Search Results (241)

Agrarian women are at the forefront of rural livelihoods increasingly affected by the frequency and severity of climate change impacts. However, their household livelihood resilience (HLR) remains limited due to gender-blind policies, scarce sex-disaggregated data, and inadequate consideration of gender-specific needs in resilience-building efforts. Grounded in participatory feminist research, this study employed a multi-method qualitative approach, including semi-structured interviews and oral history narratives, with 60 women in two climate-vulnerable provinces. Data were analyzed through thematic coding, CATWOE (Customers, Actors, Transformation, Worldview, Owners, Environmental Constraints) analysis, and descriptive statistics. The findings identify nine major climate-related events disrupting livelihoods and reveal a limited understanding of HLR as a long-term, transformative concept. Adaptation strategies remain short-term and focused on immediate survival. Barriers to HLR include financial constraints, limited access to agricultural resources and technology, and entrenched gender norms restricting women’s leadership and decision-making. While local governments, women’s associations, and community networks provide some support, gaps in accessibility and adequacy persist. Participants expressed the need for financial assistance, vocational training, agricultural technologies, and stronger peer networks. Strengthening HLR among agrarian women requires gender-sensitive policies, investment in local support systems, and community-led initiatives. Empowering agrarian women as agents of change is critical for fostering resilient rural livelihoods and achieving inclusive, sustainable development. Full article

In Vietnam, English proficiency is a graduation requirement and offers students great opportunities to win scholarships and employability after graduation. Universities in the Mekong Delta region (MDR) often face challenges in foresting students’ English proficiency despite continuous assistance offered. Although students have taken online supplementary courses (OSC) delivered through e-learning systems to support their English formal classes for several years, students’ successes in English tests with such supplementary courses and the predictors of this issue remain unknown. Therefore, we developed a model to predict students’ success in English final tests based on behaviors and grades in OSC using logistic regression (LR) and classification and regression tree (CART) classifiers. A total of 109 students of OSC in a target university in MDR participated in this study, and the result showed that CART (area under the curve (AUC) = 89.3%) was slightly better than LR. The outcomes of this study contribute to students’ success in English tests and the enhancement of the effectiveness of online supplementary courses for English improvements. Full article

The Mekong Delta, an important agricultural and economic hub in Vietnam, has suffered from severe water quality issues caused by both natural and anthropogenic forces. This paper aims to conduct a rational statistical approach to evaluate the current situation of surface water quality in the Mekong Delta, applying Factor Analysis (FA), Principal Component Analysis (PCA), and Agglomerative Hierarchical Clustering (AHC) to a database of 3117 samples collected by national and provincial monitoring stations. The results revealed significant contamination with organic pollutants (BOD5: 3.50–172.870 mg/L, COD: 6.493–472.984 mg/L), pesticides (e.g., DDTs: n.d to 1.227 mg/L), trace metals (As: 0.006–0.046 mg/L, Cr: n.d–1.960 mg/L), and microbial indicators (Coliforms: n.d–45,100 MPN/100 mL), often higher than the WHO drinking water threshold. PCA/AHC analysis identified the following five major pollution components: (1) organic pollution and sewage/industrial and deposited chemicals (PCA1—23.08% variance); (2) pesticide and agricultural runoff derived contamination with Hg (PCA2—15.44%); (3) microbial pollution of the water was found to correlate positively with Zn and Cu content (PCA3—8.90%); (4) salinity was found to mobilize As and Cr (PCA4—8.00%); (5) nutrient/microbial pollution presumably from agricultural and sewage inputs (PCA5—7.22%). AHC showed some spatial variability that grouped samples in urban/industrial (Cluster 1), rural/agricultural (Cluster 2), and a highly contaminated one, where water was toxic and presented with microbial and Cd contamination (Cluster 3). Levels of pesticides, Cr, and microbial pollution were higher than reported in previous Mekong Delta studies and exceeded regional trends. These results emphasize the importance of holistic water management strategies, including better wastewater treatment, pesticide control, sustainable farming, and climate-adaptive measures to reduce saltwater intrusion and safeguard drinking water quality for the Mekong Delta. Full article

Methane (CH₄) is a potent greenhouse gas with a significant impact on short- and medium-term climate forcing, and its atmospheric concentration has been increasing rapidly in recent decades. This study aims to analyze spatio-temporal patterns of atmospheric methane concentrations between 2019 and 2025, focusing on comparisons between regions characterized by high and low emission intensities. Level-3 XCH₄ data from the TROPOspheric Monitoring Instrument (TROPOMI) onboard the Sentinel-5 Precursor satellite were used, which were aggregated into seasonal and annual composites. High-emission regions, such as the Mekong Delta, Nile Delta, Eastern Uttar Pradesh and Bihar, Central Thailand, Lake Victoria Basin, and Eastern Arkansas, were contrasted with low-emission areas including Patagonia, the Mongolian Steppe, Northern Scandinavia, the Australian Outback, the Sahara Desert, and the Canadian Shield. The results show that high-emission regions exhibit substantially higher seasonal amplitude in XCH₄ concentrations, with an average seasonal variation of approximately 30.00 ppb, compared to 17.39 ppb in low-emission regions. Methane concentrations generally peaked at the end of the year (Q4) and reached their lowest levels during the first half of the year (Q1 or Q2), particularly in agriculturally dominated regions. Principal component and cluster analyses further confirmed a strong spatial differentiation between high- and low-emission regions based on both temporal trends and seasonal behavior. These findings demonstrate the potential of satellite remote sensing to monitor regional methane dynamics and highlight the need for targeted mitigation strategies in major agricultural and wetland zones. Full article

Canine distemper virus (CDV) is a highly contagious pathogen and causes a fatal systemic disease in domestic dogs and wild carnivores worldwide. Despite CDV infections being monitored globally, studies on CDV in Vietnam seem to be limited. This study, therefore, investigated the epidemiological, clinical, and molecular characteristics of CDV in the Mekong Delta (MD) region of Vietnam. A total of 6687 ocular/nasal swabs were collected from CDV-suspected dogs across seven cities/provinces. CDV infection was detected in 6.19% (414 dogs) of suspected dogs using a commercially available rapid kit, with infection associated with age, roaming status, and vaccination status. Hematological and blood biochemical analysis of CDV-infected dogs revealed anemia, leukopenia, neutrophilia, thrombocytopenia, a slight increase in aspartate aminotransferase (AST) levels, and a significant increase in blood urea nitrogen (BUN) levels. Molecular characterization of partial hemagglutinin (H) and fusion (F) genes exhibited high nucleotide and amino acid homology with the Asia-1 genotype. Phylogenetic analysis confirmed that the field sequences were clustered into the Asia-1 genotype together with the neighboring countries. These findings provide important insights into the current epidemiological, clinical, and molecular features of CDV circulating in Vietnam. Full article

The Ca Mau Peninsula (CMP), the southernmost region of the Mekong Delta, is increasingly threatened by groundwater salinization, posing severe risks to both the freshwater supply and land sustainability. This study develops a three-dimensional, density-dependent groundwater flow and salinity transport model to investigate salinization dynamics across the CMP’s complex multi-aquifer system. Unlike previous studies that largely rely on model calibration, this research introduces a novel approach by systematically deriving the spatial distribution of longitudinal dispersivity based on sediment characteristics. Moreover, detailed land use mapping is integrated to assign spatially and temporally variable Total Dissolved Solids (TDS) values to the uppermost layers, thereby enhancing the model realism in areas where monitoring data are limited. The model was utilized not only to simulate the regional salinity evolution, but also to critically evaluate conceptual hypotheses related to the mechanisms driving groundwater salinization. Results reveal a strong influence of seasonal and land use factors on salinity variability in the upper aquifers, while deeper aquifers remain largely stable, affected primarily by paleosalinity and localized pumping. This integrated modeling approach contributes to a better understanding of regional-scale groundwater salinization and highlights both the potential and the limitations of numerical modeling under data-scarce conditions. The findings provide a valuable scientific basis for adaptive water resource management in vulnerable coastal zones. Full article

Graduate employability remains a crucial challenge for higher education institutions, especially in developing economies. This study investigates the key academic and vocational factors influencing early employment outcomes among recent graduates at a public university in Vietnam’s Mekong Delta region. By leveraging predictive analytics, the research explores how data-driven approaches can enhance career readiness strategies. The analysis employed AI-driven models, particularly classification and regression trees (CARTs), using a dataset of 610 recent graduates from a public university in the Mekong Delta to predict early employability. The input factors included gender, field of study, university entrance scores, and grade point average (GPA) scores for four university years. The output factor was recent graduates’ (un)employment within six months after graduation. Among all input factors, third-year GPA, university entrance scores, and final-year academic performance are the most significant predictors of early employment. Among the tested models, CARTs achieved the highest accuracy (93.6%), offering interpretable decision rules that can inform curriculum design and career support services. This study contributes to the intersection of artificial intelligence and vocational education by providing actionable insights for universities, policymakers, and employers, supporting the alignment of education with labor market demands and improving graduate employability outcomes. Full article

Background: Vietnam has made significant strides in reducing the prevalence of HIV infection and achievements in its antiretroviral treatment program. However, the COVID-19 pandemic and financial challenges in the healthcare system have posed significant obstacles to maintaining effective HIV treatment and monitoring, particularly among vulnerable populations. This study aims to evaluate the situation of HIV drug resistance among patients who have experienced treatment failure in the Mekong Delta region and to compare data from 2019 to 2022. Methods: The study material was blood plasma samples from HIV-infected individuals with ART failure: 316 collected in 2019 and 326 collected in 2022. HIV-1 genotyping and mutation detection were performed based on an analysis of the nucleotide sequences of the Pol gene region. A total of 116 HIV-infected individuals with virological failure in 2019 and 2022 were assessed for HIV drug resistance. Results: The study revealed a high proportion of participants with viral loads exceeding 1000 copies/mL, significantly increasing from 12.0% in 2019 to 23.9% in 2022 (OR = 2.3; p = 0.0001). HIV drug resistance mutations were detected in 84.21% of cases in 2019 and 92.59% in 2022. The prevalence of concurrent resistance to NRTIs and NNRTIs was 37.5% and 30.13% in 2019 and 2022, respectively. There was a statistically significant decrease in NNRTI resistance (OR = 0.32, χ² = 5.43, p < 0.05). In contrast, multi-drug resistance to protease inhibitors rose from 18.52% to 45.21% (φ* = 0.00403, p < 0.05). Triple-class resistance was identified only in 2022 (17.81%). The most common mutations included M184I/V, D67N, K103N, Y181C, and V82A/S/T, with D67N rising significantly from 3.13% to 21.92%. The predominant subtype was CRF01_AE. Conclusion: A high prevalence of viral non-suppression and HIV drug resistance was observed among patients in the Mekong Delta region, particularly after the onset of the COVID-19 pandemic. Our study highlights the ongoing challenges that the HIV/AIDS treatment program in Vietnam must address in the post-pandemic period to sustain its success and achieve the goals of the country’s HIV prevention strategies. Full article

Land use and land cover (LULC) in coastal areas is critical in shaping the ecological systems, regional economy, and livelihood of indigenous communities. This study analyzes LULC changes (LULCC) in Soc Trang Province, Vietnam Mekong Delta, from 2010 to 2020 and simulates future LULC for 2030 under four scenarios: natural growth (business as usual, BAU), climate change challenges, profit optimization, and adaptation strategies. Satellite-based LULC maps and geospatial datasets were integrated into a LULC simulation model based on a Markov Chain and Cellular Automata to predict LULC in 2030 under disparate scenarios. Simultaneously, this study also estimates economic values and ecosystem service values as proxies to evaluate benefits and trade-offs between the scenarios. The research findings reveal that the critical LULCC observed during 2010–2020 are transitions from triple rice crops to double rice crops, rice–shrimp to brackish aquaculture, and expansion of perennial plantations. These transitional trends will persist at a modest rate under the BAU scenario in 2030. The climate change challenge scenario will intervene up to 24.2% of the total area, with double rice crops reaching the most extensive area compared to other scenarios, about 106,047 ha. The profit optimization scenario will affect 16.03% of the total area, focusing on aquaculture expansion to the maximum shared proportion of 34% (approximately 57,000 ha). Adaptive solutions will emphasize reducing triple rice crops while expanding double rice crops and reviving rice–shrimp to different extents depending on development pathways. Economic evaluations show a growth trend across scenarios, with maximum returns under profit optimization. Yet, ecosystem service values notably highlight ecological trade-offs, raising concerns about balancing economic benefits and ecological trade-offs in land use planning. The research findings recommend a comprehensive and multitarget approach to land use planning that integrates ecosystem services into initial assessments to balance benefits and trade-offs in coastal areas commonly affected by LULCC. By adopting well-informed and strategic land use plans that minimize ecological and social impacts, local sustainability and resilience to climate change can be significantly enhanced. Full article

Soil salinization, a major challenge caused by climate change over the past century, critically affects cultivated land and consequently reduces agricultural production worldwide. Recently, plant growth-promoting rhizobacteria have been collected and utilized to enhance plant growth and mitigate the effects of salt stress in different plant species including rice. In our current study, the Serratia marcescens strain VIRS2 with remarkable salt tolerance was successfully isolated from the saline soil in the Mekong River Delta of Vietnam. This isolate exhibited diverse plant growth-promoting properties, especially the production of a high indole acetic acid level. Treatments under both in vitro and greenhouse conditions indicated that VIRS2 could enhance growth and salt tolerance in rice. The VIRS2-inoculated rice plants exhibited biochemical profile alterations including proline, malondialdehyde, and relative water contents. In addition, the expression of genes involved in the plant stress response pathways was upregulated in the VIRS2-inoculated rice under salt treatments. Importantly, the whole genome sequencing data of VIRS2 also showed the presence of different genes associated with plant growth-promotion and stress-tolerance mechanisms. These results indicated the potential of the VIRS2 isolate for enhancing growth and salt tolerance in rice as well as other important crops. Full article

This study assessed riverbank erosion and stability along the Mekong and Bassac Rivers to propose safe river corridors and mitigate erosion risks in the Mekong Delta. Using Landsat imagery (2000–2023), field surveys, and numerical simulations, we identified severe erosion hotspots, where erosion rates reach up to 40 m annually, in the meandering sections of the Mekong River,. In contrast, the Bassac River exhibited significant sedimentation, though this trend was diminishing due to upstream sediment deficits caused by hydropower dams. Stability assessments revealed optimal safety corridor distances ranging from 20 to 38 m, influenced by local geotechnical conditions and structural loads. A significant proportion of riverbanks in Dong Thap (88%) and An Giang (48%) do not comply with conservation standards, exacerbating erosion risks and threatening infrastructure. The results of this study highlight the urgent need for enforcing conservation regulations, implementing nature-based solutions like riparian buffers, and adopting sustainable land-use planning. By addressing the interplay between natural processes and anthropogenic pressures, these findings offer actionable insights to enhance riverbank stability, protect ecosystems, and sustain livelihoods in the Mekong Delta amidst growing environmental challenges. Full article

Increased saltwater intrusion likely causes a significant reduction in food production in alluvial river deltas worldwide. One of the mitigation measures for saltwater intrusion is to increase natural flow through irrigation water conservation and land-fallowing policies to prevent the saltwater from moving further inland. However, economic estimates of the costs of such measures under uncertainty are scant. Herein, we develop an integrated modeling framework for estimating the costs of saltwater intrusion mitigation policies by 2050 in the Mekong Delta. The integrated model combines hydrodynamic, advection-dispersion, statistical, crop yield, and economic models, thus allowing us to account for the risk and uncertainty of saltwater intrusion and the costs of mitigation policies. We found that a 95% confidence interval of the saltwater intrusion-impacted area is estimated to be 186,000–201,000 hectares for the baseline, 193,000–209,000 hectares for a sea level rise of 22 cm, and 204,000–219,000 hectares for a sea level rise of 53 cm scenarios, respectively. To bring the saltwater intrusion under the sea level rise of 22 cm back to the baseline level, 100,000–150,000 hectares of currently cultivated rice would need to be fallowed at least once a year. This is equivalent to annual economic losses, with a 50% chance, ranging from $100.03–$176.67 million, implying a substantial economic cost of sea level rise-induced saltwater intrusion even under a modest sea level rise scenario. Under the sea level rise of 53 cm scenario, the results show that widespread adoption of alternate wetting and drying and approximately 300,000 ha of land-fallowing would be needed to push saltwater intrusion back to the baseline level. The findings indicate that saltwater intrusion in the Mekong Delta is more likely than not to intensify considerably and is much less predictable, posing a greater risk to one of the most important rice-producing regions in the world. Full article

The Moderate Resolution Imaging Spectroradiometer (MODIS) provides consistent long-term satellite observations that are valuable for rice mapping and production estimation through phenology extraction. This study evaluates the effectiveness of three MODIS products, MOD09GQ (1-day), MOD09Q1 (8-day), and MOD13Q1 (16-day), for mapping rice phenology in An Giang Province, a key rice-producing region in Vietnam’s climate-sensitive Mekong River Delta (MRD). The analysis focuses on rice cropping seasons from 2019 to 2021, using time series of the Normalized Difference Vegetation Index (NDVI) to capture temporal and spatial variations in rice growth dynamics. To address data gaps due to persistent cloud cover and sensor-related noises, smoothing techniques, including the Double Logistic Function (DLF) and Savitzky–Golay Filtering (SGF), were applied. Thirteen phenological parameters were extracted and used as inputs to an unsupervised K-Means clustering algorithm, enabling the classification of distinct rice growth patterns. The results show that DLF-processed MOD09GQ data most accurately reconstructed NDVI time series and captured short-term phenological transitions, outperforming coarser-resolution products. The resulting phenology maps could be used to correlate the influence of anthropogenic factors, such as the widespread adoption of short-duration rice varieties and shifts in water management practices. This study provides a robust framework for phenology-based rice mapping to support food security, sustainable agricultural planning, and climate resilience in the MRD. Full article

The Vietnamese Mekong Delta (VMD) faces increasing challenges due to upstream hydrological fluctuations and climate change, necessitating optimized water management strategies. Sluice gates play a critical role in regulating water levels, yet their effectiveness under different operational modes remains insufficiently assessed. This study examines water level fluctuations under three sluice gate operation scenarios implemented along the West Sea dike in the Long Xuyen Quadrangle, Kien Giang Province, using the MIKE 11 hydrodynamic model. The model was calibrated and validated using the observed data, yielding high accuracy at key sluice gates, including Kien River and Ba Hon. Three sluice gate management scenarios were tested: (1) the current automatic and partially forced operation, (2) fully automatic gate control, and (3) fully forced hydraulic operation. The simulation results indicate that Scenario 3 maintained water levels above +0.6 m more frequently, ensuring better water availability for irrigation and domestic use, while Scenarios 1 and 2 resulted in lower water levels at certain locations. Additionally, forced operation led to higher gate opening and closing frequencies at key sluices, allowing for more adaptive control over water levels. These findings emphasize the benefits of proactive sluice gate management in improving water regulation and mitigating the water scarcity risks. This study is among the first to provide empirical, scenario-based evidence comparing fully forced, automatic, and mixed sluice gate strategies under varying hydrological conditions in the Long Xuyen Quadrangle. Full article

Physiological disorders (PDs) in durian lead to reduced commodity prices; therefore, reducing the PD rate in durian enhances the fruit’s value and farmers’ profits. Nutrient and soil management may affect the PD rate during fruit development. Herein, we used amendments such as organic manure (OM) and foliar fertilization (FF) applications to reduce the PD rate and improve the soil health and fruit yield of durian. This study was conducted in three durian orchards in the Vietnamese Mekong Delta from 2022 to 2024. The treatments were as follows: (i) control (unamended), (ii) OM, (iii) FF, and (iv) OM + FF. N−P−K fertilizers (0.45 kg of N, 0.45 kg of P, and 0.45 kg of K per tree) were uniformly applied to all durian trees. We measured the characteristics of the soil, such as the soil pH, soil organic carbon (SOC), available phosphorus (AP), and exchangeable cations (K⁺ and Ca²⁺). The leaf nutrient (K and Ca) content, fruit yield (kg tree⁻¹), and fruit quality (PD rate, total soluble solids (TSS), and aril color characteristics) were also recorded. Our study indicates that OM + FF increased soil pH and SOC, AP, and exchangeable cations (K⁺ and Ca²⁺). In addition, the K and Ca concentrations in durian leaves increased by approximately 4% using OM + FF. Combining OM and FF decreased the PD rate of durian fruit (>85%) compared with the control. This practice increased the fruit quality TSS (13%), color, proportion of arils, and fruit yield (~10%) compared with conventional practice (control). Overall, using OM and FF contributed to improving durian production and values. Therefore, we recommend that farmers who cultivate durian apply OM + FF to their orchards to enhance soil health, fruit quality, and yield. Full article