A simplified methodology for mapping groundwater vulnerability and contamination risk, and its first application in a tropical karst area, Vietnam

A simplified methodology for mapping groundwater vulnerability and contamination risk is proposed, and the first application of the methodology, in a mountainous tropical karst area, is presented. The test site is the Tam Duong area, one of the poorest and remotest regions in northern Vietnam. The methodology requires a minimum of input data, which makes it particularly useful for developing countries. Vulnerability is assessed on the basis of two factors, which take into account the duality of recharge processes in karst aquifer systems: the overlying layers (O) and the concentration of flow (C). The risk map is obtained by putting together the vulnerability map and a simplified hazard assessment. The resulting maps provide a basis for groundwater protection zoning and land-use planning. Tracer tests and microbiological data confirmed the vulnerability and risk assessment in the test site.     

Multi-scale solution for building extraction from LiDAR and image data

This paper presents a multi-scale solution based on mathematical morphology for extracting the building features from remotely sensed elevation and spectral data. Elevation data are used as the primary data to delineate the structural information and are firstly represented on a morphological scale-space. The behaviors of elevation clusters across the scale-space are the cues for feature extraction. As a result, a complex structure can be extracted as a multi-part object in which each part is represented on a scale depending on its size. The building footprint is represented by the boundary of the largest part. Other object attributes include the area, height or number of stories. The spectral data is used as an additional source to remove vegetation and possibly classify the building roof material. Finally, the results can be stored in a multi-scale database introduced in this paper. The proposed solution is demonstrated using the data derived from a Light Detection And Ranging (LiDAR) surveying flight over Tokyo, Japan. The results show a reasonable match with reference data and prove the capability of the proposed approach in accommodation of diverse building shapes. Higher density LiDAR is expected to produce better accuracy in extraction, and more spectral sources are necessary for further classification of building roof material. It is also recommended that parallel processing should be implemented to reduce the computation time.     

Improved flood susceptibility mapping using a best first decision tree integrated with ensemble learning techniques

Improving the accuracy of flood prediction and mapping is crucial for reducing damage resulting from flood events. In this study, we proposed and validated three ensemble models based on the Best First Decision Tree (BFT) and the Bagging (Bagging-BFT), Decorate (Bagging-BFT), and Random Subspace (RSS-BFT) ensemble learning techniques for an improved prediction of flood susceptibility in a spatially-explicit manner. A total number of 126 historical flood events from the Nghe An Province (Vietnam) were connected to a set of 10 flood influencing factors (slope, elevation, aspect, curvature, river density, distance from rivers, flow direction, geology, soil, and land use) for generating the training and validation datasets. The models were validated via several performance metrics that demonstrated the capability of all three ensemble models in elucidating the underlying pattern of flood occurrences within the research area and predicting the probability of future flood events. Based on the Area Under the receiver operating characteristic Curve (AUC), the ensemble Decorate-BFT model that achieved an AUC value of 0.989 was identified as the superior model over the RSS-BFT (AUC = 0.982) and Bagging-BFT (AUC = 0.967) models. A comparison between the performance of the models and the models previously reported in the literature confirmed that our ensemble models provided a reliable estimate of flood susceptibilities and their resulting susceptibility maps are trustful for flood early warning systems as well as development of mitigation plans.     

Investigating the hydromechanical behaviour of bentonite pellets by swelling pressure tests and discrete element modelling

Acta Geotechnica - Bentonite pellet mixtures are candidate material for the sealing of galleries in radioactive waste disposals. The hydromechanical behaviour of assemblies of bentonite pellets is...     

Regional effects of natural disasters in China: investing in post-disaster recovery

We examine the effects of natural disasters on income and investment in China. Using macroeconomic province-level data and the provincial history of disaster exposure over the past two decades, we describe the relationship between disaster mortality and morbidity, disasters’ economic damages, government investment and regional economic activity, and infrastructure development. The Chinese government’s aggressive investment in post-disaster reconstruction is discussed, and the implications of this investment for post-disaster private sector economic activity are analyzed empirically. We further investigate the differential effects of natural disasters on economic activity in China’s diverse geographical regions.     

Economic impact upon agricultural production from extreme flood events in Quang Nam,central Vietnam

Natural Hazards - Quang Nam province, central Vietnam, is situated within the tropical monsoon and typhoon zone of south-east Asia and is susceptible to extreme floods. Historical water level data...     

Groundwater Potential Mapping Using GIS-Based Hybrid Artificial Intelligence Methods

Groundwater is one of the major valuable water resources for the use of communities, agriculture, and industries. In the present study, we have developed three novel hybrid artificial intelligence (AI) models which is a combination of modified RealAdaBoost (MRAB), bagging (BA), and rotation forest (RF) ensembles with functional tree (FT) base classifier for the groundwater potential mapping (GPM) in the basaltic terrain at DakLak province, Highland Centre, Vietnam. Based on the literature survey, these proposed hybrid AI models are new and have not been used in the GPM of an area. Geospatial techniques were used and geo-hydrological data of 130 groundwater wells and 12 topographical and geo-environmental factors were used in the model studies. One-R Attribute Evaluation feature selection method was used for the selection of relevant input parameters for the development of AI models. The performance of these models was evaluated using various statistical measures including area under the receiver operation curve (AUC). Results indicated that though all the hybrid models developed in this study enhanced the goodness-of-fit and prediction accuracy, but MRAB-FT (AUC = 0.742) model outperformed RF-FT (AUC = 0.736), BA-FT (AUC = 0.714), and single FT (AUC = 0.674) models. Therefore, the MRAB-FT model can be considered as a promising AI hybrid technique for the accurate GPM. Accurate mapping of the groundwater potential zones will help in adequately recharging the aquifer for optimum use of groundwater resources by maintaining the balance between consumption and exploitation.     

The occurrence of cyanobacteria and microcystins in the Hoan Kiem Lake and the Nui Coc reservoir (North Vietnam)

The occurrence of increasing blooms of toxic cyanobacteria in freshwaters has received much attention due to the ability of many cyanobacteria to produce potent cyanotoxins. In this paper, the occurrence of dominant cyanobacteria and the concentration of microcystins (MCs) analysis were investigated monthly from July 2008 to April 2009 in the Hoan Kiem Lake and from February to April 2009 in the Nui Coc reservoir. Concentrations of intracellular MCs from water, bloom samples, and isolated strains were quantified by using high performance liquid chromatography (HPLC). During the study period, the microscopic examination of the phytoplankton samples showed the dominance of the genus Microcystis in the water environment of the Hoan Kiem Lake and the Nui Coc reservoir. The toxin analysis by HPLC demonstrated the presence of two MC variants: MC-LR and MC-RR in water samples. Total concentrations of the toxins in filtered samples from surface water ranged from non-detected to 0.91 μg L^?1 at Nui Coc reservoir and they ranged from 2.1 to 46.0 μg L^?1 at Hoan Kiem Lake. The results of the HPLC analysis confirmed the production of MCs in bloom samples (ranged from 115.9 to 184.6 μg L^?1 in the Hoan Kiem Lake and from 726.5 to 1116 μg L^?1 in the Nui Coc reservoir) and isolated strains of Anabaena sp. and Microcystis with the concentration of MC ranging from 152 to 396.2 μg g^?1 dry mass, respectively.     

Hydrological and hydrogeological characterization of groundwater and river water in the North Hanoi industrial area,Vietnam

Degradation of groundwater quality by human activities is a widespread environmental problem in Vietnam. Groundwater there is a major source of water for domestic and industrial purposes. This paper reviews, compiles, and comprehensively analyzes spatiotemporal variations of hydrological and hydrogeological characteristics of shallow and deep groundwater aquifers in northern Hanoi industrial zones and in nearby Red River water. Groundwater level, electrical conductivity, and water temperature were measured in six monitoring wells, complemented by anion, cation, and stable isotope analyses of ground and surface water. The results show that the groundwater in both shallow and deep aquifers was fresh, but mainly calcium-bicarbonate type contaminants and human activities affect groundwater and surface water composition. With the goal of devising sustainable water use regulations, more research must be directed toward long-term monitoring of groundwater and surface water quality, as well as toward detailed investigation of the hydraulic characteristics of local aquifers in the study area.     

‘White cranes fly over black cranes’: The longue durée of rural–urban migration in Vietnam

The changing nature of rural–urban migration, in the context of transition economies of East and Southeast Asia, is usually interpreted as an outcome of structural transformation, while the longue durée of these migration flows tends to be neglected. Adopting a historical perspective, supported by the ’migration as resistance’ approach, this paper examines the changes in rural–urban migration dynamics in Vietnam from the 1950s to 2010 in relation to the country’s political and economic reforms (Ð?i M?i). Drawing on a case study of female migration between Phu Khe and Hanoi, it analyses how migrants resist and undermine state control over population mobility in order to pursue their movement and migration, and how they develop their migration networks over time. By doing so, the paper highlights a gradual process of the changing nature of rural–urban migration in which migrants themselves, through their resistance to governance of mobility and their establishment of migration networks prior to Ð?i M?i, play an important role.