Rets, E.P., Durmanov, I.N., Kireeva, M.B. et al. Past ‘peak water’ in the North Caucasus: deglaciation drives a reduction in glacial runoff impacting summer river runoff and peak discharges. Climatic Change 163, 2135–2151 (2020)
At the end of the 20th—early twenty-first century, mountain glaciers exhibited the most negative mass balances since the beginning of observations. The hydrological consequence of deglaciation is a rise in glacial runoff until a maximum (‘peak water’) is reached, beyond which runoff decreases as glacier extents are reduced. It is likely that the peak water of glacial runoff has already been passed in the central North Caucasus. River basins with more than 1% glacier cover show consistent decreases in mean monthly discharge in July and August (up to 4–6% per decade during 1945–2018), when glacier meltwater contribution to river runoff is high. Meanwhile, in neighbouring non-glacierised basins, runoff in July and August mostly rose. The runoff in June, when glaciers are typically mostly covered by seasonal snowpack, has increased by 2–9% at most gauges. Hydrological data from the Djankuat alpine research catchment in the central North Caucasus indicate a reduction of glacial runoff contribution in recent decades, as the area reduction of Djankuat glacier and increase in debris cover compensate for the increase in glacier melt. The Djankuat river runoff decreased by 29% in July, 42% in August, and 26% in September in 2007–2020 compared with 1968–1978. The mean annual peak discharge has dropped by 1–5% per decade in the central North Caucasus, and it occurs 1–2 weeks earlier. Possible mechanisms of observed changes are discussed. This study provides the data on climate-related changes in the glacial runoff for a previously not investigated region.
2021Е.К. Сантьева, И.Л. Башмачников, М.А. Соколовский. Об устойчивости Лофотенского вихря Норвежского моря. Океанология, 2021, том 61, № 3, с. 353–365.
2021Moreido, Vsevolod; Gartsman, Boris; Solomatine, Dimitri P.; Suchilina, Zoya. 2021. How Well Can Machine Learning Models Perform without Hydrologists? Application of Rational Feature Selection to Improve Hydrological Forecasting. Water 13, no. 12: 1696.