Using surface solute transport properties measured by time domain reflectometry to predict subsurface leaching

Gaur, Anju
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Solute transport properties are required to evaluate the risk of contaminating ground water with agricultural chemicals under a wide variety of crop and soil management practices. Most solute transport measurement techniques are tedious and lead to extensive soil excavation. Two experiments were performed to evaluate whether surface transport properties determined by a non-destructive time domain reflectometry (TDR) technique could be used to accurately predict subsurface leaching. TDR probes installed in the surface 2-cm of soil were used to determine resident solute concentration from measured soil surface soil bulk electrical conductivity. Resident concentrations were analyzed with a one-dimensional (1-D) solute transport model in order to determine the surface solute transport properties. The surface measurements technique was first tested in a greenhouse soil. Surface dispersivities (1.02 cm) determined by the TDR method were similar to the 30-cm subsurface dispersivities (1.28 cm). The surface solute transport properties were used to predict the chemical concentration distributions within the 30-cm soil layer, and it was found that the centers of mass from predicted and observed subsurface chemical distributions were similar.;Further testing of the TDR technique was done in a strip-cropped tile-drained field. The plant-row and interrow zones significantly affected surface and soil profile (120-cm) dispersivities. The soil profile dispersivity (2.68 cm) was larger and more variable than the surface dispersivity (0.91 cm) indicating greater heterogeneity of flow within the soil profile than at the surface. The large soil profile dispersivity indicated that multidimensional flow and lateral spreading occurred in the soil profile. In order to evaluate solute transport in the soil profile, a 1-D convective lognormal transfer (CLT) function model and a 2-D model (CLT combined with exponential model) were used to make tile flux predictions. Surface transport properties combined with the 2-D model predicted the tile flux concentrations more accurately (root mean square error, RMSE = 0.023) than the 1-D CLT model (RMSE = 0.123). TDR is a promising tool for determining surface solute transport properties. In this field soil, surface solute transport properties can be combined with a 2-D solute transport model for accurate prediction of tile flux concentrations.

Agronomy, Agricultural and biosystems engineering, Water resources, Agricultural engineering