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SOIL AND WATER

Errors Associated with the Use of Soil Survey Data for Estimating Plant-Available Water at a Regional Scale

^a Pacific Agric. and Agri-food Res. Ctr. (Agassiz), Agric. Canada Res. Branch, Soil Sci. Dep., Univ. of British Columbia, 139-2357 Main Mall, Vancouver, British Columbia, Canada V6T 1Z4
^b CDT Technologies, Richmond, British Columbia, Canada

fortinmc{at}interchg.ubc.ca

Agricultural models generally provide estimation procedures for soil properties that regularly are missing in data sets. In regional model applications, the inputs to these procedures are often derived from soil survey information. This study was conducted to determine two types of errors associated with 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 with 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 recent update) were evaluated against laboratory-measured water-holding capacity. The original procedure did not perform adequately, with a prediction error of 0.10 compared with 0.04 for the updated procedure. Prediction error for procedure inputs derived from soil survey data were 8 to 18% of the value 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 for the main B horizons, the single largest source of error in this study. Prediction errors for total PAW were 25 and 33% of the mean for the Ap and main B horizons, respectively. Tests for unbiasedness for total PAW failed. Field measurements are needed to validate the best of the two estimation procedures and to supplement the present horizon thickness values found in soil survey. These field measurements represent a significant investment of time and money, but are essential to optimize the allocation of resources for a modeling project at the regional scale.

Abbreviations: PAW, plant-available water • WHC, water-holding capacity

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