A three-layer parameterization framework for ENSO-runoff coupling: Enhanced flood risk in the Huaihe River Basin under climate change

Study region: Huaihe River Basin, China, a region significantly affected by ENSO events. Study focus: This research develops a three-layer parameterization framework within the SWAT model to quantify ENSO-runoff coupling mechanisms. We integrate: (1) an exponential decay function capturing ENSO lag effects with 4–5 month peak sensitivity; (2) a spatial propagation function characterizing the 0.11% per kilometer downstream amplification gradient; and (3) an integrated coupling equation linking ENSO intensity with non-linear streamflow responses. This approach embeds ENSO-specific sensitivity coefficients directly into SWAT parameter equations, connecting atmospheric forcing with watershed response through explicit physical equations. New hydrological insights: Analysis reveals: (1) Five abrupt change points (1999–2018) coinciding with major ENSO transitions (p < 0.05); (2) Spatial heterogeneity—El Niño events amplify July runoff by 55.0%, 55.9%, and 57.2% at upstream, midstream, and downstream stations, while La Niña suppresses runoff by 60.3%; (3) The enhanced model achieves high performance (NSE >0.75 calibration, 0.73 validation), with strongest ENSO influence on CN2 (α_i = 0.42), ESCO (α_i = 0.35), and CH_K2 (α_i = 0.31). Parameter constraints show systematic shifts between El Niño (CN2: +0.05–0.20) and La Niña (CN2: −0.15–0.05) phases. Future projections under SSP2–4.5 suggest declining mean runoff (∼-4.85 m³/s yearly, 95% CI: −6.2 to −3.1) but increased extreme event risk, with peak flows potentially exceeding 4000 m³ /s in ∼50% of years through 2050. Three windows of elevated flood risk are projected during the mid-2020s, mid-2030s, and mid-2040s (each with ±2-year uncertainty), contingent on HadGEM3-GC31-LL's representation of future ENSO evolution.