Academic literature on the topic 'Multi risk assessment, uncertainty, natural and technological hazards'

The paucity of a comprehensive document on Cameroon’s hazard/disaster risk profile is a limitation to the country wide risk assessment and adequate disaster resilience. This article narrows this gap by retrospectively exploring Cameroon’s hazard/disaster profile. This has been achieved through an investigative approach that applies a set of qualitative methods to derive and articulate an inventory and analysis of hazards/disasters in Cameroon. The findings indicate that Cameroon has a wide array and high incidence/frequency of hazards that have had devastating consequences. The hazards have been structured along four profiles: a classification of all hazard types plaguing Cameroon into natural, potentially socio-natural, technological, and social and anthropogenic hazards; occurrence/origin of the hazards; their impacts/effects to the ‘at risk’ communities/populace and potential disaster management or mitigation measures. In-depth analysis indicate that natural hazards have the lowest frequency but the potential to cause the highest fatalities in a single incident; potentially socio-natural hazards affect the largest number of people and the widest geographical areas, technological hazards have the highest frequency of occurrence; while social/anthropogenic hazards are the newest in the country but have caused the highest population displacement. Arguably, the multi-hazard/disaster inventory presented in this article serves as a vital preliminary step to a more comprehensive profile of Cameroon’s disaster risk profile.

Abstract. This paper combines research and commentary to reinforce the importance of integrating hazard interactions and interaction networks (cascades) into multi-hazard methodologies. We present a synthesis of the differences between multi-layer single-hazard approaches and multi-hazard approaches that integrate such interactions. This synthesis suggests that ignoring interactions between important environmental and anthropogenic processes could distort management priorities, increase vulnerability to other spatially relevant hazards or underestimate disaster risk. In this paper we proceed to present an enhanced multi-hazard framework through the following steps: (i) description and definition of three groups (natural hazards, anthropogenic processes and technological hazards/disasters) as relevant components of a multi-hazard environment, (ii) outlining of three types of interaction relationship (triggering, increased probability, and catalysis/impedance), and (iii) assessment of the importance of networks of interactions (cascades) through case study examples (based on the literature, field observations and semi-structured interviews). We further propose two visualisation frameworks to represent these networks of interactions: hazard interaction matrices and hazard/process flow diagrams. Our approach reinforces the importance of integrating interactions between different aspects of the Earth system, together with human activity, into enhanced multi-hazard methodologies. Multi-hazard approaches support the holistic assessment of hazard potential and consequently disaster risk. We conclude by describing three ways by which understanding networks of interactions contributes to the theoretical and practical understanding of hazards, disaster risk reduction and Earth system management. Understanding interactions and interaction networks helps us to better (i) model the observed reality of disaster events, (ii) constrain potential changes in physical and social vulnerability between successive hazards, and (iii) prioritise resource allocation for mitigation and disaster risk reduction.

Natural hazards continue to be an increasing challenge to societies around the world, with many societies being impacted by multiple types of hazard events. To reduce the impact of these hazards, we must not only quantify the hazard and risk associated with multi-hazard events but also understand the uncertainty associated with these events. Resilience can only be improved by considering all these factors. Multi-hazard and risk-modeling approaches are receiving increasing attention globally; however, the challenges of assessing uncertainty in both single- and multi-hazard risks are considerable. Without a clear understanding of the risks and their uncertainties, measures to mitigate these risks and to increase resilience face difficult decisions. In the present Special Issue, we have five papers and one report on the Tokyo Metropolitan Resilience Project: Interdisciplinary and Industry-Academia Collaboration Research for Enhancing Social Resilience to Natural Disasters in the Tokyo Metropolitan Area –DEKATSU Activity–, Multi-Data Integration System to Capture Detailed Strong Ground Motion in the Tokyo Metropolitan Area, Development of the Training Tool “KUG” for Temporary Lodging Facilities and Companies for Stranded Commuters, Development of Matching Modeling for Human Resource Allocation of Shelter Management by the Set Theory, Time-Cost Estimation for Early Disaster Damage Assessment Methods, Depending on Affected Area, and A Report of the Questionnaire Survey on Awareness of COVID-19 and Shelters.

The paper presents approach used for the development of the forecasting system of extreme hydro-meteorological events in the region of the Sea of Azov. Due to numerous dangerous extreme events that occurred in the beginning of XXI century the issue of creation such system has become very relevant and important. The forecasting system, named EX-MARE, was started developing in 2014 as a complex of mathematical models. For each type of hydro-meteorological events, the modeling component was designed. The EX-MARE system is based on a scenario approach implied the consideration a variety of possible futures taking into account the existing uncertainty. Accurate extreme events estimation requires automated monitoring systems and longterm database application. In the paper, the detail description of the system components and the data sources is examined. Three case studies about the sea surges, flash flood and ice conditions researches demonstrate the application of the EX-MARE system and the benefits of its using. Further development of the EX-MARE system assumes adding data on exposure and vulnerability to perform the risk assessment, as well as focusing on multi-hazards exploring methodology.

One of the prioritized project of the Belt and Road Initiative is the Silk Road Disaster Risk Reduction. The main aim of the project is to investigate natural hazards affecting Central Asia and Europe in order to understand their evolution and support the spatial planning related to the new infrastructures designing prevention and mitigation measures. The landslide susceptibility zoning is a common practice for land-use planning and environmental impact assessment. Considering the susceptibility as part of the hazard zoning work-flow, a multi-scale (multi-Tier) landslide susceptibility assessment has been carried out and the results are illustrated in this work. Starting from the continental (Tier 1) up to the regional analysis (Tier ≥ 2), the most susceptible areas have been defined to be exploited by successive zoning. Once the most susceptible areas at a regional scale are detected, the hazard zoning can be assessed. In the literature, the landslide susceptibility at continental or global scale has seldom been evaluated. The complexity of the analysis is strictly related to the extension of the study area: the smaller the scale, the higher the complexity of the analysis. Moreover, coordination issues between people and local governments, lack of data due to the absence of strategies for hazards and risk mitigation and data heterogeneity significantly affect the results and forces to find new and innovative solutions from the scientific point of view. In this framework, the Tier 1 landslide susceptibility of the southern Asia has been investigated. It represents the first application of the proposed approach. The results reveal a promising prediction capacity of the method which will be applied to the rest of the Belt and Road study area. The limits, and potentialities of a continental landslide susceptibility are here described. The uncertainty which affect the results of the Tier 1 assessment is mainly related to the lack of consistent data, especially, a global and reliable landslide inventory. However, the Tier 1 landslide susceptibility map has the role to give an overview of the entire study area and to provide the definition of the most landslides prone areas. The method adopted for the analysis is statistically-based and all the resources (software, libraries and data) are open-source. In order to support the reproducibility of the results, a new QGIS tool for statistical analysis has been developed. The Weights of Evidence method has been already implemented, whereas other methods will be coded during further activity.

1. Introduction This Special Issue (Part 2) expands upon the theme “Building Local Capacity for Long-term Disaster Resilience” presented in Special Issue Part 1 (JDR Volume 5, Number 2, April 2010) by examining the evolving concept of disaster resilience and providing additional reflections upon various aspects of its meaning. Part 1 provided a mixed set of examples of resiliency efforts, ranging from administrative challenges of integrating resilience into recovery to the analysis of hazard mitigation plans directed toward guiding local capability for developing resiliency. Resilience was broadly defined in the opening editorial of Special Issue Part 1 as “the capacity of a community to: 1) survive a major disaster, 2) retain essential structure and functions, and 3) adapt to post-disaster opportunities for transforming community structure and functions to meet new challenges.” In this editorial essay we first explore in Section 2 the history of resilience and then locate it within current academic and policy debates. Section 3 presents summaries of the papers in this issue. 2. Why is Resilience a Contemporary Theme? There is growing scholarly and policy interest in disaster resilience. In recent years, engineers [1], sociologists [2], geographers [3], economists [4], public policy analysts [5, 6], urban planners [7], hazards researchers [8], governments [9], and international organizations [10] have all contributed to the literature about this concept. Some authors view resilience as a mechanism for mitigating disaster impacts, with framework objectives such as resistance, absorption, and restoration [5]. Others, who focus on resiliency indicators, see it as an early warning system to assess community resiliency status [3, 8]. Recently, it has emerged as a component of social risk management that seeks to minimize social welfare loss from catastrophic disasters [6]. Manyena [11] traces scholarly exploration of resilience as an operational concept back at least five decades. Interest in resilience began in the 1940s with studies of children and trauma in the family and in the 1970s in the ecology literature as a useful framework to examine and measure the impact of assault or trauma on a defined eco-system component [12]. This led to modeling resilience measures for a variety of components within a defined ecosystem, leading to the realization that the systems approach to resiliency is attractive as a cross-disciplinary construct. The ecosystem analogy however, has limits when applied to disaster studies in that, historically, all catastrophic events have changed the place in which they occurred and a “return to normalcy” does not occur. This is true for modern urban societies as well as traditional agrarian societies. The adoption of “The Hyogo Framework for Action 2005-2015” (also known as The Hyogo Declaration) provides a global linkage and follows the United Nations 1990s International Decade for Natural Disaster Reduction effort. The 2005 Hyogo Declaration’s definition of resilience is: “The capacity of a system, community or society potentially exposed to hazards to adapt by resisting or changing in order to reach and maintain an acceptable level of functioning and structure.” The proposed measurement of resilience in the Hyogo Declaration is determined by “the degree to which the social system is capable of organizing itself to increase this capacity for learning from past disasters for better future protection and to improve risk reduction measures.” While very broad, this definition contains two key concepts: 1) adaptation, and 2) maintaining acceptable levels of functioning and structure. While adaptation requires certain capacities, maintaining acceptable levels of functioning and structure requires resources, forethought, and normative action. Some of these attributes are now reflected in the 2010 National Disaster Recovery Framework published by the U.S. Federal Emergency Management Agency (FEMA) [13]. With the emergence of this new thinking on resilience related to disasters, it is now a good time to reflect on the concept and assess what has recently been said in the literature. Bruneau et al. [1] offer an engineering sciences definition for community seismic resilience: “The ability of social units (e.g., organizations, communities) to mitigate hazards, contain the effects of disasters when they occur, and carry out recovery activities in ways that minimize social disruption and mitigate the effects of future earthquakes.” Rose [4] writes that resiliency is the ability of a system to recover from a severe shock. He distinguishes two types of resilience: (1) inherent – ability under normal circumstances and (2) adaptive – ability in crisis situations due to ingenuity or extra effort. By opening up resilience to categorization he provides a pathway to establish multi-disciplinary approaches, something that is presently lacking in practice. Rose is most concerned with business disruption which can take extensive periods of time to correct. In order to make resource decisions that lower overall societal costs (economic, social, governmental and physical), Rose calls for the establishment of measurements that function as resource decision allocation guides. This has been done in part through risk transfer tools such as private insurance. However, it has not been well-adopted by governments in deciding how to allocate mitigation resources. We need to ask why the interest in resilience has grown? Manyena [11] argues that the concept of resilience has gained currency without obtaining clarity of understanding, definition, substance, philosophical dimensions, or applicability to disaster management and sustainable development theory and practice. It is evident that the “emergency management model” does not itself provide sufficient guidance for policymakers since it is too command-and-control-oriented and does not adequately address mitigation and recovery. Also, large disasters are increasingly viewed as major disruptions of the economic and social conditions of a country, state/province, or city. Lowering post-disaster costs (human life, property loss, economic advancement and government disruption) is being taken more seriously by government and civil society. The lessening of costs is not something the traditional “preparedness” stage of emergency management has concerned itself with; this is an existing void in meeting the expanding interests of government and civil society. The concept of resilience helps further clarify the relationship between risk and vulnerability. If risk is defined as “the probability of an event or condition occurring [14]#8221; then it can be reduced through physical, social, governmental, or economic means, thereby reducing the likelihood of damage and loss. Nothing can be done to stop an earthquake, volcanic eruption, cyclone, hurricane, or other natural event, but the probability of damage and loss from natural and technological hazards can be addressed through structural and non-structural strategies. Vulnerability is the absence of capacity to resist or absorb a disaster impact. Changes in vulnerability can then be achieved by changes in these capacities. In this regard, Franco and Siembieda describe in this issue how coastal cities in Chile had low resilience and high vulnerability to the tsunami generated by the February 2010 earthquake, whereas modern buildings had high resilience and, therefore, were much less vulnerable to the powerful earthquake. We also see how the framework for policy development can change through differing perspectives. Eisner discusses in this issue how local non-governmental social service agencies are building their resilience capabilities to serve target populations after a disaster occurs, becoming self-renewing social organizations and demonstrating what Leonard and Howett [6] term “social resilience.” All of the contributions to this issue illustrate the lowering of disaster impacts and strengthening of capacity (at the household, community or governmental level) for what Alesch [15] terms “post-event viability” – a term reflecting how well a person, business, community, or government functions after a disaster in addition to what they might do prior to a disaster to lessen its impact. Viability might become the definition of recovery if it can be measured or agreed upon. 3. Contents of This Issue The insights provided by the papers in this issue contribute greater clarity to an understanding of resilience, together with its applicability to disaster management. In these papers we find tools and methods, process strategies, and planning approaches. There are five papers focused on local experiences, three on state (prefecture) experiences, and two on national experiences. The papers in this issue reinforce the concept of resilience as a process, not a product, because it is the sum of many actions. The resiliency outcome is the result of multiple inputs from the level of the individual and, at times, continuing up to the national or international organizational level. Through this exploration we see that the “resiliency” concept accepts that people will come into conflict with natural or anthropogenic hazards. The policy question then becomes how to lower the impact(s) of the conflict through “hard or soft” measures (see the Special Issue Part 1 editorial for a discussion of “hard” vs. “soft” resilience). Local level Go Urakawa and Haruo Hayashi illustrate how post-disaster operations for public utilities can be problematic because many practitioners have no direct experience in such operations, noting that the formats and methods normally used in recovery depend on personal skills and effort. They describe how these problems are addressed by creating manuals on measures for effectively implementing post-disaster operations. They develop a method to extract priority operations using business impact analysis (BIA) and project management based business flow diagrams (BFD). Their article effectively illustrates the practical aspects of strengthening the resiliency of public organizations. Richard Eisner presents the framework used to initiate the development and implementation of a process to create disaster resilience in faith-based and community-based organizations that provide services to vulnerable populations in San Francisco, California. A major project outcome is the Disaster Resilience Standard for Community- and Faith-Based Service Providers. This “standard” has general applicability for use by social service agencies in the public and non-profit sectors. Alejandro Linayo addresses the growing issue of technological risk in cities. He argues for the need to understand an inherent conflict between how we occupy urban space and the technological risks created by hazardous chemicals, radiation, oil and gas, and other hazardous materials storage and movement. The paper points out that information and procedural gaps exist in terms of citizen knowledge (the right to know) and local administrative knowledge (missing expertise). Advances and experience accumulated by the Venezuela Disaster Risk Management Research Center in identifying and integrating technological risk treatment for the city of Merida, Venezuela, are highlighted as a way to move forward. L. Teresa Guevara-Perez presents the case that certain urban zoning requirements in contemporary cities encourage and, in some cases, enforce the use of building configurations that have been long recognized by earthquake engineering as seismically vulnerable. Using Western Europe and the Modernist architectural movement, she develops the historical case for understanding discrepancies between urban zoning regulations and seismic codes that have led to vulnerable modern building configurations, and traces the international dissemination of architectural and urban planning concepts that have generated vulnerability in contemporary cities around the world. Jung Eun Kang, Walter Gillis Peacock, and Rahmawati Husein discuss an assessment protocol for Hazard Mitigation Plans applied to 12 coastal hazard zone plans in the state of Texas in the U.S. The components of these plans are systematically examined in order to highlight their respective strengths and weaknesses. The authors describe an assessment tool, the plan quality score (PQS), composed of seven primary components (vision statement, planning process, fact basis, goals and objectives, inter-organizational coordination, policies & actions, and implementation), as well as a component quality score (CQS). State (Prefecture) level Charles Real presents the Natural Hazard Zonation Policies for Land Use Planning and Development in California in the U.S. California has established state-level policies that utilize knowledge of where natural hazards are more likely to occur to enhance the effectiveness of land use planning as a tool for risk mitigation. Experience in California demonstrates that a combination of education, outreach, and mutually supporting policies that are linked to state-designated natural hazard zones can form an effective framework for enhancing the role of land use planning in reducing future losses from natural disasters. Norio Maki, Keiko Tamura, and Haruo Hayashi present a method for local government stakeholders involved in pre-disaster plan making to describe performance measures through the formulation of desired outcomes. Through a case study approach, Nara and Kyoto Prefectures’ separate experiences demonstrate how to conduct Strategic Earthquake Disaster Reduction Plans and Action Plans that have deep stakeholder buy-in and outcome measurability. Nara’s plan was prepared from 2,015 stakeholder ideas and Kyoto’s plan was prepared from 1,613 stakeholder ideas. Having a quantitative target for individual objectives ensures the measurability of plan progress. Both jurisdictions have undertaken evaluations of plan outcomes. Sandy Meyer, Eugene Henry, Roy E. Wright and Cynthia A. Palmer present the State of Florida in the U.S. and its experience with pre-disaster planning for post-disaster redevelopment. Drawing upon the lessons learned from the impacts of the 2004 and 2005 hurricane seasons, local governments and state leaders in Florida sought to find a way to encourage behavior that would create greater community resiliency in 2006. The paper presents initial efforts to develop a post-disaster redevelopment plan (PDRP), including the experience of a pilot county. National level Bo-Yao Lee provides a national perspective: New Zealand’s approach to emergency management, where all hazard risks are addressed through devolved accountability. This contemporary approach advocates collaboration and coordination, aiming to address all hazard risks through the “4Rs” – reduction, readiness, response, and recovery. Lee presents the impact of the Resource Management Act (1991), the Civil Defence Emergency Management Act (2002), and the Building Act (2004) that comprise the key legislation influencing and promoting integrated management for environment and hazard risk management. Guillermo Franco and William Siembieda provide a field assessment of the February 27, 2010, M8.8 earthquake and tsunami event in Chile. The papers present an initial damage and life-loss review and assessment of seismic building resiliency and the country’s rapid updating of building codes that have undergone continuous improvement over the past 60 years. The country’s land use planning system and its emergency management system are also described. The role of insurance coverage reveals problems in seismic coverage for homeowners. The unique role of the Catholic Church in providing temporary shelter and the central government’s five-point housing recovery plan are presented. A weakness in the government’s emergency management system’s early tsunami response system is noted. Acknowledgements The Editorial Committee extends its sincere appreciation to both the contributors and the JDR staff for their patience and determination in making Part 2 of this special issue possible. Thanks also to the reviewers for their insightful analytic comments and suggestions. Finally, the Committee wishes to again thank Bayete Henderson for his keen and thorough editorial assistance and copy editing support.

This paper presents some results of rainfall forecast in the monsoon onset period in South Vietnam, with the use of ensemble Kalman filter to assimilate observation data into the initial field of the model. The study of rainfall forecasts are experimented at the time of Southern monsoon outbreaks for 3 years (2005, 2008 and 2009), corresponding to 18 cases. In each case, there are five trials, including satellite wind data assimilation, upper-air sounding data assimilation, mixed data (satellite wind+upper-air sounding data) assimilation and two controlled trials (one single predictive test and one multi-physical ensemble prediction), which is equivalent to 85 forecasts for one trial. Based on the statistical evaluation of 36 samples (18 meteorological stations and 18 trials), the results show that Kalman filter assimilates satellite wind data to forecast well rainfall at 48 hours and 72 hours ranges. With 24 hour forecasting period, upper-air sounding data assimilation and mixed data assimilation experiments predicted better rainfall than non-assimilation tests. The results of the assessment based on the phase prediction indicators also show that the ensemble Kalman filter assimilating satellite wind data and mixed data sets improve the rain forecasting capability of the model at 48 hours and 72 hour ranges, while the upper-air sounding data assimilation test produces satisfactory results at the 72 hour forecast range, and the multi-physical ensemble test predicted good rainfall at 24 hour and 48 hour forecasts. The results of this research initially lead to a new research approach, Kalman Filter Application that assimilates the existing observation data into input data of the model that can improve the quality of rainfall forecast in Southern Vietnam and overall country in general.References Bui Minh Tuan, Nguyen Minh Truong, 2013. Determining the onset indexes for the summer monsoon over southern Vietnam using numerical model with reanalysis data. VNU Journal of Science, 29(1S), 187-195.Charney J.G., 1955. The use of the primitive equations of motion in numerical prediction, Tellus, 7, 22.Cong Thanh, Tran Tan Tien, Nguyen Tien Toan, 2015. Assessing prediction of rainfall over Quang Ngai area of Vietnam from 1 to 2 day terms. VNU Journal of Science, 31(3S), 231-237.Courtier P., Talagrand O., 1987. Variational assimilation of meteorological observations with the adjoint vorticity equations, Part II, Numerical results. Quart. J. Roy. Meteor. Soc., 113, 1329.Daley R., 1991. Atmospheric data analysis. Cambridge University Press, Cambridge.Elementi M., Marsigli C., Paccagnella T., 2005. High resolution forecast of heavy precipitation with Lokal Modell: analysis of two case studies in the Alpine area. Natural Hazards and Earth System Sciences, 5, 593-602.Fasullo J. and Webster P.J., 2003. A hydrological definition of India monsoon onset and withdrawal. J. Climate, 16, 3200-3211.Haltiner G.J., Williams R.T., 1982. Numerical prediction and dynamic meteorology, John Wiley and Sons, New York.Hamill T.M., Whitaker J.S., Snyder C., 2001. Distance-dependent filtering of background error covariance estimates in an ensemble Kalman filter. Mon. Wea. Rev., 129, 2776.He J., Yu J., Shen X., and Gao H., 2004. Research on mechanism and variability of East Asia monsoon. J. Trop. Meteo, 20(5), 449-459.Hoang Duc Cuong, 2008. Experimental study on heavy rain forecast in Vietnam using MM5 model. A report on the Ministerial-level research projects on science and technology, 105p.Houtekamer P.L., Mitchell H.L., Pellerin G., Buehner M., Charron M., Spacek L., Hansen B., 2005. Atmospheric data assimilation with an ensemble Kalman filter: Results with real observations. Mon. Wea. Rev., 133, 604.Houtekamer P.L., Mitchell H.L., 2005. Ensemble Kalman filtering, Quart. J. Roy. Meteor. Soc., 131C, 3269-3289.Hunt B.R., Kostelich E., Szunyogh I., 2007. Efficient data assimilation for spatiotemporal chaos: a local ensemble transform Kalman filter. Physica D., 230, 112-126.Kalnay E., 2003. Atmospheric modeling, data assimilation and predictability. Cambridge University Press, 181.Kalnay et al., 2008. A local ensemble transform Kalman filter data assimilation system for the NCEP global model. Tellus A, 60(1), 113-130.Kato T., Aranami K., 2009. Formation Factors of 2004 Niigata-Fukushima and Fukui Heavy Rainfalls and Problems in the Predictions using a Cloud-Resolving Model. SOLA. 10, doi:10.2151/sola.Kieu C.Q., 2010. Estimation of Model Error in the Kalman Filter by Perturbed Forcing. VNU Journal of Science, Natural Sciences and Technology, 26(3S), 310-316.Kieu C.Q., 2011. Overview of the Ensemble Kalman Filter and Its Application to the Weather Research and Forecasting (WRF) model. VNU Journal of Science, Natural Sciences and Technology, 27(1S), 17-28.Kieu C.Q., Truong N.M., Mai H.T., and Ngo Duc T., 2012. Sensitivity of the Track and Intensity Forecasts of Typhoon Megi (2010) to Satellite-Derived Atmosphere Motion Vectors with the Ensenble Kalman filter. J. Atmos. Oceanic Technol., 29, 1794-1810.Kieu Thi Xin, 2005. Study on large-scale rainfall forecast by modern technology for flood prevention in Vietnam. State-level independent scientific and technological briefing report, 121-151.Kieu Thi Xin, Vu Thanh Hang, Le Duc, Nguyen Manh Linh, 2013. Climate simulation in Vietnam using regional climate nonhydrostatic NHRCM and hydrostatic RegCM models. Vietnam National University, Hanoi. Journal of Natural sciences and technology, 29(2S), 243-25.Krishnamurti T.N., Bounoa L., 1996. An introduction to numerical weather prediction techniques. CRC Press, Boca Raton, FA.Lau K.M., Yang S., 1997. Climatology and interannual variability of the Southeast Asian summer monsoon. Adv. Atmos. Sci., 14,141-162.Li C., Qu X., 1999. Characteristics of Atmospheric Circulation Associated with Summer monsoon onset in the South China Sea. Onset and Evolution of the South China Sea Monsoon and Its Interaction with the Ocean. Ding Yihui, and Li Chongyin, Eds, Chinese Meteorological Press, Beijing, 200-209.Lin N., Smith J.A., Villarini G., Marchok T.P., Baeck M.L., 2010. Modeling Extreme Rainfall, Winds,and Surge from Hurricane Isabel, 25. Doi: 10.1175/2010WAF2222349.Lu J., Zhang Q., Tao S., and Ju J., 2006. The onset and advance of the Asian summer monsoon. Chinese Science Bulletin, 51(1), 80-88.Matsumoto J., 1997. Seasonal transition of summer rainy season over Indochina and adjacent monsoon region. Adv. Atmos. Sci., 14, 231-245.Miyoshi T., and Kunii M., 2012. The Local Ensenble Transform Kalman Filter with the Weather Rearch and Forecasting Model: Experiments with Real Observation. Pure Appl. Geophysic, 169(3), 321-333. Miyoshi T., Yamane S., 2007. Local ensemble transform Kalman filtering with an AGCM at a T159/L48 resolution. Mon. Wea. Rev., 135, 3841-3861.Nguyen Khanh Van, Tong Phuc Tuan, Vuong Van Vu, Nguyen Manh Ha, 2013. The heavy rain differences based on topo-geographical analyse at Coastal Central Region, from Thanh Hoa to Khanh Hoa. J. Sciences of the Earth, 35, 301-309.Nguyen Minh Truong, Bui Minh Tuan, 2013. A case study on summer monsoon onset prediction for southern Vietnam in 2012 using the RAMS model. VNU Journal of Science, 29(1S), 179-186.Phillips N.A., 1960b. Numerical weather prediction. Adv. Computers, 1, 43-91, Kalnay 2004.Phillips N., 1960a. On the problem of the initial data for the primitive equations, Tellus, 12, 121126.Phuong Nguyen Duc, 2013. Experiment on combinatorial Kalman filtering method for WRF model to forecast heavy rain in central region in Vietnam. The Third International MAHASRI/HyARC Workshop on Asian Monsoon and Water Cycle, 28-30 August 2013, Da Nang, Viet Nam, 217-224.Richardson L.F., 1922. Weather prediction by numerical process. Cambridge University Press, Cambridge. Reprinted by Dover (1965, New York).Routray, Mohanty U.C., Niyogi D., Rizvi S.R., Osuri K.K., 2008. First application of 3DVAR-WRF data assimilation for mesoscale simulation of heavy rainfall events over Indian Monsoon region. Journal of the Royal Meteorological Society, 1555.Schumacher, R. S., C. A. Davis, 2010. Ensemble-based Forecast Uncertainty Analysis of Diverse Heavy Rainfall Events, 25. Doi: 10.1175/2010WAF2222378.Snyder C., Zhang F., 2003. Assimilation of simulated Doppler radar observations with an Ensemble Kalman filter. Mon. Wea. Rev., 131, 1663.Szunyogh I., Kostelich E.J., Gyarmati G., Kalnay E., Hunt B.R., Ott E., Satterfield E., Yorke J.A., 2008. A local ensemble transform Kalman filter data assimilation system for the NCEP global model. Tellus A., 60, 113-130.Tanaka M., 1992. Intraseasonal oscillation and the onset and retreat dates of the summer monsoon east, southeast Asia and the western Pacific region using GMS high cloud amount data. J. Meteorol. Soc. Japan, 70, 613-628.Tan Tien Tran, Nguyen Thi Thanh, 2011. The MODIS satellite data assimilation in the WRF model to forecast rainfall in the central region. VNU Journal of Science, Natural Sciences and Technology, 27(3S), 90-95.Tao S., Chen L., 1987. A review of recent research on East summer monsoon in China, Monsoon Meteorology. C. P. Changand T. N. Krishramurti, Eds, Oxford University Press, Oxford, 60-92.Tippett M.K., Anderson J.L., Bishop C.H., Hamill T.M., Whitaker J.S., 2003. Ensemble square root filters. Mon. Wea. Rev., 131, 1485.Thuy Kieu Thi, Giam Nguyen Minh, Dung Dang Van, 2013. Using WRF model to forecast heavy rainfall events on September 2012 in Dong Nai River Basin. The Third International MAHASRI/HyARC Workshop on Asian Monsoon and Water Cycle, 28-30 August 2013, Da Nang, Viet Nam, 185-200.Xavier, Chandrasekar, Singh R. and Simon B., 2006. The impact of assimilation of MODIS data for the prediction of a tropical low-pressure system over India using a mesoscale model. International Journal of Remote Sensing 27(20), 4655-4676. https://doi.org/10.1080/01431160500207302. Wang B., 2003. Atmosphere-warm ocean interaction and its impacts on Asian-Australian monsoon variation. J. Climate, 16(8), 1195-1211.Wang B. and Wu R., 1997. Peculiar temporal structure of the South China Sea summer monsoon. J. Climate., 15, 386-396.Wang L., He J., and Guan Z., 2004. Characteristic of convective activities over Asian Australian ”landbridge” areas and its possible factors. Act a Meteorologic a Sinica, 18, 441-454.Wang, B., and Z. Fan, 1999. Choice of South Asian Summer Monsoon Indices. Bull. Amer. Meteor. Sci., 80, 629-638.Webster P.J., Magana V.O., Palmer T.N., Shukla J., Tomas R.A., Yanai M., Yasunari T., 1998. Monsoons: Processes, predictability, and teprospects for prediction, J. Geophys. Res., 103, 14451-14510.Wilks Daniel S., 1997. Statistical Methods in the Atmospheric Sciences. Ithaca New York., 59, 255.Whitaker J.S., Hamill T.M., 2002. Ensemble data assimilation without perturbed observations. Mon. Wea. Rev., 130, 1913.Wu G., Zhang Y., 1998. Tibetan plateau forcing and the timing of the monsoon onset over South Asia and the South China Sea. Mon.Wea.Rev., 126, 913-927.Zhang Z., Chan J.C.L., and Ding Y., 2004. Characteristics, evolution and mechanisms of the summer monsoon onset over Southeast Asia. J.Climatology, 24, 1461-1482.http://weather.uwyo.edu/upperair/sounding.html and http://tropic.ssec.wisc.edu/archive/

Climate change induced sea-level rise (SLR) is on its increase globally. Regionally the lowlands of China, Vietnam, Bangladesh, and islands of the Malaysian, Indonesian and Philippine archipelagos are among the world’s most threatened regions. Sea-level rise has major impacts on the ecosystems and society. It threatens coastal populations, economic activities, and fragile ecosystems as mangroves, coastal salt-marches and wetlands. This paper provides a summary of the current state of knowledge of sea level-rise and its effects on both human and natural ecosystems. The focus is on coastal urban areas and low lying deltas in South-East Asia and Vietnam, as one of the most threatened areas in the world. About 3 mm per year reflects the growing consensus on the average SLR worldwide. The trend speeds up during recent decades. The figures are subject to local, temporal and methodological variation. In Vietnam the average values of 3.3 mm per year during the 1993-2014 period are above the worldwide average. Although a basic conceptual understanding exists that the increasing global frequency of the strongest tropical cyclones is related with the increasing temperature and SLR, this relationship is insufficiently understood. Moreover the precise, complex environmental, economic, social, and health impacts are currently unclear. SLR, storms and changing precipitation patterns increase flood risks, in particular in urban areas. Part of the current scientific debate is on how urban agglomeration can be made more resilient to flood risks. Where originally mainly technical interventions dominated this discussion, it becomes increasingly clear that proactive special planning, flood defense, flood risk mitigation, flood preparation, and flood recovery are important, but costly instruments. Next to the main focus on SLR and its effects on resilience, the paper reviews main SLR associated impacts: Floods and inundation, salinization, shoreline change, and effects on mangroves and wetlands. The hazards of SLR related floods increase fastest in urban areas. This is related with both the increasing surface major cities are expected to occupy during the decades to come and the increasing coastal population. In particular Asia and its megacities in the southern part of the continent are increasingly at risk. The discussion points to complexity, inter-disciplinarity, and the related uncertainty, as core characteristics. An integrated combination of mitigation, adaptation and resilience measures is currently considered as the most indicated way to resist SLR today and in the near future.References Aerts J.C.J.H., Hassan A., Savenije H.H.G., Khan M.F., 2000. Using GIS tools and rapid assessment techniques for determining salt intrusion: Stream a river basin management instrument. Physics and Chemistry of the Earth, Part B: Hydrology, Oceans and Atmosphere, 25, 265-273. Doi: 10.1016/S1464-1909(00)00014-9. Alongi D.M., 2002. Present state and future of the world’s mangrove forests. Environmental Conservation, 29, 331-349. Doi: 10.1017/S0376892902000231 Alongi D.M., 2015. The impact of climate change on mangrove forests. Curr. Clim. Change Rep., 1, 30-39. Doi: 10.1007/s404641-015-0002-x. Anderson F., Al-Thani N., 2016. Effect of sea level rise and groundwater withdrawal on seawater intrusion in the Gulf Coast aquifer: Implications for agriculture. Journal of Geoscience and Environment Protection, 4, 116-124. Doi: 10.4236/gep.2016.44015. Anguelovski I., Chu E., Carmin J., 2014. Variations in approaches to urban climate adaptation: Experiences and experimentation from the global South. Global Environmental Change, 27, 156-167. Doi: 10.1016/j.gloenvcha.2014.05.010. Arustienè J., Kriukaitè J., Satkunas J., Gregorauskas M., 2013. Climate change and groundwater - From modelling to some adaptation means in example of Klaipèda region, Lithuania. In: Climate change adaptation in practice. P. Schmidt-Thomé, J. Klein Eds. John Wiley and Sons Ltd., Chichester, UK., 157-169. Bamber J.L., Aspinall W.P., Cooke R.M., 2016. A commentary on “how to interpret expert judgement assessments of twenty-first century sea-level rise” by Hylke de Vries and Roderik S.W. Van de Wal. Climatic Change, 137, 321-328. Doi: 10.1007/s10584-016-1672-7. Barnes C., 2014. Coastal population vulnerability to sea level rise and tropical cyclone intensification under global warming. BSc-thesis. Department of Geography, University of Lethbridge, Alberta Canada. Be T.T., Sinh B.T., Miller F., 2007. Challenges to sustainable development in the Mekong Delta: Regional and national policy issues and research needs. The Sustainable Mekong Research Network, Bangkok, Thailand, 1-210. Bellard C., Leclerc C., Courchamp F., 2014. Impact of sea level rise on 10 insular biodiversity hotspots. Global Ecology and Biogeography, 23, 203-212. Doi: 10.1111/geb.12093. Berg H., Söderholm A.E., Sönderström A.S., Nguyen Thanh Tam, 2017. Recognizing wetland ecosystem services for sustainable rice farming in the Mekong delta, Vietnam. Sustainability Science, 12, 137-154. Doi: 10.1007/s11625-016-0409-x. Bilskie M.V., Hagen S.C., Medeiros S.C., Passeri D.L., 2014. Dynamics of sea level rise and coastal flooding on a changing landscape. Geophysical Research Letters, 41, 927-934. Doi: 10.1002/2013GL058759. Binh T.N.K.D., Vromant N., Hung N.T., Hens L., Boon E.K., 2005. Land cover changes between 1968 and 2003 in Cai Nuoc, Ca Mau penisula, Vietnam. Environment, Development and Sustainability, 7, 519-536. Doi: 10.1007/s10668-004-6001-z. Blankespoor B., Dasgupta S., Laplante B., 2014. Sea-level rise and coastal wetlands. Ambio, 43, 996- 005.Doi: 10.1007/s13280-014-0500-4. Brockway R., Bowers D., Hoguane A., Dove V., Vassele V., 2006. A note on salt intrusion in funnel shaped estuaries: Application to the Incomati estuary, Mozambique.Estuarine, Coastal and Shelf Science, 66, 1-5. Doi: 10.1016/j.ecss.2005.07.014. Cannaby H., Palmer M.D., Howard T., Bricheno L., Calvert D., Krijnen J., Wood R., Tinker J., Bunney C., Harle J., Saulter A., O’Neill C., Bellingham C., Lowe J., 2015. Projected sea level rise and changes in extreme storm surge and wave events during the 21st century in the region of Singapore. Ocean Sci. Discuss, 12, 2955-3001. Doi: 10.5194/osd-12-2955-2015. Carraro C., Favero A., Massetti E., 2012. Investment in public finance in a green, low carbon economy. Energy Economics, 34, S15-S18. Castan-Broto V., Bulkeley H., 2013. A survey ofurban climate change experiments in 100 cities. Global Environmental Change, 23, 92-102. Doi: 10.1016/j.gloenvcha.2012.07.005. Cazenave A., Le Cozannet G., 2014. Sea level rise and its coastal impacts. GeoHealth, 2, 15-34. Doi: 10.1002/2013EF000188. Chu M.L., Guzman J.A., Munoz-Carpena R., Kiker G.A., Linkov I., 2014. A simplified approach for simulating changes in beach habitat due to the combined effects of long-term sea level rise, storm erosion and nourishment. Environmental modelling and software, 52, 111-120. Doi.org/10.1016/j.envcsoft.2013.10.020. Church J.A. et al., 2013. Sea level change. In: Climate change 2013: The physical science basis. Contribution of working group I to the fifth assessment report of Intergovernmental Panel on Climate Change. Eds: Stocker T.F., Qin D., Plattner G.-K., Tignor M., Allen S.K., Boschung J., Nauels A., Xia Y., Bex V., Midgley P.M., Cambridge University Press, Cambridge, UK. Connell J., 2016. Last days of the Carteret Islands? Climate change, livelihoods and migration on coral atolls. Asia Pacific Viewpoint, 57, 3-15. Doi: 10.1111/apv.12118. Dasgupta S., Laplante B., Meisner C., Wheeler, Yan J., 2009. The impact of sea level rise on developing countries: A comparative analysis. Climatic Change, 93, 379-388. Doi: 10.1007/s 10584-008-9499-5. Delbeke J., Vis P., 2015. EU climate policy explained, 136p. Routledge, Oxon, UK. DiGeorgio M., 2015. Bargaining with disaster: Flooding, climate change, and urban growth ambitions in QuyNhon, Vietnam. Public Affairs, 88, 577-597. Doi: 10.5509/2015883577. Do Minh Duc, Yasuhara K., Nguyen Manh Hieu, 2015. Enhancement of coastal protection under the context of climate change: A case study of Hai Hau coast, Vietnam. Proceedings of the 10th Asian Regional Conference of IAEG, 1-8. Do Minh Duc, Yasuhara K., Nguyen Manh Hieu, Lan Nguyen Chau, 2017. Climate change impacts on a large-scale erosion coast of Hai Hau district, Vietnam and the adaptation. Journal of Coastal Conservation, 21, 47-62. Donner S.D., Webber S., 2014. Obstacles to climate change adaptation decisions: A case study of sea level rise; and coastal protection measures in Kiribati. Sustainability Science, 9, 331-345. Doi: 10.1007/s11625-014-0242-z. Driessen P.P.J., Hegger D.L.T., Bakker M.H.N., Van Renswick H.F.M.W., Kundzewicz Z.W., 2016. Toward more resilient flood risk governance. Ecology and Society, 21, 53-61. Doi: 10.5751/ES-08921-210453. Duangyiwa C., Yu D., Wilby R., Aobpaet A., 2015. Coastal flood risks in the Bangkok Metropolitan region, Thailand: Combined impacts on land subsidence, sea level rise and storm surge. American Geophysical Union, Fall meeting 2015, abstract#NH33C-1927. Duarte C.M., Losada I.J., Hendriks I.E., Mazarrasa I., Marba N., 2013. The role of coastal plant communities for climate change mitigation and adaptation. Nature Climate Change, 3, 961-968. Doi: 10.1038/nclimate1970. Erban L.E., Gorelick S.M., Zebker H.A., 2014. Groundwater extraction, land subsidence, and sea-level rise in the Mekong Delta, Vietnam. Environmental Research Letters, 9, 1-20. Doi: 10.1088/1748-9326/9/8/084010. FAO - Food and Agriculture Organisation, 2007.The world’s mangroves 1980-2005. FAO Forestry Paper, 153, Rome, Italy. Farbotko C., 2010. Wishful sinking: Disappearing islands, climate refugees and cosmopolitan experimentation. Asia Pacific Viewpoint, 51, 47-60. Doi: 10.1111/j.1467-8373.2010.001413.x. Goltermann D., Ujeyl G., Pasche E., 2008. Making coastal cities flood resilient in the era of climate change. Proceedings of the 4th International Symposium on flood defense: Managing flood risk, reliability and vulnerability, 148-1-148-11. Toronto, Canada. Gong W., Shen J., 2011. The response of salt intrusion to changes in river discharge and tidal mixing during the dry season in the Modaomen Estuary, China.Continental Shelf Research, 31, 769-788. Doi: 10.1016/j.csr.2011.01.011. Gosian L., 2014. Protect the world’s deltas. Nature, 516, 31-34. Graham S., Barnett J., Fincher R., Mortreux C., Hurlimann A., 2015. Towards fair outcomes in adaptation to sea-level rise. Climatic Change, 130, 411-424. Doi: 10.1007/s10584-014-1171-7. COASTRES-D-12-00175.1. Güneralp B., Güneralp I., Liu Y., 2015. Changing global patterns of urban expoàsure to flood and drought hazards. Global Environmental Change, 31, 217-225. Doi: 10.1016/j.gloenvcha.2015.01.002. Hallegatte S., Green C., Nicholls R.J., Corfee-Morlot J., 2013. Future flood losses in major coastal cities. Nature Climate Change, 3, 802-806. Doi: 10.1038/nclimate1979. Hamlington B.D., Strassburg M.W., Leben R.R., Han W., Nerem R.S., Kim K.-Y., 2014. Uncovering an anthropogenic sea-level rise signal in the Pacific Ocean. Nature Climate Change, 4, 782-785. Doi: 10.1038/nclimate2307. Hashimoto T.R., 2001. Environmental issues and recent infrastructure development in the Mekong Delta: Review, analysis and recommendations with particular reference to large-scale water control projects and the development of coastal areas. Working paper series (Working paper No. 4). Australian Mekong Resource Centre, University of Sydney, Australia, 1-70. Hibbert F.D., Rohling E.J., Dutton A., Williams F.H., Chutcharavan P.M., Zhao C., Tamisiea M.E., 2016. Coral indicators of past sea-level change: A global repository of U-series dated benchmarks. Quaternary Science Reviews, 145, 1-56. Doi: 10.1016/j.quascirev.2016.04.019. Hinkel J., Lincke D., Vafeidis A., Perrette M., Nicholls R.J., Tol R.S.J., Mazeion B., Fettweis X., Ionescu C., Levermann A., 2014. Coastal flood damage and adaptation costs under 21st century sea-level rise. Proceedings of the National Academy of Sciences, 111, 3292-3297. Doi: 10.1073/pnas.1222469111. Hinkel J., Nicholls R.J., Tol R.S.J., Wang Z.B., Hamilton J.M., Boot G., Vafeidis A.T., McFadden L., Ganapolski A., Klei R.J.Y., 2013. A global analysis of erosion of sandy beaches and sea level rise: An application of DIVA. Global and Planetary Change, 111, 150-158. Doi: 10.1016/j.gloplacha.2013.09.002. Huong H.T.L., Pathirana A., 2013. Urbanization and climate change impacts on future urban flooding in Can Tho city, Vietnam. Hydrol. Earth Syst. Sci., 17, 379-394. Doi: 10.5194/hess-17-379-2013. Hurlimann A., Barnett J., Fincher R., Osbaldiston N., Montreux C., Graham S., 2014. Urban planning and sustainable adaptation to sea-level rise. Landscape and Urban Planning, 126, 84-93. Doi: 10.1016/j.landurbplan.2013.12.013. IMHEN-Vietnam Institute of Meteorology, Hydrology and Environment, 2011. Climate change vulnerability and risk assessment study for Ca Mau and KienGiang provinces, Vietnam. Hanoi, Vietnam Institute of Meteorology, Hydrology and Environment (IMHEN), 250p. IMHEN-Vietnam Institute of Meteorology, Hydrology and Environment, Ca Mau PPC, 2011. Climate change impact and adaptation study in The Mekong Delta - Part A: Ca Mau Atlas. Hanoi, Vietnam: Institute of Meteorology, Hydrology and Environment (IMHEN), 48p. IPCC-Intergovernmental Panel on Climate Change, 2014. Fifth assessment report. Cambridge University Press, Cambridge, UK. Jevrejeva S., Jackson L.P., Riva R.E.M., Grinsted A., Moore J.C., 2016. Coastal sea level rise with warming above 2°C. Proceedings of the National Academy of Sciences, 113, 13342-13347. Doi: 10.1073/pnas.1605312113. Junk W.J., AN S., Finlayson C.M., Gopal B., Kvet J., Mitchell S.A., Mitsch W.J., Robarts R.D., 2013. Current state of knowledge regarding the world’s wetlands and their future under global climate change: A synthesis. Aquatic Science, 75, 151-167. Doi: 10.1007/s00027-012-0278-z. Jordan A., Rayner T., Schroeder H., Adger N., Anderson K., Bows A., Le Quéré C., Joshi M., Mander S., Vaughan N., Whitmarsh L., 2013. Going beyond two degrees? The risks and opportunities of alternative options. Climate Policy, 13, 751-769. Doi: 10.1080/14693062.2013.835705. Kelly P.M., Adger W.N., 2000. Theory and practice in assessing vulnerability to climate change and facilitating adaptation. Climatic Change, 47, 325-352. Doi: 10.1023/A:1005627828199. Kirwan M.L., Megonigal J.P., 2013. Tidal wetland stability in the face of human impacts and sea-level rice. Nature, 504, 53-60. Doi: 10.1038/nature12856. Koerth J., Vafeidis A.T., Hinkel J., Sterr H., 2013. What motivates coastal households to adapt pro actively to sea-level rise and increased flood risk? Regional Environmental Change, 13, 879-909. Doi: 10.1007/s10113-12-399-x. Kontgis K., Schneider A., Fox J;,Saksena S., Spencer J.H., Castrence M., 2014. Monitoring peri urbanization in the greater Ho Chi Minh City metropolitan area. Applied Geography, 53, 377-388. Doi: 10.1016/j.apgeogr.2014.06.029. Kopp R.E., Horton R.M., Little C.M., Mitrovica J.X., Oppenheimer M., Rasmussen D.J., Strauss B.H., Tebaldi C., 2014. Probabilistic 21st and 22nd century sea-level projections at a global network of tide-gauge sites. Earth’s Future, 2, 383-406. Doi: 10.1002/2014EF000239. Kuenzer C., Bluemel A., Gebhardt S., Quoc T., Dech S., 2011. Remote sensing of mangrove ecosystems: A review.Remote Sensing, 3, 878-928. Doi: 10.3390/rs3050878. Lacerda G.B.M., Silva C., Pimenteira C.A.P., Kopp Jr. R.V., Grumback R., Rosa L.P., de Freitas M.A.V., 2013. Guidelines for the strategic management of flood risks in industrial plant oil in the Brazilian coast: Adaptive measures to the impacts of sea level rise. Mitigation and Adaptation Strategies for Global Change, 19, 104-1062. Doi: 10.1007/s11027-013-09459-x. Lam Dao Nguyen, Pham Van Bach, Nguyen Thanh Minh, Pham Thi Mai Thy, Hoang Phi Hung, 2011. Change detection of land use and river bank in Mekong Delta, Vietnam using time series remotely sensed data. Journal of Resources and Ecology, 2, 370-374. Doi: 10.3969/j.issn.1674-764x.2011.04.011. Lang N.T., Ky B.X., Kobayashi H., Buu B.C., 2004. Development of salt tolerant varieties in the Mekong delta. JIRCAS Project, Can Tho University, Can Tho, Vietnam, 152. Le Cozannet G., Rohmer J., Cazenave A., Idier D., Van de Wal R., de Winter R., Pedreros R., Balouin Y., Vinchon C., Oliveros C., 2015. Evaluating uncertainties of future marine flooding occurrence as sea-level rises. Environmental Modelling and Software, 73, 44-56. Doi: 10.1016/j.envsoft.2015.07.021. Le Cozannet G., Manceau J.-C., Rohmer J., 2017. Bounding probabilistic sea-level projections with the framework of the possible theory. Environmental Letters Research, 12, 12-14. Doi.org/10.1088/1748-9326/aa5528.Chikamoto Y., 2014. Recent Walker circulation strengthening and Pacific cooling amplified by Atlantic warming. Nature Climate Change, 4, 888-892. Doi: 10.1038/nclimate2330. Lovelock C.E., Cahoon D.R., Friess D.A., Gutenspergen G.R., Krauss K.W., Reef R., Rogers K., Saunders M.L., Sidik F., Swales A., Saintilan N., Le Xuan Tuyen, Tran Triet, 2015. The vulnerability of Indo-Pacific mangrove forests to sea-level rise. Nature, 526, 559-563. Doi: 10.1038/nature15538. MA Millennium Ecosystem Assessment, 2005. Ecosystems and human well-being: Current state and trends. Island Press, Washington DC, 266p. Masterson J.P., Fienen M.N., Thieler E.R., Gesch D.B., Gutierrez B.T., Plant N.G., 2014. Effects of sea level rise on barrier island groundwater system dynamics - ecohydrological implications. Ecohydrology, 7, 1064-1071. Doi: 10.1002/eco.1442. McGanahan G., Balk D., Anderson B., 2007. The rising tide: Assessing the risks of climate changes and human settlements in low elevation coastal zones.Environment and urbanization, 19, 17-37. Doi: 10.1177/095624780707960. McIvor A., Möller I., Spencer T., Spalding M., 2012. Reduction of wind and swell waves by mangroves. The Nature Conservancy and Wetlands International, 1-27. Merryn T., Pidgeon N., Whitmarsh L., Ballenger R., 2016. Expert judgements of sea-level rise at the local scale. Journal of Risk Research, 19, 664-685. Doi.org/10.1080/13669877.2015.1043568. Monioudi I.N., Velegrakis A.F., Chatzipavlis A.E., Rigos A., Karambas T., Vousdoukas M.I., Hasiotis T., Koukourouvli N., Peduzzi P., Manoutsoglou E., Poulos S.E., Collins M.B., 2017. Assessment of island beach erosion due to sea level rise: The case of the Aegean archipelago (Eastern Mediterranean). Nat. Hazards Earth Syst. Sci., 17, 449-466. Doi: 10.5194/nhess-17-449-2017. MONRE - Ministry of Natural Resources and Environment, 2016. Scenarios of climate change and sea level rise for Vietnam. Publishing House of Environmental Resources and Maps Vietnam, Hanoi, 188p. Montz B.E., Tobin G.A., Hagelman III R.R., 2017. Natural hazards. Explanation and integration. The Guilford Press, NY, 445p. Morgan L.K., Werner A.D., 2014. Water intrusion vulnerability for freshwater lenses near islands. Journal of Hydrology, 508, 322-327. Doi: 10.1016/j.jhydrol.2013.11.002. Muis S., Güneralp B., Jongman B., Aerts J.C.H.J., Ward P.J., 2015. Science of the Total Environment, 538, 445-457. Doi: 10.1016/j.scitotenv.2015.08.068. Murray N.J., Clemens R.S., Phinn S.R., Possingham H.P., Fuller R.A., 2014. Tracking the rapid loss of tidal wetlands in the Yellow Sea. Frontiers in Ecology and Environment, 12, 267-272. Doi: 10.1890/130260. Neumann B., Vafeidis A.T., Zimmermann J., Nicholls R.J., 2015a. Future coastal population growth and exposure to sea-level rise and coastal flooding. A global assessment. Plos One, 10, 1-22. Doi: 10.1371/journal.pone.0118571. Nguyen A. Duoc, Savenije H. H., 2006. Salt intrusion in multi-channel estuaries: a case study in the Mekong Delta, Vietnam. Hydrology and Earth System Sciences Discussions, European Geosciences Union, 10, 743-754. Doi: 10.5194/hess-10-743-2006. Nguyen An Thinh, Nguyen Ngoc Thanh, Luong Thi Tuyen, Luc Hens, 2017. Tourism and beach erosion: Valuing the damage of beach erosion for tourism in the Hoi An, World Heritage site. Journal of Environment, Development and Sustainability. Nguyen An Thinh, Luc Hens (Eds.), 2018. Human ecology of climate change associated disasters in Vietnam: Risks for nature and humans in lowland and upland areas. Springer Verlag, Berlin.Nguyen An Thinh, Vu Anh Dung, Vu Van Phai, Nguyen Ngoc Thanh, Pham Minh Tam, Nguyen Thi Thuy Hang, Le Trinh Hai, Nguyen Viet Thanh, Hoang Khac Lich, Vu Duc Thanh, Nguyen Song Tung, Luong Thi Tuyen, Trinh Phuong Ngoc, Luc Hens, 2017. Human ecological effects of tropical storms in the coastal area of Ky Anh (Ha Tinh, Vietnam). Environ Dev Sustain, 19, 745-767. Doi: 10.1007/s/10668-016-9761-3. Nguyen Van Hoang, 2017. Potential for desalinization of brackish groundwater aquifer under a background of rising sea level via salt-intrusion prevention river gates in the coastal area of the Red River delta, Vietnam. Environment, Development and Sustainability. Nguyen Tho, Vromant N., Nguyen Thanh Hung, Hens L., 2008. Soil salinity and sodicity in a shrimp farming coastal area of the Mekong Delta, Vietnam. Environmental Geology, 54, 1739-1746. Doi: 10.1007/s00254-007-0951-z. Nguyen Thang T.X., Woodroffe C.D., 2016. Assessing relative vulnerability to sea-level rise in the western part of the Mekong River delta. Sustainability Science, 11, 645-659. Doi: 10.1007/s11625-015-0336-2. Nicholls N.N., Hoozemans F.M.J., Marchand M., Analyzing flood risk and wetland losses due to the global sea-level rise: Regional and global analyses.Global Environmental Change, 9, S69-S87. Doi: 10.1016/s0959-3780(99)00019-9. Phan Minh Thu, 2006. Application of remote sensing and GIS tools for recognizing changes of mangrove forests in Ca Mau province. In Proceedings of the International Symposium on Geoinformatics for Spatial Infrastructure Development in Earth and Allied Sciences, Ho Chi Minh City, Vietnam, 9-11 November, 1-17. Reise K., 2017. Facing the third dimension in coastal flatlands.Global sea level rise and the need for coastal transformations. Gaia, 26, 89-93. Renaud F.G., Le Thi Thu Huong, Lindener C., Vo Thi Guong, Sebesvari Z., 2015. Resilience and shifts in agro-ecosystems facing increasing sea-level rise and salinity intrusion in Ben Tre province, Mekong Delta. Climatic Change, 133, 69-84. Doi: 10.1007/s10584-014-1113-4. Serra P., Pons X., Sauri D., 2008. Land cover and land use in a Mediterranean landscape. Applied Geography, 28, 189-209. Shearman P., Bryan J., Walsh J.P., 2013.Trends in deltaic change over three decades in the Asia-Pacific Region. Journal of Coastal Research, 29, 1169-1183. Doi: 10.2112/JCOASTRES-D-12-00120.1. SIWRR-Southern Institute of Water Resources Research, 2016. Annual Report. Ministry of Agriculture and Rural Development, Ho Chi Minh City, 1-19. Slangen A.B.A., Katsman C.A., Van de Wal R.S.W., Vermeersen L.L.A., Riva R.E.M., 2012. Towards regional projections of twenty-first century sea-level change based on IPCC RES scenarios. Climate Dynamics, 38, 1191-1209. Doi: 10.1007/s00382-011-1057-6. Spencer T., Schuerch M., Nicholls R.J., Hinkel J., Lincke D., Vafeidis A.T., Reef R., McFadden L., Brown S., 2016. Global coastal wetland change under sea-level rise and related stresses: The DIVA wetland change model. Global and Planetary Change, 139, 15-30. Doi:10.1016/j.gloplacha.2015.12.018. Stammer D., Cazenave A., Ponte R.M., Tamisiea M.E., 2013. Causes of contemporary regional sea level changes. Annual Review of Marine Science, 5, 21-46. Doi: 10.1146/annurev-marine-121211-172406. Tett P., Mee L., 2015. Scenarios explored with Delphi. In: Coastal zones ecosystems services. Eds., Springer, Berlin, Germany, 127-144. Tran Hong Hanh, 2017. Land use dynamics, its drivers and consequences in the Ca Mau province, Mekong delta, Vietnam. PhD dissertation, 191p. VUBPRESS Brussels University Press, ISBN 9789057186226, Brussels, Belgium. Tran Thuc, Nguyen Van Thang, Huynh Thi Lan Huong, Mai Van Khiem, Nguyen Xuan Hien, Doan Ha Phong, 2016. Climate change and sea level rise scenarios for Vietnam. Ministry of Natural resources and Environment. Hanoi, Vietnam. Tran Hong Hanh, Tran Thuc, Kervyn M., 2015. Dynamics of land cover/land use changes in the Mekong Delta, 1973-2011: A remote sensing analysis of the Tran Van Thoi District, Ca Mau province, Vietnam. Remote Sensing, 7, 2899-2925. Doi: 10.1007/s00254-007-0951-z Van Lavieren H., Spalding M., Alongi D., Kainuma M., Clüsener-Godt M., Adeel Z., 2012. Securing the future of Mangroves. The United Nations University, Okinawa, Japan, 53, 1-56. Water Resources Directorate. Ministry of Agriculture and Rural Development, 2016. Available online: http://www.tongcucthuyloi.gov.vn/Tin-tuc-Su-kien/Tin-tuc-su-kien-tong-hop/catid/12/item/2670/xam-nhap-man-vung-dong-bang-song-cuu-long--2015---2016---han-han-o-mien-trung--tay-nguyen-va-giai-phap-khac-phuc. Last accessed on: 30/9/2016. Webster P.J., Holland G.J., Curry J.A., Chang H.-R., 2005. Changes in tropical cyclone number, duration, and intensity in a warming environment. Science, 309, 1844-1846. Doi: 10.1126/science.1116448. Were K.O., Dick O.B., Singh B.R., 2013. Remotely sensing the spatial and temporal land cover changes in Eastern Mau forest reserve and Lake Nakuru drainage Basin, Kenya. Applied Geography, 41, 75-86. Williams G.A., Helmuth B., Russel B.D., Dong W.-Y., Thiyagarajan V., Seuront L., 2016. Meeting the climate change challenge: Pressing issues in southern China an SE Asian coastal ecosystems. Regional Studies in Marine Science, 8, 373-381. Doi: 10.1016/j.rsma.2016.07.002. Woodroffe C.D., Rogers K., McKee K.L., Lovdelock C.E., Mendelssohn I.A., Saintilan N., 2016. Mangrove sedimentation and response to relative sea-level rise. Annual Review of Marine Science, 8, 243-266. Doi: 10.1146/annurev-marine-122414-034025.

In this thesis, some methodologies for multi-risk assessment are presented, that can be applied to regional or local scale. At the local scale, the problem of uncertainty propagation in risk assessment is treated, testing different methodology for calculation. The work is organised in four parts: 1. Multi risk analysis at the regional scale in Lombardy (PRIM project, 2007). The methodology integrates information with different degree of accuracy into an indicator based approach, in order to develop a regional scale multirisk assessment and to identify “hot spot” risk areas for more detailed analysis. Eventually, the sensitivity of weights is investigated, and the effect on risk assessment of different individual attitudes and perception (i.e., expert, social, political, risk aversion). 2. Quantitative multi risk assessment (QRA) at the local scale on the hot spots, for lower Valtellina and the area of Brescia and lower Val Trompia, Val Sabbia, and Valcamonica. The methodology is based on the use of historical data and modelling to assess for each threat the expected number of casualties and the expected economic damage. 3. Quantitative risk assessment (QRA) for floods, earthquakes and industrial accidents in the area of Brescia (420 km2), with uncertainty propagation analysis. Frequency-damage curves were calculated. Three methods were 6 used and compared to calculate the uncertainty of the expected economic losses: Monte Carlo Simulation, First Order Second Moment approach, and Point Estimate. 4. Realization of a tool based on a system of indicators aimed at assigning a priority for the realization of new mitigation works, at the evaluation of efficacy of existent works, and at the comparison of different alternatives for the same risk scenario. Indicators are referred to the risk scenario, to the most recent and most significant event occurred in the analysed area, to the planning stage of the work, and to the technical characteristics of realization and maintenance of the work itself.

One of the great challenges facing human systems today is how to prepare for, manage, and adapt successfully to the profound and rapid changes wreaked by disasters. Wellington, New Zealand, is a capital city at significant risk of devastating earthquake and tsunami, potentially requiring mass evacuations with little or short notice. Subsequent hardship and suffering due to widespread property damage and infrastructure failure could cause large areas of the Wellington Region to become uninhabitable for weeks to months. Previous research has shown that positive health and well-being are associated with disaster-resilient outcomes. Preventing adverse outcomes before disaster strikes, through developing strengths-based skill sets in health-protective attitudes and behaviours, is increasingly advocated in disaster research, practise, and management. This study hypothesised that well-being constructs involving an affective heuristic play vital roles in pathways to resilience as proximal determinants of health-protective behaviours. Specifically, this study examined the importance of health-related quality of life and subjective well-being in motivating evacuation preparedness, measured in a community sample (n=695) drawn from the general adult population of Wellington’s isolated eastern suburbs. Using a quantitative epidemiological approach, the study measured the prevalence of key quality of life indicators (physical and mental health, emotional well-being or “Sense of Coherence”, spiritual well-being, social well-being, and life satisfaction) using validated psychometric scales; analysed the strengths of association between these indicators and the level of evacuation preparedness at categorical and continuous levels of measurement; and tested the predictive power of the model to explain the variance in evacuation preparedness activity. This is the first study known to examine multi-dimensional positive health and global well-being as resilient processes for engaging in evacuation preparedness behaviour. A cross-sectional study design and quantitative survey were used to collect self-report data on the study variables; a postal questionnaire was fielded between November 2008 and March 2009 to a sampling frame developed through multi-stage cluster randomisation. The survey response rate was 28.5%, yielding a margin of error of +/- 3.8% with 95% confidence and 80% statistical power to detect a true correlation coefficient of 0.11 or greater. In addition to the primary study variables, data were collected on demographic and ancillary variables relating to contextual factors in the physical environment (risk perception of physical and personal vulnerability to disaster) and the social environment (through the construct of self-determination), and other measures of disaster preparedness. These data are reserved for future analyses. Results of correlational and regression analyses for the primary study variables show that Wellingtonians are highly individualistic in how their well-being influences their preparedness, and a majority are taking inadequate action to build their resilience to future disaster from earthquake- or tsunami-triggered evacuation. At a population level, the conceptual multi-dimensional model of health-related quality of life and global well-being tested in this study shows a positive association with evacuation preparedness at statistically significant levels. However, it must be emphasised that the strength of this relationship is weak, accounting for only 5-7% of the variability in evacuation preparedness. No single dimension of health-related quality of life or well-being stands out as a strong predictor of preparedness. The strongest associations for preparedness are in a positive direction for spiritual well-being, emotional well-being, and life satisfaction; all involve a sense of existential meaningfulness. Spiritual well-being is the only quality of life variable making a statistically significant unique contribution to explaining the variance observed in the regression models. Physical health status is weakly associated with preparedness in a negative direction at a continuous level of measurement. No association was found at statistically significant levels for mental health status and social well-being. These findings indicate that engaging in evacuation preparedness is a very complex, holistic, yet individualised decision-making process, and likely involves highly subjective considerations for what is personally relevant. Gender is not a factor. Those 18-24 years of age are least likely to prepare and evacuation preparedness increases with age. Multidimensional health and global well-being are important constructs to consider in disaster resilience for both pre-event and post-event timeframes. This work indicates a need for promoting self-management of risk and building resilience by incorporating a sense of personal meaning and importance into preparedness actions, and for future research into further understanding preparedness motivations.

Hurricanes are multi-hazard natural hazards that can cause severe damage to chemical and process plants via individual or combined impact of strong winds, torrential rainfall, floods, and hitting waves especially in coastal areas. To assess and manage the vulnerability of process plants, failure modes and respective failure probabilities both before and after implementing safety measures should be assessed. However, due to the uncertainties arising from interdependent failure modes and lack of accurate and sufficient historical data, most conventional quantitative risk assessment techniques deliver inaccurate results, which in turn lead to inaccurate risk assessment and thus ineffective or non-cost-effective risk management strategies. Bayesian network (BN) is a probabilistic technique for reasoning under uncertainty with a variety of applications is system safety, reliability engineering, and risk assessment. In this chapter, applications of BN to vulnerability assessment and management of process vessels in the event of hurricanes are demonstrated and discussed.

Despite many advances in the field of hydroinformatics, the policy and decision-making world is unable to use these highly technical decision support systems (DSSs) because there has been an undue emphasis on the technological aspects. The historical analysis of hydroinformatics concepts and modelling shows that the technical aspects have been incorporated far better than the social aspects. Hence, there have been calls for the development of ‘socio-technical’ DSSs. However, far greater effort is required to incorporate social and political sciences into the domain of DSSs. The goal of this chapter is to elaborate on the illusive interface between science and water policy within the context of DSSs. It is an attempt to address one main question: how to link or find an interface between policy (institutional matters) and science (technical and natural environment aspects). To achieve this goal, a new paradigm for the DSS modelling approach has been envisaged based on combining multiple theoretical and analytical frameworks into a single methodological framework to attain a linkage between science and policy-making. The integrated methodological framework comprises of: (1) two ‘conceptual’ frameworks: (a) decision-making perspectives and (b) IWRM interface frameworks; (2) analytical frameworks: (a) DPSIR socio-technical assessment and (b) institutional analysis (IA) frameworks; (3) core engine of the DSS consisting of coupled decision support tools (DST) such as process, planning and evaluation models; and (4) a stakeholder participation interface framework consisting of (a(a multi-windowed dynamic cyber stakeholder interface (MDCSI) system and (b) DSS performance assessment (uncertainty and risk analysis) tools, within a shell of a graphical user interface (GUI). From experience, it can be concluded that DSSs are not just about software packages but they are a participatory communication platform for an interactive multi-stakeholder decision-making process. The required science-policy interface can be achieved by using a unique analytical approach in which technical, policy and institutional frameworks are combined within a DSS platform with an output framework, the MDCSI system, that facilitate policy dialogue by having a dynamic and interactive policy interface which can be linked to other technical and non-technical systems. DSSs should be integrated with institutional and socio-political frameworks to help attain both financial and institutional sustainability.