Ninth International Conference on Permafrost ... - IARC Research

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Specific Features of Dynamic Modeling of Processes in the South SiberianPermafrostV.A. StetjukhaState University, Chita, RussiaIntroductionThe southern Siberian permafrost is unstable becauseof natural and climatic features of the region. First of all,the condition of soil stability due to external influencesresults from their high temperature (from -0.1 up to -2°С).Degradation of warm permafrost, even due to smallexternal influences, occurs much more quickly than in otherenvironments. Anthropogenic impacts can easily contributeto this environmental balance.There are features of soil development due to physicalprocesses in warm permafrost to consider. Traditionalmodels for forecasting the impact on the environment donot give realistic results. They do not adequately model thephysical processes in soils, as they do not take into accounta number of processes that have an influence on soils. Thecumulative impact of these neglected processes is significant.Anthropogenic factors are also not taken into account.Modeling of ProcessesThe methods of heat-mass transfer and stress-strainmodeling of unstable geocryological systems is presented.The method takes into consideration the adaptation of themodel to natural and climatic conditions, and incorporationof technological influences like mining and building. Withina modeling framework, the advanced equations of heat-masstransfer and a technique for their use are developed. Thepublication is devoted to a process-modeling approach.The basic process equations are given in an article byStetjukha (2003a). The model includes the following components:thermo-gradient streams of moisture, the distributedsources and convective streams of thermal energy, a gravitationalcomponent for moisture streams, electro-osmoticstreams of moisture, and thermal streams caused by electroosmoticmoisture streams. The equations of thermal and waterbalance on a surface of soil column takes into considerationevaporation, steepness and exposure of slopes, and anthropogenicinfluences. At the surface boundary, the temperatureand moisture balances of a near-surface layer are carried out.The equations are solved in finite difference form.In conditions of warm permafrost, the total influence ofthe neglected processes on depth of thawing and freezingthat are not taken into account in the majority of traditionalmodels, reaches 75%. Results are confirmed by calculationsand comparison with observations.To determine stresses and strains in soils, the finite elementmethod is again used. In this case, the variable characteristicsof loading in time, changeability of soil properties, changingboundary conditions, and temperature deformations aresimultaneously taken into consideration.The proposed technique of forecasting is based on theconsideration of several interactions of soil properties andtheir change with time. This modeling technique differsfrom others in that it considers mining influences, thecumulative impact of several processes, the application ofa system analysis approach, and a new way of consideringfactors that change with time. The offered model is exposedto continuous change and regulation owing to continuouslychanging conditions. The mathematical model is exposed toa continuous readjustment in connection with degradation offrozen soils.The distinctive features of the dynamic model are:• the coupling of the tasks of heat-mass transfer and geomechanicson the basis of developed mathematical models.Thus, researched soils are broken into elements of finite sizeby grids with common junctions;• increase in quantity of factors (variables);• the consideration of complex geometry to capturehuman-caused changes;• transformation of impacts in time, caused by thepresence of two fronts of freezing, by migration of moisture,by degradation of permafrost;• ability to adjust, in time, physical-technical parametersof soils: porosity, density, deformation modulus, Poisson’scoefficient, an angle of internal friction, coupling forces,tensile and compressive strengths based on change oftemperature, humidity and pressure in various points ofspace. During periods of compression of soils, the thermalcapacity, thermal conductivity, coefficient of linear expansionare corrected;• the consideration of changes in soil properties due tochanges in density as a function of their position in the soilprofile;• the consideration of temperature deformations;• use of the method of combined influences on soilcolumn (Stetjukha 2003b), which provides a determinationof extreme values, adverse combinations, and the periodsand sequence of loading of separate factors of influences;• a determination of optimum accommodation ofinfluences in time and space and definition of their optimumquantitative characteristics;• application of imitating modeling (Stetjukha 2003b)for perfection of preliminary generated mathematicalmodels.The developed algorithm has the distinctive featuresshown in Figure 1.The block model diagram is characterized by an extensivequantity of initial factors. The incorporation of the quantity ofthe initial data has required statistical processing. Within theframework of the block, the double-step process of correction301
Ni n t h In t e r n at i o n a l Co n f e r e n c e o n Pe r m a f r o s tFigure 1. The integrated circuit of calculations with change of model in time.= the common modules of system; = the modules used at regulation.of the complex model is carried out. Preliminary selection ofparameters is carried out by generating alternative variants.The correlation analysis of factors provides a procedure ofparameter selection on the degree of their importance. Frominitial analysis results, some parts of the complex modelcan be removed. Those factors staying are divided into twogroups. First, those used in the performance of numericalexperiments; second, those used for forming regressionequations (Stetjukha 2003b). The second stage of modelcorrection consists in quantitative correction of separateparameters. The algorithm of imitating modeling andoptimization of system lays in the basis of this stage.Computing procedures are carried out under the obviouscircuit. It allows tracing the development of processes andinserting corrective changes.The analysis of the system at each step of calculations takesinto account changes of borders between thawed and frozenzones, achievement by soil of a condition of saturation bymoisture, etc. The control points are analyzed. Control pointsare established on restrictions in the use of materials, on designfactors, on restrictions of technological process, etc.The major elements of the model are mechanisms of systemadaptation to changed conditions. Thus two stages areallocated. One of them is updating of the model at the nextstep on the basis of change of a physical condition of systemcomponents. New dependences between factors are determinedhere. The second stage of adaptation of the combinedmodel is its regulation on the basis of results of imitationmodeling and optimization. The procedure of imitation modelingand optimization of processes includes performance ofnumerical experiments on a considered circle of tasks. Asa result of regulation, a planned correction of physical-mechanicalproperties and other parameters of the system onthe next step of external forcing are carried out.Results of CalculationThe described modeling was carried out in an area ofconstruction of a federal motorway, “Amur.” Thawing ofpermafrost imbedded with ice on a slope with an inclinationof 34° was predicted. Opening of frozen soils was carriedout in the middle of April. The site with an open cut on aslope with the weak soils on 726 km of the motorway wasconsidered. Up to a depth of 1.5 m on a slope, loam isencountered (layer 1); up to a depth of 2.5 m, fine loamysand (layer 2); up to 4.4 m, loamy sand containing ice (layer3); up to 5.6 m, fine sand containing ice (a layer 4); up to6.5 m, loam, including rubble (layer 5); finally, a diorite.The depth and speed of thawing of separate layers duringthe warm period of the year were determined. Calculationsestablished loss of stability of a slope in the middle of July.The predicted results are confirmed with observation.The author carried out the forecast of results of impactson other environments, such as where the soil/vegetationcover has been disturbed, preservation of frozen soils withuse of heat insulating materials, shading screens, waterproofscreens, and frozen veils (Stetjukha 2003b).Depth of permafrost thawing under the bottom of theprojected channel on a deposit of brown coal on a coal pitwas determined. Predicted depth of thaw in 5 years was5.5 m; in 10 years, 7.8 m. The threat of destruction of thechannel is confirmed.On the basis of the described method, a model ofanthropogenic ices mound forecasting (Stetjukha 2003b) isdeveloped.The offered model of dynamic development of anatural-technological system allows objective estimationof temperature distribution, humidity, pressure, anddeformation fields in conditions of changing influences onsoil. Forecasting of processes in frozen soil has allowed thedevelopment of recommendations on optimum technologicalcircuits of work during various seasons of the year.ReferencesStetjukha, V.A. 2003a. Complex analytical modeling ofprocesses in the south Siberian permafrost. Permafrost.Zurich, Switzerland: Swets and Zeitlinger Publishers:1103-1106.Stetjukha, V.A. 2003b. Forecasting of a Mining ProcessesInfluence for a Condition of a Permafrost Region Soils.Chita: Publishing of Chita State University, 192 pp.302
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ContentsPreface ...................
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Mapping and Modeling the Distributi
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Satellite Observations of Frozen Gr
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xiiIce Wedge Thermal Regime in Nort
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xivPermafrost Response to Dynamics
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NICOP SponsorsUniversitiesUniversit
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Deep Permafrost Studies at the Lupi
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Effect of Fire on Pond Dynamics in
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Cryological Status of Russian Soils
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Acoustical Surveys of Methane Plume
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Permafrost Delineation Near Fairban
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Preparatory Work for a Permanent Ge
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A Provisional Soil Map of the Trans
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Martian Permafrost Depths from Orbi
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Time Series Analyses of Active Micr
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Impact of Permafrost Degradation on
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DC Resistivity Soundings Across a P
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Modeling Thermal and Moisture Regim
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A Provisional Permafrost Map of the
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Alpine Permafrost Distribution at M
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Cryogenic Formations of the Caucasu
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Modeling Potential Climatic Change
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A Hypothesis: A Condition of Growth
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Modeled Continual Surface Water Sto
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Freeze/Thaw Properties of Tundra So
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Discontinuous Permafrost Distributi
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Thermal Regime Within an Arctic Was
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Seasonal and Interannual Variabilit
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Twelve-Year Thaw Progression Data f
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Continued Permafrost Warming in Nor
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Landsliding Following Forest Fire o
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A Permafrost Model Incorporating Dy
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Seasonal Sources of Soil Respiratio
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Greenland Permafrost Temperature Si
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The Importance of Snow Cover Evolut
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The Account of Long-Term Air Temper
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The Combined Isotopic Analysis of L
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Adaptating and Managing Nunavik’s
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Human Experience of Cryospheric Cha
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HiRISE Observations of Fractured Mo
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A Soil Freeze-Thaw Model Through th
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Mapping and Modeling the Distributi
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First Results of Ground Surface Tem
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Historical Changes in the Seasonall
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Rock Glaciers in the Kåfjord Area,
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Snowpack Evolution on Permafrost, N
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Climate Change in Permafrost Region
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Maximizing Construction Season in a
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Pleistocene Sand-Wedge, Composite-W
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