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Determining in-situ unsaturated soil hydraulic conductivity at a fine depth scale with heat pulse and water potential sensors

Tian, Zhengchao, Kool, Dilia, Ren, Tusheng, Horton, Robert, Heitman, Joshua L.
Journal of hydrology 2018 v.564 pp. 802-810
bulk density, equations, evaporation rate, field experimentation, heat, irrigation rates, monitoring, rain, soil depth, soil quality, soil water, soil water characteristic, soil water content, space and time, unsaturated hydraulic conductivity, water potential, water storage
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.