Determining In-situ Unsaturated Soil Hydraulic Conductivity at a Fine Depth Scale with Heat Pulse and Water Potential Sensors

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 insitu 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

Approaches for estimating unsaturated soil hydraulic conductivities at various bulk densities with the extended Mualem-van Genuchten model

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. Kumeasurements 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

Approaches for estimating soil water retention curves at various bulk densities with the extended van Genuchten model

Soil 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

Whole Brain Mapping of Long-Range Direct Input to Glutamatergic and GABAergic Neurons in Motor Cortex

Long-range neuronal circuits play an important role in motor and sensory information processing. Determining direct synaptic inputs of excited and inhibited neurons is important for understanding the circuit mechanisms involved in regulating movement. Here, we used the monosynaptic rabies tracing technique, combined with fluorescent micro-optical sectional tomography, to characterize the brain-wide input to the motor cortex (MC). The whole brain dataset showed that the main excited and inhibited neurons in the MC received inputs from similar brain regions with a quantitative difference. With 3D reconstruction we found that the distribution of input neurons, that target the primary and secondary MC, had different patterns. In the cortex, the neurons projecting to the primary MC mainly distributed in the lateral and anterior portion, while those to the secondary MC distributed in the medial and posterior portion. The input neurons in the subcortical areas also showed the topographic shift model, as in the thalamus, the neurons distributed as outer and inner shells while the neurons in the claustrum and amygdala were in the ventral and dorsal part, respectively. These results lay the anatomical foundation to understanding the organized pattern of motor circuits and the functional differences between the primary and secondary MC

Estimating thermal conductivity of frozen soils from air‐filled porosity

Soil 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 (n a), which can be determined by using an oven‐drying method. A λ and n a relationship was established based on measurements for 28 partially frozen soils. A strong exponential relationship between λ and n a was found (with R2 of 0.82). Independent tests on 10 partially frozen soils showed that the exponential λ‐n a 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‐n a model is easier to use than existing models, because it requires fewer parameters. Note that the λ‐n a model ignores the effect of temperature on λ of frozen soils and is most applicable to soil at temperatures ≤ ‐4°C.This is a manuscript of an article published as Tian, Zhengchao, Tusheng Ren, Joshua L. Heitman, and Robert Horton. "Estimating thermal conductivity of frozen soils from air‐filled porosity." Soil Science Society of America Journal (2020). doi: 10.1002/saj2.20102. Posted with permission.</p

Self-Assembling RADA16-I Peptide Hydrogel Scaffold Loaded with Tamoxifen for Breast Reconstruction

More and more breast cancer patients prefer autologous fat tissue transfer following lumpectomy to maintain perfect female characteristics. However, the outcome was not satisfactory due to the transplanted fat absorption. In this study, we prepared two RADA16-I peptide scaffolds with and without tamoxifen. Both scaffolds were transparent, porous, and hemisphere-shaped. The hADSCs isolated from liposuction were attached to the scaffold. The growth inhibition of the hADSCs induced by TAM in 2-demensional (2D) culture was higher than that in TAM-loaded hydrogel scaffold 3D culture (P<0.05); however, the same outcomes were not observed in MCF-7 cells. Correspondingly, the apoptosis of the hADSCs induced by TAM was significantly increased in 2D culture compared to that in scaffold 3D culture (P<0.05). Yet the outcomes of the aoptosis in MCF-7 were contrary. Apoptosis-related protein Bcl-2 was involved in the process. In vivo experiments showed that both scaffolds formed a round mass after subcutaneous implantation and it retained its shape after being pressed slightly. The implantation had no effect on the weight and activity of the animals. The results suggested that TAM-loaded RADA16-I hydrogel scaffolds both provide support for hADSCs cells attachment/proliferation and retain cytotoxic effect on MCF-7 cells, which might be a promising therapeutic breast tissue following lumpectomy

Structural Changes of Compacted Soil Layers in Northeast China due to Freezing-Thawing Processes

Soil compaction has become a global concern that reduces soil quality and may jeopardize agricultural sustainability. The objective of this study is to evaluate if the freezing&ndash;thawing process can alleviate the negative effects of soil compaction during overwinter time in Northeast China. The field experiment was a split plot design including two surface treatments (bare and mulch) and three compaction levels (low, moderate, and high compactions with initial bulk densities of 1.2, 1.4 and 1.6 g cm&minus;3). Results showed that compared with initial values in the fall, freezing&ndash;thawing events increased soil porosity (by 4.28% to 25.68%) and the ratio of large-size pores (by 44.5% to 387.6%) after thawing in the spring. The greatest changes were observed in the high compaction treatment, and mulch-enhanced soil structural transformation. Additionally, the ratio of large-size aggregates (&gt;1 mm) was increased and the fraction of small-size aggregates (&lt;1 mm) was decreased. These changes in soil structural characteristics were attributed mainly to the modification of ice-filled pores space during the overwinter period. We concluded that the freezing&ndash;thawing process was an effective natural force for ameliorating soil compaction in Northeast China

Determining In-situ Unsaturated Soil Hydraulic Conductivity at a Fine Depth Scale with Heat Pulse and Water Potential Sensors

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 insitu 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.This is a manuscript of an article published as Tian, Zhengchao, Dilia Kool, Tusheng Ren, Robert Horton, and Joshua L. Heitman. "Determining In-situ Unsaturated Soil Hydraulic Conductivity at a Fine Depth Scale with Heat Pulse and Water Potential Sensors." Journal of Hydrology (2018). doi: 10.1016/j.jhydrol.2018.07.052. Posted with permission.</p

Approaches for estimating unsaturated soil hydraulic conductivities at various bulk densities with the extended Mualem-van Genuchten model

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. Kumeasurements 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.This is a manuscript of an article published as Tian, Z., Kool, D., Ren, T., Horton, R., Heitman, J.L., Approaches for estimating unsaturated soil hydraulic conductivities at various bulk densities with the extended Mualem-van Genuchten model, Journal of Hydrology (2019), doi: 10.1016/j.jhydrol.2019.03.027.</p

Numerical simulation of three-dimensional fracturing fracture propagation in radial wells

A fracture propagation model of radial well fracturing is established based on the finite element-meshless method. The model considers the coupling effect of fracturing fluid flow and rock matrix deformation. The fracture geometries of radial well fracturing are simulated, the induction effect of radial well on the fracture is quantitatively characterized, and the influences of azimuth, horizontal principle stress difference, and reservoir matrix permeability on the fracture geometries are revealed. The radial wells can induce the fractures to extend parallel to their axes when two radial wells in the same layer are fractured. When the radial wells are symmetrically distributed along the direction of the minimum horizontal principle stress with the azimuth greater than 15°, the extrusion effect reduces the fracture length of radial wells. When the radial wells are symmetrically distributed along the direction of the maximum horizontal principal stress, the extrusion increases the fracture length of the radial wells. The fracture geometries are controlled by the rectification of radial borehole, the extrusion between radial wells in the same layer, and the deflection of the maximum horizontal principal stress. When the radial wells are distributed along the minimum horizontal principal stress symmetrically, the fracture length induced by the radial well decreases with the increase of azimuth; in contrast, when the radial wells are distributed along the maximum horizontal principal stress symmetrically, the fracture length induced by the radial well first decreases and then increases with the increase of azimuth. The fracture length induced by the radial well decreases with the increase of horizontal principal stress difference. The increase of rock matrix permeability and pore pressure of the matrix around radial wells makes the inducing effect of the radial well on fractures increase