Flooding is one of the greatest disasters that produces strong effects on the ecosystem and livelihoods of the local population. Flood frequency is expected to increase globally making its risk assessment an urgent issue. In spring-summer 2017, an extreme flooding occurred in the Indigirka River lowland of Northeastern Siberia that inundated a large area. In this study, the extent and climatic drivers of the flooding were determined using the results of field observations, satellite images, and climate reanalysis dataset, and its possible effects on the ecosystem were discussed. In 2017, a significant lowland area of around 16,016 km 2 was covered with water even in July, which was 5,217 km 2 (around 4% of the total area) greater than the water-covered area in 2015 when usual hydrological condition in the area was observed. The hydrographic signature obtained for the Indigirka River water level in 2017 was unusual. Although the water level rose sharply at the end of May (which was typical for the Arctic region), it did not fall afterwards and even increased again to an annual daily maximum value in the middle of July. The climate reanalysis dataset obtained for the temporal-spatial variations of snow water equivalent, snowmelt, and runoff over the lowland revealed that a large amount of snowmelt runoff in June and July 2017 produced a large water-covered area and unusually high river water levels that lasted until summer. Snow depth from winter to spring was largest in 2017 over the period from 2009 to 2017, and the surface of the lower reach of the lowland was partially covered with snow even in the end of June due to the extreme snowfall that occurred in October 2016. Such unusual hydrological conditions waterlogged most trees over the lowland, which caused serious ecosystem devastation and changes in the material cycle.
Minor seismicity may occur at volcanoes with hydrothermal system before a steam eruption. To forecast any steam eruption, it is indispensable to detect and understand the nature of this shallow seismicity. As the fumarolic gas resides in the hydrothermal system, it may provide insights for elucidating the nature of any seismicity and thus forecast steam eruptions. At Kusatsu-Shirane volcano Japan, intense seismic activity took place in 2014 and 2018. To investigate the relationship between the seismicity and gas chemistry, five fumarolic gas discharges have been repeatedly analyzed. Since July 2014 to November 2017 a monotonic decrease in CO 2 /H 2 O, He/H 2 O and N 2 /H 2 O ratios was recorded in the fumarolic gasses located north of the summit of volcano, suggesting the decline of the magmatic component. On the contrary the CH 4 /H 2 O ratio significantly increased during the seismically quiet period, indicating that reduced conditions developed in the hydrothermal system, favoring the formation of CH 4. The high N 2 /He ratio in the quiet period indicates the addition of N 2 , likely deriving from the crustal rocks hosting hydrothermal reservoir. The N 2 /He ratio in 2018 was significantly lower than those recorded in 2014, indicating the evolution of magma with the progress of degassing. The δD(H 2 O) and δ 18 O(H 2 O) values and the CO 2 /H 2 O ratios of fumarolic gas discharges were modeled with the following processes: generation of vapor phase after the mixing between magmatic gas and a cold groundwater with meteoric origin, addition of vapor phase with meteoric origin, and partial condensation of water vapor near surface. Only a single magmatic gas is necessary for the above modeling. These data suggest that at Kusatsu-Shirane volcano the activation of seismicity was synchronized with the increase of the magmatic component in the fumarolic gas. It is postulated that the injection of magmatic gas increased the fluid pressure in the reservoir, which triggered seismicity. The injection would have been triggered by a break of the sealing zone surrounding the degassing magma. The injection of magmatic gas can be detected by monitoring the composition of the fumarolic gas, thus giving the possibility to forecast any future seismicity.
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