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1 Problem-solving diagram for the construction of a framework to assess vulnerability to climate change impacts on agriculture production.
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Agriculture production is one of the most vulnerable sectors to climate change in Vietnam. Therefore, assessing levels of climate change vulnerabilities on agriculture production is extremely necessary. Vulnerability assessment using an index method has been broadly applied throughout the world. However, this method is a preliminary step and is com...
Contexts in source publication
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... on the vulnerability concept given by the IPCC, and diverse literature throughout Vietnam and all over the world, a vulnerability assessment framework that comprises an actual field situation is presented in Fig. ...
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... on the questions on crop production we constructed a cropping calendar consisting of the main crops and their labor activities (Fig. 4.1). The most important crops observed were irrigated rice (one and two cycles) on paddy and terrace land; upland rice, maize, peanuts, cassava, soybeans, sweet potatoes, and ginger on sloping land; and tea, cardamom, and cinnamon on perennial land. ...
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... communities including Pac Ngoi Hamlet in terms of ES. The quality of forests in Duong Hamlet strongly impacts the quality and quantity of water in Nam Mau Commune and Ba Be Lake. In 2013, 550 ha of Duong Hamlet was occupied by forests, which includes 180 ha of protection forest, 350 ha of production forest, and 20 ha of rehabilitation forest ( Fig. ...
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... the study villages, poor and food-poor (hungry) households constitute a major part of the population (54.54%), of which 13.13% are food-poor and 41.41% are poor (see Fig. 8.1). These rates vary significantly across the sites. In Pieng Pho Village, 6% of the local households are food-poor and 26% are poor, while in Binh Son 1, these figures are 17% and 50%, respectively. Table 8.2 presents income and expenditures by group in the study sites. Generally, the income per head in Pieng Pho Village was higher than ...
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... study was conducted in Tat Hamlet of Tan Minh Village, Da Bac District, Hoa Binh Province in Vietnam's northwestern mountains (latitude 20°N and longitude 105°E; Fig. 9.1). This hamlet is inhabited by the Da Bac Tay ethnic minority group who have practiced composite swiddening for at least a century ...
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... projects achieve impacts and what impacts they achieve. As stated above, this study utilized the sustainable livelihoods framework as a lens to identify four key groups of impact assessment indicators for AR4D projects: direct research outputs, livelihood impacts, institutional impacts, and impacts in the vulnerability context. The diagram in Fig. 10.1 shows the four key groups of impact assessment indicators, and Table 10.2 presents a detailed description of these groups. Depending on the research objectives, the specific social context of the research locations, and the length of time in which the assessment takes place after a project is completed, the impact assessment set out in ...
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... the findings and facilitate the use of the research outputs on a large scale. The findings can also be reported to funding and implementation agencies, and can be shared among research partners and development agencies through publications, media, and other electronic means for better implementation and assessment of future AR4D interventions ( Fig. ...
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... Each commune had distinct characteristics of participation in conservation initiatives, biophysical condition, and varied preference for agricultural cultivation. Each of these communes has also been engaged in a series of Integrated Conservation and Development Projects (ICDPs) to support local people's livelihoods and biodiversity conservation. Fig. 11.1 shows the location of the research ...
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... formed, consisting of Viet Hai Hamlet and Tra Bau Hamlet. By the end of 1959, the population of the commune was 28 households, all of them Kinh people. In 1965, the population of the Viet Hai Commune rose significantly to 57 households due to a government resettlement program that aimed to reduce the stress of overcrowding on agricultural land ( Fig. 11.2). Gia Luan Commune had a total population of 50 households in the 1960s, and this commune was not divided into hamlets. In 1948, when Gia Luan was first established, there were 12 Chinese households and only 2 Vietnamese households in the ...
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... reduced from 57 to 35 households due to the commune's location being isolated from other parts of the island. In contrast, the population of Gia Luan Commune increased significantly from 50 to 100 households over the same period due to increasing population, resulting in division of households. However, the commune did not divide into hamlets ( Fig. ...
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... study was conducted in three forest-independent communities of Kho Mu and Thai ethnic community living in Nghe An and Son La provinces (Fig. 12.1). These are the leading provinces in implementing the decentralizing FLA in Vietnam. The selected hamlets include Na Be, Xieng Huong, and Huoi Toi hamlets. ...
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... of Khomu people got worse after the implementation of the Decrees 02/cP and 163/ND-cP: more swidden area appeared and the natural forest area shrank. The forest cover changes of the three hamlets-Xieng Huong, Na Be, and Huoi Toi-before and after the implementation of the decentralization policies, are shown in the following participatory maps (Figs. ...
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... one of the world's biosphere reserves. The biosphere is considered as one of Vietnam's most favored and beautiful places, has not only become a preferred destination for tourists from all parts of Vietnam but also attracts tourists from around the world. The number of tourists visiting Cat Ba Island has dramatically increased over the last decade (Fig. 14.1) resulting in the tourism sector making a significant contribution to the local economy (Cat hai People's Committee, 2005). however, there are a number of challenges that pose a significant threat to the development of sustainable tourism in the biosphere ...
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... were conducted on Cat Ba Island with the local communities, business operators, and local authorities. Discussion and consultation with stakeholders revealed a number of issues that are potential threats to sustainable tourism development on the island, such as a shortage of natural resources, chronic poverty, and environmental degradation. Fig. 14.2 depicts a general picture of tourism development on Cat Ba Island. These graphs show that the island is experiencing strong growth in tourism, while environmental degradation is declining and poverty levels persist. This indicates that achieving a sustainable tourism system on the island is still far from becoming a reality. The next ...
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... First, a preliminary CLD was developed by the research team based on prior knowledge of tourism development on Cat Ba Island. Second, a working CLD was then constructed based on the preliminary CLD and consulting with individual stakeholders. Finally, we organized a joint stakeholder workshop to review the working CLD to produce a final CLD (Fig. 14.3). ...
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... R1 links the variables: number of tourists, investment, infrastructure and facilities, and attractiveness of Cat Ba Island (Fig. 14.4). This simple reinforcing loop portrays the drivers behind the exponential tourism growth on the island during the last few ...
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... R2 and R3 (Fig. 14.5) describe the effects that tourist numbers are having on the increasing need for infrastructure and facilities and subsequently the increase in employment opportunities for the local people (ie, construction of hotels, various tourism-related activities, small businesses, and home stays). This could clearly contribute to poverty ...
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... are two important balancing loops highlighted in Fig. 14.6 that explain the longterm effects of tourism development on the environment and attractiveness of the island as It is clear that the increased number of facilities lead to increasing amounts of waste (solid and liquid) generated by hotels and restaurants. These are discharged into the environment. In addition, the increased number of ...
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... B3 and B4 are highlighted in Fig. 14.7. Loop B3 indicates the number of tourists, social issues, and attractiveness of Cat Ba Island, while B4 shows that an increase in the number of tourists and infrastructure and facilities influences employment opportunities, which in turn will increase temporary immigration that could lead to negative social issues. This could be ...
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... B5 depicts how the number of tourists, the island's population, and immigration to the island are interlinked with fresh water consumption and availability of underground water ( Fig. 14.8). Loop B6 describes how the number of tourists affects infrastructure and facilities, which in turn puts a demand on available land for tourism to the detriment of the natural beauty of the island and its attractiveness to tourists. These loops describe the effects of scarce resources (particularly land and fresh water) on tourism ...
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... could be expected that the effects of the balancing loops demonstrated in Fig. 14.6 will finally reduce the attractiveness of Cat Ba Island, which could lead to a decline in the number of tourists to the island. In other words, loops B5 and B6 also control tourism ...
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... B7 and B8 (Fig. 14.9) describe the effects of tourism development on the social demography and environmental attractiveness of the island. As the number of tourists primarily affects the availability of underground water, increasing tourist numbers would lead to less water being available for ...
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... summary, the conceptual model or CLD of the tourism system on Cat Ba Island (Fig. 14.3) provides a fair idea of the integration of the mental models that are shared and discussed by the relevant stakeholders. The model was able to present the systems in their entirety, visualizing and capturing the most important factors (drivers and inhibitors) and feedback mechanisms (reinforcing and balancing loops) that constitute, ...
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... most obvious archetype seen in the tourism conceptual model is limited to growth (Fig. 14.10). This archetype represents situations where improvements in performance or growth are limited and cannot go on forever. The lesson learned from this archetype is that some element always pushes the system back; thus, if we do not plan for limits, we are planning for failure (Senge, 2006). To anticipate future problems and eliminate ...
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... and poor service quality. These constraints are a significant threat to the sustainability of tourism on the island. In other words, tourism development must be controlled and sensitive to the limits of Cat Ba Island's natural resources, particularly freshwater and land. Another archetype that is within the conceptual model is "fixes that fail" (Fig. 14.11). This archetype represents situations where the managerial response to a problem is a quick fix. This fix works in the short term (balancing effect); however, it has unintended and often harmful consequences that exacerbate the original problem (reinforcing effect) and the system is reverted to its original or a worse condition after ...
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... SFM of tourism system on Cat Ba Island developed based on its conceptual model. Note that not all feedback loops in the conceptual model simulated because we did not have enough information on all feedback loops. Fig. 14.12 shows the systems map of main sectors and loops included in the SFM. The arrows indicate connections (material and information linkages) between the sectors. Details of SFM for each sector is seen in ...
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... relative performance of the five development scenarios (Fig. 14.13), along with the radar chart polygon area and symmetry (Table 14.3) indicate that scenarios 1 (base case) and 5 (worst case) were the worst performing overall. Scenario 3, while not the most symmetrical ...
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... 2 and 4 have similar polygon areas and symmetries; however, scenario 2 has a slightly larger polygon area, indicating better overall performance compared to scenario 4. Surprising, scenario 2 (best case) was not the best performing scenario overall. To assist policy makers and tourism managers see the consequence of their decisions and actions, Fig. 14.14 provides a managerial-friendly interface with the computer model or control panel that allows them to conduct policy experiments. One of the features of the control panel is "sliders," such as boxes identified as "cap on Cat Ba town population"; "cap on tourism numbers"; "solid waste treated"; and "wastewater treated." These sliders ...
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Citations
... There are two broad approaches to vulnerability calculations which empirically refer to conventional and indicatorbased methods [11]. In this study, we aggregate the exposure, resilience and capacity indicators following [43] and [44]. First, normalization was performed for the purpose of rescaling the indicators using min-max Eq. (1) and Eq. ...
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... This logic was adopted in the present study. Therefore, the normalized data were assumed to have equal importance, so the vulnerability was calculated using the following method (Duong et al 2017). ...
this assessment aims to assess the vulnerability of the forestry and
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... Assessment of vulnerability to climate change following IPCC's definition has been considered as a common integrated approach, which consists of both biophysical and social vulnerability (Adger, 2006;Deressa et al., 2008). Thus, a significant number of recent studies have used IPCC's definition of vulnerability to assess the susceptibility of a country, a region or a community to climate change (Duong et al., 2017;Fernandez et al., 2015;Gebreegziabher et al., 2016;Nguyen & Woodroffe, 2016;Nguyen et al., 2017). Accordingly, sub-components and/or variables under the three components of sensitivity, exposure and adaptive capacity are identified to evaluate the vulnerability to climate change depending on the study objectives and local contextual circumstances. ...
... Data used in calculating the vulnerability index come from either primary source such as Hahn et al. (2009), Shah et al. (2013, Nguyen et al. (2017), Huong et al. (2018, Pham et al. (2020), Tran et al. (2020) or from secondary source such as Fernandez et al. (2015), Nguyen and Woodroffe (2016) and Duong et al. (2017). In addition, the vulnerability index has been measured in different ways. ...
... In addition, the vulnerability index has been measured in different ways. For instance, specific formulas are used by Hahn et al. (2009), Gebreegziabher et al. (2016, Duong et al. (2017) and Nguyen et al. (2017). However, in the studies by Fernandez et al. (2015) and Nguyen and Woodroffe (2016) the vulnerability index is scored by the overall mean of the main components. ...
This study investigates the livelihood vulnerability to climate change of farm households in Northeast Vietnam. Data for the study is based on a survey with 534 farm households in the study site. The livelihood vulnerability index was used to measure the household vulnerability to natural hazards and climate variability. The results show that the livelihood of farm households in the study site is moderately vulnerable to natural hazards and climate variability. However, livelihood strategies, health and food are more susceptible than social networks, water, housing, land tenure and assets; while the socio-demographic profile is least vulnerable. The result suggests that to sustain the livelihood and improve the adaptive capacity of farm households to respond to climate change impacts, specific interventions for each component of the livelihood should be planned and applied.
... Assessment of vulnerability to climate change following IPCC's definition has been considered as a common integrated approach, which consists of both biophysical and social vulnerability (Adger, 2006;Deressa et al., 2008). Thus, a significant number of recent studies have used IPCC's definition of vulnerability to assess the susceptibility of a country, a region or a community to climate change (Duong et al., 2017;Fernandez et al., 2015;Gebreegziabher et al., 2016;Nguyen & Woodroffe, 2016;Nguyen et al., 2017). Accordingly, sub-components and/or variables under the three components of sensitivity, exposure and adaptive capacity are identified to evaluate the vulnerability to climate change depending on the study objectives and local contextual circumstances. ...
... Data used in calculating the vulnerability index come from either primary source such as Hahn et al. (2009), Shah et al. (2013, Nguyen et al. (2017), Huong et al. (2018, Pham et al. (2020), Tran et al. (2020) or from secondary source such as Fernandez et al. (2015), Nguyen and Woodroffe (2016) and Duong et al. (2017). In addition, the vulnerability index has been measured in different ways. ...
... In addition, the vulnerability index has been measured in different ways. For instance, specific formulas are used by Hahn et al. (2009), Gebreegziabher et al. (2016, Duong et al. (2017) and Nguyen et al. (2017). However, in the studies by Fernandez et al. (2015) and Nguyen and Woodroffe (2016) the vulnerability index is scored by the overall mean of the main components. ...
This study investigates the livelihood vulnerability to climate change of farm households in Northeast Vietnam. Data for the study is based on a survey with 534 farm households in the study site. The livelihood vulnerability index was used to measure the household vulnerability to natural hazards and climate variability. The results show that the livelihood of farm households in the study site is moderately vulnerable to natural hazards and climate variability. However, livelihood strategies, health and food are more susceptible than social networks, water, housing, land tenure and assets; while the socio-demographic profile is least vulnerable. The result suggests that to sustain the livelihood and improve the adaptive capacity of farm households to respond to climate change impacts, specific interventions for each component of the livelihood should be planned and applied.
... The calculation of the weights using this technique ensures that considerable variation in any one of the indices would not unduly govern the rest of the indicators' contribution and distort inter-regional comparisons. The vulnerability index calculated using this technique lies between zero and one, with one value indicating maximum vulnerability and zero value indicating no vulnerability (Iyengar & Sudarshan 1982;Duong et al. 2017). ...
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Multivariate Integrated Drought Monitoring Index (MIDMI) – a remote sensing-based index to measure the vulnerability of agricultural drought.;
Various drought indices were compared using unsupervised classification and percentage area calculation under each drought category.;
MIDMI is computed using the Landsat-8 satellite data by assigning unequal weights to five drought indices as per the Iyengar and Sudarshan method.;
... If too many factors are involved in the operation, not all the data could be obtained and modeled. However, a larger number of indicator variables would improve the accuracy of the calculation [36]. Most variables in this research were derived directly from census data and available data. ...
... The second phase was the construction of an EVI that was developed through multivariate statistical analysis. The Iyengar and Sudarshan methods were applied to normalize and calculate the weight of each variable in this study, in accordance with the availability and feasibility of the required input data, and the conditions of the study area [36,46]. All multivariate datasets were standardized with the normalization process, using linear min-max in Eq. (1). ...
This research was conducted with a view to updating the management of earthquakes through an exposure vulnerability and potential seismic risk assessment, along with its application in Sabah (a state in East Malaysia). A set of indicators and methodologies has been proposed in this study with the goal of evaluating the level of exposure vulnerability and potential risk of certain locations to earthquake events at the local district scale. This study specifically involves the development of exposure vulnerability indicators; the statistical analysis method to standardize multivariate data together with a weight calculation of indicator variables; and a mathematical combination of different indicators for the development of the index map using the spatial analysis function of Geographical Information System (GIS) tools. Then, the derived exposure vulnerability index (EVI) map is overlaid with the seismic hazard in determining the geographical location of the most vulnerable areas and their exposure to seismic hazard events. As a result, and based on the available data, the exposure vulnerability index map shows that most districts in Sabah are at relatively low and moderate levels of risk except for a few districts, with several major cities in Sabah, such as Kota Kinabalu, Penampang, Sandakan and Tawau municipality, being situated at a high or very high exposure index. The combination of EVI maps and hazard maps indicate the dominance of the two factors influencing the potential level of earthquake risk. Studies reveal most of the southwest and central parts of the region are not at risk, as both exposure and hazard factors are at a low level. The proposed approach depicts an instrument for identifying cost-effective risk reduction initiatives by providing a scientific method for regional risk planning and management strategies. This research represents the first attempt to evaluate Sabah’s vulnerability to this type of natural disaster by understanding the spatial relationship between exposure vulnerability and earthquake hazard, which undoubtedly could be improved in several aspects.
... The data source obtained in this study was in the multivariate form, resulting in the normalization process performed to standardize the dataset to a standard range (0 to 1) (UNDP 2018). This was carried out by using the linear min-max equation (Iyengar and Sudarshan 1982;Duong et al. 2016). Apart from the lack of standard ways of assigning weight to each indicator, the methods prescribed by Iyengar and Sudarshan (unequal weighting schemes) were deployed as the initial attempt to calculate the weighting values for the respective seismic vulnerability indicators in this study. ...
Various techniques and frameworks for an evaluation of seismic vulnerability have been developed and established in previous studies. However, some techniques demand a significant amount of empirical data currently not readily available in developing countries. Therefore, this study proposes a new seismic risk evaluation method at the local district level. A holistic model was constructed for the purpose of assessing potential seismic vulnerability based on appropriate indices and their relative contribution towards vulnerability and coping capacity. It allowed the estimation of vulnerability in terms of exposure, resilience, and capacity factors. Then, utilization of Geographical Information System (GIS) tools resulted in the generation of a total vulnerability map via integration of the study variables to highlight the socio-economic and physical characteristics of vulnerability for the districts in Pahang, Malaysia. Subsequently, a seismic risk map of the study area was derived by overlying the derived map with the seismic hazard map. Consequently, the study revealed the highest levels of seismic risk were concentrated in the central-west of the Pahang region, namely the Bentong district. In contrast, the least vulnerable areas encompassed the Pekan and Jerantut areas, which were located in the eastern region. In brief, the study findings would serve as the foundation towards reducing the country’s vulnerability to disasters.
... This research has been carried out in accordance to Iyengar and Sudarshan's approach, which essentially is a multivariate data analysis method in normalizing and calculating the weighting for selected indicators excluding the seismic hazard component. The standardization of the multi-source data was performed through the following normalization Eq. (1) [33,34]. The normalized values fall between 0 and 1 [35]. ...
Devastating effects of natural disasters dynamically depends on the vulnerability components
of a specific area. Therefore, assessing vulnerability is necessary to estimate the earthquake
risk. This paper argues for a multidisciplinary method that integrates social vulnerability into
the seismic risk analysis in Pahang. The methodology specifically relies on; (1) the
development on a set of social indicators using multivariate data analysis to identify and
evaluate the local characteristics that contribute to the vulnerability and risk of inhabitants of
district space; and (2) the application of Geographical Information System (GIS) technology
for generating and mapping the spatial pattern of social vulnerability index for seismic hazard
in Pahang, Malaysia that was based on the classification of its exposure level. The classes of
a social vulnerability index map were overlaid with a seismic hazard map that was proposed
by JMG (Mineral and Geoscience Department Malaysia) through the use of map algebra
functions in GIS tools. Results for social vulnerability map showed that, majority of the study
area are in relatively low to moderate level except for Kuantan district, which is highly
vulnerable. Meanwhile, the combination of the social vulnerability map and seismic hazard
map reveals that, districts in the central parts of the region are the most highly exposed to
earthquake threats, whereas in the eastern part it demonstrates the low level of exposure to
seismic hazard (with the exception for the Kuantan district, where it is highly vulnerable). The
proposed method provides useful information on the spatial variability of exposure
vulnerability to seismic hazard that could enhance the earthquake preparedness and mitigation.
... Next is the collection of input data for those indicators by a variety of sources such as field survey, statistical data and remote sensing datasets. The third step is normalization of input datasets via the formula involving the UNDP's Human Development Index (HDI) (Duong et al., 2017;McNicoll, 2007). ...
... The new water vulnerability assessment framework is built based on the general vulnerability assessment of IPCC, while the quantitative vulnerability assessment is devised by applying the index calculation method, normalization method, and weight evaluation method devised by Iyengar and Sudanrshan (Duong et al., 2017). The availability and accurately of input data for identified indicators is an integral part of this framework. ...
Water deficiency due to climate change and the world's population growth increases the demand for the water industry to carry out vulnerability assessments. Although many studies have been done on climate change vulnerability assessment, a specific framework with sufficient indicators for water vulnerability assessment is still lacking. This highlights the urgent need to devise an effective model framework in order to provide water managers and authorities with the level of water exposure, sensitivity, adaptive capacity and water vulnerability to formulate their responses in implementing water management strategies. The present study proposes a new approach for water quantity vulnerability assessment based on remote sensing satellite data and GIS ModelBuilder. The developed approach has three layers: (1) data acquisition mainly from remote sensing datasets and statistical sources; (2) calculation layer based on the integration of GIS-based model and the Intergovernmental Panel on Climate Change's vulnerability assessment framework; and (3) output layer including the indices of exposure, sensitivity, adaptive capacity and water vulnerability and spatial distribution of remote sensing indicators and these indices in provincial and regional scale. In total 27 indicators were incorporated for the case study in Vietnam based on their availability and reliability. Results show that the most water vulnerable is the South Central Coast of the country, followed by the Northwest area. The novel approach is based on reliable and updated spatial-temporal datasets (soil water stress, aridity index, water use efficiency, rain use efficiency and leaf area index), and the incorporation of the GIS-based model. This framework can then be applied effectively for water vulnerability assessment of other regions and countries.
... It considered the indigenous setting (e.g., traditional agricultural practices) and social concerns (e.g., older farmers) which have estimated the current vulnerability of the rice terraces to climate change impacts. With normalization and aggregation of the indicators, the Hay and Mimura (2006); Priceputu and Greppin (2006); and Duong et al. (2017) Incidence of drought Hay and Mimura (2006); Alcamo et al. (2007); Acosta-Michlik and Espaldon (2008); Madu (2012); and Duong et al. (2017); Annual mean temperature Hay and Mimura (2006); Priceputu and Greppin (2006) Hay and Mimura (2006); and Madu (2012) vulnerability of the rice terraces was computed. Lastly, strategies were proposed based on the identified key vulnerability indices. ...
... It considered the indigenous setting (e.g., traditional agricultural practices) and social concerns (e.g., older farmers) which have estimated the current vulnerability of the rice terraces to climate change impacts. With normalization and aggregation of the indicators, the Hay and Mimura (2006); Priceputu and Greppin (2006); and Duong et al. (2017) Incidence of drought Hay and Mimura (2006); Alcamo et al. (2007); Acosta-Michlik and Espaldon (2008); Madu (2012); and Duong et al. (2017); Annual mean temperature Hay and Mimura (2006); Priceputu and Greppin (2006) Hay and Mimura (2006); and Madu (2012) vulnerability of the rice terraces was computed. Lastly, strategies were proposed based on the identified key vulnerability indices. ...
... Weights influence the totality of composite indicators where the contribution of each indicator is reflected against the composite. Most vulnerability studies did not assign weights for each component especially differential weights (Duong et al. 2017). Indicators do not have equal influence on the component so there are several techniques used to weigh the indicators. ...
The pressing issue of climate change poses a serious threat to agriculture specifically to rice production and its impacts could be devastating since rice is a staple food and serves as a subsistence agriculture in Ifugao, Philippines. However, little is known on the impacts of climate change at the rice terraces; hence, vulnerability assessment to climate change impacts of the Batad Rice Terraces, a UNESCO Inscribed World Heritage Site and one of the Globally Important Agricultural Heritage Systems in the Philippines, was conducted. Reviewed, adopted, and modified indices were used as deemed fit to the area to assess the vulnerability as a function of exposure, sensitivity, and adaptive capacity. The data were gathered through literature review, actual measurements, key informant interview, and household interview in 2017. Results revealed that sensitivity indicators contribute to the vulnerability of the rice terraces to climate change impacts. Overall, socially and culturally appropriate adaptation strategies should be critical considerations to decrease the vulnerability of the system.
