The Utilization of a 3D Groundwater Flow and Transport Model for a Qualitative Investigation of Groundwater Salinization in the Ca Mau Peninsula (Mekong Delta, Vietnam)
Abstract
1. Introduction
- (a)
- “There is no lateral saline intrusion from the ocean into the deeper aquifer”.
- (b)
- “Different land use classes impact the salinity in the qh aquifer and contribute to the high spatial variability of the salinity in the qh aquifer”.
- (c)
- “Interannual variations in the surface water salinity in the river and channel system, as well as in mangrove, rice, and shrimp farming areas, could cause the high variability in the salinity in the qh aquifer”.
- (d)
- “Salinity variations in the deeper aquifers might be caused by the extraction of water during pumping”.
2. Study Area
3. Data Collection
- -
- Sampling campaigns at various observation wells in different aquifers, with the laboratory analysis of Total Dissolved Solids (TDS) since 2011 with two measurements per year (dry and rainy season);
- -
- Electrical Conductivity (EC) measurements (data logging sensor) with a calibration factor for TDS calculations, implemented since 2019, at various observation wells in different aquifers.
4. Methodology
4.1. Approach to Salinity Transport Modeling
4.2. Saline Intrusion Model Setup
- Infiltration from saline surface water sources (rivers, canals, aquaculture ponds, salt production, and tidal inundations) into the upper aquifers as identified by the land use map;
- Lateral saline intrusion from the offshore areas into the aquifer system induced by pumping, assuming that freshwater/saline water in deep aquifers is extrapolated from inland data up to 30 km offshore;
- Salinization by mixing and dispersion from areas with higher salinity to areas with lower salinity along the flow path;
- Downward or upward leakage from one aquifer to another through hydraulic windows in the aquitard, either naturally or from drilled wells. Although not included in the current model, this process is considered relevant to understanding salinity changes in the region.
4.2.1. Groundwater Flow Model
4.2.2. Mass Transport Model
Model Boundary Conditions
- (1)
- Seawater intrusion was implemented as Dirichlet BCs with defined concentrations. For Layer 1–Layer 5, representing aquifers qh and qp3, this was set to 35 g/L (similar to the current TDS of seawater), while for Layer 6–Layer 14, which represent the main exploited aquifers (freshwater to slightly brackish water), this was set to 3 g/L [38] at the model boundary offshore.
- (2)
- No boundary conditions for salinity were defined at the northern model boundary. As there is a flow boundary condition defined at the northern model boundary, the FEFLOW software automatically generates a salinity boundary condition to adapt the concentration of the inflowing water to maintain the concentration near the boundary.
- (3)
- The land use-based estimation of human activities influencing the salinity in the qh aquifer was determined using land use maps [39] ( Figure 7, left side). For most land use classifications, a constant salinity concentration BC was used (see Figure 7, right side) for the top layer and the qh aquifer depending on the predominant land use class in each region. At selected locations, these boundary conditions were refined to time-varying fixed-concentration BCs according to the interannual dynamics illustrated in Figure 8 with monthly data.
- (4)
- Surface water–groundwater interaction: The channel and river system in the CMP is strongly influenced by the tidal system of the ocean as well as seasonal (dry/rainy) interactions. The water levels in the river and channel system were interpolated from measurements based on the mean monthly change in the water level. In addition, we used the measured mean monthly salinity data (Ca Mau and Song Doc stations) to interpolate the interannual variation in the surface water bodies, mangrove, and semi-intensive shrimp and salt production zones and implemented them as time-varying fixed-concentration BCs (shown in Figure 8).
Initial Conditions
Dispersivity Parameter Adaptation
- The longitudinal dispersivity coefficients for homogeneous soil and layered heterogeneous sediments show that stratification affects the longitudinal dispersivity coefficient, and the longitudinal dispersivity coefficients for layered heterogeneous sediments are nearly half than those in homogeneous sediments [44,45,46,47].
- The longitudinal dispersion coefficient is influenced by the distance of travel, and its values undergo changes as the distance increases. In both homogeneous and layered heterogeneous sediments, the dispersion coefficient’s values increase by a factor of 2.5 with the expansion of the horizontal travel distance [47,48,49].
- There is also a dependency of the longitudinal dispersivity coefficient on the sediment type. From sand to clay, the longitudinal dispersion coefficient decreases with the smaller grain size of the material.
4.3. Limitations of the Model
5. Salinity Model Results
6. Discussion
6.1. Key Controls on Salinity Dynamics
6.2. Model Representation and Applicability
6.3. Management Strategies and Research Priorities
7. Conclusions
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Well Name | Aquifer | Longitudinal Dispersivity | Effective Porosity | Specific Storage | Average Filtration Velocity | Flow Distance | Location |
---|---|---|---|---|---|---|---|
αL (m) | ne (%) | µ (m−1) | V (m/min) | m | |||
CM2E (1) | n22 | 1.14 | 14.0 | 7.53 × 10−4 | 4.54 × 10−2 | Ca Mau | |
BL4D (2) | n22 | 0.02 | 16.0 | 4.58 × 10−3 | 4.20 × 10−3 | 8.0 | Bac Lieu |
BL2B (3) | qp2−3 | 0.12 | 19.4 | 5.58 × 10−4 | 8.90 × 10−4 | 8.0 | Bac Lieu |
IGPVN 1.4 (4) | n22 | 0.09–1.1 | 11.5–29.50 | 4.0–9.9 × 10−5 | 10.09 | Ca Mau | |
CHN5 (5) | qp1 | 2.5 | 32.00 | Hanoi |
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Hoan, T.V.; Richter, K.-G.; Dörr, F.; Bauer, J.; Börsig, N.; Steinel, A.; Le, V.T.M.; Pham, V.C.; Than, D.V.; Norra, S. The Utilization of a 3D Groundwater Flow and Transport Model for a Qualitative Investigation of Groundwater Salinization in the Ca Mau Peninsula (Mekong Delta, Vietnam). Hydrology 2025, 12, 126. https://doi.org/10.3390/hydrology12050126
Hoan TV, Richter K-G, Dörr F, Bauer J, Börsig N, Steinel A, Le VTM, Pham VC, Than DV, Norra S. The Utilization of a 3D Groundwater Flow and Transport Model for a Qualitative Investigation of Groundwater Salinization in the Ca Mau Peninsula (Mekong Delta, Vietnam). Hydrology. 2025; 12(5):126. https://doi.org/10.3390/hydrology12050126
Chicago/Turabian StyleHoan, Tran Viet, Karl-Gerd Richter, Felix Dörr, Jonas Bauer, Nicolas Börsig, Anke Steinel, Van Thi Mai Le, Van Cam Pham, Don Van Than, and Stefan Norra. 2025. "The Utilization of a 3D Groundwater Flow and Transport Model for a Qualitative Investigation of Groundwater Salinization in the Ca Mau Peninsula (Mekong Delta, Vietnam)" Hydrology 12, no. 5: 126. https://doi.org/10.3390/hydrology12050126
APA StyleHoan, T. V., Richter, K.-G., Dörr, F., Bauer, J., Börsig, N., Steinel, A., Le, V. T. M., Pham, V. C., Than, D. V., & Norra, S. (2025). The Utilization of a 3D Groundwater Flow and Transport Model for a Qualitative Investigation of Groundwater Salinization in the Ca Mau Peninsula (Mekong Delta, Vietnam). Hydrology, 12(5), 126. https://doi.org/10.3390/hydrology12050126