Adaptive Capacity Index Research Articles

A framework to assess the contextual composite heat vulnerability index for a heritage city in India- A case study of Madurai

In developing cities, rapid urbanization and climate change leads to drought and urban heat island effects which affects the energy consumption, economy and the environment. Extreme temperature rise has amplified the stress on vulnerable groups and has reduced livability. The sustainability of a city lies in the adaptability of the city to the climatic stresses. The role of adaptability is guided by the contextual vulnerability assessment of the city. This paper intends to assess the contextual vulnerability of Madurai, an ancient city with high social and cultural value. Composite heat vulnerability index (CHVI), a function of exposure, sensitivity and adaptive capacity of the context has been construed by many as the quantitative representation of the vulnerability of a place to high temperature. This paper focuses on the development of a framework to assess the CHVI considering the contextual socio-cultural indicators like social capital and cultural value along with components of meteorological, geophysical, biophysical, fragility, socially-marginalised, and development quotient .The research methodology identifies suitable context specific indicators, computes and maps exposure, sensitivity and adaptive capacity indices, spatially maps the categorised vulnerable zones and identifies the critical indicators that contribute to vulnerability. The framework can support decision-making to enable socially resilient cities.

Assessing Flood Vulnerability from Rapid Urban Growth: A Case of Central Java — Indonesia

Urban growth, in many Asian cities, may lead to increased exposure to flood and growing sensitivity mainly because of the presence of informal settlements. On the other hand, urban areas may offer better access to public facilities, improving adaptive capacity and enhancing the local government’s capabilities. This study aims to investigate to what extent urban growth exacerbates flood vulnerability in Central Java. Concurrently, floods are the most frequent disaster in the area. The approach used in the vulnerability assessment involves socioeconomic conditions (population density, the number of impoverished families, public facilities) associated with three main aspects (exposure, sensitivity, and adaptive capacity), resulting in the Exposure and Sensitivity Index and the Adaptive Capacity Index. Scoring and weighting analysis using secondary data in a sub-district unit from the Central Bureau of Statistics are applied. The result shows that urban growth contributes to the escalation of hazards and vulnerability. On the other hand, a high population also increases the number of public facilities and affects adaptive capacity in certain areas. Indeed, strategic urban development policies are critical to manage the three elements that form the flood vulnerability.

Improving Adaptive Capacity of Riverine Communities in Responding to Floods in Beledweyne District, Somalia

This study aimed at improving the adaptive capacity of riverine communities in responding to floods in Beledweyne district, Somalia. The objectives of the study were to examine the factors that determine flood vulnerability of riverine communities in responding to floods in Beledweyne District, Somalia, to assess the indicators of adaptive capacity of riverine communities in responding to floods in Beledweyne District, Somalia and to evaluate the adopted strategies for improving adaptive capacities to flood hazards by riverine communities of Beledweyne District, Somalia. The study employed quantitative research approach using descriptive research design to analyse the adaptive capacity of riverine communities in responding to floods in Beledweyne District, Somalia. The research used data collection tools like questionnaire, interview and documentary review to collect the data. The main findings of the study were that there are many factors determining flood vulnerability of riverine communities in responding to floods in Beledweyne District, Somalia like staying very close to the river increases community members’ vulnerability to floods in the areas, staying near the estuary to flood, staying near the high-water mark, staying near the river defense walls, staying near the basin bridge with poor condition and many others. Secondly, the findings of the study indicate that there are indicators of adaptive capacity of riverine communities in responding to floods in Beledweyne District, Somalia which they encompass: low level of emergency and preparedness plan and resources, low level of emergency and preparedness plan and resources, low improvement of livelihoods and rural economy in the flood prone areas and low improvement of livelihoods and rural economy in the flood prone areas. Furthermore, the findings of the study indicate that the recommend strategies for improving adaptive capacities to flood hazards by riverine communities of Beledweyne District, Somalia entail: continuous assessment of the sector and infrastructure vulnerability in the riverine communities, executing early actions to increase economic resilience in livelihoods, assessment of the critical infrastructure (roads, bridges, utilities, prevention of ad hoc basin defenses, favor non-structural solutions and preparation and implementation of effective early warning messages that reach marginalized groups of people. The study recommends that there should be preparation of medium-term development and spatial plans, there should be proper preparation of medium-term development and spatial plans in Beledweyne district, preparation of proper local plans and the district authority or leaders in collaboration with the national leaders should prepare proper local plans for riverine communities.

Assessment of multidimensional drought vulnerability using exposure, sensitivity, and adaptive capacity components.

This study provides a method for analyzing the drought-vulnerability index (DVI) from a multidimensional perspective that includes biophysical and social aspects, considering the Intergovernmental Panel on Climate Change's (IPCC) assessment. The proposed method generates the "exposure index (EI)", "sensitivity index (SI)", and "adaptive capacity index (ACI)" components of the proposed DVI using nine sub-indicators and 29 proxy variables. By using it throughout all of Turkey's provinces, the performance of the developed index was evaluated. In this study, the decision matrices were built utilizing expert knowledge, and the weights of the indicators and variables were obtained by using the Analytical Hierarchy Process (AHP) technique. Moreover, the values of these four indices were classified as "very high, high, moderate, low, and very low," and their geographical distribution across the country was drawn, as well as relevant patterns retrieved. The study's major results show that 17 of the 81 provinces are classified as "very high," 16 as "high," 15 as "moderate," 17 as "low," and the remaining 16 as "very low" drought vulnerable. Another significant result is that the majority of people in the country's south, center, and southeast rely on agriculture and are thus more vulnerable to drought due to socioeconomic underdevelopment in those regions.

Assessing Social Vulnerability to Climate Change in a Fishery-Dependent Village in South Central Vietnam

Fishery-dependent communities are highly susceptible to the impacts of climate change due to their proximity to vulnerable coastal areas and reliance on ecosystem services for their livelihoods. The study assessed the effects of climate change on the socioeconomic livelihoods and adaptive capacity of Xuan Tu, a community located in South Central Vietnam. The assessment employed the social vulnerability index (SVI) and adaptive capacity index (ACI). A hybrid data collection approach was utilized to gather information from households, and a composite method was employed to aggregate the data, enabling an assessment of community vulnerability. The findings indicated exposure, sensitivity, and adaptive capacity index values of 0.16, 0.34, and 0.26, respectively. The community exhibited a moderate vulnerability to climate change, with a social vulnerability index of 0.43. Notably, economic sufficiency, access to social groups, and level of education emerged as significant factors in reducing social vulnerability. To adapt to climate change, the community modified their fish feeding practices, fish culture methods, increased technology usage, and diversified their sources of income. However, the study identified a lack of institutional support as a significant obstacle to the community's autonomous adaptation. Based on these results, the study recommends livelihood diversification and the implementation of planned adaptation strategies to enhance preparedness for climate emergencies in South Central Vietnam.

A new index assessing adaptive capacity across Africa

The recent Sixth Assessment Report of the IPCC posits that across Africa, temperatures will continue to rise in almost all regions, while precipitation will decline in North and Southern parts of Africa and increase in the Sahel and most of sub-Saharan Africa. Vulnerability to these stressors is expected to increase across Africa due mainly to declining adaptive capacities. There is therefore a need to develop novel ways of assessing and monitoring the adaptive capacity of populations and communities across regions and countries of Africa. This work, therefore, aims at developing and testing a new adaptive capacity index based on two key inversely related proxies of adaptive capacity which are literacy and poverty rates. The data for these proxies were collected for the period 1991–2021 from the Readiness Index Database on figshare, the World Bank Group and Macro Trends. The historical data were analysed using the newly developed adaptive capacity index. Regionally, the results show that North Africa and Southern Africa have the highest adaptive capacity indices while West Africa, Middle and East Africa have the lowest adaptive capacity indices. Nationally, Sao Tome and Principe and Seychelles record the highest adaptive capacity indices. Generally, the indices at the country level as well as at the regional level are within the low-range scale, depicting a generally low level of adaptive capacity when compared to other regions of the world. The index suggested here will serve as a tool for bench-marking adaptive capacity at various scales as it is easily applicable in various contexts.

Selection of highly adaptive source material of watermelon for selection for early ripening

In terms of watermelon selection, the issue of stability of obtaining high yields in the conditions of manifestation of abiotic stressors of the external environment is relevant. The purpose of this study was to select a highly adaptive source material of watermelon according to the duration of the growing season and its components for use in breeding for early ripening. 101 collection samples of watermelon from 9 countries of the world were analysed. The study was based on the following methods: general scientific, measurement and weight, calculation, statistical. The watermelon collection was divided into ripeness groups and the sample was ranked according to the “duration of the seedling-ripening period”. The study established the amplitude (Am) and range of variation (Lim) of the signs of the duration of the components of the growing season. Samples with the smallest individual interphase periods were selected for use in selection for early ripening. The study found Vi – general adaptive capacity (GAC), σ2 SACi – specific adaptive capacity (SAC), Sgi – genotype stability, bi – regression coefficient of genotype response to changing conditions (plasticity), SVGi – selection value of the watermelon collection genotype based on the “duration of the growing season period”. According to the general adaptive capacity, the samples with the shortest duration of the “seedling – ripening” period were selected – 19 samples (Vi =-11.72…-6.05). As the most stable genotypes according to the “duration of the growing season” characteristic, 32 collection samples with a low value of the specific adaptive capacity indicator were selected, 23 of which are early ripening. The high stability of the genotype (Sgi) according to the characteristic “duration of the seedling-ripening period” was determined in 31 collection samples, of which 24 were early ripening. Based on the results of determining the regression coefficient (ecological plasticity coefficient), according to the characteristic “duration of the growing season”, the collection samples of watermelon were divided into three groups – with low (bi =0.01-2.20), medium (bi =2.21-4.22), and high (bi =4.23-6.24) ecological plasticity. According to the selection value of the genotype according to the trait “duration of the seedling-ripening period”, 18 collection samples had high indicators (SVGi =110.22-119.92), which are valuable for use in selection work with watermelon as sources of the characteristic “early ripeness”

Gauging Heat Vulnerability in Southeast Florida: A Multimodal Approach Integrating Physical Exposure, Sensitivity, and Adaptive Capacity

Urbanization and warming climate suggest that health impacts from extreme heat will increase in cities, thus locating vulnerable populations is pivotal. However, heat vulnerability indices (HVI) overwhelmingly interpret one model that may be inaccurate or methodologically flawed without considering how results compare with other HVI. Accordingly, this analysis applied a multimodal approach incorporating underrepresented health and adaptability measures to analyze heat vulnerability more comprehensively and better identify vulnerable populations. The Southeast Florida HVI (SFHVI) blends twenty-four physical exposure, sensitivity, and adaptive capacity indicators using uncommon statistical weights removing overlap, then SFHVI scores were compared statistically and qualitatively with ten models utilizing alternative methods. Urban areas with degraded physical settings, socioeconomic conditions, health, and household resources were particularly vulnerable. Rural and agricultural areas were also vulnerable reflecting socioeconomic conditions, health, and community resources. Three alternative models produced vulnerability scores not statistically different than SFHVI. The other seven differed significantly despite geospatial consistency regarding the most at-risk areas. Since inaccurate HVI can mislead decisionmakers inhibiting mitigation, future studies should increasingly adopt multimodal approaches that enhance analysis comprehensiveness, illuminate methodological strengths and flaws, as well as reinforce conviction about susceptible populations.

Multiparameter flood hazard, socioeconomic vulnerability and flood risk assessment for densely populated coastal city

In the current study, flood risk assessment of densely populated coastal urban Surat City, on the bank of the lower Tapi River in India, was conducted by combining the hydrodynamic model-based flood hazard and often neglected socioeconomic vulnerability. A two-dimensional (2D) hydrodynamic (HD) model was developed using physically surveyed topographic data and the existing land use land cover (LULC) of the study area (5248 km2). The satisfactory performance of the developed model was ascertained by comparing the observed and simulated water levels/depths across the river and floodplain. The 2D HD model outputs with geographic information system (GIS) applications were further used to develop probabilistic multiparameter flood hazard maps for coastal urban city. During a 100-year return period flood (Peak discharge = 34,459 m3/s), 86.5% of Surat City and its outskirt area was submerged, with 37% under the high hazard category. The north and west zones are the worst affected areas in Surat City. The socioeconomic sensitivity and adaptive capacity indicators were selected at the city's lowest administrative (ward) level. The socioeconomic vulnerability was evaluated by employing the robust data envelopment analysis (DEA) technique. Fifty-five of 89 wards in Surat City, covering 60% of the area under the jurisdiction of the Municipal Corporation, are highly vulnerable. Finally, the flood risk assessment of the city was conducted using a bivariate technique describing the distinctive contribution of flood hazard and socioeconomic vulnerability to risk. The wards adjoining the river and creek are at high flood risk, with an equal contribution of hazard and vulnerability. The ward-level hazard, vulnerability, and risk assessment of the city will help local and disaster management authorities to priorities high risk areas while planning flood management and mitigation strategies.

Testing the reliability of adaptive capacity as a proxy for adaptive and transformative responses to climate change

The concept of adaptive capacity is increasingly being applied to understand and predict people’s ability to adapt to the emerging impacts of climate change. Despite its potential utility, the degree to which adaptive capacity is a reliable predictor of adaptation remains unclear; evidence for a causal relationship is insufficient and conflicting. To address this gap, we surveyed 231 reef tourism companies across eight countries in the Asia-Pacific that have been affected by severe climate disturbances between 2014 and 2019. We used a combination of descriptive and multivariate statistical approaches to explore the relationships between adaptive capacity, adaptive responses, and contextual conditions. Our findings indicate that a comprehensive operationalization of actor-specific adaptive capacity is not necessarily a reliable proxy for measuring potential adaptation to future climate change. The severity of impacts on individual operators was the major determinant of adaptive action. Adaptive action might therefore be adopted autonomously by the majority of microeconomic actors (when they are severely affected), irrespective of their a priori adaptive capacity. Adaptive capacity was, however, a reliable proxy for the likelihood that an operator would take transformative action as their primary response to a climate disturbance; several of our indicators of adaptive capacity had a meaningful effect size, in particular those within the adaptive capacity domain of social organization. Policies focused on improving coordination and collaboration between industry, research, and government actors might therefore be more effective than alternatives in promoting long-term transformation of social-ecological systems. Adaptation confidence and government effectiveness were barriers to transformative action, and we provide some potential explanations. Further empirical research is needed to evaluate the generality of our findings in different contexts over space and time.

Assessing health sector climate vulnerability in 226 local entities of South Korea based on principal component analysis

This study aims to construct composite indices for health sector climate vulnerability in 226 local entities of South Korea from 2011 to 2018 using principal component analysis methods. After calculating exposure, sensitivity, and adaptive capacity indices respectively, which comprises a function of vulnerability, the composite indices for climate vulnerability are drawn. GIS maps visualize each index to provide more intuitive information on year-by-year transition in the 226 local entities, as well as to identify the proper local conditions in responding to climate change in the health sector more effectively. The overall tendency from 2011 to 2018 in each local entity is quite consistent without remarkable transition. Therefore, this overcomes the limitation of using cross-sectional data when conducting a measurement study. Local entities in major cities and municipalities in South Korea appear to be low in vulnerability to climate change in the health sector thanks to their low sensitivity with less vulnerable population and high adaptive capacity with a good health infrastructure. Nevertheless, there are quite a few exceptional cases among the cities and municipalities observed. This demonstrates why climate vulnerability assessment should be implemented at the local context, rather than through a top-down manner, as such exceptional cases could be overlooked in top-down approaches. This study provides a policy contribution to both central and local governments to fill gaps in current adaptation plans. In addition, the established micro-level time-series dataset for PCA analysis can contribute to further research in the future.

The Regional Vulnerability Assessment Model of Heat Wave Considering Heat Wave Disaster Vulnerable Groups

This study developed regional vulnerability assessment model of heat wave considering heat wave disaster vulnerable groups. As indicators of the vulnerability assessment model, climate exposure, sensitivity, adaptive capacity indicators were considered. As detailed indicators in sensitive, the heat wave disaster vulnerable groups were considered (Model A). In addition, the model considering general disaster vulnerable groups (Model B) as indicators in sensitive were analyzed. AHP survey was conducted to measure the relative importance and ranking of the heat wave vulnerability assessment indicators. Results showed that the farmer and obesity were recognized as highly vulnerable among sensitive indicators in Model A and female, multicultural family, and foreigner were recognized as highly vulnerable in Model B based on AHP analysis. By comparing the relationship between the damage from heat wave and the results of the vulnerability assessment, Model A showed high explanatory power in case of heat wave deaths while Model B showed high explanatory power in case of heat wave victims.

Mapping Adaptive Capacity of Urban Residents: A Case Study of Rawalpindi, Pakistan

The study estimated the adaptive capacity ranking of urban union councils of Rawalpindi through composite index considering fifteen economic, social, and institutional indicators as drivers of adaptive capacity through a structured questionnaire. The required sample size was 385 households and questionnaires were distributed to the residents of thirty urban union councils at random. The results showed that union councils of MC Stadium Block B, Khayaban e Sir Syed (KSS) Sector III and New Katarian- I had adaptive capacity 709, 676, and 674 respectively. Lakhan union council was found to have the lowest adaptive capacity of 422. The difference between the lowest and the highest adaptive capacity is surprisingly high with the difference of 287. KSS Sector III had highest savings ratio as compared to other union councils. New Katarian-I was bestowed with institutional as well as non-institutional sources of loan. Lakhan was found to be weak in almost all indicators of adaptive capacity except availability of institutional and non-institutional sources of loan. Pakistan, with high mass urban population, needs to be well prepared for climate change risks as well as health hazards, therefore, new planned urban spaces are a dire need.

Socio-Economic Vulnerability and Adaptations of Fish Farmers to Climate Variability and Extreme Climate Events in Selected Parts of Kitui County, Kenya

Climate variability and extreme climate events is one of the many challenges faced by fish farmers. The present study was carried out to assess and compare the socio-economic vulnerability and adaptations of fish farmers to climate variability and extreme climate events in arid and semi-arid lands of Central and Eastern parts of Kitui County, Kenya. Both study sites were purposively selected and the descriptive research design adopted. A total of 60 fish farming households were randomly selected to form the sample size for the study. The socio-economic vulnerability analysis of the fish farmers was based on an index constructed from carefully selected indicators for adaptive capacity. Principal Component Analysis was used to give weights to the indicators. The overall adaptive capacity index results revealed that possession of various assets varied between the two study sites, implying a spatial difference in socio-economic vulnerability between the two study sites. Regarding adaptation, results revealed that the level of adoption of various adaptation strategies to climate variability and extreme climate events also differed significantly between the two study sites and was subject to the adaptive capacity of the fish farmer. Therefore, this study recommends that the socio-economic vulnerability profile of the fish farmers inform any adaptation actions to be taken on fish farmers in arid and semi-arid lands.

Inequality of Global Thermal Comfort Conditions Changes in a Warmer World

AbstractChanges in the thermal comfort condition of the living environment of human beings are one of the main concerns related to global warming. While previous studies largely focused on mean temperature and warm/cold extremes, changes in thermal comfort conditions (both comfort and discomfort conditions) have not been adequately revealed. Based on climate projections from the Coupled Model Intercomparison Project phase 6 (CMIP6), future thermal comfort conditions over global land using net effective temperature index that considers the aggregate effects of temperature, relative humidity, and wind on human thermal perception were investigated. The focus was on the projected changes in thermal comfort conditions in different regions based on gross domestic product per capita, an indicator of adaptive capacity. An inequitable impact of escalating global warming on thermal comfort conditions emerges: in high‐income regions (mostly distributed in cool mid‐high latitudes), a diminishing number of cold‐uncomfortable days and an increasing number of comfort days collectively would contribute to an improvement in thermal comfort conditions; however, in low‐income regions (mostly distributed in warmer low latitudes), thermal comfort conditions are expected to worsen as a result of a dramatic increase in the number of warm‐uncomfortable days that greatly exceeds the decrease in the number of cold‐uncomfortable days and a decrease in the number of comfortable days. Moreover, analysis accounting for population exposure suggests that the overall impact of future changes in thermal comfort conditions on the global population is negative. Therefore, prioritized support for climate mitigation and adaptation to developing nations is justified and urgently needed.

What influences the adaptive capacity of coastal critical infrastructure providers?

Maintaining critical infrastructure functionality in the face of climate change through adaptation is a pressing issue for organisations responsible for critical infrastructure – especially in coastal areas. It is equally pressing to ensure those organisations have the capacity to adapt. The Adaptive Capacity Wheel was used to understand perceptions of the adaptive capacity held by critical infrastructure providers who have assets in locations at risk to the impacts of coastal hazards in Australia and Aotearoa-New Zealand. The findings demonstrate that those in executive management positions perceive the level of adaptive capacity to be higher than those at lower organisational levels. This is problematic as those tasked with implementing adaptive actions generally sit below the executive level. Leadership was overwhelmingly recognised as the most important element of adaptive capacity and dependencies emerged between leadership and other indicators of adaptive capacity. This article provides valuable insights into how critical infrastructure providers in Australia and Aotearoa-New Zealand are equipped to adapt to climate change. The findings indicate that building adaptive capacity within these organisations will begin with looking at the capabilities of the leadership.

Climate change adaptation and adaptive capacities of dairy farmers: Evidence from village tank cascade systems in Sri Lanka

CONTEXTDairy farmers are affected by climate change (CC). To reduce the negative effects of CC, farmers need to take numerous adaptive measures. The ability to adapt is context-specific and there is a dearth of research on the adaptation and adaptive capacity (AC) of dairy farmers in village tank cascade systems (VTCS). OBJECTIVEThe study investigates dairy farmers' perception of CC, their AC, adaptation, and the social and institutional drivers of AC and adaptation in the two selected VTCS in Sri Lanka. The knowledge of this is vital in planning specific interventions to enhance the climate resilience of farmers. METHODSThe level of CC adaptation and AC was measured using the Activity-based Adaptation Index and Adaptive Capacity Index. Using an ordered logistic regression model, the determinants of the CC adaptation were examined. Social dimensions of AC are studied by comparing AC scores across social groups differentiated by income and gender. Data were collected from 200 dairy farmers in two VTCS in the Anuradhapura District, North Central Province of Sri Lanka, where dairy farming is predominantly practiced. Pre-tested structured questionnaires were used for data collection. RESULTS AND CONCLUSIONPasture shortage, reduction in milk yield, and growth retardation of animals are reported as perceived CC effects by a majority of dairy farmers. The adaptation strategies mostly implemented by dairy farmers are aimed at reducing the effects of CC on animal physiology. A lesser number of farmers implement adaptation strategies that address pasture shortages. Farmer's perception of CC, socioeconomic characteristics and resource endowment determine the level of adaptation, while the AC moderates the relationship between perception and response to CC. The institutional and social context in which dairy farmers operate differentiates the AC of farmers. Women and poorer farmers tend to have a lower AC. The difference in AC across these social groups is explained by access to resources. The study recommends interventions to address social gaps in AC and highlights the importance of strengthening and expanding extension services and rural credit facilities. SIGNIFICANCEGlobally, fewer studies have been conducted on the impacts of climate-related risks on dairy farming systems and adaptation in comparison with such risks and adaptation in crop farming. This study provides insights into resource-poor dairy farmers' responses to CC and potential solutions in using common resources in VTCS to reduce vulnerability to CC.

Real‐time irrigation diversion data delivery can benefit adaptive capacity in communal irrigation systems

AbstractThere is a need to support applied, community‐relevant hydrologic research within changing climate, population, and socioeconomic conditions to better inform water policy and management. We hypothesized that providing a rural agricultural community in a semiarid valley with the necessary monitoring tool to meet local water management needs would increase adaptive capacity within the context of long‐term drought. Through a community science approach, researchers installed a telemetry monitoring system at participating acequia irrigation diversions that remotely sent water data to a web interface every 15 min. Two surveys distributed before and after web interface access targeted seven adaptive capacity indicators. After the first season of improved data accessibility, the following adaptive capacity indicators significantly increased: information diversity, cognitive social capital, leadership, and proactivity. Rather than focusing on the water savings aspect of real‐time monitoring, this paper summarizes a novel water resources study that assessed the social impact of real‐time irrigation water delivery monitoring on adaptive capacity. This study suggests that bridging the gap between community need and hydrologic research through community science, sociologic analysis, and stakeholder engagement provides significant benefits for communities facing water management challenges, further supporting problem‐driven water resources research.

Integrated assessment of flood risk in Arial Khan floodplain of Bangladesh under changing climate and socioeconomic conditions

AbstractIn the assessment of flood risk, the future flood hazard due to climate change is often tied to the present socioeconomic conditions. This makes an implicit assumption that the drivers of risk, other than the hazard, remain constant with time. Therefore, such risk assessment does not provide a realistic outlook for devising plausible mitigation strategies and plans. In this study, flood risk was assessed from an integrated perspective by considering both physical hazard, and socioeconomic exposure and vulnerability—all changing with time. The flood hazard in the Arial Khan River floodplain in the southcentral Bangladesh was simulated with a two‐dimensional hydrodynamic model, and the exposure and vulnerability were projected using different statistical techniques. Principal component analysis was conducted to assign weights to the indicators of hazard, exposure, sensitivity, and adaptive capacity. The results show that the flood depth, duration, and extent would increase from the baseline to 2080s under regional concentration pathway (RCP) 2.6 and RCP 8.5 scenarios. The sensitivity and vulnerability would decrease, reflecting an improved adaptive capacity. The low‐risk areas could increase from 62% in the baseline to 85%–91% in 2080s depending on the RCPs. The approach followed can be applied elsewhere in developing countries, particularly in riverine floodplain settings.

Assessing the Dynamics of Agropastoral farmers’ Adaptive Capacity to Drought in Uganda’s Cattle Corridor

Adaptive capacity provides a pivotal role in resilience building for socio-ecological systems to overcome both natural and anthropogenic disturbances. Persistent droughts increasingly cause abrupt changes in communities’ ability to mobilize scarce resources, anticipate or respond to perceived or current effects over time. This paper examines the factors influencing agropastoral farmers’ adaptive capacity dynamics in the cattle corridor of Uganda, and quantify their relative contributions. Data analysed was derived from a household survey of 426 households randomly and purposively selected from the six districts in the cattle corridor. Agropastoral farmers' adaptive capacity was assessed using the Local Adaptive Capacity (LAC) framework and measured using Principal component Analysis (PCA). Multivariate probit regression model was used to reveal the significant factors influencing adaptive capacity. The study illustrates that farmers' adaptive capacity index was low and variable across the cattle corridor sub-regions, significant indicators were; innovations, asset base, knowledge, and information. Farmers' gender, level of education, land size, off-farm activities, and membership to savings and loan-based associations significantly changed adaptive capacity. This study enlightens stakeholders with better knowledge of adaptive capacity, its component indicators, and factors at the household level. It also provides methodological approaches for assessing adaptive capacity at local level to climate change hazards. The study recommends an integrated application of the knowledge on the underlying factors to help infer innovative approaches and avert the long-term/ expected effects of drought on the context under investigation.