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Based on simulations with an ensemble of CMIP6 (Coupled Models Intercomparison Project, phase 6) climate models using Bayesian averaging, an analysis of changes in the runoff of a number of Russian rivers—the Volga, Ob, Yenisei, Lena, Amur, and Selenga—has been carried out this century. Bayesian weights take into account the skill of runoff reproduction by models (long-term average runoff, linear runoff trend over a time interval with available runoff observations, and interannual and interdecadal variability). The skill of reproduction of runoff characteristics by individual CMIP6 ensemble models varies most widely for long-term average runoff; runoff trend; and, to a lesser extent, interannual variability. In the 21st century, the ensemble average runoff increases for most of the analyzed rivers, with the exception of the Volga. This increase is more pronounced in scenarios with large anthropogenic impacts. It is especially significant for the SSP5-8.5 scenario (Shared Socioeconomic Pathways, 14 5-8.5), in which the trend of increase in runoff in 2015–2100 relative to its modern long-term average value is (10 ± 4)% for the Ob, (16 ± 3)% for the Yenisei, (39 ± 7)% for the Lena, (36 ± 7)% for the Amur, and (18 ± 6)% for the Selenga. The main reason for changes in ensemble average runoff in the 21st century in models under all SSP scenarios is the changes in precipitation. Accounting for differences in model skill when reproducing river runoff on average for 2015–2100 reduces intermodel deviations relative to the corresponding values when uniformly weighting the model calculation results by 6–26%, depending on the SSP scenario and river catchment. [ABSTRACT FROM AUTHOR]

Primary production in the Sea of Okhotsk is largely supported by dissolved iron (dFe) transported by the Amur river, indicating the importance of dFe discharge from terrestrial environments. However, little is known about the mechanisms of dFe discharge into the Amur river, especially in terms of long-term change in dFe concentration. In the Amur river, extreme increase in dFe concentration was observed between 1995 and 1997, the cause of which remains unclear. As a cause of this iron anomaly, we considered the impact of permafrost degradation. To link the permafrost degradation to long-term variation in dFe concentration, we examined the changes in annual air temperature (Ta), accumulated temperature (AT), and net precipitation for three regions (northeast, south, and northwest) of the basin between 1960 and 2006. Ta and AT were relatively high in one out of every few years, and were especially high during 1988–1990 continuously. Net precipitation in late summer (July to September) has increased since 1977 and has stayed positive until 2006 throughout the basin. Most importantly, we found significant correlations between Ta and late summer dFe concentration with a 7-year lag (r = 0.54–0.69, p < 0.01), which indicate a close relationship between high Ta in year Y and increased late summer dFe concentration in year Y + 7. This correlation was the strongest in northeastern Amur basin where permafrost coverage is the highest. Similar 7-year lag correlation was also found between AT in the northeastern basin and late summer dFe concentration (r = 0.51, p < 0.01). Based on our findings, we propose the following hypothesis as a cause of iron anomaly. (1) Increased net precipitation since 1977 has increased soil moisture, which created suitable conditions for microbial dFe generation; (2) permafrost degradation during the warm years of 1988–1990 promoted iron bioavailability and led to the intensive dFe generation in the deeper part of the active layer; and (3) dFe took approximately 7 years to reach the rivers and extremely increased dFe concentration during 1995–1997. This is the first study to suggest the time-lagged impact of permafrost degradation on iron biogeochemistry in the Amur river basin. [ABSTRACT FROM AUTHOR]

The studies of the applicability of simulated precipitation in hydrological calculations and forecasts are presented on the example of the Amur basin rivers. It is shown that the use of simulated precipitation has a positive effect on forecasting rainfall floods in case of a sparse observational network. There is an especially noticeable lack of hydrological and precipitation data on the catchments of the Amur right-bank tributaries located in China (the Songhua River and its tributaries), whose runoff is a significant contributor to the water balance of the Middle and Lower Amur. It is revealed that the catchment-averaged fluctuations in simulated 5-day total precipitation above and below a certain threshold are linked to the temporal variations in water levels at the outlets of the Amur partial catchments. [ABSTRACT FROM AUTHOR]

The analysis is carried out for changes in runoff of the Amur and Selenga rivers in the 21st century according to the CMIP6 (Coupled Model Intercomparison Project, Phase 6) climate model ensemble simulations using the Bayesian approach versus stream gage data on annual runoff and GPCP-2.3 dataset on annual precipitation over catchments on different timescales. For both catchments, significant intermodel differences are associated with the projections of multiyear mean runoff and interannual variability. The intermodel distribution of Bayesian weights indicates a high role of uncertainty related to initial conditions for model simulations. There is a positive trend in total runoff in the Amur River basin in the 21st century under all analyzed anthropogenic forcing scenarios. For total runoff of the Selenga River, there are no trends in the 21st century for all analyzed scenarios. No significant trends for the Amur and Selenga surface runoff were revealed for all algorithms for considering Bayesian weights and all anthropogenic forcing scenarios. At the same time, significant interdecadal variations in the interannual variability of runoff were found. [ABSTRACT FROM AUTHOR]

The most severe large-scale lood on record occurred on the Amur River and its main tributaries (the Songhua, the Zeya, and the Bureya Rivers) in August-early September 2013. Prolonged heavy rainfalls over the vast territory of the Amur River basin produced the lood during the summer of 2013. During the lood monitoring, it was noted that observed precipitation data from the Amur River observational network had not represented areal precipitation over drainage basins of the Amur River and its tributaries well enough. Therefore, operational Weather Research and Forecasting (WRF)-Advanced Research WRF (WRF-ARW) model with grid distance of 15 km was applied for prediction of areal precipitation over that territory. The results of the simulation were compared with observed precipitation and water level data from the outlet points of partial drainage basins of the Amur River in June-September 2012 and 2013 to discuss the possibility of using numerically simulated precipitation in hydrological applications related to the Amur River basin. During the summer months of those years, an extreme lood occurred in 2013, while the hydrological situation was normal in 2012 on the Amur River. The results of the comparison show that the amount of precipitation simulated on grid points of partial basins of the Amur River and its tributaries are in better agreement with major lood peaks than precipitation data obtained from the observational network. Additionally, if the ive-day total areal precipitation averaged over the territory of a partial drainage basin exceeds 20 mm, the water level on an outlet point of a partial drainage basin of the Amur River monotonically increases independent of any variations of precipitation at an amount above the 20 mm value. [ABSTRACT FROM AUTHOR]

A wide range of trace elements contained in solution and suspension in surface waters in Amur River basin, which are subject to different anthropogenic load, has been considered. They have been found to vary widely because of their natural conditions, the impact of anthropogenic factors near cities (Khabarovsk, Komsomol'sk-on-Amur), and transboundary transport from the territory of China. Dissolved Mo, Br, and I are proposed as tracers of such transport. [ABSTRACT FROM AUTHOR]

In the basin of the Amur River in the Russian Far East, the influence of watershed areas covered by forests on the river basin has a complex nature, and no strict functional dependency has been established yet between these two factors. A study of the Amur River watershed in the current conditions, between 2000 and 2016 (climate, forest coverage, fires, and felling), has been conducted using the ground and satellite observations. The purpose of the study was to identify their influence on the river behaviour (flow, flooding, and levels of water). The study of hydrological regime of rivers was conducted in conjunction with the analysis of the dynamics of forest and burns areas over the synchronised periods of time. A special attention was given to the changing nature of the species composition of the forests (coniferous and deciduous forests separately) from 2000 to 2016, and climatic parameters over thirty years (atmospheric temperature, dew point, precipitation). New facts have been obtained, which provide an explanation of the reasons for predominant prolonged trends in the dynamics of the summer streamflow. In the view of the general tendency toward increased forest coverage combining all species of forest stand, the trend in the dynamics of the coniferous species areas is negative. Therefore, a conclusion can be made, that one of the major factors in the increase of the river flood flow (alongside the atmospheric precipitation), is deforestation of primary coniferous forests on the watershed areas, in contrast with the deciduous forests, where the trend is positive. Practicability of such conclusions can be justified, as different types of forests have different root systems, which mellow the ground and facilitate partial loss of the atmospheric precipitation and its transformation into the groundwater flow. Besides, coniferous forests attract more frequent and intensive fires, more subjected to felling, have longer regeneration period, and also, use larger volumes of ground waters for growing and functioning. Consequently, with their disappearance, an increase in streamflow should be expected. No changes in surface temperature and humidity of the forest cover in the watersheds during 1980-2016 despite global warming. Therefore, annual variability of forested areas of watersheds is greatly influenced by fires and felling. There are reasons to assume, that because of the tendency for decreasing areas of coniferous forests, the conditions contributing to the increases in rivers' flood flow and flood risks during monsoon and frontal cyclonic rainfalls will remain. [ABSTRACT FROM AUTHOR]