The Hoa Binh dam (HBD), located on a tributary of the Red River in Vietnam, has a capacity of 9.45 × 109 m3 and was commissioned in December 1988. Although it is important for flood prevention, electricity production and irrigation in northern Vietnam, the Hoa Binh dam has also highly influenced the suspended sediment distribution in the lower Red River basin, in the delta and in the coastal zone. Its impact was analysed from a 50-year data set of water discharge and suspended sediment concentration (1960–2010), and the distribution of water and sediment across the nine mouths of the delta was simulated using the MIKE11 numerical model before and after the dam settlement. Although water discharge at the delta inlet decreased by only 9%, the yearly suspended sediment flux dropped, on average, by 61% at Son Tay near Hanoi (from 119 to 46 × 106 t yr−1). Along the coast, reduced sedimentation rates are coincident with the lower sediment delivery observed since the impoundment of the Hoa Binh dam. Water regulation has led to decreased water discharge in the wet season (−14% in the Red River at Son Tay) and increased water discharge in the dry season (+12% at the same station). The ratios of water and suspended sediment flows, as compared to the total flows in the nine mouths, increased in the northern and southern estuaries and decreased in the central, main Ba Lat mouth. The increasing volume of dredged sediments in the Haiphong harbour is evidence of the silting up of the northern estuary of Cam–Bach Dang. The effect of tidal pumping on enhanced flow occurring in the dry season and resulting from changed water regulation is discussed as a possible cause of the enhanced siltation of the estuary after Hoa Binh dam impoundment.

In this study, we analyze sea surface height referenced against the WGS84 ellipsoid at the Hon Dau tidal gauge station (Hai Phong, Vietnam), in front of the Red River Delta, between 1961 and 2020. The annual sea level varied from 165.23 cm to 206.06 cm in this period (+20.28 cm over 60 years). The average water level was 190.87 cm for 60 years, with higher annual values in recent years, especially from 2016 to the present (above 201.5 cm). The Mann–Kendall (MK) test with Sen’s slope estimator and Şen’s innovative trend analysis (ITA) were applied and compared to estimate the sea level rise. These methods showed complete agreement among tests with significant rising trends of about 3.38 mm/year with the MK test and 3.08 mm/year with the ITA method for 1961–2020. During the last 20 years (2001–2020), the mean sea level increased about 7.16 mm/year (MK test and Sen’s slope), 7.38 mm/year (ITA method), and around twice higher than the rate of the region and globally. The MK test and ITA method provided similar results for periods: 1961–2020, 1961–1980, and 2001–2020, with relatively stable monotonic related trend conditions. For the period 1981–2000, with a more nonmonotonic trend, the MK test and ITA method provided different trends and allowed to illustrate the specificity of each method.

This study propose a new approach through which the landslide susceptibility in Quang Nam (Vietnam) will be estimated using the best model among the following algorithms: Decision Table (DT), Naïve Bayes (NB), Decision Table - Naïve Bayes (DTNB), Bagging Ensemble, Cascade Generalization Ensemble, Dagging Ensemble, Decorate Ensemble, MultiBoost Ensemble, MultiScheme Ensemble, Real Ada Boost Ensemble, Rotation Forest Ensemble, Random Sub Space Ensemble. In this regard, a map with 1130 landslide, was created and further partitioned into training (70%) and testing (30%) locations. The correlation-based features selections (CFS) method was used to select a number of 15 landslide influencing factors. Landslide locations, included in the training sample, and the landslide predictors were used as input data in order to run the above mentioned models. Kappa index, Accuracy (%) and ROC curve were employed to estimate the model’s performance and to test the outcomes provided by the models. Among the eleven machine learning algorithms, Random Sub Space Decision Table Naïve Bayes (RSSDTNB) was the most performant model with an AUC = 0.839, Accuracy = 76.55% and Kappa Index = 0.531. Therefore, this algorithm was involved in the estimation of landslide susceptibility. The Success Rate (AUC = 0.815) and Prediction Rate (AUC = 0.826) revealed the achievement of high-quality results.

The Mekong River is ranked as the 8th in terms of water discharge and as the 10th in terms of sediment load in the world. During the last 4500 years, its delta prograded more than 250 km to the south due to a tremendous amount of sediments deposited, and turned from a “tide-dominated” delta into a “wave-and-tide dominated” delta. This study aims at completing our knowledge on the fate of sediments that may be stored in estuarine or coastal systems, or dispersed over the continental shelf and slope. Sediment transport in the Mekong River Delta (MRD) coastal area was studied by numerical simulations using the Delft3D model. The model configuration was calibrated and validated from data collected in situ during 4 periods from 2012 to 2014. Then, 50 scenarios corresponding to different wave conditions (derived from the wave climate) and river discharge values typical of low flow and flood seasons enabled us to quantify the dispersal patterns of fluvial sediments close to the mouths and along the coast. Sediments mostly settled in the estuary and close to the mouths under calm conditions, and suspended sediment with higher concentrations extend further offshore with higher waves. Waves from the Southeast enhanced the concentration all along the MRD coastal zone. Waves from the South and Southwest induced coastal erosion, higher suspended sediment concentrations in front of the southern delta, and a net transport towards the Northeast of the delta. Because of episodes of Southern and Southwestern waves during the low flow season, the net alongshore suspended sediment transport is oriented Northeastward and decreases from the Southwestern part of the coastal zone (~960 × 10³ t yr⁻¹) to the Northeastern part (~650 × 10³ t yr⁻¹).

The Red River basin is a typical Asian river system affected by climate and anthropogenic changes. The purpose of this study is to build a tool to separate the effect of climate variability and anthropogenic influences on hydrology and suspended sediments. A modeling method combining in situ and climatic satellite data was used to analyze the discharge (Q) and suspended sediment concentration (SSC) at a daily time scale from 2000 to 2014. Scenarios of natural and actual conditions were implemented to quantify the impacts of climate variability and dams. The modeling gained satisfactory simulation results of water regime and SSC compared to the observations. Under natural conditions, the Q and SSC show decreasing tendencies, and climate variability is the main influence factor reducing the Q. Under actual conditions, SSC is mainly reduced by dams. At the outlet, annual mean Q got reduced by 13% (9% by climate and 4% by dams), and annual mean SSC got reduced to 89% (13% due to climate and 76% due to dams) of that under natural conditions. The climate tendencies are mainly explained by a decrease of 9% on precipitation and 5% on evapotranspiration, which results in a 13% decrease of available water for the whole basin.