Truong An Dang

Purpose: As Vietnam accelerates its transition toward a sustainable energy future under ambitious national strategies like the Power Development Plan VIII (PDP8), a critical barrier persists: the lack of high-fidelity resource maps for strategic planning. This is particularly acute in data-scarce regions with high potential, such as Vietnam’s Central Highlands. This study aims to address this strategic gap by developing and validating a robust deep learning framework to produce an enhanced and detailed high-resolution wind energy map for this region, providing a conservative proof-of-concept for regional energy planning. Design/methodology/approach: The framework integrates coarse-resolution daily wind speed data from an ensemble of 11 global climate models with long-term observational records (1985–2023) from a sparse network of meteorological stations. To preserve synoptic extremes critical for wind power, the downscaling was conducted at a daily temporal resolution. A suite of advanced machine learning and deep learning models were systematically trained. To address the limitations of spatial interpolation in complex terrain, the downscaled 10 m wind speeds were extrapolated to a 149 m commercial hub-height using a terrain-aware power law, integrating high-resolution surface roughness data. A technical potential map (GWh/km²/year) was then generated by combining the turbine power curve (Enercon E-101) with a GIS-based availability index (AI), factoring in constraints such as elevation, slope, land cover and urban buffers. Findings: Deep learning architectures, particularly the convolutional neural network and XGBoost, significantly outperformed traditional models, achieving R-Pearson correlation coefficients exceeding 0.85 on daily predictions. Validation against ERA5 reanalysis data demonstrated that our ML-downscaled outputs substantially reduced severe negative biases present in ERA5 over complex terrain. The framework generated one of the most detailed wind energy maps for the region, identifying specific “hotspots” capable of generating significant yields (>6.0 GWh/km²/year) while strictly masking physically constrained zones. Projections under future shared socioeconomic pathways indicate that this wind resource potential is expected to remain robust. Originality/value: This study could provide a powerful, replicable methodological blueprint for de-risking renewable energy investment in data-scarce regions. By embedding high-resolution spatial covariates (DEM, roughness) into the vertical extrapolation rather than relying solely on 2D interpolation, it delivers an early, scientifically rigorous tool to guide national energy policy, optimize land-use planning and accelerate the sustainable expansion of wind energy for other regions in the country and abroad.

Offshore island and nearshore energy systems in southern Vietnam remain constrained by diesel dependence, fuel-logistics risks, and carbon emissions. This study applies a Delft3D-WAVE/SWAN framework forced by hourly ERA5 winds to quantify significant wave height (Hs), peak period (Tp), and finite-depth wave-power density at six strategic locations over 1995–2025. Model skill was evaluated against in situ acoustic wave and current observations. Hs performance was strong at Ca Mau (R = 0.90; Willmott d = 0.93) and moderate at Ben Tre (R = 0.70; d = 0.60), whereas Tp skill was weaker, especially at Ben Tre; wave-period-dependent results are therefore interpreted cautiously. A sharp east–west resource gradient was identified: Phu Quy had the highest mean power (13.87 kW/m) and P95 (60.10 kW/m), followed by Con Dao and Tra Vinh. Significant positive wave-power trends occurred at Phu Quy (+0.1436 kW/m/yr; p = 0.005), Tra Vinh (+0.0795 kW/m/yr; p < 0.001), and Vung Tau (+0.0563 kW/m/yr; p < 0.001). The dominant directional sector contributed 56.4–73.5% of annual energy at the eastern stations and exceeded 70% at Phu Quy and Con Dao. An equal-weight, min–max-normalized Long-term Suitability Score ranked Phu Quy and Tra Vinh first and second; both positions were stable when each criterion weight was varied by ±20%. The findings provide a multi-decadal resource-screening basis for marine spatial planning, while the device yield, future-climate response, and hybrid-system performance require dedicated techno-economic and scenario analyses.

Reliable island-scale wave-energy appraisal requires joint assessment of resource magnitude, spectral shape, directionality, persistence, and technology relevance. This study combines hourly Delft3D-WAVE/Simulating WAves Nearshore (SWAN) bulk outputs for 1995–2023 with native frequency–direction spectra for 2024–2025 at Phu Quy and Con Dao. The parent regional model was evaluated against hourly observations; significant-wave-height skill was strongest at Ca Mau (bias = 0.05 m, Root Mean Square Error (RMSE) = 0.09 m, Scatter Index (SI) = 0.24, R = 0.90), while mixed period skill remains a limitation. Year-held-out validation of the seasonal Tp–Te transfer yielded Te RMSE of 0.411–0.453 s at Phu Quy and 0.39–0.42 s at Con Dao, with annual available incident energy (AAE) errors from −1.30% to +1.15%. Excluding 2016 (91.5% coverage) left 28 valid years. Mean transferred incident flux and annual available incident energy were 11.7 kW m−1 and 102.9 MWh m−1 yr−1 at Phu Quy, versus 5.1 kW m−1 and 44.5 MWh m−1 yr−1 at Con Dao. Trend-free prewhitening indicated a positive Phu Quy AAE trend (p = 0.005), whereas Con Dao was not significant (p = 0.07); these model-derived proxies are not observed climate trends. The northeast monsoon supplied 78.0% and 82.5% of directly integrated spectral energy, respectively. At both sites, the dominant energy cell was Hm0 = 3–4 m and Te = 6–7 s, and about 70% of energy fell within a reciprocal ±30° axial window. Attenuator and terminator/overtopping archetypes achieved the highest central resource-shape scores, but overlapping Monte Carlo rank probabilities prevented unequivocal ranking.

Purpose: The Vietnamese Mekong Delta (VMD) is confronting a fundamental hydrological shift. This study aims to quantify this emerging hydrological normal by distinguishing the effects of upstream regulation from basin-wide climate variability. Design/methodology/approach: We analyzed daily discharge and rainfall data for 2000–2024 at Tan Chau and at upstream stations (Luang Prabang, Pakse, Mukdahan and Kratie). The analysis combines Mann–Kendall tests, Sen’s slope estimator, the range of variability approach (RVA), the hydrologic alteration factor (HAF) and Mann–Whitney U tests for the 2000–2009 baseline and 2010–2024 regulated period. Findings: The analysis reveals a profound hydrological homogenization of the annual hydrograph. Key findings include: While upstream rainfall trends were non-significant or decreasing (Z < 0), dry-season discharge increased significantly across upstream and mid-basin stations (e.g. + 110.0 m³/s/year at Luang Prabang), whereas Tan Chau showed no statistically significant trend, indicating downstream attenuation of the regulated signal; RVA analysis shows high alteration levels for discharge (HAF∼−0.87 to −1.00), whereas rainfall RVA/HAF includes some high-magnitude monthly values but is mostly not statistically significant in Mann–Whitney tests, supporting discharge-rainfall decoupling; The flood pulse has been severely dampened. Notably, the strong La Niña year of 2021 produced flood peaks 41.3% below the 2000–2008 baseline at Pakse and 25.5% below the baseline at Kratie, confirming that reservoirs are systematically overriding natural climate signals. Originality/value: The revised analysis shows that upstream regulation has reshaped the basin hydrograph most clearly in the upper and middle Mekong, while the delta gateway response is buffered by tributary inflows, Tonle Sap storage and channel-scale attenuation. This distinction provides a more defensible basis for adaptation planning in the VMD.

Relevance. Global climate change is intensifying hydro-meteorological extremes, posing significant threats to vulnerable regions. North-Central Vietnam, with its unique climatic and geographical characteristics, is particularly susceptible to shifts in rainfall patterns, yet it remains a relatively under-researched area. Understanding recent trends in rainfall and drought is critical for developing effective regional adaptation strategies. Aim. To provide a comprehensive analysis of the spatiotemporal dynamics of rainfall and meteorological drought in the North-Central Vietnam over the recent 25-year period (1998–2022). Specifically, it sought to quantify rainfall trends, characterize drought events, and investigate the paradoxical relationship between them. Methods. We analyzed monthly rainfall data from four representative meteorological stations. Trends were detected using the non-parametric Mann–Kendall test and their magnitudes were quantified by Sen's slope estimator. Meteorological drought was characterized using the 12-month Standardized Precipitation Index (SPI). Results. A statistically significant increasing trend in annual rainfall was found at two of the four stations, with rates up to 26.9 mm/year. Paradoxically, despite this wetting trend, the region experienced three major drought intervals (1999–2000, 2003–2004, and 2015–2016), including several events of extreme severity (SPI<–2.0). This coexistence of increasing total rainfall with severe droughts indicates a shift towards a more volatile climate regime, challenging conventional water resource management and highlighting the need for strategies that address both flood and drought risks. For citation: Tran Thi Tuyen, Dang Truong An. Spatiotemporal dynamics of rainfall and drought in North-Central Vietnam: trends, variability, and implications under a changing climate. Bulletin of the Tomsk Polytechnic University. Geo Assets Engineering, 2026, vol. 337, no. 4, pp. 84-91.

Vietnam’s Power Development Plan 8 (PDP8) identifies offshore wind power as a key pillar for carbon neutrality and long-term energy security. Realizing this potential requires accurate, high-resolution resource assessments to guide strategic planning and de-risk multi-billion-dollar investments. This study delivers the first scientifically validated, bias-corrected estimate of offshore wind energy potential in the strategic maritime region from Vung Tau to Ca Mau. Using the ERA5 reanalysis dataset (2011–2020), we apply a robust, monthly, component-wise regression method calibrated against long-term in-situ observations from two island stations. Raw, unvalidated ERA5 data are shown to grossly overestimate the resource, with mean annual Wind Power Density (WPD) inflated by more than 1.5–2.0 fold. After correction, data quality improves substantially: the overall Mean Bias Error (MBE) is reduced from 3.91 m/s to 0.38 m/s (by 90%), and the Root Mean Square Error (RMSE) drops by 75.0% (from 4.35 m/s to 1.09 m/s). The corrected dataset yields a realistic and conservative mean annual WPD at a 100-meter hub height of 90–290 W/m², compared with an unrealistic 140–460 W/m² from the raw data. These results provide a scientifically grounded baseline for Vietnam’s near-shore wind resource, clarify the limitations of using coastal-based observations to represent offshore conditions, and underscore the need for future offshore measurement campaigns to further reduce uncertainties and support the sustainable implementation of PDP8.

The Vietnamese Mekong Delta (VMD) is a region of immense socio-economic and ecological importance, that has experienced significant alterations to its hydrological regime. The objective of this study is to quantitatively disentangle and attribute these changes to their primary drivers: anthropogenic interventions from upstream civil works (UCWs) and climatic variability, particularly the El Niño-Southern Oscillation (ENSO). A 25-year (2000–2024) dataset of daily water discharge and local precipitation from key stations across the VMD was analyzed. The Oceanic Niño Index (ONI) was used as a proxy for ENSO events. A multi-method framework was employed, combining non-parametric trend analysis (Mann-Kendall test), Pearson’s correlation, and a multiple linear regression model. The VMD’s hydrology has been fundamentally reshaped and characterized by a significant increase in dry-season discharge (+45-48%) along with a decrease in rainy-season peak flows (-18-21%). The attribution analysis finds that UCWs are the dominant driver of these seasonal shifts, accounting for approximately 60–70% of the observed changes based on standardized regression coefficients. Climatic factors, primarily strong ENSO events, underlie the remaining 30–40% by modulating inter-annual variability. Local rainfall showed a minor but statistically significant contribution in the regression model, despite a weak direct correlation with discharge. By characterizing the VMD as a hybrid hydro-climatic system, the results underscore the need for adaptive transboundary water management in heavily modified and climate-sensitive deltas.

The Vietnamese Mekong Delta (VMD), a crucial region for rice cultivation, faces challenges from climate variability, including altered rainfall patterns, rising temperatures, and droughts, which pose risks of rain-fed water deficits. This study investigated the impacts of global climate change on irrigation water potential and irrigation water demand for rice paddies in the Plain of Reeds. The study applied the FAO-AquaCrop model to simulate irrigation water potential and irrigation water demand for the winter-spring, summer-fall, and fall-winter seasons under current climatic conditions (baseline) and future Representative Concentration Pathways - RCP4.5 and RCP8.5 scenarios for 2011-2040 (2025s), 2041-2070 (2055s), and 2071-2099 (2085s). The model was calibrated and validated against observed yield data from 2002-2023. The results indicate a general increase in irrigation water potential across seasons and sub-areas, with the winter-spring crop showing the most substantial rise (up to 65.7% by 2071-2099 under RCP8.5). Irrigation water demand also generally increased, particularly for the winter-spring crop, though RCP8.5 did not always result in higher demand than RCP4.5, suggesting complex climate-irrigation interactions. These findings highlight the need for adaptive water management and the potential of adjusting sowing schedules to mitigate increased irrigation water demand.

The Vietnamese Mekong Delta (VMD), a region of immense ecological and economic importance, faces unprecedented environmental pressures. This study provides a comprehensive analysis of shoreline dynamics along the VMD coast of Vinh Long province, focusing on the segment between the Co Chien and Bassac River mouths from 2009 to 2023. Utilizing a multi-temporal remote sensing approach with satellite imagery, shoreline changes were quantified to investigate the interplay of natural and anthropogenic drivers. Shorelines were extracted using an automated histogram thresholding method and standardized to the mean sea level (MSL) datum, enabling robust inter-annual comparisons. Results reveal a dominant erosional trend, with approximately 72.6% of the coastline experiencing retreat at a mean rate of -5.7 ± 6.9 m per year. To isolate coastal engineering impacts, the analysis specifically compared pre-2014 and post-2014 periods, marking the completion of the Duyen Hai Thermal Power Plant breakwater system and the Quan Chanh Bo canal groins. Pre-2014 changes were characterized by widespread erosion, primarily attributed to significant reductions in sediment supply from the Mekong River. In contrast, post-2014 shorelines exhibited a classic structural impact pattern: pronounced accretion in the northern section and accelerated erosion in the southern section. This pattern is strongly modulated by monsoonal seasons, with the energetic Northeast monsoon driving dominant southwestward longshore sediment transport, causing a larger sediment supply deficit along the southern shoreline. This research underscores the coast’s critical vulnerability to regional sediment deficits, locally exacerbated by engineering works, providing a scientific basis for sustainable coastal management.

Climate variability is expected to alter global temperatures and precipitation, significantly impacting cassava (Manihot esculenta) water requirements. This study investigated the impacts of climate variability on rainfed cassava in the Song Hinh district, Phu Yen province of Vietnam, utilizing the CSM-MANIHOT-Cassava (Version 4.8) crop simulation model. The model was calibrated and validated using local field data, demonstrating strong model performance (R2 up to 0.93, RMSE of 12.84%, and NRMSE of 2.74% for root yield validation). Future cassava water requirements were simulated for the Vu Xuan and Vu He cassava crops under RCP4.5 and RCP8.5 scenarios for the 2025s, 2055s, and 2085s time windows, relative to a climate baseline of 1986-2005 and a crop parameter baseline of 2001-2021. The results revealed divergent trends in the cassava water requirements. Under the moderate RCP4.5 scenario, total cassava water requirements were projected to decrease for both Vu Xuan (by 11.8 to 16.9%) and Vu He (by 9.0 to 13.7%). In contrast, the high-emission RCP8.5 scenario indicated a significant eventual increase by 2085, with requirements rising by 13.6% for Vu Xuan and 21.3% for Vu He. These findings highlight the critical need for adaptive solutions. Adjusting planting schedules to better align with changing rainfall patterns emerges as a key strategy to sustain cassava production. For instance, under future scenarios, particularly RCP8.5, strategic adjustments such as delaying planting for Vu Xuan and advancing planting for Vu He could optimize water use efficiency and sustain cassava production in the Song Hinh district.