Tran Van Ty

Multifunctional urban lakes provide ecosystem services but may accumulate plastic waste from surrounding activities. This study assessed plastic pollution along the shoreline and within a sampled bottom-deposition area of Bung Xang Lake, Can Tho City, Vietnam. Plastic represented 99.19% of shoreline litter abundance and 95.63% of dry mass. Exploratory omnibus tests yielded p-values of 0.023 and 0.031 for Abundance density and Mass density, respectively, but no Bonferroni-adjusted pairwise comparison was significant, and unverified transect independence limits between-site inference. All 12 shoreline transects were classified as Extremely Dirty by the Clean Coast Index and as Very High Abundance by the Plastic Abundance Index (PAI = 22.66–92.75). Plastic represented 97.68% of item abundance and 86.49% of dry mass among 560 bottom-litter items. Packaging Plastics dominated the bottom plastic assemblage; 91.77% of plastic items measured 100–500 mm, and all four bottom transects showed Very High Abundance under the operationally adapted PAI (19.71–31.62). The findings provide complementary evidence of plastic accumulation in two physical compartments of the same urban lake without establishing direct transport between them. The observed litter composition may inform management planning for the sampled areas, but specific sources, input fluxes, and intervention effectiveness require further investigation.

Riverbank erosion threatens settlements, infrastructure, and river-dependent livelihoods along the Bassac River in the Vietnamese Mekong Delta. This study examines long-term bankline change from 2001 to 2025 and develops expert-informed priorities for assessing livelihood vulnerability within the Can Tho reach. Six Landsat images were analysed in QGIS using the Linear Regression Rate method, while present-day hydraulic conditions were investigated through Acoustic Doppler Current Profiler measurements at five representative locations. An Analytic Hierarchy Process based on interviews with 10 experts was used to derive relative weights for livelihood sensitivity and adaptive-capacity indicators and variables. Accretion was more spatially extensive than erosion along both banks; however, the left bank experienced a greater total extent and magnitude of erosion. Spatially extensive erosion was identified in Binh Thuy, whereas more intense but localised hotspots occurred near Cai Rang and Cai Von. The exploratory hydraulic observations varied among the five selected locations but showed no consistent correspondence with historical erosion magnitude and are therefore interpreted only as a snapshot of conditions on the survey date. Experts assigned weights of 0.547 to sensitivity and 0.453 to adaptive capacity. Savings capacity, decreased food production, extent of land loss, and the ability to shift livelihoods were among the highest-ranked variables. The physical and expert-derived findings support a differentiated and staged approach to riverbank-risk management, but they should be interpreted as complementary evidence rather than as a household-level vulnerability assessment. Future research should combine repeated seasonal hydraulic and bathymetric surveys, bank-material investigations, exposed-asset mapping, and household-based vulnerability assessments.

Trong nghiên cứu này, bản đồ nguy cơ sạt lở cho sông Mái Dầm và rạch Xẻo Chồi thuộc hệ thống sông, kênh chính tại xã Châu Thành, thành phố Cần Thơ đã được xây dựng nhằm góp phần hỗ trợ công tác quản lý và quy hoạch ven bờ. Dựa trên khảo sát thực địa và nghiên cứu trước, bốn yếu tố chính gồm địa chất, hình thái dòng chảy, vận tốc dòng chảy và tải trọng ven bờ được lựa chọn để xây dựng các bản đồ thành phần. Dữ liệu tại các mặt cắt được nội suy trong môi trường hệ thống thông tin địa lý, việc phân cấp theo thang 5 mức nguy cơ và tích hợp bằng mô hình chồng lớp có trọng số được thực hiện dựa trên phương pháp phân tích thứ bậc. Kết quả cho thấy sông Mái Dầm có nguy cơ sạt lở cao với 41,3% chiều dài thuộc mức nguy cơ cao, rạch Xẻo Chồi có nguy cơ thấp hơn (17,6%). Bản đồ nguy cơ tổng hợp cho thấy điều kiện địa chất và tải trọng ven bờ là các yếu tố chi phối ổn định mái bờ. Phương pháp đề xuất có thể được áp dụng cho các hệ thống sông, kênh tương tự tại khu vực Đồng bằng sông Cửu Long.

Salinity intrusion has become a critical threat to agricultural stability and water resource management in the Vietnamese Mekong Delta (VMD), particularly in coastal regions. This study evaluates the efficacy of the Long Short-Term Memory (LSTM) neural network, a sophisticated deep learning (DL) architecture, for predicting salinity concentrations at two monitoring stations: Hung My and Tra Vinh. Using historical salinity data, the research explores the impact of varying the lookback window from 15- to 45-day and the forecast horizons (1- to 3-day) on model performance. Experimental results demonstrate that the 15-day lookback window provides the most robust temporal context, enabling the model to achieve high predictive accuracy for short-term horizons. For 1-day forecast horizon, the model achieved Nash–Sutcliffe Efficiency (NSE) values exceeding 0.85 and low Root Mean Square Error (RMSE) at both stations. However, a progressive decline in performance was observed as the lead time extended to 3-day forecast horizon, primarily due to increased prediction uncertainty and the inherent non-linearity of estuarine dynamics. A detailed analysis of the results reveals a consistent underestimation of extreme salinity peaks, a phenomenon attributed to the smoothing effect of the Mean Squared Error (MSE) loss function and the absence of real-time exogenous inputs such as wind speed and tidal pressure. These findings provide a valuable scientific foundation for developing early warning systems, offering actionable insights for farmers and supporting evidence-based decision-making for policymakers in managing salinity risks.

Drought is a recurrent hazard in the Vietnamese Mekong Delta (VMD), with major implications for agriculture, water resources, and rural livelihoods. This study assesses drought variability in Kien Giang Province, Vietnam, from 1992 to 2024 using two multiscale indicators: the Multivariate Standardized Precipitation Index (MSPI) and the Multivariate Standardized Precipitation Evapotranspiration Index (MSPEI). Principal Component Analysis (PCA) was applied to Standardized Precipitation Index (SPI)- and Precipitation Evapotranspiration Index (SPEI)-based time series spanning multiple accumulation periods (3–48 months) to derive integrated drought signals and to reduce redundancy across timescales. The results show that the first principal component (PC1) captured a high proportion of total variance across stations, indicating strong coherence in drought dynamics across the province. Both MSPI and MSPEI successfully identified major historical drought episodes, particularly the severe events of 2004–2005 and 2015–2016. However, the two indices differed in their temporal behaviour: MSPI responded more directly to precipitation deficits, whereas MSPEI showed slower post-drought recovery in recent years, suggesting greater sensitivity to evaporative demand and climatic water-balance stress. These differences indicate that evapotranspiration-sensitive indices may provide added analytical value in warming coastal environments. Overall, the combined multiscale framework offers a robust basis for drought monitoring, comparative assessment, and water-resource planning in Kien Giang and other drought-prone coastal delta settings.

Drought is an increasing threat to livelihood security and sustainable development in the Vietnamese Mekong Delta (VMD), particularly in Kien Giang Province. This study examines the spatiotemporal dynamics of meteorological drought from 1992 to 2024 using daily rainfall data from 10 rain gauges. The Standardized Precipitation Index (SPI) was calculated at 3-, 6-, and 12-month timescales to assess short-, medium-, and longer-term precipitation deficits across the province. The results show that the most severe drought events were concentrated in the most recent decade, especially during the 2015–2016 and 2019–2020 dry seasons. Spatial analysis identified clear drought hotspots: the northern coastal zone, including Ha Tien and Hon Dat, exhibited the strongest long-timescale drought signal, while central inland areas such as Go Quao experienced more frequent short-timescale drought conditions. A significant negative relationship was also observed between SPI and the Oceanic Niño Index (ONI), indicating that El Niño conditions intensified drought severity, particularly in coastal areas. These findings highlight the need for spatially differentiated drought adaptation in Kien Giang Province, with stronger emphasis on water storage and water-use efficiency in inland districts and on early warning and integrated drought–salinity management in high-risk coastal zones.

This study evaluates the spatiotemporal variations in surface water quality in An Giang province, a key upstream region of the Vietnamese Mekong Delta (VMD), under the influence of hydrological alterations and climate change impacts. Water quality data from 2010 to 2023 were collected from 10 monitoring stations along the Tien and Hau Rivers, focusing on key parameters including pH, temperature, Dissolved Oxygen (DO), Total Suspended Solids (TSS), Biological Oxygen Demand (BOD), Chemical Oxygen Demand (COD), Ammonium (N-NH₄⁺), Nitrate (NO₃⁻), orthophosphate (P-PO₄³⁻), and Coliforms. The Mann–Kendall test and Sen’s slope estimator were employed to detect long-term trends and quantify the magnitude of changes. The findings indicated that the Hau River exhibits significant organic pollution, evidenced by elevated levels of BOD and COD, alongside diminished levels of DO. The Tien River exhibits elevated concentrations of NH₄⁺ and total suspended solids (TSS). The MK test indicated that BOD, COD, and NH₄⁺ levels were increasing at most locations in a statistically significant manner. This indicates that the water quality deteriorated over time. The study revealed that the majority of pollutants exhibited statistically significant increasing trends (p ≤ 0.05). The Tien River’s COD is increasing by 1.6 mg/L annually, whereas the Hau River’s COD is escalating by 1.7 mg/L per year. The biochemical oxygen demand on both rivers is increasing by 0.5 mg/L each year. The diminishing quantities of dissolved oxygen indicated a decline in water quality. Pollutant concentrations demonstrated significant positive associations with maximum temperature (r = 0.47–0.64) and hours of sunshine (r ≈ 0.50–0.64). A significant negative correlation with river discharge was observed, particularly during the dry season (r = −0.79 to −0.88), when diminished flows resulted in elevated pollution concentrations. The findings offer measurable evidence that increasing temperatures and decreasing river flows significantly affect water quality, underscoring the necessity of adapting water resource management in the Mekong Delta.