Tuesday, November 6, 2007
183-1

Pedotransfer Functions Estimating near-Saturated and Saturated Hydraulic Conductivities.

Bo V. Iversen, Christen D. Børgesen, Ole Jacobsen, and Mogens Greve. University of Aarhus, Faculty of Agricultural Sciences, Research Centre Foulum, DK-8830 Tjele, Denmark

Leaching of pesticides and phosphorous through fin-textured, structured soils is mainly controlled by colloid-facilitated transport in the macropores of the soil. Estimates of hydraulic conductivities in the near-saturated and saturated range using pedotransferfunctions (PTF) can be useful in predicting the potential of water transport in the macropores of the soil. The initiation of water transport in soil macropores is controlled by two factors: The hydraulic conductivity in the matrix and the presence or absence of macropores. Soils with macropores and with a low near-saturated hydraulic conductivity are believed to show the highest degree of preferential transport. This study aims at developing point pedotransfer functions predicting the near-saturated hydraulic conductivity (here defined as the conductivity at a soil water potential of -1 kPa) and the saturated hydraulic conductivity using simple soil parameters as predictors. The dataset was based on measurements on almost 500 large soil columns (6280 cm3) sampled on 68 different localities in Denmark. In the laboratory, the near-saturated hydraulic conductivity was measured on a drip infiltrometer. Saturated hydraulic conductivity was measured using the constant head method. The developed PTFs were based on neural networks and the Bootstrap method using different sets of predictors. The result showed that the neural network was able to develop reasonably accurate PTFs predicting the near-saturated hydraulic conductivity whereas the PTFs predicting the saturated hydraulic conductivity were less accurate. Most accurate were PTFs including seven texture classes, amount of organic matter, bulk density, and horizon as predictors. PTFs including only five or four texture classes as predictors gave reasonably results as well. The results open of for the possibility predicting maps of soil hydraulic parameters which can be used to point out areas having high risk of water transport in macropores.

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