Summary/Abstract
Global warming intensifies the hydrological cycle, increasing the frequency and magnitude of floods worldwide, a trend particularly pronounced in the Arctic, where enhanced flooding exacerbates erosion and impacts ecosystems. However, the key drivers of Arctic flood variability remain unclear. To address this, the authors integrated hydrological and statistical modelling to quantify the contributions of hydrological factors to flood changes across 13 major Arctic rivers. The authors first reconstructed daily discharge using the CemaNeige-GR4J model, which, through multi-objective calibration targeting both runoff and snow processes, performed robustly (total Kling–Gupta Efficiency > 0.7 in most basins) and significantly improved the simulation of snow dynamics.
The analysis reveals spatially heterogeneous trends: flood magnitudes (maximum daily discharge) increased significantly on annual and seasonal scales in most basins (0.33–1567.17 m3·s−1·yr−1), while flood timing (date of maximum discharge) shifted earlier in spring/summer and later in autumn. Critically, all-subsets regression attribution shows that for ∼70% of the basins, interannual flood variations are predominantly driven by antecedent moisture conditions—specifically, soil moisture and snow water equivalent—rather than by precipitation or snowmelt events. This finding underscores the dominant role of accumulated basin storage over short-term meteorological extremes in shaping Arctic flood regimes.