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"Disaster Planning methods Vietnam."
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A workbook on planning for urban resilience in the face of disasters : adapting experiences from Vietnam's cities to other cities
This workbook is intended to help policy makers in developing countries plan for a safer future in urban areas in the face of natural disasters and the consequences of climate change. It is based on the experiences of three cities in Vietnam, Can Tho, Dong Hoi, and Hanoi, that worked with international and local experts under World Bank supervision to develop local resilience action plans (LRAPs) in 2009-10. An LRAP is a detailed planning document that reflects local concerns and priorities based on the experiences of the past and projections for the future. It is not a wish list of projects that may never be completed because they are too costly or lack political support. Rather, it should be a realistic document that describes and establishes priorities for specific steps that can be undertaken in the near term to adapt to both climate related and other hazards. Regardless of their size, location, political orientation, or technical capacity, other cities can learn from the experiences of these pilot cities to develop their own LRAPs. The purpose of this workbook is to adapt the initial experiences of Can Tho, Dong Hoi, and Hanoi to benefit the national government and other communities in Vietnam and beyond. Indeed, the process described in this workbook was later adopted in the cities of Iloilo, the Philippines; Ningbo, China; and Yogyakarta, Indonesia, and the concluding chapter of this workbook draws on some of the lessons learned in these cities. However, the workbook, while generalizable to other contexts, largely reflects the Vietnamese experience.
eBook
A novel ensemble modeling approach for the spatial prediction of tropical forest fire susceptibility using LogitBoost machine learning classifier and multi-source geospatial data
A reliable forest fire susceptibility map is a necessity for disaster management and a primary reference source in land use planning. We set out to evaluate the use of the LogitBoost ensemble-based decision tree (LEDT) machine learning method for forest fire susceptibility mapping through a comparative case study at the Lao Cai region of Vietnam. A thorough literature search would indicate the method has not previously been applied to forest fires. Support vector machine (SVM), random forest (RF), and Kernel logistic regression (KLR) were used as benchmarks in the comparative evaluation. A fire inventory database for the study area was constructed based on data of previous forest fire occurrences, and related conditioning factors were generated from a number of sources. Thereafter, forest fire probability indices were computed through each of the four modeling techniques, and performances were compared using the area under the curve (AUC), Kappa index, overall accuracy, specificity, sensitivity, positive predictive value (PPV), and negative predictive value (NPV). The LEDT model produced the best performance, both on the training and on validation datasets, demonstrating a 92% prediction capability. Its overall superiority over the benchmarking models suggests that it has the potential to be used as an efficient new tool for forest fire susceptibility mapping. Fire prevention is a critical concern for local forestry authorities in tropical Lao Cai region, and based on the evidence of our study, the method has a potential application in forestry conservation management.
Journal Article
Machine learning-based assessment of regional-scale variation of landslide susceptibility in central Vietnam
Recurrent landslide events triggered by typhoons and tropical storms over Vietnam pose a longstanding threat to the nation’s population and infrastructure. Changes in hydroclimatic conditions, especially the growing intensity and frequency of storms, have elevated landslide susceptibility in many parts of the country. This research examines the spatio-temporal variations in landslide susceptibility across central Vietnam over several years, using multi-temporal landslide inventories from Typhoon Ketsana (2009), Tropical Storm Podul (2013), and Typhoon Molave (2020). Additionally, the research explores the impact of individual landslide causative factors on the probabilistic occurrences of landslides. The post-event landslide susceptibility models of these three climate extreme events were developed using nine causative factors and a Random Forest machine learning algorithm. The results indicate a notable areal expansion of high to very high landslide susceptibility in the northern and eastern regions and a moderate reduction in the central and southern areas during the post-Molave period compared to the post-Ketsana period. These changes may be early indicators of increasing landslide susceptibility in response to changing hydro-climatic conditions. The research found that annual average rainfall and topographic elevation are the two most important variables influencing landslide prediction, showing a nonlinear relationship with landslide probability. The landslide susceptibility models achieved high Area Under the Receiver Operating Characteristic Curve (AUC) (>95%), accuracy (>89%), and sensitivity (>90%) scores, signifying the robustness of the models. Additionally, the uncertainty of the models was quantified and spatially mapped. This multi-temporal analysis of landslide susceptibility is crucial for understanding the regional susceptibility trends and identifying areas with increasing, decreasing, and consistently high susceptibility to landslides. These insights are invaluable for prioritizing mitigation and risk reduction strategies in landslide-prone regions and guiding appropriate land use planning.
Journal Article
Designing a Short Disaster Risk Reduction Course for Primary Schools: An Experimental Intervention and Comprehensive Evaluation in Hue City, Vietnam
Disaster risk reduction (DRR) education is considered increasingly necessary, particularly for children. DRR educational interventions aim to enhance knowledge and attitudes related to self-protective capacity. However, comparative studies on students in areas prone to different disasters and comprehensive criteria covering both knowledge and attitudes toward behavior remain limited. A short DRR course was developed for primary schools across three regions (mountainous, low-lying, and coastal) in Hue City, one of Vietnam’s most vulnerable areas to extreme weather events. This study aimed to comprehensively evaluate student performance by applying Bloom’s taxonomy and treatment-control pre-post-follow-up design with panel analysis methods. From December 2022 to September 2023, three surveys, involving 517 students each, were conducted in six schools (three schools received the course and surveys, while the other three only participated in surveys). The intervention revealed similarities and differences between the groups. The course positively impacted on some elements of knowledge and preparedness intentions in students from low-lying and mountainous regions (including ethnic minorities). Higher-grade students in the mountainous region showed improvement in intentions, but not in attitudes toward self-protection. No gender differences in intentions were found. Although limited overall improvements, the study’s various methods, approaches and continuous assessment can be applied globally to design, implement, and assess DRR education courses effectively.
Journal Article
Adverse shocks, household expenditure and child marriage: evidence from India and Vietnam
Child marriage is associated with negative outcomes in regard to education, health and economic empowerment in later life. While the consequences of child marriage have been studied extensively, there has been limited discussion on the drivers of child marriage. This paper examines the impact of adverse shocks on child marriage. We use a sample of 886 girls between 12 and 18 years of age from India and Vietnam involved in the Young Lives project. The potential endogeneity problem is addressed by using rainfall deviation as the instrument. We find that in Vietnam, where bride price payment is a common practice in the event of expenditure reduction resulting from adverse shocks, a household may consider marrying off their daughter as a possible coping strategy. In contrast, in India where dowry payments are common, shocks may reduce the probability of child marriage, possibly, because a girl’s family is unable to meet the dowry requirements. These findings are robust to alternative ways of measuring child marriage, expenditure and rainfall deviation. We recommend that policies designed to reduce child marriage are considered in the context of cultural and social norms.
Journal Article
Assessment of Tangible Direct Flood Damage Using a Spatial Analysis Approach under the Effects of Climate Change: Case Study in an Urban Watershed in Hanoi, Vietnam
Due to climate change, the frequency and intensity of Hydro-Meteorological disasters, such as floods, are increasing. Therefore, the main purpose of this work is to assess tangible future flood damage in the urban watershed of the To Lich River in Hanoi, Vietnam. An approach based on spatial analysis, which requires the integration of several types of data related to flood characteristics that include depth, in particular, land-use classes, property values, and damage rates, is applied for the analysis. To simulate the future scenarios of flooding, the effects of climate change and land-use changes are estimated for 2030. Additionally, two scenarios based on the implementation of flood control measures are analyzed to demonstrate the effect of adaptation strategies. The findings show that climate change combined with the expansion of built-up areas increases the vulnerability of urban areas to flooding and economic damage. The results also reveal that the impacts of climate change will increase the total damage from floods by 26%. However, appropriate flood mitigation will be helpful in reducing the impacts of losses from floods by approximately 8% with the restoration of lakes and by approximately 29% with the implementation of water-sensitive urban design (WSUD). This study will be useful in helping to identify and map flood-prone areas at local and regional scales, which can lead to the detection and prioritization of exposed areas for appropriate countermeasures in a timely manner. In addition, the quantification of flood damage can be an important indicator to enhance the awareness of local decision-makers on improving the efficiency of regional flood risk reduction strategies.
Journal Article
How do local communities adapt to climate changes along heavily damaged coasts? A Stakeholder Delphi study in Ky Anh (Central Vietnam)
The Central Vietnamese coast faces increasing impacts on the local livelihoods of coastal communities as a result of the increasing natural hazards which include tropical storms, heavy rains, and floods. A challenge for the local populations is improving their adaptation capacity to climate change hazards in a sustainable way. This study deals with the impacts of climate change-associated hazards and adaptation capacity in coastal communes of the Ky Anh district, Ha Tinh province along the coast in Central Vietnam. A combination of the Stakeholder Delphi technique and the DPSIR (drivers–pressures–states–impacts–responses) framework was used. Delphi questionnaires allowed assessing the consensus among the respondents of a stakeholder group. Twenty questions and 20 statements were listed reflecting the DPSIR components. Thirty-six panel members, which were randomly selected from four stakeholder groups which included local authorities, farmers, fishermen, and fish traders, were involved in a two-round Delphi process. The results show that, both agricultural and non-agricultural sectors are main drivers (D); migration, calamities, population growth, mineral mining, aquaculture processing, and agriculture are main pressures (P); changes in the frequency of extreme weather events, increasing intensity of storms, floods, and droughts indicate main states (S); changes in agricultural land use and productivity are main impacts (I); construction of and upgrading dykes and irrigation systems should be the principal responses (R) in the vision of the local stakeholders. The Kendall’s W value for the second round is 0.681, indicating a high degree of consensus among the panel members and confidence in the ranks. Overall, the study advocates developing sustainable ecosystems, an upgraded New Rural Planning, and renewable energy strategies as the main local adaptations to climate change hazards in this area.
Journal Article