Soil Thermal Conductivity Research Articles

Quartz contents derived from particle density measurements improve the accuracy of soil thermal conductivity estimates

Quartz content (fquartz) is a key value used to estimate soil thermal conductivity (λ) in land surface models. Due to the difficulties in measuring fquartz directly, many studies use sand content (fsand) to approximate fquartz in λ models, causing large uncertainties in λ estimates. The existing methods for determining fquartz are quite limited and complicated, and it is still desired to derive fquartz values with simple parameters. Here, we present an empirical equation to estimate fquartz values from soil particle density (ρs). The empirical equation was developed from two published datasets including laboratory measurements on 56 soils, and its performance was evaluated by comparing measured λ values to estimated λ values. Four models were used to estimate λ using inputs of fsand, actual measures of fquartz, and the new empirical equation estimates of fquartz. The root mean square errors, RMSEs, of modeled λ values (based on the empirical equation estimated fquartz) were less than 0.27 W m−1 K−1, which were similar to the RMSEs (< 0.26 W m−1 K−1) when actual fquartz values were used as model inputs. The new empirical equation estimates of fquartz led to much lower RMSEs in modeled λ values than the RMSEs (< 0.39 W m−1 K−1) obtained when fsand values were used to represent quartz content. The new empirical equation provides a simple and easy approach to estimate fquartz as an input to λ models.

Effects of salt and pH on microstructure and physico-mechanical behaviors of clay sediments：A references review

Three quarters of the world’s significant urban centers are located in coastal regions where clay minerals are prevalent. The microstructures and physico-mechanical properties of clay sediments are highly susceptible to alterations in pore water chemistry. The pore water chemistry in soil changes easily due to groundwater pollution, seawater erosion, degradation, etc. However, there are several inconsistencies in the literature on the change of physical and mechanical properties of clay soils caused by the change of pore water chemical properties, i.e., disparate experimental results were reported for the same soil property, or varying explanations were proposed for the identical experimental results. Currently, the research in this field mainly focuses on the macroscopic behavioral modifications while lacking the explanations of microscopic mechanism. Therefore, this paper presents a comprehensive review of researches conducted over the past four decades on the impact of pore water chemistry (including salt type, salinity, ion valence, pH) on soil properties such as the microstructure, settlement, Atterberg limits, shear strength, conductivity, unsaturated soil mechanics properties and thermal properties. The fundamental mechanisms underlying the varied experimental observations on clay sediments affected by salt and pH are systematically explored, and deficiencies in this field are identified. The observed dispersion in the literatures is attributed to the spatial variation and heterogeneity of soil compositions, different test methods, and insufficiency of the fundamental microscopic mechanisms of the observed soil behaviors, etc. Therefore, it is necessary to further explore the essential mechanisms of the test results in the future to establish a unified conclusion.

Effects of thermal and hydrophysical properties of sandy Haplic Podzol on actual evapotranspiration of spring wheat

Abstract The objectives of the research were to: (1) assess the strength of relationships between the soil thermal and hydrophysical properties, (2) evaluate the strength of association of evapotranspiration of spring wheat crop with soil thermal and hydrophysical properties, and (3) estimate the ranges of the thermal and hydrophysical properties of the sandy Haplic Podzol during the growing period of spring wheat in 2022. The study included instrumental simultaneous measurements of meteorological data, soil water retention curve, soil moisture content (SMC) and thermal properties. Actual evapotranspiration was calculated according to the Allen equation. Spearman’s rank correlation coefficients showed that the increase in SMC from 0.10 cm3 cm−3 to 0.26 cm3 cm−3 resulted in a significant increase in thermal conductivity (r = 0.81, p &lt; 0.001), volumetric heat capacity (r = 0.93, p &lt; 0.001) and thermal diffusivity (r = 0.94, p &lt; 0.001). Actual evapotranspiration also rose with the increasing SMC (r = 0.91, p &lt; 0.001) and matric water potentials (r = 0.61, p &lt; 0.05). As a consequence of the changes in SMC, the Spearman’s rank correlation coefficients supported the strong positive relationships of actual evapotranspiration with volumetric heat capacity (r = 0.97, p &lt; 0.001), thermal conductivity (r = 0.96, p &lt; 0.001) and thermal diffusivity (r = 0.96, p &lt; 0.001). Pearson correlation coefficients also supported the strong input of thermal inertia to the actual evapotranspiration (r = 0.88, p &lt; 0.01). During the whole period of observations, actual evapotranspiration varied from 0.05 to 0.59 mm hr−1, soil thermal conductivity – from 0.225 to −1.056 W m−1 K−1, volumetric heat capacity – from 1.057 to 1.889 MJ m–3 K−1, heat diffusivity from 0.189 to 0.559 mm2 s−1, and thermal inertia – from 516 to 1412 J m−2 K−1 s−0.5.

Development of a transient analytical method for multi-pipe earth-to-air heat exchangers with parallel configuration

A novel analytical model for calculating the thermal performance of multi-pipe earth-to-air heat exchangers is presented by considering soil thermal saturation as well as soil temperature fluctuations on the ground surface. The accuracy of the analytical model is validated using a three-dimensional numerical simulation. The proposed analytical model shows a great coincidence compared to the numerical simulation as well as already reported experimental data. Using this analytical approach, a three-pipe earth-to-air heat exchanger in realistic working conditions is simulated and the effect of the center-to-center distance of pipes on the outlet air temperature and averaged cooling capacity are also investigated. It is shown that while decreasing the distance between the pipes does not change the temperature of the outlet air in the initial working days, a reduction in the thermal performance is observed as the simulation proceeds. This can be attributed to the soil thermal saturation around the middle pipe. The average cooling capacity of the middle pipe reduces by 48%, 35%, 19%, 5%, 2%, and 1% with respect to a single-pipe earth-to-air heat exchanger system for the distance of 25, 50, 100, 200, 250 and 300 cm between the pipes, respectively. In addition, it is shown that increasing the air velocity through the pipes enhances the cooling capacity, especially for larger pipes distance. The cooling capacity of the earth-to-air heat exchanger is enhanced as a result of the increment in the soil thermal conductivity in such a way that the increment percentage is higher for smaller pipe distances. The appropraite distance between the pipes is also shown to be related to the soil thermal conductivity. It is shown that for soil with thermal conductivity of 0.5 and 2 W/m.K, the appropraite distance becomes 200 cm and 300 cm, respectively.

Numerical modeling of soil temperature variation under an extreme desert climate

The soil temperature profile is useful for different engineering, architecture, and agriculture areas. In recent years, the growth of direct uses of geothermal energy has increased the interest in soil temperature prediction models. This research paper numerically models the soil temperature variation under extreme desert climate conditions and compares it with experimental data measured on-site to evaluate the reliability of numerical models based on the one-dimensional transient state heat conduction equation as a tool for the evaluation of low enthalpy geothermal resource using meteorological data and soil thermal properties. From the study results, it can be concluded that the numerical models present temperature values close to those measured experimentally. The model that presents the more significant mismatches concerning the experimental data is the 1 m model, presenting the following statistical values; R2 of 0.97, mean absolute error of 0.61 °C, RMSE of 0.76 °C, NRMSE of 3.01%, and a MBIAS of 0.23. Although the numerical models present values are close to those measured, some coefficients, such as the soil surface water content greatly influence the model's accuracy regardless of depth.

Effect of tillage systems combined with plastic film mulches and fertilizers on soil physical properties in a wheat-agricultural site in southern Iraq

This study researches the influence of the three tillage systems (conventional, economical and mulch tillage) when combined with different soil plastic mulching and fertilizer applications on key selected soil physical properties (SPP) at 0-20 cm soil depth in a wheat agricultural site, during summer (from 1st June to 31st July 2015). SPP include soil porosity (Φ), volumetric soil water content 60 days after irrigation to field capacity (q60), and mean weight diameter of aggregates (MWD). The term mulch tillage refers here to a soil conservation practice where the soil surface is disturbed by tillage whereby crop residues are mixed with the soil and a certain amount of residues remain on the soil surface, while mulching refers to the placement of inorganic material over the top of a soil surface to protect it. Soil treatments included tillage system: conventional tillage using a combination of a mouldboard plough and a disc harrow (MP+DH), economical tillage using a rotary cultivator (RC), and mulch tillage using a chisel plough (MT+CP); soil plastic mulching: transparent mulching (TM), black mulching (BM) of 200 cm wide with 0.05 cm thick, and without mulching (WM); and fertilisers: composed organic fertiliser (CoF), no-composed organic fertiliser (NoF), and chemical fertiliser (ChF). The split–split-plot design under the randomized complete block design (RCBD) was established in 27 treatments with 3 replicated, to map Φ, q60, and MWD based on 81 soil samples from all treatments. Results showed that the different soil treatments have diverse impacts on SPP. MP+DH resulted in the higher q60 (0.22 cm3 cm-3), MWD (0.85 mm), and Φ (56.87%). Our findings showed that MT+CP obtained a higher MWD of 0.98 mm and lower Φ of 49% compared to other tillage systems. Soil mulching had significantly modified SPP, with BM resulting in the highest Φ (55.65%), q60 (0.35 cm3 cm-3), and MWD (1.06 mm). Results indicated no significant differences between fertiliser types on SPP. The CoF had a significant effect on MWD and related soil characteristics studied. These findings can help us to understand the individual and combined effects of the tillage system, mulching, and fertilization application on some soil characteristics in wheat agriculture. A further study with more focus on the influence of tillage depths and mulching types (plastic vs organic mulch for different crops) under a variety of soils and climatic conditions, as well as on soil thermal properties needs further investigation.

Soil thermal properties during freeze–thaw dynamics as function of variable organic carbon and grain size distribution

AbstractPermafrost regions are experiencing increasing air temperatures, accelerating the thawing process, and thickening the active layer in summer. This can accelerate the release of greenhouse gasses into the atmosphere from the organic carbon stored in the permafrost. The long‐term thawing rates of permafrost below the active layer are governed by the soil thermal properties, the heat capacity, and thermal conductivity, which vary due to differences in grain sizes and distribution and organic matter content. Using nine column experiments comprised of fully saturated synthetic permafrost samples exposed to freeze–thaw cycles, the relative contributions of a range of soil grain sizes and organic matter contents on the soil thermal properties were investigated. The columns were subjected to a freeze and thaw cycle while soil temperatures were recorded in profiles. To infer the thermal properties from these experimental data, a numerical heat transfer model was used. The best fit between the observations and a batch of 5544 numerical models was used to find optimum values for permafrost thermal properties. The optimized heat capacity varied between 500 and 650 (J/m3 K) and thermal conductivity between 2.45 and 3.55 (W/m K). These optimized parameters were subsequently used to model a 100‐year permafrost active layer thaw scenario under warming air temperatures. Variations in the optimized thermal properties resulted in a time difference in thawing depth of 10–15 years and thawing depths varied between 9 and 10 m between the different optimized thermal properties at the end of the 100‐year scenario.

Exploring the relationship between soil thermal conductivity and frostbite prevention: a comprehensive modeling and experimental approach

Exploring the relationship between soil thermal conductivity and frostbite prevention: a comprehensive modeling and experimental approach

No-till cover crop effects on the thermal properties of a Paleudult

Soil thermal properties play an important role in crop productivity, but the influence of a multi-species cover crops (CCs) on these properties are not well understood. This study evaluated the effects of no-till CCs (winter wheat [Triticum aestivum L.], crimson clover [Trifolium incarnatum L.], triticale [Triticale hexaploide Lart], hairy vetch [Vicia villosa], oats [Avena sativa], and cereal rye [Secale cereale L.]) on soil physical (bulk density [BD], and volumetric water content [ϴ] at 0, −33, and −100 kPa soil water pressures) and thermal properties (thermal conductivity [λ], volumetric heat capacity [CV], and thermal diffusivity [D]). Soil samples were collected just before CC termination at 0–10, 10–20, and 20–30 cm depths from CC and no cover crop (NC) plots during 2021 and 2022. Results showed that, after 2 years, CCs reduced BD by 17% and increased ϴ at 0, − 33, and − 100 kPa soil water pressures by 23%, 25%, and 28%, respectively relative to NC management. Thus, λ under NC was 16%, 19%, and 20% higher at 0, − 33, and − 100 kPa soil water pressures, respectively, compared with CC management. Conversely, CV was 17%, 14%, and 15% higher under CC compared with NC management at 0, − 33, and − 100 kPa soil water pressures. Regression analysis further demonstrated that while plant root was the most important factor influencing λ at saturation, ϴ played the greatest role in λ at other soil water pressures. Expectedly, ϴ was the most important factor influencing CV at all measured soil water pressures. Conclusively, no-till CCs can improve laboratory measured soil thermal properties by moderating heat transfer.

Seasonal Variations of Soil Thermal Conductivity at the InSight Landing Site

AbstractThe heat flow and physical properties package measured soil thermal conductivity at the landing site in the 0.03–0.37 m depth range. Six measurements spanning solar longitudes from 8.0° to 210.0° were made and atmospheric pressure at the site was simultaneously measured using InSight's Pressure Sensor. We find that soil thermal conductivity strongly correlates with atmospheric pressure. This trend is compatible with predictions of the pressure dependence of thermal conductivity for unconsolidated soils under martian atmospheric conditions, indicating that heat transport through the pore filling gas is a major contributor to the total heat transport. Therefore, any cementation or induration of the soil sampled by the experiments must be minimal and soil surrounding the mole at depths below the duricrust is likely unconsolidated. Thermal conductivity data presented here are the first direct evidence that the atmosphere interacts with the top most meter of material on Mars.

The Thermal Conductivity and Matric Potential (Moisture Tension) Relationships for Soils of Different Gypsum Content

The soil samples have been taken from a soil profile at the Research Station of College of Agriculture in the University of Tikrit at a longitude of 430 38- 23= in the east and at a latitude of 340 48- 40= in the north. The samples were taken from the surface horizon with a gypsum content of 62 g.kg-1 (G1) and also from the subsurface horizon of 443g.kg-1 (G7) gypsum content. Different gypsum content samples were prepared as G2, G3, G4, G5, and G6 that have Gypsum contents of 106, 153, 202, 245, and 337 g.kg-1 respectively. These samples were prepared by mixing the surface soil samples with the soil of gypsic horizon. The prepared soil samples were wetted by water spraying to two thirds the field capacity levels (0.25 kg.kg-1). Then they incubated for two months in order to make soils homogeneity in addition to moisture distribution in soil. The plastic rings of 10.4 cm diameter and 10 cm heights were drilled from the middle to fix the sensor of heat flux of thermometer plug. The size and height of the soil to be placed in the plastic ring was calculated based on the area A and height h of ring and then the mass of the soil (m) was calculated based on the value of the bulk density. The samples were oven dried at 70° degree until the weight of samples were fixed to obtain the completely dry soils. The amount of water to be added per sample was calculated based on the moisture characteristics curve and by the tensions specified in this study (0.1, 5, 15, 33 and 100) kPa. The moisture was converted to a depth of water and then soil samples were wetted in a light spraying manner with continuous flipping and the thermometer sensors were fixed up and down the heat flux sensor and then six readings per replication were recorded. The time from one reading to another was 60 seconds and their rate was extracted. Based on the results of the experiment, it can be concluded that by the fixation of moisture tension, the thermal conductivity values of the soil decreased with the increased soil content of gypsum, as the G3 treatment with gypsum content 15% gave the highest significant value while the least significant average value of thermal conductivity values at the G7 treatment with gypsum content was 43%. The increase in gypsum from 25% at G5 to 30% and 44% in G6 and G7 successive treatments did not significantly affect the values of the soil’s thermal conductivity averages. The overlap point of the relationship between soil gypsum content and thermal conductivity was found at G3 and G4 that have gypsum content of 15% and 25% respectively. The average of gypsum decreases the thermal conductivity values of the soil with increased moisture tension values, as the tension gave 0.1 kPa a significant increase in the values of the average thermal conductivity from the rest of the tensions and for all treatments while the least significant average of thermal conductivity values at tension was 100 kPa.

Simulation of soil thermal conductivity based on different schemes: An empirical comparison of 13 models

Thermal conductivity is a key soil property widely used for agricultural production, land surface processing research, and geothermal resource development, among others. Although the rapid and accurate determination of soil thermal conductivity (λ) has been a hot topic in recent years, there is still no unified model for the different soil types of soil. Furthermore, the lack of data on thermal conductivity and soil properties leads to errors in parametric models of thermal conductivity. In order to overcome the data shortage, a comprehensive λ dataset of 2972 items was established and 10 influential parameters on thermal conductivity were identified in this study. Based on this, an empirical comparison was made between four classical parametric models and nine machine-learning models with and without an intelligent optimization algorithm was carried out. Of all the methods, the ensemble machine-learning methods perform better in λ simulations. The XGBoost model has better simulation accuracy and generalization capability. Soil moisture properties are the key parameters in performing λ simulations, while the soil texture-related properties such as bulk density and solid thermal conductivity, along with the sand content, also play an important role. The results of this study can provide basic thermal conductivity data and a parameterization scheme for referencing in land surface processing research.

Effect of Long-Term Semiarid Pasture Management on Soil Hydraulic and Thermal Properties

Semiarid pasture management strategies can affect soil hydraulic and thermal properties that determine water fluxes and storage, and heat flow in unsaturated soils. We evaluated long-term (>10 years) perennial and annual semiarid pasture system effects on saturated hydraulic conductivity (ks), soil water retention curves (SWRCs), soil water thresholds (i.e., volumetric water content (θv) at saturation, field capacity (FC), and permanent wilting point (PWP); plant available water (PAW)), thermal conductivity (λ), and diffusivity (Dt) within the 0-20 cm soil depth. Forage systems included: Old World bluestem (Bothriochloa bladhii) + legumes (predominantly alfalfa (Medicago sativa)) (OWB-legume), native grass-mix (native), alfalfa + tall wheatgrass (Thinopyrum ponticum) (alfalfa-TW), and annual grass-mix (annual) pastures on a clay loam soil; and native, teff (Eragrostis tef), OWB-grazed, and OWB-ungrazed pastures on a sandy clay loam soil. The perennial OWB-legume and native pastures had increased soil organic matter (SOM) and reduced bulk density (ρb), improving ks, soil water thresholds, λ, and Dt, compared to annual teff and alfalfa-TW (P < 0.05). Soil λ, but not Dt, increased with increasing θv. Grazed pastures decreased ks and water retention compared to other treatments (P < 0.05), yet did not affect λ and Dt (P > 0.05), likely due to higher ρb and contact between particles. Greater λ and Dt at saturation and PWP in perennial versus annual pastures may be attributed to differing SOM and ρb, and some a priori differences in soil texture. Overall, our results suggest that perennial pasture systems are more beneficial than annual systems for soil water storage and heat movement in semiarid regions.

Optimization of the number and locations of the calibration stations needed to monitor soil moisture using distributed temperature sensing systems: A proof-of-concept study

The single-probe heat-pulse (SPHP) technique combined with the Fiber-optic Distributed Temperature Sensing (DTS) technology can offer novel high-resolution measurements of soil moisture (θ) over spatial scales ranging from several centimeters to several kilometers. However, the key limitation of this method is in obtaining the calibration relationship between θ and soil thermal conductivity (λ) across a specific field. In a previous study, a new methodology using a Gaussian processes model was presented to account for the spatial variability in the λ-θ relationship. The model aggregated θ measurements from soil moisture sensors scattered over the SPHP transect with the corresponding DTS λ measurements at their locations. In this study, a novel methodology is tested to optimize the number and locations of soil moisture sensors required to account for the spatial variability of the λ-θ relationship to achieve higher accuracy from the SPHP technique. The proposed methodology utilizes hierarchical clustering to analyze the information contained in the spatial structure of the SPHP measurements as the soil dries from a nearly-saturated condition. The proposed methodology was tested using data from a field in Oklahoma. Monte-Carlo simulation was performed to validate the performance of the proposed methodology. The predictions obtained from the proposed methodology resulted in θ measurements accuracy comparable to those obtained from the 10% best Monte-Carlo iterations of randomly assigned soil moisture locations. This study demonstrates that the proposed methodology is more efficient than the traditional practice of randomly spreading calibration soil moisture sensors along the SPHP transect.

Relationship between thermal and electrical conductivity curves of soils with a unimodal pore size distribution: Part 1. A unified series-parallel resistor model

Soil thermal conductivity (λ) and electrical conductivity (σ) characterize heat and electricity conduction through soils. Both λ and σ are affected by similar factors, such as soil water content (θ), texture, bulk density (ρb), temperature, structure, and organic matter content. Little is known about the quantitative relationship between λ and σ, and how soil texture and ρb modify the relationship. In this part one of a two-part series, we examine the correlation between λ(θ) and σ(θ) curves and develop a new model for normalized σ curves of soils with a unimodal pore size distribution. We introduce an Ohm’s law analogy to describe the λ and σ curves conceptually, based on a cubic cell unit model. A unified series–parallel resistor model considering θ and ρb effects is established for both λ(θ) and σ(θ) curves by considering heat and electrical conduction pathways (solid, solid–liquid, and liquid pathways) in the hydration, menisci, and continuous liquid ranges. Simultaneous measurements of θ, λ and σ with thermo-TDR sensors on two soils are used to examine the model performance at various values of ρb and θ. The modeled and measured λ (θ) and σ (θ) curves provide consistent trends, and the normalized λ and σ values vs. degree of saturation confirm the existence of an earlier reported “mirror image” phenomenon between the functions.

Relationship between thermal and electrical conductivity curves of soils with a unimodal pore size distribution: Part 2. Estimating bulk electrical conductivity from thermal conductivity

Soil thermal conductivity (λ) and electrical conductivity (σ) influence heat conduction and electrical conduction through soils. In Part 1 of this two-part series, we demonstrated that for soils with a unimodal pore size distribution, the λ and σ curves were interrelated and could be described with a unified series–parallel resistor model. Based on the conceptual model presented in Part 1, the “mirror image” phenomenon in the λ-σ relationship was further evaluated. Starting with the Lu et al. (2007) λ model, the “mirror image” phenomenon was used to derive a new normalized σ model. The new σ model was dependent on degree of water saturation (S), and shared the same shape parameters as those in the λ model. Here, the new σ model is examined using new datasets consisting of simultaneous thermo-TDR sensor measurements of soil water content (θ), λ and σ. New model σ values interpolated between known dry and saturated σ values agreed well with measured σ values, with RMSE values within 0.102 dS m−1 and bias values between −0.083 and 0.014 dS m−1 for a variety of soil samples. Using repeated in situ λ measurements made in soils during an evaporative drying period, the new σ model estimated normalized σ values with RMSEs within 0.015 dS m−1. The new σ model offers an effective way to estimate σ of unsaturated soils.

An improved model for predicting the thermal conductivity of sand based on a grain size distribution parameter

Soil thermal conductivity is a critical parameter in various fields related to soil heat transfer, mainly affected by porosity and saturation. In this research, the thermal conductivity of three types of sands with different properties was measured. Eight soil thermal conductivity models (including two semi-empirical models and six empirical models) were compared and evaluated. By analyzing the inadequacies of the existing models and microscopic mechanism of soil, a grain size distribution parameter was defined, and an improved model was proposed. The results showed that four empirical models from published literature provided relatively satisfactory performance but still required improvement. The improved model can accurately predict the thermal conductivity of different types of soils as the root mean square error for the three soils were 0.072, 0.073, and 0.056 W·m−1· k−1, respectively. Moreover, compared with the existing models, the improved model provided more scientific explanations for the limiting cases of porosity and saturation. In addition, this model revealed a close linear relationship between the thermal conductivity of soil and solid particles. The prominent nonlinear relationships between thermal conductivity and porosity or saturation were also depicted. Furthermore, the content of fine particles has a remarkable impact on the thermal conductivity of dry soil. It is suggested that the improved model can be used for predicting the complete thermal conductivity of soil in case there is no available field test data.

Regulation Effect of Porous Materials on Soil Quality in Farmland

Porous materials of biomass carbonized products have the characteristics of rich carbon, high porosity, high specific surface area and strong adsorption, and are widely used in fields such as improving soil quality in farmland, improving crop productivity, reducing greenhouse gas emissions and mitigating climate change. Based on previous studies, this paper summarized and analyzed the effect of the application of porous materials on the improvement of soil physical and chemical properties and nutrient content, and explored the change of soil thermal properties under the action of porous materials, in order to provide useful reference for the study of porous materials on the improvement of soil quality and crop yield.

Mismatch problem of the model and topology of oil pumping facilities

The mismatch of the model and the topology of real objects is important in modeling technological processes, which is the purpose of this paper. The problem is considered when modeling hot oil pumping in the "Kasymov–Bolshoy Chagan" oil pipeline. In this problem, the topology of objects consists of the linear part of the pipeline and technological equipment (pumps and heating furnaces) of the stations. The accuracy of the simulation results is determined by the calculations of pressure and temperature in the oil pipeline. The pressure in the pipeline is created by pumps at the stations and is determined by the dependence of the pressure and efficiency of the pump on the oil flow rate. These characteristics change depending on the service life of the pump. The identification of the actual dependences of the pressure and efficiency of the pump on the oil flow rate was carried out by the regression analysis of experimental data. The pressure in the linear part is determined by the hydraulic resistance of the pipeline. The actual dependence of the hydraulic resistance coefficient on the Reynolds number and wall roughness was obtained by regression analysis of experimental data. The temperature in the oil pipeline is created at the stations by heating furnaces. The identification of the actual characteristics of the heating furnace was also found by regression analysis of the experimental data. The temperature distribution in the linear part is determined by the heat transfer of oil with the surrounding environment. An undefined parameter for calculating heat transfer is the soil thermal conductivity, which depends on the type of rock and the degree of soil moisture. The soil thermal conductivity is determined in such a way that at a given oil flow rate, oil temperatures at the beginning of the section and soil at the section, the calculated oil temperature at the end of the section has the smallest discrepancy with the actual one. Thus, the determination of the actual dependencies of the objects makes it possible to increase the accuracy of the results of hot pumping modeling and eliminates the mismatches of the model and the topology of the objects.

The thermal response of permafrost to coastal floodplain flooding

Flooding of low-lying Arctic regions has the potential to warm and thaw permafrost by changing the surface reflectance of solar insolation, increasing subsurface soil moisture, and increasing soil thermal conductivity. However, the impact of flooding on permafrost in the continuous permafrost environment remains poorly understood. To address this knowledge gap, we used a combination of available flooding data on the Ikpikpuk delta and a numerical model to simulate the hydro-thermal processes under coastal floodplain flooding. We first constructed the three most common flood events based on water level data on the Ikpikpuk: snowmelt floods in the late spring and early summer, middle and late summer floods, and floods throughout the whole spring and summer. Then the impact of these flooding events on the permafrost was simulated for one-dimensional permafrost columns using the Advanced Terrestrial Simulator (ATSv1.0), a fully coupled permafrost-hydrology and thermal dynamic model. Our results show that coastal floods have an important impact on coastal permafrost dynamics with a cooling effect on the surficial soil and a warming effect on the deeper soil. Cumulative flooding events over several years can cause continuous warming of the deep subsurface but cool down the surficial layer. Flood timing is a primary control of the vertical extent of the permafrost thaw and the active layer deepening.