Том 45, № Suppl 2 (2018)

The paper deals with justification of estimates for solutions of groundwater flow equations in the case of incomplete information on soil permeability. In engineering applications, this problem is treated by means of mathematical modeling and implies a search through numerous alternate distributions of unknown parameters. Usually, these approaches involve, explicitly or implicitly, the monotonicity assumption, which provides an opportunity to reduce the number of alternative calculations. The paper presents some counterexamples to show that the monotonicity assumption, even if it is in agreement with engineering intuition, can be invalid.

The Selenga River, which originates in Mongolia, contributes about 50% of the total inflow into Lake Baikal. Hydroclimatic development and abrupt landscape evolution due to mining, industrial, and agricultural activities within the Selenga drainage basin affect the pollutant influx and transport along the course of the river and its tributaries and influence the riverine ecosystem, including fish habitats. This paper presents a process-based distributed modeling approach for the assessment of water, sediment, and contaminants dynamics and its environmental consequences at river basin scale by integrating various tools at multiple spatial scales. Different water quantity and quality processes were considered and modelled, e.g., the hydrology in the river basin, the erosion and sediment transport and budget, and fish migration. A set of regression models and a climate-driven hydrological model (ECOMAG) were applied to create projections of possible changes to the sediment and pollutants transport regime of the Selenga River and its delta that may occur in response to the projected variations of climate of the XXI century. Climate change may reduce the mean flow in the Selenga River at Kabansk by an average of 3–5% in the 2020s–2030s and 4–25% in the 2080s–2090s, depending on climate projections. The future increase in temperatures with permafrost thaw and the expansion of agricultural and mining activities along with urbanizaiton processes may induce up to 6% increase in the particulate modes and 3%, in the dissolved modes of some metals in the river system. Water runoff decline will dramatically decrease suspended sediment retention in the delta. Depending on the climate change scenario, in the 2080–2099, the suspended sediment load will change in the delta by –0.8% (retention) or by +1% (increase), which is much less than the recent observed average of sediment retention rates –33%. The reduction of runoff will induce a decrease in the migration distance of Baikal omul (Coregonus migratorius)) in the XXI century from 185 to 320 km, with a tendency to an increase towards the end of the century.

In the summer and autumn of 2017, anomalously high methane fluxes were measured using the chamber method on oligotrophic, mesotrophic, and eutrophic mires in the southern taiga in Western Siberia (mean ± std): up to 42.4 ± 18.7, 10.9 ± 6.1, and 17.9 ± 8.1 mg C m^–2 h^–1, respectively. The winter periods of the previous 3 years (2013–2016) showed air temperatures 1.3–2.1°C higher than the average over the past 13 years, which, combined with the maximum snow cover height and relatively windless weather, had led to heating of the peat layer by 3.5–5.5°С in 2017. The incubation experiments, made to calculate the potential methanogenic activity, confirmed the possibility of the formation of the amount of methane in peat that is necessary to explain the results of field studies.

Mathematical modeling was used to identify zones with different magnitudes of the barrage effect on the construction of buildings with deep-laid foundation in the Moscow region. Assessment of the barrage effect should take into account not only the magnitude of the groundwater flow but its level position relative to the earth’s surface. If the groundwater level (GWL) is located at a considerable depth, even deep-laid foundations of a building under construction and, accordingly, a substantial rise in groundwater table will not result in a critical situation whereby the foundations of neighboring buildings are submerged and the bearing capacity of the soil under the foundations is changed. Analysis of the geological data and the calculations that were carried out made it possible to establish the distribution of barrage effect values in Moscow.

Projections of possible changes in streamflow of three northern rivers (the Northern Dvina, Kolyma, and Indigirka) up to 2100 were calculated for two greenhouse gas emission scenarios: a high emissions scenario (RCP8.5) and a medium mitigation scenario (RCP4.5) used for the fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC). For each scenario, several hydrological projections were obtained using different models (AOGCM INMCM4.0 and LSM SWAP) and different post-processing techniques for correcting biases in meteorological forcing data simulated by INMCM4.0 and used to drive the SWAP model. Uncertainties in river runoff projections associated with the application of different emission scenarios, different models, and bias-correction techniques were estimated and analyzed.

Based on the analysis of 162 longest (more than 100 years each) series of annual, maximal, and minimal runoff in rivers of different genetic types, the regularities of changes in the degree of stationarity/nonstationarity of the runoff changes are studied. It is shown that changes in the average annual and maximum runoff in the rivers of the “main” type—non-effluent, unregulated, as well as in the rivers of glacial feeding—throughout the period of observations generally correspond to the stationarity hypothesis. On the contrary, for a significant part of the runoff series of all types of effluents and regulated rivers, as well as the minimum flow of rivers of the main type, the alternation of segments of realizations of stationary and nonstationary processes with respect to mathematical expectation, is typical. To describe this effect, we propose the concept of “intermittent” nonstationarity. The nonstationarity parameters of the indicated type are compared with the nonstationarity parameters of the monotonous type.