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SPECIAL SECTION: FROM FIELD- TO LANDSCAPE-SCALE VADOSE ZONE PROCESSES

Field-Scale Water Flow Simulations Using Ensembles of Pedotransfer Functions for Soil Water Retention

^a Dep. of Earth and Environmental Sciences, Univ. of California, Riverside, CA 92521
^b USDA-ARS, Environmental Microbial Safety Lab., BARC-East, 173 Powder Mill Rd., Beltsville, MD 20705
^c USDA-ARS, George E. Brown, Jr. Salinity Lab., Riverside, CA
^d USDA-ARS Hydrology and Remote Sensing Lab., Beltsville, MD
^e SCK-CEN, Belgium
^f USNRC, ONRR, Washington, DC
^* Corresponding author (ypachepsky{at}anri.barc.usda.gov)

Received 14 September 2005.

Using pedotransfer functions (PTF) to estimate soil hydraulic properties may be necessary in soil water flow simulations for large-scale projects or in pilot studies. The accuracy of a PTF outside of its development dataset is generally unknown. The existence of multiple models that are developed and tested in one region, but may perform relatively poorly in other regions, is also common in meteorology, where multimodel ensemble prediction techniques have been developed (i.e., those using an averaged prediction from several models) to address this problem. The objective of this work was to estimate the applicability of an ensemble of PTFs for water regime simulations. Measured soil water contents and pressure heads of 60 points at five depths in a 6-m transect of a layered loamy soil were collected during an extremely wet year in Belgium. Soil water fluxes were measured with passive capillary lysimeters at two depths. Water retention was measured in the laboratory on samples taken at 60 locations at three depths. Contents of soil textural fractions, organic matter content, and bulk density were averaged across the transect and used as input in the ensemble of 22 published PTFs developed from large datasets in different regions. The HYDRUS-1D software was used to simulate water content time series with (i) each of the PTFs from the ensemble and (ii) the laboratory-measured water retention data of each of the 60 locations. Simulations with the PTF ensemble had, on average, two times smaller errors those from using laboratory data. A possible explanation for this is that the PTF estimation gave substantially better approximations of field water retention than the laboratory data. The ensemble prediction appears to be a promising source of soil hydraulic properties to simulate soil water dynamics.

Abbreviations: PTF, pedotransfer function

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