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
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