Water (Feb 2024)

Future Changes in Hydro-Climatic Extremes across Vietnam: Evidence from a Semi-Distributed Hydrological Model Forced by Downscaled CMIP6 Climate Data

  • Hong Xuan Do,
  • Tu Hoang Le,
  • Manh-Hung Le,
  • Dat Le Tan Nguyen,
  • Nhu Cuong Do

DOI
https://doi.org/10.3390/w16050674
Journal volume & issue
Vol. 16, no. 5
p. 674

Abstract

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Flood hazards have led to substantial fatalities and economic loss in the last five decades, making it essential to understand flood dynamics in a warming climate. This study reports the first comprehensive assessment of projected flood hazards across Vietnam. We used downscaled climate data from the CMIP6 initiative, involving a total of 20 climate models, and streamflow projection simulated using a semi-distributed hydrological model. The assessment covers seven near-natural catchments, each representing a climate zone of the country. To evaluate climate change impacts on floods, the study simultaneously analyzes changes in three indices: (i) the annual hottest day temperature, to represent temperature extremes; (ii) the maximum daily rainfall amount, to represent rainfall extremes; and (iii) the discharge value exceeding 5% in a year, to assess streamflow extremes. Changes in the selected indices (relative to the reference period from 1985 to 2014) are assessed under four emission scenarios (SSP1–2.6, SSP2–4.5, SSP3–7.0, and SSP5–8.5) and two future time slices (2036–2065 and 2070–2099). Although the robustness (as indicated by multi-model agreement) and significance (identified through the statistical test) of the changes vary substantially, depending on the selected indices and assessed time slices, an overall increase is consistently identified across all of the assessed hydro-climatic extremes (up to 4.8 °C for temperature extremes, 43 mm for rainfall extremes, and 31% for streamflow extremes). The findings suggest a potential increase in flood risk across Vietnam in a warming climate, highlighting the urgent need for improved flood preparedness and investment to reduce economic loss and mortality in an uncertain future.

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