Climate disaster resilience of the education sector in Thua Thien Hue Province, Central Vietnam

Recognizing the importance of building disaster resilience for education sector, this study aims to develop a methodology to measure the level of educational resilience to cope with natural disasters and is then applied in Central Vietnam. The assessment tool in this paper is developed through a combination of climate disaster resilience indexes and the 16 tasks of Hyogo framework for action designed for education sector. It looks at five dimensions namely physical conditions, human resources, institutional issues, external relationships, and natural conditions, with each dimension characterized by three parameters and five variables. Findings from this study provide important insights into enhancing resilience of the education system in Thua Thien Hue at the provincial, local, and school levels. By giving the overall resilience situation, it can help policy-makers and practitioners in developing an effective plan to increase the level of educational resilience. In addition, it provides the School Management Board with a means to assess the school??s resilience level and set out priorities that need to be focused on with regard to the improvement of school safety and disaster risk reduction education.     

Beta-�� distribution and its application to hydrologic events

The beta-κ distribution is a distinct case of the generalized beta distribution of the second kind. In previous studies, beta-p and beta-κ distributions have played important roles in representing extreme events, and thus, the present paper uses the beta-κ distribution. Further, this paper uses the method of moments and the method of L-moments to estimate the parameters from the beta-κ distribution, and to demonstrate the performance of the proposed model, the paper presents a simulation study using three estimation methods (including the maximum likelihood estimation method) and beta-κ and non beta-κ samples. In addition, this paper evaluates the performance of the beta-κ distribution by employing two widely used extreme value distributions (i.e., the GEV and Gumbel distributions) and two sets of actual data on extreme events.     

Surface complexation modeling for predicting solid phase arsenic concentrations in the sediments of the Mississippi River Valley alluvial aquifer, Arkansas, USA

The potential health impact of As in drinking water supply systems in the Mississippi River Valley alluvial aquifer in the state of Arkansas, USA is significant. In this context it is important to understand the occurrence, distribution and mobilization of As in the Mississippi River Valley alluvial aquifer. Application of surface complexation models (SCMs) to predict the sorption behavior of As and hydrous Fe oxides (HFO) in the laboratory has increased in the last decade. However, the application of SCMs to predict the sorption of As in natural sediments has not often been reported, and such applications are greatly constrained by the lack of site-specific model parameters. Attempts have been made to use SCMs considering a component additivity (CA) approach which accounts for relative abundances of pure phases in natural sediments, followed by the addition of SCM parameters individually for each phase. Although few reliable and internally consistent sorption databases related to HFO exist, the use of SCMs using laboratory-derived sorption databases to predict the mobility of As in natural sediments has increased. This study is an attempt to evaluate the ability of the SCMs using the geochemical code PHREEQC to predict solid phase As in the sediments of the Mississippi River Valley alluvial aquifer in Arkansas. The SCM option of the double-layer model (DLM) was simulated using ferrihydrite and goethite as sorbents quantified from chemical extractions, calculated surface-site densities, published surface properties, and published laboratory-derived sorption constants for the sorbents. The model results are satisfactory for shallow wells (10.6 m below ground surface), where the redox condition is relatively oxic or mildly suboxic. However, for the deep alluvial aquifer (21-36.6 m below ground surface) where the redox condition is suboxic to anoxic, the model results are unsatisfactory.     

Factor and cluster analysis of water quality data of the groundwater wells of Kushtia, Bangladesh: Implication for arsenic enrichment and mobilization

The study area is located in the southwestern part of Bangladesh. Twenty-six groundwater samples were collected from both shallow and deep tube wells ranging in depth from 20 to 60 m. Multivariate statistical analyses including factor analysis, cluster analysis and multidimensional scaling were applied to the hydrogeochemical data. The results show that a few factors adequately represent the traits that define water chemistry. The first factor of Fe and HCO₃ is strongly influenced by bacterial Fe (III) reduction which would raise both Fe and HCO₃ concentrations in water. Na, Cl, Ca, Mg and PO₄ are grouped under the second factor representing the salinity sources of waters. The third factor, represented by As, Mn, SO₄ and K is related to As mobilization processes. Cluster analysis has been applied for the interpretation of the groundwater quality data. Initially Piper methods have been employed to obtain a first idea on the water types in the study area. Hierarchical cluster analysis was carried out for further classification of water types in the study area. Twelve components, namely, pH, Fe, Mn, As, Ca, Mg, Na, K, HCO₃, Cl, SO₄ and NO₃ have been used for this purpose. With hierarchical clustering analysis the water samples have been classified into 3 clusters. They are very high, high and moderately As-enriched groundwater as well as groundwater with elevated SO₄.     

Understanding indigenous people’s perception on climate change and climatic hazards: a case study of Chakma indigenous communities in Rangamati Sadar Upazila of Rangamati District, Bangladesh

This study explores the relationship between perception on climate change as well as climatic hazards and socio-demographic characteristics such as age, gender, occupation, exposure to mass media, amount of land, education, and income. Following simple random sampling technique, a total of 384 households were sampled from Rangamati Sadar Upazila of Bangladesh and were interviewed through a predesigned semistructured questionnaire. The findings of the study reveal that a substantial number of respondents (61 %) perceive that climate is changing moderately over the years. The bivariate results indicate that age, gender, education, occupation, income, amount of land, and access to mass media are significantly associated with perception on climate change as well as climatic hazards. In addition, age, education, and exposure to mass media are also found as significant predictors of climate change perception. Education has been found as the single best predictor.     

Role of women as risk communicators to enhance disaster resilience of Bandung,Indonesia

This study addresses the need for women risk communication and highlights the potential role of Women Welfare Associations (WWAs) of Bandung, Indonesia, as risk communicators. A risk communication framework is modeled for women’s risk communication process. A set of indicators in social, institutional, and economic resilience activities (SIERAs), with a scope of 45 activities covering three different disaster periods, were developed to characterize the delivery process of risk information by women in WWAs through their activities at sub-district and ward levels. The data were collected through a questionnaire survey method using the risk communication SIERA approach. Women’s leaders at wards were surveyed concerning their perceptions on these 45 scopes of SIERA, ongoing activities, and their risk information source and dissemination process. Correlation analysis was applied to determine the relationship between the variables such as periods of disaster, types of activities (social, institutional, economic), and attributing factors (location, population, and education institution) in finding variations in risk communication activity that functions for women and communities. Five risk communication processes of WWAs are identified and implemented that work for women in Bandung. When their perceptions and ongoing activities are compared, activities such as dissemination of disaster risk information, conveying early warnings to their peers, and involvement of the local government have been confirmed to match the risk communication plans and implementation of WWAs. These indicate that WWAs’ activities in Bandung implement a certain degree of risk communication that is embedded in their activities. The results confirm that women through their social networks can become active agents of change and thus act beyond their usual domestic roles and responsibilities in order to contribute to the overall enhancement of community resilience.

     

Community-based disaster risk and vulnerability models of a coastal municipality in Bangladesh

Bangladesh is one of the most natural hazard-prone countries in the world with the greatest negative consequences being associated with cyclones, devastating floods, riverbank erosion, drought, earthquake, and arsenic contamination, etc. One way or other, these natural hazards engulfed every corner of Bangladesh. The main aim of this research paper is to carry out a multi-hazards risk and vulnerability assessment for the coastal Matlab municipality in Bangladesh and to recommend possible mitigation measures. To this aim, hazards are prioritized by integrating SMUG and FEMA models, and a participation process is implemented so as to involve community both in the risk assessment and in the identification of adaptation strategies. The Matlab municipality is highly vulnerable to several natural hazards such as cyclones, floods, and riverbank erosion. The SMUG is a qualitative assessment, while FEMA is a quantitative assessment of hazards. The FEMA model suggests a threshold of highest 100 points. All hazards that total more than 100 points may receive higher priority in emergency preparedness and mitigation measures. The FEMA model, because it judges each hazard individually in a numerical manner, may provide more satisfying results than the SMUG system. The spatial distributions of hazard, risk, social institutions, land use, and other resources indicate that the flood disaster is the top environmental problem of Matlab municipality. Hazard-specific probable mitigation measures are recommended with the discussion of local community. Finally, this study tries to provide insights into the way field research combining scientific assessments tools such as SMUG and FEMA could feed evidence-based decision-making processes for mitigation in vulnerable communities.     

Site amplification investigation in Dhaka, Bangladesh, using H/V ratio of microtremor

The degree of damage during earthquakes strongly depends on dynamic characteristics of buildings as well as amplification of seismic waves in soils. Among the other approaches, microtremor is, perhaps, the easiest and cheapest way to understand the dynamic characteristics of soil. Non-reference microtremor measurements have been carried out in 45 locations in and around the capital Dhaka city of Bangladesh. Subsoil investigations (Standard Penetration Test and Shear Wave Velocity) have also been executed in those locations. Soil model has been developed for those locations for site response analysis by means of the program SHAKE. Among those 45 locations, predominant frequency of microtremor observation varies from 0.48 to 3.65 Hz. Out of those 45, for 35 locations Transfer function obtained from the program SHAKE have higher frequency compared to microtremor H/V ratio and for one location it has lower predominant frequency. For six locations, frequencies obtained from two methods are identical. For three other locations, there are no similarities between predominant frequency obtained from microtremor and transfer function. The seismic Vulnerability Index (Kg) for 45 sites varies between 0.45 and 31.85. Ten sites have been identified as having moderate vulnerability of soil layers to deform.     

Suspended sediment load prediction of river systems: GEP approach

This study presents gene expression programming (GEP), an extension of genetic programming, as an alternative approach to modeling the suspended sediment load relationship for the three Malaysian rivers. In this study, adaptive neuro-fuzzy inference system (ANFIS), regression model, and GEP approaches were developed to predict suspended load in three Malaysian rivers: Muda River, Langat River, and Kurau River [ANFIS (R ²?=?0.93, root mean square error (RMSE)?=?3.19, and average error (AE)?=?1.12) and regression model (R ²?=?0.63, RMSE?=?13.96, and AE?=?12.69)]. Additionally, the explicit formulations of the developed GEP models are presented (R ²?=?0.88, RMSE?=?5.19, and AE?=?6.5). The performance of the GEP model was found to be acceptable compare to ANFIS and better than the conventional models.