Features in REE and Methane Anomalies Distribution in the East China Sea Water Column: a Comparison with the South China Sea

Water Resources - This paper presents review of dissolved Rare Earth Elements (REE) and methane anomalies distribution in the East China Sea water column. In general, the REE concentrations of the...     

Integrated Geological–Geophysical and Oceanographic Research in the South China Sea: Cruise 88 of the R/V “Akademik M.A. Lavrentyev”

Oceanology - Abstract—The paper gives brief results of comprehensive studies in the South China Sea obtained from a joint Russian–Vietnamese expedition in November 2019 (cruise 88 of...     

Predicting water flow in fully and partially saturated porous media: a new fractal-based permeability model

Hydrogeology Journal - Predicting the permeability of porous media in saturated and partially saturated conditions is of crucial importance in many geo-engineering areas, from water resources to...     

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.     

Evaluation of food risk parameters in the Day River Flood Diversion Area,Red River Delta,Vietnam

An interdisciplinary approach is necessary for flood risk assessment. Questions are often raised about which factors should be considered important in assessing the flood risk in an area and how to quantify these factors. This article defines and quantitatively evaluates the flood risk factors that would affect the Day River Flood Diversion Area in the context of integrated flood management in the Red River Delta, Vietnam. Expert analysis, in conjunction with field survey and Analytical Hierarchy Process (AHP), is applied to define and quantify parameters (indicators, subcomponents, and components) that contribute to flood risk. Flood duration is found to be the most prominent indicator in determining flood hazard. Residential buildings, population, and pollution are other fairly significant indicators contributing to flood vulnerability from the economic, social, and environmental perspectives, respectively. The study results will be useful in developing comprehensive flood risk maps for policy-makers and responsible authorities. Besides, local residents will also be able to implement suitable measures for reducing flood risk in the study area.     

A fractal model for streaming potential coefficient in porous media

Streaming potential is the result of coupling between a fluid flow and an electric current in porous rocks. The modified Helmholtz–Smoluchowski equation derived for capillary tubes is mostly used to determine the streaming potential coefficient of porous media. However, to the best of our knowledge, the fractal geometry theory is not yet applied to analyse the streaming potential in porous media. In this article, a fractal model for the streaming potential coefficient in porous media is developed based on the fractal theory of porous media and on the streaming potential in a capillary. The proposed model is expressed in terms of the zeta potential at the solid?liquid interface, the minimum and maximum pore/capillary radii, the fractal dimension, and the porosity of porous media. The model is also examined by using another capillary size distribution available in published articles. The results obtained from the model using two different capillary size distributions are in good agreement with each other. The model predictions are then compared with experimental data in the literature and those based on the modified Helmholtz–Smoluchowski equation. It is shown that the predictions from the proposed fractal model are in good agreement with experimental data. In addition, the proposed model is able to reproduce the same result as the Helmholtz–Smoluchowski equation, particularly for high fluid conductivity or large grain diameters. Other factors influencing the streaming potential coefficient in porous media are also analysed.     

The October 13, 2020, deadly rapid landslide triggered by heavy rainfall in Phong Dien,Thua Thien Hue,Vietnam

Landslides - At about 12:00 a.m., on October 13, 2020, a rapid rotational landslide induced by rainfall swept over Ranger Station-7 in Phong Xuan commune, Phong Dien district, Thua Thien Hue...     

Effects of urbanization on groundwater level in aquifers of Binh Duong Province,Vietnam

The purpose of this paper was to assess the impact of urbanization on the groundwater level(GWL)in aquifers of Binh Duong(BD)Province.The research method is to analyze the trend of GWL,the recharge capacity of surface over time and the relationship between them.The data of the GWL used in the study are the average values in the dry and rainy seasons of 35 observation wells from 2011 to 2018,which are in Pleistocene and Pliocene aquifers.The ability to recharge groundwater from the surface in this study was represented by the curve number(CN),a parameter used in hydrology for calculating direct runoff or infiltration from rainfall.The land use data to identify the CN was analyzed from the Landsat images.The results show that besides over-exploitation,the change of surface characteristic due to the urbanization development process is also the cause of the GWL decline.The analysis of seasonal GWL data shows that the increase in impervious surface area is the cause of GWL decline in the Pleistocene aquifer,which is more evident in the rainy season than in the dry season.The statistical results also show that in the rainy season and in shallow aquifers,a higher CN change can be found with the wells that had a remarkable GWL decline compared to the remaining wells.