Inter‐annual variability in snow cover depletion patterns and atmospheric circulation indices in the Upper Irtysh basin, Central Asia

The Irtysh River is the main water resource of eastern Kazakhstan and its upper basin is severely affected by spring floods each year, primarily as a result of snowmelt. Knowledge of the large scale processes that influence the timing of these snow‐induced floods is currently lacking, but critical for the management of water resources in the area. In this study, we evaluated the variability in winter–spring snow cover in five major sub‐basins of the Upper Irtysh basin between 2000 and 2017 as a possible explanatory factor of spring flood events, assessing the time of peak snow cover depletion rate and snow cover disappearance from the MODIS MOD10A2 dataset. We found that on average, peak snow cover retreat occurs between 22 March and 14 April depending on the basin, with large inter‐annual variations but no clear trend over the MODIS period, while our comparative analysis of longer‐term snow cover extent from the NOAA CDR dataset suggests a shift to earlier snow cover disappearance since the 1970s. In contrast, the annual peak snow cover depletion rate displays a weak increasing trend over the study period and exceeded 5,900 km2 day−1 in 2017. The timing of snow disappearance in spring shows significant correlations of up to 0.82 for the largest basin with winter indices of the Arctic Oscillation over the region. The primary driver is the impact of the large scale pressure anomalies upon the mean spring (MAM) air temperatures and resultant timing of snow cover disappearance, particularly at elevations 500–2000 m above sea level. This suggests a lagged effect of this atmospheric circulation pattern in spring snow cover retreat. The winter Arctic Oscillation index could therefore be incorporated into long‐term runoff forecasts for the Irtysh. Our approach is easily transferable to other similar catchments, and could support flood management strategies in Kazakhstan and other countries.