Using Ensembles of Pedotransfer Functions for Soil Water Retention in Field-Scale Water Flow Simulations.
Andrey Guber1, Yakov Pachepsky2, Diederik Jacques3, M. Th. Van Genuchten4, Walter J. Rawls5, Attila Nemes6, Jirka Simunek6, Thomas J. Nicholson7, and Ralph E. Cady7. (1) Univ of California, Dept of Earth and Environmental Sciences, Riverside, CA 92521, (2) USDA/ARS/BA/ANRI/ESML, Bldg.173, BARC-EAST, Powder Mill Rd., Beltsville, MD 20705, (3) SCK-CEN, Boeretang 200, Mol, 2400, Belgium, (4) George E. Brown, Jr. Salinity Lab USDA-ARS, 450 W Big Springs Rd., Riverside, CA 92507, (5) USDA-ARS Hydrology and Remote Sensing Lab, 10300 Baltimore Ave. Bldg 007., BARC-West, Beltsville, MD 20705, (6) Univ of California Riverside, Dept of Environmental Sciences, Geology Bldg, Riverside, CA 92521, (7) US NRC, Mail Stop T-9C34, Washington, DC 20555
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 multi-model 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 5 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. Soil water retention was measured in laboratory in samples taken at sixty locations at three depths. The ensemble of PTF comprised 22 published PTFs developed from large datasets in different regions of the World. Contents of soil textural fractions, organic matter content and bulk density were averaged across the transect and used as PTF inputs. The uncertainty of the ensemble-estimated water retention (quantified as the width of 95% tolerance interval of water content at a specific pressure head) was comparable with the uncertainty in laboratory water retention. The ensemble estimation gave a substantially better approximation of field water retention compared with laboratory data. The HYDRUS-1D software was used to simulate water content time series with (a) each of the PTFs from the ensemble and (b) the laboratory-measured water retention data of each of the 60 locations. The PTF ensemble provided more robust simulations, the tolerance interval of water contents simulated with the PTF ensemble prediction was substantially smaller than with laboratory water retention. Simulations with ensemble-estimated water retention had, on average, two times smaller errors compared with laboratory-measured water retention. The accuracy of simulating cumulative soil water fluxes did not differ between simulations with laboratory and ensemble-estimated water retention. Ranking PTFs by the root-mean-square error values showed that the best results were obtained with PTFs derived from the all-USA database and the all-European database that encompassed the widest variety of soils. Varying the saturated hydraulic conductivity in the realistic range had a substantial effect on simulation results, and this implied the need to emphasize measurements of hydraulic conductivity in field campaigns to characterize soil hydraulic properties. Using the PTF ensemble is, in essence, the utilization of generic information available prior to the site study. The ensemble prediction of soil hydraulic properties is a promising method to estimate soil hydraulic properties for simulations of field-scale water flow.
Keywords: soil water flow simulations, soil water retention, pedotransfer function, ensemble prediction