@article{tian_kojima_heitman_horton_ren_2020, title={Advances in thermo-time domain reflectometry technique: Measuring ice content in partially frozen soils}, volume={84}, ISSN={["1435-0661"]}, DOI={10.1002/saj2.20160}, abstractNote={AbstractIce content (θi) is a critical parameter affecting soil thermal, mechanical, and hydraulic properties in cold regions. Few techniques are available for accurately determining θi in laboratory samples and in situ. A combined heat‐pulse and time domain reflectometry (thermo‐TDR) sensor, which measures soil thermal properties and electrical properties simultaneously, can be used to estimate θi. The thermo‐TDR method determines θi by using a heat‐capacity‐based (C‐based) approach or a thermal‐conductivity‐based (λ‐based) approach. Here, we describe the principles and procedures of such approaches. The C‐based thermo‐TDR approach is simple to use and provides reasonable θi values at temperatures below −5°C, but it fails at higher temperatures. The λ‐based approach, which solves for θi from thermo‐TDR measurements with an iterative method, gives more accurate θi estimates than does the C‐based approach and extends the thermo‐TDR measurement range to temperatures near the freezing point of water. Therefore, the λ‐based thermo‐TDR method is preferred for determining θi in partially frozen soils.}, number={5}, journal={SOIL SCIENCE SOCIETY OF AMERICA JOURNAL}, author={Tian, Zhengchao and Kojima, Yuki and Heitman, Joshua L. and Horton, Robert and Ren, Tusheng}, year={2020}, pages={1519–1526} }
 @article{tian_ren_heitman_horton_2020, title={Estimating thermal conductivity of frozen soils from air-filled porosity}, volume={84}, ISSN={["1435-0661"]}, DOI={10.1002/saj2.20102}, abstractNote={AbstractSoil thermal conductivity (λ) is an important thermal property for environmental, agricultural, and engineering heat transfer applications. Existing λ models for frozen soils are complicated to use because they require estimates of both liquid water content and ice content. This study introduces a new approach to estimate λ of partially frozen soils from air‐filled porosity (na), which can be determined by using an oven‐drying method. A λ and na relationship was established based on measurements for 28 partially frozen soils. A strong exponential relationship between λ and na was found (with R2 of 0.82). Independent tests on 10 partially frozen soils showed that the exponential λ–na model produced reliable λ estimates with a RMSE of 0.319 W m−1 K−1, which was smaller than those of two widely used λ models for partially frozen soils. The λ–na model is easier to use than existing models, because it requires fewer parameters. Note that the λ‐na model ignores the effect of temperature on λ of frozen soils and is most applicable to soil at temperatures of at least −4 °C.}, number={5}, journal={SOIL SCIENCE SOCIETY OF AMERICA JOURNAL}, author={Tian, Zhengchao and Ren, Tusheng and Heitman, Joshua L. and Horton, Robert}, year={2020}, pages={1650–1657} }
 @article{tian_chen_cai_gao_ren_heitman_horton_2021, title={New pedotransfer functions for soil water retention curves that better account for bulk density effects}, volume={205}, ISSN={["1879-3444"]}, DOI={10.1016/j.still.2020.104812}, abstractNote={Abstract Pedotransfer functions (PTFs) describing soil water retention curves (WRCs) have been widely used in crop, soil, and land surface models. A limitation of the available PTFs is that they fail to account for shape changes in WRCs due to bulk density variations caused by soil tillage, compaction, and other processes. This study develops new PTFs that include bulk density effects on the WRC shape. A new framework is introduced to build the bulk density-associated PTFs based on a widely-used WRC dataset. The new PTFs were validated by comparing the performance with two common PTFs from the literature using two independent datasets. The results show that the newly developed PTFs provide reliable WRC estimates for the validation datasets, with mean RMSE values of 0.055 and 0.059 m3 m-3, respectively. The accuracy of the new PTFs is comparable or in some cases better than the common PTFs. While the literature PTFs investigated do not always properly describe bulk density effects on WRC changes, the new PTFs effectively account for such effects on the WRC shape, thus have the potential to be integrated into crop and soil management models to represent bulk density impacts on WRCs due to anthropogenic (e.g., plowing and compaction) and natural (e.g., wetting/drying) processes.}, journal={SOIL & TILLAGE RESEARCH}, author={Tian, Zhengchao and Chen, Jiazhou and Cai, Chongfa and Gao, Weida and Ren, Tusheng and Heitman, Joshua L. and Horton, Robert}, year={2021}, month={Jan} }
 @article{kool_tong_tian_heitman_sauer_horton_2021, title={Soil water retention and hydraulic conductivity dynamics following tillage (vol 193, pg 95, 2019)}, volume={207}, ISSN={["1879-3444"]}, DOI={10.1016/j.still.2020.104853}, journal={SOIL & TILLAGE RESEARCH}, author={Kool, D. and Tong, B. and Tian, Z. and Heitman, J. L. and Sauer, T. J. and Horton, R.}, year={2021}, month={Mar} }
 @article{tian_kool_ren_horton_heitman_2019, title={Approaches for estimating unsaturated soil hydraulic conductivities at various bulk densities with the extended Mualem-van Genuchten model}, volume={572}, ISSN={["1879-2707"]}, DOI={10.1016/j.jhydrol.2019.03.027}, abstractNote={The Mualem-van Genuchten model has been widely used for estimating unsaturated soil hydraulic conductivity (Ku) from measured saturated hydraulic conductivity (Ks) and fitted water retention curve (WRC) parameters. Soil bulk density (ρb) variations affect the accuracy of Ku estimates. In this study, we extend the Mualem-van Genuchten model to account for the ρb effect with ρb-related WRC and Ks models. We apply two functions (A and B) that relate the van Genuchten WRC model to ρb and two models (1 and 2) that estimate Ks with various ρb. By combining the ρb-related WRC functions and Ks models, we develop four integrated approaches (i.e., A1, A2, B1, and B2) for estimating Ku at various ρb. Ku measurements made on five soils with various textures and ρb are used to evaluate the accuracy of the four approaches. The results show that all approaches produce reasonable Ku estimates, with average root mean square errors (RMSEs) less than 0.35 (expressed in dimensionless unit because logarithmic Ku values are used). Approach A2, with an average RMSE of 0.25, agrees better with Ku measurements than does Approach A1 that has an average RMSE of 0.28. This is because Model 2 accounts for the WRC shape effect near saturation. Approaches A1 and A2 give more accurate Ku estimates than do Approaches B1 and B2 which both have average RMSEs of 0.35, because Function A performs better in estimating WRCs than does Function B. The proposed approaches could be incorporated into simulation models for improved prediction of water, solute, and gas transport in soils.}, journal={JOURNAL OF HYDROLOGY}, author={Tian, Zhengchao and Kool, Dilia and Ren, Tusheng and Horton, Robert and Heitman, Joshua L.}, year={2019}, month={May}, pages={719–731} }
 @article{tian_ren_horton_heitman_2020, title={Estimating soil bulk density with combined commercial soil water content and thermal property sensors}, volume={196}, ISSN={["1879-3444"]}, DOI={10.1016/j.still.2019.104445}, abstractNote={Accurate information of soil bulk density (ρb) is essential for many models that predict soil water, gas, and heat transfer processes and for estimating soil carbon pools. Several indirect methods have been used to estimate ρb as a derivative of various soil properties. One approach is to estimate ρb from soil thermal conductivity (λ) and volumetric water content (θw) measured with a custom fabricated sensor (thermo-TDR). In this study, we introduce a new approach to determine ρb with a combination of commercially available θw and thermal property sensors. Repacked samples of four differently-textured soils and a field experiment on a clay soil were used to evaluate the ability of four available sensors from METER Group, Inc. (Pullman, WA, USA) to estimate ρb. The θw was measured with the GS3 and EC-5 sensors, and soil λ was determined with the TR-1 and SH-1 thermal property sensors. The θw and λ measurements were used to determine ρb inversely from a λ-model. Compared with the GS3 sensor, the EC-5 sensor provided more accurate measurements of θw for the investigated soils, and thus, the EC-5 sensor was used with the new ρb estimation approach. Both TR-1 and SH-1 sensors gave accurate λ estimates when compared to modeled values. The ρb estimates with the TR-1/EC-5 and SH-1/EC-5 sensor combination methods agreed well with independent gravimetrically-derived ρb values of the repacked samples and the in-situ measurements, with average root mean square errors of 0.12 and 0.13 Mg m−3, respectively. Thus, the commercial multi-sensor combinations can provide accurate ρb estimates similar to those with custom fabricated thermo-TDR sensors, and they are simpler to operate than the custom fabricated sensors.}, journal={SOIL & TILLAGE RESEARCH}, author={Tian, Zhengchao and Ren, Tusheng and Horton, Robert and Heitman, Joshua L.}, year={2020}, month={Feb} }
 @article{fu_tian_amoozegar_heitman_2019, title={Measuring dynamic changes of soil porosity during compaction}, volume={193}, ISSN={0167-1987}, url={http://dx.doi.org/10.1016/j.still.2019.05.016}, DOI={10.1016/j.still.2019.05.016}, abstractNote={Soil porosity and pore-size distribution changes in response to compaction are important for heat, water, and air flow in soils. In this study, we used the thermo-time domain reflectometry (thermo-TDR) technique to investigate dynamics of in-situ soil porosity and pore-size distribution as affected by number of traffic passes, water content and soil depth. The study was conducted at a field site located near Clayton, NC, USA. A roller was dragged across the length of a 3- by 12-m plot three to five times to repeatedly compact the soil after tillage. Nine thermo-TDR probes, installed at 2.5-, 7.5-, and 12.5-cm depths (representing 0–5, 5–10, and 10–15 cm depth intervals, respectively) at three locations within the plot, were used to determine dynamic changes in soil porosity after each compaction event. Pore-size distribution changes within the top soil layer were determined for a subset of conditions by measuring in-situ infiltration at low tension using a mini disk infiltrometer. Nine core samples were also collected (considered to be a destructive method) near each thermo-TDR probe for measuring total porosity and water content after each compaction. Results showed that the thermo-TDR technique can accurately monitor the change of soil porosity during soil compaction compared to the destructive core method. Variability of replicated soil porosity measurements by the thermo-TDR technique (with a root mean square error (RMSE) of 0.011 m3 m−3 and mean standard error (MSE) of 0.010 m3 m−3) was lower than that of the core method (RMSE = 0.017 m3 m−3, MSE = 0.019 m3 m−3). As expected, total soil porosity decreased with the number of passes; a major portion of compaction (59–89% of the total porosity decrease) occurred during the first pass. The trend of topsoil (0–5 cm) compaction differed from that of subsoil layers (5–10 and 10–15 cm). Changes in porosity were highly sensitive to soil water content. For the sandy-textured soil in this study, soil porosity decreased as water content increased (during compaction period), and the maximum compaction (associated with the lowest porosity) was reached at an initial water content range between 0.08 and 0.10 g g-1. Above this range, the compaction level decreased with increasing water content. In addition, there was a shift in pore-size distribution for the surface layer. More importantly, pore-size distribution continued to change with additional traffic passes even after soil total porosity became stable.}, journal={Soil and Tillage Research}, publisher={Elsevier BV}, author={Fu, Yongwei and Tian, Zhengchao and Amoozegar, Aziz and Heitman, Josh}, year={2019}, month={Oct}, pages={114–121} }
 @article{kool_tong_tian_heitman_sauer_horton_2019, title={Soil water retention and hydraulic conductivity dynamics following tillage}, volume={193}, ISSN={0167-1987}, url={http://dx.doi.org/10.1016/j.still.2019.05.020}, DOI={10.1016/j.still.2019.05.020}, abstractNote={Soil bulk density (ρb) may be purposely reduced in agricultural fields using tillage to improve hydraulic properties. However, tillage alters the soil structure, resulting in unstable soils. As the soil stabilizes, ρb increases over time. While this is known, studies on soil hydraulic properties in tilled soils, including comparisons between tilled and non-tilled soils, commonly assume a rigid soil structure. This study presents changes in soil water retention and saturated hydraulic conductivity (Ksat) as ρb increased dynamically with time following tillage at a loam-textured field site. Over the summer of 2015, soil cores were collected at several depths below the surface following precipitation events. Soil water retention curves and Ksat were determined using pressure cells and the constant head method, respectively. Tillage reduced ρb to 0.94 g cm−3. Changes in ρb increased with depth, reaching a ρb of 1.11 g cm−3 in the 0–5 cm layer, and a ρb of 1.42 g cm−3 at the deepest tilled layer. Soil water retention curves were markedly steeper for samples with higher ρb, indicating an overall increase in water retained at a soil matric potential (Ψ) of −33 kPa. Evaluation of two modeling approaches for water retention as a function ρb indicated that changes in water retention with increases in ρb could be reasonably estimated if a matching point was used. No clear relationship between Ksat and ρb was obvious for ρb < 1.06 cm3 cm−3, but for ρb > 1.06 cm3 cm−3, Ksat decreased markedly (order of magnitude) as ρb increased. Hydraulic properties varied strongly depending on time since tillage and soil depth, and results have implications for models of tilled soils, as well as for studies comparing tilled and non-tilled soils.}, journal={Soil and Tillage Research}, publisher={Elsevier BV}, author={Kool, D. and Tong, B. and Tian, Z. and Heitman, J.L. and Sauer, T.J. and Horton, R.}, year={2019}, month={Oct}, pages={95–100} }
 @article{tian_gao_kool_ren_horton_heitman_2018, title={Approaches for Estimating Soil Water Retention Curves at Various Bulk Densities With the Extended Van Genuchten Model}, volume={54}, ISSN={["1944-7973"]}, DOI={10.1029/2018WR022871}, abstractNote={AbstractSoil bulk density (ρb) variations influence soil hydraulic properties, such as the water retention curve (WRC), but they are usually ignored in soil water simulation models. We extend the van Genuchten WRC model parameters to account for ρb variations using a series of empirical expressions. WRC measurements made on eight soils with various ρb, and textures are used to calibrate these ρb‐related empirical equations. Accordingly, two approaches are developed to estimate WRCs of soils at various ρb. Another eight soils with a wide range of ρb and textures are used to evaluate the accuracy of the new approaches. Approach 1 estimates WRCs for each soil at various ρb using a WRC measurement made at a reference ρb and the soil texture fractions. This approach gives reasonable WRC estimates for the eight validation soils, with an average root‐mean‐square error (RMSE) of 0.025 m3/m3 and an average determination coefficient (R2) of 0.94. For Approach 2, a WRC measurement made at a reference ρb and one additional water content‐matric potential value measured at a different ρb value are used, which produces WRC estimates with an average RMSE of 0.017 m3/m3 and an average R2 of 0.97. The methodology used in Approach 2 is also applied to the Brooks and Corey WRC model to obtain accurate and precise WRC estimates. The proposed approaches have the potential to be incorporated into simulation models for estimating soil hydraulic properties that are affected by transient and variable ρb.}, number={8}, journal={WATER RESOURCES RESEARCH}, author={Tian, Zhengchao and Gao, Weida and Kool, Dilia and Ren, Tusheng and Horton, Robert and Heitman, Joshua L.}, year={2018}, month={Aug}, pages={5584–5601} }
 @article{tian_kool_ren_horton_heitman_2018, title={Determining in-situ unsaturated soil hydraulic conductivity at a fine depth scale with heat pulse and water potential sensors}, volume={564}, ISSN={["1879-2707"]}, DOI={10.1016/j.jhydrol.2018.07.052}, abstractNote={Abstract Unsaturated hydraulic conductivity (K) of surface soil changes substantially with space and time, and it is of great importance for many ecological, agricultural, and hydrological applications. In general, K is measured in the laboratory, or more commonly, predicted using soil water retention curve and saturated hydraulic conductivity. In the field, K can be determined through infiltration experiments. However, none of these approaches are capable of continuously monitoring K in-situ at fine depth scales. In this study, we propose and investigate an approach to continuously estimate fine depth-scale K dynamics under field conditions. Evaporation rate and change in water storage in a near-surface soil layer are measured with the heat pulse method. Then, water flux density at the lower boundary of the soil layer is estimated from evaporation rate, change in water storage, and rainfall or irrigation rate using a simple water balance approach. Finally, K values at different soil depths are derived using the Buckingham-Darcy equation from water flux densities and measured water potential gradients. A field experiment is performed to evaluate the performance of the proposed approach. K values at 2-, 4-, 7.5-, and 12.5-cm depths are estimated with the new approach. The results show that in-situ K estimates vary with time following changes in soil water content, and the K-water content relationship changes with depth due to the difference in bulk density. In-situ estimated K-matric potential curves agree well with those measured in the laboratory. In-situ K estimates also show good agreement with the Mualem-van Genuchten model predictions, with an average root mean square error in log10 (K, mm h−1) of 0.54 and an average bias of 0.17. The new approach provides reasonable in-situ K estimates and has potential to reveal the influences of natural soil conditions on hydraulic properties as they change with depth and time.}, journal={JOURNAL OF HYDROLOGY}, author={Tian, Zhengchao and Kool, Dilia and Ren, Tusheng and Horton, Robert and Heitman, Joshua L.}, year={2018}, month={Sep}, pages={802–810} }
 @article{tian_lu_ren_horton_heitman_2018, title={Improved thermo-time domain reflectometry method for continuous in-situ determination of soil bulk density}, volume={178}, ISSN={["1879-3444"]}, DOI={10.1016/j.still.2017.12.021}, abstractNote={Quantifying the dynamics of surface soil bulk density (ρb) is important for characterizing water, heat, and gas exchanges in agricultural and environmental applications. Unfortunately, very few approaches are available for continuous in-situ monitoring of ρb. The soil heat capacity-based (C-based) thermo-time domain reflectometry (thermo-TDR) approach has been used to measure ρb in-situ, but this approach gives ρb estimates with relatively large errors. In this study, we present a new soil thermal conductivity-based (λ-based) thermo-TDR approach for continuous and automatic determination of ρb variation in-situ. An error analysis, literature data, and field experiments were used to evaluate the performance of the C-based and λ-based approaches. The error analysis undertaken on hypothetical soils indicated that the new λ-based approach was less sensitive to errors in the measurement inputs than was the C-based approach when the same relative errors occurred, except on very dry soils. Thermo-TDR measurements reported in the literature on seven soils showed that the new λ-based approach provided more accurate and precise ρb estimates, with coefficient of determination (R2) of 0.70 and root mean square error (RMSE) of 0.103 Mg m−3, than did the C-based approach which gave ρb with R2 of 0.32 and RMSE of 0.178 Mg m−3. Two field experiments were conducted to test the performance of the new λ-based thermo-TDR approach for monitoring ρb dynamics. The results showed that following tillage surface ρb increased by about 35% within 40 days. The ρb obtained by the λ-based thermo-TDR approach agreed well with independent core sampling measurements, with an average RMSE of 0.122 Mg m−3. The C-based approach failed to give acceptable ρb estimates in most cases because of probe deflection and environmental factors. We conclude that the new λ-based thermo-TDR approach is a promising method for continuous in situ measurements of ρb.}, journal={SOIL & TILLAGE RESEARCH}, author={Tian, Zhengchao and Lu, Yili and Ren, Tusheng and Horton, Robert and Heitman, Joshua L.}, year={2018}, month={May}, pages={118–129} }