Long-term water level dynamics in the Red River basin in response to anthropogenic activities and climate change.

Understanding the regular variations in water levels and identifying the potential drivers under the combined pressures of anthropogenic activities and climate change can offer valuable insights into riverine management. In this study, we analyzed long-term daily observational data, including water levels and water discharge, spanning from the ~1950s to 2021 at seven gauging stations within the Red River basin. We investigated the spatiotemporal variation in mean water levels using standard analytical tools, including the Mann-Kendall (MK) test, rating curves, and Empirical Orthogonal Function (EOF).

Identifying the impact of land use land cover change on streamflow and nitrate load following modeling approach: a case study in the upstream Dong Nai River basin, Vietnam.

Tri An Reservoir is a vital source of water for agriculture, industry, hydropower, and public usage in Southern Vietnam. Due to human activities, water eutrophication has become a serious problem in recent decades. This study investigated for the first time the impact of land use and land cover (LULC) change on streamflow and nitrate load from the upstream Dong Nai River basin, which is the largest watershed of the reservoir.

Radiation exposure in a region with natural high background radiation originated from rare earth element deposits at Bat Xat district, Vietnam.

Surface deposits of rare earth element (REE) were identified in the Bat Xat district, Northern Vietnam. As the area is inhabited, an in-depth investigation was carried out to assess the radioactivity levels and to evaluate the radiation exposure and radiological risks for the population. Samples of REE ore, soils, water and several foods locally produced were collected and analyzed by gamma spectrometry for determination of Th, Ra, and  K.

Comparing the performance of machine learning algorithms for remote and in situ estimations of chlorophyll-a content: A case study in the Tri An Reservoir, Vietnam.

Chlorophyll-a (Chl-a) is one of the most important indicators of the trophic status of inland waters, and its continued monitoring is essential. Recently, the operated Sentinel-2 MSI satellite offers high spatial resolution images for remote water quality monitoring. In this study, we tested the performance of the three well-known machine learning (ML) (random forest [RF], support vector machine [SVM], and Gaussian process [GP]) and the two novel ML (extreme gradient boost (XGB) and CatBoost [CB]) models for estimation a wide range of Chl-a concentration (10.

Estimation of nitrogen and phosphorus concentrations from water quality surrogates using machine learning in the Tri An Reservoir, Vietnam.

Surface water eutrophication due to excessive nutrients has become a major environmental problem around the world in the past few decades. Among these nutrients, nitrogen and phosphorus are two of the most important harmful cyanobacterial bloom (HCB) drivers. A reliable prediction of these parameters, therefore, is necessary for the management of rivers, lakes, and reservoirs.

Inland harmful cyanobacterial bloom prediction in the eutrophic Tri An Reservoir using satellite band ratio and machine learning approaches.

In recent years, Tri An, a drinking water reservoir for millions of people in southern Vietnam, has been affected by harmful cyanobacterial blooms (HCBs), raising concerns about public health. It is, therefore, crucial to gain insights into the outbreak mechanism of HCBs and understand the spatiotemporal variations of chlorophyll-a (Chl-a) in this highly turbid and productive water. This study aims to evaluate the predictable performance of both approaches using satellite band ratio and machine learning for Chl-a concentration retrieval-a proxy of HCBs.

Estimation of Radionuclide Concentrations and Average Annual Committed Effective Dose due to Ingestion for the Population in the Red River Delta, Vietnam.

Radioactivity concentrations of nuclides of the Th and U radioactive chains and K, Sr, Cs, and Pu were surveyed for raw and cooked food of the population in the Red River delta region, Vietnam, using α-, γ-spectrometry, and liquid scintillation counting techniques. The concentration of K in the cooked food was the highest compared to those of other radionuclides ranging from (23 ± 5) (rice) to (347 ± 50) Bq kg dw (tofu). The Po concentration in the cooked food ranged from its limit of detection (LOD) of 5 mBq kg dw (rice) to (4.