Vulnerability assessment in the Mekong delta of vietnam: a review

An Giang University Journal of Science – 2017, Vol. 5 (2), 26 – 31 26 VULNERABILITY ASSESSMENT IN THE MEKONG DELTA OF VIETNAM: A REVIEW Nguyen Huu Tri1 1An Giang University Information: Received: 09/11/2016 Accepted: 28/01/2017 Published: 06/2017 Keywords: Vulnerability assenssment, Mekong Delta ABSTRACT This paper reviewed the methodology of vulnerability assessment in the context of climate change. Although many methods were applied in vulnerability assessment, lack of clear methods can be applied in the Mekong Delta of Vietnam. This paper recommended that vulnerability should be assessed basing on the function of impact (I) and adaptation (A) in the past, present, and future, including future projected impacts. 1. INTRODUCTION The Mekong Delta is extremely sensitive region to climate change. According to IPCC (2007), the most significant vulnerability factors are settlements and societies located in river flood plains. Poor inhabitants are more vulnerable because they have limited adaptive capacity and mainly depend on climate-sensitive resources. In the Mekong Delta, the effect of climate change can come from one of three sources: (1) indirect socioeconomic impacts of change in resource dependent sectors as agriculture and fisheries; (2) direct impact on physical infrastructure, life conditions and population; and (3) deterioration of regional or national technological, economics and social trend. This study aims to review methods which relate to vulnerable assessment in the Mekong Delta of Vietnam. 2. APPLIED METHODS IN VULNERABILITY ASSESSMENT IN THE MEKONG DELTA According to IPCC (2007), the vulnerability to climate change could be evaluated by three elements: exposure, sensitivity, and adaptive capacity. The vulnerability assessment could be undertaken by evaluating (1) exposure to threats, (2) sensitivity, and (3) the adaptive capacity to cope with and adapt to threats. The degree of vulnerability was directly related to the degree of exposure, sensitivity, and adaptive capacity. Vulnerability was assessed by the determining of impact and adaptive capacity. UNEP (2011) suggested vulnerability indices which could be used for quantitative measure. Different levels of local, regional and international users may use different quantitative indices of vulnerability (Figure 1). Vulnerability indices can be measured by designing and targeting project in each level. At local level, for example, vulnerability indices focus on profile of vulnerable situation or syndrome as project evaluation. While regional level, vulnerability indices concern on planning adaptation strategies as program design to promote adaptation capacity. At the global level, indices are normally used to compare countries, and help frame eligibility for fund to reduce vulnerability and force adaptation to climate change. Chinvanno (2007) applied the simple methodologies for community vulnerability An Giang University Journal of Science – 2017, Vol. 5 (2), 26 – 31 27 assessments for potential future climate threats analysis, suggested that the implementation of these steps of actions: (1) scenario-based study, use climate threats scenario and proxy of its impact to measure potential socioeconomic impacts; (2) use multiple indicators to evaluate sensitivity or coping capacity; (3) assess disasters impact on household or community livelihood conditions; and (4) compare livelihood conditions to understand household or community vulnerability. The ultimate purpose of vulnerability assessment is to implement the appropriate adaptation. Figure 1. A hierarchy of vulnerability and vulnerability indices (adapted from UNEP, 2001) In terms of vulnerability assessment at community level, Smit and Wandel (2006) proposed a framework of Community Based Vulnerability Assessment that assisted to understand the complexities and inequities of intra-regional climate change vulnerability in order to foster successful local adaptation. There are three stages as shown in Figure 2. The Community-Based Vulnerability Assessment Framework focuses on community engagement throughout the entire process, and aims to highlight the needs of various stakeholders within communities, while integrating interdisciplinary and local-traditional knowledge. It aims to not only identify current exposure, sensitivity and adaptive strategies but also consider future exposure, sensitivity and adaptive capacity based on community level. This framework should be applied in assessment of exposure, sensitivity and adaptive strategies at present and future in order to build the adaptation options at community level. Metzger et al. (2006) developed vulnerability function V = f (E, S, AC) where vulnerability (V) depends on exposure (E), sensitivity (S) and adaptive capacity (AC). Klein and Nicholls (1999) designed a framework for vulnerability assessment showing relationship between the vulnerability of natural and socioeconomic sectors of a region to climate change impacts via their susceptibility (potential impacts), resiliencies (ability to prevent or continue functioning) and the adaptation provided to them. An Giang University Journal of Science – 2017, Vol. 5 (2), 26 – 31 28 Figure 2. Community-Based Vulnerability Assessment Framework (adapted from Smit and Wandel, 2006) In 2012, the Climate Change Vulnerability Assessment and Adaptation Methodology (CAM) of International Centre for Environmental Management (ICEM) was applied into approach to saline intrusion mitigation and adaptation planning. This conceptual approach was recently taken by International Union for Conservation of Nature (IUCN) and The United States Agency for International Development (USAID) at different levels and stages of climate change mitigation and adaptation planning (Meynell et al., 2014; ICEM, 2013; USAID, 2010). CAM process steps and concepts comprised three main phases, including vulnerability assessment, adaptation planning and adaptation implementation. For vulnerability assessment, this method focused on identifying impacts and assessing vulnerability of rice and fish farming households to saline intrusion. The vulnerability assessment followed a recognized pattern of assessing the exposure and sensitivity to saline intrusion, and the likely impacts that might result. When combined with the adaptive capacity of households, the analysis of their vulnerability can be made (Figure 3). For practical application, a precise step-wise process was defined and supported by tool boxes which facilitated appropriate information inputs at each step. The operational vulnerability assessment and adaptation planning process involved six main components, i.e. determining the scope, determining the saline intrusion threats, conducting a baseline assessment, conducting the impact assessment, assessing the adaptation capacity, and establishing the relative vulnerability. Stage 1 Stage 2 Current Exposures and Sensitivities Current Adaptive Strategies Future Exposures and Sensitivities Future Adaptive Strategies Expected Changes in Natural and Social System Governance assessment (Multi-level networks, adaptiveness, transformations) Stage 3 Community Adaptation Visioning and Evaluation Against Maladaptation Criteria Adaptation Needs, Options An Giang University Journal of Science – 2017, Vol. 5 (2), 26 – 31 29 Figure 3. Saline intrusion impacts and vulnerability assessment process (modified from ICEM, 2012); (SI = saline intrusion; E = Exposure; S = Sensitivity) The CAM method outlined four important components in assessing vulnerability: exposure, sensitivity, impact, and adaptive capacity (Figure 4). Figure 4. Major components considered in the baseline and vulnerability assessment process (adapted from ICEM, 2012) Applied to vulnerability assessment in the Mekong Delta of Vietnam, exposure was the degree of saline intrusion stress on rice and fish farming systems. Especially, rice varieties and fish species were influenced by long-term changes in salinity conditions and variability, including the magnitude and frequency of saline intrusion. Sensitivity was the degree to which rice varieties, fish species or rice and fish farming systems would be affected by, or responsive to saline intrusion exposure. The potential impact (or level of risk) was a function of the level of exposure to climate change-induced An Giang University Journal of Science – 2017, Vol. 5 (2), 26 – 31 30 threats, and the level of sensitivity of the target farming system to that exposure. Qualitative terms of measurement could be divided into different orders, for examples, (1) very low: inconvenience (days); (2) low: short disruption to system function (weeks); (3) moderate: medium term disruption to system function (months); (4) high: long term damage to system property or function (years); and (5) very high: loss of life, livelihood or system integrity. Adaptive capacity was understood in terms of the ability to prepare for the future saline intrusion threat, to increase resilience, and to recover from the impact. Qualitative terms of measurement could be divided into different orders, for examples, (1) very low: very limited institutional capacity and no access to technical or financial resource; (2) low: limited institutional capacity and limited access to technical or financial resource; (3) moderate: growing institutional capacity and access to technical and financial resource; (4) high: sound institutional capacity and good access to technical and financial resource; and (5) very high: exceptional institutional capacity and abundant access to technical and financial resource. According to Meynell et al. (2014), the determinants of adaptive capacity included natural systems, infrastructure, social factors, and crosscutting factors. Applied to this research, the determinants of adaptive capacity were defined by production systems, infrastructure, social factors, and crosscutting factors as follows.  Production systems: varieties or species diversity and ecosystem integrity; varieties or species tolerance levels; availability of alternative farming systems; ability to regenerate or spatially shift; individual varieties or species: dispersal range and life strategy.  Infrastructure: availability of physical resources (e.g. preventive engineering structures, materials, and equipments).  Social factors: social networks; insurance and financial resources; access to external services (medical services, credits and loans, markets, disaster information); access to alternative products and services.  Crosscutting factors: the range of available adaptation technologies, planning and management tools; availability and distribution of financial resources; availability of relevant skills and knowledge; management, maintenance, and response systems including policies, structures, technical staff, and budgets; political will and policy commitment. The CAM method could use ranking, rating, and scoring for exposure, sensitivity, impact, and adaptive capacity leading to comparative levels for vulnerability. Table 1 and Table 2 show examples of rating matrices used in this research to assess impact of and vulnerability to saline intrusion. Table 1. Determining impact (Exposure x Sensitivity) (adapted from ICEM, 2012) Exposure to saline intrusion S en si ti vi ty t o sa li n e in tr u si on Very low Low Moderate High Very high Very high Moderate Moderate High Very high Very high High Low Moderate Moderate High Very high Moderate Low Moderate Moderate High Very high Low Low Low Moderate Moderate High Very low Very low Low Low Moderate High An Giang University Journal of Science – 2017, Vol. 5 (2), 26 – 31 31 Table 2. Determining vulnerability (Impact/Adaptive capacity) (adapted from ICEM, 2012) Impact A d ap ti ve c ap ac it y Very low Low Moderate High Very high Very low Moderate Moderate High Very high Very high Low Low Moderate Moderate High Very high Moderate Low Moderate Moderate High Very high High Low Low Moderate Moderate High Very high Very low Low Low Moderate High 3. CONCLUSION AND RECOMMENDATION Vulnerability (V) was defined as a function of impacts (I) and adaptation (A) as V = f (I, A). Vulnerability, in particular, was seen as a dependent variable which was affected by the independent variables i.e. impacts (I) and adaptation (A). Additionally, V would not be only affected by I and A in the past and present, but also would be impacted by potential impacts (e.g. economic, social and environment potential impacts) and adaptation in the future. REFERENCES Chinvanno, S. (2007). 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