Abstract
Rivers worldwide are facing an escalating risk of devastating floods driven by climate change, despite the extensive regulation of human infrastructures. Previous large-scale analyses of floods have reconstructed global and regional patterns by accounting for reservoir regulation; however, the critical role of levees remains largely ignored. Here, we provide a timely assessment of infrastructure-driven flood dynamics by simulating the joint influence of dams and levees across the Yangtze River Basin during 1980–2019 using the CaMa-Flood model. Results clarify the distinct and complementary roles of these structures: levees rectify peak-flow fidelity (median Nash–Sutcliffe Efficiency 0.62 at 32 validated flow stations) while dams primarily enhance low-flow accuracy (median logNSE 0.71). Ignoring levees results in a ~ 15% overestimation of annual maximum inundation area relative to dam-only assessments. Despite parameterization uncertainties, this study provides the first insights highlighting the critical role of integrating levees to accurately simulate regulated river systems and flood risk assessments.
Data availability
The data generated during this study are available upon reasonable request from the corresponding author.
Code availability
The codes are available upon reasonable request from the corresponding author.
References
Gudmundsson, L. et al. Globally observed trends in mean and extreme river flow attributed to climate change. Science 371, 1159–1162. https://doi.org/10.1126/science.aba3996 (2021).
Gou, J. J. et al. Sensitivity analysis-based automatic parameter calibration of the VIC model for streamflow simulations over China. Water Resour. Res. 56(1), e2019WR025968 (2020).
Manandhar, B., Cui, S., Wang, L. & Shrestha, S. Urban flood hazard assessment and management practices in South Asia: A review. Land 12(3), 627. https://doi.org/10.3390/land12030627 (2023).
Lehner, B. et al. High-resolution mapping of the world’s reservoirs and dams for sustainable river-flow management. Front. Ecol. Environ. 9, 494–502. https://doi.org/10.1890/100125 (2011).
Shen, Y., Nielsen, K., Revel, M., Liu, D. & Yamazaki, D. Res-CN (Reservoir dataset in China): Hydrometeorological time series and landscape attributes across 3254 Chinese reservoirs. Earth Syst. Sci. Data 15, 2781–2808. https://doi.org/10.5194/essd-15-2781-2023 (2023).
Coerver, H. M., Rutten, M. M. & van de Giesen, N. C. Deduction of reservoir operating rules for application in global hydrological models. Hydrol. Earth Syst. Sci. 22, 831–851. https://doi.org/10.5194/hess-22-831-2018 (2018).
Shen, Y., Yamazaki, D., Pokhrel, Y. & Zhao, G. Improving global reservoir parameterizations by incorporating flood storage capacity data and satellite observations. Water Resour. Res. 61, e2024WR037620. https://doi.org/10.1029/2024WR037620 (2025).
Sabaj Pérez, M. H. Where the Xingu bends and will soon break. Am. Sci. 103(6), 395–403 (2015).
Timpe, K. & Kaplan, D. The changing hydrology of a dammed Amazon. Sci. Adv. 3(11), e1700611 (2017).
Räsänen, T. A. et al. Observed river discharge changes due to hydropower operations in the upper Mekong Basin. J. Hydrol. 545, 28–41. https://doi.org/10.1016/j.jhydrol.2016.12.023 (2017).
Cochrane, T. A., Arias, M. E. & Piman, T. Historical impact of water infrastructure on water levels of the Mekong River and the Tonle Sap system. Hydrol. Earth Syst. Sci. 18(11), 4529–4541 (2014).
Gao, B., Yang, D. & Yang, H. Impact of the Three Gorges Dam on flow regime in the middle and lower Yangtze River. Quat. Int. 304, 43–50. https://doi.org/10.1016/j.quaint.2012.11.023 (2013).
Liang, X., Lettenmaier, D. P., Wood, E. F. & Burges, S. J. A simple hydrologically based model of land surface water and energy fluxes for general circulation models. J. Geophys. Res. Atmos. 99(D7), 14415–14428. https://doi.org/10.1029/94JD00483 (1994).
Arnold, J. G., Srinivasan, R., Muttiah, R. S. & Williams, J. R. Large area hydrologic modeling and assessment Part I: Model development. JAWRA J. Am. Water Resour. Assoc. 34(1), 73–89. https://doi.org/10.1111/j.1752-1688.1998.tb05961.x (1998).
Perrin, C., Michel, C. & Andréassian, V. Improvement of a parsimonious model for streamflow simulation. J. Hydrol. 279(1–4), 275–289. https://doi.org/10.1016/S0022-1694(03)00225-7 (2003).
Shin, S. et al. High-resolution modeling of river-floodplain-reservoir inundation dynamics in the Mekong River Basin. Water Resour. Res. 56(5), e2019WR026449. https://doi.org/10.1029/2019WR026449 (2020).
Dong, N. et al. Model estimates of China’s terrestrial water storage variation due to reservoir operation. Water Resour. Res. 58(6), e2021WR031787. https://doi.org/10.1029/2021WR031787 (2022).
Boulange, J., Hanasaki, N., Yamazaki, D. & Pokhrel, Y. Role of dams in reducing global flood exposure under climate change. Nat. Commun. 12(1), 417. https://doi.org/10.1038/s41467-020-20704-0 (2021).
Pinter, N. One step forward, two steps back on U.S. floodplains. Science 308(5719), 207–208. https://doi.org/10.1126/science.1108411 (2005).
Czech, W., Radecki-Pawlik, A., Wyżga, B. & Hajdukiewicz, H. Modelling the flooding capacity of a Polish Carpathian river after channelization and levee reconstruction. J. Hydrol. Hydromech. 64(2), 97–106. https://doi.org/10.1515/johh-2016-0010 (2016).
USACE (U.S. Army Corps of Engineers). National Levee Safety Program Interim Report. U.S. Army Corps of Engineers. (2018). https://www.usace.army.mil/Missions/Civil-Works/Levee-Safety-Program/
Wing, O. E. J. et al. A new automated method for improved flood defense representation in large‐scale hydraulic models. Water Resour. Res. 55(12), 11007–11034. https://doi.org/10.1029/2019WR025957 (2019).
Özer, I. E., Rikkert, S. J. H., van Leijen, F. J., Jonkman, S. N., & Hanssen, R. F. Sub-millimeter SAR interferometry for dike monitoring: Doetinchem case study. In Proceedings of the ESA Living Planet Symposium, Milan, Italy. (2019).
Sofia, G., Fontana, G. D., Ronchi, C. & Dallamura, F. Flood dynamics in urban areas: Data and modeling. J. Hydrol. 517, 428–439. https://doi.org/10.1016/j.jhydrol.2014.05.052 (2014).
Do, H. X. et al. Mapping the world’s river levees: A hyper‐resolution levee database based on digital elevation models. Geophys. Res. Lett. 52(11), e2024GL114121. https://doi.org/10.1029/2024GL114121 (2025).
Di Baldassarre, G. et al. An interdisciplinary assessment of private sector engagement in flood risk management in Europe. Hydrol. Earth Syst. Sci. 22(10), 5629–5646. https://doi.org/10.5194/hess-22-5629-2018 (2018).
Moftakhari, H. R., AghaKouchak, A., Sanders, B. F., Wood, R. R. & Matthew, R. A. Linking statistical and hydrodynamic modeling for compound flood hazard assessment in tidal channels and estuaries. Adv. Water Resour. 128, 28–38. https://doi.org/10.1016/j.advwatres.2019.04.009 (2019).
Gharari, S. et al. A flexible framework for simulating the water balance of lakes and reservoirs from local to global scales: MizuRoute‐Lake. Water Resour. Res. 60(5), e2022WR032400. https://doi.org/10.1029/2022WR032400 (2024).
Hanazaki, R., Yamazaki, D. & Yoshimura, K. Development of a reservoir flood control scheme for global flood models. J. Adv. Model. Earth Syst. 14(4), e2021MS002944. https://doi.org/10.1029/2021MS002944 (2022).
Zhao, G. et al. Developing a levee module for global flood modeling with a reach‐level parameterization approach. Water Resour. Res. 61(8), e2024WR039790. https://doi.org/10.1029/2024WR039790 (2025).
Li, X., Zhang, Q. & Xu, C. Spatiotemporal evolution of 1998 extreme flood event in the Yangtze River Basin based on hydrological modeling. J. Hydrol. Reg. Stud. 53, 101832. https://doi.org/10.1016/j.ejrh.2024.101832 (2025).
Yamazaki, D., Kanae, S., Kim, H. & Oki, T. A physically based description of floodplain inundation dynamics in a global river routing model. Water Resour. Res. 47(4), W04501. https://doi.org/10.1029/2010WR009726 (2011).
Zhou, X., Yamazaki, D., Zhao, G., Yoshimura, K. & Hirabayashi, Y. Benchmark framework for global river models. J. Adv. Model. Earth Syst. 16(3), e2024MS004379. https://doi.org/10.1029/2024MS004379 (2025).
Bates, P. D., Horritt, M. S. & Fewtrell, T. J. A simple inertial formulation of the shallow water equations for efficient two-dimensional flood inundation modelling. J. Hydrol. 387(1–2), 33–45. https://doi.org/10.1016/j.jhydrol.2010.03.027 (2010).
Gao, H. Global reservoir surface area dataset (GRSAD) (Version 1.0). Texas Data Repository. (2020) https://doi.org/10.18738/T8/DF80WG.
Yigzaw, W. et al. Global reservoir geometry database. Zenodo https://doi.org/10.5281/zenodo.1322884 (2018).
Shin, S., Pokhrel, Y. & Miguez-Macho, G. High-resolution modeling of reservoir release and storage dynamics at the continental scale. Water Resour. Res. 55(1), 787–810. https://doi.org/10.1029/2018WR023025 (2019).
Arnold, J. G., Moriasi, D. N., Gassman, P. W., Abbaspour, K. C., White, M. J., Srinivasan, R., ... & Jha, M. K. (2012). SWAT: Model use, calibration, and validation. Transactions of the ASABE. 55(4), 1491–1508.
Warren, I. R. & Bach, H. MIKE 21: a modelling system for estuaries, coastal waters and seas. Environ. Softw. 7(4), 229–240 (1992).
Shustikova, I., Domeneghetti, A., Neal, J. C., Bates, P. & Castellarin, A. Comparing 2D capabilities of HEC-RAS and LISFLOOD-FP on complex topography. Hydrol. Sci. J. 64(14), 1769–1782 (2019).
Tang, R., Dai, Z., Mei, X. & Lou, Y. Joint impacts of dams and floodplain on the rainfall-induced extreme flood in the Changjiang (Yangtze) River. J. Hydrol. 627, Article 130428. https://doi.org/10.1016/j.jhydrol.2023.130428 (2023).
Funding
This work was supported by the Fundamental Research Program of Shanxi Province (Grant numbers [202303021211196])(X.S.), the Teaching Reform and Innovation Project of Higher Education Institutions in Shanxi Province in 2024 (No. J20241550) (X.S.), the Key Laboratory of Transparent Mine Geology and Digital Twin Technology, National Mine Safety Administration Open Topics (No.SYSKT-2025-6)( P.R.), the Research Program of Northwest Institute of Eco-environment Resources of Chinese Academy of Sciences (Project No. HF2025-R&D-722)(Y.L.). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Author information
Authors and Affiliations
Contributions
S.X. and L.T. collected and analyzed the research data and wrote the original draft. S.X., H.S. and L.T. designed and applied the models of the research, H.S. generated the figures in the main manuscript. L.Z., J.H., R.P., L.Y. and X.X. contributed to data collection and manuscript revision. L.T. supervised the project. All authors have read and approved the final manuscript.
Corresponding author
Ethics declarations
Competing interests
The authors declare no competing interests.
Additional information
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.
About this article
Cite this article
Xu, S., Sun, H., Zhang, L. et al. Compound effects of dams and levees reshape Yangtze flood dynamics and reveal substantial risk misestimations from ignoring levees. Sci Rep (2026). https://doi.org/10.1038/s41598-026-41694-x
Received:
Accepted:
Published:
DOI: https://doi.org/10.1038/s41598-026-41694-x
