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

Davide Fugazza,Benjamin Brock,Thomas E Shaw,Shamshagul Mashtayeva

doi:10.1002/hyp.13843

Abstract

AbstractThe 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 moderate‐resolution imaging spectroradiometer (MODIS) MOD10A2 data set. We found that on average, peak snow cover retreat occurs between 22 March and 14 April depending on the basin, with large interannual variations but no clear trend over the MODIS period, while our comparative analysis of longer‐term snow cover extent from the National Oceanic and Atmospheric Administration Climate Data Record data set 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 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 (AO) 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 500–2,000 m above sea level. This suggests a lagged effect of this atmospheric circulation pattern in spring snow cover retreat. The winter AO 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.

Highlights

In the regions of Central Asia, owing to the arid and continental climate, snow cover melt provides an important contribution to runoff, determining the availability of freshwater for the local populations
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 National Oceanic and Atmospheric Administration (NOAA) Climate Data Record (CDR) dataset suggests a shift to earlier snow cover disappearance since the 1970s
4 Results 4.1 Multiannual snow cover variability from 2000 to 2017 While there are no notably strong trends in mean DSCD in any of the elevation intervals over the MODIS period there appear to be large inter-annual fluctuations at the lower elevations, especially in the larger Kara Ertis basin, while very little variability is seen above 3500 m a. s.l. (Fig. 3d)

Summary

Introduction

In the regions of Central Asia, owing to the arid and continental climate, snow cover melt provides an important contribution to runoff, determining the availability of freshwater for the local populations. Floods caused by late winter and spring snow melt are one of the most severe natural hazards in the country, displacing 10-30,000 people each year and causing on average more than $30 million in damages through loss of infrastructure, crops and livestock (UNOCHA, 2016; Guha-Sapir et al, 2018). Floods affect both lowland and mountain rivers, and there is evidence that the number of extreme events affecting mountain rivers has increased by 80% in recent years (Kozhakhmetov and Nikiforova, 2016). This issue is relevant in the East Kazakhstan region, which was one of the regions most affected by flooding between 1967 and 1990 and the most affected between 1991 and 2015, with over 42 floods reported (Kozhakhmetov and Nikiforova, 2016)

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Conclusion