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Luu Chinh Bui Quynh Duy Costache Romulus Nguyen Luan Thanh Nguyen Thu Thuy Van Phong Tran Van Le Hiep Pham Binh Thai 《Natural Hazards》2021,108(3):3229-3251
Natural Hazards - Vietnam’s central coastal region is the most vulnerable and always at flood risk, severely affecting people’s livelihoods and socio-economic development. In... 相似文献
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Shakirov R. B. Cuong Do Huy Obzhirov A. I. Valitov M. G. Lee N. S. Legkodimov A. A. Kalgin V. Yu. Yeskova A. I. Proshkina Z. N. Telegin Yu. A. Storozhenko A. V. Ivanov M. V. Pletnev S. P. Sedin V. T. Bulanov A.V. Shvalov D. A. Lipinskaya N. A. Bovsun M. A. Makseev D. S. Thanh Nguyen Trung Anh Le Duc Luong Le Duc 《Oceanology》2021,61(1):147-149
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... 相似文献
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Nguyen Le Duy Nguyen Viet Dung Ingo Heidbüchel Hanno Meyer Markus Weiler Bruno Merz Heiko Apel 《水文研究》2019,33(24):3098-3118
Groundwater transit time is an essential hydrologic metric for groundwater resources management. However, especially in tropical environments, studies on the transit time distribution (TTD) of groundwater infiltration and its corresponding mean transit time (mTT) have been extremely limited due to data sparsity. In this study, we primarily use stable isotopes to examine the TTDs and their mTTs of both vertical and horizontal infiltration at a riverbank infiltration area in the Vietnamese Mekong Delta (VMD), representative of the tropical climate in Asian monsoon regions. Precipitation, river water, groundwater, and local ponding surface water were sampled for 3 to 9 years and analysed for stable isotopes (δ18O and δ2H), providing a unique data set of stable isotope records for a tropical region. We quantified the contribution that the two sources contributed to the local shallow groundwater by a novel concept of two‐component lumped parameter models (LPMs) that are solved using δ18O records. The study illustrates that two‐component LPMs, in conjunction with hydrological and isotopic measurements, are able to identify subsurface flow conditions and water mixing at riverbank infiltration systems. However, the predictive skill and the reliability of the models decrease for locations farther from the river, where recharge by precipitation dominates, and a low‐permeable aquitard layer above the highly permeable aquifer is present. This specific setting impairs the identifiability of model parameters. For river infiltration, short mTTs (<40 weeks) were determined for sites closer to the river (<200 m), whereas for the precipitation infiltration, the mTTs were longer (>80 weeks) and independent of the distance to the river. The results not only enhance the understanding of the groundwater recharge dynamics in the VMD but also suggest that the highly complex mechanisms of surface–groundwater interaction can be conceptualized by exploiting two‐component LPMs in general. The model concept could thus be a powerful tool for better understanding both the hydrological functioning of mixing processes and the movement of different water components in riverbank infiltration systems. 相似文献
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Le Duc Luong Shakirov Renat B. Hoang Nguyen Shinjo Ryuichi Obzhirov Anatoly Syrbu Nadezhda Shakirova Maria 《Water Resources》2019,46(5):807-816
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... 相似文献
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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. 相似文献
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A. Nguyen Van Nghia Jougnot Damien Thanh Luong Duy Van Do Phan Thuy Tran Thi Chung Hue Dang Thi Minh Hung Nguyen Manh 《Hydrogeology Journal》2021,29(6):2017-2031
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... 相似文献
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Binh Thai Pham Abolfazl Jaafari Tran Van Phong Hoang Phan Hai Yen Tran Thi Tuyen Vu Van Luong Huu Duy Nguyen Hiep Van Le Loke Kok Foong 《地学前缘(英文版)》2021,12(3):101105
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. 相似文献
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Huu Duy Nguyen Dinh-Kha Dang Quang-Thanh Bui Alexandru-Ionut Petrisor 《Transactions in GIS》2023,27(5):1614-1640
Natural hazards constitute a diverse category and are unevenly distributed in time and space. This hinders predictive efforts, leading to significant impacts on human life and economies. Multi-hazard prediction is vital for any natural hazard risk management plan. The main objective of this study was the development of a multi-hazard susceptibility mapping framework, by combining two natural hazards—flooding and landslides—in the North Central region of Vietnam. This was accomplished using support vector machines, random forest, and AdaBoost. The input data consisted of 4591 flood points, 1315 landslide points, and 13 conditioning factors, split into training (70%), and testing (30%) datasets. The accuracy of the models' predictions was evaluated using the statistical indices root mean square error, area under curve (AUC), mean absolute error, and coefficient of determination. All proposed models were good at predicting multi-hazard susceptibility, with AUC values over 0.95. Among them, the AUC value for the support vector machine model was 0.98 and 0.99 for landslide and flood, respectively. For the random forest model, these values were 0.98 and 0.98, and for AdaBoost, they were 0.99 and 0.99. The multi-hazard maps were built by combining the landslide and flood susceptibility maps. The results showed that approximately 60% of the study area was affected by landslides, 30% by flood, and 8% by both hazards. These results illustrate how North Central is one of the regions of Vietnam that is most severely affected by natural hazards, particularly flooding, and landslides. The proposed models adapt to evaluate multi-hazard susceptibility at different scales, although expert intervention is also required, to optimize the algorithms. Multi-hazard maps can provide a valuable point of reference for decision makers in sustainable land-use planning and infrastructure development in regions faced with multiple hazards, and to prevent and reduce more effectively the frequency of floods and landslides and their damage to human life and property. 相似文献