Detection and attribution of changes in streamflow and snowpack in Arctic river basins

Olga Nasonova (), Yeugeniy Gusev and Evgeny Kovalev
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Olga Nasonova: Water Problems Institute of Russian Academy of Sciences
Yeugeniy Gusev: Water Problems Institute of Russian Academy of Sciences
Evgeny Kovalev: Water Problems Institute of Russian Academy of Sciences

Climatic Change, 2023, vol. 176, issue 11, No 4, 23 pages

Abstract: Abstract This study is dedicated to the detection and attribution of changes in annual streamflow, maximum and mean winter snow water equivalent (SWE), start and end dates of seasonal snow cover, and its duration in three Arctic river basins (the Northern Dvina, Taz, and Indigirka) located in the European part of Russia, West, and East Siberia in different natural conditions. The observations of the above characteristics are rather scarce to detect statistically significant trends. At the same time, the available observations make it possible to calibrate the key parameters of the SWAP model, apply for hydrological simulations, and validate the model. Then, following the approach suggested within the framework of the international ISIMIP3a project, long-term simulations are performed for each basin using observational (factual) climate data, characterized by long-term changes, and counterfactual de-trended climate data. A comparison of factual and counterfactual simulations allows us to attribute the detected changes (in terms of trends) in the analyzed variables to climatic drivers. Statistically significant positive trends in streamflow are attributed to changes in annual precipitation for the Northern Dvina and Indigirka, and to the joint impact of increasing precipitation and warming, which resulted in permafrost thawing, for the Taz River. Negative trends in the basin-averaged end dates of snow cover and its duration as well as positive trends in winter and maximum SWE are detected for all basins and attributed to joint influence of changes in seasonal precipitation, air temperature, and solar radiation. The results highlight the vulnerability of Arctic river basins to climate change.

Keywords: Land surface model; Trend detection and attribution; Climate change; River runoff; Snow water equivalent; Snow cover duration (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s10584-023-03626-w

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