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1

Modeling spatial structure of thermokarst lake fields in permafrost of Western Siberia based on satellite images

Автор: Polishchuk

Deciphering the satellite images of medium and high spatial resolution of the northern territories of Western Siberia has been carried out using geoinformation system ArcGIS 10.3. Images of medium resolution Landsat-8 and high resolution Kanopus-V were used. Kanopus-V images alluded to determine the number and areas of small lakes, which are considered as intensive sources of methane emission into the atmosphere from thermokarst lakes. Data on the spatial characteristics of thermokarst lakes were obtained. Based on the integration of images of medium and high spatial resolution, a synthesized histogram of the distribution of lakes in a wide range of sizes was constructed, taking into account small lakes. The obtained histogram was approximated by a lognormal distribution law by the Pearson criterion with a probability of 0.99. Based on the geo-simulation approach, a new model of the spatial structure of the fields of thermokarst lakes is presented, taking into account the lognormal law of the lake size-distribution. Algorithms for modeling the spatial structure of the fields of thermokarst lakes are described. An example of modeling the field of thermokarst lakes with a lognormal law of their size-distribution is given. The practical applicability of the previously developed model with an exponential distribution of lakes in size, based on data from Landsat images, has been experimentally confirmed. The results can be used to obtain predictions of the dynamics of methane emissions from the thermokarst lakes of the Arctic zone of Northern Eurasia for the coming decades in the context of climate changes.

2

Modeling spatial structure of thermokarst lake fields in permafrost of Western Siberia based on satellite images

Автор: Polishchuk

Deciphering the satellite images of medium and high spatial resolution of the northern territories of Western Siberia has been carried out using geoinformation system ArcGIS 10.3. Images of medium resolution Landsat-8 and high resolution Kanopus-V were used. Kanopus-V images alluded to determine the number and areas of small lakes, which are considered as intensive sources of methane emission into the atmosphere from thermokarst lakes. Data on the spatial characteristics of thermokarst lakes were obtained. Based on the integration of images of medium and high spatial resolution, a synthesized histogram of the distribution of lakes in a wide range of sizes was constructed, taking into account small lakes. The obtained histogram was approximated by a lognormal distribution law by the Pearson criterion with a probability of 0.99. Based on the geo-simulation approach, a new model of the spatial structure of the fields of thermokarst lakes is presented, taking into account the lognormal law of the lake size-distribution. Algorithms for modeling the spatial structure of the fields of thermokarst lakes are described. An example of modeling the field of thermokarst lakes with a lognormal law of their size-distribution is given. The practical applicability of the previously developed model with an exponential distribution of lakes in size, based on data from Landsat images, has been experimentally confirmed. The results can be used to obtain predictions of the dynamics of methane emissions from the thermokarst lakes of the Arctic zone of Northern Eurasia for the coming decades in the context of climate changes. Citation: Polishchuk VYu, Muratov IN, Polishchuk YuM (2019) Modeling spatial structure of thermokarst lake fields in permafrost of Western Siberia based on satellite images. Arctic Environmental Research 19(1): 1–10. https://doi.org/10.3897/issn2541-8416.2019.19.1.1

3

Method for the monitoring of hydrate formation process in intrafield flowlines

Автор: Emets

During the production of gas in the Far North and the Arctic, the formation of hydrate and ice plugs in intrafield flowlines is a major concern. The existing methods for determining the onset of hydrate formation are mostly based on the analysis of pressure-and-temperature conditions and therefore they only allow to detect the occurrence of conditions for hydrate formation. They do not allow to localize the specific place where hydrates start to form. The recently developed methods based on echolocation technology have a number of limitations due to the physical nature of the radiation used in them. The proposed method for the monitoring of hydrate formation processes in intrafield flowlines is based on a combination of analysis of pressure-and-temperature conditions in the flowline and the results of flowlines echolocation obtained by means of periodic generation of scanning pressure waves at the end of the flowline (from the side of the switching valve building). The flowlines are divided into characteristic sections bound by characteristic points linked to the structure of the flowline. The propagation speed of the scanning pressure wave is determined in each measuring cycle within the reference section. This can be any section between the characteristic points to which the distance is precisely known and which produce well-defined waveforms and time-stable reflections of scanning pressure waves, for example, the first section located adjacent to the switching valve building. The obtained echograms are compared with the model echogram, which is obtained from a flowline, which is known to be unclogged. Any abnormal change in the signal amplitude is indicative of an onset of the formation of a new local resistance. The proposed recursion formula makes it possible to calculate the temperature in the proximity of this local resistance and, taking into account the pressure value using the diagram of three-phase equilibria for hydrate-forming gases, to diagnose the possibility of existence of crystalline hydrates at a given point. Since pressure-and-temperature conditions for the formation of ice and hydrates are different, the proposed method is selective and enables accurate prediction of the nature of potential buildups.