Errors associated with the use of soil survey data for estimating plant-available water at a regional scale

Agricultural models generally provide estimation procedures for soil proper ties that regularly are missing in data ses In regional model applications, the inputs to these procedures are often derived from soil survey informat ion. This study was conducted to determine two types of errors associated w ith the use of soil survey. data for estimating plant-available water (PAW) for the Peace River region of British Columbia: the error associated with the use of an estimation procedure and the error associated dth the use of soil survey data rather than measured data as inputs for the procedure. Two PAW estimation procedures (one used in CERES-Maize and in EPIC, and a rece nt update) were evaluated against laboratory-measured water-holding capacit y. The original procedure did not perform adequately, with a prediction err or of 0.10 compared with 0.04 for the updated procedure. Prediction error f or procedure inputs derived from soil sun ev data were 8 to 18% of the valu e of the measured mean for particle size and as much as 51% for organic C. The updated procedure was relatively insensitive to input prediction errors . Prediction errors for horizon thickness were 38 mm for the Ap and 95 mm f or the main B horizons, the single largest source of error in this study. P rediction errors for total PAW were 25 and 33% of the mean for the Ap and m ain B horizons, respectively, Tests for unbiasedness for total PAW faded. f ield measurements are needed to validate the best of the two estimation pro cedures and to supplement the present horizon thickness values found in soi l survey. These field measurements represent a significant investment of ti me and money, but are essential to optimize the allocation of resources for a modeling project at the regional scale.