Ten years of biogeochemical monitoring in the highly urbanized tropical Saigon-Dong Nai River estuary (2015-2025), Vietnam

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Ten years of biogeochemical monitoring in the highly urbanized tropical Saigon-Dong Nai River estuary (2015-2025), Vietnam
Le, Thi-Minh-Tam; Nguyen, Truong An; Nguyen, Trung-Tin; Strady, Emilie; Nguyen, Tuyet T.n.; Baduel, Christine; Némery, Julien, 2026, "Ten years of biogeochemical monitoring in the highly urbanized tropical Saigon-Dong Nai River estuary (2015-2025), Vietnam", https://doi.org/10.23708/KMFNNY, DataSuds, V2, UNF:6:X1d17YeJuDGvEFYAzNpVCQ== [fileUNF]
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Description
This dataset comprises quality-controlled biogeochemical observations from the Saigon-Dong Nai River estuary collected over a 10-year period (July 2015 - July 2025). The monitoring program addresses a critical data gap in Southeast Asian tropical estuaries by providing sustained, high-frequency measurements across the freshwater-to-marine continuum in the Ho Chi Minh City metropolitan region.

The dataset includes two complementary components:
  • (1) Fixed-station time series: biweekly sampling at four stations (HA, PC, BD, BK) spanning upstream-to-estuarine gradients, yielding 894 observations from 225 campaigns over 10 years.
  • (2) Longitudinal transects: seasonal surveys at 27 sites covering 140 km of the river-estuary system, comprising 162 observations from 13 campaigns (2017-2022).
Parameters measured (20 total): Temperature, pH, dissolved oxygen, electrical conductivity, salinity, oxidation-reduction potential, total suspended solids, nitrate, ammonium, total nitrogen, phosphate, total phosphorus, dissolved silicate, dissolved organic carbon, particulate organic carbon, total organic carbon, chlorophyll-a, and total alkalinity (2020-2025).

All measurements include parameter-specific quality control flags (5-tier system) documenting data quality, analytical precision, and gap explanations. Overall data completeness is 96.6% (flags 1-3), with 83.8% classified as Good quality (flag 1). The dataset provides approximately 20,000 individual measurements with complete metadata, reproducible processing code, and comprehensive documentation. (2026-02-06)
Subject Earth and Environmental Sciences
Keyword biogeochemistry, water quality, time series, South East Asia, Vietnam, Ho Chi Minh City, Dong Nai River, Saigon River, eutrophication, nutrients, tropical estuary, urban river, nutrient cycles, carbon cycle, long-term monitoring, dissolved organic carbon
Related Publication Le, T.-M.-T., Nguyen, T.-A., Nguyen, T.-T., Nguyen, T.T.N., Strady, E., Baduel, C., & Némery, J. (in prep) "Ten years of biogeochemical monitoring in the highly urbanized tropical Saigon-Dong Nai River estuary (2015-2025), Vietnam ", Earth System Science Data.
Notes This research was supported by the International Joint Laboratory CARE (Asian Center for Water Research), which facilitated the long-term collaboration enabling this dataset.
Some additional financial support for analysis was obtained from :
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README.txt
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Published Mar 5, 2026
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MD5: 1a51b70055abea9c0e273ee61a8c6c04
Master overview of the folder structure and files. This archive contains quality-controlled biogeochemical observations from the Saigon-Dong Nai River estuary collected from July 2015 to July 2025.
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ReadMe_10_23708_KMFNNY.txt
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Published Mar 5, 2026
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MD5: 1e54bbda364c0e6e80a4390b7affbd55
contains the citation, description and conditions of use, or even access, depending on the case, to the dataset
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01_analyze_grqa_global_bias.py
code/Python Source Code - 19.8 KB
Published Mar 5, 2026
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MD5: 5efae69ee4bc4dea8bf4211e975225c1
- Generate manuscript Figure 1 (global monitoring coverage map) - OUTPUT: grqa_coverage_and_bias.png, grqa_asia_subregions_stacked.png
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02_qc_flags.py
code/Python Source Code - 15.4 KB
Published Mar 5, 2026
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MD5: 7b6691de2a2138e42ab91ba31d80a9d9
- INPUT: SDNR_*_standardized.csv (included in ../data/) - Applies quality control rules (outlier detection, range checks) - Enforces stoichiometric constraints (TN ≥ DIN, TP ≥ PO4) - Assigns 5-tier QC flags (1=Good → 5=Rejected) - Generates flag_overall column - OUTPUT: SDNR_*_QC.csv (final products in ../data/)
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03_export_good.py
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MD5: 45f1c783248e9cb6f1534dc4381240bc
- Exports flag==1 subset (optional) - Useful for users wanting only Good data
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03_tables.py
code/Python Source Code - 9.9 KB
Published Mar 5, 2026
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MD5: ea086b59b899ff44382454ff1b7ce85c
- INPUT: SDNR_*_QC.csv - Generates gap audit tables - Creates data completeness summary - OUTPUT: gap_audit_*.csv, data_completeness_summary.csv
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04_figures_qc.py
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Published Mar 5, 2026
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MD5: 0e4495fcb31a90e54ba2355fa854369d
- INPUT: SDNR_*_QC.csv - Generate all manuscript figures
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05_figures_timeseries.py
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MD5: 8d6c9d6fcc4f157728a0ae0bcc6d1a71
- INPUT: SDNR_*_QC.csv - Generate all manuscript figures
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06_tables_results.py
code/Python Source Code - 18.2 KB
Published Mar 5, 2026
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MD5: 2734be52bc574253299bb04c5d70b952
- INPUT: SDNR_*_QC.csv - Generates statistical summary tables - Seasonal/spatial comparisons, trends
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07_figures_seasonal_climatology.py
code/Python Source Code - 12.0 KB
Published Mar 5, 2026
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MD5: ba958a27618548fec96b4f52191f994b
- INPUT: SDNR_*_QC.csv - Generate all manuscript figures
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