• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.187-187
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• 2016

High intensity of population distribution in deltaic setting especially in Asia tends to have increased and causes coastal flood risk due to lower elevations and significant subsidence. Maximum or peak discharge of flood always causes numerous deaths and huge economic losses. New technology of spatial satellite image has been applied to analyze flood damage. In this research, the relationship of nightlight intensity associated with flood damages has been determined during 1992-2013 with spatial resolution of 30 arc sec ($0.0083^{\circ}$) which is nearly one kilometer at the equator in whole six countries along the Mekong River (i.e., China, Myanmar, Lao PDR, Thailand, Cambodia and Vietnam). ArcGIS Hydrological Flow Length Tool has been used to determine the distance of each pixel areas from the rivers and streams. Statistical analysis results highlight the significant correlation R = 0.47 between nightlight digital number and economic damages per unit area (US$/km2) and R = 0.62 for number of affected people for unit area ($people/km^2$). The areas near by the Mekong River and its tributaries correspond to high flood damage. This spatial analysis result is going to be prestigious key information to the regions and all related stakeholders for decisions and mitigation strategies.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.2
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• pp.209-215
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• 2022

This study aims to analyze the livelihood resources and income diversification of informal recyclers in the Mekong River Delta (MRD). The multiple linear regression model was applied to determine income diversification and total household income with the sustainable livelihood analysis framework developed by the United Kingdom Department for International Development (2000), including human resources, physical resources, natural resources, financial resources, and social resources. The results indicated that up to 25% of itinerant waste buyers worked on average more than 7.3 hours/day, which was higher than the urban near-poor level regulated by the Vietnam government. The results of the regression model revealed that total households' income was affected by the factors of health status, gender, urban location type 1, the amount of potential savings, and informal credit participation, while the factors of health status, urban location, the amount of potential savings, and informal credit participation have the effect of diversifying farm household income. Thus, if the informal waste recycling sector is supported and regulated by proper government management, it will not only help poor households diversify their income, but it will also help poor households diversify their income, particularly women's income, which is vulnerable and lower than male income in the MRD.

• Journal of Korea Water Resources Association
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• v.52 no.1
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• pp.71-82
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• 2019

The purpose of this study is to analyze the Mekong River streamflow alteration due to climate change. The future climate change scenarios were produced by bias corrections of the data from East Asia RCP 4.5 and 8.5 scenarios, given by HadGEM3-RA. Then, SWAT model was used for discharge simulation of the Kratie, the main point of the Mekong River (watershed area: $646,000km^2$, 88% of the annual average flow rate of the Mekong River). As a result of the climate change analysis, the annual precipitation of the Kratie upper-watershed increase in both scenarios compared to the baseline yearly average precipitation. The monthly precipitation increase is relatively large from June to November. In particular, precipitation fluctuated greatly in the RCP 8.5 rather than RCP 4.5. Monthly average maximum and minimum temperature are predicted to be increased in both scenarios. As well as precipitation, the temperature increase in RCP 8.5 scenarios was found to be more significant than RCP 4.5. In addition, as a result of the duration curve comparison, the streamflow variation will become larger in low and high flow rate and the drought will be further intensified in the future.

• Water for future
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• v.46 no.6
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• pp.28-33
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• 2013

• Journal of People, Plants, and Environment
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• v.24 no.6
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• pp.551-561
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• 2021

Background and objective: Vietnam is prioritizing agricultural production for food export capacity in all national policies. As a result, for three decades, its agriculture has been making quite many remarkable achievements. Methods: The most successful one is that the nation has become one of the world's leading rice exporters and ensures its national food security. Through these endeavors, the Mekong River Delta (MRD), in particular, has emerged as a key region in ensuring national food security and rice export. Results: The new era can now see Vietnamese agriculture turning to place special emphasis on commodity quality and the improvement of the living environment. This is evidenced, for example, by the phenomenon that the MRD, as a rice basket of the whole country, is making moves back to nature-based agriculture with attempts to restore the natural ecology, including preserving and restoring local traditional rice seeds, adopting natural farming practices and minimizing the use of chemical fertilizers and pesticides. Conclusion: The case studies of nature-based farming practices in the MRD indicate that, while the national agriculture is generally developing large-scale production, the small-scale farming in the region, integrated with tourist and educational activities on-site, is meeting the demands of a highly potential domestic niche market. Moreover, this model appears to be a sustainable farming approach that defines itself as a working green livelihood for the region.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.682-686
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• 2003

This paper is concerned with 'reverse difference' of marine sediments at the Camau tongue in the extreme south of Vietnam. We demonstrate the importance of remote sensing in geomorphology and marine geological application, using only visual evaluation and some data-processing techniques. In this paper, about 10,000 km$^2$ of the territorial water in the extreme south of Vietnam is being studied. We show that form and behavior of Mekong and its branch can be determined by visually interpreting remote sensing images and using ERDAS IMAGE 8.5 software. Besides, the 'reverse difference' phenomenon is explained by flows of Mekong river and its branches.

• Parasites, Hosts and Diseases
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• v.58 no.4
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• pp.431-443
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• 2020

Echinostoma mekongi n. sp. (Digenea: Echinostomatidae) is described based on adult flukes collected from humans residing along the Mekong River in Cambodia. Total 256 flukes were collected from the diarrheic stool of 6 echinostome egg positive villagers in Kratie and Takeo Province after praziquantel treatment and purging. Adults of the new species were 9.0-13.1 (av. 11.3) mm in length and 1.3-2.5 (1.9) mm in maximum width and characterized by having a head collar armed with 37 collar spines (dorsal spines arranged in 2 alternative rows), including 5 end group spines. The eggs in feces and worm uterus were 98-132 (117) ㎛ long and 62-90 (75) ㎛ wide. These morphological features closely resembled those of Echinostoma revolutum, E. miyagawai, and several other 37-collar-spined Echinostoma species. However, sequencing of the nuclear ITS (ITS1-5.8S rRNA-ITS2) and 2 mitochondrial genes, cox1 and nad1, revealed unique features distinct from E. revolutum and also from other 37-collar-spined Echinostoma group available in GenBank (E. bolschewense, E. caproni, E. cinetorchis, E. deserticum, E. miyagawai, E. nasincovae, E. novaezealandense, E. paraensei, E. paraulum, E. robustum, E. trivolvis, and Echinostoma sp. IG). Thus, we assigned our flukes as a new species, E. mekongi. The new species revealed marked variation in the morphology of testes (globular or lobulated), and smaller head collar, collar spines, oral and ventral suckers, and cirrus sac compared to E. revolutum and E. miyagawai. Epidemiological studies regarding the geographical distribution and its life history, including the source of human infections, remain to be performed.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.173-173
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• 2023

The Mekong River Basin (MRB) is a crucial watershed in Asia, impacting over 60 million people across six developing nations. Accurate satellite-based precipitation products (SPPs) are essential for effective hydrological and watershed management in this region. However, the performance of SPPs has been varied and limited. The APHRODITE product, a unique gauge-based dataset for MRB, is widely used but is only available until 2015. In this study, we present a novel framework for correcting SPPs in the MRB by employing a deep learning approach that combines convolutional neural networks and encoder-decoder architecture to address pixel-by-pixel bias and enhance accuracy. The DLF was applied to four widely used SPPs (TRMM, CMORPH, CHIRPS, and PERSIANN-CDR) in MRB. For the original SPPs, the TRMM product outperformed the other SPPs. Results revealed that the DLF effectively bridged the spatial-temporal gap between the SPPs and the gauge-based dataset (APHRODITE). Among the four corrected products, ADJ-TRMM demonstrated the best performance, followed by ADJ-CDR, ADJ-CHIRPS, and ADJ-CMORPH. The DLF offered a robust and adaptable solution for bias correction in the MRB and beyond, capable of detecting intricate patterns and learning from data to make appropriate adjustments. With the discontinuation of the APHRODITE product, DLF represents a promising solution for generating a more current and reliable dataset for MRB research. This research showcased the potential of deep learning-based methods for improving the accuracy of SPPs, particularly in regions like the MRB, where gauge-based datasets are limited or discontinued.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.120-120
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• 2020

Spatial precipitation data is one of the essential components in modeling hydrological problems. The estimation of these data has achieved significant achievements own to the recent advances in remote sensing technology. However, there are still gaps between the satellite-derived rainfall data and observed data due to the significant dependence of rainfall on spatial and temporal characteristics. An effective approach based on the Convolutional Neural Network (CNN) model to correct the satellite-derived rainfall data is proposed in this study. The Mekong River basin, one of the largest river system in the world, was selected as a case study. The two gridded precipitation data sets with a spatial resolution of 0.25 degrees used in the CNN model are APHRODITE (Asian Precipitation - Highly-Resolved Observational Data Integration Towards Evaluation) and PERSIANN-CDR (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks). In particular, PERSIANN-CDR data is exploited as satellite-based precipitation data and APHRODITE data is considered as observed rainfall data. In addition to developing a CNN model to correct the satellite-based rain data, another statistical method based on standard deviations for precipitation bias correction was also mentioned in this study. Estimated results indicate that the CNN model illustrates better performance both in spatial and temporal correlation when compared to the standard deviation method. The finding of this study indicated that the CNN model could produce reliable estimates for the gridded precipitation bias correction problem.

• Journal of Korea Water Resources Association
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• v.51 no.7
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• pp.565-574
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• 2018

High population density in deltaic settings, especially in Asia, tends to increase and causes coastal flood risk because of lower elevations and significant subsidence. Large flood annually causes numerous deaths and huge economic losses. In this paper, an innovative technology of spatial satellite imagery has been used as tool to analyze the socio-economic flood-related damage in Mekong river basin. The relationship between nightlight intensity and flood damages has been determined for the period of 1992-2013 with a spatial resolution of 30 arc sec ($0.0083^{\circ}$), which is nearly one kilometer at the equator. Flow path distance was calculated to identify the distance of each cell to river network and to examine how nightlight intensity correlate to the area close to and far from river network. Statistical analysis results highlight the significant correlation between nocturnal luminosity intensity and flood-related damages in countries along the Mekong river (i.e., Cambodia, China, Lao PDR, Thailand, and Vietnam). This result reveals that the areas close to the river network correspond to high human distribution and causes huge damage during flooding. The result may provide key information to the region with respect to decisions, attentions, and mitigation strategies.