFA) to estimate both the magnitude and frequency of the 1-in-100 year flood is severely limited by short gauging station records. On average, these records are 42 years in Eastern Australia and many have a poor representation of extreme flood events. The major aim of this study is to test the application of an alternative method to estimate flood frequency in the form of the Probabilistic Regional Envelope Curve (PREC) approach which integrates additional spatial information of extreme flood events. In order to better define and constrain a working definition of an extreme flood, an Australian Envelope Curve is also produced from available gauging station data. Results indicate that the PREC method shows significant changes to the larger recurrence intervals (≥100 years) in gauges with either too few, or too many, extreme flood events. A decision making process is provided to ascertain when this method is preferable for FFA.