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

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Abstract

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.

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Data Availability

The data used in this study can be requested from the corresponding author upon reasonable request.

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Funding

This research is funded by Vietnam National Foundation for Science and Technology Development (NAFOSTED) under grant number 105.06-2017.320 and the Vietnam basic science development program in the fields of Chemistry, Life Science, Earth Science and Marine Science for the period 2017–2025 under grant number ĐTĐL.CN-56/21.

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Authors and Affiliations

  1. Water Resources Institute, 8 Phao Dai Lang, Dong Da, Hanoi, 10000, Vietnam

    Anh Phuong Tran, Duong Hong Son, Nguyen Anh Duc & Manh Cuong Tran

  2. Thuyloi University, 175 Tay Son, Dong Da, HaNoi, 10000, Vietnam

    Pham Van Chien & Thanh Thuy Nguyen

  3. Technische Universität Dortmund - Fakultät Raumplanung, 10 August-Schmidt-Straße, 44227, Dortmund, Germany

    Nhat Anh Nguyen

  4. Faculty of Hydrology Meteorology and Oceanography, Vietnam National University, Hanoi, 334 Nguyen Trai, Thanh Xuan, Hanoi, 10000, Vietnam

    Phong V.V. Le

  5. Oak Ridge National Laboratory, 1 Bethel Valley Road, Oak Ridge, TN, 37830, USA

    Phong V.V. Le

  6. INTERA INC, 9600 Great Hills Trl Ste 300W, Austin, TX, 78759, USA

    Hai V. Pham

Authors
  1. Anh Phuong Tran
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  2. Duong Hong Son
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  3. Nguyen Anh Duc
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  4. Pham Van Chien
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  5. Thanh Thuy Nguyen
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  6. Manh Cuong Tran
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  7. Nhat Anh Nguyen
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  8. Phong V.V. Le
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  9. Hai V. Pham
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Contributions

A.P. Tran conceived of the presented idea and developed the theory. A.P. Tran, H.S. Duong, A.D. Nguyen, T.T. Nguyen, and N.A. Pham performed the numerical model computations and Bayesian data fusion; A.P. Tran and M.C. Tran processed and developed the relationship between satellite bands and salinity; A.P. Tran, H.S. Duong, V.H. Pham, Phong V.V. Le wrote the main manuscript with input from all authors; all authors reviewed the manuscript.

Corresponding author

Correspondence to Anh Phuong Tran.

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Tran, A.P., Son, D.H., Duc, N.A. et al. Bayesian merging of numerical modeling and remote sensing for saltwater intrusion quantification in the Vietnamese Mekong Delta. Environ Monit Assess 195, 1415 (2023). https://doi.org/10.1007/s10661-023-11947-7

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