Bayesian merging of numerical modeling and remote sensing for saltwater intrusion quantification in the Vietnamese Mekong Delta.

Saltwater intrusion has become one of the most concerning issues in the Vietnamese Mekong Delta (VMD) due to its increasing impacts on agriculture and food security of Vietnam. Reliable estimation of salinity plays a crucial role to mitigate the impacts of saltwater intrusion. This study developed a hybrid technique that merges satellite imagery with numerical simulations to improve the estimation of salinity in the VMD. The salinity derived from Landsat images and by numerical simulations was fused using the Bayesian inference technique. The results indicate that our technique significantly reduces the uncertainties and improves the accuracy of salinity estimates. The Nash-Sutcliffe coefficient is 0.74, which is much higher than that of numerical simulation (0.63) and Landsat estimation (0.6). The correlation coefficient between the ensemble and measured salinity is relatively high (0.88). The variance of the ensemble salinity errors (5.0 ppt2) is lower than that of Landsat estimation (10.4 ppt2) and numerical simulations (9.6 ppt2). The proposed approach shows a great potential to combine multiple data sources of a variable of interest to improve its accuracy and reliability wherever these data are available.

Intensified salinity intrusion in coastal aquifers due to groundwater overextraction: a case study in the Mekong Delta, Vietnam.

Groundwater salinization is one of the most severe environmental problems in coastal aquifers worldwide, causing exceeding salinity in groundwater supply systems for many purposes. High salinity concentration in groundwater can be detected several kilometers inland and may result in an increased risk for coastal water supply systems and human health problems. This study investigates the impacts of groundwater pumping practices and regional groundwater flow dynamics on groundwater flow and salinity intrusion in the coastal aquifers of the Vietnamese Mekong Delta using the SEAWAT model-a variable-density groundwater flow and solute transport model. The model was constructed in three dimensions (3D) and accounted for multi-aquifers, variation of groundwater levels in neighboring areas, pumping, and paleo-salinity. Model calibration was carried for 13 years (2000 to 2012), and validation was conducted for 4 years (2013 to 2016). The best-calibrated model was used to develop prediction models for the next 14 years (2017 to 2030). Six future scenarios were introduced based on pumping rates and regional groundwater levels. Modeling results revealed that groundwater pumping activities and variation of regional groundwater flow systems strongly influence groundwater level depletion and saline movement from upper layers to lower layers. High salinity (>2.0 g/L) was expected to expand downward up to 150 m in depth and 2000 m toward surrounding areas in the next 14 years under increasing groundwater pumping capacity. A slight recovery in water level was also observed with decreasing groundwater exploitation. The reduction in the pumping rate from both local and regional scales will be necessary to recover groundwater levels and protect fresh aquifers from expanding paleo-saline in groundwater.

Upscaling of transport through discrete fracture networks via random walk: A comparison of models.

Many models have been created for upscaled transport modeling in discrete fracture networks (DFNs). Random walk examples of these are the Markov directed random walk (MDRW), Monte Carlo solution of the Boltzmann transport equation (BTE), and the spatial Markov model (SMM). Each model handles the correlation between the random walk steps using different techniques and has successfully reproduced the results of full-resolution transport simulations in DFNs. However, their predictive capabilities under different modeling scenarios have not been compared. We construct a set of random 2D DFNs for three different fracture transmissivity distributions to comparatively evaluate model performance. We focus specifically on random walk models to determine what aspects of the space and time step distributions (e.g., correlation and coupling) must be accounted for to get the most accurate predictions. For DFNs with low heterogeneity in fracture transmissivity, accounting for correlation generally leads to less accurate predictions of transport behavior, but as the fracture transmissivity distribution widens, preferential pathways form and correlation between modeling steps becomes important, particularly for early breakthrough predictions.

Gold nanorod/molybdenum sulfide core-shell nanostructures synthesized by a photo-induced reduction process.

Coupling of plasmonic nanostructures and semiconductors gives promising hybrid nanostructures that can be used in different applications such as photosensing and energy conversion. In this report, we describe an approach for fabricating a new hybrid material by coupling a gold nanorod (Au NR) core and amorphous molybdenum sulfide (MoSx) shell. The Au NR/MoSx core-shell structure is achieved by exploiting the hot electrons generated in the plasmonic excitation of Au NRs to drive the reduction of [MoS4]2-, which is pre-adsorbed on the Au NR surface, producing a thin MoSx layer. This approach allows us to control the thickness of the MoSx coating layer on the Au NR surface. The resultant Au NR/MoSx hybrid is characterized by absorption spectroscopy, scanning electron microscopy, transmission electron microscopy, energy-dispersive x-ray spectroscopy elemental mapping, x-ray diffraction and x-ray photoelectron spectroscopy.

Insights into the Electrochemical Polymerization of [Mo3 S13 ]2- Generating Amorphous Molybdenum Sulfide.

Amorphous molybdenum sulfide is an attractive electrode material for Li/Mg batteries and an efficient Pt-free catalyst for the hydrogen evolution reaction in water. By using the electrochemical quartz crystal microbalance (EQCM) analysis, new insights were gained into the electrochemical polymerization of the [Mo3 S13 ]2- cluster, which generates amorphous molybdenum sulfide thin films. In this work, it is shown that, at the anodic potential, a two-electron oxidative elimination of the terminal disulfide ligand within the [Mo3 S13 ]2- cluster induces the polymerization. A reductive elimination of the terminal disulfide ligand also occurs at the cathodic potential, inducing the polymerization. However, in sharp contrast to the anodic polymerization, according to which the film growth is rapid, the cathodic polymerization competes with the electrochemical reductive corrosion of the readily grown film, therefore occurring at a significant lower growth rate.

Bayesian Chance-Constrained Hydraulic Barrier Design under Geological Structure Uncertainty.

The groundwater community has widely recognized geological structure uncertainty as a major source of model structure uncertainty. Previous studies in aquifer remediation design, however, rarely discuss the impact of geological structure uncertainty. This study combines chance-constrained (CC) programming with Bayesian model averaging (BMA) as a BMA-CC framework to assess the impact of geological structure uncertainty in remediation design. To pursue this goal, the BMA-CC method is compared with traditional CC programming that only considers model parameter uncertainty. The BMA-CC method is employed to design a hydraulic barrier to protect public supply wells of the Government St. pump station from salt water intrusion in the "1500-foot" sand and the "1700-foot" sand of the Baton Rouge area, southeastern Louisiana. To address geological structure uncertainty, three groundwater models based on three different hydrostratigraphic architectures are developed. The results show that using traditional CC programming overestimates design reliability. The results also show that at least five additional connector wells are needed to achieve more than 90% design reliability level. The total amount of injected water from the connector wells is higher than the total pumpage of the protected public supply wells. While reducing the injection rate can be achieved by reducing the reliability level, the study finds that the hydraulic barrier design to protect the Government St. pump station may not be economically attractive.