This study examines the changing rainfall patterns in the Vietnamese Mekong Delta (VMD) utilizing observational data spanning from 1978 to 2022. We employ the Mann–Kendall test, the sequential Mann–Kendall test, and innovative trend analysis to investigate trends in annual, wet, and dry season rainfall, as well as daily rainfall events. Our results show significant spatial variations. Ca Mau, a coastal province, consistently showed higher mean annual and seasonal rainfall compared to the further inland stations of Can Tho and Moc Hoa. Interestingly, Ca Mau experienced a notable decrease in annual rainfall. Conversely, Can Tho, showed an overall decrease in some months of the wet season and an increase in dry season rainfall. Furthermore, Moc Hoa showed an increase in the number of rainy days, especially during the dry season. Principal component analysis (PCA) further revealed strong correlations between annual rainfall and extreme weather events, particularly for Ca Mau, emphasizing the complex interplay of geographic and climatic factors within the region. Our findings offer insights for policymakers and planners, thus aiding the development of targeted interventions to manage water resources and prepare for changing climate conditions.

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.

Climate change and river flow alterations in the Mekong River have significantly exacerbated drought conditions in the Vietnamese Mekong Delta (VMD). Understanding the temporal dynamics and propagation mechanisms of drought, coupled with the compounded impacts of human activities, is crucial. This study analyzed meteorological (1992–2021) and hydrological (2000–2021) drought trends in the Lower Mekong River Basin (LMB) using the Standardized Precipitation Index (SPI) and the Streamflow Drought Index (SDI), respectively, complemented by Mann–Kendall (MK) trend analysis. The results show an increasing trend of meteorological drought in Cambodia and Lao PDR, with mid-Mekong stations exhibiting a strong positive correlation with downstream discharge, particularly Tan Chau (Pearson r ranging from 0.60 to 0.70). A key finding highlights the complexity of flow regulation by the Tonle Sap system, evidenced by a very strong correlation (r = 0.71) between Phnom Penh and the 12-month SDI lagged by one year. Crucially, the comparison revealed a shift in drought severity since 2010: hydrological drought has exhibited greater severity (reaching severe levels in 2020–2021) compared to meteorological drought, which remained moderate. This escalation is substantiated by a statistically significant discharge reduction (95% confidence level) at the Chau Doc station during the wet season, indicating a decline in peak flow due to upstream dam operations. These findings provide a robust database on the altered hydrological regime, underlining the increasing vulnerability of the VMD and motivating the urgent need for comprehensive, adaptive water resource management strategies.

Aims: Reed (Phragmites autralis) is a plant species with a seasonal reproductive cycle, it has a very high biomass in U Minh Thuong National Park. in Vietnam. To evaluate fresh and dry biomass, then made of biochar on reed plants to use biochar products provide bio-organic fertilizer raw materials for watermelon plant in agriculture. Methods: To achieve that goal several experiments were performed as (1) investtigate the biomass of fresh and dry reeds and made of biochar by using the traditional method; (2) adsorption with pig urine and chemical fertilizer (nitrogen, phosphorus and potash) to see the retention of chemical coponents dispersed into the environment in the adsorbed biochar; (3) mix biochar with inorganic mineral fertilizers and peat to from some inorganic fertilizer – biochar formulas, then consider the chemical composition of that mixture; (4) using some mix biochar fertilizer to grow watermelon with local variety. Results: The results show that reeds can provide very high biomass to made of biochar fertilizer and reed biochar can adsorption the pig urine as ammonium, nitrate, nitrogen, phosphorus and it also adsorption inorganic as nitrogen, phosphorus and potash. So it is possible to propose the use study for planting watermelon and application treatment environment in the region polluted. Conclusions: Biomass and biochar of reed is very high, biochar can adsorb nitrogen, phosphorus and potash fertilizer; biochar can mixed peat and inorganic mineral fertilizer to planting watermelon in Mekong Delta. Implications of the research: With forest fire in U Minh Thuong national park every year by reed vegetation causing damage to property and human labor; Its research not only exploits renewable raw materials but also help control the risk of forest fires. Originality/valeu: This study the aim give the methods to control forest fires by product the biochar of reed (Phragmites autralis) U Minh Thuong national park of Vietnam, the species growing well the growth give biomass big volume on the rainny season and suplly dry material to made big forest fires on dry season in Vietnam.