Causative classification of river flood events

A wide variety of processes controls the time of occurrence, duration, extent, and severity of river floods. Classifying flood events by their causative processes may assist in enhancing the accuracy of local and regional flood frequency estimates and support the detection and interpretation of any changes in flood occurrence and magnitudes. This paper provides a critical review of existing causative classifications of instrumental and preinstrumental series of flood events, discusses their validity and applications, and identifies opportunities for moving toward more comprehensive approaches. So far no unified definition of causative mechanisms of flood events exists. Existing frameworks for classification of instrumental and preinstrumental series of flood events adopt different perspectives: hydroclimatic (large‐scale circulation patterns and atmospheric state at the time of the event), hydrological (catchment scale precipitation patterns and antecedent catchment state), and hydrograph‐based (indirectly considering generating mechanisms through their effects on hydrograph characteristics). All of these approaches intend to capture the flood generating mechanisms and are useful for characterizing the flood processes at various spatial and temporal scales. However, uncertainty analyses with respect to indicators, classification methods, and data to assess the robustness of the classification are rarely performed which limits the transferability across different geographic regions. It is argued that more rigorous testing is needed. There are opportunities for extending classification methods to include indicators of space–time dynamics of rainfall, antecedent wetness, and routing effects, which will make the classification schemes even more useful for understanding and estimating floods

Tropical cyclone disaster management using remote sensing and spatial analysis: a review

Tropical cyclones and their often devastating impacts are common in many coastal areas across the world. Many techniques and dataset have been designed to gather information helping to manage natural disasters using satellite remote sensing and spatial analysis. With a multitude of techniques and potential data types, it is very challenging to select the most appropriate processing techniques and datasets for managing cyclone disasters. This review provides guidance to select the most appropriate datasets and processing techniques for tropical cyclone disaster management. It reviews commonly used remote sensing and spatial analysis approaches and their applications for impacts assessment and recovery, risk assessment and risk modelling. The study recommends the post-classification change detection approach through object-based image analysis using optical imagery up to 30. m resolution for cyclone impact assessment and recovery. Spatial multi-criteria decision making approach using analytical hierarchy process (AHP) is suggested for cyclone risk assessment. However, it is difficult to recommend how many risk assessment criteria should be processed as it depends on study context. The study suggests the geographic information system (GIS) based storm surge model to use as a basic input in the cyclone risk modelling process due to its simplicity. Digital elevation model (DEM) accuracy is a vital factor for risk assessment and modelling. The study recommends DEM spatial resolution up to 30. m, but higher spatial resolution DEMs always performs better. This review also evaluates the challenges and future efforts of the approaches and datasets

Basic Study on Flood Management Assessment in Metro Manila, Philippines

Flooding is the most frequent and damaging natural hazard worldwide. The resulting impact of flood disasters on society depends on the economic strength of the affected country prior to the disaster. The larger the disaster and the smaller the economy, the more significant is the impact. This is very clearly seen in developing countries, like the Philippines, where weak economies become much weaker after a devastating flood event. In 2009, tropical storm Ondoy, brought heavy rainfalls that produced destructive floods in the northern islands of the Philippines, leaving inconceivable damages, especially in Metro Manila, which caused the Philippine government to re-evaluate its decades\u27 worth of flood management strategies. Deliberate strategies for flood damage reduction, as well as environmental protection, may aid a country (or a community) to efficiently manage scarce resources for flood mitigation. Nevertheless, many governments lack an adequate institutionalized system for applying cost effective and reliable technologies for disaster prevention, early warnings, and mitigation, mainly due to lack of systematic and reliable flood management assessment strategies. In Metro Manila, important decision elements, such as stakeholders\u27 perception and environmental protection are often overlooked in the development of sustainable flood mitigation plans. Stakeholders can significantly contribute in achieving the desired level of prevention and protection in flood disaster-prone regions. Knowledge of the local conditions and understanding of the public\u27s perception can significantly help address the prioritization issues involved in flood management planning. However, the integration of the stakeholders\u27 perception in the appraisal of flood management systems has not yet been clearly established. In the case of environmental protection, environmental impact assessment (EIA) can provide a certain level of awareness on the benefits of environmentally sound and sustainable urban development. However, the common practice of EIA in the Philippines is generally qualitative and lacks clear methodology in evaluating multi-criteria systems. A study that deals with flood management assessment in Metro Manila is thus necessary to find solutions that may help cope with these inadequacies. This study focuses on the following main objectives: 1) to develop a heuristic analytical strategy that helps identify priority concerns in the flood management systems of Metro Manila using a perception-based appraisal, and 2) to develop a systematic and rational evaluation scheme that would help incorporate environmental assessment in the appraisal of flood mitigation measures. To achieve the first objective, an analytical assessment approach was developed to identify and analyze the flood management gaps using the questionnaire-based stakeholders\u27 perception obtained during the aftermath of the tropical storm Ondoy. For the second objective, a quantitative analytical approach was developed for EIA to further enhance the evaluation process in the planning of flood mitigation projects. This dissertation is composed of six chapters: Chapter 1 is the introduction, which contains the background, motivation, and objectives of this study. A comprehensive review of literature and a description of the scopes and methods were presented in this chapter. Chapter 2 focuses on the performance of the flood management systems in Metro Manila. A brief description of the flood management systems used in Metro Manila, before and during the aftermath of tropical storm Ondoy, was provided. The nature and characteristics of the tropical storm, as well as its effects on the flood management systems, were presented in this chapter. A multi-criteria gap analysis technique was developed to examine the flood disaster risk reduction (FDRR) management systems, which is demonstrated using a questionnaire-based database to obtain an explicit representation of the systems\u27 strengths and weaknesses. In this study, 14 out of 17 municipalities in Metro Manila were investigated. Results revealed that small to medium scale flood management gaps exist within the 14 assessed municipalities. Chapter 3 further explores the potential of a multi-criteria gaps assessment technique in the evaluation of FDRR management systems in Metro Manila. Perception-based assessment is inherently vague and imprecise, which often operates in a fuzzy environment. To cope with this, a fuzzy-based analytical approach was proposed to handle the uncertainties in the evaluation process of flood management gaps. The new approach is demonstrated using the same database in Chapter 2. The results reveal that the municipal-based FDRR management systems in Metro Manila are insufficient in terms of flood disaster prevention, preparedness, response and recovery. Larger gaps were found in the emergency response mechanism of the disaster preparedness management system. Chapter 4 deals with the EIA of nine planned structural flood mitigation measures (SFMMs) in Metro Manila. A modified rapid impact assessment matrix (RIAM) technique was proposed to systematically and quantitatively evaluate the socioeconomic and environmental impacts of the planned SFMMs. The distribution of impacts of each SFMM was estimated for each environmental component of the 4 environmental categories. Based on the results, most of the negative and positive impacts of SFMMs occur during their construction and operation phases, respectively. The modified RIAM approach provided a clear panoramic view of the environmental impacts of each assessed SFMM. Chapter 5 presents a new EIA approach that provides enhancement to the modified RIAM technique in Chapter 4. A utility-based assessment approach using the RIAM technique, coupled with a recursive evidential reasoning approach, was proposed to rationally and systematically evaluate the ecological and socio-economic impacts of 4 planned SFMMs in Metro Manila. This new approach quantitatively characterized the overall impact of each of the planned SFMMs which can provide the means for benefit maximization and optimization. Results show that the overall environmental contributions of each of the planned SFMMs is generally positive, which indicate that the utility of their positive impacts would generally outweigh their negative ones. The results also indicated that the planned river channel improvements have higher environmental benefits than the planned open channels. Chapter 6 presents the overall conclusions and recommendations for the assessment of flood management systems in Metro Manila, including the future research works.首都大学東京, 2014-09-30, 博士(工学), 甲第421号首都大学東

Infrastructure systems modeling using data visualization and trend extraction

“Current infrastructure systems modeling literature lacks frameworks that integrate data visualization and trend extraction needed for complex systems decision making and planning. Critical infrastructures such as transportation and energy systems contain interdependencies that cannot be properly characterized without considering data visualization and trend extraction. This dissertation presents two case analyses to showcase the effectiveness and improvements that can be made using these techniques. Case one examines flood management and mitigation of disruption impacts using geospatial characteristics as part of data visualization. Case two incorporates trend analysis and sustainability assessment into energy portfolio transitions. Four distinct contributions are made in this work and divided equally across the two cases. The first contribution identifies trends and flood characteristics that must be included as part of model development. The second contribution uses trend extraction to create a traffic management data visualization system based on the flood influencing factors identified. The third contribution creates a data visualization framework for energy portfolio analysis using a genetic algorithm and fuzzy logic. The fourth contribution develops a sustainability assessment model using trend extraction and time series forecasting of state-level electricity generation in a proposed transition setting. The data visualization and trend extraction tools developed and validated in this research will improve strategic infrastructure planning effectiveness”--Abstract, page iv

Failure detection and separation in SOM based decision support

Failure management in process industry has difficult tasks. Decision support in control rooms of nuclear power plants is needed. A prototype that uses Self-Organizing Map (SOM) method is under development in an industrial project. This paper has focus on failure detection and separation. A literature survey outlines the state-of-the-art and reflects our study to related works. Different SOM visualizations are used. Failure management scenarios are carried out to experiment the methodology and the Man-Machine Interface (MMI). U-matrix trajectory analysis and quantization error are discussed more in detail. The experiments show the usefulness of the chosen approach. Next step will be to add more practical views by analyzing real and simulated industrial data with the control room tool and by feedback from the end users

Earthquake risk assessment using an integrated Fuzzy Analytic Hierarchy Process with Artificial Neural Networks based on GIS: A case study of Sanandaj in Iran

Earthquakes are natural phenomena, which induce natural hazard that seriously threatens urban areas, despite significant advances in retrofitting urban buildings and enhancing the knowledge and ability of experts in natural disaster control. Iran is one of the most seismically active countries in the world. The purpose of this study was to evaluate and analyze the extent of earthquake vulnerability in relation to demographic, environmental, and physical criteria. An earthquake risk assessment (ERA) map was created by using a Fuzzy-Analytic Hierarchy Process coupled with an Artificial Neural Networks (FAHP-ANN) model generating five vulnerability classes. Combining the application of a FAHP-ANN with a geographic information system (GIS) enabled to assign weights to the layers of the earthquake vulnerability criteria. The model was applied to Sanandaj City in Iran, located in the seismically active Sanandaj-Sirjan zone which is frequently affected by devastating earthquakes. The Multilayer Perceptron (MLP) model was implemented in the IDRISI software and 250 points were validated for grades 0 and 1. The validation process revealed that the proposed model can produce an earthquake probability map with an accuracy of 95%. A comparison of the results attained by using a FAHP, AHP and MLP model shows that the hybrid FAHP-ANN model proved flexible and reliable when generating the ERA map. The FAHP-ANN model accurately identified the highest earthquake vulnerability in densely populated areas with dilapidated building infrastructure. The findings of this study are useful for decision makers with a scientific basis to develop earthquake risk management strategies

Application of geographic Information system and remote sensing in multiple criteria analysis to identify priority areas for biodiversity conservation in Vietnam

There has been an increasing need for methods to define priority areas for biodiversity conservation since the effectiveness of biodiversity conservation in protected areas planning depends on available resources (human resources and funds) for the conservation. The identification of priority areas requires the integration of biodiversity data together with social data on human pressures and responses. However, the deficit of comprehensive data and reliable methods are key challenges in zoning where the demand for conservation is most urgent and where the outcomes of conservation strategies can be maximized. In order to fill this gap, the environmental model Pressure–State–Response (PSR) was applied to suggest a set of criteria to identify priority areas for biodiversity conservation. The empirical data have been compiled from 185 respondents, categorizing into three main groups: Governmental Administration, Research Institutions, and Protected Areas in Vietnam, by using a well-designed questionnaire. Then, the Analytic Hierarchy Process (AHP) theory was used to identify the weight of all criteria. These results show that three main factors could identify the priority level for biodiversity conservation: Pressure, State, and Response, with weights of 41%, 26%, and 33%, respectively. Based on the three factors, seven criteria and 17 sub-criteria were developed to determine priority areas for biodiversity conservation. In addition, this study also indicates that the groups of Governmental Administration and Protected Areas put a focus on the “Pressure” factor while the group of Research Institutions emphasized the importance of the “Response” factor in the evaluation process. Then these suggested criteria were applied by integrating with Geographic Information System (GIS) and Remote Sensing (RS) to define priority areas for biodiversity conservation in a particular conservation area (Pu Luong-Cuc Phuong area) in Vietnam. The results also reveal the proportion of very high and high priority areas, accounting for 84.9%, 96%, and 65.9% for Cuc Phuong National Park, Pu Luong Nature Reserve, and Ngoc Son Ngo Luong Nature Reserve, respectively. Based on these results, recommendations were provided to apply the developed criteria for identifying priority areas for biodiversity conservation in Vietnam.:Acknowledgement I Abstract III Table of contents IV List of figures VI List of tables X Acronyms and Abbreviations XII Chapter 1. Introduction 1 1.1. Problem statement and motivation 1 1.2. Research objectives and questions 2 1.3. Study contribution 3 1.4. Thesis structure 6 Chapter 2. Literature review 8 2.1. Background information on Vietnam 8 2.2. Environmental Pressure-State-Response model 11 2.3. Defining criteria for biodiversity conservation 13 2.4. Application of GIS and RS for biodiversity conservation 16 Chapter 3. Research methodology 19 3.1. Study areas 19 3.2. Data collection 23 3.3. Analytic Hierarchy Process 25 3.4. Remote Sensing 27 3.5. Geography Information System 35 3.6. Climate change scenarios 40 Chapter 4. Establishment of criteria 42 4.1. Summary of responses 44 4.2. Statistic of pairwise comparison 46 4.3. Weights of criteria based on all respondents 48 4.4. Weights of criteria based on groups 60 Chapter 5. Application of Criteria 64 5.1. Mapping criteria 64 5.2. Synthesis of multiple criteria 144 Chapter 6. Conclusions and recommendations 158 6.1. Establishment of criteria 158 6.2. Application of criteria 161 6.3. Recommendations 165 References 167 Appendix I. Questionnaire 197 Appendix II. Establishment of criteria 207 Appendix III. Application of criteria 23

An AHP-derived method for mapping the physical vulnerability of coastal areas at regional scales

International audienceAssessing coastal vulnerability to climate change at regional scales is now mandatory in France since the adoption of recent laws to support adaptation to climate change. However, there is presently no commonly recognised method to assess accurately how sea level rise will modify coastal processes in the coming decades. Therefore, many assessments of the physical component of coastal vulnerability are presently based on a combined use of data (e.g. digital elevation models, historical shoreline and coastal geomorphology datasets), simple models and expert opinion. In this study, we assess the applicability and usefulness of a multi-criteria decision-mapping method (the analytical hierarchy process, AHP) to map physical coastal vulnerability to erosion and flooding in a structured way. We apply the method in two regions of France: the coastal zones of Languedoc-Roussillon (north-western Mediterranean, France) and the island of La Réunion (south-western Indian Ocean), notably using the regional geological maps. As expected, the results show not only the greater vulnerability of sand spits, estuaries and low-lying areas near to coastal lagoons in both regions, but also that of a thin strip of erodible cliffs exposed to waves in La Réunion. Despite gaps in knowledge and data, the method is found to provide a flexible and transportable framework to represent and aggregate existing knowledge and to support long-term coastal zone planning through the integration of such studies into existing adaptation schemes

Failure detection and separation in SOM based decision support

Failure management in process industry has difficult tasks. Decision support in control rooms of nuclear power plants is needed. A prototype that uses Self-Organizing Map (SOM) method is under development in an industrial project. This paper has focus on failure detection and separation. A literature survey outlines the state-of-the-art and reflects our study to related works. Different SOM visualizations are used. Failure management scenarios are carried out to experiment the methodology and the Man-Machine Interface (MMI). U-matrix trajectory analysis and quantization error are discussed more in detail. The experiments show the usefulness of the chosen approach. Next step will be to add more practical views by analyzing real and simulated industrial data with the control room tool and by feedback from the end users