The soil water retention curve (SWRC) is essential for the modeling of water flow and chemical transport in the vadose zone. The Campbell function and its b (poresize distribution index) parameter fitted to measured data is a simple method to quantify retention under relatively moist conditions. Measuring soil water retention is time consuming, and a method to accurately predict the Campbell relation from either typically available soil parameters such as bulk density, clay-size fraction, and organic matter content (soil fines) or from visible-near-infrared (vis-NIR) spectroscopy may provide a fast and inexpensive alternative. However, the traditional Campbell model has a reference point at saturated water content, and this soil-structure-dependent water content will typically be poorly related to basic texture properties and thus be poorly predicted from vis-NIR spectra. In this study, we anchor the Campbell model at the water content at −1000 cm H 2 O matric potential [log(1000)= pF 3]. Agricultural soil samples with a wide textural range from across Denmark were used. Soil water retention was measured at a number of matric potentials between pF 1 and 3. The soil water content at pF 3 and Campbell b were both well predicted using either a soil-fines-based pedotransfer function or vis-NIR spectroscopy. The resulting Campbell function anchored at pF 3 compared closely to measured water retention data for a majority of soils. The ability of the two methods to also predict field average SWRC was evaluated for three fields. Field average, predicted SWRC compared well with field average measured data, with vis-NIR overall performing better.Abbreviations: CF, clay-size fraction; PLS, partial least squares; RMSEC, root mean square error of calibration; RMSECV, root mean square error of cross-validation; RPIQ, ratio of performance to interquartile distance; R 2 Cal, coefficient of variation of the calibration dataset; R 2 CV, coefficient of variation of the cross-validation dataset; OM, organic matter; SWRC, soil water retention curve; vis-NIR, visible-near-infrared.The soil water retention curve (SWRC), which relates the soil water content and matric potential, is important for understanding water and solute movement in the vadose zone and water availability for plants. However, measuring the SWRC in the laboratory is a highly time consuming and laborious process. During the last decades, several mechanistic and empirical models for predicting the SWRC have been proposed (Brooks
Parameterization of theeffective properties as input in hydrogeological models for simulating water flow is a time consuming and costly process, and it is characterized by high uncertainty because of the spatial variability of soil properties. Integrating visible−near-infrared spectroscopy (vis−NIRS) models and a developed pedotransfer function, a hydrogeological tool was suggested by Varvaris et al. in 2019 for estimating the hydraulic properties used in an equilibrium approach. In the current study, the proposed concept was further expanded for assisting on a rapid and inexpensive parameterization of effective parameters in nonequilibrium models. In our approach, the soil-water retention curves for the wet and hyper-dry ends were predicted using existing vis−NIRS calibration models for obtaining the parameters for the Campbell retention model and the Campbell and Shiozawa model, respectively.The HYDRUS-2D software package was used to simulate tile drainage discharge in a loamy structured field using as initial input hydraulic parameters the output from the suggested concept. The estimated parameters were validated based on measured hydraulic properties in the laboratory. Two-dimensional models incorporating nonequilibrium flow were used to evaluate the ability of each approach to predict the tile drainage discharge: a single-porosity with modified van Genuchten function, a dual-porosity model, and a dual-permeability model. All approaches gave a fairly good fit to the hydrograph features for both calibration and validation datasets with dual-porosity to present the highest predictive ability. Finally, the suggested initial parameterization concept proved its potential to be used as an alternative for covering the absence of measured data of soil hydraulic properties.
In this study, a tracer field experiment was conducted to study the temporal dynamics of bromide movement in a loamy tile-drained agricultural landscape. Moreover, tritium leaching experiments were performed on undisturbed soil columns from the same field. The HYDRUS-2D software package was used to model water and solute transport. Three water flow models developed in Part 1-a single-porosity approach with modified soil hydraulic functions (SP), a dual-porosity approach (DP), and a dual-permeability approach (DUP)-were used as a foundation for building solute transport models, of which the initial parameterization was based on a suggested hydrogeological tool from previous studies. The selected solute transport models were an SP, an SP with immobile water, a DP, a DUP, and a DUP with immobile water. The model predictions were compared against measurements of bromide concentrations in soil-water. The DP captured the degree of the initial peaks and predicted well the shape of the observed concentrations. However, DP presented low capability to match the timing of bromide concentration peaks. In contrast, the DUP with immobile water illustrated better predictive ability by introducing an additional pore region into the matrix domain. Validation of field-scale solute transport models was implemented using the data from the following leaching experiments. The already suggested parameterization concept was further evaluated for its capability to provide a sufficient initial representation of the internal pathways. The output from such hydrogeological studies shows that macropores and their interconnection with tile drains are key to understanding the water flow and solute transport processes in loamy structured soils.
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