Assess Hydrological Regime Changes in the Upper Da River under the Impacts of Climate Change and Socio-economic Development
Main Article Content
Abstract
The Da River, the principal tributary of the Red River system, plays a strategic role in hydropower generation and water supply for northern Vietnam. The hydrological regime of its upper basin has been increasingly influenced by the combined impacts of climate change and transboundary reservoir regulation. This study presents the first integrated assessment of these two factors within a unified SWAT-SUFI-2 modelling framework to evaluate the streamflow alterations in the upper Da River basin. Results indicate that under natural flow conditions without reservoir regulation, climate change intensifies flow extremes, with mean flood-season discharge increasing by approximately 2.5 times, while the number of low-flow months (Q < P₅) during the dry season rises 17 - fold compared with the baseline period (1980 - 2003). In contrast, during the reservoir operation phase (post-2007), the flood peak magnitude decreased by 17.5%, whereas dry-season discharge increased by 11.7%, effectively flattening the seasonal hydrograph. When both factors are considered jointly, reservoirs dominate the redistribution of seasonal flows, and climate change amplifies hydrological variability and extremes. This study provides the first quantitative evidence of the combined impacts of climate change and reservoir regulation on the transboundary Da River basin, offering a scientific basis for adaptive reservoir operation, data sharing, and integrated downstream water-risk management.
References
[2] M. Van Camp, K. Walraevens, O. Batelaan et al., Groundwater Resources in Transboundary Basins - Review of Assessments under the 1992 UNECE Water Convention in Central, Eastern and South-Eastern Europe, United Nations Economic Commission for Europe, Geneva, 2014.
[3] Y. Satoh, Y. Pokhrel, H. Kim et al., The Timing of Unprecedented Hydrological Drought under Climate Change, Nature Geoscience, Vol. 10, 2017, pp. 191-197,
https://doi.org/10.1038/ngeo2903.
[4] Z. Li, S. Liu, T. Nakayama et al., Large-Scale Hydrological Alterations in the Mekong and Yangtze River Basins, Nature Geoscience, Vol. 9, 2016, pp. 38-45, https://doi.org/10.1038/ngeo2586.
[5] X. Wang, Y. Ding, J. Xu et al., Transboundary Water Resources Management: Challenges and Opportunities, Springer Nature, Singapore, 2020.
[6] A. K. Gain, M. M. Hoque, S. Akter et al., Assessing the Flood Hazard Impacts of Dams and Climate Change in the Lower Mekong Basin, Natural Hazards, Vol. 114, No. 2, 2022, pp.11557-1579, https://doi.org/10.1007/s11069-022-05444-y.
[7] Y. Pokhrel, F. Felfelani, Y. Satoh et al., Global Terrestrial Water Storage and Drought Severity under Climate Change, Nature Climate Change, Vol. 11, 2021, pp. 226-233, https://doi.org/10.1038/s41558-020-00972-w.
[8] T. D. Dang, T. A. Cochrane, M. E. Arias, P. D. T. Van, Future Hydrological Alterations in the Mekong Delta Under the Impact of Water Resources Development, Land Subsidence and Sea Level Rise, Journal of Hydrology: Regional Studies, Vol. 15, 2018, pp. 119-133, https://doi.org/10.1016/j.ejrh.2018.01.002.
[9] A. Truong, M. T. Trinh, Study on the Impact of Climate Change on Surface Runoff Variation in the Nam Muc River Basin, Journal of Natural Resources and Environment, No. 20, 2018,
pp. 3-10, https://tapchi.hunre.edu.vn/index.php/tapchikhtnmt/article/view/82 (accessed on: August 14th, 2025) (in Vietnamese).
[10] T. M. H. Vu, Study on the Operation Regime of Water Storage for Son La and Hoa Binh Reservoirs, Vietnam National University, Hanoi, 2016 (in Vietnamese).
[11] T. T. A. Nguyen, Application of the SWAT Model and GIS Technology to Evaluate Streamflow in the Dak Bla River Basin, VNU Journal of Science: Earth and Environmental Sciences, Vol. 29, No. 3, 2013, pp. 1-13 (in Vietnamese).
[12] A. D. Nguyen, Study on the Application of the SWAT Model and SUFI-2 Algorithm for Parameter Identification and Simulation of Transboundary Inflows into Vietnam in the Da River Basin Using Global Datasets, Vietnam National University, Hanoi, 2021 (in Vietnamese).
[13] National Geographic Atlas of China, National Geographic Society, Washington, DC, ISBN 978-1-4262-0136-3, 2007, pp. 119.
[14] ESA (European Space Agency), WorldCover 2020 Product User Manual (Version 1.1), https://worldcover2020.esa.int/data/docs/WorldCover_PUM_V1.1.pdf (accessed on: August 2nd, 2025).
[15] ESA Climate Change Initiative, Land Cover (v2.1.1): European Space Agency Climate Change Initiative Data Portal, European Space Agency, 2021.
[16] Fao/Iiasa/Isric/Isscas/Jrc, Harmonized World Soil Database (Version 1.2), FAO, Rome, Italy, and IIASA, Laxenburg, Austria, 2012.
[17] FAO (Food and Agriculture Organization of the United Nations), Harmonized World Soil Database (Version 2.0),
https://www.fao.org/soils-portal/data-hub/soil-maps-and-databases/harmonized-world-soil-database-v20/en/ (accessed on: 2nd, 2025).
[18] DKRZ (German Climate Computing Center), ERA Data Access and Documentation Portal, https://docs.dkrz.de/doc/dataservices/finding_and_accessing_data/era_data/index.html (accessed on: August 14th, 2025).
[19] C. Song, C. Fan, J. Zhu, J. Wang, Y. Sheng, K. Liu, T. Chen, P. Zhan, S. Luo, C. Yuan, L. Ke, A Comprehensive Geospatial Database of Nearly 100,000 Reservoirs in China, Earth System Science Data, Vol. 14, 2022, pp. 4017-4034, https://doi.org/10.5194/essd-14-4017-2022.
[20] J. G. Arnold, R. Srinivasan, R. S. Muttiah, J. R. Williams, Large Area Hydrologic Modeling and Assessment: Part I - Model Development, Journal of the American Water Resources Association, Vol. 34, No. 1, 1998, pp. 73-89, https://doi.org/10.1111/j.1752-1688.1998.tb05961.x.
[21] K. C. Abbaspour, C. A. Johnson, M. T. Van Genuchten, Estimating Uncertain Flow and Transport Parameters Using a Sequential Uncertainty Fitting Procedure (SUFI-2), Vadose Zone Journal, Vol. 3, No. 4, 2004, pp. 1340-1352, https://doi.org/10.2136/vzj2004.1340.
[22] K. C. Abbaspour, SWAT-CUP 2012: SWAT Calibration and Uncertainty Programs - A User Manual, Swiss Federal Institute of Aquatic Science and Technology (Eawag), Dübendorf, Switzerland, 2015.
[23] D. N. Moriasi, J. G. Arnold, M. W. Van Liew, R. L. Bingner, R. D. Harmel, T. L. Veith, Model Evaluation Guidelines for Systematic Quantification of Accuracy in Watershed Simulations, Transactions of the Asabe, Vol. 50, No. 3, 2007, pp. 885-900, https://doi.org/10.13031/2013.23153.
[24] T. D. Dang, T. A. Cochrane, M. E. Arias, V. H. Dang, T. T. De Vries, Combined Impacts of Climate Change and Upstream Hydropower Development on Floodplain Inundation Dynamics in the Mekong Delta, Hydrology and Earth System Sciences, Vol. 27, No. 1, 2023, pp. 51-71, https://doi.org/10.5194/hess-27-51-2023.
[25] J. Wang, Y. Chen, Z. Li, Attribution of Streamflow Changes in the Brahmaputra River Basin: Climate Change or Human Activities?, Journal of Hydrology, Vol. 570, 2019, pp. 403-415, https://doi.org/10.1016/j.jhydrol.2018.12.052.
[26] L. Li, Q. Zhang, V. P. Singh, Changes in Streamflow Regime in the Yangtze River Basin under Human and Climate Influences, Journal of Hydrology, Vol. 585, 2020, pp. 124829, https://doi.org/10.1016/j.jhydrol.2020.124829.
[27] W. W. Immerzeel, A. F. Lutz, M. Andrade, A. Bahl, H. Biemans, T. Bolch, P. Wester, Importance and Vulnerability of the World’s Water Towers, Nature, Vol. 577, No. 7790, 2019, pp. 364-369, https://doi.org/10.1038/s41586-019-1822-y.