Processes In Cold Regions Research Articles

Dynamic characteristics of soil pore structure and water-heat variations during freeze-thaw process

Freeze-thaw processes in cold regions alter soil pore structure and properties, leading to engineering geological issues. Soil pores are crucial, but research on their changes and freeze-thaw impacts is limited. This study used MRI-Cryogenic Soil Moisture Analyzer (MRI-CSMA) to explore pore structure, water, and temperature changes in saturated loess during freeze-thaw, and Scanning Electron Microscopy (SEM) to compare changes before and after. The results indicate that during the freezing process, the temperature in the frozen zone of the soil sample exhibited a staged change characterized by rapid cooling, transitional cooling, and stabilization at low temperatures, while the temperature decrease in the unfrozen zone showed no significant stages. Freeze-thaw action significantly affected the macropores and mesopores in the frozen zone, with an average increase of 15 % in macropores, a decrease of 16 % in mesopores, and minimal change in micropores (about a 1 % increase). In the unfrozen zone, there was a slight increase in micropores and mesopores (2 % and 3 %, respectively), and a 4 % decrease in macropores. Furthermore, during the freezing process, macropores in the unfrozen zone gradually decreased, while mesopores and micropores increased, leading to soil structure densification and promoting water migration towards the freezing front. This resulted in an initial increase followed by a decrease in water content near the freezing front during the early stages of freezing, confirming the view that pore structure compression drives water migration in the early stages of soil freezing. This study provides important insights for addressing engineering geological issues in cold regions under freeze-thaw conditions.

High resolution (1-km) surface soil moisture generation from SMAP SSM by considering its difference between freezing and thawing periods in the source region of the Yellow River

Soil moisture (SM) is a critical component of the land surface hydrological cycle, significantly impacting various sectors such as hydrology, meteorology, and agriculture. Accurate, high-resolution SM data are essential for effective flood forecasting, water resource management, and understanding the soil freeze-thaw processes in cold regions. This study aims to generate 1 km resolution liquid surface SM (SSM) data with a twice-daily update frequency by downscaling SMAP Level-4 SSM data using random forest (RF) and multiple linear regression (MLR) in the source region of the Yellow River (SRYR), by considering the differences in SM changes between freezing and thawing periods. To obtain the SSM data, 16 downscaling schemes of both RF and MLR were designed for each of the three scenarios. In each downscaling process, both land surface temperature (LST) and normalized difference vegetation index (NDVI) were utilized in MLR and RF models, alongside various combinations of additional variables such as albedo, elevation, leaf area index (LAI), soil texture. Results showed that during the freezing period, RF produced superior SSM estimates when supplemented with NDVI, LST, albedo, elevation, LAI, and soil texture. MLR was more effective during the thawing period when paired with NDVI, LST, elevation, LAI, and soil texture. During the freezing period, the downscaled SMAP SSM exhibited average R, RMSE, ubRMSE of 0.76, 0.029 m3·m-3, and 0.023 m3·m-3, respectively, when compared with in-situ measurements. During the thawing period, the average R, MAE, RMSE, and ubRMSE between the downscaled SMAP SSM and in-situ measurements were 0.52, 0.057 m3·m-3, 0.067 m3·m-3, and 0.054 m3·m-3, respectively, compared to 0.45, 0.070 m3·m-3, 0.083 m3·m-3, and 0.060 m3·m-3 for the original SMAP SSM. Thus, the research significantly enhances both the accuracy and spatial resolution of SMAP SSM estimations, underscoring its vital role in advancing hydrological studies within the SRYR.

Towards an improved prediction of soil-freezing characteristic curve based on extreme gradient boosting model

As an essential property of frozen soils, change of unfrozen water content (UWC) with temperature, namely soil-freezing characteristic curve (SFCC), plays significant roles in numerous physical, hydraulic and mechanical processes in cold regions, including the heat and water transfer within soils and at the land–atmosphere interface, frost heave and thaw settlement, as well as the simulation of coupled thermo-hydro-mechanical interactions. Although various models have been proposed to estimate SFCC, their applicability remains limited due to their derivation from specific soil types, soil treatments, and test devices. Accordingly, this study proposes a novel data-driven model to predict the SFCC using an extreme Gradient Boosting (XGBoost) model. A systematic database for SFCC of frozen soils compiled from extensive experimental investigations via various testing methods was utilized to train the XGBoost model. The predicted soil freezing characteristic curves (SFCC, UWC as a function of temperature) from the well-trained XGBoost model were compared with original experimental data and three conventional models. The results demonstrate the superior performance of the proposed XGBoost model over the traditional models in predicting SFCC. This study provides valuable insights for future investigations regarding the SFCC of frozen soils.

Divergent controlling factors of freeze–thaw-induced changes in dissolved organic carbon and microbial biomass carbon between topsoil and subsoil of cold alpine grasslands

Freeze-thaw (FT) processes in cold regions significantly influence the mineralization and sequestration of soil organic carbon (SOC), particularly in its active pools, such as dissolved organic carbon (DOC) and microbial biomass carbon (MBC). However, manipulation experiments often amplify the effects of natural FT processes and overlook soils below 20 cm depth. To investigate carbon responses to seasonal FT events across soil depths (0–80 cm) and identify controlling factors, field sampling was conducted before freezing and after thawing in alpine grassland soils on the Qinghai-Tibet Plateau. Results are as follows: 1) After soil thawing, the entire soil profile showed insignificant changes in SOC (−4.46%) and MBC (3.21%), but DOC (45.27%) and DOC/SOC (160.08%) increased significantly, and strong associations were observed in DOC changes between adjacent soil layers. 2) FT indicators (number and temperature amplitude of daily FT cycles, frozen temperature, and frozen days) influenced SOC changes differently in the topsoil (0–10 cm) and subsoil (20–30 cm). Contrary to the impact of frozen temperature, other FT indicators largely facilitated the production of DOC0–10 and DOC20–30. The effects of FT indicators on MBC were nonlinear. 3) Structural equation models indicated that average soil water governed FT-induced changes in both DOC0–10 and DOC20–30. The varying effects of porosity and pH from topsoil to subsoil, along with the weakening relationship between changes in DOC and MBC, favored a stronger increase in DOC20–30. Increases in soil water and DOC after thawing stimulated the increment of MBC0–10, while porosity (positively) and sand content (negatively) regulated the MBC20–30 change. It indicates that, influenced by soil structure and biogeochemical environment, DOC and MBC in grassland soils are more sensitive to natural FT processes than SOC. Nevertheless, changes in FT patterns due to long-term climate change may cumulatively affect SOC.

Estimation of Permafrost Ground Ice to 10 m Depth on the Qinghai‐Tibet Plateau

ABSTRACTPermafrost ground ice melting could alter hydrological processes in cold regions by releasing water. Currently, there is a lack of gridded data of ground ice from the Qinghai‐Tibet Plateau (QTP). Using 664 borehole sample records, we applied a random forest (RF) method to predict the ground ice content of permafrost between 2 and 10 m depth in three layers (2–3, 3–5, and 5–10 m) at a spatial resolution of 1 km. The RF predictions demonstrated an R2 value exceeding 0.80 for all three layers with a negligible positive overestimation (0.98%–1.85%). The ground ice content of the first layer (2–3 m) can be predicted primarily using climate variables, but the contribution of terrain and soil variables increases as the depth increases. The total water storage of ground ice across the QTP permafrost (2–10 m depth) is approximately 3330.0 km3, with 403.5 km3 in the 2–3 m layer, 857.2 km3 in the 3–5 m layer, and 2069.3 km3 in the 5–10 m layer. This study generated for the first time a gridded dataset of the shallow permafrost ground ice content across the entire QTP which can be used to improve simulations of hydrological processes in the permafrost regions.

Modeling hydraulic conductivity function of frozen soil

Hydraulic conductivity function for frozen soils (HCFF) is crucial for accurately simulating the water transfer process in cold regions, impacting hydrological states and frost heave diseases. However, the HCFF model capturing the relation between hydraulic conductivity and unfrozen water content (θ) or temperature (T) remains an open question. This study delves into HCFF encompassing both empirical and prediction models. This study begins with introducing θ-form and innovative T-form empirical HCFF models, showcasing their solid performance in fitting measured hydraulic conductivity data. Furthermore, the extension of the T-form empirical model to incorporate vapor flow and bimodal soils, through the introduction of maximum vapor conductivity and weighting factors, demonstrates a closer alignment with physical mechanisms and observed trends. In terms of predicting HCFF, the study provides a theoretical foundation through statistical hydraulic conductivity models and thermodynamic equilibrium in frozen soils. Additionally, it clarifies three routes for HCFF prediction—single Soil Freeze Characteristic Curve (SFCC), single Soil Water Characteristic Curve (SWCC), and a combination of the two—and validates their effectiveness through test results and comparison of HCFF prediction outcomes using SWCC and SFCC data from specific soil samples. In practice, the empirical and prediction models are recommended for available hydraulic conductivity data and available SFCC or SWCC data, respectively. Overall, this study not only lays the theoretical groundwork for most prediction models but also presents a valid empirical equation for modeling hydraulic conductivity function tailored specifically for frozen soils.

Estimation of unfrozen water content in frozen soils based on data interpolation and constrained monotonic neural network

Accurately predicting the unfrozen water content (UWC) in frozen soils is crucial for modeling various soil processes in cold regions. However, existing empirical and theoretical models suffer limitations due to oversimplified assumptions or limited applicable conditions. Meanwhile, data-driven approaches are typically challenged by insufficient high-quality data and poor alignment with the underlying mechanisms in question. In the present study, a monotonic neural network (MNN) model for generalized UWC prediction was developed by leveraging data interpolation and monotonicity constraints. Experimental UWC data of various soils were collected from the literature and a raw dataset was formed. By first best-fitting each UWC curve in the raw dataset and then data interpolation, a new large dataset was generated and used for model development. A constrained MNN architecture for estimating UWC was constructed by constraining the weights of the neural network. The performance of the MNN was then compared with a standard deep neural network (DNN). The results demonstrated that the statistical characteristics of the generated dataset were comparable to that of the raw dataset. Both the MNN and DNN achieved good performance on the generated dataset. However, compared to DNN, the MNN yielded much more accurate prediction when tested on three new soils. In addition, the MNN was able to consistently give monotonic prediction on the UWC-Temperature relationship, even though both the monotonic and non-monotonic data were used for training. Overall, the monotonicity-constrained MNN can provide a robust and physical mechanisms aligned solution for estimating UWC in frozen soils.

Characteristics of ground source heat pump considering soil freezing process in cold regions

Characteristics of ground source heat pump considering soil freezing process in cold regions

Heat flow characteristics and thermal resistance model for soil-rock mixtures during freezing-thawing processes: Damping properties

As a special heterogeneous geological material, soil-rock mixtures are widely distributed in nature and used in civil engineering. Heat flow is one of the most significant factors affecting the development of water balance and redistribution, ground temperature evolution, and heat transport processes in cold regions. This study explores the heat flow characteristics and generalized thermal resistance model for soil-rock mixtures during freezing-thawing processes. A series of freezing-thawing experiments for soil-rock mixtures with different rock contents (i.e., 10%, 25%, and 40%) were conducted. The effects of rock content and water–ice phase transition on heat flux during the freezing-thawing processes were analyzed, and the damping properties of heat flow for soil-rock mixtures during freeze–thaw cycles were found and illustrated. Subsequently, a generalized thermal resistance model for soil-rock mixtures was proposed and discussed. The results show that the freezing-thawing processes and rock content significantly influence the heat flux and soil temperature of the soil-rock mixtures. Regardless of rock content, the sums of heat flux in freezing and thawing stages all firstly decreased, and then gradually tends to be stable with freeze–thaw cycles. Besides, the reduction of volumetric unfrozen water content increases with the freeze–thaw cycles, and the amplitude of unfrozen water reduction for sample with high rock content is larger than that with low rock content. Additionally, owing to the effect of the latent heat released by water/ice phase transition and thermal sensitive property of rock, the variation of heat flow for soil-rock mixtures presents damping property in the stages without completely freezing, and the variation of heat flow exhibits reversed damping property in the post-freezing stages due to the denser structure and ice crystal growth. Furthermore, based on the thermal resistance in series, characteristics of water–ice phase transition, and thermal sensitive property of rocks, a new generalized thermal resistance model of soil-rock mixtures during freezing-thawing processes is proposed.

Thermokarst lakes group accelerates permafrost degradation in the Qinghai–Tibet Plateau, China: A modeling study

Thermokarst lakes in the Qinghai–Tibet Plateau (QTP) are increasing in number and lake surface area, intensifying the lake–permafrost interaction and making it more complex, thus affecting the hydrological and ecological environment. Although the impact of the individual lake on permafrost has been studied, the effects of lakes group on permafrost and regional hydrological processes remain unexplored. Hence, in this study, modified SUTRA models considering thermal conduction and convection processes were established for five scenarios, including a current environment and four thought experiments, to determine whether and how thermokarst lakes group accelerates permafrost degradation. The models could effectively simulate the variations in the ground temperature with time and depth, with the highest RMSE and lowest R2 being 1.443 °C and 0.706, respectively. Thermal conduction and convection played a dominant role before and after the formation of through-taliks below the thermokarst lakes, respectively. Through-taliks strengthened the hydraulic connection between supra-permafrost water, sub-permafrost water, and lakes, and changed the groundwater circulation pattern. An increase in the number of thermokarst lakes led to the formation of more through-taliks and improved the heat transfer efficiency, accelerating permafrost degradation. Thermal erosion of the permafrost base was more severe in the presence of a recharge source and pathway via a talik. The results highlight the importance of thermal convection and groundwater circulation in permafrost degradation. The findings can help understand the interaction mechanism between permafrost and thermokarst lakes and the variation in environmental and eco-hydrological processes in cold regions.

Measuring soil freezing characteristic curve with thermo‐time domain reflectometry

AbstractThe soil freezing characteristic curve (SFCC) has applications in determining the soil water retention curve (SWRC) and modelling thermal and hydrological processes in cold regions. Accurate measurement of the SFCC in the laboratory has been constrained to the thawing process because of the interference of supercooling during the freezing process. In this study, we introduce a dynamic method based on the technique of thermo‐time domain reflectometry (thermo‐TDR) for measuring the SFCC quickly and accurately. A simple iced‐toothpick approach was used for eliminating supercooling during a freezing experiment. The performance of the thermo‐TDR‐based method was evaluated by comparing the measurements with the equilibration method on two soils of different textures. The results showed that the supercooling phenomena during the freezing process could be eliminated effectively by inserting iced‐toothpicks into the samples at soil freezing point, and both the SFCC (at a freezing rate of 2.5°C h−1) and the soil thawing characteristic curves (STCC) could be determined accurately with the thermo‐TDR‐based method. The thermo‐TDR measured SFCCs agreed well with estimates from the SWRCs, with an average root‐mean square error (RMSE) of 0.02 m3 m−3. The dynamic thermo‐TDR‐based method has the advantages of being easy to operate, time‐saving, and applicable for in situ monitoring of SFCC, and could be used to determine SWRCs indirectly.Highlights The thermo‐TDR method can measure the soil freezing characteristic curve (SFCC) accurately. Supercooling during the freezing process was eliminated by using an iced‐toothpick approach. The slow‐rate dynamic method provided reliable SFCCs as compared with the equilibration method. The thermo‐TDR measured SFCCs could be used to estimate soil water retention curves.

Estimating snow cover from high-resolution satellite imagery by thresholding blue wavelengths

The extent and duration of snow cover, a critical component of the hydrologic cycle and the global climate system, is expected to shift dramatically under climate change. Therefore, developing high-resolution assessments of snow cover change is crucial for estimating the impact of changing snow cover on watershed and ecosystems processes in cold regions. Remote sensing tools provide a powerful method for mapping snow-covered area (SCA) across a landscape. The most common method for estimating SCA utilizes the normalized difference snow index (NDSI), which relies on spectral measurements in the shortwave-infrared wavelengths (SWIR). NDSI can effectively estimate catchment- to regional-scale SCA, but it cannot be used to assess fine-scale SCA because of current limitations on the spatial resolution of satellite-derived SWIR measurements. Here, we map SCA using a threshold of blue wavelengths and high-resolution satellite imagery. The thresholding method, which we call the Blue Snow Threshold algorithm (BST), has previously been used with digital camera imagery. We refine and automate the algorithm for use with cloud-free high-resolution satellite imagery and find that the BST can be used to assess fine-scale SCA. For validation, we compared BST-derived estimates of SCA to a) airborne lidar surveys, b) Landsat fractional SCA, and c) snow disappearance dates from Snow Telemetry (SNOTEL) stations. When compared to airborne lidar surveys of SCA, the BST predicted SCA had a range of F-scores between 0.81 and 0.94 in four study areas in California and Colorado. We also found general agreement between SCA and snow disappearance at multiple SNOTEL sites across the western United States. Given the relatively recent availability of high-resolution satellite imagery with spectral measurements in the visible wavelengths but lacking in SWIR, the BST offers a reliable and easy-to-apply tool for examining fine-scale snow-related processes.

Analysis of the Runoff Component Variation Mechanisms in the Cold Region of Northeastern China under Climate Change

Climate change alters hydrological processes in cold regions. However, the mechanisms of runoff component variation remain obscure. We implemented a WEP-N model to estimate monthly runoff in the Songhua River Basin (SRB) between 1956 and 2018. All flow simulations were accurate (NSE > 0.75 and RE < 5%). The annual runoff was attenuated in 1998, and the hydrological series (1956–2018) was divided into base and change periods in that year. Relative to the BS (base scenario), annual production flow reduction was −28.2% under climate change and water use. A multifactor attribution analysis showed that climate change and water use contributed 77.0% and 23.0% to annual runoff reduction, respectively. Decreases in annual surface and base flow explained 62.1% and 35.7% of annual production flow reduction, respectively. The base flow increased by 8.5% and 6.5% during the freezing and thawing periods, respectively. Relative to the BS, groundwater recharge increased by 9.2% and 4.1% during the freezing and thawing periods, respectively, under climate change conditions. Climate change was the dominant factor attenuating production flow. The change in production flow occurred mainly during the non-freeze-thaw period. The decrease in total production flow in the SRB was caused mainly by the decrease in the surface flow, where the reduction in base flow accounted for a relatively small proportion. Production flow attenuation aggravated water shortages. The utilization rate of groundwater resources is far below the internationally recognized alarm line. Therefore, attention should be directed towards certain areas of the SRB and other regions with minimal groundwater exploitation.

Recession and hysteresis effects of hyporheic zone permeability changes on baseflow in seasonal freeze-thaw mountainous areas

Baseflow is the main groundwater discharge mode from mountainous areas to rivers and is an important component of river runoff. Temperature changes in the hyporheic zone in seasonal freeze–thaw areas cause changes in its permeability, which then affect the recession of baseflow. It is critical to study underground surface water transformation processes in cold regions to explore baseflow recession and hysteresis effects caused by permeability changes in the hyporheic zone under variable temperatures. In this study, we investigated the Hanyangtun Basin in the Changbai Mountain District to determine the functional relationship between permeability and temperature in the hyporheic zone using theoretical analysis combined with laboratory saturated permeability experiments using medium- and fine-grained sand at variable temperatures. We then calculated and analyzed the recession amplitude and hysteresis time of the baseflow caused by permeability changes in the hyporheic zone of this freeze–thaw mountainous area using water temperature and reference baseflow data. The results indicate that owing to large temperature changes in the study area, the permeability of the hyporheic zone changed substantially. Lower permeability leads to the blocking of groundwater discharging to surface water, i.e., the baseflow hysteresis effect. The recession amplitude of the baseflow caused by lower permeability increased with decreasing temperatures, reaching a maximum of 41.67%. The groundwater discharge hysteresis time increased with decreasing temperature. The hysteresis effect was most obvious during the stable melting period, with a maximum hysteresis time of 16 days, while the total annual hysteresis time was 60 days. This study provides a new perspective for qualitative and quantitative studies of the relationship between groundwater and surface water in the mountainous areas that experience seasonal freeze–thaw.

The Impact of Freeze‐Thaw History on Soil Carbon Response to Experimental Freeze‐Thaw Cycles

AbstractFreeze‐thaw is a disturbance process in cold regions where permafrost soils are becoming vulnerable to temperature fluctuations above 0°C. Freeze‐thaw alters soil physical and biogeochemical properties with implications for carbon persistence and emissions in Arctic landscapes. We examined whether different freeze‐thaw histories in two soil systems led to contrasting biogeochemical responses under a laboratory‐controlled freeze‐thaw incubation. We investigated controls on carbon composition through Fourier‐transform ion cyclotron resonance mass spectrometry (FT‐ICR‐MS) to identify nominal carbon oxidation states and relative abundances of aliphatic‐type carbon molecules in both surface and subsurface soils. Soil cores (∼60 cm‐depth) were sampled from two sites in Alaskan permafrost landscapes with different in situ freeze‐thaw characteristics: Healy (>40 freeze‐thaw cycles annually) and Toolik (<15 freeze‐thaw cycles annually). FT‐ICR‐MS was coupled with in situ temperature data and soil properties (i.e., soil texture, mineralogy) to assess (a) differences in soil organic matter composition associated with previous freeze‐thaw history and (b) sensitivity to experimental freeze‐thaw in the extracted cores. Control (freeze‐only) samples showed greater carbon oxidation in Healy soils compared with Toolik, even in lower mineral horizons where freeze‐thaw history was comparable across both sites. Healy showed the most loss of carbon compounds following experimental freeze‐thaw in the lower mineral depths, including a decrease in aliphatics. Toolik soils responded more slowly to freeze‐thaw as shown by intermediary carbon oxidation distributed across multiple carbon compound classes. Variations in the response of permafrost carbon chemistry to freeze‐thaw is an important factor for predicting changes in soil function as permafrost thaws in high northern latitudes.

A Review of the Research on Thermo-Hydro-Mechanical Coupling for the Frozen Soil

This paper reviews the history of the research development on the coupling mechanism of the multiphysical field, e.g., thermo-hydro-mechanical (THM), for frozen soil. The objective is to deepen the current understanding of the theories and mechanism of multiphysical field coupling in the frozen soil and the dynamic changes in the temperature, moisture, and stress fields during soil freezing. A new differential equation of the coupling of temperature field and moisture field is proposed. Based on the DiscreteFrechetDist algorithm, a fitting method of evaluating a curve is proposed. The paper is expected to help understand the soil freezing process in cold regions and enhance the innovativeness of the research methodologies dealing with multifield coupling for the frozen soil.

Study on Energy Dissipation Characteristic of Ice-Rich Frozen Soil in SHPB Compression Tests

Frozen soil will inevitably bear dynamic loads (impact and blasting) in the construction process in cold regions; the investigation of dynamic energy dissipation characteristic of ice-rich frozen soil is beneficial to optimize blasting parameters and the design of underground explosion-proof structure. In this study, the dynamic impact laboratory tests were conducted for frozen sandy soil with various water contents (from 15% to 110%) and strain rates (from 450 s-1 to 728 s-1) based on the split Hopkinson pressure bar (SHPB) system. The influences of strain rate, temperature, and water content on the energy parameters (i.e., absorption energy, reflected energy, and absorption energy rate) were systematically analyzed. Moreover, the energy dissipation characteristics of frozen sandy soil under different deformation stages were studied. Test results revealed that under impact load, the proportion of reflected energy to incident energy was the largest for frozen soil materials. Both the absorption energy and reflected energy were associated with strain rate. However, compared with the water content and temperature, the sensitivities of strain rate on the absorption energy rate were not obvious. At -10°C, the average absorption energy rate decreases from 17.6% to 14.5% when the water content increases from 15% to 37.5%, with a reduction of 18%. However, it substantially decreases to 6.9% at 45% water content, with a large-scale reduction of 61% compared with that at 15% water content. The energy dissipation parameters (i.e., absorption energy, releasable elastic strain energy, and dissipation energy) were closely associated with the water content, temperature, and strain rate.

Compound changes in temperature and snow depth lead to asymmetric and nonlinear responses in landscape freeze\u2013thaw

Cycles of freeze–thaw (FT) are among the key landscape processes in cold regions. Under current global warming, understanding the alterations in FT characteristics is of a great importance for advising land management strategies in northern latitudes. Using a generic statistical approach, we address the impacts of compound changes in air temperature and snow depth on FT responses across Québec, a Canadian province ~ 2.5 times larger than France. Our findings show significant and complex responses of landscape FT to compound changes in temperature and snow depth. We note a vivid spatial divide between northern and southern regions and point to the asymmetric and nonlinear nature of the FT response. In general, the response of FT characteristics is amplified under compound warming compared to cooling conditions. In addition, FT responses include nonlinearity, meaning that compounding changes in temperature and snow depth have more severe impacts compared to the cumulative response of each individually. These asymmetric and nonlinear responses have important implications for the future environment and socio-economic management in a thawing Québec and highlight the complexity of landscape responses to climatic changes in cold regions.

Can we use precipitation isotope outputs of isotopic general circulation models to improve hydrological modeling in large mountainous catchments on the Tibetan Plateau?

Abstract. Issues related to large uncertainty and parameter equifinality have posed big challenges for hydrological modeling in cold regions where runoff generation processes are particularly complicated. Tracer-aided hydrological models that integrate the transportation and fractionation processes of water stable isotope are increasingly used to constrain parameter uncertainty and refine the parameterizations of specific hydrological processes in cold regions. However, the common unavailability of site sampling of spatially distributed precipitation isotopes hampers the practical applications of tracer-aided models in large-scale catchments. This study, taking the precipitation isotope data (isotopes-incorporated global spectral model – isoGSM) derived from the isotopic general circulation models (iGCMs) as an example, explored its utility in driving a tracer-aided hydrological model in the Yarlung Tsangpo River basin (YTR; around 2×105 km2, with a mean elevation of 4875 m) on the Tibetan Plateau (TP). The isoGSM product was firstly corrected based on the biases between gridded precipitation isotope estimates and the limited site sampling measurements. Model simulations driven by the corrected isoGSM data were then compared with those forced by spatially interpolated precipitation isotopes from site sampling measurements. Our results indicated that (1) spatial precipitation isotopes derived from the isoGSM data helped to reduce modeling uncertainty and improve parameter identifiability in a large mountainous catchment on the TP, compared to a calibration method using discharge and snow cover area fraction without any information on water isotopes; (2) model parameters estimated by the corrected isoGSM data presented higher transferability to nested subbasins and produced higher model performance in the validation period than that estimated by the interpolated precipitation isotope data from site sampling measurements; (3) model calibration forced by the corrected isoGSM data successfully rejected parameter sets that overestimated glacier melt contribution and gave more reliable contributions of runoff components, indicating the corrected isoGSM data served as a better choice to provide informative spatial precipitation isotope than the interpolated data from site sampling measurements at the macro scale. This work suggested plausible utility of combining isoGSM data with measurements, even from a sparse sampling network, in improving hydrological modeling in large high mountain basins.

Experimental investigation on improving defrosting performance of air source heat pump through vapor injection

During the defrosting process in cold regions, the air source heat pump with vapor injection encounters some problems, e.g. long defrosting time and low defrosting efficiency. To solve these problems, a new defrosting strategy through injecting medium-pressure vapor refrigerant into compressor during defrosting process was proposed based on its special structure. Five groups of experiments having different openings of injection electronic expansion valve were designed and conducted to investigate the effect of this defrosting strategy. Results indicate that an optimal opening of injection electronic expansion valve exists during defrosting process with vapor injection. For the experimental air source heat pump, it is 50%. At the opening of less than 50%, the experimental unit can run safely and defrosting performance improves gradually with the opening increase. When the opening increases to greater than 50%, the defrosting process is unsteady. At the optimal opening of injection electronic expansion valve, the defrosting time and power consumption are respectively decreased by 20.61% and 17.98%, while the defrosting efficiency is improved by 6.22%.