Projecting multi-attribute flood regime changes for the Yangtze River basin

Chen Zhang, Fengyun Sun, Sanjib Sharma, Peng Zeng, Alfonso Mejia, Yongpeng Lyu, Jun Gao, Rui Zhou, Yue Che

Research output: Contribution to journalArticlepeer-review

10 Scopus citations

Abstract

Climate change is altering flood risk globally. The nature of those alterations varies locally, creating the need for regional assessments to inform flood-risk management and planning. This study projects future changes in flood regime in the Yangtze River basin. To characterize flood regimes, we use a multi-attribute approach that measures the relative change in flood magnitude, timing, frequency, and duration between historical and future periods. We use climate projections from the Coupled Model Intercomparison Project Phase 6 (CMIP6) to force the Soil and Water Assessment Tool (SWAT), and generate daily streamflow projections along the Yangtze River network for two Shared Socioeconomic Pathways (SSPs), SSP2-4.5 and SSP5-8.5. We use seasonal maxima, annual maxima, and peaks-over-threshold to determine the different flood attributes. Results show that downscaled CMIP6 precipitation and near-surface temperature are both projected to increase substantially in the future, with a consequent surge in floods across the basin. In the far future (years 2061–2100), under SSP5-8.5, average annual flood magnitude, timing, frequency, and duration are projected to increase 66.6 %, arrive 1.9 days earlier, increase 27.5 %, and prolong 19.1 days, respectively. Projected changes in flood attributes at annual timescale are generally higher in the basin's northern tributaries than in the southern ones. Changes in flood magnitude and frequency tend to resemble each other, whereas flood timing and duration exhibit distinct change patterns. Our multi-attribute approach to flood regime characterization provides a systematic way for translating raw CMIP6 projections into informative future flood projections. This approach can help inform flood-risk planning and improve the reliability of climate change impact assessment.

Original languageEnglish (US)
Article number128846
JournalJournal of Hydrology
Volume617
DOIs
StatePublished - Feb 2023

All Science Journal Classification (ASJC) codes

  • Water Science and Technology

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